Masoud Rais-Rohani

Mississippi State University, Mississippi, United States

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Publications (37)15.92 Total impact

  • M. Islam, A. Buijk, M. Rais-Rohani, K. Motoyama
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    ABSTRACT: A welding process design tool is proposed for arc welding parametric optimization.•It is based on integrated Finite Element Method, Response Surface Method and Genetic Algorithms.•Simulation based process parameter optimization is possible without expensive experiments.•The method effectively determines optimum parameters for minimum distortion.
    Advances in Engineering Software. 01/2015; 79.
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    ABSTRACT: A vehicle–dummy multidisciplinary design optimization problem is treated as a multilevel system composed of structural and occupant restraint system design elements. The vehicle-based responses and the dummy-based responses are obtained from nonlinear transient dynamic finite element simulations of full frontal impacts and side impacts. The wall thicknesses of a set of energy-absorbing components together with the occupant restraint system control parameters associated with the seat belt and the airbag are treated as design variables and used to optimize the multilevel system to minimize both the structural mass and the selected injury criteria. Each element optimization problem is modeled using the augmented Lagrangian with exponential penalty function formulation. A single-loop coordination strategy is used to solve the multilevel optimization problem. To maximize the computational efficiency, surrogate models are used to approximate the vehicle-based responses and the dummy-based responses. The results of the vehicle–dummy design problem are used to examine the computational efficiency and the accuracy of the decomposed multilevel optimization methodology.
    Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering 08/2014; · 0.58 Impact Factor
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    M. Islam, A. Buijk, M. Rais-Rohani, K. Motoyama
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    ABSTRACT: This paper presents an effective numerical approach for welding process parameter optimization to minimize weld-induced distortion in structures. A numerical optimization framework based on coupled Genetic Algorithm (GA) and Finite Element Analysis (FEA) is developed and implemented for a low and a high fidelity model. Classical weakly coupled thermo-mechanical analysis with thermo-elasto-plastic assumptions is carried out for distortion prediction of numerical models. The search for optimum process parameters is executed by direct integration of numerical models and GA-based optimization technique. The developed framework automatically inserts the process parameters into the simulation models, executes the FE-based welding simulations and evaluates the required simulation output data for iterative evolutionary optimization. The optimization results show that the proposed approach can contribute substantially to enhance final welded product quality while facilitating and accelerating the product design and development.
    Finite Elements in Analysis and Design 07/2014; 84:54–64. · 1.39 Impact Factor
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    ABSTRACT: Car body design in view of structural performance and lightweighting is a challenging task due to all the performance targets that must be satisfied such as vehicle safety and ride quality. In this paper, material replacement along with multidisciplinary design optimization strategy is proposed to develop a lightweight car body structure that satisfies the crash and vibration criteria while minimizing weight. Through finite element simulations, full frontal, offset frontal, and side crashes of a full car model are evaluated for peak acceleration, intrusion distance, and the internal energy absorbed by the structural parts. In addition, the first three fundamental natural frequencies are combined with the crash metrics to form the design constraints. The wall thicknesses of twenty-two parts are considered as the design variables. Latin Hypercube Sampling is used to sample the design space, while Radial Basis Function methodology is used to develop surrogate models for the selected crash responses at multiple sites as well as the first three fundamental natural frequencies. A nonlinear surrogate-based optimization problem is formulated for mass minimization under crash and vibration constraints. Using Sequential Quadratic Programming, the design optimization problem is solved with the results verified by finite element simulations. The performance of the optimum design with magnesium parts shows significant weight reduction and better performance compared to the baseline design.
