
Léo Balland
Marketing Manager, Cognitive Design
As industries push the boundaries of product innovation, the pressure on design engineers to deliver faster, more efficient solutions is greater than ever. Traditional design methods, often reliant on trial and error, struggle to meet the growing demands for precision, speed, and cost-effectiveness. In response, many companies have integrated simulation into their product development processes, guiding engineers through design iterations and significantly reducing lead time and costs. Teams specifically dedicated to simulation now work closely with design engineers, offering continuous feedback on performance. This collaboration occurs mainly at a stage where the design is mostly defined, and minor adjustments need to be carried out before final validation by the expert team.
Recent technological advancements, including artificial intelligence and implicit modeling, have further enhanced the role of simulation by enabling faster calculations and real-time analysis. These innovations accelerate the iterative loop between design and simulation. By extending the role of simulation across more stages of the product development process—from the ideation phase to pre-verification—these new practices are laying the foundation for the concept of Simulation-driven Design.
Simulation-driven design is an engineering methodology that utilizes sophisticated virtual simulation technologies to guide engineers in the design and development process. By simulating factors like stress, heat, fluid dynamics, and material behavior, the Simulation-driven design approach helps engineers make better decisions throughout the design process before a physical prototype is created.
The Simulation-driven Design approach differs from traditional simulation methods in design engineering by streamlining the entire product development process. By integrating simulation data at every stage of design, this method enables engineers to identify first-feasible designs earlier and more quickly, explore a wider range of design possibilities, and avoid costly late-stage errors.
The rise of simulation-driven design is supported by advancements in several key technologies.
Solvers like Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and multi-physics simulations are now more accessible and powerful than ever before. These tools allow engineers to simulate complex phenomena such as fluid dynamics, mechanical stress, and heat transfer with a high degree of accuracy.
Machine Learning (ML) and Artificial Intelligence (AI) are also being integrated into simulation workflows, offering predictive insights and automating certain aspects of the design process. Even though these new technologies are powerful and highly precise, they can’t replace the need for final validation of the last design, which is thoroughly proceeded by an expert team.
Implicit modeling technology is also a key enabler of the simulation-driven design approach. Due to its ability to handle complex geometries and modifications with greater reliability and efficiency, it allows for accurate modeling of intricate geometries and material behaviors, which are crucial for detailed design optimization. This capability supports thorough and reliable analysis, facilitating better-informed design decisions and accelerating the development process.
Without any supportive hardware solutions, running simulation can be a real challenge due to the quantity of data to process. Now with graphics cards (GPUs) this process has shifted from taking hours or days to being virtually instantaneous. Engineers can now see results within seconds after importing a model, without needing a high-end computing setup as GPUs leverage thousands of parallel processors to handle the computations. Engineers can adjust designs and physics settings on the fly, observing the outcomes in real-time.
Simulation-driven design offers multiple advantages that significantly enhance the product development process.
Although companies using simulation to guide the design process observe a remarkable reduction of the design development cycle, integrating simulation might cause some delay in the final design delivery. In most companies, this design-simulation process is currently siloted between different teams: the simulation experts who are running the virtual testing and the design engineering team, who is responsible for developing the design. Design engineers create initial designs, while the simulation team analyzes and tests them, providing feedback to the first protagonists. The design engineers would then adjust the models’ geometry based on the simulation results to improve performance and address any identified issues. This back-and-forth communication between the two teams would occur iteratively, gradually refining the design throughout the process. Although this approach allows companies to increase the chance of having flawless designs, the separation of roles creates a slower feedback loop and requires constant coordination, impacting the efficiency and agility of the design process.
While simulation provides design engineers with valuable data, the modifications to the 3D model must be done manually. Currently, tools integrating simulation does not automatically adjust the design geometry. Engineers must modify designs based on the insights provided by simulations, which significantly extend the optimization process. This becomes especially cumbersome as the designs grow more complex and the performance requirements become more demanding. Additionally, as the amount of data generated by simulations increases, the time required to analyze and implement modifications manually also rises, slowing down the overall optimization cycle.
