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The purpose of this study is to investigate the bending analysis of metal (Ti-6Al-4V)-ceramic (ZrO₂) functionally graded material (FGM) sandwich plate with material property gradation along length and thickness direction under thermo-mechanical loading using inverse trigonometric shear deformation theory (ITSDT). FGM sandwich plate with a ceramic core and continuous variation of material properties has been modelled using Voigt’s micro-mechanical model following the power law distribution method. The impact of bi-directional gradation of material properties over the bending response of FGM plate under thermo-mechanical loading has been investigated in this work.

In this study, gradation of material properties for FGM plates is considered along length and thickness directions using Voigt’s micromechanical model following the power law distribution method. This type of FGM is called bi-directional FGMs (BDFGM). Mechanical and thermal properties of BDFGM sandwich plates are considered temperature-dependent in the present study. ITSDT is a non-polynomial shear deformation theory which requires a smaller number of field variables for modelling of displacement function in comparison to poly-nominal shear deformation theories which lead to a reduction in the complexity of the problem. In the present study, ITSDT has been utilized to obtain the governing equations for thermo-mechanical bending of simply supported uni-directional FGM (UDFGM) and BDFGM sandwich plates. Analytical solution for bending analysis of rectangular UDFGM and BDFGM sandwich plates has been carried out using Hamilton’s principle.

The bending response of the BDFGM sandwich plate under thermo-mechanical loading has been analysed and discussed. The present study shows that centre deflection, normal stress and shear stress are significantly influenced by temperature-dependent material properties, bi-directional gradation exponents along length and thickness directions, geometrical parameters, sandwich plate layer thickness, etc. The present investigation also reveals that bi-directional FGM sandwich plates can be designed to obtain thermo-mechanical bending response with an appropriate selection of gradation exponents along length and thickness direction. Non-dimensional centre deflection of BDFGM sandwich plates decreases with increasing gradation exponents in length and thickness directions. However, the non-dimensional centre deflection of BDFGM sandwich plates increases with increasing temperature differences.

For the first time, the FGM sandwich plate with the bi-directional gradation of material properties has been considered to investigate the bending response under thermo-mechanical loading. In the literature, various polynomial shear deformation theories like first-order shear deformation theory (FSDT), third-order shear deformation theory (TSDT) and higher-order shear deformation theory (HSDT) have been utilized to obtain the governing equation for bending response under thermo-mechanical loading; however, non-polynomial shear deformation theory like ITSDT has been used for the first time to obtain the governing equation to investigate the bending response of BDFGM. The impact of bi-directional gradation and temperature-dependent material properties over centre deflection, normal stress and shear stress has been analysed and discussed.

This study aims to demonstrate the numerical application of differential quadrature (DQ) methods and show the experimental application of free vibration analysis of fiber-metal laminated composite (FML) plates with various boundary conditions.

The FMLs are hybrid structures consisting of fiber-reinforced polymer matrix composites such as carbon, glass, aramid and different metal sheets, and are currently widely used in the automobile, aircraft and aerospace industries. Thus, free vibration analysis of these hybrid materials is necessary for the design process. The governing equations of motion are derived based on the classical plate theory. The DQ, generalized DQ (GDQ) and harmonic DQ (HDQ) differential quadrature methods have been used to solve the governing equations of an FML composite plate numerically. The accuracy and convergence of the numerical model have been verified by comparing the results available in the published literature with the results obtained from these methods. Moreover, an experimental procedure has been performed in order to compare the results against those of the numerical methods.

It is noteworthy that a high degree of similarity and accuracy was observed between the numerical results obtained by the DQ methods and the experimental results. Thus, the present study validates the applicability of the DQ methods for designing the FML composite plates.

In this study, the advantages of the DQ methods have been demonstrated differently from previous studies on the vibration analysis of the FML plates.

This paper aims to develop an optimization model to enhance pipeline assembly performance. It focuses on predicting the pipeline’s assembly pose while ensuring compliance with clamp constraints.

The assembly pose of the pipeline is quantitatively assessed by a proposed indicator based on joint defects. The assembly interference between the pipeline and assembly boundary is characterized quantitatively. Subsequently, an analytical mapping relationship is established between the assembly pose and assembly interference. A digital fitting model, along with a novel indicator, is established to discern the fit between the pipeline and clamp. Using the proposed indicators as the optimization objective and penalty term, an optimization model is established to predict the assembly pose based on the reinforced particle swarm optimization, incorporating a proposed adaptive inertia weight.

