Automating the Design Optimization of Vehicle Structures

structures, parametric design and finite element analysis are common tools for simulating structural behavior of systems under static and quasi-static loading. While these tools provide significant benefits over physical experimentation, cumbersome to set up and this time-consuming setup may need to be repeated many times while iterating on a design. The designers would therefore benefit from automating this design and analysis process so that they can explore the design space more efficiently or obtain higher performance design alternatives. To take full advantage of the benefits of this automation, it important to make the process as quick and easy as possible. Otherwise, the cost of setting up the automated analysis may exceed the benefits obtained during design exploration and iteration. This research introduces a template-based approach to the automation of structural design and analysis that simplifies the setup process for certain classes of design problems. The platform for this automation is the process integration and design optimization tool, modeFRONTIER. Through several case studies in the area of vehicle structure analysis and design, it will be demonstrated how templates can significantly reduce the time and effort needed to frame complex structural design problems

Manufacturability-Driven Multi-Component Topology Optimization Of Thin-Walled Structures Based On A Level Set Method

Thin-walled structures (TWS) are suitable for lightweight, load-bearing enclosures with various external geometries with internal reinforcements. Thin-walled structures find application in automobiles, aircrafts, ships, and industrial facilities. Past research in the field of structural design optimization have been done to make single-piece thin-walled structures less costly, lighter and of better performance. The primary drawback of these research is that complex structures are scarcely manufactured as a single piece, and this has made the optimization of single-piece structures to be of little industrial relevance. The goal of this dissertation is to develop a computational method for simultaneous design and partitioning of assemblies made of thin-walled components, driven by component manufacturability. First, the conventional level set function for monolithic topology optimization based on a signed distance function is extended to realize a simple representation of monolithic thin-walled structures with uniform thickness, by taking advantage of the signed-distance property. Second, a new multi-domain representation within a level set, inspired by level-set methods for multi-material topology optimization, is introduced to model multiple components, where the additional level sets specify partitioning of the level set for a monolithic thin walled structures. Finally, the geometric constraints imposed by a manufacturing process for thin-walled components, sheet metal stamping as an example, are introduced to formulate the manufacturability-driven, multi-component topology optimization of thin-walled structures. The optimization problem is formulated as continuous optimization with respect of the level set parameters that specify overall structural geometry and its partitioning, which can be solved efficiently by gradient-based optimization algorithms. A few examples inspired by the sheet metal structures for automotive applications demonstrated the effectiveness of the new formulation to automatically design thin-walled structures made of multiple component each of which satisfies process-specific geometric constraint for component manufacturing. The conventional approach for design and partitioning is a two-step process in which the optimization of the single-piece geometry is first carried out, followed by the decomposition of the optimized single-piece geometry to refine part boundaries and joint configurations. Since the outcome of the second step largely depend on the first step, the two-step approach is likely to yield suboptimal solution. Although the improvement resulting from the new formulation of simultaneous design and partitioning cannot be quantify, it is expected to bring about improvement when joint modeling is implemented. This dissertation advances the state of the art of the simultaneous designing and partitioning of thin-walled structures driven by manufacturability. While the dissertation focuses on the auto-body application, it is expected that the methodology will be applicable to other domains of thin-walled structures.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155229/1/sayinde_1.pd

