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Parameter identification is an important issue in structural health monitoring and damage identification for concrete dams. The purpose of this paper is to introduce a novel adaptive fireworks algorithm (AFWA) into inverse analysis of parameter identification.

Swarm intelligence algorithms and finite element analysis are integrated to identify parameters of hydraulic structures. Three swarm intelligence algorithms: AFWA, standard particle swarm optimization (SPSO) and artificial bee colony algorithm (ABC) are adopted to make a comparative study. These algorithms are introduced briefly and then tested by four standard benchmark functions. Inverse analysis methods based on AFWA, SPSO and ABC are adopted to identify Young’s modulus of a concrete gravity dam and a concrete arch dam.

Numerical results show that swarm intelligence algorithms are powerful tools for parameter identification of concrete structures. The proposed AFWA-based inverse analysis algorithm for concrete dams is promising in terms of accuracy and efficiency.

Fireworks algorithm is applied for inverse analysis of hydraulic structures for the first time, and the problem of parameter selection in AFWA is studied.

This study aims to explore the innovative capabilities of building information modeling (BIM) in construction projects. The objectives are to construct an inclusive conceptual framework of BIM-enabled construction innovation, identify the status and trends of innovation-related research in BIM publications, synthesize research pertaining to BIM-enabled construction innovation and discover core research requirements in the related body of knowledge.

This study proposes a comprehensive theoretical framework, named innovation pyramid, comprising context, actor, artifact, process, structure and innovative task for exploring and analyzing the innovative capability of BIM in construction projects. Accordingly, mixed methods were used to perform a systematic review of research on the topic of BIM-enabled construction innovation.

The findings reveal that BIM innovation-related articles have predominantly considered BIM as an innovation from a technological standpoint, while the innovative capabilities of BIM have remained under-researched with a fragmented research focus. Fertile grounds for research have emerged and call for research pertaining to entities of “structure” and “innovative task” as well as interaction, interrelations and mutually adjusting effect among the entities.

The framework proposed may be useful for subsequent research design and for assisting project management practitioners in the use of BIM to achieve innovation more efficiently.

This research provides an insight into the innovative capabilities of BIM based on the BIM–collaboration–construction innovation logic chain. It contributes to the body of knowledge by devising an inclusive conceptual framework of BIM-enabled construction innovation, synthesizing the state of the art and exposing the research needs in this area.

This research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.

Firstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.

The calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.

This study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.

In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative analytical procedure, which can overcome various drawbacks suffered by methods currently used in existing studies. Firstly, our procedure makes use of spatially high-resolution data, so that idiosyncratic effects of physical environment drivers, e.g., soil textures, can be explicitly modeled. Secondly, we address the well-known censored data problem, which often hinders a successful analysis of land-use shares. Thirdly, we incorporate spatial error dependence (SED) and heterogeneity in order to obtain efficiency gain and a more accurate formulation of variances for the parameter estimates. Finally, the authors reduce the computational burden and improve estimation accuracy by introducing an alternative generalized method of moments (GMM)–quasi maximum likelihood (QML) hybrid estimation procedure. The authors apply the newly proposed procedure to spatially high-resolution data in England and found that, by taking these features into consideration, the authors are able to formulate conclusions about causal effects of climatic and physical environment, and environmental policy on land-use shares that differ significantly from those made based on methods that are currently used in the literature. Moreover, the authors show that our method enables derivation of a more effective predictor of the land-use shares, which is utterly useful from the policy-making point of view.

The purpose of this paper is to present an original iterative nodal approach to calculate the fault current distribution on overhead lines.

By changing the mutual couplings among different conductors into the equivalent voltage sources, node voltages are updated iteratively by using conventional nodal analysis with those additional sources until the convergence is achieved.

The proposed algorithm can handle the complicated topology of a power transmission line and has no difficulties in taking all physical couplings into account. The fault current distribution calculated by this method is in good agreement with those published in the literature. Although the proposed approach is iterative, the CPU time needed is still reasonable compared to the direct solution approach. The memory requirement is low because the coefficient matrix is highly sparse for the nodal analysis of each iteration loop.

The proposed approach can serve as an alternative in calculating the fault current because of its efficiency and ease of implementation.

The disparities of COVID-19 vaccination rates between the rural and urban areas have become apparent during this pandemic. There is a need to understand the root causes of vaccine hesitancy demonstrated by the rural population to increase coverage and to contain the disease spread throughout the United States. This study aimed to explore other factors influencing vaccine hesitancy among rural dwellers besides the geography-related barriers such as poor health care access and individuals having no or suboptimal insurance coverage.

By reviewing existing data and literature about vaccination, health literacy, and behaviors, and prevailing ideologies, we discuss the potential causes of vaccine hesitancy in rural areas that could create barriers for successful public health efforts related to vaccine coverage and provide suggestions to ameliorate the situation.

