scholarly journals Structural analysis and optimization of an automotive propeller shaft

2021 ◽  
Vol 13 (10) ◽  
pp. 168781402110531
Author(s):  
Ji-Won Choi ◽  
Seung-Ho Han ◽  
Kwon-Hee Lee
Keyword(s):  
Structural Analysis ◽  
Weight Reduction ◽  
Optimization Technique ◽  
Kriging Model ◽  
Kriging Interpolation ◽  
Design Stage ◽  
Propeller Shaft ◽  
Power Train ◽  
Steel Material ◽  
Ansys Workbench

It is a trend to implement weight reduction in parts in recent years when developing a new car. This trend is because weight reduction is essential to respond to tightening environmental regulations. In other words, parts manufacturers of body, chassis, and power train systems have made considerable efforts to reduce weight from the proto design stage. This study performed structural analysis and optimization for weight reduction of a propeller shaft for a passenger car. The natural frequency and the durability of the developing propeller shaft were examined through finite element analyses and tests. Then, optimization was accomplished by focusing on the weight reduction of the tubes made of given steel material. In this process, the metamodel-based optimization technique, kriging interpolation, was applied, and the weight was reduced by 5.3% based on the propeller shaft and 14.1% based on the tube. ANSYS Workbench was used for structural analysis, an in-house program was used to build the kriging model, and MATLAB was used for optimization.

Structural Analysis of Electronic Housing Using ANSYS Workbench

2020 ◽  
Author(s):  
Mann Kothari ◽  
Manankumar Patel ◽  
Ulkesh Desai ◽  
Jigar Sura
Keyword(s):  
Structural Analysis ◽  
Electronic Housing ◽  
Ansys Workbench

Optimization Design for the Pressure Shell of Autonomous Underwater Glider Based on GDO Method

2013 ◽  
Vol 312 ◽  
pp. 80-84 ◽  
Author(s):  
Jin Liu ◽  
Yan Hui Wang ◽  
Yu Hong Liu ◽  
Fang Liu
Keyword(s):  
Carrying Capacity ◽  
Weight Reduction ◽  
Total Mass ◽  
Optimization Design ◽  
Underwater Robot ◽  
Underwater Glider ◽  
Effective Measure ◽  
Autonomous Underwater Glider ◽  
Ansys Workbench

Autonomous Underwater Glider (AUG) is a kind of unmanned underwater robot. Weight reduction is an effective measure to extend the duration performance and increase the carrying capacity of the AUG. In this paper, on the basis of the application of ANSYS-workbench, optimization for the structure and mass of the pressure hull of the AUG was conducted through the goal-driven optimization (GDO) method. After optimization, the total mass was reduced from 12.74 kg to 11.06 kg. The present work plays a key role for improving duration performance of AUG.

Enhancement of Labyrinth Seals Efficiency by Means of a Multi-Objective Optimization Technique

2018 ◽  
Author(s):  
Mikhail Gritckevich ◽  
Kunyuan Zhou ◽  
Vincent Peltier ◽  
Markus Raben ◽  
Olga Galchenko
Keyword(s):  
Optimization Technique ◽  
Leakage Flow ◽  
Multi Objective Optimization ◽  
Labyrinth Seals ◽  
Engine Operation ◽  
Turbine Engine ◽  
Multi Objective ◽  
Single Objective ◽  
Ansys Workbench ◽  
Comprehensive Study

A comprehensive study of several labyrinth seals has been performed in the framework of both single-objective and multi-objective optimizations with the main focus on the effect of stator grooves formed due to the rubbing during gas turbine engine operation. For that purpose, the developed optimization workflow based on the DLR-AutoOpti optimizer and ANSYS-Workbench CAE environment has been employed to reduce the leakage flow and windage heating for several seals. The obtained results indicate that the seal designs obtained from optimizations without stator grooves have worse performance during the lifecycle than those with the stator grooves, justifying the importance of considering this effect for real engineering applications.

scholarly journals To Optimize the Deflection of Beams by Conducting Bending Test Using Ansys Workbench 15

2019 ◽  
pp. 238-243
Author(s):  
Mulayam Kumar ◽  
Dr. Simant ◽  
Vijay Gupta
Keyword(s):  
Stainless Steel ◽  
Structural Analysis ◽  
Taguchi Method ◽  
Aluminium Alloy ◽  
Structural Steel ◽  
Cantilever Beam ◽  
Bending Test ◽  
Equivalent Stresses ◽  
Simply Supported ◽  
Ansys Workbench

