“The moment you push performance limits, heat becomes the enemy that never sleeps.”

Alexander Fischer

Co-founder & Product Manager, SimScale

Electric vehicles depend on compact thermal architectures that keep batteries and power electronics within a narrow operating windows. AI accelerators concentrate extraordinary wattage into small footprints. Industrial automation, renewable energy hardware and medical technology all follow the same pattern.

They raise performance expectations while shrinking available space. This creates a new reality in which cold plate design becomes a strategic engineering function rather than a late stage add on. Teams that recognize this shift early gain more performance, more reliability and more control over how their products evolve.

The Practical Challenges Facing Design Teams

Engineering teams face real constraints. They must balance:

• manufacturability,
• pressure drop,
• integration,
• weight targets,
• and routing!

You often work within tight envelopes while trying to handle rising heat flux. Parametric CAD can slow the process because feature trees resist change and complex channels break easily when edited. Conservative geometry becomes the default. This is risky as thermal loads continue to rise across industries. Cold plate cooling demands broader concept exploration, faster iteration and clearer structure throughout the development process.

A High Level View of the Cold Plate Design Workflow Step by Step

A typical cold plate project moves through several major steps from concept to validated geometry.

• It begins with requirement gathering where engineers define heat flux levels, target temperatures, available space, allowable pressure drop, material constraints and manufacturing options.
• Next comes the architectural exploration where macro level decisions such as cooling method, channel layout, inlet and outlet placement and flow balance strategies are evaluated.
• Concept modeling follows with early geometry that tests feasibility and identifies potential performance issues.
• Detailed design development then refines internal channels, surface area enhancements, flow paths and structural supports.
• In parallel, system level integration ensures correct fit and interaction with electronics, enclosures and the larger cooling loop.
• The final stages focus on simulation driven optimization, design for manufacturability and preparation for prototyping.

High performance applications cycle through these steps rapidly as iteration speed becomes a core advantage.

How Implicit Modeling Transforms the Design Phase

Implicit modeling fits directly into this workflow and accelerates it significantly. Traditional parametric CAD relies on sketches, constraints and feature trees. Implicit modeling uses continuous mathematical fields to define form.

Complex shapes become easy to create and sturdy during modification. Families of designs can be generated quickly without model failures. Smooth blends are inherent. Microchannels, graded thicknesses, TPMS surfaces or lattice supported walls appear without manual surfacing.

This matters because cold plate cooling often benefits from organic or highly detailed internal geometry that explicit modeling tools struggle to express.

Why Advanced Cooling Geometry Matters Now

This shift aligns perfectly with the pressure placed on modern hardware. EV power electronics keep increasing in output while packaging shrinks. AI hardware demands targeted thermal strategies that match component level heat flux. Data centers monitor every watt because cooling efficiency now affects operating cost directly. Aerospace, hydrogen systems and compact industrial machinery all follow similar trends. They require high performance cooling solutions that combine low weight, high efficiency and manufacturable complexity.

Cold plate design sits at this intersection because it enables direct heat removal and supports structurally complex yet lightweight geometries.

The Impact of Simulation and AI Assisted Optimization

When advanced modeling is paired with CAE simulation or AI driven physics prediction, the later stages of the workflow become dramatically more effective. Engineers can apply cold plate topology optimization to reshape channels for uniform thermal behavior. Microchannel networks can align with localized heat flux. TPMS or lattice structures can increase surface area while keeping weight low. Iteration becomes flexible and exploration becomes normal rather than exceptional. Cold plates evolve into highly tuned components tailored to the exact demands of each device.

Key Insights

1. Microchannel cold plates deliver high surface area for extreme heat flux handling
2. TPMS and lattice structures enable lightweight internal geometries with strong manufacturability profiles
3. Implicit modeling and topology optimization accelerates every design stage and supports shapes that parametric tools struggle to represent
4. Simulation driven workflows improve accuracy and bridge the gap between concept and validated performance
5. Cold plate design has become a strategic differentiator for any product facing rising thermal loads

Cold plates are no longer secondary components. They enable the future of mobility, computing and energy systems and they reward engineering teams that prioritize them early in development.

The post Cold Plate Cooling Design appeared first on SimScale.

As power densities increase and form factors shrink, the choice between a passive or active cooling strategy becomes one of the most critical decisions in the design cycle. Making the wrong call leads to costly redesigns and field failures.

This is where simulation provides a decisive advantage. Cloud-based analysis allows engineers to test, validate, and optimize thermal solutions before committing to physical prototypes, transforming a high-stakes gamble into a predictable science. This article will dissect the two primary cooling methodologies – passive and active cooling methods – and provide a comprehensive framework for selecting and simulating the optimal approach to provide cooling for your project.

Passive Cooling: The Silent Guardian

Passive cooling represents engineering elegance – achieving thermal management without active cooling components consuming additional energy. It is a reliable, silent, and cost-effective solution for dissipating low-to-moderate heat loads, making it a cornerstone of modern electronics design.

What is Passive Cooling?

Passive cooling leverages the fundamental laws of physics to transport thermal energy. It relies on conduction, natural convection, and radiation to move heat from a source to the surrounding environment. Because these systems have no moving parts, the cooling systems are inherently fail-proof from a mechanical standpoint. This is a key principle behind passive cooling strategies offering unparalleled long-term reliability.

The process begins with conduction, governed by Fourier’s Law (q=−k∇T), where heat moves through a solid material like aluminum or copper. The heat then transfers to the surroundings via natural convection and radiation. Radiative cooling, described by the Stefan-Boltzmann Law (P=ϵσA(Thot⁴​−Tcold⁴​)), is why heat sinks are often anodized or painted black—to increase their emissivity (ϵ) and maximize heat dissipation.

How Does Passive Cooling Work?

The primary workhorse of passive cooling is the heat sink, which uses a large surface area to efficiently transfer heat. The process is straightforward:

1. Conduction: Heat is generated by the electronic component and conducted into the heat sink base, often through a Thermal Interface Material (TIM) that minimizes thermal resistance on the interface.
2. Dissipation: The heat spreads through the heat sink to its fins, which dramatically increase the surface area for dissipation into the ambient via natural convection and radiation.

More advanced passive systems like heat pipes and vapor chambers use two-phase heat transfer. A sealed working fluid evaporates at the hot interface (absorbing latent heat) and condenses at the cold interface (releasing heat), achieving an effective thermal conductivity that is orders of magnitude higher than solid copper.

Benefits of Passive Cooling

• Extreme Reliability: With no moving parts, there are zero mechanical failure points, which is essential for systems in inaccessible locations like satellites or remote telecom towers. Systems without openings offer a huge advantage in terms of preventing dirt and dust to negatively affect the cooling system or require regular maintenance.
• Zero Operational Cost: These solutions add nothing to a product’s energy consumption or a facility’s utility bill.
• Silent Operation: The absence of fans is a critical requirement for noise-sensitive applications like high-fidelity audio equipment or medical devices.
• Lower Cost: Passive solutions are typically cheaper to manufacture than their active counterparts.

Passive Cooling Systems Examples

• Extruded Aluminum Heat Sinks: The most common type, found in routers, set-top boxes, and solid-state drives (SSDs).
• Heat Pipes & Vapor Chambers: Used in high-performance laptops and compact, fanless PCs.
• Strategically Vented Enclosures: Designing a product’s housing to maximize the natural “chimney effect” of rising hot air.
• Phase Change Materials (PCMs): Materials that absorb thermal spikes by melting and re-solidify when the load decreases.

Real world passive cooling example

Cobalt Design used SimScale to reduce their passive heat sink temperature by 11% through the analysis of existing designs which highlighted localized peak temperatures inside the unit without an adequate exfiltration path.

Read the case study

Active Cooling: The Power Play

When the heat load generated by a system surpasses the capacity of passive methods, engineers must turn to active cooling. This approach uses forced convection components  to dramatically accelerate heat removal, making active cooling solutions essential for enabling performance levels that would be otherwise impossible.

What is Active Cooling?

Active cooling is any thermal management system that consumes energy to enhance heat transfer. By introducing a mechanical component like a fan or pump, these systems overcome the limitations of natural convection, allowing them to manage much higher heat fluxes within a compact form factor.

How Does Active Cooling Work?

The most common form of active cooling is forced convection. A fan or blower moves air across a heat sink at high velocity. This turbulent flow dramatically increases the heat transfer coefficient (h), enhancing the cooling performance and meaning more thermal energy is transferred away from the component.

For more demanding applications, active liquid cooling is used. A pump circulates a coolant through a cold plate mounted on the heat source. The heated liquid then flows to a radiator, where a fan dissipates the heat into the air, improving overall energy efficiency. A case study on high-power electronics demonstrated that a direct liquid cooling solution could maintain a component’s temperature at 55°C, while an air-cooled solution could only manage 77°C under the same heat load—a crucial 22°C difference.