The optimization model demonstrates robust search capability and rapid convergence, effectively minimizing joint defects while adhering to clamp constraints. This leads to enhanced pipeline assembly efficiency and the achievement of a one-time assembly process.

The offset of the assembly boundary and imperfections in pipeline manufacturing may lead to joint defects during pipeline assembly, as well as failure in the fit between the pipeline and clamp. The assembly pose predicted by the proposed optimization model can effectively reduce the joint defects and satisfy clamp constraints. The efficiency of pipeline modification and assembly has been significantly enhanced.

The newsvendor problem is fundamental to many operations management models. The problem focuses on the trade-off between the gains from satisfying demand and losses from unsold products. The newsvendor model and its extensions have been applied to various areas, such as production plan and supply chain management. This chapter examines the study about newsvendor problem. In this research, there is a review of the contributions for the multiproduct newsvendor problem. It focuses on the current literature concerning the mathematical models and the solution methods for the multiitem newsvendor problems with single or multiple constraints, as well as with the risks. The objective of this research is to go over the newsvendor problem and bring into comparison different newsvendor models applied to the flower industry. A few case studies are described addressing topics related to the newsvendor problem such as discounting and replenishment policies, inventory inaccuracies, or demand estimation. Three newsvendor models are put into practice in the field of flower selling. A full database of the flowers sold by an anonymous retailer is available for the study. Computational experiments for practical example have been conducted with use of the CPLEX solver with AMPL programming language. Models are solved, and an analysis of different circumstances and cases is accomplished.

Nowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing style and color design via computer language, which aims to edit and control the garment image based on the specified target attributes while preserving other details from the original image. The current image attribute editing model often generates images containing missing or redundant attributes. To address the problem, this paper aims for a novel design method utilizing the Fashion-attribute generative adversarial network (AttGAN) model was proposed for image attribute editing specifically tailored to women’s blouses.

The proposed design method primarily focuses on optimizing the feature extraction network and loss function. To enhance the feature extraction capability of the model, an increase in the number of layers in the feature extraction network was implemented, and the structure similarity index measure (SSIM) loss function was employed to ensure the independent attributes of the original image were consistent. The characteristic-preserving virtual try-on network (CP_VTON) dataset was used for train-ing to enable the editing of sleeve length and color specifically for women’s blouse.

The experimental results demonstrate that the optimization model’s generated outputs have significantly reduced problems related to missing attributes or visual redundancy. Through a comparative analysis of the numerical changes in the SSIM and peak signal-to-noise ratio (PSNR) before and after the model refinement, it was observed that the improved SSIM increased substantially by 27.4%, and the PSNR increased by 2.8%, serving as empirical evidence of the effectiveness of incorporating the SSIM loss function.

The proposed algorithm provides a promising tool for precise image editing of women’s blouses based on the GAN. This introduces a new approach to eliminate semantic expression errors in image editing, thereby contributing to the development of AI in clothing design.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

This paper considers an option contract in a two-stage supplier-retailer supply chain (SC) when market demand is stochastic. The problem is a Stackelberg game with the supplier as a leader. This research assumes demand information sharing. The purpose of this study is to determine the optimal pricing strategy of the supplier along with the optimal order strategy of the retailer in three option contract cases.

The paper model the option contract pricing problem as a bilevel problem. The problem is then solved using bilevel programing methods. After computing, the generated outcomes are compared to a benchmark (wholesale price contract) to evaluate the contract.

The results reveal that only one of the contract cases can arbitrarily allocate the SC profit. In both other cases, the Stackelberg supplier manages to earn the total SC profit. Further analysis of the first contract, show that from the supplier’s perspective, the first stage forecast inaccuracy is beneficial, whereas the demand uncertainty in the second stage is detrimental. This contracting strategy guarantees both players better outcomes compared to the wholesale price contract.

To the best of the authors’ knowledge, this research is the first that links the option contract literature to the bilevel programing literature. It also the first to solve the pricing problem of the commitment option contract with demand update where the retailer exercises the option before knowing the exact demand.

The purpose of this study is to regard winter heating as a quasi-natural experiment to identify the possible causal effects of winter heating on population mobility. However, there are scant research studies examining the effect of atmospheric quality on population mobility. There also exists some relevant research studies on the relationship between population mobility and environmental degradation (Lu et al., 2018; Reis et al., 2018; Shen et al., 2018), and these studies exist still some deficiencies.

