Technical Papers

Erik Wendeberg
Master’s Thesis in the Automotive Engineering Programme
Department of Applied Mechanics
Division of Vehicle Engineering and Autonomous Systems
Vehicle Dynamics Group

Computer aided engineering is becoming an increasingly important tool in the automotive industry since it can reduce development time of new vehicles. However, in order to draw the same conclusions from test and simulation results it is important that the behaviour and characteristics of a simulation model match test data. Traditionally, to ensure that a suspension simulation model is accurate, it is correlated by a manual adjustment of the parameters in the model. This is time-consuming and error-prone. By automating the correlation process using a suitable optimization technique and a properly defined procedure, the process can be performed faster and the quality of the results can be improved since more parameters and objectives can be included. The aim of this study was to develop a well-defined correlation procedure, with minimal user input, that optimizes parameters in a suspension model so the behaviour of the model matches test data. A design of experiment study was conducted to analyse the influence of suspension parameters on corresponding suspension characteristics, and based on this a suitable correlation method and optimization model setup could be defined. By running the correlation procedure in the optimization software HEEDS MDO, connected with ADAMS/Car, suspension characteristics could be correlated to measurement data. The defined auto-correlation procedure was found to be effective and a front suspension assembly was successfully correlated to physical kinematics and compliance measurement results. However, the baseline suspension model has to be modelled correctly and include all the necessary variables in order to fully correlate the suspension simulation model. Some of the correlated suspension parameters were found to have optimized values outside normal production tolerances, in order to compensate for limitations in the simulation model, such as rigid modelling of components. By using the defined auto-correlation procedure, the correlation time was reduced and it is recommended that HEEDS MDO is used for future correlation of suspension assemblies. If the setup of the optimization model is adjusted, the defined correlation procedure can also be used to create suspension simulation models of competitor vehicles or optimizing suspension design concepts to meet requirements.
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Abvabi, Akbar, Rolfe, Bernard, Hodgson, Peter D., Weiss, Matthias
Presented at Esaform 2013 Conference, April 2013, Aveiro, Portugal

Bending and reverse bending are the dominant material deformations in roll forming, and hence property data derived from bend tests could be more relevant than tensile test data for numerical simulation of a roll forming process. Recent investigations have shown that residual stresses change the material behavior close to the yield in a bending test. So, residual stresses introduced during prior steel processing operations may affect the roll forming process, and therefore they need to be included in roll forming simulations to achieve improved model accuracy. Measuring the residual stress profile experimentally is time consuming and has limited accuracy while analytical models that are available require detailed information about the pre-processing conditions that is generally not available for roll forming materials. The main goal of this study is to develop an inverse routine that determines a residual stress profile through the material thickness based on experimental pure bend test data. A numerical model of the skin passing (temper rolling) process is performed to introduce a residual stress profile in DP780 steel sheet. The skin passed strips are used in a pure bending simulation to record moment-curvature data and this data is then applied in an inverse analysis to predict the residual stress profile in the material. Comparison of the residual stress profile predicted by the inverse routine with that calculated by finite element analysis (FEA) indicates an inverse approach combined with pure bend test may present an alternative to predict residual stresses in sheet metals.
Manufacturing, Marc, Nonlinear Stress, Parameter Estimation

Lee, Jin Woo, M.S., Embry-Riddle Aeronautical University, 2011, 159 pages; AAT EP33513

Development of a multidisciplinary design optimization (MDO) of a large scale hybrid composite wind turbine blade is performed. Multiple objectives are considered in the MDO process to maximize annual energy production and lifetime profit, minimize weight and power production rate. A wind turbine blade is divided into regions and the layup sequences for each region are considered as design variables. The scale of wind turbine blade is also considered to find the optimum size of a wind turbine blade. Applied loads due to extreme wind conditions for rotor rotation and rotor stop condition are considered for finite element analysis (FEA) to evaluate the structural strength. The designed structural strength and stiffness are demonstrated to withstand the loads due to harmonic excitation from rotor rotation. An MDO process for obtaining an optimum hybrid composite laminate layup and an optimum length of a wind turbine blade is developed and illustrated in this research. The finite element (FE) model and cost estimation model are calibrated and the developed MDO process is verified for an optimum design. The optimum hybrid composite layup sequence and size of a large scale wind turbine blade are highlighted in this research.
Energy, Excel, FEMAP, Linear Stress, Nastran

Maurer, Myron John, M.S., Michigan State University, 2010, 116 pages; AAT 1485601