Benefits of Active Cooling

• Superior Thermal Performance: The ability to dissipate immense heat loads enables high-performance CPUs and GPUs to operate at peak potential without throttling.
• Precise Thermal Control: Fan speeds can be dynamically adjusted using Pulse Width Modulation (PWM) based on sensor data, optimizing cooling while minimizing noise and power use.
• Design Compactness: Active cooling achieves high performance in tight spaces, like blade servers, where a comparable passive solution would be too large.

Active Cooling Systems Examples

• Axial Fans & Centrifugal Blowers: Found in virtually all desktop computers, servers, and industrial cabinets.
• Closed-Loop Liquid Coolers: Standard for enthusiast PCs, workstations, and increasingly, direct-to-chip data center cooling.
• Thermoelectric Coolers (TECs): Solid-state Peltier devices that “pump” heat electrically, used for spot cooling in lab equipment and portable refrigerators.

Real world active cooling example

Rimac Automobili used SimScale to improve the thermal management of their EV batteries which lead to a 96% time saving for simulations as well as improved overall performance.

Read the case study

Choosing Active vs. Passive Cooling: A Design Framework

The decision between active and passive cooling is a trade-off analysis based on key design constraints. There is no single “best” solution, only the most appropriate one.

• Thermal Design Power (TDP) & Heat Flux: This is the starting point. Below ~15W, passive solutions usually suffice. Above 100W, active cooling is almost always necessary. The region between is a complex trade-off zone.
• Environment & Form Factor: High ambient temperatures reduce the effectiveness of all cooling but can render passive solutions inadequate. The available volume will also dictate if a large passive heat sink is even a viable option.
• Acoustics & Vibration: If silent operation is a primary requirement (e.g., medical devices), passive cooling is the clear choice. Fans introduce noise and micro-vibrations that can be problematic for sensitive equipment.
• Reliability & Maintenance (MTBF): Compare the Mean Time Between Failures of a fan (30k-70k hours) against the near-infinite lifespan of a solid heat sink. For products designed to last a decade, a fan is a potential point of failure.
• Total Cost of Ownership (TCO): An active solution has ongoing operational costs due to its power consumption. A slightly more expensive passive solution may have a lower TCO over the product’s lifetime.

Often, a hybrid approach is optimal, using a passive heat sink for normal operation and a fan that activates only under peak thermal load.

Simulate Your Active and Passive Cooling Solution with SimScale

Guesswork and over-engineering are not effective design strategies, especially when it comes to implementing hybrid cooling systems . Before committing to expensive tooling, you must validate your design. Cloud-native simulation with SimScale provides the quantitative proof needed to make data-driven decisions.

• De-Risk Your Design: Identify thermal failures in the digital domain to save weeks of time and thousands in wasted prototypes. Integrating CFD simulation early can reduce the number of physical prototypes required to one or a few at max and transform the physical testing into a pure validation step at the end of the design phase.
• Optimize for Performance: Run parametric studies on heat sink fin geometry or fan placement in parallel on the cloud. This allows you to find the configuration that offers the lowest thermal resistance (Rth​) for the lowest mass.
• Visualize the Invisible: Use CFD analysis to get a complete picture of airflow and heat distribution. You can visualize recirculation zones, identify thermal bottlenecks, and ensure your cooling solution performs as intended.
• Quantify with Precision: Move from estimation to prediction. A SimScale thermal simulation provides precise temperature calculations, confirming that a critical processor will be cooled from a dangerous 95°C to a safe 78°C, ensuring you meet reliability targets before manufacturing begins.

Stop gambling with your product’s thermal performance. Start your free trial of SimScale today and discover how cloud-based simulation can help you build more reliable, efficient, and powerful products with confidence.

The post Active vs Passive Cooling appeared first on SimScale.

If you missed the session or want a quick refresher, here are the five key highlights from the event—including technical insights, real-world use cases, and a look at how our AI Assistant accelerates simulation workflows.

• Conjugate heat transfer meets compressible flow – without the headaches
• Simulating hydrogen tank filling: A transient CHT case
• Using AI to set up a complete CHT simulation – with just a few prompts
• Fast, scalable simulation – powered by the cloud
• Getting started: Access, accuracy & support

On-Demand Webinar

If the above highlights caught your interest, there are many more to see. Watch the on-demand Simulation Expert Series webinar from SimScale on how real-time simulation with AI is driving faster design cycles and superior products by clicking the link below.

Watch On Demand

1. Conjugate Heat Transfer Meets Compressible Flow—Without the Headaches

We kicked things off with a technical overview of our multi-purpose solver, purpose-built for simulating compressible flows and conjugate heat transfer in a single environment. Unlike traditional solvers that often struggle with convergence or require extensive tuning, this solver handles complex physics, including real gas behavior and transient conditions, with a high level of robustness and automation.

Thanks to its robust meshing and smart numerical defaults, users can simulate everything from subsonic to supersonic regimes (up to Mach 5) with ease, even across multiple solid and fluid domains.

Key Takeaway:
Running compressible CHT simulations doesn’t need to be difficult. With the right solver setup, it’s possible to simulate real-world heat transfer scenarios – quickly, reliably, and without extensive manual tuning.

2. Simulating Hydrogen Tank Filling: A Transient CHT Case

In our first live demo, we walked through a hydrogen fuel tank filling simulation, a transient application involving real-gas behavior and multi-material heat transfer. The setup covered every essential step:

• Uploading and simplifying the CAD geometry (including symmetry extraction)
• Selecting the Multi-Purpose analysis type
• Assigning materials (e.g., hydrogen as a real gas, insulation, aluminium liner)
• Defining transient pressure inlet conditions (e.g., ramping from 1 to 500 bar)
• Applying convective heat loss to the tank exterior
• Using adaptive meshing with local refinements

We also set up result control items such as probe points and area averages, and ran the simulation entirely in the browser on cloud hardware. The post-processing revealed clear insights into temperature distribution and jet behavior during fill-up – critical for validating safety and performance!

Key Takeaway:
This case showed how to model complex flow and thermodynamic phenomena with minimal effort. Perfect for those optimizing fill-time, insulation, or structural design in hydrogen applications.

3. Using AI to Set Up a Complete CHT Simulation—With Just a Few Prompts

Our second case study featured an automotive muffler and a different kind of demonstration: how to set up the entire simulation using our built-in AI Assistant.

By typing simple prompts like “run a CHT simulation” or “assign air as the fluid,” the AI automatically:

• Chose the appropriate solver configuration
• Assigned materials to solid and fluid regions
• Created inlet and outlet boundary conditions
• Suggested convective heat transfer coefficients and ambient settings
• Generated monitoring outputs like surface averages

This AI-guided workflow eliminated nearly all manual steps. For engineers who are new to simulation or simply want to accelerate setup, the assistant provides both recommendations and automation—along with contextual support links where needed.

Key Takeaway:
AI doesn’t just assist with troubleshooting – it can build entire simulation setups, letting you go from CAD to results in record time.

4. Fast, Scalable Simulation—Powered by the Cloud

Both case studies demonstrated how easy and fast it is to run advanced simulations directly in the browser. There’s no need for installations, licenses, or local compute power. Simulations ran on scalable cloud hardware, automatically selecting optimal cores (or letting users configure their own).

For example, the hydrogen tank simulation was set up and launched in about 10 minutes, while the muffler case, set up via the AI assistant, ran in under 30 minutes.

Key Takeaway:
SimScale’s cloud-native platform removes infrastructure barriers, allowing teams to run high-fidelity simulations with minimal hardware requirements and rapid turnaround.

5. Getting Started: Access, Accuracy & Support

We wrapped up the session with an open Q&A. Attendees asked about solver availability, performance, and support:

• The multi-purpose solver used in both demos is available to professional users—just reach out to our sales team to request access or a trial.
• Accuracy was a key point: internal validation and customer results show 2–5% deviation compared to physical tests, even for high-speed or thermally complex systems.
• The AI Assistant is available on request – contact us if you’d like it enabled on your account.

Key Takeaway:
If you’re looking to bring advanced thermal-fluid simulation into your workflow, we’re here to support you with the tools, accuracy, and guidance you need to get started confidently.

Final Thoughts

Conjugate heat transfer and compressible flow problems can be some of the more challenging simulations to set up and run. However, with the right tools, they don’t have to be.

Whether you’re designing hydrogen systems, automotive components, or any application where heat and flow interact under pressure or at high speed, the workflows demonstrated in this webinar show how quickly you can go from concept to insight.

With robust solvers, cloud-native speed, and AI-assisted setup, it’s never been easier to simulate with confidence—even for complex multiphysics scenarios. We’re excited to see what you’ll build with these capabilities.

The post Webinar Highlights: How to Get Started with Conjugate Heat Transfer Analysis of Compressible Flows appeared first on SimScale.

This growth has also been fueled by an equally rapid expansion of model capabilities. The first steps toward multi-modality came quickly and introduced the same text-to-output inference to other content types. We already almost take for granted the ability to generate high-quality images, video, and source code through such tools.

Can AI Generate Engineering Output?

Mechanical engineering teams have adopted these tools as well to accelerate all sorts of work processes. For example, to analyze and summarize RFQs faster or to search faster for technical information. But these use cases are mostly adjacent to the core engineering work and mechanical design. So why is it that we can ask AI to generate very useful text, images, video, and code but not a useful engineering design?