Gradient-Based Multi-Component Topology Optimization for Manufacturability

Topology optimization is a method where the distribution of materials within a design domain is optimized for a structural performance. Since the geometry is represented non-parametrically, it facilitates innovative designs through the exploration of arbitrary shapes. Due to its unconstrained exploration, however, topology optimization often generates impractical designs with features that prevent economical manufacturing, e.g., complex perimeters and many holes. Above all, existing topology optimization methods assume that the optimized structure will be made as a single piece. However, structures are usually not monolithic (i.e., single-piece), but assemblies of multiple components, e.g., cars, airplanes, or even chairs. It is mainly because producing multiple components with simple geometries is often less expensive (i.e., better manufacturability) than producing a large single-piece part with complex geometries, even with the additional cost of assembly. This dissertation discussed a topology optimization method for designing structures assembled from components, each built by a certain manufacturing process, termed the MTO. The prior art of MTO used discrete formulations solved by genetic algorithms. To overcome the high computational cost associated with non-gradient heuristic optimization, this dissertation proposed a continuously relaxed gradient-based formulation for MTO. The proposed formulation was demonstrated with three manufacturing processes. For the sheet metal stamping process, by modeling stamping die cost manufacturing constraints and assuming resistant spot welding joints, the simultaneous optimization of base topology and component decomposition was, for the first time, attained using an efficient gradient-based optimization algorithm based on design sensitivities. For the composite manufacturing process, a cube-to-simplex projection and penalization method was proposed to handle the membership unity requirement. With the multi-component concept, a unique structural design solution for economical composite manufacturing was achieved. The component-wise anisotropic material orientation design for topology optimization was presented without prescribing a set of alternative discrete angles as required by most existing material orientation methods. For the additive manufacturing process, the MTO method enabled the design of additively manufactured structures larger than the printer's build volume. By modeling manufacturing constraints on the build volume limit and elimination of enclosed holes, the optimized structure was an assembly of multiple components, each produced by a powder bed additive manufacturing machine. The first reported 3D example of MTO was presented.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145989/1/yuqingz_1.pd

Multi-Objective structural optimization of repairs of blisk blades

Modern manufacturing technologies offer multiple options to extend the service life of expensive jet engine components through repairs. In this context, the repair processes of blade-integrated disks (blisks) are of particular interest, as the complex design makes replacement of this part very costly. However, currently, repairs of blisks are mainly done manually and repair design decisions still rely on the expertise of maintenance technicians. From a scientific perspective, these subjective, experience-based decisions are a major drawback, as today’s computational methods allow for systematic analysis and evaluation of design alternatives. The present doctoral thesis contributes to the decision-making process related to the repair of blisk blades by blending and patching by providing an engineering optimization framework and simulation routines for structural assessment of different repair designs. First, an object-oriented optimization framework is developed that is ideally suited to address engineering optimization problems such as blisk repair optimization. The design of the software architecture is chosen to achieve a high degree of flexibility and modularity. In particular, the framework provides a unified interface for global and local derivative-free optimization algorithms and custom engineering optimization problems. Thereby, optimization of single- as well as multi-objective problems is supported. The broad applicability of the framework in engineering optimization is demonstrated using examples from wind energy research. Furthermore, the optimization framework forms a suitable environment for structural multi-objective optimization of blend and patch repairs. The second part of this thesis is devoted to the application of the optimization framework to blend repairs of a compressor blisk. The geometry of the removed blade part and the resulting blend is parameterized by three geometric design variables. The two objectives of the optimization correspond to two modal criteria, because especially the vibration behavior of blades is affected by this kind of geometric modification. To check if frequency requirements are harmed by the repair the first objective reflects the deviation of the natural frequencies of the repaired blade to the natural frequencies of the nominal blade. The second objective considers resonance conditions by evaluating the proximity of natural frequencies to excitation frequencies. Pareto optimal repair designs are found by solving the derived optimization problem using appropriate structural mechanics models of a blade sector and employing the developed optimization framework. By analyzing the optimal blend shapes for two different damage patterns, it is shown that the characteristics of Pareto frontiers, like the occurrence of discontinuities, are damage-specific. Therefore, it is concluded that design decisions on blend repairs have to be made on a case-by-case basis. The third part of this thesis is concerned with the multi-objective optimization of patch repairs. While blend repairs change the blade geometry, patch repairs restore the original blade contour. In terms of structural integrity, the most significant modification due to patching is hence associated with the welding process to join patch and blade. The remaining residual stresses, affect the strength of the repaired blade, are therefore the most critical aspect of patch repairs. Utilizing the engineering optimization framework and the parametric simulation model, a multi-objective optimization problem is solved considering the length of the weld and the fatigue strength of the repaired blade. In addition to fatigue strength properties, the weld length is selected as an optimization goal, since the manufacturing effort of the high-tech repair is of practical importance. Pareto optimal repair designs are presented for a damage pattern at the leading edge. The optimization results are further complemented by subsequent thermal and mechanical simulations of the welding and heat treatment process. Different patch geometries are classified from the Pareto optimal solutions. Depending on the preferences in terms of weld length and the High-Cycle Fatigue strength of different load cases, short or long patches are to be used. In addition, the results show that some potential patch designs are not optimal in any case, and therefore can be completely excluded. Finally, the benefits of the unified interface of the engineering optimization framework are emphasized. Different optimization settings of a patch repair optimization are presented and compared utilizing the hypervolume metric. Concluding remarks on the potential of computational methods for improved repair design and an outlook on future maintenance of blisks complete this work.DFG/SFB 871/119 193 472./E