    Journal of Magnesium and Alloys. 06/2014;
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    ABSTRACT: An approach is presented to evaluate the structural performance of a vehicle model in terms of the joint stiffness. Seven major joints on the left and right sides of the vehicle body are identified, and each joint is decomposed in the finite element model and assigned a separate set of material properties. By adjusting the elastic modulus of each structural member, the effects of the joint stiffness on the full and offset frontal impacts as well as the vibration characteristics are examined. Latin hypercube sampling is used in the design of experiments to approximate the acceleration, the intrusion distance, and the fundamental vibration frequencies using full quadratic polynomial response surface models. Through direct differentiation, the sensitivities of the crash responses and the vibration responses to the joint stiffness are calculated. A constrained multi-objective optimization problem is formulated and solved to improve the structural responses by adjusting the stiffness at each joint. Evaluation of the car body structure based on the optimum joint stiffness showed a superior performance relative to the baseline model without a weight penalty. The results of both the sensitivity analysis and the design optimization are presented and discussed.
    Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering 01/2014; 228(6):689-700. · 0.58 Impact Factor
  • Ali Najafi, Erdem Acar, Masoud Rais-Rohani
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    ABSTRACT: The stochastic uncertainties associated with the material, process and product are represented and propagated to process and performance responses. A finite element-based sequential coupled process–performance framework is used to simulate the forming and energy absorption responses of a thin-walled tube in a manner that both material properties and component geometry can evolve from one stage to the next for better prediction of the structural performance measures. Metamodelling techniques are used to develop surrogate models for manufacturing and performance responses. One set of metamodels relates the responses to the random variables whereas the other relates the mean and standard deviation of the responses to the selected design variables. A multi-objective robust design optimization problem is formulated and solved to illustrate the methodology and the influence of uncertainties on manufacturability and energy absorption of a metallic double-hat tube. The results are compared with those of deterministic and augmented robust optimization problems.
    Engineering Optimization 01/2014; 46(2). · 0.96 Impact Factor
  • S. DorMohammadi, M. Rais-Rohani
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    ABSTRACT: An exponential penalty function (EPF) formulation based on method of multipliers is presented for solving multilevel optimization problems within the framework of analytical target cascading. The original all-at-once constrained optimization problem is decomposed into a hierarchical system with consistency constraints enforcing the target-response coupling in the connected elements. The objective function is combined with the consistency constraints in each element to formulate an augmented Lagrangian with EPF. The EPF formulation is implemented using double-loop (EPF I) and single-loop (EPF II) coordination strategies and two penalty-parameter-updating schemes. Four benchmark problems representing nonlinear convex and non-convex optimization problems with different number of design variables and design constraints are used to evaluate the computational characteristics of the proposed approaches. The same problems are also solved using four other approaches suggested in the literature, and the overall computational efficiency characteristics are compared and discussed.
    Structural and Multidisciplinary Optimization 04/2013; 47(4). · 1.73 Impact Factor
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    Amin Kargarian, Yong Fu, Saber DorMohammadi, Masoud Rais-Rohani
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    ABSTRACT: Active distribution grid is composed of autonomous systems which should collaborate with each other in order to operate the entire distribution grid in a secure and economic manner. This paper presents a system of systems (SoS) framework for optimally operating active distribution grids. The proposed SoS framework defines both distribution company (DISCO) and microgrids (MGs) as independent systems, and identifies the process of information exchange among them. As the DISCO and MGs are physically connected together, the operating condition of one might impact the operating point of other systems. The proposed mathematical model uses a decentralized optimization problem aimed at maximizing the benefit of each independent system. A hierarchical optimization algorithm is presented to coordinate the independent systems and to find the optimal operating point of the SoS-based active distribution grid. The numerical results show the effectiveness of the proposed SoS framework and solution methodology.
    IEEE Transactions on Smart Grid 01/2013;
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    ABSTRACT: An evidence-based approach is developed for optimization of structural components under material parameter uncertainty. The approach is applied to evidence-based design optimization (EBDO) of externally stiffened circular tubes under axial impact load using an isotropic–elastic–plastic plasticity model to simulate dynamic material behaviour. Uncertainty modelling considers the changes in material parameters that are caused by variability in material properties as well as incertitude and errors in experimental data and procedure to determine the material parameters. Spatial variation of material parameters across the structural component is modelled using a field joint belief structure and propagated for the calculation of evidence-based objective function and design constraints. Surrogate models are used in both uncertainty propagation and solution of the optimization problem. The methodology and the solution to the EBDO example problem are presented and discussed.
