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Journal of Computing and Information Science in Engineering
EISSN: 1944-7078
ISSN: 1530-98270
Priority: 4
Publisher: American Society of Mechanical Engineers
Description: The Journal of Computing and Information Science in Engineering publishes archival research results and advanced technical applications More ...
Now showing items 881-890 of 1277
Statistical Tolerance Analysis of Over-Constrained Mechanical Assemblies With Form Defects Considering Contact Types
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Tolerance analysis aims toward the verification impact of the individual tolerances on the assembly and functional requirements of a mechanism. The manufactured products have several types of contact and are inherent in ...
Multicomponent Topology Optimization for Additive Manufacturing With Build Volume and Cavity Free Constraints
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Topology optimization for additive manufacturing has been limited to the design of single-piece components that fit within the printer's build volume. This paper presents a gradient-based multicomponent topology optimization ...
Challenges and Status on Design and Computation for Emerging Additive Manufacturing Technologies
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The revolution of additive manufacturing (AM) has led to many opportunities in fabricating complex and novel products. The increase of printable materials and the emergence of novel fabrication processes continuously expand ...
Nonlinear Material Model in Part Variation Simulations of Sheet Metals
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Current methodologies for variation simulation of compliant sheet metal assemblies and parts are simplified by assuming linear relationships. From the observed physical experiments, it is evident that plastic strains are ...
A Generative Human-in-the-Loop Approach for Conceptual Design Exploration Using Flow Failure Frequency in Functional Models1
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A challenge systems engineers and designers face when applying system failure risk assessment methods such as probabilistic risk assessment (PRA) during conceptual design is their reliance on historical data and behavioral ...
Computational Functional Failure Analysis to Identify Human Errors During Early Design Stages
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that ...
Product Architecture Transition in a Modular Cyber-Physical Truck
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A modular product architecture is a strategic means to deliver external variety and internal commonality. In this paper, we propose a new clustering-based method for product modularization that integrates product complexity ...
Automatic Extraction of Engineering Rules From Unstructured Text: A Natural Language Processing Approach
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Manufacturers use cloud manufacturing platforms to offer their services. The literature has suggested a semantic web-based cloud manufacturing framework, in which engineering knowledge is modeled using structured syntax. ...
Boundary Encryption-Based Monte Carlo Learning Method for Workspace Modeling
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: As an important branch of machine learning, Monte Carlo learning has been successfully applied to engineering design optimization and product predictive analysis, such as design optimization of heavy machinery. However, ...
Generative Inverse Design of Aerodynamic Shapes Using Conditional Invertible Neural Networks
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Conditional invertible neural networks (cINNs) were used for generative inverse design of aerodynamic shapes for a given aerodynamic performance target. The methodology was used to generate two-dimensional (2D) airfoil ...