scholarly journals Modelling and FE Simulation of HVC Using Multi Objective Response Surface Optimization Techniques

2021 ◽  
Vol 31 (6) ◽  
pp. 307-315
Author(s):  
Abhishek Agarwal ◽  
Linda Mthembu
Keyword(s):  
Response Surface ◽  
Fe Simulation ◽  
Material Selection ◽  
Equivalent Stress ◽  
Optimization Techniques ◽  
Production Costs ◽  
Design Scheme ◽  
Stress Deformation ◽  
Vehicle Chassis ◽  
Optimal Space

The purpose of an automotive chassis is to maintain the shape of the vehicle and bear the various loads that are applied to the vehicle. The structure typically accounts for a large portion of the development and production costs of the new vehicle program, and the designer has many different structural concepts available. Choosing the best is important to ensure acceptable structural performance under other design constraints, such as cost, volume and method of production, product application, and more. The material selection for chassis depends upon various factors like lightness, economy, safety, recyclability, and circulation of life. The current study aims to perform optimization of the design of a heavy vehicle chassis using central composite design & optimal space fill design scheme (s) with the material tested is Al6092/SiC/17.5p MMC. Different design points are generated using design of experiments. The equivalent stress, deformation and mass are evaluated for each design points. The CAD modelling and FE simulation of heavy motor vehicle chassis is conducted using ANSYS software. From the optimization conducted on chassis design, response surface plots of equivalent stress, deformation and mass are generated which enabled to determine the range of dimensions for which these parameters are maximum or minimum. The use of Discontinuously Reinforced Aluminium-Matrix Composites Al6092/SiC/17.5p MMC aided to reduce weight of chassis by 66.25% and 66.68% by using CCD and Optimal space fill design scheme respectively, without much reduction in strength of chassis.

scholarly journals Numerical Modelling and Multi Objective Optimization Analysis of Heavy Vehicle Chassis

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 2028
Author(s):  
Abhishek Agarwal ◽  
Linda Mthembu
Keyword(s):  
Motor Vehicle ◽  
Equivalent Stress ◽  
Optimization Techniques ◽  
Mass Reduction ◽  
Space Filling ◽  
Design Scheme ◽  
Taguchi Design Of Experiments ◽  
Cross Member ◽  
Vehicle Chassis ◽  
Optimal Space

The primary supporting structure of an automobile and its other vital systems is the chassis. The chassis structure is required to bear high shock, stresses, and vibration, and therefore it should possess adequate strength. The objective of current research is to analyze a heavy motor vehicle chassis using numerical and experimental methods. The CAD design and FE analysis is conducted using the ANSYS software. The design of the chassis is then optimized using Taguchi design of Experiments (DOE); the optimization techniques used are the central composite design (CCD) scheme and optimal space filling (OSF) design. Thereafter, sensitivity plots and response surface plots are generated. These plots allow us to determine the critical range of optimized chassis geometry values. The optimization results obtained from the CCD design scheme show that cross member 1 has a higher effect on the equivalent stresses as compared to cross members 2 and 3. The chassis mass reduction obtained from the CCD scheme is approximately 5.3%. The optimization results obtained from the OSF scheme shows that cross member 2 has a higher effect on equivalent stress as compared to cross members 1 and 3. The chassis mass reduction obtained from optimal space filling design scheme is approximately 4.35%.

Analysis of the stress-strain state of a vertical ground electrode system for permafrost soils under pushing loads

2021 ◽  
pp. 77-89
Author(s):  
I. S. Sukhachev ◽  
P. V. Chepur ◽  
A. A. Tarasenko ◽  
A. A. Gruchenkova ◽  
Yuhai Guan
Keyword(s):  
Equivalent Stress ◽  
Side Surface ◽  
Metal Structure ◽  
Vertical Displacement ◽  
Soil Mass ◽  
Electrode System ◽  
Plastic Properties ◽  
Design Scheme ◽  
Permafrost Soils ◽  
Vertical Ground

The article proposes the design, design scheme and model of a vertical ground electrode system with lobe lugs for permafrost soils. The model was implemented using the ANSYS software. In the design scheme, the soil — ground electrode system is taken into account, the elastic-plastic properties of the soil are taken into account by the Drucker — Prager model. When modeling the work of the foundation soils, the Mises strength condition was adopted, according to which the equivalent stress is calculated under the condition of the material hydrostatic compression. The following boundary conditions are accepted: a cylinder-shaped soil mass is rigidly fixed along the lower face and along the side surface of the cylinder. Calculations are made for 5 standard sizes of grounding conductors. Maps of the distribution of stresses in the metal structure of the ground electrode (the rod and petals-emphasis) are received, the movements of the ground electrode in the soil mass are determined. The dependences between the maximum equivalent stresses in the ground electrode lobes and the value of vertical displacement in the ground base are established, as well as the amount of movement of the earthing pad, at which the effective equivalent voltages reach critical values in the area where the paddles are adjacent to the rod.