Let’s consider how these types of AI models are trained. Generative AI models have been trained on trillions of tokens, primarily from the internet. Transformer models on huge datasets of public text/code and diffusion models on equally large datasets of text-image pairs. Not only is this training data available in vast quantities, but the data formats are also very straightforward to read and use for model training.

Things look rather different in the engineering realm, the most obvious challenge being that, unlike text or source code, there is little to no public product design engineering data available. Then there is also the question of data quality, in the sense of whether or not a given design is fit-for-purpose, meeting the requirements that it was designed for. Added to that is the fact that the most widely used data formats storing mechanical design information are proprietary, requiring commercial licenses even to read it, let alone manipulate it. In summary, the idea of obtaining and processing millions of engineering designs to train a generative model still looks like a very challenging ask today, but technical progress in this field is happening fast.

Does That Mean That Core Engineering Work Will Remain AI-Free for Now?

Absolutely not. In due course, novel AI approaches might rise to the challenge of handling big chunks of typically manual engineering workflows, possibly including the transformation of a text prompt into a meaningful design, but it is going to take time to get there.

Meanwhile, there are AI engineering workflows that are easier to attain while still very helpful. We can get a long way by using AI to speed up the cycle time for a single design iteration to such an extent that it appears to be instantaneous. We will do this by accelerating all of the steps in the workflow, including CAD generation, model preprocessing and setup, simulation workflows, and the analysis of results.

Once we have all that proven out, an AI agent can then drive the (accelerated) machine, taking design decisions along the way and looping around to discover optimal solutions.

Replacing a human-in-the-loop with a machine-in-the-loop in this way has the advantage of leaving the workflow and toolchain fundamentally unchanged, with the AI system ‘driving’ the tools in the same way that a human does. This means the human can easily understand what is being done and intervene at any point. Most importantly, the human can provide input to direct the AI, for example, where a design needs to balance competing objectives – decisions that require careful consideration and mutual understanding.

Not Just a Case of “Prompt Engineering”

Let’s dig into how we deploy AI to accelerate and augment engineering workflows. Let’s start by looking at how these processes work today. They tend to be centered around the manual engineering work where humans make decisions to advance the iterative design by designing and evaluating the design’s performance, depicted in green below. The CAD system involved can be conceptualized as a computational process going from parameterization to geometry (yellow) and the CAE system going from the simulation setup to the results (blue). 

This is a very simplified conceptual view of the engineering process, but helpful as it differentiates between the unstructured, human workflows in the middle and the purely computational ones left and right. All three can be automated already, to search through a prescribed design space for example. But this automation is very much rate-limited when using so-called traditional physics solvers to evaluate each design. What’s more is that AI can transform this process into something not only automatic, but autonomous.

Introducing Physics AI & Engineering AI

Let’s tackle that first bottleneck of simulation run time (the right-hand block in the diagram above). Depending on the physics and fidelity needed, a computing time of hours to days is not unusual. A growing set of AI methodologies to speed up this solve process is available, from deep learning surrogate models that replace full physics solvers to tools that speed up those ‘traditional’ solvers. Given the availability of a suitable, pre-trained, method, you can reduce the solve time almost to zero. We call these ‘Physics AI’ methods to indicate that, at the core, it’s about predicting physics with AI, and with the big benefit of being able to do that very fast. 

The second, more dispersed bottleneck visible in the process is the human interaction needed to go from a given design to a well defined simulation setup, then to consider the results of that simulation, and lastly to determine which point in the design space to look at next (the middle block in the diagram). These are all steps where an AI agent can assist, facilitate, accelerate, as well as act autonomously – performing complete workflows by operating on the existing tool stack just as a human would. As such, it is performing a series of discrete and logical steps that can be justified or even debated, as you might with a colleague. Since this agent is performing the core engineering work for you, we refer to it as ‘Engineering AI’.

Lastly, let’s turn our attention to the left-hand block – the CAD definition of a design. Once a model has been created and parameterized, generating a new variant based on a new set of parameters is already near-instantaneous. What is very much slower, though, is the process of creating that CAD model in the first place.

There are several exciting technologies emerging in the CAD space that could make the process of CAD generation far faster and more robust. Latent space parameterization, implicit representations, and cloud-native BREP are just three such technologies that could enable vastly faster design iterations, and we are actively working on integrating them into SimScale.

We Are Placing AI Tools in the Hands of Every Engineer

Thanks to its cloud-native architecture with built-in AI infrastructure, SimScale is uniquely able to provide AI features to help you navigate engineering workflows and accelerate performance predictions by leveraging your simulation data in the cloud. As we have explored so far in this blog, unlocking value from AI means touching almost every aspect of the simulation workflow. It requires a deep and immediate connection to models and data which is only practical to do in a cloud-native stack.

Engineering AI and Physics AI are built into SimScale in such a way that it can become second nature to use these tools to supercharge your productivity. SimScale users do not need to deal with any of the typical headaches experienced when attempting to deploy AI tools such as data cleaning/organizing/relocation, model versioning and management, or provisioning of suitable GPU resources for model training and execution. All of these are taken care of by the vertically integrated tool stack and intuitive user experience.

At NVIDIA GTC 25, we announced that we are making it even easier and faster to adopt Physics AI for certain applications by building a set of pre-trained foundation models. The unique aspect of these models is that they are pre-trained on a broad set of designs, providing users with a Physics AI model that they can use out-of-the-box or that they can augment with a small amount of their own proprietary training data. To learn more about foundation models in SimScale, check out this blog.

Unlock AI Value by Selecting an Impactful Application to Start With

Once you have test-driven the capability, the next step is to test-drive the value unlock. Each engineering team we work with has unique legacy data stored, sometimes from decades of engineering work. We frequently see teams expecting to start there, trying to find value in it. The reality is that finding and processing legacy data can be an immensely difficult task, and one that may take a very long time to yield results, even if useful data exists.

We recommend a different approach: Select an engineering process in your organization that – if collapsed to seconds – would create hard value for your organization (revenue or costs) and try tackling that with an AI-powered workflow. 

Remember: The best time to start leveraging AI systems in your engineering team was yesterday. The second best is today – give us a ring!

The post AI Is Sweeping Into Knowledge Work. What About Engineering? appeared first on SimScale.

What is Engineering Analysis Software?

Imagine designing an electric vehicle and needing to know exactly how its structure will perform under varying loads. Or consider managing the heat dissipation of a densely packed telecom tower. Engineering analysis software transforms these challenges into solvable tasks by simulating real-world conditions before a single part is built. From validating designs to optimizing performance, this software is indispensable in industries like automotive, electronics, and industrial equipment, where every detail counts.

Here are some key applications and capabilities to address real-world challenges:

• Structural Analysis: Engineers can predict how materials and structures will respond to stresses, strains, and external forces. This is essential in ensuring product durability and safety across applications, from bridges to vehicle components.
• Fluid Dynamics: Simulation of fluid flow, whether for optimizing aerodynamics in vehicles or ensuring efficient cooling systems, helps engineers fine-tune designs for peak performance.
• Thermal Analysis: Managing heat is critical in industries like electronics, where overheating can compromise functionality. Thermal analysis tools allow engineers to design effective heat dissipation systems, ensuring reliability and longevity.
• Multiphysics Simulation: Real-world problems often involve overlapping physical phenomena, such as thermal and structural interactions. Multiphysics tools empower engineers to analyze these complexities in a unified framework, reducing the risk of unexpected failures.

These physics modeling applications enable engineers to make informed decisions, iterate rapidly, and deliver solutions with greater confidence and precision.

Key Features to Look for in Engineering Software

1. Comprehensive Design Visualization and Prototyping

Design space exploration tools enable engineers to predict how changes in design will affect real-world performance. These tools provide a framework for testing edge cases, analyzing trade-offs, and optimizing configurations, allowing engineers to predict real-world outcomes accurately. This ensures that every detail of a design is refined and validated before moving to production, reducing risks and improving overall performance.

Design visualization and virtual prototyping capabilities in SimScale enable engineers to iterate on multiple scenarios rapidly, benefiting from an infinite number of parallel simulations that can be used for parameterization. This capability ensures that the final prototype is robust, cost-effective, and ready for manufacturability, helping engineers meet tight deadlines while maintaining high standards of precision and reliability.

2. Cost Estimation and Manufacturability

Modern engineering tools must incorporate cost estimation and manufacturability analysis to streamline production processes. SimScale’s advanced simulation capabilities allow engineers to assess material usage, assembly challenges, and production feasibility early in the design phase. This proactive approach reduces waste, lowers costs, and ensures that designs can be manufactured without extensive modifications, making workflows more efficient and reliable.

3. Integration with Motion and Stress Analysis Tools

Motion and stress analysis tools are essential for predicting how components will perform under operational conditions. These features help engineers understand load distributions, identify weak points, and verify structural stability. SimScale’s structural analysis tools provide detailed insights into stresses, deformations, and material behavior, ensuring that products meet safety and durability standards. By incorporating these analyses, engineers can eliminate rework and reduce time-to-market.

