Modeling of friction-stir butt-welds and its application in automotive bumper impact performance Part 1. Thermo-mechanical weld process modeling

The demand for better structural performance in joining of components for road vehicles prompts the implementation of aluminum alloy friction stir welding technology in the automotive industry. The aim of current study is the creation of a 3-D finite element (FE) friction thermal model and stir welding (FSW) process of dissimilar aluminum alloy and for the estimation of crash worthiness performance of FSW fabricated shock absorber assembly. Thermo mechanical simulations and analysis are performed to understand the thermal behavior in the FSW weld zones. The developed models are correlated against published experimental results in terms of temperature profile of the weld zone. The developed models are then implemented for fabricating vehicle bumper parts to illustrate the performance of FSW welded components during an impact. Customary sled testing for low-speed guard necessities is performed utilizing a grating blend welded test apparatus at Wichita State University (WSU) at the National Institute for Aviation Research (NIAR). A few guard congregations are then appended to the test installation utilizing FSW and conventional Gas bend GMAW welding strategies. Numerical models are likewise created where limited component investigation is utilized to contrast the anticipated harm and the real harm maintained by both of the FSW and GMAW manufactured guards. During the research, a new FSW weld mold is created that allows for a better representation of the desired progressive crack propagation. The FSW fabricated bumper based on the Johnson-Cook failure model yields better failure prediction and is in good agreement to the test. The results from this study provide a guideline for an accurate finite element modeling of a FSW fabricated components and their application in the crashworthiness of such structural components.     

Non-unified Compact Residual-Distribution Methods for Scalar Advection–Diffusion Problems

This paper solves the advection–diffusion equation by treating both advection and diffusion residuals in a separate (non-unified) manner. An alternative residual distribution (RD) method combined with the Galerkin method is proposed to solve the advection–diffusion problem. This Flux-Difference RD method maintains a compact-stencil and the whole process of solving advection–diffusion does not require additional equations to be solved. A general mathematical analysis reveals that the new RD method is linearity preserving on arbitrary grids for the steady-state advection–diffusion equation. The numerical results show that the flux difference RD method preserves second-order accuracy on various unstructured grids including highly randomized anisotropic grids on both the linear and nonlinear scalar advection–diffusion cases.     

Damping vibration behavior of visco-elastically coupled double-layered graphene sheets based on nonlocal strain gradient theory

Microsystem Technologies - This paper develops a nonlocal strain gradient plate model for damping vibration analysis of visco-elastically coupled double-layered graphene sheets. For more accurate...     

In-situ EQCM evaluation of the formation of UPD and OPD during electrodeposition of Pb on gold

Underpotential (UPD) and overpotential (OPD) deposition of Pb from a perchlorate solution on gold substrate was studied using in-situ electrochemical quartz crystal microbalance (EQCM) method. Cyclic voltammograms and current-transients recorded during potentiostatic electrochemical deposition were measured simultaneously with EQCM data including frequency and resistance. Results show that underpotential deposition (UPD) of Pb occurs before overpotential deposition (OPD) of Pb starts to grow, based on both massogram and cyclic voltammogram. The OPD of Pb grows at higher overpotentials which significantly influence the mechanism of nucleation and growth. EQCM reveals that the mass to charge ratio of OPD is different at different overpotentials, owing to the mechanism of nucleation and growth and possible roughening of grown Pb or hydrogen evolution. A comparison between our experimental data with the Scharifker-Hills theory based on non-dimensional plots shows an instantaneous mechanism. Scanning electron microscope taken from the electrodeposited lead on gold confirms the behaviour exhibiting almost same size of nuclei.     

Cross section recondensation method via generalized energy condensation theory

The standard multigroup method used in whole-core reactor analysis relies on energy condensed (coarse-group) cross sections generated from single lattice cell calculations, typically with specular reflective boundary conditions. Because these boundary conditions are an approximation and not representative of the core environment for that lattice, an error is introduced in the core solution (both eigenvalue and flux). As current and next generation reactors trend toward increasing assembly and core heterogeneity, this error becomes more significant. The method presented here corrects for this error by generating updated coarse-group cross sections on-the-fly within whole-core reactor calculations without resorting to additional cell calculations. In this paper, the fine-group core flux is unfolded by making use of the recently published Generalized Condensation Theory and the cross sections are recondensed at the whole-core level. By iteratively performing this recondensation, an improved core solution is found in which the core-environment has been fully taken into account. This recondensation method is both easy to implement and computationally very efficient because it requires precomputation and storage of only the energy integrals and fine-group cross sections. In this work, the theoretical basis and development of cross section recondensation is presented, and the method is verified with several sample problems.     