Combining Response Surface Method and Metaheuristic Algorithms for Optimizing SPIF Process

2021 ◽  
Vol 11 (4) ◽  
pp. 1-25
Author(s):  
Amr Ahmed Shaaban ◽  
Omar Mahmoud Shehata
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Single Point ◽  
Experimental Studies ◽  
Optimization Techniques ◽  
Parameters Optimization ◽  
Second Phase ◽  
Fe Model ◽  
Optimum Conditions ◽  
Surface Method

Recently, studies have focused on optimization as a method to reach the finest conditions for metal forming processes. This study tests various optimization techniques to determine the optimum conditions for single point incremental forming (SPIF). SPIF is a die-less forming process that depends on moving a tool along a path designed for a specific feature. As it involves various parameters, optimization based on experimental studies would be costly, hence a finite element model (FE-model) for the SPIF process is developed and validated through experimental results. In the second phase, statistical analyses based on the response surface method (RSM) are conducted. The optimum conditions are determined using the desirability optimization method, in addition to two metaheuristic optimization algorithms, namely genetic algorithm (GA) and particle swarm optimization (PSO). The results of all optimization techniques are compared to each other and a confirmation test using the FE-model is subsequently performed.

Study on Optimal Design of a Folding-Type Hatch Cover Considering Material Selection

2021 ◽  
pp. 1-11
Author(s):  
Gerry Liston Putra ◽  
Mitsuru Kitamura ◽  
Akihiro Takezawa
Keyword(s):  
Production Systems ◽  
Material Selection ◽  
Optimization Technique ◽  
Plate Thickness ◽  
Optimization Methods ◽  
Optimization Method ◽  
Production Costs ◽  
Plate Material ◽  
Material Type ◽  
Material Cost

Abstract Most shipyard companies maintain efficiency in all aspects of their business to survive. One of these aspects is ship production costs and their reduction. This study proposes a solution to this problem using an optimization method. A hatch cover composed of plates and stiffeners was selected as a case study. In this study, the mass and material cost of the hatch cover was optimized as an objective function using the Pareto approach with developed optimization methods. Plate thickness t, stiffener shape s, and plate material type m were selected as the design variables in this study along with some constraints. To estimate the optimal plate thickness, an expression of stress equations was Developed using an optimization technique. Furthermore, stiffener shape and plate material type selection were optimized using a genetic algorithm (GA). The results show that the optimization method is effective to decrease the mass and material cost of a hatch cover. Introduction The demand for new shipbuilding has decreased because of the effect of the economic crisis that hit almost every country in the world. Shipyard companies must think innovatively and creatively to survive under the pressure of this crisis by evaluating various studies and improvising new methods to achieve efficiency. One of the studies that has been performed examines the methods to reduce the fabrication cost of ship structures to stay profitable through the optimization of work hours, workflow production systems, and structural design.

scholarly journals Combination of optimization techniques to find of processing optimal condition of postharvest broccoli by vacuum cooling process

2018 ◽  
Vol 40 (1) ◽  
pp. 36222 ◽  
Author(s):  
Tian Ding ◽  
Charles Gobber ◽  
José Carlos Curvelo Santana ◽  
Wonder Alexandre Luz Alves ◽  
Sidnei Alves de Araújo ◽  
...  
Keyword(s):  
Weight Loss ◽  
Response Surface Methodology ◽  
Tabu Search ◽  
Optimal Condition ◽  
Response Surface ◽  
Search Algorithm ◽  
Optimization Techniques ◽  
Water Volume ◽  
Tabu Search Algorithm ◽  
Vacuum Cooling

