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Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The purpose of this paper is to investigate the fault estimation issue of nonlinear dynamical systems via distributed sensor networks. Furthermore, based on the communication topology of sensor networks, the nonfragile design strategy considering the gain fluctuation is also adopted for distributed fault estimators.

By means of intensive dynamical model transformation, sufficient conditions with disturbance attenuation performance are established to design desired fault estimator gains with the help of convex optimization.

A novel distributed fault estimation framework for a class of nonlinear dynamical systems is established over a set of distributed sensor networks, where sampled data of sensor nodes via local information exchanges can be used for more efficiency.

The proposed distributed fault estimator gain fluctuations are taken into account for the nonfragile strategy, such that the distributed fault estimators are more applicable for practical sensor networks implementations. In addition, an illustrative example with simulation results are provided to validate the effectiveness and applicableness of the developed distributed fault estimation technique.

Recently, deep reinforcement learning is developing rapidly and shows its power to solve difficult problems such as robotics and game of GO. Meanwhile, satellite attitude control systems are still using classical control technics such as proportional – integral – derivative and slide mode control as major solutions, facing problems with adaptability and automation.

In this paper, an approach based on deep reinforcement learning is proposed to increase adaptability and autonomy of satellite control system. It is a model-based algorithm which could find solutions with fewer episodes of learning than model-free algorithms.

Simulation experiment shows that when classical control crashed, this approach could find solution and reach the target with hundreds times of explorations and learning.

This approach is a non-gradient method using heuristic search to optimize policy to avoid local optima. Compared with classical control technics, this approach does not need prior knowledge of satellite or its orbit, has the ability to adapt different kinds of situations with data learning and has the ability to adapt different kinds of satellite and different tasks through transfer learning.

This study aims to investigate the crevice corrosion behavior of carbon steel in neutral/alkaline environments utilizing a transient multi-physics field model.

The crevice corrosion of carbon steel with different solution pH and crevice width was modeled, incorporating mass transfer, homogeneous phase and localized electrochemical reactions. The extent of crevice corrosion was evaluated by the geometric deformation of the model mesh. The hydro-chemical state inside the crevice was discussed through the Cl⁻ concentration and potential distribution of the solution.

Results revealed that the formation of pitting corrosion near the crevice mouth was accelerated in a neutral solution. When pH = 8 and pH = 9, the carbon steel matrix was dissolved and the Cl⁻ content within the solution was significantly reduced due to the higher concentration of hydroxide ions (OH⁻).

The crevice corrosion behavior of carbon steel in neutral/alkaline environments is closely associated with solution pH rather than the crevice width. The inhibition of crevice corrosion in alkaline environments was proved by finite element simulation. These findings provide valuable insights that can be applied in engineering applications to prevent and mitigate crevice corrosion in neutral/alkaline environments.

Electrochromic window (ECW) has been gradually applied to building engineering in recent years. However, empirical study of this technology used in green building design is still lacking. This study aims to verify the lighting and energy-saving performance of ECW under a specific geographical environment.

The meditation pavilion of Jinwan new materials research institute in Zhuhai is taken for research object. Three kinds of sun-shading techniques, namely, ECW, Low-E window and ordinary glass window, with same specifications are selected as the building facade structure for simulation. Day lighting analysis, sun-shading performance and annual energy consumption are separately simulated in the same environment by the Autodesk Ecotect Analysis software. The energy-saving performance of ECW is obtained by comparisons.

Result shows that the shading performance of ECW is much better than ordinary window and Low-E window. When ECW is used in the east, west or top lighting interfaces of a building, about 40% of the total solar radiation can be reduced during daytime in summer. Taking the ordinary glass window as a basic reference, ECW can save about 90% of the annual energy consumption of the glass house. ECW can effectively reduce the annual refrigeration energy consumption of buildings in the subtropical region.

Reasonable use of ECW in the subtropical region can effectively reduce the annual energy consumption of buildings.

It is a precedent study to analyze the lighting performance and energy consumption of a glass house with ECW. The energy-saving characteristics and beautiful appearance of ECW shall make it a future green building technology.

The strength of printed parts by application of fused deposition modeling (FDM) has been broadly studied through experimental methods. However, constitutive behaviors of the printed parts in theory are still unclear. Therefore, this paper aims to focus on building an elasto-plastic model of the printed parts to reveal the constitutive behavior.

An elasto-plastic constitutive model that considers anisotropic characteristics is proposed. Tensile tests are performed for parameter identification by using different samples with varying printing angles. Finally, the constitutive model is completed and applied to the numerical analysis of a tensile procedure.

The experimental study indicated that the anisotropic characteristics are significant for elastic modulus and strength of printed parts. The polar anisotropic model is suitable for describing the anisotropic behavior of parts during the elastic deformation. The Hill model is suitable to describe the yield property. The elastic modulus and yield point of parts printed in any specific orientation can be calculated using the proposed constitutive model.

