Formula 1 cars epitomize the bleeding edge of innovation. Developing an F1 contender is a complex and expensive endeavor. Teams must follow strict technical regulations from a governing body (FIA) and physical testing at a track is expensive and limited to six days per year. To mitigate these limitations, all of F1’s teams have invested in simulation to develop and fine-tune their expensive machinery – worth between $12 and $15 million each.


Although F1 is an extreme example, the same trend is happening across all industries: Departments in charge of innovation rely heavily on science-based modeling and simulation to accelerate the innovation cycle and cut design costs. In this post, we will explore how science-based modeling and simulation are at the heart of modern product innovation.


Soaring Customer Expectations and Complex Requirements

In a turbulent economic phase such as the one we are currently experiencing, customer expectations shift as inflation rises, supply chain challenges persist, and environmental, social, and governance (ESG) considerations soar. Customers demand products with a reduced carbon footprint encompassing the latest innovations and a great overall user experience. They must fit budget constraints and be delivered on time. A pretty tall order.


While designers and engineers strive to imagine and deliver innovative products and experiences, this new market makes clear the difficult task of navigating different and often conflicting requirements to meet and exceed the customers’ expectations. It’s no surprise they often feel ill-equipped when faced with complex engineering decisions.


In a survey conducted by Tech-Clarity, 44% of respondents from a broad cross-section of industries said decisions affecting competitiveness have gotten harder. Why? Increased performance and quality requirements, shortened schedules, and a number of components were among the top factors given.


When faced with challenges throughout the engineering process, the majority of respondents said they’re relying heavily on two factors: personal experience (69%) and simulation (53%). When asked about the ideal way to solve challenges, respondents overwhelmingly said simulation.


Better together

To shorten time to market, deal with complexity, and achieve a competitive advantage, companies are relying on science-based modeling and simulation at all stages of the product lifecycle from product requirement to design and manufacturing to in‑use scenarios. As a result, they require less real-world prototyping and enjoy faster physical certification testing – ultimately getting more innovative products to market faster.


Science-based modeling and simulation are an integral part of the capabilities delivered by the 3DEXPERIENCE platform and rely on three fundamental characteristics: unified, multidisciplinary, and multi-scale.


  • Unified: Modeling and simulation are part of one unified environment and share a single source of truth. By embedding design and simulation together in the engineering process, stakeholders are empowered to use realistic simulation at the earliest stages of development, validating design performance, quickly assessing design alternatives, and executing refinements concurrently.
  • Multidisciplinary: Engineering teams must simulate complex behaviors and systems and capture the interaction of multiple physics to validate system performance. Simulation technologies to address different disciplines such as structures, fluids, electromagnetics, acoustics, etc. must be available and work together. The simulation must also extend to the manufacturing disciplines. By creating products and experiences in 3D, teams test and validate designs and simulate manufacturing virtually. Using simulation, the assembly setup is optimized in accordance with the manufacturing process and with robustness, weight, and cost constraints.
  • Multi-scale: Innovation is not restricted to a particular scale. Achieving the innovation demanded by the market requires 3D modeling and simulation technologies for any scale – from molecules at the nanoscale to aircraft to entire cities. For example, researchers and engineers must be able to understand the fundamental interactions underlying material properties at the smallest of scales and determine its behavior at the macro scale. At the other end of the scale spectrum, simulation greatly improves the design of complex, dynamic systems such as buildings, airports, and even cities and provides the ability to analyze resultant structure performance under in-service conditions in a multiscale aspect.


5 Benefits of an Integrated Approach

Let’s look at some of the benefits companies gain when they adopt science-based modeling and simulation as a foundational part of their innovation process:


  • Efficient simulation cycle. With simulation and modeling together in the same unified environment based on a single source of truth, teams get more efficient at simulation. If you change the model, you immediately cascade the changes to your simulation models. Reusable models, automatic meshing, and results shared in the same environment save both time and cost.
  • Faster potential validation of innovation. Teams can quickly assess the strengths and weaknesses of different concepts and combine high-performing aspects of different concepts tested into new designs. By having a model fully parametrized, you take advantage of simulation earlier in the process as teams rapidly explore the impact of any geometry parameter on the performance of the design.
  • Reduced physical prototyping and redesign costs. Having the ability to conduct a simulation in a virtual environment and test any number of options, allows you to reduce the number of physical prototypes built, compared to the traditional linear design-simulation approach, and ensure less failure during the actual physical testing.
  • Greater collaboration. Design and simulation capabilities are available from the same unified environment. Having a single representation of your project or product empowers all stakeholders to work on the same model and data, avoiding data duplication, data incompatibility, and version control issues.
  • Greater design continuity. Connecting multiple disciplines allows teams to develop and simulate complex scenarios, and connect products faster.


“With simulation and additive manufacturing, it takes around three to four months to create a train. It takes double that with the traditional approach and uses far more energy. We estimate that our clients can save around 30% in development and running costs. From ideation to production, we are much faster.”

Eric Bernadini, CEO of Extreme Analyses Engineering



Leading companies are already taking advantage of a science-based modeling and simulation approach one that is unified, multidisciplinary, and multi-scale and used at all stages of the product lifecycle from product design to manufacturing and in‑use scenarios.