Sustainable Design with Roundtrip Optimization

Sustainable Design with Roundtrip Optimization

By Karl Kueres

Simulation on the 3DEXPERIENCE Platform

Design for sustainability is a key consideration for producing the optimal product. Engineers often use sophisticated simulation tools to assess all aspects of sustainability, such as weight, performance efficiency and waste reduction. After multiple changes and simulation iterations, the picture starts to emerge.

Unfortunately, legacy tools rely on rudimentary file-based data exchanges to support this iterative process, leaving the engineers to spend a significant portion of their time managing the data exchange.

Such a restriction severely limits the number of design points that can be investigated within a given design cycle, often leading to released designs that are far from optimum. Optimal designs are lighter, last longer and can be easily recycled. Lighter designs, not only consume less material but also result in more efficient performance of the overall system. For example, a lighter vehicle has higher chances of being more fuel efficient, and therefore more sustainable.

What if engineers could just pick the parameters to be changed and let the system optimize the design considering all aspects of sustainability?

This requires a new level of interoperability that eliminates the silos between modelling and simulation tools. This platform-based roundtrip optimization helps achieve faster design convergence and eliminates non-value-added effort related to data transfer and translation.

Predicting the performance of a component or system is critical in making informed decisions and achieving an optimum design. Modelling and simulation allow users to investigate various scenarios before selecting the best design, enabling the prediction of key performance indicators for a given design:

  • Will it survive under critical loads?
  • Will it fit?
  • Can it be manufactured in a sustainable manner?
  • How long will it last?
  • How much will it cost?
  • How heavy is it?

Such models clarify how the product will work. To create accurate models, many questions must be answered:

  • What loading will it be subjected to?
  • What form will it take? What kind of fit is required?
  • What are the potential modes of failure?
  • What material is appropriate? How much will it cost?

How does each design parameter affect the behaviour?

SCENARIO: Function Drives Fit and Form

The following scenario — a simple example of a link component — illustrates how users can identify design parameters and study the effect of changing values on the structural performance of a component.  

For this case we will study the effects of varying a single parameter (the pocket depth shown in Figure 1) on the structural performance.


Scenario Considerations:

  1. Designing the most optimal form requires consideration of the maximum allowable stress, manufacturing costs and other considerations.
  2. In the example, the link is limited to a maximum allowable stress of 100MPa. The design parameter — pocket depth — is optimized to minimize weight.
  3. Additional target to minimize deformation to within a maximum of 0.05mm.

The following video illustrates this optimization process:

Figure 2 compares the difference between a traditional file-based PLM environment with electronic documents to the data-driven, model-based approach of the 3DEXPERIENCE platform. It shows how to design the optimum part in the most cost-effective and time-efficient way possible.


Each step is outlined to show it is possible to achieve an optimum design with SIMULIA on the 3DEXPERIENCE platform.

Karl Kueres is a 3DEXPERIENCE engagement manager in the SIMULIA Growth Team, providing technical solution support to various industries in their adoption of the 3DEXPERIENCE Platform. He joined HKS (later Abaqus, which was acquired in 2005 by Dassault Systèmes) in 2002 after graduating from Cambridge University with a master’s degree in engineering. Karl spent eight years working in the UK technical team supporting the Abaqus suite of products, during which time he spent several months providing onsite support at major automotive and aerospace clients.

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