Simulation-based optimisation techniques have been continually developing within the industrial environment for over 25 years. They have, however, remained a relatively under-utilised technique when compared to other CAE techniques such as the Finite Element Method. In more recent years, legislative requirements such as C02 emissions in the Automotive sector have driven industry to find solutions to achieving significant mass reduction. This recent push towards light-weighting to improve efficiency and reduce material cost has come at a time when computer processing speeds and memory capacities have improved such that many simple optimisation problems can now be solved on local workstations, and not high performance computing clusters.
When this is combined with the fact that additive manufacturing processes are becoming more and more accessible, there has been a real upsurge in the use and popularity of topology optimisation and simulation-based optimisation methods more generally. One of the key factors in the successful industry wide acceptance of optimisation into the development process is its integration into existing tools and practices. This acceptance of optimisation into the development process is its integration into existing tools and practices. This acceptance and adoption is driven by both engineering companies, and the CAD/CAE vendors recognising the opportunities available. This recognition has led to the release of a number of optimisation tools over the last 5 years offering simpler, more accessible optimisation capabilities to a wider audience. While the larger OEM’s have been conducting simulation-based optimisation for many years, and will be pushing the limits of what is possible in optimisation, SME’s and companies who don’t have a significant software simulation budget have been able to enter into this arena and start to see the benefits of using simulation-based optimisation during their design process. Simulation-based optimisation techniques have been continually developing within the industrial environment for over 25 years. They have, however, remained a relatively under-utilised technique when compared to other CAE techniques such as the Finite Element Method. In more recent years, legislative requirements such as C02 emissions in the Automotive sector have driven industry to find solutions to achieving significant mass reduction.
This recent push towards light-weighting to improve efficiency and reduce material cost has come at a time when computer processing speeds and memory capacities have improved such that many simple optimisation problems can now be solved on local workstations, and not high performance computing clusters. When this is combined with the fact that additive manufacturing processes are becoming more and more accessible, there has been a real upsurge in the use and popularity of topology optimisation and simulation-based optimisation methods more generally.
One of the key factors in the successful industry wide acceptance of optimisation into the development process is its integration into existing tools and practices. This acceptance of optimisation into the development process is its integration into existing tools and practices. This acceptance and adoption is driven by both engineering companies, and the CAD/CAE vendors recognising the opportunities available. This recognition has led to the release of a number of optimisation tools over the last 5 years offering simpler, more accessible optimisation capabilities to a wider audience.
While the larger OEM’s have been conducting simulation-based optimisation for many years, and will be pushing the limits of what is possible in optimisation, SME’s and companies who don’t have a significant software simulation budget have been able to enter into this arena and start to see the benefits of using simulation-based optimisation during their design process.
This presentation will look at four recent case studies where simulation-based optimisation has added real value to the design process and ultimately to the final designs generated. The case studies presented were conducted with a mixture of well-established designs, analysis and optimisation tools, demonstrating the proliferation of optimisation technology throughout modern engineering. The studies also demonstrate the applicability of simulation based optimisation to a range of manufacturing techniques, from traditional fabrication techniques to the latest additive manufacturing methods.
1. Case Study 1 – HITACHI Cantilever Pedestal
The Hitachi cantilever pedestal was developed using topology optimisation during a recent train seat design project conducted by GRM Consulting. The train seat was developed from concept to production design usign CAE led design process. Dynamic assessments for crash-worthiness were carried out using LS-DYNA, while optimisation methods such as sizing and topology were carried out using VR&D Genesis. Utilising optimisation throughout the design process meant that it was possible to start with a blank sheet, without any carry over, or any preconceptions about the potential design. The pedestal is a great example of simulation-based optimisation in action because it was used throughout the design process. Topology optimisation was used as a brainstorming tool to define the key load paths before an initial design had been proposed. This meant the design could be led by its core functions, and all the was required was a design envelope and a comprehensive list of performance requirements. In this case abuse, fatigue, and static loads extracted from the LS-DYNA crash simulations, were applied to the seat, with the objective of reducing the mass and increasing the first mode as much as possible, while meeting the other performance criteria.
The topology results were used by the design team to generate their first concepts of how the pedestal should look. The FE crash model was then updated with the latest design to verify performance, and allow freash loads to be extracted for re-applying in more detailed optimisation conducted on the mature design. The design was interpreted into a feasible folded sheet metal design based on the topology results, and then optimised further using sizing, to determine the optimum thickness of the panels, and topology to determine the ideal locations to put laser cut holes. This seat represents the cutting redge of technology in the rail industry and so far 30 seats have been manufactured as part of a Hitachi showcase on light-weight design.
2. Case Study 2 – PILBEAM Upright Top
The second case study to be discussed involved the design and development through optimisation of an upright top for a Pilbeam hill climb race car. The processes involved in delivering the successful design were very similar to those required for the train seat pedestal described above. It all starts with the definition of a package space. Then the load cases were applied to the package space model, in this case a conering left, conering right, braking, and a kerb strike abuse event were all applied as load cases to the package space model. A topology optimisation was then run with the objective of minimising the mass, while meeting the strength and stiffness performance requirements for each load case. As with the pedestal, the initial concept design was generated based on the software and the rapid generation of the key load paths. The topology optimisation result was the interpreted into a feasible design for manufacture and verification by simulation. In this particular example there were local stress hotspots on one of the corners so shape optimisation studies delivered a 30% mass saving over the baseline design, and the design was again generated in a short product development lifecycle because of the use of topology as a brainstorming tool.
3. Case Study 3 – ROADSPORTS Z3 Rear Wing Stay
The BMW Z3 rear wing stay was conducted as a development study using a Topology optimisation tool integrated into the SolidWorks user interface. In this particular example the third evolution of a rear wing stay for a BMW Z3 is optimisaed for stiffness performance. An available package space for the wing stay was defined and aerodynamic forces based on the wing geometry, car speed and drag were applied in SolidWorks simulation. Topology optimisation was then conducted in order to rapidly identify the optimal load paths and material layout to support the wing under the aerodynamic loads.
The topology results were then interpreted into a feasible design by GRM’s engineers, and subsequently verified for performance in SolidWorks simulation. This part was subsequntly verified for performance in SolidWorks simulation. This part was subsequently laser cut out of standard thickness aluminium sheet sections, and raced in the 750 Motorclub Roadsports championship throughout 2016. This particular case study really highlights the accessibility of optimisation to the modern day engineer compared to even 5 years ago. This entire process was conducted in SolidWorks CAD software, using the simulation module for the FEA, and GRM’s propriety optimisation code TruForm for the optimisation. Total time spent on this design process from package space and load definition to design interpretation, including solve was only 3 hours.
4. Case Study 4 – BCIT Downhill Bike Crown
The fourth case study takes a look at a project conducted by the British Columbia Institute of Technology (BCIT) to design an integrated crown and stem for a downhill mountain bike. The aims of the project were to eliminate the four bolts holding the stem onto the crown in the current design, and investigate a lighter geometry for the crown that was stiffer and stronger using titanium instead of aluminium. As with the BMW Z3 rear wing stay all the design optimisation work was conducted within the SolidWorks design environment. BCIT generated a package space, for the required loading. The topology optimisation result was used to develop concept designs, with two concept designs generated for manufacture. One design was developed for CNC machining using aluminium, while the other was developed to be 3D printed in Titanium. Both interupted designs presented a significant weight saving compared to the baseline, however the lighter Titanium 3d printed design was 30% lighter while improving the stiffness and strength performance.
