Structural Optimization of Truck Front-Frame Under Multiple Load Cases

Author(s):  
Shuvodeep De ◽  
Karanpreet Singh ◽  
Berkan Alanbay ◽  
Rakesh K. Kapania ◽  
Raymond Aguero

An optimization framework is developed to minimize structural weight of the front-frame of heavy-duty trucks while satisfying stress constraint. The shape of the frame is defined by a number of design parameters (which define the shape of the side-rail, position and width of the internal brackets, and width of the flanges). In addition, the thickness of the engine-mount, the side-rails, inner-brackets, radiator mount, shock absorber and cab-mount connector are also considered as design variables. Aluminum Alloy, 6013-T6 is chosen as the material and the maximum allowable stress is the yield stress (320 MPa). A quantity known as ‘Violation’ is defined as the ratio of area in the front-end module where stress constraint is violated to the total area of the frame is introduced to implement stress constraints. For optimization, the penalty method is used where the objective is to minimize the total weight while keeping the value of the ‘Violation’ parameter less than 0.1 %. The Particle Swarm Optimization Algorithm is implemented using parallel computation for optimizing the structure. Commercial FEA software MSC.PATRAN is used for creating the geometry and the mesh whereas MSC.NASTRAN is used to perform static analysis. Six design load conditions, each corresponding to a road condition are used for the problem.

Author(s):  
Sudhir Kaul ◽  
Anoop K. Dhingra ◽  
Timothy G. Hunter

This paper presents a comprehensive model to capture the dynamics of a motorcycle system in order to evaluate the quality of vibration isolation. The two main structural components in the motorcycle assembly - the frame and the swing-arm - are modeled using reduced order finite element models; the power-train assembly is modeled as a six degree-of-freedom (DOF) rigid body connected to the frame through the engine mounts and to the swing-arm through a shaft assembly. The engine mounts are modeled as tri-axial spring-damper systems. Models of the front-end assembly as well as front and rear tires are also included in the overall model. The complete vehicle model is used to solve the engine mount optimization problem so as to minimize the total force transmitted to the frame while meeting packaging and other side constraints. The mount system parameters - stiffness, position and orientation vectors - are used as design variables for the optimization problem. The imposed loads include forces and moments due to engine imbalance as well as loads transmitted due to irregularities in the road surface through the tire patch.


Author(s):  
Ameya K. Naik ◽  
Raghunath S. Holambe

An outline is presented for construction of wavelet filters with compact support. Our approach does not require any extensive simulations for obtaining the values of design variables like other methods. A unified framework is proposed for designing halfband polynomials with varying vanishing moments. Optimum filter pairs can then be generated by factorization of the halfband polynomial. Although these optimum wavelets have characteristics close to that of CDF 9/7 (Cohen-Daubechies-Feauveau), a compact support may not be guaranteed. Subsequently, we show that by proper choice of design parameters finite wordlength wavelet construction can be achieved. These hardware friendly wavelets are analyzed for their possible applications in image compression and feature extraction. Simulation results show that the designed wavelets give better performances as compared to standard wavelets. Moreover, the designed wavelets can be implemented with significantly reduced hardware as compared to the existing wavelets.


Author(s):  
Sayed M. Metwalli ◽  
M. Alaa Radwan ◽  
Abdel Aziz M. Elmeligy

Abstract The convensional procedure of helical torsion spring design is an iterative process because of large number of requirements and relations that are to be attained once at a time. The design parameters are varied at random until the spring design satisfies performance requirements. A CAD of the spring for minimum weight is formulated with and without the variation of the maximum normal stress with the wire diameter. The CAD program solves by employing the method of Lagrange-Multipliers. The optimal parameters, in a closed form are obtained, normalized and plotted. These explicit relations of design variables allow direct evaluation of optimal design objective and hence, an absolute optimum could be achieved. The comparison of optimum results with those previously published, shows a pronounced achievement in the reduction of torsion spring weight.


Author(s):  
Masao Arakawa ◽  
Hiroshi Yamakawa

Abstract In this study, we summerize the method of fuzzy optimization using fuzzy numbers as design variables. In order to detect flaw in fuzzy calculation, we use LR-fuzzy numbers, which is known as its simplicity in calculation. We also use simple fuzzy numbers’ operations, which was proposed in the previous papers. The proposed method has unique characteristics that we can obtain fuzzy sets in design variables (results of the design) directly from single numerical optimizing process. Which takes a large number of numerical optimizing processes when we try to obtain similar results in the conventional methods. In the numerical examples, we compare the proposed method with several other methods taking imprecision in design parameters into account, and demonstrate the effectiveness of the proposed method.


