What if the moment your product design becomes clearest is also the moment when it\u2019s too expensive to change?<\/p>\n
That uncomfortable reality sits at the heart of modern product development, and it\u2019s one of the biggest reasons why engineering teams leave performance, efficiency, and innovation on the table.<\/p>\n
This blog explores why simulation is still underused where it matters most: early design. Moreover, modern, GPU\u2011based simulation tools such as Ansys Discovery<\/u><\/strong><\/a> <\/span>are changing the status quo, making fast, interactive design exploration not only possible, but practical.<\/p>\n Here we discuss the key ideas, examples, and insights into a single narrative: why we need to shift simulation left, what\u2019s been holding us back, and how design space exploration is unlocking better decisions earlier in the process.<\/p>\n <\/p>\n Most engineering organisations recognise some version of this curve.<\/p>\n Early in development during conceptual and preliminary design, engineers have enormous design freedom. Changes are cheap. Ideas flow freely. But at this stage, knowledge is limited. Assumptions dominate.<\/p>\n Later in the cycle, during detailed design, prototyping, and testing, knowledge about the product grows rapidly. Simulation results are richer. Physical behaviour is clearer. But by then, change is expensive. Tooling has been developed. Schedules are firmed up. Budgets are committed.<\/p>\n This creates a paradox:<\/p>\n When you have the most freedom to change the design, you know the least. Traditionally, simulation lives in that second statement. High\u2011fidelity CFD, structural, and thermal analysis are often used as validation tools, not exploration tools. They confirm whether a design works, but don\u2019t help define what the design should be.<\/p>\n And that\u2019s a missed opportunity.<\/p>\n <\/p>\n If shifting simulation earlier is so obviously valuable, why hasn\u2019t the industry already done it?<\/p>\n The reasons are familiar to anyone who\u2019s worked across design and analysis teams:<\/p>\n Siloed workflows<\/strong><\/span><\/p>\n Concept designers and CAD engineers often work separately from simulation specialists. The tools, skills, and responsibilities sit in different teams. By the time simulation enters the process, key design decisions are already fixed.<\/p>\n High barriers to entry<\/strong><\/span><\/p>\n Traditional simulation requires geometry cleanup, meshing strategies, solver configuration, and long run-times. That\u2019s manageable in later phases but incompatible with fast, iterative conceptual work.<\/p>\n Slow feedback loops<\/strong><\/span><\/p>\n Early design thrives on immediacy. Designers need to see what happens when something moves, changes, or scales dynamically. Waiting hours, or days for results kills momentum.<\/p>\n Accuracy trade\u2011offs<\/strong><\/span><\/p>\n Historically, faster tools often meant lower accuracy. That made engineers reluctant to trust early\u2011stage simulation results for anything other than rough visualization.<\/p>\n Together, these factors have kept simulation anchored late in the process. Until now.<\/p>\n <\/p>\n Ansys Discovery exists to answer a single question:<\/p>\n What if simulation were fast, intuitive, and interactive enough to be used during design, not after it?<\/strong><\/span><\/em><\/p>\n Discovery is not a replacement for flagship solvers like Ansys Fluent or Mechanical. Instead, it complements them by enabling early\u2011stage exploration, where speed and insight matter more than ultimate fidelity.<\/p>\n Three characteristics make this possible.<\/p>\n Interactive speed<\/strong><\/span><\/p>\n Discovery is built to run entirely on GPUs for meshing, solving, and post\u2011processing. This allows designers and engineers to rotate geometries, move components, or adjust parameters and see flow or thermal behaviours regenerate almost instantly.<\/p>\n This isn\u2019t about shaving minutes off runtimes. It\u2019s about thinking with simulation rather than waiting for simulation.<\/p>\n Minimal setup overhead<\/strong><\/span><\/p>\n Complex CAD can be imported directly, often without time\u2011consuming cleanup. Geometry preparation, automatic meshing, and volume extraction are designed to \u201cjust work,\u201d even for assemblies most engineers would normally hesitate to simulate early on.<\/p>\n Increasing accuracy<\/strong><\/span><\/p>\n Speed is meaningless without trust. Importantly, Discovery\u2019s underlying CFD technology increasingly overlaps with Fluent\u2019s GPU solver. Benchmark comparisons show strong correlation with experimental data, particularly for trend\u2011driven analysis. Exactly what early design requires.