Changing established process to a simulation-driven design approach can also present several challenges for organizations and engineers. While the core design processes remain unchanged, engineers face new demands in practice and skill acquisition. Adopting this approach requires engineers to conduct various simulations at different stages of the design cycle, from simple directional analyses early on to more detailed and accurate evaluations later. This evolution necessitates a deep understanding of engineering physics, proficiency with CAD and CAE applications, and knowledge of analysis methods.
For companies, adopting a simulation-driven design approach can also be challenging. Transitioning to this approach often involves significant changes in engineering practices, requiring substantial investment in new tools and training for staff.
Currently, integrating simulation driven design can be a significant challenge for companies evolving in competitive industries where the ability to innovate fast is key to stay ahead. Now, thanks to recent cutting-edge technologies, companies can leverage the full potential of modern simulation-driven design by gathering both simulation and design on a single platform. This integration breaks down the traditional barriers between design and simulation teams, reducing significantly the time required for iterations, thus optimizing the product development cycle. By streamlining operations from ideation to pre-verification, engineers can now efficiently create, test, and refine designs in real-time from the ideation stage to pre-verification and testing.
This shift of paradigm has already begun with software like Cognitive Design, a revolutionary tool using simulation-driven design approach to accelerate optimization and ensure manufacturability for even the most complex models. By leveraging advanced features, this software automatically identifies and implements geometric optimizations according to simulation results. Its unique geometric engine enables rapid iteration and precise optimization, allowing for informed decisions at every stage of the design process. Discover how Cognitive Design can transform your engineering process.
Sign up for a 60-day free trial of Cognitive Design today and experience the future of simulation-driven design. Try it now
Explore our frequently asked questions to understand how our software can benefit you.
Yes, some functions in cognitive design uses AI (costing, conversion to CAD, manufacturing analysis). It is pre-trained by CDS and packaged in the software, so there is no training happening on your side, and your data is not used.
Yes, you can convert mesh or implicit models to CAD and export them as a .step. It works best for midly complex models (e.g. generative design results). Lattice models could techically be converted to CAD, but would be too heavy for CAD tools to import and handle.
No, our APP workflows use hybrid meshing, keep ing the original CAD precision around functional regions, and having smooth mesh elements on organic features.
Cognitive Design uses a proprietary hybrid geometrical engine, mainly based on volumetric modeling (Signed Distance functions), with in addition mesh and CAD operators.
Cognitive Design uses a node-locked license system, tied to each workstation. This approach aligns with the offline, on-premise setup. Floating licenses are not yet available.
You can export 3D models in BREP format, with .step or .stp extensions—ensuring compatibility with most CAD software.
Cognitive Design runs fully offline. It's an on-premise software that doesn’t require any internet connection for day-to-day use.
Cognitive Design is particularly well suited for complex, high-value mechanical parts such as lightweight structures, gearbox housings, functional brackets, or fixtures subjected to multiphysics loads. It is optimized for use cases in aerospace, defense, space, and advanced mobility systems.
Cognitive Design is an advanced design optimization software that enhances part performance. It incorporates production constraints directly into the design phase, ensuring efficiency. This allows design engineers to streamline workflows and reduce development time.
Cognitive Design is tailored for design engineers in large and medium-sized industrial companies. It is particularly beneficial for sectors like aerospace, automotive, defense, and space. The software addresses the unique challenges faced in these industries.
The software uses an implicit modeling engine to generate and optimize designs rapidly. By factoring in manufacturing constraints, it ensures that designs are feasible and efficient. This process minimizes the risk of failure during production.
Cognitive Design significantly reduces development time and enhances agility in the design process. It allows for quick iterations and optimizations, keeping your projects on track. By integrating manufacturing constraints early, it helps maintain competitiveness.
While Cognitive Design is user-friendly, we offer comprehensive training to maximize its potential. Our support team is available to assist with onboarding and any questions. This ensures that users can leverage the software effectively.
Request a demo to see how Cognitive Design by CDS can revolutionize your engineering workflow