Mechanical Design Synthesis: Proof that Computer Aided Engineering Tools Cut Development Time and Provide Optimal Design

1993 ◽  
Author(s):  
Brent Backhaus
Keyword(s):  
Optimal Design ◽  
Development Time ◽  
Mechanical Design ◽  
Computer Aided Engineering ◽  
Design Synthesis ◽  
Computer Aided

The Research of CAE Active Knowledge Aided System Based on Network

2012 ◽  
Vol 182-183 ◽  
pp. 783-787
Author(s):  
Xi Ai Zhang ◽  
Fei Ma
Keyword(s):  
Mechanical Design ◽  
Computer Aided Engineering ◽  
Design Engineering ◽  
Effective Utilization ◽  
Computer Aided ◽  
Innovation Ability ◽  
Set Up

According to the application status of the Computer Aided Engineering (CAE) in mechanical design field and the higher knowledge threshold that is set up for designer by CAE technique, this paper puts forward to construct a basic prototype of system to provide knowledge assistance for CAE designer with active knowledge assistance method and operation encapsulation based on network. And it is encapsulated as the partner software of the CAE software to realize the effective utilization of the CAE to reduce the learning burden of designer and designing cost. The existence of this aided system promotes the application of CAE in mechanical design engineering and improves the innovation ability.

Structural Durability Design Optimization and Its Reliability Assessment

2003 ◽  
Author(s):  
Kyung K. Choi ◽  
Byeng D. Youn ◽  
Jun Tang
Keyword(s):  
Fatigue Life ◽  
Optimal Design ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Uncertainty Propagation ◽  
Data Communication ◽  
Computer Aided Engineering ◽  
Durability Analysis ◽  
Structural Durability ◽  
Computer Aided

Mechanical fatigue subject to external and inertia transient loads in the service life of mechanical systems often leads a structural failure due to accumulated damage. Structural durability analysis that predicts the fatigue life of mechanical components subject to dynamic stresses and strains is a compute intensive multidisciplinary simulation process, since it requires an integration of several computer-aided engineering tools and large amount of data communication and computation. Uncertainties in geometric dimensions due to manufacturing tolerances cause the indeterministic nature of fatigue life of the mechanical component. Due to the fact that uncertainty propagation to structural fatigue under transient dynamic loading is not only numerically complicate but also extremely expensive, it is a challenging task to develop structural durability-based design optimization process and reliability analysis to ascertain whether the optimal design is reliable. The objective of this paper is development of an integrated CAD-based computer-aided engineering process to effectively carry out the design optimization for a structural durability, yielding a durable and cost-effectively manufacturable product. In addition, a reliability analysis is executed to assess the reliability for the deterministic optimal design.

Self-Moving Tail Prototyping and Structural Improvements

2013 ◽  
Vol 744 ◽  
pp. 153-156
Author(s):  
Jin Cheng ◽  
Yong Cun Guo
Keyword(s):  
Research And Development ◽  
Mechanical Design ◽  
Virtual Prototyping ◽  
Computer Aided Engineering ◽  
Surface Level ◽  
Computer Aided ◽  
Technology Applications ◽  
Virtual Prototyping Technology

virtual prototyping technology 1980s developed a computer-aided engineering and virtual prototyping technology applications in the research and development of self-moving tail can greatly enhance progress in the development of the mechanical design of fully mechanized coal miningthe surface level of mechanization upgrade of great significance.

On the evolution of CAE research

1994 ◽  
Vol 8 (4) ◽  
pp. 275-282 ◽  
Author(s):  
Clive L. Dym ◽  
Raymond E. Levitt
Keyword(s):  
Artificial Intelligence ◽  
Computer Aided Engineering ◽  
Computer Support ◽  
Engineering Analysis ◽  
New Paradigm ◽  
Design Synthesis ◽  
Engineering Research ◽  
Open Questions ◽  
Computer Aided ◽  
Separate Discipline

AbstractLess than a decade ago it seemed that a new paradigm of engineering–called computer-aided engineering (CAE) – was emerging. This emergence was driven in part by the success of computer support for the tasks of engineering analysis and in part by a new understanding of how computational ideas largely rooted in artificial intelligence (AI) could perhaps improve the practice of engineering, especially in the area of design synthesis. However, while this “revolution” has failed to take root or flourish as a separate discipline, it has spawned research that is very different from traditional engineering research. To the extent that such CAE research is different in style and paradigm, it must also be evaluated according to different metrics. Some of the metrics that can be used are suggested, and some of the evaluation issues that remain as open questions are pointed out.

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