4. Cloud-Connected Collaboration

Cloud-based solutions enhance collaboration by enabling teams to work together in real time, regardless of geographic location. SimScale’s cloud-native platform offers secure data storage and seamless sharing, allowing stakeholders to review and modify designs collaboratively. Engineers can provide real-time feedback, integrate client inputs, and maintain version control effortlessly. This fosters a cohesive development process, reducing delays caused by miscommunication or siloed workflows.

5. AI Integration for Enhanced Analysis

Artificial intelligence is transforming engineering workflows by automating repetitive tasks, optimizing designs, and improving simulation accuracy. SimScale leverages AI to accelerate simulations, allowing engineers to analyze multiple design scenarios simultaneously and predict simulation results as soon as a CAD is input to the workbench. This capability supports predictive modeling, identifies the most efficient configurations, and contributes to sustainability by optimizing energy and resource use. By integrating AI, SimScale empowers engineers to achieve precise results faster, boosting productivity and innovation.

Categories of Engineering Software for Advanced Analysis

3D Design and CAD Software

Tools like SolidWorks, Fusion 360, and Onshape by PTC are widely used for creating 3D models, CAD/CAM designs, and manufacturability checks. These platforms and software enable engineers to create detailed 3D models, conduct manufacturability checks, and streamline CAD modeling workflows. They simplify the transition from concept to production, enabling precise and efficient product development.

Simulation Software

Simulation software plays a crucial role in validating designs under real-world conditions, allowing engineers to test and refine concepts before committing to physical prototypes. Among well-known tools like ANSYS and COMSOL, SimScale distinguishes itself with its cloud-native approach. This platform enables faster design iterations by allowing engineers to run multiple simulations in parallel, reducing lead times significantly. Its ease of use makes it accessible to both seasoned engineers and those new to simulation, while its scalability supports projects and enterprises of all sizes.

Cloud-Native Engineering Platforms

Cloud-native platforms enhance accessibility and reduce hardware dependencies, enabling engineers to work with greater flexibility and efficiency. SimScale’s platform is optimized for real-time simulation, offering engineers the ability to run detailed analyses and share results without delays. Its real-time collaboration features allow teams to synchronize efforts seamlessly, focusing on tasks like optimizing aerodynamics, enhancing thermal performance, or ensuring structural integrity, all within a single, cohesive workflow.

Industry-Specific Applications of Engineering Software

Engineering software adapts to meet the unique demands of different sectors. Whether tackling the complexities of electric vehicle designs, optimizing telecom infrastructure, or improving industrial water systems, engineering software offers tailored solutions that drive efficiency and innovation.

Engineering Software for the Automotive Industry

SimScale’s cloud-native platform empowers automotive engineers to address critical design challenges across multiple domains. By enabling detailed airflow simulations, for example, engineers can optimize vehicle aerodynamics to reduce drag and improve energy efficiency. Thermal management simulations help refine cooling systems, ensuring optimal performance of EV batteries and power electronics. Additionally, SimScale supports structural analysis to help safeguard structural integrity and durability, which can be critical for safety compliance and long-term reliability. Its ability to handle multiphysics scenarios allows automotive teams to integrate thermal, structural, and fluid dynamics into a single simulation environment, streamlining the design process and accelerating time-to-market.

An automotive supplier of sustainable fastening solutions utilized SimScale to enhance the design of EV battery module connectivity. By running multiple thermal and structural simulations, they were able to validate their design faster, ensuring it met performance and reliability standards. This approach not only accelerated their development process but also minimized the risk of thermal runaway, a common challenge in EV battery systems.

Engineering Software for Electronics

Thermal and structural analyses are critical for ensuring the reliability and performance of electronic devices, especially as systems become more compact and powerful. SimScale provides tools that enable engineers to simulate heat transfer, evaluate cooling strategies, and predict structural behavior under varying loads. With the ability to handle high-fidelity thermal simulations, SimScale helps engineers optimize designs to prevent overheating, improve efficiency, and ensure durability.

Beamlink, for example, used SimScale to redesign its telecom towers. By conducting detailed thermal simulations, they identified and resolved potential heat management issues early in the design process. Additionally, structural analysis performed with SimScale validated the mechanical integrity of their towers, ensuring they could withstand environmental stresses while maintaining optimal functionality. This approach led to a faster design cycle, reduced development costs, and improved product reliability.

Engineering Software for Industrial Equipment Manufacturing

SimScale provides vital tools for improving flow efficiency, thermal performance, and structural durability in industrial equipment. It enables engineers to simulate fluid flow, optimize cooling systems, and ensure the robustness of structural components under various operational conditions. By leveraging SimScale, industrial equipment manufacturers can address challenges related to energy efficiency, sustainability, and reliability.

Nalco Water, a leader in water treatment solutions, faced urgent challenges in improving the efficiency and reliability of industrial water nozzles for high-throughput paper mills. SimScale’s CFD simulations enabled them to analyze and optimize flow distribution, reducing pressure losses and enhancing operational efficiency. This led to a 70% reduction in unplanned downtime, saving approximately $10 million annually. The redesigned nozzle also improved machine stability, product quality, and throughput while reducing material and steam consumption. By leveraging SimScale, Nalco Water achieved a streamlined design process that not only addressed immediate operational challenges but also supported long-term sustainability and cost savings.

SimScale: The Best Tool for Engineering Analysis

Cloud-Native Simulation Leadership

SimScale is a versatile platform designed to revolutionize engineering analysis. With its cloud-native architecture, it enables engineers to simulate complex scenarios without the need for costly hardware, democratizing access to advanced simulation tools. This scalability and ease of use make it suitable for experts and new users alike, transforming how teams approach engineering challenges.

AI Integration

SimScale’s AI capabilities significantly enhance simulation workflows by automating repetitive tasks and improving accuracy. By leveraging predictive modeling, engineers can analyze multiple design iterations more efficiently, leading to faster decision-making and reduced time-to-market.

For example, RLE International, a leading development, technology, and consultation service provider, sought to enhance product design, accelerate development, and reduce costs to remain competitive in the automotive industry. Using SimScale’s AI-powered tools and deploying machine learning models trained within SimScale, RLE obtained accurate aerodynamic parameters like lift, drag, and speed within seconds. As a result, RLE reduced computation costs by 45% and significantly shortened prototyping cycles. These rapid simulations enabled RLE to explore innovative aerodynamic designs while maintaining high efficiency.

Integrating AI and cloud-native simulation tools streamlines engineering workflows, enabling rapid and cost-effective design iterations. These technologies empower engineers to obtain precise results faster, optimize resources, and drive innovation in complex projects.

Accessibility for Education

SimScale also offers free access to students and educators, providing a competitive edge for those entering the engineering field by delivering hands-on experience with professional-grade simulation tools. The platform includes a comprehensive suite of learning resources such as tutorials, and learning videos which provides structured courses in CFD, FEA, and thermal analysis. These resources empower learners to tackle engineering challenges confidently while gaining practical skills applicable to real-world solutions.

SimScale also fosters collaborative opportunities through shared projects, enabling students and educators to work together and build a sense of community. By equipping the next generation with accessible, high-quality educational tools, SimScale ensures that future engineers are well-prepared to innovate and excel.

Driving Engineering Innovation with SimScale

Choosing the right engineering software is vital for staying ahead in today’s competitive environment. Digital engineering is transforming traditional practices, enabling engineers to integrate advanced tools like AI and cloud-native platforms into their workflows. SimScale exemplifies this transformation by combining cloud-native technology, AI-driven simulation, and accessibility into a single platform. Engineers can streamline workflows, iterate faster, and optimize designs with unprecedented precision and efficiency. This digital shift empowers teams to tackle complex projects confidently while staying aligned with modern engineering demands. To explore how SimScale can transform your projects, start a free trial or dive into its case studies to see the platform in action.

The post Top Engineering Software for Advanced Analysis: A Guide to Innovation and Efficiency appeared first on SimScale.

Physics simulation allows engineers to model physical forces, interactions, and behavior digitally. Instead of relying solely on physical prototypes, simulations provide insights faster and at a lower cost. Effective physics modeling software empowers engineers to analyze and optimize designs across multiple domains.

This guide explores physics simulation, its diverse applications, and how SimScale, a cloud-native platform, stands out as a versatile and collaborative physics modeling tool.

What is Physics Simulation and Physics Modeling Software?

Physics simulation is the process of modeling and analyzing how physical systems behave under various conditions. It uses numerical methods to predict responses like fluid flow, thermal distribution, structural deformation, and electromagnetic fields.

Physics modeling software enables engineers to create, run, and analyze these simulations. It provides a digital environment where users define geometries, apply physical parameters, and visualize results.