    Engineering Optimization 01/2013; 45(9). · 0.96 Impact Factor
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    ABSTRACT: The traditional crashworthiness optimisation problem is augmented by inclusion of additional design criterion associated with vehicle vibration characteristics. Through finite element (FE) simulations, full frontal, offset frontal and side crashes of a full vehicle model are analysed for peak acceleration, intrusion distance and internal energy. Moreover, the FE crash model of the vehicle is modified to develop a vibration-analysis model for evaluation of natural frequencies and mode shapes. Design of computer experiments through Latin hypercube sampling is used to sample the design space defined by the wall thicknesses of 22 parts. Radial basis functions are used to generate separate surrogate models for the selected crash responses measured at multiple sites as well as the fundamental natural frequencies in bending and torsion. A nonlinear surrogate-based mass minimisation problem is formulated and solved under crash and vibration constraints with the results verified through FE simulations. The optimum vehicle design under multiple design criteria is presented and the vehicle's characteristics are compared with those of the baseline design as well as those associated with the optimum design based on crash responses alone.
    International Journal of Crashworthiness 01/2013; 18(5).
  • Andrew Parrish, Masoud Rais-Rohani, Ali Najafi
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    ABSTRACT: This paper explores the effects of replacing the baseline steel with lightweight magnesium alloy parts on crashworthiness characteristics and optimum design of a full-vehicle model. Full frontal, offset frontal and side crash simulations are performed on a validated 1996 Dodge Neon model using explicit nonlinear transient dynamic finite element analyses in LS-DYNA to obtain vehicle responses such as crash pulse, intrusion distance, peak acceleration and internal energy. Twenty-two parts of the vehicle body structure are converted into AZ31 magnesium alloy with adjustable wall thickness while the remaining parts are kept intact. The magnesium alloy material model follows a piecewise linear plasticity law considering separate tension and compression properties and maximum plastic strain failure criterion. Six different metamodelling techniques including optimised ensemble are developed and tuned for predictions of crash-induced responses within the design optimisation process. The crashworthiness optimisation problem is solved using the sequential quadratic programming method with most accurate surrogate models of structural responses considering both constrained single- and multi-objective formulations. The results show that under the combined crash scenarios with the selected material models and design constraints, the vehicle model with magnesium alloy parts can be optimised to maintain or improve its crashworthiness characteristics with up to 50% weight savings in the redesigned parts.
    International Journal of Crashworthiness - INT J CRASHWORTHINESS. 01/2012;
  • Cynthia M. Tamasco, Masoud Rais-Rohani, Arjaan Buijk
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    ABSTRACT: This article presents the development and application of a coupled finite element simulation and optimization framework that can be used for design and analysis of sheet-forming processes of varying complexity. The entire forming process from blank gripping and deep drawing to tool release and springback is modelled. The dies, holders, punch and workpiece are modelled with friction, temperature, holder force and punch speed controlled in the process simulation. Both single- and multi-stage sheet-forming processes are investigated. Process simulation is coupled with a nonlinear gradient-based optimization approach for optimizing single or multiple design objectives with imposed sheet-forming response constraints. A MATLAB program is developed and used for data-flow management between process simulation and optimization codes. Thinning, springback, damage and forming limit diagram are used to define failure in the forming process design optimization. Design sensitivity analysis and optimization results of the example problems are presented and discussed.