This study aimed to investigate the impact of each factor on the weight loss of postharvest broccoli and treatment efficacy, and also attempted to fix the optimal condition for vacuum cooling treatment on postharvest broccoli by response surface methodology combined with tabu search techniques. Fresh broccoli samples were harvested from a Chinese farm and the green heads of selected samples were cut into smaller ones with approximately 3~4 cmdiameter, and sequentially equilibrated to room temperature. Pressure (200-600 Pa), broccoli weight (200-500 g), water volume (2-6 %, v v-1) and time (20-40 min) were used as factors and weight loss, final temperature and cost as responses. A tabu search algorithm was developed to find the optimum condition for processing broccoli and its initial condition were from response surface methodology. Results demonstrates a good adjust of tabu search algorithm in simulation of the broccoli freezing process. From tabu list the best condition were found as follows: the broccoli weight between 273.5 and 278.0 g with a water volume of 3.0%, processed for 40.0 min and at 200 Pa, where the weight loss was 0.34 ± 0.01%, of end temperature was 2.0 ± 0.0°C and profit percent was 99.66 ± 0.01%. 

Parameter optimization of a diesel engine to reduce noise, fuel consumption, and exhaust emissions using response surface methodology

2005 ◽  
Vol 219 (10) ◽  
pp. 1181-1192 ◽  
Author(s):  
Z Win ◽  
R P Gakkhar ◽  
S C Jain ◽  
M Bhattacharya
Keyword(s):  
Response Surface Methodology ◽  
Diesel Engine ◽  
Response Surface ◽  
Fuel Consumption ◽  
Parameter Optimization ◽  
Direct Injection ◽  
Engine Performance ◽  
Optimization Techniques ◽  
Injection Timing ◽  
Test Engine

The conflicting effects of the operating parameters and the injection parameter (injection timing) on engine performance and environmental pollution factors is studied in this paper. As an optimization objective, a 3.5 kW small direct injection diesel engine was used as the test engine, and its speed, load, and static injection timing were varied as per 4 × 4 × 3 full factorial design array. Radiated engine noise, smoke level, brake specific fuel consumption, and emissions of unburned hydrocarbons and nitrogen oxides were captured for all test runs. Objective functions relating input and output parameters were obtained using response surface methodology (RSM). Parameter optimization was carried out to control output responses under their mean limit using multi-objective goal programming and minimax programming optimization techniques.

scholarly journals Modeling and Analysis of Machining Parameters and Responses of Wirecut Electric Discharge Machining of Al2124/SiCp using Response Surface Methodology and Soft Computing Techniques

2019 ◽  
Vol 8 (2) ◽  
pp. 5429-5434
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Soft Computing ◽  
Electric Discharge ◽  
Optimization Techniques ◽  
Machining Parameters ◽  
Electric Discharge Machining ◽  
Soft Computing Techniques ◽  
Input Parameters ◽  
Single Objective

In this work, Wirecut Electric Discharge Machining (WEDM) of Al 2124/ SiCp metal matrix composite material is studied to evaluate the influence of input parameters on response characteristics namely, kerf, Material Removal Rate (MMR), Surface Roughness (SR), Recast Layer Thickness (RCT), and Surface Crack Density (SCD). Central composite design, a technique from design of experiments is used to conduct 31 experiments. The input parameters selected for estimation of machinability are pulse on time (Ton), pulse off time (Toff), current (IP), and Servo Voltage (SV). Analysis of variance (ANOVA) is carried out to know the effect of influence parameters on responses. The regression models are developed in Response Surface Methodology (RSM)and are used in soft computing techniques as input equations for optimizing the single and multi-response optimization of response parameters. Desirability approach is used in single and multi-objective optimization of response parameters. Single objective optimization is carried out by RSM, the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Firefly Algorithms (FA). Confirmation experiments are conducted on the adequacy of the mathematical models developed in RSM and it shows good agreement between experimental and predicted values. The variation of predicted responses from different optimization techniques for single objective optimization is found to be less than 1%. From the results it is also observed that for single objective optimization all evolutionary algorithms are found to be suitable for WEDM

Components for Composite Material Customization System

2009 ◽  
Author(s):  
Soumitra Nandi ◽  
Zahed Siddique
Keyword(s):  
Composite Materials ◽  
Material Selection ◽  
Selection Process ◽  
Material Design ◽  
Optimization Techniques ◽  
Conventional Approach ◽  
Wide Range ◽  
Properties Of Materials ◽  
Selection Of

