Forget the long waits! New advancements in engineering simulation, particularly real-time surrogate and reduced order models, are bringing instant insights to complex designs, offering immense benefits for rapid prototyping and risk assessment, while simultaneously evolving the expertise required from simulation specialists.
For decades, engineering simulations have been the backbone of product development, allowing designers and engineers to predict performance and identify potential flaws long before physical prototypes are built. However, these powerful tools have traditionally come with a significant bottleneck: time. Complex models, especially those involving multiple interacting physical phenomena—known as multiphysics computations—could take hours, days, or even weeks to yield results, slowing down the iterative design process.
This challenge is now being addressed by cutting-edge innovations that are making simulations faster and more accessible than ever before. The advent of real-time simulation is transforming the engineering landscape, empowering designers and fundamentally shifting the skills required for modern engineering roles. It’s moving from a post-design validation step to an integrated, instantaneous feedback loop.
The Evolution of Simulation: From Complex Models to Real-Time Insights
Early validation data for complex machine designs, such as a barrel-flipping mechanism, often requires engineers to simplify models to manage computational complexity. Techniques like using rigid connectors, remote masses, or remote loads for components like a barrel, or simplifying fixture representations, have been essential to achieve a manageable finite element model that can be quickly meshed and solved, as demonstrated in SolidWorks Simulation. These simplifications, while practical, highlight the constant trade-off between model accuracy and computational cost.
The core problem has always been that executing high-fidelity simulations can be incredibly time-consuming, sometimes taking “weeks per design” as noted in a review published in the journal Procedia Computer Science. However, new technologies are dramatically reducing this wait time.
Introducing Surrogate Models and Reduced Order Models (ROMs)
A major breakthrough in achieving real-time simulation comes from innovations like surrogate models. These models take a fully-fledged multiphysics simulation and compress it into a compact, faster-to-evaluate format, often leveraging machine learning. By strategically sampling the original complex model at key points, a surrogate model can train a faster approximation that predicts results for new scenarios instantaneously.
Bjorn Sjodin, senior vice president of product management at COMSOL, highlighted that these models can be evaluated “instantaneously,” drastically cutting down solution times that previously might have taken 15 minutes for a full model with unknown inputs. This kind of speed is crucial for impatient engineers and accelerated design cycles, as reported by IEEE Spectrum.
Beyond surrogate models, reduced order models (ROMs) employ other mathematical optimizations, including pattern recognition and slimming down complex equations. ROM techniques, as described in an industry-wide review of ROMs, can be intrusive (manipulating governing equations) or non-intrusive (using simulation data). Combining neural networks with traditional ROM tools can achieve computational speedups of up to 100,000 times, making sophisticated analysis feasible in near real-time.
Empowering Design: Why Speed Matters
The ability to run simulations in real-time has profound implications across industries, particularly for accelerating the product development lifecycle and managing risk.
- Rapid Prototyping and Validation: For machine designs requiring early validation, real-time simulations allow engineers to quickly test design iterations. This means less guesswork and more data-driven decisions at every stage, from initial concept to detailed design.
- Startup Agility: Hardware startups, often operating with limited capital and tight timelines, benefit immensely. Simulation allows them to determine the feasibility of complex technology without pouring years of hard work and money into physical prototypes that might fail. It reduces uncertainty and accelerates market testing.
- On-the-Go Decision Making: Real-time models can be compiled into standalone apps runnable on laptops or even smartphones. This enables engineers and even non-specialists on the factory floor to evaluate performance and make immediate decisions, such as simulating electric vehicle battery packs or predicting food spoilage in cold storage to reduce waste by 20 percent.
Beyond Physics: Simulation for Strategic Decision-Making
The power of simulation extends beyond purely physical phenomena to encompass strategic and economic decision-making. In engineering economy problems, uncertainty in variables like interest rates, cash flows, and project life can lead to flawed traditional analyses based on point estimates.
Using Monte Carlo techniques with simulation software, engineers can model this uncertainty, generating probability distributions for outcomes like future worth or Net Present Value (NPV). This provides a more realistic understanding of project risk and improves decision quality. For example, incorporating variability can reveal a much higher probability of a negative NPV than a deterministic analysis would suggest, offering invaluable insight for investment comparisons under uncertainty.
The Future of Engineering Roles: Adapting to Real-Time Tools
The rise of real-time FEA (Finite Element Analysis) and CFD (Computational Fluid Dynamics) solvers has prompted questions about the future of dedicated simulation engineering roles. While some worry that advanced tools might eliminate the need for specialized analysts, the consensus within the community points to an evolution rather than an obsolescence.
The reality is that simulation still requires deep engineering understanding beyond just “pressing a button.” As solvers become faster and more automated, the role of the engineer shifts:
- Model Creation and Simplification: Expertise in setting up accurate models and making intelligent simplifications remains crucial.
- Interpretation and Validation: Analyzing and interpreting simulation results, validating them against real-world data, and understanding their implications requires a strong engineering background.
- Integration and Optimization: Engineers will focus more on integrating simulation into the broader design workflow, using real-time feedback to optimize designs more rapidly and explore a wider range of possibilities.
- Application Development: With tools like COMSOL allowing users to compile models into standalone apps, engineers with a blend of simulation and software development skills will be highly valuable in creating tailored, accessible simulation tools for specific applications.
Ultimately, real-time simulation empowers engineers to be more agile, innovative, and impactful. It transforms the bottleneck of analysis into an integrated, interactive part of the design process, allowing for more robust product development and better decision-making across the board.