Global Estimation Methodology for Wave Adaptation Modular Vessel Dynamics Using a Genetic Algorithm

Determining parameters for a system model for marine vessels becomes more difficult as the model is made more complex. Work has been done to determine the equations of motion, but not to fully define how to estimate all of the system parameters. This work utilizes a global optimization methodology for estimating the system parameters using a genetic algorithm. The optimizer uses training data sets created from a set of ship maneuvering standards to minimize the error in the 3 degree-of-freedom equations of motion. The model has been optimized using a “No Surge-Yaw” model (minimal surge coupling) and a “Full” model (all states have coupling effects to each other) to determine how well each model can be estimated. The “No Surge-Yaw” model had the best results with making a working marine vessel model. The “Full” model was difficult to optimize due to the additional parameters that had unknown, nonlinear constraints. The “No Surge-Yaw” model was compared to linearized, no coupling version of the model that is commonly used. The linearized model vastly overestimated the results in sway and yaw rate motion while the “No Surge-Yaw” captured the expected coupling dynamics that do exist. Overall, the results of this methodology did generate a set of working marine vessel parameters for an unknown, coupled-state dynamic model

Topology Optimization Applications on Engineering Structures

Over the years, several optimization techniques were widely used to find the optimum shape and size of engineering structures (trusses, frames, etc.) under different constraints (stress, displacement, buckling instability, kinematic stability, and natural frequency). But, most of them require continuous data set where, on the other hand, topology optimization (TO) can handle also discrete ones. Topology optimization has also allowed radical changes in geometry which concludes better designs. So, many researchers have studied on topology optimization by developing/using different methodologies. This study aims to classify these studies considering used methods and present new emerging application areas. It is believed that researchers will easily find the related studies with their work

PHYSICS-BASED SHAPE MORPHING AND PACKING FOR LAYOUT DESIGN

The packing problem, also named layout design, has found wide applications in the mechanical engineering field. In most cases, the shapes of the objects do not change during the packing process. However, in some applications such as vehicle layout design, shape morphing may be required for some specific components (such as water and fuel reservoirs). The challenge is to fit a component of sufficient size in the available space in a crowded environment (such as the vehicle under-hood) while optimizing the overall performance objectives of the vehicle and improving design efficiency. This work is focused on incorporating component shape design into the layout design process, i.e. finding the optimal locations and orientations of all the components within a specified volume, as well as the suitable shapes of selected ones. The first major research issue is to identify how to efficiently and accurately morph the shapes of components respecting the functional constraints. Morphing methods depend on the geometrical representation of the components. The traditional parametric representation may lend itself easily to modification, but it relies on assumption that the final approximate shape of the object is known, and therefore, the morphing freedom is very limited. To morph objects whose shape can be changed arbitrarily in layout design, a mesh based morphing method based on a mass-spring physical model is developed. For this method, there is no need to explicitly specify the deformations and the shape morphing freedom is not confined. The second research issue is how to incorporate component shape design into a layout design process. Handling the complete problem at once may be beyond our reach,therefore decomposition and multilevel approaches are used. At the system level, a genetic algorithm (GA) is applied to find the positions and orientations of the objects, while at the sub-system or component level, morphing is accomplished for select components. Although different packing applications may have different objectives and constraints, they all share some common issues. These include CAD model preprocessing for packing purpose, data format translation during the packing process if performance evaluation and morphing use different representation methods, efficiency of collision detection methods, etc. These common issues are all brought together under the framework of a general methodology for layout design with shape morphing. Finally, practical examples of vehicle under-hood/underbody layout design with the mass-spring physical model based shape morphing are demonstrated to illustrate the proposed approach before concluding and proposing continuing work