A theoretical model has been developed to describe the constitutive behavior of FDM printed part. This model can precisely describe the elastic behavior and yield point of parts printed with various orientations. This model can be applied to the finite element simulation of printed structures.

The purpose of this paper is to study the operation performance of the high-speed ramjet kinetic energy projectile using solid fuel ramjet as power plant that is a new short-range and small caliber projectile.

The numerical investigation on combustion characteristic of polyethylene in high-speed ramjet kinetic energy projectile is carried out in this paper. The flow characteristics’ differences are analyzed when ramjet works or do not work, and both the combustion characteristics and propulsive performance are analyzed when ramjet works.

The results show that with the increase of the abscissa x, the flame front is close to solid fuel surface at first and then keeps away from solid fuel surface. With the increase of the abscissa x, the temperature of solid fuel surface and regression rate of solid fuel continues to increase before re-attachment point and then decreases, which a maximum locate at the re-attachment point. Both the average temperature and the regression rate on the surface of the solid fuel tend to rise as the increase of inflow Mach number. As the inflow of Mach number increases, the mass flow rate of gaseous fuel increases.

The research results can provide useful database for the subsequent research on high-speed ramjet kinetic energy projectile.

This paper studies the operation characteristics of the ramjet projectile, especially the effect of the change of the flight velocity on the performance of high-speed ramjet projectile.

We explore the driving forces behind the channel choices of the manufacturer and the platform by considering asymmetric selling cost and demand information.

This paper develops game-theoretical models to study different channel strategies for an E-commerce supply chain, in which a manufacturer distributes products through a platform that may operate in either the marketplace channel or the reseller channel.

Three primary models are built and analyzed. The comparison results show that the platform would share demand information in the reseller channel only if the service cost performance is relatively high. Besides, with an increasing selling cost, the equilibrium channel might shift from the marketplace to the reseller. With increasing information accuracy, the manufacturer tends to select the marketplace channel, while the platform tends to select the reseller channel if the service cost performance is low and tends to select the marketplace channel otherwise.

All these results have been numerically verified in the experiments. At last, we also resort to numerical study and find that as the service cost performance increases, the equilibrium channel may shift from the reseller channel to the marketplace channel. These results provide managerial guidance to online platforms and manufacturers regarding strategic decisions on channel management.

Although prior research has paid extensive attention to the driving forces behind the online channel choice between marketplace and reseller, there is at present few study considering the case where a manufacturer selling through an online platform faces a demand information disadvantage in the reseller channel and sales inefficiency in the marketplace channel. To fill this research gap, our work illustrates the interaction between demand information asymmetry and selling cost asymmetry to identify the equilibrium channel strategy and provides useful managerial guidelines for both online platforms and manufacturers.

This study provides a comprehensive overview of the research landscape of Kansei engineering (KE) within the domain of emotional clothing design. It explores the pivotal technologies, challenges and potential future directions of KE, offering application methodologies and theoretical underpinnings to support emotional clothing design.

This study briefly introduces KE, outlining its overarching research methodologies and processes. This framework lays the groundwork for advancing research in clothing Kansei. Subsequently, by reviewing literature from both domestic and international sources, this research initially explores the application of KE in the design and evaluation of clothing products as well as the development of intelligent clothing design systems from the vantage point of designers. Second, it investigates the role of KE in the customization of online clothing recommendation systems and the optimization of retail environments, as perceived by consumers. Finally, with the research methodologies of KE as a focal point, this paper discusses the principal challenges and opportunities currently confronting the field of clothing Kansei research.

At present, studies in the domain of clothing KE have achieved partial progress, but there are still some challenges to be solved in the concept, technical methods and area of application. In the future, multimodal and multisensory user Kansei acquisition, multidimensional product deconstruction, artificial intelligence (AI) enabling KE research and clothing sales environment Kansei design will become new development trends.

This study provides significant directions and concepts in the technology, methods and application types of KE, which is helpful to better apply KE to emotional clothing design.

This article aims to study unionisation of foreign companies in China and to evaluate its effectiveness on representing labour rights and interests, so as to explore the relationships between the Chinese unions and other industrial relations actors.

The article is based on in‐depth interview of key stakeholders from national, regional and company trade unions, as well as company management personnel. An archive study of union and company files is also conducted.

The Chinese trade union has realised that its interests stem from both the increase of membership dues and expansion of the membership base. Unionisation in transnational corporations (TNCs) is a key approach to achieve the interests of the union, which conducts grassroots mobilisation to counteract non‐operative companies but turns a blind eye on labour interest violations in collaborative firms. From the aspect of the union, the effectiveness of unionisation depends on raising its power leverage by affording fewer duties for the workers. Labour rights and workers' demands are not the structural concern of unionisation in TNCs.

The article challenges the research framework about Chinese unionism, which mainly emphasises a state‐union relationship or draws a corporatism perspective. The article concludes that the power relationship between the union and firm has acted as the key theme of the power struggle among industrial relations actors of China.