<\/p>\n The result: simulation moves from a specialist activity to a design capability.<\/p>\n <\/p>\n One of the most powerful shifts enabled by fast simulation isn\u2019t just doing things earlier, it\u2019s doing more of them.<\/p>\n Early designs often rely on single \u201cbest\u2011guess\u201d inputs, for example, one assumed inlet temperature, one estimated flow rate, one heat generation value.<\/p>\n But real systems are variable. Manufacturing tolerances, operating conditions, and user behaviour all introduce uncertainty.<\/p>\n This is where design space exploration comes in.<\/p>\n Instead of asking, \u201cDoes this design work?\u201d, engineers can ask:<\/p>\n <\/p>\n Within Discovery, engineers can define parameters, such as ambient temperature, convection coefficients, inlet mass flow, and power losses. Rather than testing every possible combination – which quickly becomes unmanageable – Discovery now supports Latin Hypercube sampling. This creates an efficient set of simulation points that represent the design space with far fewer runs than a full factorial approach.<\/p>\n Once complete, a sensitivity analysis reveals how much each parameter influences key result, such as maximum temperature or pressure drop.<\/p>\n The insight is more often surprising.<\/p>\n Taking an electronics cooling example: \u00a0several assumed \u201cimportant\u201d variables turned out to have almost no impact on peak temperatures within the tested range. Others, such as mass flow rate, dominated performance.<\/p>\n That clarity changes how teams work:<\/p>\n <\/p>\n Once the important parameters are identified, the natural next step is optimization.<\/p>\n Discovery\u2019s upcoming one\u2011click optimization capability builds directly on sensitivity results. Engineers define objectives, such as:<\/p>\n The solver then automatically explores the design space, generating a Pareto front of optimal trade\u2011offs.<\/p>\n Instead of hunting manually for a \u201cgood enough\u201d design, teams can see which improvements are possible, where trade\u2011offs occur and which designs are optimal under competing objectives<\/p>\n Crucially, this happens early enough that changes are still affordable.<\/p>\n <\/p>\n *Important note: none of this replaces detailed analysis.<\/em><\/p>\n Discovery\u2019s role is to inform and guide, not to finalize production decisions. Once a promising concept is identified, models can be transferred directly into high\u2011fidelity solvers such as Fluent, Icepak, or Mechanical for detailed validation.<\/p>\n This creates a continuous digital thread to deliver fast exploration, early, targeted high\u2011accuracy analysis later and fewer late\u2011stage surprises.<\/p>\n As Discovery\u2019s capabilities continue to expand, particularly in multiphysics coupling and solver accuracy, the overlap with traditional tools grows. But the philosophy remains the same: right tool, right phase, right question.<\/p>\n <\/p>\n The most important idea here isn\u2019t a new solver or feature. It\u2019s a mindset shift.<\/p>\n Simulation doesn\u2019t have to wait until designs are \u201cfinished.\u201d In fact, that\u2019s the moment when it delivers the least strategic value.<\/p>\n By enabling fast, interactive design space exploration, tools like Ansys Discovery allow engineering teams to learn more, earlier, take better decisions with incomplete information and preserve design freedom when it matters most.<\/p>\n <\/p>\n That\u2019s how you move from verifying designs to designing with insight.<\/p>\n And that\u2019s how simulation finally earns its place at the start of the development curve, not the end.<\/p>\n <\/p>\nThe Product Development Paradox: When Knowledge Rises, Freedom Falls<\/strong><\/h3>\n
\nWhen you know the most, it\u2019s too expensive to act.<\/strong><\/span><\/p>\nWhy Simulation Struggles in Early Design<\/strong><\/h3>\n
Shifting Simulation with Ansys Discovery<\/strong><\/h3>\n
From Single Designs to Design Space Exploration<\/strong><\/h3>\n
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Sensitivity Studies: Understanding What Really Matters<\/strong><\/h3>\n
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From Understanding to Optimization<\/strong><\/h3>\n
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Discovery in the Wider Simulation Process<\/strong><\/h3>\n
Rethinking How We Use Simulation<\/strong><\/h3>\n