The notorious atmospheric quality problems caused by coal-fired heating in winter of northern China have an aroused widespread concern. However, the quantitative study on the effects on population mobility of winter heating is still rare. In this study, the authors regard the winter heating as a quasi-natural experiment, based on the of daily panel data of 58 cities of Tencent location Big Data in China from August 13 to December 30 in 2016 and August 16 to December 30 in 2017, and examine the impacts of winter heating on population mobility by utilizing a regression discontinuity method.

The findings are as follows, in general, winter heating significantly aggravates regional population mobility, but the impacts on population mobility among different cities are heterogeneous. Specifically, the effects of winter heating on population mobility is greater for cities with relatively good air quality, and the effects is also more obvious for big and medium-sized cities than that in small cities. In addition, different robustness tests, including continuity test, different bandwidth tests and alternative empirical model, are adopted to ensure the reliability of the conclusion. Finally, the authors put forward corresponding policy suggestions from the three dimensions of government, enterprises and residents.

First, regarding winter heating as a quasi-natural experiment, a regression discontinuity design method is introduced to investigate the relationship between winter heating and population mobility, which is helpful to avoid the estimation error caused by endogeneity. Second, the authors use the passenger travel “big data” based on the website of Tencent Location Big Data, which can effectively capture the daily characteristics of China's population mobility. Third, this study discusses the population mobility from the perspective of winter heating and researches population mobility before and after winter heating, which is helpful in enriching the research on population mobility.

This paper aims to propose the new two-step adaptive direct slicing method for building bio-scaffold with digital micro-mirror device (DMD)-based MPμSLA systems.

In this paper, the authors proposed a new approach to directly slice a scaffold’s CAD model (i.e the three-dimensional model built by computer-aided design platforms) and save the slices’ data as BMP (bitmap, i.e. the data format used in DMD) files instead of other types of two-dimensional patterns as an intermediary. The proposed two-step strategy in this paper, i.e. a CAD model’s exterior surface and internal architecture were sliced, respectively, at first, and then assembled together to obtain one intact slice. The assembly process is much easier and convenient based on the slice data in BMP format. To achieve the adaptive slicing for both the exterior part and internal part, two new indices, the exterior surface-dominated index and internal architecture-dominated index, are, respectively, utilized as the error estimation indices. The proposed approach in this paper is developed on SolidWorks platform, but it can also be implemented on other platforms.

The authors found that the approach is not only more accurate but also more efficient by avoiding the repeated running of those inefficient rasterization programs. The approach is able to save computer resource and time, and enhance the robustness of slicing program, as well as is appropriate for the scaffolds’ model with internal pore architecture and external free-form surface.

Bio-scaffolds in tissue engineering require precise control over material distribution, such as the porosity, connectivity, internal pore architecture and external free-form surface. The proposed two-step adaptive direct slicing approach is a good balance of slicing efficiency and accuracy and can be useful for slicing bio-scaffolds’ models.

This paper gives supports to build bio-scaffold with DMD-based MPμSLA systems.

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea, wind energy has great potential to become the primary energy. As a critical part of the wind turbine, the gearbox of a wind turbine often bears a large external load. Especially at sea, due to the effects of ocean corrosion, waves and wind, the burden of the wind turbine gearbox is greater, which brings great challenges to its reliability analysis. This study aims to systematically review the reliability research in wind turbine gearboxes and guide future research directions and challenges.

This study systematically reviews some design requirements and reliability analysis methods for wind turbine gearboxes. Then, it summarizes previous studies on wind load uncertainty modeling methods, including the processing of wind measurement data and the summary of three different classifications of random wind speed prediction models. Finally, existing reliability analysis studies on two major parts of the gearbox are described and summarized.

First, the basic knowledge of wind turbine gearboxes and their reliability analysis is introduced. The requirements and reliability analysis methods of wind turbine gearboxes are explained. Then, the processing methods of wind measurement data and three different random wind speed prediction models are described in detail. Furthermore, existing reliability analysis studies on two common parts of wind turbine gearboxes, gears and bearings, are summarized and classified, including a summary of bearing failure modes. Finally, three possible future research directions for wind turbine gearbox reliability analysis are discussed, namely, reliability research under the influence of multiple factors on gears, damage indicators of bearing failure modes and quantitative evaluation criteria for the overall dynamic characteristics of offshore wind turbine gearboxes and a summary is also given.

This paper aims to systematically introduce the relevant contents of wind turbine gearboxes and their reliability analysis. The contents of wind speed data processing, predictive modeling and reliability analysis of major components are also comprehensively reviewed, including the classification and principle introduction of these contents.