Author(s):  
Shilpa A. Vaze ◽  
Prakash Krishnaswami ◽  
James DeVault

Most state-of-the-art multibody systems are multidisciplinary and encompass a wide range of components from various domains such as electrical, mechanical, hydraulic, pneumatic, etc. The design considerations and design parameters of the system can come from any of these domains or from a combination of these domains. In order to perform analytical design sensitivity analysis on a multidisciplinary system (MDS), we first need a uniform modeling approach for this class of systems to obtain a unified mathematical model of the system. Based on this model, we can derive a unified formulation for design sensitivity analysis. In this paper, we present a modeling and design sensitivity formulation for MDS that has been successfully implemented in the MIXEDMODELS (Multidisciplinary Integrated eXtensible Engine for Driving Metamodeling, Optimization and DEsign of Large-scale Systems) platform. MIXEDMODELS is a unified analysis and design tool for MDS that is based on a procedural, symbolic-numeric architecture. This architecture allows any engineer to add components in his/her domain of expertise to the platform in a modular fashion. The symbolic engine in the MIXEDMODELS platform synthesizes the system governing equations as a unified set of non-linear differential-algebraic equations (DAE’s). These equations can then be differentiated with respect to design to obtain an additional set of DAE’s in the sensitivity coefficients of the system state variables with respect to the system’s design variables. This combined set of DAE’s can be solved numerically to obtain the solution for the state variables and state sensitivity coefficients of the system. Finally, knowing the system performance functions, we can calculate the design sensitivity coefficients of these performance functions by using the values of the state variables and state sensitivity coefficients obtained from the DAE’s. In this work we use the direct differentiation approach for sensitivity analysis, as opposed to the adjoint variable approach, for ease in error control and software implementation. The capabilities and performance of the proposed design sensitivity analysis formulation are demonstrated through a numerical example consisting of an AC rectified DC power supply driving a slider crank mechanism. In this case, the performance functions and design variables come from both electrical and mechanical domains. The results obtained were verified by perturbation analysis, and the method was shown to be very accurate and computationally viable.


2003 ◽  
Vol 17 (08n09) ◽  
pp. 1374-1380
Author(s):  
Jong Yun Jang ◽  
Chong Sun Lee ◽  
Chang Min Suh

The present study investigated design parameters of an anti-siphon device used with shunt valves to treat patients with hydrocephalus. Structural analyses were performed to understand roles of design variables and optimize performance of the diaphragm-type anti-siphon device (hereafter referred to as the ASD). Experiments were performed on the lab-made product and showed good agreements with the numerical simulations. Using the simulations, we were able to design a more physiological ASD which gave equal opening pressures in both supine and upright postures. Tissue encapsulization phenomenon was also simulated and the results indicated underdrainage of CSF in the upright position of the patient.


2020 ◽  
Vol 40 (5) ◽  
pp. 703-721
Author(s):  
Golak Bihari Mahanta ◽  
Deepak BBVL ◽  
Bibhuti B. Biswal ◽  
Amruta Rout

Purpose From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems. Design/methodology/approach In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer. Findings This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis. Practical implications The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries. Originality/value In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.


Polymers ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 3154
Author(s):  
Md Mohosin Rana ◽  
Hector De la Hoz Siegler

Poly(N-isopropylacrylamide) (PNIPAm) is a three-dimensional (3D) crosslinked polymer that can interact with human cells and play an important role in the development of tissue morphogenesis in both in vitro and in vivo conditions. PNIPAm-based scaffolds possess many desirable structural and physical properties required for tissue regeneration, but insufficient mechanical strength, biocompatibility, and biomimicry for tissue development remain obstacles for their application in tissue engineering. The structural integrity and physical properties of the hydrogels depend on the crosslinks formed between polymer chains during synthesis. A variety of design variables including crosslinker content, the combination of natural and synthetic polymers, and solvent type have been explored over the past decade to develop PNIPAm-based scaffolds with optimized properties suitable for tissue engineering applications. These design parameters have been implemented to provide hydrogel scaffolds with dynamic and spatially patterned cues that mimic the biological environment and guide the required cellular functions for cartilage tissue regeneration. The current advances on tuning the properties of PNIPAm-based scaffolds were searched for on Google Scholar, PubMed, and Web of Science. This review provides a comprehensive overview of the scaffolding properties of PNIPAm-based hydrogels and the effects of synthesis-solvent and crosslinking density on tuning these properties. Finally, the challenges and perspectives of considering these two design variables for developing PNIPAm-based scaffolds are outlined.


2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Hong Zhou

The hybrid discretization model for topology optimization of compliant mechanisms is introduced in this paper. The design domain is discretized into quadrilateral design cells. Each design cell is further subdivided into triangular analysis cells. This hybrid discretization model allows any two contiguous design cells to be connected by four triangular analysis cells whether they are in the horizontal, vertical, or diagonal direction. Topological anomalies such as checkerboard patterns, diagonal element chains, and de facto hinges are completely eliminated. In the proposed topology optimization method, design variables are all binary, and every analysis cell is either solid or void to prevent the gray cell problem that is usually caused by intermediate material states. Stress constraint is directly imposed on each analysis cell to make the synthesized compliant mechanism safe. Genetic algorithm is used to search the optimum and to avoid the need to choose the initial guess solution and conduct sensitivity analysis. The obtained topology solutions have no point connection, unsmooth boundary, and zigzag member. No post-processing is needed for topology uncertainty caused by point connection or a gray cell. The introduced hybrid discretization model and the proposed topology optimization procedure are illustrated by two classical synthesis examples of compliant mechanisms.


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