Custom engineering workflow: From CAD to optimized design

The engineering process begins once we receive the CAD model of the part or system to be analyzed. Regardless of whether the goal is to assess structural strength, fluid flow and/or heat transfer, we take care of adapting the CAD for simulation.

Our first step is to refine the geometry, ensuring it is optimized for computational analysis. This may involve simplifying unnecessary details, closing small gaps, or making adjustments that improve the accuracy of the results. These refinements ensure that the simulation process runs smoothly and provides meaningful insights into how the design will perform under real-world conditions.

We work closely with our customers throughout this process, ensuring that each step aligns with their expectations. Follow-ups and milestones are established to maintain transparency, allowing adjustments to be made whenever necessary, thus reducing costly design setbacks.

Once the CAD model is ready, it is converted into a mesh—a network of small elements (or cells in CFD) that enable the simulation to calculate how forces, fluids, or heat interact with the part. The quality of this mesh directly impacts the precision of the results.

A well-structured mesh captures critical details while maintaining computational efficiency. If the elements are too large, important features may be overlooked; if they are too small, computation time can increase significantly. Our approach ensures the right balance, delivering accurate and cost-effective simulations without unnecessary complexity.

Depending on the computational requirements, we conduct simulations either on-premises or using our high-performance cloud computing provider (CFD FEA Service). This flexibility allows us to optimize resources according to the size and complexity of each simulation. If there are any concerns regarding information confidentiality, we can implement customized privacy agreements to meet the client’s needs.

After meshing, the next step is to define the physical conditions under which the model will be tested. This includes applying real-world factors such as:

• Material properties (e.g., yield stress, heat capacity, fluid viscosity)
• Forces and pressures (e.g., static loads, impact forces, fluid flow rates)
• Environmental conditions (e.g., operating temperature ranges, constraints, relative movement)

A crucial aspect of this stage is defining boundary conditions, which determine how the system interacts with its surroundings. In solid mechanics (FEM), these include fixed supports, contact interfaces, and distributed loads. In fluid dynamics (CFD), this involves specifying inlets, outlets, wall conditions, and heat exchange surfaces. Properly defining boundary conditions is essential for ensuring reliable results.

The accuracy of a simulation significantly depends on having precise material and fluid properties. In solid mechanics, this often includes:

• Stress-strain data: Defines how a material deforms under loading.
• Rate-dependent behavior: Important for materials that change properties based on loading speed (e.g., viscoplastic materials).
• Fatigue properties: Essential for predicting the long-term performance of materials subjected to cyclic loads.

For fluids, key properties characterize behavior under different operating conditions. For example, in a heat exchange liquid scenario, vital parameters include:

• Density (ρ): Affects buoyancy and inertial forces.
• Viscosity (μ): Influences flow resistance and turbulent flow development.
• Specific heat capacity (Cp): Determines how much energy is required to raise the fluid’s temperature, impacting thermal performance.
• Thermal conductivity (k): Governs how efficiently heat is transferred within the fluid.

With everything set up, the simulation is executed to generate numerical results. However, engineering analysis is inherently iterative. In advanced cases, issues such as numerical instability, divergence, or unexpectedly high local stresses may arise, requiring refinement of the mesh or adjustment of solver parameters. We may modify need to adapt material models (e.g., incorporating strain-rate dependence) or adapt turbulence models for more accurate CFD predictions.

Debugging often involves reviewing convergence plots, checking energy balances, or comparing intermediate results against simplified analytical estimates. This refinement process ensures that results are both robust and actionable for design decisions.

Ideally, any virtual model should be validated by comparing its outcomes with experimental data. This correlation can refine numerical parameters (e.g., friction coefficients, boundary layer thicknesses), improving the predictive accuracy of the model. However, experimental data cannot always be provided, in that case our domain expertise allows us to select appropriate assumptions and reference cases. In such scenarios, the analysis focuses on relative comparisons, highlighting how design variations impact the system’s overall performance.

The final stage is where real value is unlocked—using the results to improve the design. By applying advanced optimization techniques, we systematically reduce weight, increase efficiency, or improve durability. These iterations may involve refining geometry, adjusting material selection, or modifying operational parameters to enhance performance while maintaining safety and reliability.

By managing the entire engineering simulation workflow—from CAD adaptation to delivering data-driven insights—you can concentrate on your core project objectives while we handle complex simulations. Our advanced techniques, combined with your domain knowledge, ensure that each design iteration moves closer to optimal performance and cost-effectiveness.