Joint Effect of the Nonlinearity of Elastic Foundations and the Variation of the Inertia Ratio on Buckling Behavior of Prismatic and Nonprismatic Columns Using a GDQ MethodRead the full article
Mathematical Problems in Engineering is a broad-based journal publishes results of rigorous engineering research across all disciplines, carried out using mathematical tools.
Chief Editor, Professor Guangming Xie, is currently a full professor of dynamics and control with the College of Engineering, Peking University. His research interests include complex system dynamics and control and intelligent and biomimetic robots.
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Deep Forest-Based Fault Diagnosis Method for Chemical Process
With the rapid expanding of big data in all domains, data-driven and deep learning-based fault diagnosis methods in chemical industry have become a major research topic in recent years. In addition to a deep neural network, deep forest also provides a new idea for deep representation learning and overcomes the shortcomings of a deep neural network such as strong parameter dependence and large training cost. However, the ability of each base classifier is not taken into account in the standard cascade forest, which may lead to its indistinct discrimination. In this paper, a multigrained scanning-based weighted cascade forest (WCForest) is proposed and has been applied to fault diagnosis in chemical processes. In view of the high-dimensional nonlinear data in the process of chemical industry, WCForest first designs a set of relatively suitable windows for the multigrained scan strategy to learn its data representation. Next, considering the fitting quality of each forest classifier, a weighting strategy is proposed to calculate the weight of each forest in the cascade structure without additional calculation cost, so as to improve the overall performance of the model. In order to prove the effectiveness of WCForest, its application has been carried out in the benchmark Tennessee Eastman (TE) process. Experiments demonstrate that WCForest achieves better results than other related approaches across various evaluation metrics.
A Theoretical Calculation Method of Influence Radius of Settlement Based on the Slices Method in Tunnel Construction
At present, the empirical formula is used to calculate the influence radius of surface settlement and the width of settlement trough, which lacks theoretical support. Aiming at this problem, this paper derived the theoretical calculation formula for predicting the influence radius of formation settlement based on the slices method. Then, the expression of the width of settlement trough was obtained according to the relationship between the settlement influence radius and the settlement trough width. The rationality of the formula was verified by the Heathrow Express tunnel and the Green Park tunnel. Through analysis and discussion, it was found that in the clay stratum, the settlement calculation formula can more accurately predict the surface settlement, while there is a big error in predicting the stratum settlement within 4d near the tunnel vault. In the sand layer, the internal friction angle is less than 40°, and the reinforcement surface is applied to the unsupported face to reduce the radius of influence; in the clay formation, when the cohesion is less than 50 kPa, the influence radius can be reduced by applying reinforcement measure to the unsupported face.
Biobjective Emergency Logistics Scheduling Model Based on Uncertain Traffic Conditions
Emergency logistics scheduling appears more and more important in modern society because of frequent occurrence of unpredictable disasters. Most of the existing studies consider a certain emergency logistics scheduling model, and most of them are based on an ideal scenario. Considering the uncertain traffic condition and the real road condition, a biobjective emergency logistics scheduling model is proposed, which includes two objectives: transportation time and transportation cost. The uncertainty of the proposed model is reflected in two aspects: the occurrence time of emergencies and the traffic volume predicted by the cloud model. The numerical characteristics of traffic information are abstracted from the spatial-temporal trajectory data by the reverse cloud model, and the inference procedure of the one-dimension cloud model further predicts the uncertain traffic volume using the numerical characteristics. In addition, the crossover and mutation operators of multiobjective evolutionary algorithms are modified to solve the model. The experimental results show that the inference procedure of one-dimension cloud model can accurately predict the traffic volume at the departure time; and the proposed model is more reasonable than the existing scheduling models; at the same time, the improved NSGA-II can also provide superior schemes in different departure times and traffic conditions for decision makers.
PSS Parameter Optimization Based on Comprehensive Damping Effect Method Aiming at Actual Grid Characteristics in Northern China
In this paper, we proposed the comprehensive damping effect method to optimize the PSS parameters. Different from other studies, the optimization in this paper is based on both the amplitude-frequency and the phase-frequency properties, while other studies mainly focus on the phase-frequency characteristics. The actual grid data in Northern China are employed to verify the optimization effect in the multimachine system. The proposed method is compared with the engineering method, the existing optimization method, and the commercial software. The comparison shows that the PSS parameters obtained by the proposed method in this paper are superior to those obtained by the engineering experience, the phase-frequency optimization method, and the commercial software. In the cases of different phase-frequency range requirements, the wider the phase-frequency range is, the better the damping effect of the obtained parameters will be.
A Generation of Special Triangular Boundary Element Shape Functions for 3D Crack Problems
This paper focuses on tackling the two drawbacks of the dual boundary element method (DBEM) when solving crack problems with a discontinuous triangular element: low accuracy of the calculation of integrals with singularity and crack front element must be utilized to model the square-root property of displacement. In order to calculate the integrals with higher order singularity, the triangular elements are segmented into several subregions which consist of subtriangles and subpolygons. The singular integrals in those subtriangles are handled by the singularity subtraction technique in the integration space and can be regularized and accurately calculated. For the nearly singular integrals in those subpolygons, the element subdivision technique is employed to improve the calculation accuracy. In addition, considering the location of the crack front in the element, special crack front elements are constructed based on a 6-node discontinuous triangular element, in which the displacement extrapolation method is introduced to obtain the stress intensity factors (SIFs) without consideration of orthogonalization of the crack front mesh. Several numerical results are investigated to fully verify the validation of the presented approach.
Research on Two-Stage Joint Optimization Problem of Green Manufacturing and Maintenance for Semiconductor Wafer
This paper proposes a two-stage joint optimization problem of green manufacturing and maintenance for semiconductor wafer (TSGMM-SW) considering manufacturing stage, inspection, and repair stage simultaneously, which is a typical NP-hard problem with practical research significance and value. Aiming at this problem, a green scheduling model with the objective of minimizing makespan, total carbon emissions, and total preventive maintenance (PM) costs is constructed, and an improved hybrid multiobjective multiverse optimization (IHMMVO) algorithm is proposed in this paper. The joint optimization of green manufacturing and maintenance is realized by designing synchronous scheduling and maintenance strategy for wafer manufacturing and equipment PM. The diversity of the population is expanded and the optimization performance of IHMMVO is improved by designing the initial population fusion strategy and subpopulation evolution strategy. In the experimental phase, we perform the simulation experiments of 900 test cases randomly generated from 90 parameter combinations. The IHMMVO algorithm is compared with other existing algorithms to verify the effectiveness and feasibility for TSGMM-SW.