Key Features of Effective Physics Modeling Software

1. Multiphysics Capabilities: The ability to combine different types of physics (e.g., thermal, structural, and fluid) within a single simulation to capture complex interactions.
2. Flexibility: Support for user-defined physics parameters, allowing engineers to tailor simulations to specific challenges.
3. Ease of Use: Intuitive interfaces and streamlined workflows make advanced simulations accessible, even for those without deep simulation expertise. This focus on user experience helps teams adopt simulation more effectively, leading to better project outcomes.
4. Real-time Collaboration: SimScale’s cloud-native platform enables teams to share simulation results effortlessly. Design engineers, manufacturing teams, and testing departments can access the latest simulation data in real time, ensuring everyone stays aligned.
5. Workflow Efficiency: Integrating simulations into the design process reduces development time. Instead of waiting for physical prototypes, engineers can make real-time adjustments based on simulation insights, accelerating decision-making.

SimScale integrates these features, providing a unified platform where engineers can model complex physical systems, simulate multiple physics domains, and collaborate effectively to achieve precise and actionable insights. By leveraging SimScale, teams can seamlessly bridge the gap between design and simulation, ensuring higher productivity and innovation.

Diverse Engineering Applications of Physics Simulation

SimScale supports a wide range of engineering applications, making it an indispensable tool across various industries, including automotive, industrial equipment, electronics manufacturing, and Architecture, Engineering, and Construction (AEC). By enabling simulations for complex physical systems, SimScale helps engineers address challenges in design, optimization, and testing more efficiently. Below is an overview of the physics available in SimScale and how to leverage them in key domains:

1. Structural Mechanics

Structural analysis simulations assess how components handle stresses, loads, and deformations. Engineers use these simulations to ensure designs meet safety and performance standards.

One example of structural analysis using cloud-native simulation is validating the load-bearing capacity of industrial machinery frames. This ensures designs meet safety standards and comply with regulatory requirements, reducing the risk of costly failures in real-world applications.

2. Fluid Flow (CFD)

Computational Fluid Dynamics (CFD) models how gases and liquids flow through and around objects. CFD simulations help engineers improve efficiency and performance in fluid-related systems.

For instance, HVAC simulations are essential for engineers looking to optimize airflow and temperature distribution in buildings. By using CFD, engineers can design systems that enhance energy efficiency while maintaining occupant comfort.

3. Heat Transfer

Heat transfer simulations model the distribution of heat within systems, helping engineers design effective cooling or heating solutions.

Thermal simulations are particularly valuable for improving battery thermal management. By modeling thermal distribution, engineers can prevent overheating and enhance the lifespan of electric vehicle batteries, ensuring both performance and safety.

4. Electromagnetics

Electromagnetic simulations predict how electric and magnetic fields interact with components. These simulations are crucial for optimizing electrical devices and minimizing interference.

For example, electromagnetic simulations can help optimize the design of electric motors by modeling the interactions of electric and magnetic fields. This enables engineers to identify inefficiencies, reduce energy losses, and enhance motor performance, ensuring reliable operation and cost savings in the long term.

5. NVH (Noise, Vibration, and Harshness) Simulation

NVH simulations evaluate and minimize noise and vibration in mechanical systems. This is especially valuable for automotive engineers seeking to enhance vehicle comfort (user experience) and product quality. For example, by modeling and reducing cabin noise and vibrations, engineers can create smoother and quieter rides, enhancing the overall driving experience for passengers.

SimScale supports all these applications in a single cloud-native platform, making it easier for engineers to switch between different types of simulations seamlessly.

The Role of Physics Simulation in Optimizing Designs

By leveraging the power of the cloud with SimScale, engineers can efficiently identify design flaws early in the development process, significantly reducing the need for physical prototypes. The platform’s ability to explore multiple design variations quickly not only accelerates development cycles but also lowers associated costs and enhances precision and accuracy.

Additionally, the flexibility of SimScale’s user-defined physics capabilities provides engineers with customization capabilities, enabling them to adapt simulations to address unique and specialized challenges and ensure results remain accurate and highly relevant to the problem at hand.

Case Study: Bühler Group

Bühler, a global leader in industrial equipment, leveraged SimScale’s cloud-native simulation to revolutionize their design process. By deploying early-stage simulations across 25 departments, over 100 engineers were able to run simulations online and on demand without capacity limitations. This approach enabled faster design convergence and reduced reliance on physical prototypes, saving both time and costs.

SimScale allowed Bühler to evaluate 60 design variants in just two weeks, a feat that previously required far more time and resources. This rapid iteration capability not only accelerated innovation but also supported bottom-line savings by eliminating the need for expensive hardware and traditional simulation tools. By streamlining workflows and enhancing collaboration across globally distributed teams, Bühler could achieve greater operational efficiency and bring products to market faster. Read more about Bühler’s success here.

“Integrating simulation early in the product development process allows one to better understand the physics and gain confidence in design choices. With SimScale, every design engineer has access to simulation.”

Clément Zémerli Senior Simulation Engineer in Corporate Technology at Bühler

Advanced Model Management Capabilities

SimScale’s advanced model management tools provide engineers with the capabilities to organize, track, and collaborate on their simulation projects seamlessly. These features are designed to enhance productivity, streamline workflows, and ensure precision throughout the simulation process.

SimScale’s model management capabilities stand out by providing:

• Version Control: Engineers can manage and track multiple iterations of their simulations, ensuring no critical updates are lost, and previous iterations remain accessible.
• Collaboration Tools: Customizable user permissions allow teams to collaborate securely, ensuring data integrity even with multiple contributors.
• Search and Organization: Engineers benefit from features such as tags, filters, and efficient search functions, enabling them to organize and locate simulation files with ease.
• Cloud-Native Integration: All model data is stored securely in the cloud, making it accessible from any location and removing the need for specialized hardware setups.
• AI-Powered Simulation Insights: SimScale leverages artificial intelligence to analyze simulation data, offering engineers predictive insights and optimization suggestions. This feature accelerates decision-making by identifying potential performance improvements or design flaws early in the process.

These tools empower engineers to streamline project workflows and make informed decisions efficiently.

Guided Simulation Workflows for Efficient Modeling

SimScale’s guided simulation workflows allow simulation experts to create templates and standardized processes. These workflows ensure consistency and help non-experts perform reliable simulations.

Step-by-Step Process

1. Import your CAD file into a SimScale template.
2. Adjust simulation parameters based on your company design guide.
3. Run the simulation in the cloud and get instant, standardized results.
4. Access, track, and share your results in SimScale from anywhere and with any team member.
5. Sync your results with your PLM system for seamless integration into your workflow.

Benefits of Guided Templates

• Efficiency: Standardized workflows reduce setup time.
• Accuracy: Templates ensure simulations are performed correctly.
• Collaboration: Teams can follow established processes, enhancing teamwork.

More about SimScale’s guided simulation workflows here.

The Power of Multiphysics Simulation in SimScale

SimScale’s Multiphysics simulation in the cloud allows engineers to model multiple physical phenomena in a single comprehensive analysis. This provides a more accurate representation of real-world behavior.

It also enables flexibility and a seamless combination of analyses, all in a single workbench. SimScale’s “One Platform, Broad Physics” approach enables engineers to combine different physics types, such as thermal, structural, electromagnetic, and fluid simulations, to analyze complex interactions within a design.

Here are some real-world examples:

• EV Motor Development: Analyze heat, stress, magnetic flux, and fluid interactions to optimize motor performance.
• Battery Thermal Management: Ensure efficient cooling in battery packs to prevent overheating.
• Fluid Flow Optimization: Improve industrial processes by modeling fluid dynamics accurately.

Give SimScale a Try?

Physics simulation enables engineers to overcome design challenges with precision and speed, making it an indispensable tool in modern engineering. By providing access to multiphysics analysis, guided workflows, and real-time collaboration, SimScale ensures engineers can streamline their processes and achieve optimized designs faster and more effectively.

Explore SimScale’s comprehensive resources for more information, or start simulating today by clicking the button below.

The post Physics Modeling Software: The Ultimate Guide to Physics Simulation appeared first on SimScale.

On-Demand Webinar

If these highlights caught your interest, there are many more to see. Watch the on-demand Simulation Expert Series webinar from SimScale on Rapid Design Simulations for Home Appliances & Consumer Electronics by clicking the link below.

Watch On Demand

1. Accelerate Design with Cloud-Native Simulation

SimScale’s cloud-native approach eliminates the need for heavy computational resources. Engineers can run high-fidelity simulations directly from a browser, anytime, anywhere, even on low-powered devices. The platform supports diverse physics, including structural, thermal, fluid dynamics, and electromagnetic simulations, making it a versatile tool for the entire design process.

2. Optimize Induction Cooktop Designs with Multiphysics Simulations

A live demonstration showcased how SimScale can simulate electromagnetic and thermal behaviors in induction cooktop designs. Key insights included:

• Electromagnetic field optimization to improve energy transfer efficiency and uniform heating
• The ability to analyze variations in coil geometry and air gaps for different cookware materials
• Thermal simulations to assess cooling efficiency within induction hubs, ensuring safe operation

These features help teams fine-tune designs for performance and energy efficiency.

3. Unlock AI-Powered Simulation Predictions

SimScale’s AI capabilities reduce lead times by narrowing down design options, enabling quick identification of optimal configurations. For example, in scenarios requiring the exploration of multiple geometries or material combinations, AI can predict performance trends, cutting down on iterative manual simulations.