The present work has been carried out to study the effect of the varying the load at different materials (Aluminium Alloy 7075-T6, stainless steel 305 and Structural Steel 345w) on deflection. The simply supported beam has been subjected to varying load 5000N - 10000N and cantilever beam has been subjected to varying load 500N-1000N. The result obtained is in form of Directional Deflection and Equivalent Stresses. This analysis is done by the ANSYS Workbench 15.0 software under the static structural analysis further this result has been optimized using TAGUCHI METHOD using MINITAB17.

scholarly journals ANALYSIS OF STUDENT FORMULA CAR FOR OPTIMUM SAFETY AND PERFORMANCE

2020 ◽  
pp. 137-142
Author(s):  
Rabi Pathak
Keyword(s):  
Boundary Conditions ◽  
Weight Reduction ◽  
Structural Performance ◽  
Complete Analysis ◽  
Loading Conditions ◽  
Different Types ◽  
And Performance ◽  
Reliability Performance ◽  
Ansys Workbench

The Formula Student competitions are held everyyear. This paper is the result of the analysis done on the sample car design that can be presented in the Formula Student competition. The purpose of the paper is to provide a final summary on chassis analysis and structural performance. It also talks about all the important analysis that is to be done on a Formula Student car to make it safe and perform well on the track. The design has been made such that it focusses on maximum adjustability, reliability, performance, safety, weight reduction and ease of manufacturing. The analysis was done to make sure the objectives of design are fulfilled. After going through many papers, documents, blogs and videos we found that many people get confused about the loading conditions and boundary conditions for different types of tests so this paper prioritizes to make people understand about those conditions as well as about the major tests required to perform complete analysis of Formula Student cars. The weight of the chassis was calculated as 36 kg approximately according to the data obtained from design modeler of Ansys workbench as well as Solidworks. The design sustained all the loading conditions and passed all the tests. Thus, one of the objective of this paper is to help other universities and passionate students to successfully design and analyze their cars that can pass all necessary tests included in the paper. KEYWORDS—Formula Student; FEA; Boundary Conditions; Loading Conditions; Ansys; Solidworks

A Novel Methodology to Manage Uncertainty for Multidisciplinary Design and Optimization in Conceptual Design

2008 ◽  
Vol 44-46 ◽  
pp. 225-232 ◽  
Author(s):  
Xin Yu Shao ◽  
Xue Zheng Chu ◽  
Liang Gao ◽  
Hao Bo Qiu
Keyword(s):  
Conceptual Design ◽  
Probabilistic Method ◽  
Kriging Model ◽  
Design Stage ◽  
Design And Optimization ◽  
Rough Sets Theory ◽  
Innovative Methodology ◽  
Traditional Approaches ◽  
Sets Theory

Uncertainty in design and simulation affects the quality of product directly during the process of MDO, which should be considered to help designers to make the design decisions, especially at conceptual design stage. In traditional approaches, this uncertainty is ignored in the hope that it is not significant to the decision making. In this investigation, firstly, three main uncertainties in MDO of conceptual design are pointed out and carefully analyzed. Then, an innovative methodology integrating extract knowledge and probabilistic method to manage these uncertainties is presented. Considering practical application and eliminating the uncertainty in configuration, we propose a promising method combining Fuzzy c-means algorithm (FCM) and Rough Sets theory (RST) to deduce the configuration rule. Furthermore, probabilistic kriging model is utilized as an approximation model to reduce global computational expense of complex product. Sensitivity analysis (SA) is used to reduce uncertainty of inputs of simulation, and mean square error (MSE) is employed to assess model error to reduce model uncertainty. Finally, the validity and necessity of this methodology are demonstrated through the conceptual design of bulk carrier.

scholarly journals INTERPOLASI KRIGING DALAM PEMODELAN GSTAR-SUR DAN GSTARX-SUR PADA SERANGAN HAMA PENGGEREK BUAH KOPI

2020 ◽  
Vol 13 (1) ◽  
pp. 25-35
Author(s):  
Henny Pramoedyo ◽  
Arif Ashari ◽  
Alfi Fadliana
Keyword(s):  
Forecast Accuracy ◽  
Kriging Model ◽  
Complete Data ◽  
Kriging Interpolation ◽  
Coffee Berry ◽  
Coffee Berry Borer ◽  
Interpolation Technique

