Exact solution of elasto-plastic stresses in a metal-matrix composite beam of arbitrary orientation subjected to transverse loads

An analytical elasto-plastic stress analysis is presented for a metal-matrix composite beam of arbitrary orientation subjected to a single transverse force applied to the free end of the beam and a uniformly distributed load. The material is assumed to be perfectly plastic in the elasto-plastic solution. A composite consisting of stainless-steel-reinforced aluminum was produced for this work. Sample problems are given for various orientation angles. Elastic, elastoplastic and residual normal and shear stresses are calculated. The location of the elasto-plastic boundary of the beam is obtained according to the x coordinates of the beam.     

CFD simulation of free-surface flow over triangular labyrinth side weir

Side weirs are extensively used in the hydraulic and environmental engineering applications. The modeling of free surface flow over a labyrinth side weir is a sophisticated problem in the hydraulic engineering. The water surface profiles over the triangular labyrinth side weirs were investigated by many of the researchers experimentally and theoretically. In this study, the free surface flow over the triangular labyrinth side weir was modeled by using Volume of Fluids (VOF) method to describe the flow characteristics in subcritical flow conditions. A valid method, Grid Convergence Index (GCI) was used to determine the numerical uncertainty of the simulation results. The simulation results were compared with experimental observations, and good agreements were obtained between the both results.     

Biofuel supply chain optimal design considering economic,environmental, and societal aspects towards sustainability

Biofuel supply chain design plays a critical role in facilitating the large‐scale substitution of biofuel for traditional fossil fuels with a cost‐effective and environmentally friendly manner towards sustainability. This paper proposes a multiobjective optimization model for a 4‐layer biofuel supply chain network using mixed integer nonlinear programming while considering the benefits from economic, environmental, and societal aspects. The model can be used either to optimize an existing biofuel supply chain network or to guide the construction of a new biofuel supply chain network. The profit, the greenhouse gas emissions in transportation, and the market share of biofuel were set as targets for optimization. The selection of the participators at each layer, and the amount of the material flow between each pair of selected supplier and customer located at two adjacent layers were modeled as decision variables. The conventional weighted aggregation method was used to unify 3 objectives after normalization. Particle swarm optimization was used to solve this high‐dimension multiobjective problem to obtain a near optimal solution. A numerical case study based on the state of Missouri in the United States was implemented to verify the effectiveness of the proposed model. The results of the case study illustrate that the benefits in terms of transportation emission, profit, and market share can be achieved simultaneously. Using the equal weights configuration in conventional weighted aggregation as an example, a 21% reduction of the transportation emission, a 33% increase of the profit, and a 2% augmentation of the market share were achieved compared to the benchmark scenario.     

Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks

International Journal of Computer Vision - Sign languages are multi-channel visual languages, where signers use a continuous 3D space to communicate. Sign language production (SLP), the automatic...     

Sulfurized Co-Mo Alloy Thin Films as Efficient Electrocatalysts for Hydrogen Evolution Reaction

Catalysis Letters - Here, we successfully fabricated sulfurized Co-Mo alloy thin film electrodes with different compositions and studied their catalytic properties for hydrogen evolution reaction...     

Failure Analysis of Two-Dimensional Carbon-Epoxy Composite Plate Pinned Joint

The aim of this study is to investigate failure strength and failure mode of a mechanically fastened carbon-epoxy composite plate of arbitrary orientation. The failure load and the failure mode are analyzed numerically and experimentally. The numerical method includes two steps. First, the stress distribution in the plate is calculated by the use of finite-element method. Second, the failure load and the failure mode are predicted by means of Tsai-Hill and fiber tensile-compressive failure criteria. A computer program was developed which can be used to calculate the failure load, the failure mode, and the propagation of failure. The distance-to-diameter, E/D , and width-to-diameter, W/D , ratios in the plate are changed from 1 to 5 and 2 to 5, respectively. It is found that full bearing strength is developed when E/D and W/D ratios are equal to or greater than 4.     

Artificial neural network approach in printed circuit board assembly

In this study, automation of the circuit board assembly process is considered using artificial neural networks with knowledge-based systems. Basic issues in achieving intelligent control that can adapt to changing conditions in the assembly process are discussed. The feasibility of using neural networks for pattern recognition and optimum component insertion sequence generation is examined. The study provides a basic foundation for designing a conceptual architecture for adaptive intelligent control of circuit board assembly. Real-time testing of component recognition is conducted using adaptive resonance theory (ART 1) as a neural network paradigm.