Study of payment scheduling problem to achieve client–contractor agreement

This paper aims to determine simultaneously the amount, timing, and location of progress payments in projects in order to achieve a set of equitable solutions in the client–contractor negotiation process. The objective function tries to minimize the distance between the final solutions and the best achievable solutions of the client and the contractor. Due to combinatorial nature of the proposed problem, an iterative two-stage search method is proposed. In the first stage, a set of payments is determined to maximize the contractor's net present value (NPV), another set to maximize the client's NPV, and another one to minimize the objective function. In the second stage, activities are rescheduled to improve the solutions by fixing the amount and location of progress payments. A hybrid meta-heuristic algorithm named GASA, along with a simulated annealing (SA) and a genetic algorithm (GA), is introduced for the first stage, while the activities are optimally scheduled in the second stage. It has been shown that SA is better for the contractor’s objective function and GA for the client’s objective function, but GASA is the best in all situations; besides, the proposed method has represented to be an efficient approach to obtain non-dominated solutions in the client–contractor negotiation process.     

Innovation in artificial neural network learning: Learn-On-Demand methodology

The artificial neural networks represent the state of the art tool for forecasting and prediction. However, the technique relies heavily on the availability of adequate data for its training. There have been many attempts to overcome the problems associated with the acquisition of learning data. These include the use of simulation techniques, which prepare the data for pre-processing prior to learning. Nevertheless, these methods tend to undermine the specific nature of the application that is reflected in its data. Furthermore, it is evident that, in certain circumstances, the current learning methods, grouped under on-line and off-line, do not provide an effective learning solution and their advantages are mutually exclusive. With these problems in mind, this research proposes a method for rectifying these shortcomings. The solution focuses on the learning processes rather than data. The work offers a new learning mechanism, namely the “Learn-On-Demand” (LOD) methodology, which enables the ANN to learn where the lack of knowledge is evident. The proposed LOD methodology integrates into ANN's learning process. Having produced the algorithm for its implementation, the paper then produces the mathematical representation of the Learn-On-Demand methodology by integrating the new algorithm into existing methodologies. The need for this solution emerged out of a research in the field of construction, where Structured Systems Analysis and Design was sued as a platform for integrating a hybrid of AI techniques in order to develop an enhanced method of client briefing.     

Using plasmonic cloaking method on infinite cylindrical structures and its applications

Journal of Computational Electronics - In recent years, cloaking using materials with negative electric permittivity or magnetic permeability has been studied and researched. It has been...     

Investigation of effective dimensionless numbers on initiation of instability in combustion of moisty organic dust简

In this work, the effect of various effective dimensionless numbers and moisture contents on initiation of instability in combustion of moisty organic dust is calculated. To have reliable model, effect of thermal radiation is taken into account. One- dimensional flame structure is divided into three zones： preheat zone, reaction zone and post-flame zone. To investigate pulsating characteristics of flame, governing equations are rewritten in dimensionless space-time （（, r/, ~） coordinates. By solving these newly achieved governing equations and combining them, which is completely discussed in body of article, a new expression is obtained. By solving this equation, it is possible to predict initiation of instability in organic dust flame. According to the obtained results by increasing Lewis number, threshold of instability happens sooner. On the other hand, pulsating is postponed by increasing Damk6hler number, pyrolysis temperature or moisture content. Also, by considering thermal radiation effect, burning velocity predicted by our model is closer to experimental results.     

Observer-based reliable control for Lipschitz nonlinear networked control systems with quadratic protocol

International Journal of Control, Automation and Systems - In this paper, observer-based reliable control problem for nonlinear networked control systems (NCSs) with quadratic protocol (QP) in...