The GSTAR and GSTARX models normally can only be formed from observed locations. The problem that sometimes occurs is that not all locations that want to be modeled have complete data as well as other locations. This study uses GSTAR and GSTARX modeling using SUR approach and combines them with the kriging interpolation technique for forecasting coffee berry borer attack in Probolinggo Regency. This modeling is called GSTAR-SUR Kriging and GSTARX-SUR Kriging. This study aims to determine the best model between GSTAR-SUR Kriging and GSTARX-SUR Kriging for forecasting coffee borer attack in an unobserved location. The result of this study shows that GSTAR-SUR Kriging and GSTARX-SUR Kriging models can be used for forecasting coffee berry borer attack in unobserved locations with high forecast accuracy shown by MAPE values <10%. In this study the GSTARX-SUR Kriging model (1,[1,12])(10,0,0) is the best model for forecasting boffee berry borer attacks in unobserved locations.

Curve and Surface Modeling with Uncertainties Using Dual Kriging

1999 ◽  
Vol 121 (2) ◽  
pp. 249-255 ◽  
Author(s):  
A. Limaiem ◽  
H. A. ElMaraghy
Keyword(s):  
Measurement Errors ◽  
Geometric Modeling ◽  
Curve Surface ◽  
Tolerance Analysis ◽  
Kriging Model ◽  
Surface Modeling ◽  
Kriging Interpolation ◽  
Average Deviation ◽  
Dual Kriging ◽  
Potential Applications

This paper presents a new technique based on dual Kriging interpolation for modeling curves and surfaces in the presence of uncertainties in data points. Uncertainties result from measurement errors; therefore, a direct application of this method is found in curve/surface modeling using discrete sets of digitized points. It focuses on a common problem in geometric modeling, the trade-off between curve/surface smoothness and the approximation errors. The Kriging model filters the noise in the data while controlling the deviation locally at each point. However, the classical least-squares technique minimizes the average deviation, hence allowing only a global control of the model. The presented method generates smoother and more accurate representation of the actual curve or surface. It has potential applications in reverse engineering, NC machining, computer-aided inspection and tolerance analysis and verification. Examples of a computer mouse and a portion of the hood of a scaled-down car are presented for illustration.

Efficient uncertainty propagation for MAPOD via polynomial chaos-based Kriging

2019 ◽  
Vol 37 (1) ◽  
pp. 73-92 ◽  
Author(s):  
Xiaosong Du ◽  
Leifur Leifsson
Keyword(s):  
Polynomial Chaos ◽  
State Of The Art ◽  
Uncertainty Propagation ◽  
Kriging Model ◽  
Probability Of Detection ◽  
Kriging Interpolation ◽  
Benchmark Problems ◽  
Content Type ◽  
Order Of Magnitude ◽  
Polynomial Chaos Expansions

Purpose Model-assisted probability of detection (MAPOD) is an important approach used as part of assessing the reliability of nondestructive testing systems. The purpose of this paper is to apply the polynomial chaos-based Kriging (PCK) metamodeling method to MAPOD for the first time to enable efficient uncertainty propagation, which is currently a major bottleneck when using accurate physics-based models. Design/methodology/approach In this paper, the state-of-the-art Kriging, polynomial chaos expansions (PCE) and PCK are applied to “a^ vs a”-based MAPOD of ultrasonic testing (UT) benchmark problems. In particular, Kriging interpolation matches the observations well, while PCE is capable of capturing the global trend accurately. The proposed UP approach for MAPOD using PCK adopts the PCE bases as the trend function of the universal Kriging model, aiming at combining advantages of both metamodels. Findings To reach a pre-set accuracy threshold, the PCK method requires 50 per cent fewer training points than the PCE method, and around one order of magnitude fewer than Kriging for the test cases considered. The relative differences on the key MAPOD metrics compared with those from the physics-based models are controlled within 1 per cent. Originality/value The contributions of this work are the first application of PCK metamodel for MAPOD analysis, the first comparison between PCK with the current state-of-the-art metamodels for MAPOD and new MAPOD results for the UT benchmark cases.

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