Energy efficiency in residential building applications is an important aspect in reducing greenhouse gas emissions such as carbon dioxide. Thus, significant emphasis is now being placed on the building enclosure and the importance of having a continuous boundary of insulation between the interior conditioned space and the external environment. Structural insulated panels (SIP's) comprised of an expanded polystyrene (EPS) bead foam core sandwiched between oriented strand board (OSB) facings have been used predominantly in exterior wall applications to date due to deficiencies in meeting load-bearing requirements for structural roof panel applications. An alternative approach combines OSB facings with structural lath frames and orthotropic extruded polystyrene (XPS) foam core to render composite sandwich panels that satisfy allowable spans for self-supported installation. Foam constitutive material properties and finite element (FE) models of composite roof panels were constructed to investigate the effects of facing, lath and foam core characteristics on panel deflection and constituent strength factor of safety considerations. Such FE models were then used in conjunction with HEEDS automated design software to optimize the geometric configuration of various roof sandwich panels.
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Elisa Toulson, Casey M. Allen, Dennis J. Miller, Harold J. Schock, and Tonghun Lee
Energy & Fuels 2010 24 (6), 3510-3516

The research presented here describes the numerical optimization of a multi-step ignition model to predict the auto-ignition of dimethyl ether (DME) in a rapid compression machine. Experimental data for the ignition of DME/O2/N2 mixtures at more than 60 different conditions were used by the optimizer to determine the 26 kinetic parameters of the multi-step model that are unique to each individual fuel or fuel blend. The optimization was performed for conditions with compressed pressures in the range of 10−20 bar, compressed temperatures from 615 to 735 K, and equivalence ratios of 0.43, 0.75, and 1.5.
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Praveen Halepatali and Christopher Ha, Caterpillar Inc.; Ronald C. Averill, Red Cedar Technology Inc.
Presented at SAE 2010 World Congress & Exhibition, April 2010, Detroit, MI, USA, Session: CAE Analysis, Test Correlation and Optimization: Durability CAE

In this paper we demonstrate how the type of setup and algorithmic choice can have an influence and make optimization more lucrative in a new product development atmosphere. We also present some results from a design exploration activity, involving linkage and structural development, of an earth moving machine application. The kinematic requirements in this study, involving point layout and performance requirements, were evaluated using an in house code and structural aspects, involving yield, buckling and weld fatigue requirements, were evaluated by using Nastran and FE-SAFE. The development plan broke the tasks into two optimization stages, kinematic and structural optimization, which were executed sequentially using optimization algorithms in HEEDS. The results demonstrate that the optimization activities not only lead to designs with a better performance, lower mass and reduced cost but also realized a significantly shorter turnaround time.

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Bonyoung Ghoo, Yasuyoshi Umezu, Yuko Watanabe, Ninshu Ma, and Ron Averill
AIP Conf. Proc. 1252, 537 (2010)

In the present study, 3-dimensional finite element analyses for hot-stamping processes of Audi B-pillar product are conducted using JSTAMP/NV and HEEDS. Special attention is paid to the optimization of simulation technology coupling with thermal-mechanical formulations. Numerical simulation based on FEM technology and optimization design using the hybrid adaptive SHERPA algorithm are applied to hot stamping operation to improve productivity. The robustness of the SHERPA algorithm is found through the results of the benchmark example. The SHERPA algorithm is shown to be far superior to the GA (Genetic Algorithm) in terms of efficiency, whose calculation time is about 7 times faster than that of the GA. The SHERPA algorithm could show high performance in a large scale problem having complicated design space and long calculation time.

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Automotive, Manufacturing

John C. Oliva and Erik D. Goodman
Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, (Montreal, Québec, Canada, July 08 - 12, 2009). GECCO '09. ACM, New York, NY, pp. 1577-1584.

In the field of mechanical engineering, synthesizing a mechanism to perform an intended task is deceptively complex. In this paper, a novel approach to automated mechanism synthesis is described which uses an evolutionary search algorithm and a technique called "convertible agents" to simultaneously find the most appropriate mechanism type for a given problem, while finding an optimum set of dimensions for that mechanism to complete a specified task. The search was limited to four-bar, Stephenson, and Watt types of planar, single-degree-of-freedom mechanisms, although the method is readily scalable to include any number of different types. Several case studies are described which illustrate the effectiveness of the method. The developed convertible agent approach is well suited for evolutionary design applications in which there are a small number of distinct topological possibilities each with parametric variables to be optimized.
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Equivalent fuel consumption optimal control of a series hybrid electric vehicle
J-P Gao, G-M G. Zhu, E.G. Strangas, and F-C Sun
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
, Volume 223, Number 8/2009, pp. 1003-1018 

Improvements in hybrid electric fuel economy with reduced emissions strongly depend on their supervisory control strategy. In order to develop an efficient real-time supervisory control strategy for a hybrid electric bus, the proposed equivalent fuel consumption optimal control strategy is compared with two popular strategies, thermostat and power follower, using backward simulations in ADVISOR. For given driving cycles, global optimal solutions were also obtained using dynamic programming to provide an optimization target for comparison purposes. Comparison simulations showed that the thermostat control strategy optimizes the operation of the internal combustion engine, and the power follower control strategy minimizes the battery charging and discharging operations, which, hence, reduces battery power loss and extends the battery life. The equivalent fuel consumption optimal control strategy proposed in this paper provides an overall system optimization between the internal combustion engine and battery efficiencies, leading to the best fuel economy.

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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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Abaqus, Biomedical