Technical Papers

J.E. Bischoff, E.S. Drexler, A.J. Slifka, and C.N. McCowan
Computer Methods in Biomechanics and Biomedical Engineering, Volume 12, Issue 3 June 2009, pp. 353-369

Determination of material parameters for soft tissue frequently involves regression of material parameters for nonlinear, anisotropic constitutive models against experimental data from heterogeneous tests. Here, parameter estimation based on membrane inflation is considered. A four parameter nonlinear, anisotropic hyperelastic strain energy function was used to model the material, in which the parameters are cast in terms of key response features. The experiment was simulated using finite element (FE) analysis in order to predict the experimental measurements of pressure versus profile strain. Material parameter regression was automated using inverse FE analysis; parameter values were updated by use of both local and global techniques, and the ability of these techniques to efficiently converge to a best case was examined. This approach provides a framework in which additional experimental data, including surface strain measurements or local structural information, may be incorporated in order to quantify heterogeneous nonlinear material properties.
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Optimization of Engineering Systems
M.H. Rademacher, R.C. Averill, and R.S. Sidhu
Inverse Problems Symposium 2009, East Lansing, MI USA

Engineers are forced to design products that are higher performing and more complex due to increasing market pressure. This results in the need for more complex simulation models that take into account nonlinear phenomena. In these models, gradients are often unavailable analytically, so optimization must be performed using methods that do not require gradients. In this study, several problems are presented where the system was optimized using a new hybrid optimization strategy that does not need gradients. This strategy was applied to three problems. The first was the design of a chemical process, where a minimum input of energy was desired. The second application was in the design of an automotive front suspension system where toe and camber curves needed to be matched. The third and final problem presented was the design of a rubber automotive engine mount, where a nonlinear stiffness curve was matched.
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Design optimization of progressively crushing rails
Nate Chase, Ronald C. Averill, and Ranny Sidhu
SAE World Congress and Exhibition, April 2009

To increase robustness of the crush mode and to decrease repair costs after a crash, it is desirable for front and rear rails in an automotive vehicle to crush progressively. In this study, a new strategy is investigated to achieve progressively crushing designs during an automated design optimization study using HEEDS Professional. This strategy employs the definition of crush zones along the length of a rail, and a design optimization problem statement that encourages maximum energy absorption in any particular crush zone to occur prior to any energy absorption in rearward zones. It is demonstrated that high performing designs with progressive crush can be obtained using the proposed approach.
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Optimization methods for the tube hydroforming process applied to advanced high-strength steels with experimental verification
Nader Abedrabbo, Michael Worswick, Robert Mayer, and Isadora van Riemsdijk
Journal of Materials Processing Technology, Volume 209, Issue 1, 1 January 2009, pp. 110-123.

In this paper, an optimization method linked with the finite element method is presented for developing forming parameters of the tube hydroforming (THF) process for several advanced high-strength steel (AHSS) materials. The goal of this research was to maximize formability by identifying the optimal internal hydraulic pressure and end-feed rate, while satisfying the failure limits defined by the forming limit diagram (FLD). The optimization software HEEDS was used in combinaton with the nonlinear structural finite element code LS-DYNA to carry out the investigation.
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Ligament property optimization within a virtual biomechanical knee
Jeffrey E. Bischoff, Eik Siggelkow, Daniel Sieber, Mariana Kersch, Heidi Ploeg, and Marc Münchinger
Proceedings of the ASME Summer Bioengineering Conference (SBC2008)

The goal of this work was to utilize inverse finite element (FE) analysis to determine material parameters of ligaments in a specimen-specific model of the knee, using both local and global optimization algorithms. Several optimization algorithms were considered: local algorithms LSQNONLIN and FMINCON in Matlab, quadratic programming (QP) in HEEDS, and the hybrid local/global proprietary HEEDS algorithm, SHERPA.

Impact of time-dependency on long-term material testing and modeling of polyethylene
Jeffrey E. Bischoff
Mechanics of Time-Dependent Materials, Volume 12, Number 3, September 2008

Ultra-high molecular weight polyethylene (UHMWPE) has an important role in orthopaedic implants because of its favorable properties as an articulating surface. UHMWPE component testing often focuses on measuring the long-term fatigue or wear response of the material that could be realized during many years of use. However, the impact of time-dependent properties of UHMWPE on such tests is not well characterized. In particular, altering the frequency of loading and allowing for material creep or relaxation can significantly alter the stress/strain state of the material, and therefore affect long-term mechanical properties (e.g. wear, fatigue) that are dependent on the constitutive state. The goal of this work was to use advanced, validated material modeling of UHMPWE that incorporated time-dependent properties to explore the effects of frequency and rest time on the mechanical response of UHMWPE. Various approaches could be used for the parameter regression including gradient-based techniques (Bischoff 2007) and simplex techniques (Bergström et al. 2004). The optimization software HEEDS 5.1 was used in this study. This software affords use of the proprietary SHERPA algorithm, which incorporates both local and global optimization techniques, as well as standard gradient-based approaches.
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Structured synthesis of MEMS using evolutionary approaches
Zhun Fan, Jiachuan Wang, Sofiane Achiche, Erik Goodman, and Ronald Rosenberg
Applied Soft Computing 8 (2008) 579–589

