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The partially prestressed concrete beam with unbonded tendon is still an active field of research because of the difficulty in analyzing and understanding its behavior. The finite-element (FE) simulation of such beams using numerical software is very scarce in the literature and therefore this study is taken to demonstrate the modeling aspects of unbonded partially prestressed concrete (UPPSC) beams. This study aims to present the three-dimensional (3-D) nonlinear FE simulations of UPPSC beams subjected to monotonic static loadings using the numerical analysis package ANSYS.

The sensitivity study is carried out with three different mesh densities to obtain the optimum elements that reflect on the load–deflection behavior of numerical models, and the model with optimum element density is used further to model all the UPPSC beams in this study. Three half-symmetry FE model is constructed in ANSYS parametric design language domain with proper boundary conditions at the symmetry plane and support to achieve the same response as that of the full-scale experimental beam available in the literature. The linear and nonlinear material behavior of prestressing tendon and conventional steel reinforcements, concrete and anchorage and loading plates are modeled using link180, solid65 and solid185 elements, respectively. The Newton–Raphson iteration method is used to solve the nonlinear solution of the FE models.

The evolution of concrete cracking at critical loadings, yielding of nonprestressed steel reinforcements, stress increment in the prestressing tendon, stresses in concrete elements and the complete load–deflection behavior of the UPPSC beams are well predicted by the proposed FE model. The maximum discrepancy of ultimate moments and deflections of the validated FE models exhibit 13% and −5%, respectively, in comparison with the experimental results.

The FE analysis of UPPSC beams is done using ANSYS software, which is a versatile tool in contrast to the experimental testing to study the stress increments in the unbonded tendons and assess the complete nonlinear response of partially prestressed concrete beams. The validated numerical model and the techniques presented in this study can be readily used to explore the parametric analysis of UPPSC beams.

The developed model is capable of predicting the strength and nonlinear behavior of UPPSC beams with reasonable accuracy. The load–deflection plot captured by the FE model is corroborated with the experimental data existing in the literature and the FE results exhibit good agreement against the experimentally tested beams, which expresses the practicability of using FE analysis for the nonlinear response of UPPSC beams using ANSYS software.

The purpose of this paper is to propose a fractal model of thermal contact conductance (TCC) of rough surfaces based on cone asperity.

A detailed numerical study is conducted to examine the effects of contact load, fractal dimensional, fractal roughness and material properties on the TCC of rough surfaces.

The results indicate that when the fractal dimension D is less than 2.5, the TCC of rough surfaces increases nonlinearly with the increase of the contact load. However, when the fractal dimension D is greater than or equal to 2.5, the TCC of rough surfaces increases linearly with the increase of the contact load; the TCC of the rough surfaces increases with the increase of the fractal dimension D and the decrease of the fractal roughness G; the material parameters also have an influence on the TCC of the rough surfaces, and the extent of the effect on the TCC is related to the fractal dimension D.

A fractal model of TCC of rough surfaces based on cone asperity is established in this paper. Some new results and conclusions are obtained from this work, which provides important theoretical guidance for further study of TCC of rough surfaces.

To solve the instability problem of Zhangjiayao landslide caused by rainfall, the internal mechanism of slope instability and the supporting effect of anti-slide piles are studied. The research results can provide theoretical basis for the prevention and control of loess landslides.

A three-dimensional finite element model of Zhangjiayao landslide is established by field geological survey, laboratory test and numerical simulation.

The results show that Zhangjiayao landslide is a loess-mudstone contact surface landslide, and rainfall leads to slope instability and traction landslide. The greater the rainfall intensity, the faster the pore water pressure of the slope increases and the faster the matrix suction decreases. The longer the rainfall duration, the greater the pore water pressure of the slope and the smaller the matrix suction. Anti-slide pile treatment can significantly improve slope stability. The slope safety factor increases with the increase of embedded depth of anti-slide pile and decreases with the increase of pile spacing.

Based on the unsaturated soil seepage theory and finite element strength reduction method, the failure mechanism of Zhangjiayao landslide was revealed, and the anti-slide pile structure was optimized and designed based on the pile-soil interaction principle. The research results can provide theoretical basis for the treatment of loess landslides.

1. A three-dimensional finite element model of Zhangjiayao landslide is established.

2. Zhangjiayao landslide is a loess-mudstone contact surface landslide.

3. The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

4. The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

5. The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

A three-dimensional finite element model of Zhangjiayao landslide is established.

Zhangjiayao landslide is a loess-mudstone contact surface landslide.

The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

Construction schedule delays and quality problems caused by construction errors are common in the field of prefabricated buildings. The effective monitoring of the construction project process is one of the key factors for the success of a project. How to effectively monitor the construction process of prefabricated building construction projects is an urgent problem to be solved. Aiming at the problems existing in the monitoring of the construction process of prefabricated buildings, this paper proposes a monitoring method based on the feature extraction of point cloud model.

This paper uses Trimble X7 3D laser scanner to complete field data collection experiments. The point cloud data are preprocessed, and the prefabricated component segmentation and geometric feature measurement are completed based on the PCL platform. Aiming at the problem of noisy points and large amount of data in the original point cloud data, the preprocessing is completed through the steps of constructing topological relations, thinning, and denoising. According to the spatial position relationship and geometric characteristics of prefabricated frame structure, the segmentation algorithm flow is designed in this paper. By processing the point cloud data of single column and beam members, the quality of precast column and beam members is measured. The as-built model and as-designed model are compared to realize the visual monitoring of construction progress.