4. Seamless Collaboration with Cloud-Native Sharing

SimScale simplifies collaboration with a Google Docs-style sharing model. Engineers and stakeholders can view or edit simulation setups in real time, regardless of location. This promotes faster iterations and minimizes delays in the design process.

5. Thermal Coupling for Improved Product Safety

The webinar highlighted SimScale’s ability to couple electromagnetic and thermal simulations. This is crucial for designs like induction cooktops, where understanding heat distribution and cooling is paramount. SimScale also allows teams to simulate temperature-dependent material properties, ensuring reliability under varying conditions.

Driving Innovation in Home Appliances and Consumer Electronics

The webinar underscored how cloud-native simulation tools like SimScale are reshaping the consumer electronics and home appliance sectors. By enabling engineers to explore designs earlier and more efficiently, teams can accelerate innovation and reduce costs while maintaining high standards of performance and safety.

If you missed the live session, don’t worry! Access the webinar recording here to dive deeper into the capabilities of SimScale for your projects.

For any questions or a live demo tailored to your application, feel free to contact us. Let’s shape the future of design together!

The post Top 5 Webinar Highlights: Rapid Design Simulations for Home Appliances & Consumer Electronics appeared first on SimScale.

ICs are fundamental to all microelectronic designs (in smartphones, laptops, industrial automation, medical devices, aerospace systems, etc).

Efficiency, reliability, and thermal management are at the heart of integrated circuit design, as they directly influence the performance and lifespan of the chip. A well-designed IC must balance power usage, maintain consistent operation, and effectively dissipate heat to avoid failures or degradation.

Key Components of Integrated Circuit (IC)

Integrated circuits function by leveraging the collaborative roles of their key components—transistors, resistors, capacitors, and diodes—on a compact silicon substrate.

In digital ICs, transistors toggle between on and off states to process binary data, while in analog ICs, they amplify or modify signals for precise output. Their rapid switching capability and scalability make transistors the driving force behind the IC’s functionality.

Resistors adjust signal levels and protect sensitive components by limiting current. Capacitors, on the other hand, store and discharge electrical energy, playing a critical role in filtering noise, smoothing power supply variations, and enabling signal timing adjustments. Diodes contribute by directing current flow and managing signal modulation.

In complex printed circuit boards (PCBs), components like transistors, resistors, capacitors, and diodes are arranged across multiple layers to accommodate high-density interconnections and optimize performance.

Thermal management through thermal vias (plated holes that transfer heat from hot layers to cooler ones) and heat sinks prevents overheating.

Types of Integrated Circuits and Key Components

Integrated circuits can be functionally classified into three main categories: digital, analog, and mixed ICs. Each type serves specific operational needs and applications.

Digital Integrated Circuit

Digital ICs process discrete signals, working exclusively with binary data—0s and 1s. They are ideal for computational tasks, logic operations, and data storage. Below are some of its applications:

• Microprocessors and microcontrollers
• Memory units (RAM, ROM, Flash)
• Logic gates and digital signal processors (DSPs)
• Embedded systems and IoT devices
• Communication systems (e.g., routers, switches)

Analog Integrated Circuit

Analog ICs operate with continuous signals, amplifying or processing voltage and current for applications. They offer precision and adaptability in translating natural phenomena into usable electronic signals. Here are some common applications:

• Audio amplifiers and signal processing devices
• Power management systems (e.g., voltage regulators)
• RF circuits in communication systems
• Medical instrumentation (e.g., ECG amplifiers)

Mixed Integrated Circuit

Mixed ICs combine digital and analog functions within a single chip, enabling complex tasks like analog-to-digital conversion (ADC) and digital-to-analog conversion (DAC).
While their hybrid nature delivers unmatched functionality, it also makes them more complex and cost-intensive to design and manufacture. Applications include:

• Smartphones and wearable devices
• Automotive systems (e.g., infotainment, sensors)
• Industrial automation and control systems
• Communication modules integrating RF and digital processing

Design Principles and Challenges in IC Design

IC design demands precision, with thermal management a critical priority to ensure performance and reliability. Here are five key factors to consider:

1. Power Management

Effective power management in ICs requires precise regulation and distribution to maintain stability and efficiency. Integrated voltage regulators ensure consistent supply levels, safeguarding transistors and logic gates from transient fluctuations that could disrupt operation.

Power and ground planes within the PCB layout provide low-impedance paths to handle current flow while minimizing noise.

Decoupling capacitors, strategically placed near active components, filter high-frequency noise and stabilize voltage at critical nodes.

2. Signal Integrity

In IC design, electric signals should maintain their quality and timing as they propagate through the circuit. High-frequency designs demand precise control over propagation delays to prevent timing mismatches that can disrupt functionality. Here are some common considerations:

• Crosstalk, a common issue in tightly packed layouts, should be minimized by careful spacing and using ground planes to isolate signal paths.
• For clock signal distribution, skew reduction techniques such as matching trace lengths and impedance are critical to maintaining synchronized signal timing across the circuit.
• Low-dielectric/highly conductive materials are increasingly used in interconnects to minimize resistive losses and ensure sharp signal transmission.

3. Thermal Management

Excessive heat buildup can cause shifts in operating parameters, degrade components, and even lead to complete failure. Poor thermal management risks damaging sensitive parts and forcing the system to operate outside its designed temperature range.

Engineers dissipate the heat efficiently to keep the operating temperature within safe limits. A low thermal resistance ensures better heat transfer, keeping the IC cooler during operation. Operating temperatures of the IC materials are designed to stay within specific limits.

PCB passive cooling mechanism has become an integral design choice. By integrating thermal vias and copper planes into the board layout, the PCB dissipates heat away from hotspots and distributes it across the layers. It reduces the dependency on external heat sinks or active cooling systems while maintaining the compact footprint required in modern IC designs.

External heat sinks remain a standard solution, especially in applications where high power density demands active heat dissipation.

Heat pipes are also a solid option for moving heat fast in compact systems. They work by transferring heat from the source to a cooler area using phase-change materials. For even more control, Peltier effect cooling plates can pull heat away directly using thermoelectric technology.

4. Miniaturization

The goal is to create smaller, more compact IC designs while maximizing power output—a concept known as power density. Careful optimization of the form factor (physical dimensions, shape, and layout) ensures the IC delivers high performance without increasing its physical footprint.

Compact designs are particularly critical in applications like portable electronics, IoT devices, and advanced computing systems, where space constraints are non-negotiable.

5. Durability

Mechanical stresses, such as those caused by temperature cycling, vibration, or physical impacts, can lead to microcracks in the package or bonding wires. Thermal stresses accelerate material fatigue and degrade the performance of critical components.

Electrical stresses, including voltage spikes and power surges, can push the IC beyond its operating limits, leading to breakdowns in transistors or interconnects.

Durability also involves optimizing the PCB layout and package design to distribute stress evenly and reduce localized strain.

The Role of Simulation in Integrated Circuit Design

Simulation enables engineers to create compact, high-performance circuits with greater precision than traditional validation methods. Engineers can simulate complex IC designs to manage thermal performance, minimizing hotspots and ensuring signal integrity.

SimScale offers a powerful yet accessible platform for IC design. Its thermal management software is particularly effective for applications where heat and energy are critical, such as PCBs with anisotropic material properties. It also supports thermomechanical analysis with multiphysics capabilities to evaluate stress and deformation caused by thermal expansion.

Engineers can run multiphysics simulations within minutes, combining thermal and structural analysis. It helps them identify potential hotspots and predict how these areas could impact the overall durability of the design.

IC Design Optimization in the Cloud

Cloud-based simulation tools, like SimScale, provide engineers with powerful capabilities to analyze and refine their designs using transient thermal analysis.

In a recent PCB design study in SimScale, nine chips were tested under varying conditions to observe how temperature and heat flux changed over time. For five chips, temperature changes were mapped by uploading time-dependent data tables, while the remaining chips had surface heat fluxes modeled similarly.

These images illustrate how temperature evolves over time in a PCB thermal simulation.

The next two images depict how surface heat flux varies over time.

These simulations allowed engineers to visualize temperature distributions on both the top and bottom of the PCB, offering insights into how heat flows through the system over time. The results highlighted areas requiring design improvements, which were integrated into the CAD model and re-tested iteratively until optimal performance was achieved.

Conclusion

Effective IC design means creating functional components while adapting to ever-shrinking form factors and rising demands for reliability.

SimScale allows engineers to predict and resolve challenges before they become costly mistakes.

Start simulating today with SimScale. No installation or credit card required.

Main Contributor: Muhammad Faizan Khan

The post Integrated Circuit Design, Types & Simulation appeared first on SimScale.

In every electric motor application, design requirements, such as size, power, efficiency, and precision, can vary significantly, especially under different working conditions. Electric motor simulation and modeling provide a cost-effective and efficient method of testing and optimizing design parameters, predicting performance, and evaluating design alternatives without the need for expensive physical prototyping. This accelerates the design process, improves efficiency, and minimizes costs.

