The Structure Design and Parametric Study of Dynamic and Static Grinding Head

Based on the second development platform of CAXA electronic board, using the object-oriented programming method and vc++6.0 as the second development language, combining with the user's actual production, the structure of dynamic and static grinding head has been analyzed and the parameters of dynamic and static grinding head have been determineed. A system with friendly interface, clear structure, convenient operation has been designed which can realize the structure parametric design of dynamic and static grinding head.

Download Full-text

VIRTUAL IMPLEMENTATION OF RC FRAMES PUSH-OVER TEST BASED ON THE OBJECT-ORIENTED PROGRAMMING METHOD

Tall Buildings ◽

10.1142/9789812701480_0086 ◽

2005 ◽

Author(s):

YUSHI ZHOU ◽

XIAN LIU ◽

YONG YUAN

Keyword(s):

Object Oriented ◽

Object Oriented Programming ◽

Programming Method ◽

Rc Frames

Download Full-text

Visual Computation of Thermohydrodynamic Lubrication of Dynamically Loaded Journal Bearings

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.97-101.3781 ◽

2010 ◽

Vol 97-101 ◽

pp. 3781-3784

Author(s):

Jian Ping Yuan ◽

Zhi Xia He ◽

Qian Wang ◽

Ju Yan Liu

Keyword(s):

Reynolds Equation ◽

Energy Equation ◽

Object Oriented ◽

Journal Bearings ◽

Object Oriented Programming ◽

Connecting Rod ◽

Development Platform ◽

Dynamically Loaded ◽

Automobile Engines ◽

Thermal Balance Equation

The Reynolds equation and energy equation with the thermal balance equation in combination were applied to build the thermohydrodynamic (THD) computational model of the dynamically loaded journal bearings. The most popular development platform——Visual C ++ in the field of computer science and the drawing platform of AutoCAD were combined with the medium of ObjectARX and the object oriented programming technology was used, on the basis of which, the visual computational software of the THD lubrication of the dynamically loaded journal bearings for main shaft and connecting rod bearings of automobile engines was developed. The analysis results of an example indicate that the bearing behaviors are closely tied to the radial clearances and inlet lubricant temperature of the bearing.

Download Full-text

Intelligent Design Prediction Aided by Non-Uniform Parametric Study and Machine Learning in Feature Based Product Development

10.1115/detc2021-67923 ◽

2021 ◽

Author(s):

Satchit Ramnath ◽

Jiachen Ma ◽

Jami J. Shah ◽

Duane Detwiler

Keyword(s):

Machine Learning ◽

Parametric Study ◽

Parametric Design ◽

Learning Algorithm ◽

Structure Design ◽

Data Sets ◽

Element Analysis ◽

Automotive Body ◽

Current Design ◽

Feature Based

Abstract Automotive body structure design is critical to achieve lightweight and crash worthiness based on engineers’ experience. In the current design process, it frequently occurs that designers use a previous generation design to evolve the latest designs to meet certain targets. However, in this process the possibility of adapting design ideas from other models is unlikely. The uniqueness of each design and presence of non-uniform parameters further makes it difficult to compare two or more designs and extract useful feature information. There is a need for a method that will fill the missing gap in assisting designers with better design options. This paper aims to fill this gap by introducing an innovative approach to use a non-uniform parametric study with machine learning in order to make valuable suggestions to the designer. The proposed method uses data sets produced from experiment design to reduce the number of parameters, perform parameter correlation studies and run finite element analysis (FEA), for a given set of loads. The response data generated from this FEA is then used in a machine learning algorithm to make predictions on the ideal features to be used in the design. The method can be applied to any component that has a feature-based parametric design.

Download Full-text