With the advancements of composite materials and research in nano-composites, designers have the flexibility to select materials from a wide range of properties to meet their specific design needs. Even with all these advancements, the material selection process during design follows a very conventional approach. The conventional approach to material design is to select a certain material from a given pre-set material list that allows the attainment of nearest properties required for the product. One of the disadvantages of this approach is that the trade-off inherent in the selection of material, when multiple properties are targeted, can be cumbersome to achieve or addressed at all. In this paper we present an approach to select and design composite materials, where the designer will have flexibility to select multiple properties of materials during the design of a new product. This approach employs an index for selection combined with heuristic optimization techniques to select the optimized combination of composite materials that could meet closest possible property goals. In the case study presented in this paper, we did not perform any optimization; rather, emphasize is given to the explanation of material selection technique, and an RMS value is introduced as an index for the selection.

Design for Injection Molding: Balancing Mechanical Requirements, Manufacturing Costs, and Material Selection

1995 ◽  
Author(s):  
Kurt A. Beiter ◽  
James M. Cardinal ◽  
Kos Ishii
Keyword(s):  
Cycle Time ◽  
Material Selection ◽  
Performance Measure ◽  
Production Costs ◽  
Manufacturing Cost ◽  
Manufacturing Costs ◽  
Time Estimates ◽  
Current Implementation ◽  
Molded Parts ◽  
Design Selection

Abstract This paper describes a procedure for considering mechanical requirements, manufacturing costs, and material selection in the design of injection molded parts. The benefit of this approach is the simultaneous consideration of the implications of material selection and part geometry on estimated manufacturing cost during candidate design selection. The current implementation uses the allowable deflection of a flat plate as an example performance measure. Manufacturability concerns include required part thickness and gating scheme to adequately mold the part, and a resulting cycle time based on part cooling time estimates. Part manufacturing cost includes material cost, cycle time, and production costs. A PC-based and CAD-integrated program illustrate our proposed procedure.

Application of the corrected response surface methodology for the optimization of a permanent magnet synchronous machine

2018 ◽  
Vol 37 (2) ◽  
pp. 740-754 ◽  
Author(s):  
Stéphane Vivier
Keyword(s):  
Optimal Design ◽  
Permanent Magnet ◽  
Response Surface ◽  
Synchronous Machine ◽  
Optimization Techniques ◽  
Permanent Magnet Synchronous Machine ◽  
Optimization Approach ◽  
Content Type ◽  
Coarse Model ◽  
Conventional Optimization

PurposeThis paper aims to introduce an original application of the corrected response surface method (CRSM) in the context of the optimal design of a permanent magnet synchronous machine used as an integrated starter generator. This method makes it possible to carry out this design in a very efficient manner, in comparison with conventional optimization approaches. Design/methodology/approachThe search for optimal conditions is achieved by the joint use of two multi-physics models of the machine to be optimized. The former models most finely the physical functioning of the machine; it is called “fine model”. The second model describes the same physical phenomena as the fine model but must be much quicker to evaluate. Thus, to minimize its evaluation time, it is necessary to simplify it considerably. It is called “coarse model”. The lightness of the coarse model allows it to be used intensively by conventional optimization algorithms. On the other hand, the fine reference model makes it possible to recalibrate the results obtained from the coarse model at any instant, and mainly at the end of each classical optimization. The difference in definition between fine and coarse models implies that these two models do not give the same output values for the same input configuration. The approach described in this study proposes to correct the values of the coarse model outputs by constructing an adjustment (correcting) response surface. This gives the name to this method. It then becomes possible to have the entire load of the optimization carried over to the coarse model adjusted by the addition of this correction response surface. FindingsThe application of this method shows satisfactory results, in particular in comparison with those obtained with a traditional optimization approach based on a single (fine) model. It thus appears that the approach by CRSM makes it possible to converge much more quickly toward the optimal configurations. Also, the use of response surfaces for optimization makes it possible to capitalize the modeling data, thus making it possible to reuse them, if necessary, for subsequent optimal design studies. Numerous tests show that this approach is relatively robust to the variations of many important functioning parameters. Originality/valueThe CRSM technique is an indirect multi-model optimization method. This paper presents the application of this relatively undeveloped optimization approach, combining the features and benefits of (Indirect) efficient global optimization techniques and (multi-model) space mapping methods.

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