Today, electric motors have become indispensable in achieving optimal performance and energy conservation due to their efficiency, reliability, and precise control. In this article, we explore the working principle of electric motors, how they are designed, and how simulation tools can replicate real-world design conditions and help troubleshoot and optimize the design process.

How Electric Motors Work?

An electric motor is a device that converts electrical energy into mechanical motion. It operates on the principle of electromagnetism: When an electric current flows through a wire coil placed in a magnetic field, a force is exerted on the coil, causing it to rotate. This rotational motion is harnessed to perform useful work.
An electric motor consists of several essential components:

• Stator: The stator is the stationary part of the motor and consists of a core made of laminated steel sheets. It houses the wire coils, known as windings, which generate the magnetic field.
• Rotor: The rotor is the rotating part of the motor and is typically composed of a shaft and a set of laminated steel cores. The rotor rotates within the stator’s magnetic field and is responsible for producing the mechanical output.
• Windings: The windings are insulated wire coils wound around the stator. These windings are often made of copper or aluminum and carry the electrical current that creates the magnetic field.
• Commutator (for DC motors): In DC motors, the commutator is a segmented cylindrical structure connected to the rotor. It plays a crucial role in reversing the direction of the electric current in the rotor windings, allowing for continuous rotation.
• Brushes (for DC motors): Brushes are conductive contacts that supply electrical current to the commutator, enabling the flow of electricity to the rotor windings.

Types of Electric Motors

Electric motors can be classified in several ways, such as “single-phase vs poly-phase” or “air-cooled vs liquid-cooled” electric motors. But the most prominent and prudent classification is based on the power source. Thus, we can classify electric motors broadly into DC and AC electric motors [2].

DC Electric Motors

DC motors are powered by direct current and are mainly of two types: brushed and brushless electric motors.

• Brushed DC motors use brushes mounted on the stationary stator of the motor. These brushes serve two purposes:
  • To carry the necessary current required to create a magnetic field to the rotor, and;
  • To ensure, with the help of a commutator, that the fixed magnetic field of the stator is in a continuous cycle of repulsion and attraction with the magnetic field generated in the rotor
• Brushless DC motors are constructed in reverse. The rotors have permanent magnets attached to them, and the stator has windings. The stator’s magnetic field is rotated via control electronics rather than mechanical commutation. Brushless DC motors are known for their improved efficiency, reliability, and reduced maintenance needs.

AC Electric Motors

AC Electric motors are powered by an alternating current applied to the stator, which generates a magnetic field that interacts with another magnetic field in the rotor, causing rotation. There are also two main types of AC electric motors: synchronous motors and asynchronous motors (also known as induction motors).

• Synchronous AC motors have rotors that independently produce their own magnetic field (either via permanent magnets affixed to them or via a separate DC source), which interacts with the magnetic field of the stator to produce rotation. In these motors, the speed of the rotor is synchronized with the frequency of the alternating current that powers it and they are both linked immutably.
• Induction AC motors, also called asynchronous motors, have rotors with no magnetic fields of their own but have wire windings that are induced with a magnetic field from the magnetic field of the stator. The magnetic field of the stator and the induced magnetic field in the rotor interact to cause rotation. These motors have lower rotor speeds than the alternating current frequency; this difference is known as ‘slip’. The torque of the motor is proportional to this slip.

The Theory behind Electric Motors

Electric motors work based on the relationship between an electric current and the magnetic field it generates when passing through a conductor. Important formulas in expressing this relationship include Coulomb’s Law, Ampere’s law, Faraday’s law of induction, and Lenz’s law.

Coulomb’s Law

Coulomb’s law states that the force of attraction or repulsion \(F\) between two charges, \(q_1\) and \(q_2\), is directly proportional to the product of the quantities of each charge and inversely proportional to the square of the distance \(d\) between them:
$$ F = k_e \frac{q_1 q_2}{d^2} $$
Where \(k_e\) is the electrostatic constant.

This tells us that there is a force between two charges interacting with each other, be they similarly or oppositely charged.

Ampere’s Law

Ampere’s law indicates that an object of length \(l\), carrying an electric current \(I\) creates a magnetic field \(B\) around it. It is expressed as:
$$ \int{B.dl} = \mu_0 I $$

Where \(\mu\) is the permeability constant.

Faraday’s Law

Faraday’s law of induction states that the induced electromotive force in a coil \(\epsilon\) is directly proportional to the negative of the change of magnetic flux \(\Phi_B\) over time \(t\):
$$ \Phi_B = -N \frac{d\Phi_B}{dt} $$
Where \(N\) is the number of loops in the coil.

This allows us to predict the strength of an electromotive force given the rate of change in the magnetic flux and the number of winding coils on a conductor. The negative sign indicates that the direction of the electromotive force is opposite to the direction of the rate of change of the magnetic flux. This principle is known as Lenz’s law, and its expression is identical to that of Faraday’s law, albeit with a different focus.

These fundamental formulas allow us to understand how electromagnetism works and consequently, how an electric motor works. These were brought together into Maxwell’s equations and are used in electric motor simulation and design to model the electromagnetic phenomena taking place. Other types of engineering simulation are also used to simulate the physical properties of the electric motor and how they interact with each other while the electric motor is in operation. These include structural mechanics simulation and thermal analysis.

Electric Motor Simulation and Design using SimScale

Engineering simulation enables engineers to virtually recreate and study motor behavior under various operating conditions. It provides insights into performance, efficiency, and potential design improvements, saving time and resources compared to traditional trial-and-error methods. By simulating motor performance, engineers can evaluate different design options, identify potential issues, and fine-tune motor parameters to achieve optimal performance. It allows for the exploration of various scenarios and helps in making informed decisions to enhance motor efficiency, reliability, and overall performance.

As a cloud-native simulation platform, SimScale offers a comprehensive range of tools for simulating and optimizing electric motors without any hardware or software limitations. All simulations can be run online directly in a web browser. These include electromagnetic simulation, thermal simulation, and structural analysis.

Electromagnetic Simulation of Electric Motors

EM simulation uses magnetostatics, time-harmonic magnetics, and electrostatics simulation features to visualize and analyze electromagnetic parameters and study their interaction in an electric motor during operation. This gives the designer valuable insight into torque generation and ripple effects and how to potentially reduce inefficiencies due to slip or other design flaws. It also helps in selecting the correct magnetic and conductor materials that work best together to achieve the highest efficiencies.

Using SimScale’s electromagnetic simulation solver, engineers can analyze the following:

• Magnetic Field Analysis: SimScale provides tools to analyze the magnetic fields generated by electric motors. This includes both static and transient simulations.
• Eddy Current Analysis: Users can simulate eddy currents to evaluate losses and heating effects in the motor components.
• Torque Calculation: Users can calculate the torque produced by the motor under various operating conditions.
• Inductance and Resistance Calculation: Users can determine the inductance and resistance of motor windings, essential for understanding the motor’s electrical characteristics.

Thermal Simulation of Electric Motors

Thermal analysis uses thermal simulation tools to visualize the forms of heat transfer: conduction, convection, and radiation in an electric motor. It enables engineers to design and test cooling systems, find ways to mitigate excessive heating, or design easier and quicker heat distribution and dissipation. This can minimize energy losses and maximize the motor’s efficiency and lifespan.

Using SimScale’s thermal analysis tool, engineers can study the following aspects:

• Heat Transfer Analysis: SimScale allows users to perform thermal simulations to evaluate the temperature distribution within the motor, ensuring that the motor operates within safe temperature limits.
• Cooling System Design: The platform can be used to design and optimize cooling systems, such as air or liquid cooling, to effectively manage heat dissipation.

Structural Analysis of Electric Motors

In addition to studying the electromagnetic and thermal phenomena in an electric motor, engineers can couple those with analyses of the motor’s structural integrity. This includes stress and vibration analyses, where users can leverage SimScale’s structural mechanics simulation capabilities to analyze the mechanical stresses and vibrations experienced by the motor components during operation, helping to ensure structural integrity and longevity.

This makes use of Finite Element Analysis (FEA) to simulate the physical properties of the parts of an electrical motor, the mechanics of its operation, and the effects of this operation on the properties of the motor parts. FEA can give an engineer valuable insight into the mechanical behavior and structural integrity of an electric motor and help evaluate areas of deformation or weak spots, highly stressed areas, and sources of vibration.

Cloud-based Parametrization, Optimization, and Collaboration

By leveraging the cloud, SimScale offers unparalleled levels of optimization and parametrization, enabling engineers to reduce their simulation time from days and weeks to hours and minutes. To understand the impact of different design variables on motor performance, users can conduct parametric studies and run as many simulations as needed in parallel without compromising the quality of the results or being limited by local hardware constraints. This allows for efficient shape and design optimization to reach the optimal design under the electric motor’s operational conditions.

SimScale also supports easy and quick collaboration by streamlining the ability to share simulation projects with team members and stakeholders. In other words, team members can access simulation projects anywhere by simply accessing the corresponding URLs. This enhances collaboration and feedback, accelerates design innovation, and allows for enterprise-wide deployment of simulation.