    Engineering Optimization 01/2012; · 0.96 Impact Factor
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    S. Salehghaffari, M. Rais-Rohani, A Najafi
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    ABSTRACT: Nonlinear finite element analysis is used to investigate the quasi-static axial collapse response of cylindrical tubes which are externally stiffened by multiple identical rings. The rings divide the long tube into a series of short thin-walled tubes. It is assumed that the size and shape of integral stiffeners are controlled through a machining process. The effects of various geometric parameters such as wall thickness, ring spacing, ring thickness and width on the collapse response, crush force and energy absorption of monolithic, integrally stiffened steel tubes are studied and used as a general framework for a design optimization study. Through design and analysis of computer experiments, global metamodels are developed for the mean crush force and energy absorption, using the radial basis function approximation technique. Using both single- and multi-objective design optimization formulations, optimum designs for different response characteristics are found. The crush mode in the form of progressive collapse or buckling is found to heavily depend on the ratio of stiffener spacing to stiffener height as well as the ratio of wall thickness to stiffener thickness. The optimization results show the viability of externally stiffened tubes as efficient energy absorbers.
    Thin-Walled Structures. 01/2011;
  • Ali Najafi, Masoud Rais-Rohani
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    ABSTRACT: Quasi-static nonlinear finite element simulations are performed to study the energy absorption characteristics of axially crushed thin-walled aluminum tubes with different multi-cell, multi-corner configurations. By considering the kinematically consistent representation of plastic collapse as observed in the crush simulations, an analytical formula for the mean crush force is derived using the super folding element theory. In this model, the isotropic material is treated as rigid-perfectly plastic and the total internal energy is calculated by considering both bending and membrane deformation during the folding process. The simulation results show a strong correlation between the cross-sectional geometry and the crush response of the tubes. The analytical predictions for the mean crush force are compared with the FE results as well as other analytical models reported in the literature.
    Thin-Walled Structures. 01/2011;
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    ABSTRACT: Uncertainties in material microstructure features can lead to uncertainty in damage predictions based on multiscale microstructure–property models. This paper presents an analytical approach for stochastic uncertainty analysis by using a univariate dimension reduction technique. This approach is used to analyze the effects of uncertainties pertaining to the structure–property relations of an internal state variable plasticity–damage model that predicts failure. The results indicate that the higher the strain the greater the scatter in damage, even when the uncertainties in the material plasticity and microstructure parameters are kept constant. In addition, the mathematical sensitivity analysis results related to damage uncertainty are consistent with the physical nature of damage progression. At the beginning, the initial porosity and void nucleation are shown to drive the damage evolution. Then, void coalescence becomes the dominant mechanism. And finally, when approaching closer to failure, fracture toughness is found to dominate the damage evolution process.
    Probabilistic Engineering Mechanics 01/2010; 25(2):198-205. · 1.09 Impact Factor
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    ABSTRACT: This paper presents the results of a study on the combined shape and sizing optimisation of automotive structures while examining the effects of different design constraints and associated uncertainties on reliability and efficiency of the optimum designs. Nonlinear transient dynamic finite element analysis is used for full- and offset-frontal crash simulations of a full vehicle model. Surrogate models are developed for the intrusion distance and peak acceleration responses at different vehicle locations based on the material and geometric characteristics of the rail component. The obtained solutions provide insight on the effect of uncertainties in optimum design of automotive structures.
    Int. J. of Vehicle Design. 01/2010; 54(4):309 - 338.