This paper discusses the hierarchy involved in a typical MEMS design and how evolutionary approaches can be used to automate the hierarchical synthesis process for MEMS. The paper first introduces the flow of a structured MEMS design process and emphasizes that systemlevel, lumped-parameter model synthesis is the first step of the MEMS synthesis process. At the system level, an approach combining bond graphs and genetic programming can lead to satisfactory design candidates as system-level models that meet the predefined behavioral specifications for designers to trade off. Then at the physical layout synthesis level, the selection of geometric parameters for component devices and other design variables is formulated as a constrained optimization problem and addressed using a constrained genetic algorithm approach. A multiple-resonator microsystem design is used to illustrate the integrated design automation idea using these evolutionary approaches.
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Material Layout Optimization of Natural Fiber Composite Cellular Panels
Rigoberto Burgueño and Christina Isaac
Proceedings of the 6th International Conference on Computation of Shell and Spatial Structures, IASS-IACM 2008

In spite of their environmental appeal, the use of natural fiber composites (biocomposites) for load-bearing applications has been restricted because of their low mechanical properties. However, the performance of biocomposite components can be overcome by using optimized designs. A finite parametric approach to material layout optimization was investigated and implemented to improve the performance of cellular structural components made from biocomposites. Unlike traditional topology optimization, the presented approach leads to optimized material layouts while permitting the use of multiple objectives and constraints. The optimization procedure was validated using benchmark topology problems. Small-scale component testing was conducted to evaluate the structural performance and manufacturing feasibility of the optimized solutions.
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Forming of AA5182-O and AA5754-O at elevated temperatures using coupled thermo-mechanical finite element models  
Nader Abedrabbo, Farhang Pourboghrat, and John Carsley
International Journal of Plasticity, Volume 23, Issue 5, May 2007, pp. 841-875

A temperature-dependent anisotropic material model was developed for two aluminum alloys AA5182-O and AA5754-O and their anisotropy parameters were established. A coupled thermo-mechanical finite element analysis of the forming process was then performed for the temperature range 25–260 °C (77–500 °F) at different strain rates. As a design tool, the Genetic Algorithm optimization program HEEDS was linked with the developed thermo-mechanical models and used to numerically predict the “optimum” set of temperatures that would generate the maximum formability for the two materials in the pure stretch experiments.
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Nonlinear Material Characterization using HEEDS and Abaqus
M.H. Rademacher, R.C. Averill, and R. S. Sidhu
Inverse Problems Symposium 2007, East Lansing, Michigan, USA

In this study, a new hybrid optimization strategy is discussed and applied to two material characterization problems: rate-sensitive hyper-elastic polymers and rubbers used in automotive engine mount applications.
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A Process of Decoupling and Developing Body Structure for Safety Performance
John M. Madakacherry, Dr. David Eby, Martin B. Isaac, Dr. Akbar Farahani, Dr. Charles A. Bruggeman, and Dr. Ron. C. Averill
Proceedings of the 5th European LS-DYNA Users Conference

A process for decoupling and developing an optimized automotive body structure for enhanced safety performance has been developed, implemented, and verified. The approach facilitates the development of a load path strategy and decoupling of a complex system into structural components or sub-systems, thus allowing for high-fidelty design optimization of a sub-system to meet desired performance targets. In the present study, the proposed approach was used to design a hydroformed motor compartment rail to meet the NCAP front crash and 40 mph 40% offset deformable barrier impact performance requirements, resulting in a 20% mass reduction and improved overall performance compared to a baseline design.  The decomposed subsets were developed through a combination of component-level DYNA3D analyses, linear dynamic, linear static analyses, and Genetic Algorithm techniques using HEEDS.
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Improved Vehicle Crashworthiness via Shape Optimization
Ranny S. Sidhu, Johanna E. Burgueño, Ron C. Averill, and Erik D. Goodman
2003 ASME International Mechanical Engineering Congress and Exposition, Washington, D.C.

While many design optimization approaches are limited to a small number of continuous design variables, the approach described here leads to a productive search over hundreds of variables at a time. This capability has been implemented in HEEDS (Hierarchical Evolutionary Engineering Design System) Professional. HEEDS was applied to two crashworthiness problems using various search agents to evaluate potential designs with different design variable representations and performance measures.
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Shape Optimization for Improved Vehicle Safety and Reliability
R. Sidhu, J. Burgueño, R.C. Averill, and E.D. Goodman
2003 Abaqus Users' Conference, Munich, Germany

HEEDS design optimization software was used to perform shape optimization of an automotive lower compartment rail and a torque arm bracket. A HEEDS mesh generator was used to model the rail, while Abaqus/CAE was used within the HEEDS environment to create new models for the torque arm. Abaqus solvers were used to evaluate the performance of each potential design.
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Design Optimization of Hydroformed Crashworthy Automotive Body Structures
Akbar Farahani, Ronald C. Averill, and Ranny Sidhu
2003 CAD-FEM Users' Meeting, Berlin, Postdam, Germany.

The design optimization approach described here leads to a productive search over hundreds of variables at a time. This capability has been implemented in HEEDS Professional, which uses multiple autonomous agents to hierarchically decompose a problem into subsets with highly decomposed overlapped relationships. Decomposition is effected by using different numbers of design variables, different levels of design variable discretization, and/or other problem-specific divide-and-conquer rules. HEEDS combines evolutionary search algorithms with local optimization techniques. Using explicit finite element codes such as LS-DYNA as the finite element solver within the HEEDS optimization environment, this process has been applied to several automotive rail designs, resulting in significant gains in performance in addition to substantial reductions in mass compared to baseline rails designed by experienced engineers. Two example applications of this method are described herein.
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