By leveraging SimScale’s comprehensive simulation capabilities, engineers can efficiently optimize electric motor designs, enhancing performance, efficiency, and reliability while reducing development time and costs.

Electric Motor Simulation: Start Simulating Now

The design phase of any product often requires multiple design iterations to achieve every possible performance improvement. Using SimScale’s FEA, EM, and Thermal simulation tools, cloud-native simulation allows for iterations of design changes to be carried out relatively stress-free.

SimScale offers simulation with an assortment of cutting-edge proprietary and open-source solvers, which have been incorporated into SimScale’s cloud-native computing interface to be able to run multiple electric motor simulations in parallel rather than one at a time. All this can be done within a web browser with a user-friendly interface without the need for any expensive and cumbersome hardware.

You can start simulating right away on the SimScale platform straight from your favorite web browser without any need for software installation or hardware required.

Contributor: Olawale Olayemi

The post Electric Motor Simulation and Design appeared first on SimScale.

The performance and durability of EV batteries are significantly influenced by how much they are kept from overheating. That’s why effective cooling systems are used to manage their thermal performance. Proper EV battery thermal management is essential for maintaining battery health, ensuring safety, and optimizing vehicle efficiency. This aspect crucially impacts the battery’s lifespan and the vehicle’s range.

SimScale, with its advanced thermal design analysis capabilities, emerges as a key player in the battery simulation software market. As a sophisticated cloud-native platform, SimScale empowers engineers and designers to analyze, simulate, and enhance EV battery cooling systems, addressing the complex thermal challenges of EV batteries and enabling the development of efficient and reliable solutions. Let’s take a look at how EV battery cooling can be done and what challenges stand in the way.

Understanding EV Battery Cooling

EV battery cooling is essential for regulating battery temperature to maintain efficiency and safety. Batteries generate heat during operation, which can reduce efficiency and lifespan and pose safety risks if not properly managed. Common cooling systems include:

• Air cooling: it uses fans to circulate air.
• Liquid cooling: it involves circulating particular types of coolant through the battery pack for more efficient heat dissipation.

How to Cool Down an EV Battery?

Cooling down an EV battery, especially during rapid charging or in high-demand scenarios, requires innovative strategies to handle intense heat generation. Key methods include:
Enhanced Air Cooling Systems: These systems use improved airflow techniques and advanced materials to increase heat dissipation efficiency.

• Advanced Liquid Cooling Solutions: More effective in managing high heat loads, these systems circulate coolant more efficiently and can be integrated directly with battery cells.
• Thermal Regulation Technologies: Incorporating smart sensors and control units that actively monitor and adjust the cooling process based on real-time battery temperature data.
• Phase-Change Materials: These materials absorb and release thermal energy to maintain consistent battery temperatures.
• Cold Plate Technology: Particularly effective in high-performance EVs, cold plates draw heat away from the battery cells more directly and efficiently.

Key Challenges in EV Battery Cooling

Thermal management of EV batteries still faces multifaceted challenges that impact battery performance and longevity. High heat dissipation during operations, particularly under fast-charging conditions, intensifies thermal management demands and can accelerate battery degradation if not managed properly. Cooling systems must also adapt to diverse environmental temperatures and balance efficiency with the constraints of space and weight. Additionally, the pressure to be cost-effective and sustainable necessitates innovative solutions for maintaining battery health and ensuring vehicle safety.

EV Battery Thermal Management: A Key to Sustainable EV Battery Design

EV battery thermal management goes beyond ensuring performance and safety; it plays a vital role in the sustainability of the entire EV ecosystem. Efficient cooling systems are integral to reducing the overall energy consumption of the vehicle, thereby decreasing its environmental impact. Better thermal regulation directly translates to less energy waste, prolonging battery life and reducing the frequency of battery replacements [2]. This is crucial in the context of environmental sustainability, as it minimizes the ecological footprint associated with battery production and disposal.

Efficient cooling systems play a pivotal role in enhancing the sustainability of EVs. By maintaining optimal operating temperatures, these systems ensure that batteries operate at peak efficiency, thereby conserving energy and extending the vehicle’s range. This efficiency is particularly important as the EV market grows, as it contributes to reducing the total energy demand of the transportation sector. Moreover, advancements in cooling technologies, such as the use of eco-friendly coolants and materials, further align EVs with environmental sustainability goals.

The Role of SimScale in EV Battery Cooling and Design

EV batteries are a highly competitive landscape, and the demand for innovative solutions in battery cooling is more pressing than ever. This is a domain where efficiency, safety, and performance intersect, necessitating advanced EV battery thermal management strategies. It’s within this challenging environment that SimScale enters the picture.

Offering a cloud-native engineering simulation platform, SimScale empowers professionals to tackle the complexities of EV battery cooling with highly accessible and scalable simulation capabilities. By utilizing SimScale’s thermal analysis, CFD, and structural analysis tools, engineers can experiment with and refine cooling system designs quickly and effectively all in a virtual space, accelerating the product development process and propelling the innovation of efficient and robust EV technologies.

SimScale offers a comprehensive suite of simulation capabilities based on multiple physics that can be run simultaneously all on one platform. Thanks to their cloud-native nature, SimScale’s simulation tools are not limited by hardware constraints or siloed workflows. On the contrary, they leverage the power of cloud computing to enable engineers to run as many simulations as they need in parallel with no delay. This shortens the simulation lead time and enables the use of simulation early in the design process, which in turn allows engineers to iterate faster and optimize their designs more efficiently.

In the examples below, we take a look at how thermal simulation in SimScale is utilized to improve EV battery cooling.

Case Study 1: Thermal Simulation for High-Performance EV Components

In a case study featuring Rimac Automobili, SimScale’s thermal simulation capabilities were leveraged to enhance the design of high-performance EV components. The simulation focused on critical aspects like cooling efficiency and heat dissipation, which are paramount for the high-power electronic systems used in Rimac’s electric hypercars. This collaboration underscores the potential of cloud-native simulation to drive innovation in the design of high-performance EVs, ensuring both efficiency and reliability.

Case Study 2: Thermal Management Simulation of an EV Battery

An EV battery thermal management simulation case study involving Bold Valuable Technology showcases how they utilized SimScale to develop a high-end electric motorsport series battery. The team conducted over 100 simulations to analyze thermal behavior and coolant dynamics, significantly reducing the need for physical prototypes and experimental tests, thereby demonstrating the effectiveness and efficiency of using SimScale for EV battery cooling. Read more about this in our dedicated blog on Battery Thermal Management for Electric Vehicles.

Case Study 3: Thermomechanical Simulation of an EV Battery

A thermochemical simulation case study on SimScale was conducted to assess the performance of EV Battery Pack Gap Fillers. Utilizing SimScale’s thermomechanical simulation capabilities, this comprehensive analysis covered aspects such as thermal conductivity and mechanical stresses, offering insights into how different gap filler materials and thicknesses affect battery temperatures and mechanical swelling. The study highlighted the critical role of material selection and design optimization in improving EV battery thermal management while ensuring mechanical robustness in EV battery packs.

Case Study 4: Simulation and Optimization of an EV Battery Cooling Plate

Improving the design of EV battery cooling plates is crucial for optimizing battery performance, reliability, and lifecycle return on investment. This SimScale study simulated and optimized an EV battery cold plate design. The study involves several stages of simulation, including geometry setup, automatic meshing, and thermomechanical analysis. It focuses on fully coupled conjugate heat transfer (CHT) analysis and uses a Multi-purpose CFD solver for evaluating pressure-flow characteristics. The cloud-native simulations in SimScale allow for analyzing various scenarios, including geometric variants and different coolant flow rates, providing valuable insights into the design’s thermal and flow dynamics.

Case Study 5: Vibration Analysis Simulation of an EV Battery

Vibration analysis is crucial for EV batteries, as they are sensitive to shocks and vibrations, which can impact their performance and safety. That’s why it is crucial to analyze and optimize the structure of the battery to conform to standards and regulations. Using SimScale’s Finite Element Analysis (FEA) tools, the vibration of an EV battery was simulated, adhering to the UN 38.3 standard for safe transportation. It involves a virtual shaker table test, replicating the T3 standard, and covers setting up simulations within SimScale for modal and harmonic analysis, which is crucial for designing batteries that withstand various vibration conditions. This study is particularly useful for identifying potential resonance issues and optimizing battery structure before physical testing, thereby enhancing reliability and safety in real-world conditions.

The Future of EV Battery Cooling with SimScale

SimScale’s cloud-native simulation platform proves to be a valuable tool in advancing EV battery cooling and design. From thermomechanical analyses of gap fillers to optimizing cold plates and conducting vibration tests, SimScale enables a comprehensive understanding and enhancement of battery performance. Its efficient, cost-effective solutions demonstrate how cloud-native engineering simulation is pivotal in addressing the challenges and pushing the boundaries in the EV industry. To explore more of SimScale’s capabilities and how it can advance your EV battery cooling solutions, visit our product pages or simply sign up for free and let our team of experts support you with your analysis and design.

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