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    Mohammad Rouhi, Masoud Rais-Rohani, Thomas N. Williams
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    ABSTRACT: This paper presents a stochastic direct search method for topology optimization of continuum structures. In a systematic approach requiring repeated evaluations of the objective function, the element exchange method (EEM) eliminates the less influential solid elements by switching them into void elements and converts the more influential void elements into solid resulting in an optimal 0–1 topology as the solution converges. For compliance minimization problems, the element strain energy is used as the principal criterion for element exchange operation. A wider exploration of the design space is assured with the use of random shuffle while a checkerboard control scheme is used for detection and elimination of checkerboard regions. Through the solution of multiple two- and three-dimensional topology optimization problems, the general characteristics of EEM are presented. Moreover, the solution accuracy and efficiency of EEM are compared with those based on existing topology optimization methods. KeywordsTopology optimization-Element exchange method-EEM-Stochastic-Non-gradient-Binary
    Structural and Multidisciplinary Optimization 01/2010; 42(2):215-231. · 1.73 Impact Factor
  • Christopher D. Eamon, Masoud Rais-Rohani
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    ABSTRACT: In this paper, we present the application of probabilistic design modeling and reliability-based design optimization (RBDO) methodology to the sizing optimization of a composite advanced submarine sail structure under parametric uncertainty. With the help of probabilistic sensitivity analysis, the influence of individual random variables on each structural failure mode is examined, and the critical modes are treated as probabilistic design constraints under consistent lower bounds on the corresponding reliability indices. Whereas the failure modes are evaluated for structural components in the solution of the RBDO problem, the overall system reliability is also evaluated as a post-optimization step. The results indicate that in comparison to a deterministic-optimum design, the structural mass of the probabilistic optimum design is slightly higher when consistent probabilistic constraints are imposed, and the overall structural stiffness is found to be more critical than individual component laminate ply thicknesses in meeting the specified design constraints. Moreover, the post-optimality analysis shows that the overall system failure probability of the probabilistic optimum design is more than 50% lower than that of the deterministic optimal design with less than 5% penalty in structural mass.
    Marine Structures - MAR STRUCT. 01/2009; 22(2):315-334.
  • Journal of Engineering Materials and Technology-transactions of The Asme - J ENG MATER TECHNOL. 01/2009; 131(4).
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    ABSTRACT: In this paper, we present a methodology for simulation-based product design optimisation using an internal state variable (ISV) constitutive modelling approach that captures the microstructure-property relations in the material. By modelling the stochastic uncertainties in the material model and the loading conditions, the design optimisation problem is formulated and solved using the reliability-based design optimisation (RBDO) methodology. The application problem considers the design optimisation of an A356-T6 cast aluminium component under maximum stress and damage constraints. Alternative metamodelling techniques are used to develop appropriate surrogate models in lieu of direct coupling of non-linear static finite element analysis and numerical design optimisation. Probabilistic design constraints are modelled using the safety index approach with the solution of the nested 48 K.N. Solanki et al. optimisation problem facilitated with the help of analytical surrogate models. Comparison of the optimisation results reveals the importance of using an ISV-based constitutive model that is sensitive to the growth of damage in material. Moreover, the solution of the RBDO problem captures the effects of uncertainty on finding the minimum weight design for the cast component. 'Product design optimisation with microstructure-property modelling and associated uncertainties', Int. J. Design Engineering, Vol. 2, No. 1, pp.47–79. Biographical notes: Kiran Solanki is an Assistant Research Professor. His research efforts are centred on multiscale material modelling, automotive crash simulations and uncertainty characterisation of metallic materials. Erdem Acar is a Postdoctoral Research Associate. His research efforts are centred on reliability analysis, reliability-based design and response surface techniques. Masoud Rais-Rohani is a Professor of Aerospace Engineering and Engineering Mechanics. His research efforts are centred on simulation-based design optimisation of structural and multidisciplinary systems, composite structures and metamodelling techniques. He teaches courses in the areas of engineering design optimisation, aircraft structures and engineering mechanics. Mark F. Horstemeyer is a Chair Professor of Mechanical Engineering. His research efforts are centred on solid mechanics, microstructure-property constitutive modelling, finite deformation inelasticity, damage evolution, fracture, composites, electromigration-stress voiding, fatigue, penetration and impact; numerical modelling of nano-and microstructural mechanics; atomistic simulations; finite element analyses of manufacturing methods such as forming, forging and other metal processing methods. He teaches courses in the areas of inelasticity, elasticity, failure of engineering material and engineering mechanics. Glenn Steele is a Professor of Mechanical Engineering. His research efforts are centred on simulation-based uncertainty analysis, experimental techniques, heat transfer and energy systems. He teaches courses in the areas of engineering analysis, uncertainty analysis and experimental techniques.
    Int. J. Design Engineering. 01/2009; 2.