The experimental results show that the dimensional measurement accuracy of beam and column proposed in this paper is more than 95%. This method can effectively detect the quality of prefabricated components. In the aspect of progress monitoring, the visualization of real-time progress monitoring is realized.

This paper proposed a new monitoring method based on feature extraction of the point cloud model, combined with three-dimensional laser scanning technology. This method allows for accurate monitoring of the construction process, rapid detection of construction information, and timely detection of construction quality errors and progress delays. The treatment process based on point cloud data has strong applicability, and the real-time point cloud data transfer treatment can guarantee the timeliness of monitoring.

This paper aims to propose a two-stage vibration isolation system for large airborne equipment to isolate aircraft vibration load.

First, the vibration isolation law of the discrete model of large airborne equipment under different damping ratios, stiffness ratios and mass ratios is analyzed, which guides the establishment of a three-dimensional solid model of large airborne equipment. Subsequently, the vibration isolation transfer efficiency is analyzed based on the three-dimensional model of the airborne equipment, and the angular and linear vibration responses of the two-stage vibration isolation system under different frequencies are studied.

Finally, studies have shown that the steady-state angular vibration at the non-resonant frequency changes little. In contrast, the maximum angular vibration at the resonance peak reaches 0.0033 rad, at least 20 times the response at the non-resonant frequency. The linear vibration at the resonant frequency is at least 2.14 times the response at the non-resonant frequency. Obviously, the amplification factor of linear vibration is less than that of angular vibration, and angular vibration has the most significant effect on the internal vibration of airborne equipment.

The two-stage vibration isolation equipment designed in this paper has a positive guiding significance for the vibration isolation design of large airborne equipment.

This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.

To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.

Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.

This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

This paper aims to investigate the impact of three different flow channel cross sections on the performance of the fuel cell.

A comprehensive three-dimensional polymer electrolyte membrane fuel cell model has been developed, and a set of conservation equations has been solved. The flow is assumed to be steady, fully developed, laminar and isothermal. The investigated cross sections are the commonly used square cross section, the increasingly used trapezoidal cross section and a novel hybrid configuration where the cross section is square at the inlet and trapezoidal at the outlet.

The results show that a slight gain is obtained when using the hybrid configuration and this is because of increased velocity, which improves the supply of the reactant gases to the catalyst layers (CLs) and removes heat and excess water more effectively compared to other configurations. Further, the reduction of the outlet height of the hybrid configuration leads to even better fuel cell performance and this is again because of increased velocity in the flow channel.

The data generated in this study will be highly valuable to engineers interested in studying the effect of fluid cross -sectional shape on fuel cell performance.

This study proposes a novel flow field with a variable cross section. This design can supply a higher amount of reactant gases to the CLs, dissipates heat and remove excess water more effectively.

This study aims to leverage the implementation of building information modelling (BIM) in facilities management (FM), and thus the integration of BIM and FM are explored. It looks at identifying the information needed to implement BIM application in FM, to determine the level of implementation of BIMFM as well as to recommend BIMFM application mapping for building life cycle.

This study applied qualitative methodology, upon which a purposive sampling to 16 interviewees were conducted among professionals involved in any BIM, FM, BIMFM projects. Final analysis was conducted using thematical analysis by ATLAS.ti software.

The types of information required to implement BIMFM range from managerial information, commercial information, technical information and all full life cycle data. The implementation of BIMFM is agreed as beneficial, as it builds up efficiency of building performance, able to close gap of loses information, helps to improve FM in terms of data management, mitigates the problems, identifies priority defects and to enhance the FM processes. Respondents also believed that the causes where there is no implementation of BIMFM is in the situations where things are in order and when it becomes very expensive.

This paper has managed to gather the essential elements toward leveraging the implementation of BIMFM in digital construction project which are in the means of information types, the needs of BIMFM implementation and towards the end drawing the BIMFM implementation plan framework that could be used as a reference for the practitioners and industry.

This study aims to present a novel Genetic Algorithm-Based Design Model (GABDM) to provide reduced-risk areas, namely, a “safe footprint,” in interior spaces during earthquakes. This study focuses on housing interiors as the space where inhabitants spend most of their daily lives.

The GABDM uses the genetic algorithm as a method, the Nondominated Sorting Genetic Algorithm II algorithm, and the Wallacei X evolutionary optimization engine. The model setup, including inputs, constraints, operations and fitness functions, is presented, as is the algorithmic model’s running procedure. Following the development phase, GABDM is tested with a sample housing interior designed by the authors based on the literature related to earthquake risk in interiors. The implementation section is organized to include two case studies.

The implementation of GABDM resulted in optimal “safe footprint” solutions for both case studies. However, the results show that the fitness functions achieved in Case Study 1 differed from those achieved in Case Study 2. Furthermore, Case Study 2 has generated more successful (higher ranking) “safe footprint” alternatives with its proposed furniture system.

This study presents an original approach to dealing with earthquake risks in the context of interior design, as well as the development of a design model (GABDM) that uses a generative design method to reduce earthquake risks in interior spaces. By introducing the concept of a “safe footprint,” GABDM contributes explicitly to the prevention of earthquake risk. GABDM is adaptable to other architectural typologies that involve footprint and furniture relationships.