Geography-related barriers, health literacy, and preconceived notions are key determinants of adopting healthy behaviors and complying with public health authorities' recommendations among rural individuals during a public-health crisis. We argue that ideology, which is much deeper than preconception or misconception on vaccination, should be incorporated as a key factor to redefine the term “vulnerable populations” in public health research.

The limitation of our study is that we have not found an effective way to encourage the populations who hold conservative religious and political ideologies to join the efforts for public health. Even though geography-related barriers may strongly impact the rural dwellers in achieving optimal health, the various forms of ideologies they have toward certain health behaviors cannot be discounted to understand and address vaccine-related disparities in rural areas. There is a need to redefine the term “vulnerable population” particularly as it relates to rural areas in the United States. During large-scale public health disasters, scholars and public health authorities should consider the ideologies of individuals, in addition to other factors such as race/ethnicity, area of residence (rural vs. urban), and socioeconomic factors influencing the existing vulnerabilities and health disparities.

This paper aims to investigate how a prospective buyer’s optimal home-size purchase can be determined by means of a stochastic-dominance (SD) analysis of the historical data of Hong Kong.

By means of SD analysis, the paper uses monthly property yields in Hong Kong over a 15-year period to illustrate how buyers of different risk preference may optimize their home-size purchase.

Regardless of whether the buyer eschews risk, embraces risk or is indifferent to it, in any adjacent pairing of five well-defined housing classes, the smaller class provides the optimal purchase. In addition, risk-averters focusing on total yield would prefer to invest in the smallest and second-smallest classes than in the largest class.

As the smaller class provides the optimal purchase, the smallest class affords the buyer the optimal purchase over all classes in this important housing market – at least where rental yields are of primary concern.

The findings suggest that in the Hong Kong housing market, long-term investors may be better off purchasing smaller homes. For other type of investors, it depends on their risk preference.

There is a very small body of empirical literature on housing investment, especially if the focus is on the optimal home-size purchase.

The purpose of this paper evaluates the effects of the Great Western Development (GWD) policy on agricultural intensification, land use, agricultural production and rural poverty in western China.

The authors collect county-level data on land use, input application, grain crop production, income, poverty and geophysical characteristics for 1996–2005 and use a quasi-natural experimental design of difference-in-differences (DD) in the empirical analysis.

Results suggest that the GWD policy significantly increased the grain crop production in western China. This increase resulted from higher yield, with increased fertilizer use and agricultural electricity consumption per hectare, and more land allocated to grow grain crops. The policy also increased land-use concentration, reduced crop diversity and alleviated rural poverty in western China.

This paper makes three contributions. First, the authors add to the growing literature on the GWD policy by evaluating its effects on farm household decisions and exploring the mechanisms and broad socioeconomic impacts in western China. Second, the authors take advantage of a quasi-natural experimental design to improve the identification strategy where input use, land allocation, production and off-farm labor participation are all endogenous in a farm household. Third, the authors explore a long list of variables within one integrated dataset to present a comprehensive picture of the impact of the GWD policy.

Fabric has complicated anisotropic mechanical behavior because of the woven pattern and complex physical properties. However, most current fabric simulation models are not satisfied because the models are usually geometrical models with stiffness parameters.

In this paper, the authors present a modeling technique to simulate fabric with Riemann manifold. The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area. It decomposes the m × n matrix constituting the fabric into several batches and processes the fabric dots in batches. In this model, the distance between any two adjacent particles of the fabric's is assumed to be equal, and the area of the curved surface is always constant, and the inclination and decay of the ridge wave-curved surface are also considered.

As the result, the simulated shape is lifelike. In time cost performance, the model improves the efficiency of the fabric styling and meets the requirements of real-time simulation.

The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area.

The purpose of this paper is to present a finite element analysis (FEA) of filament-wound composites, as well as application of these materials.

In this paper, a new finite element method of filament-wound composite is presented. The stress and strain fields in the composite cylinders are analyzed using the ABAQUS software packages for considering the filament undulation and crossover. The paper presented results of buckling load of composite cylinders with different types of filament-winding patterns.

The result of the example shows that the stress distributions are uniform along the cylinder length and around the circumference when the analytical approach is based on the conventional FEA. The stress distributions are not uniform along the cylinder length and around the circumference for considering the filament undulation and crossover. The stress units are arranged in a regular geometric pattern around circumference and along the axis of rotation. The analysis of the effect of filament-winding mosaic patterns on the mechanical characteristics of composite cylindrical is presented in the paper.

The stress and strain fields in the composite cylinders were analyzed for considering the filament undulation and crossover. The buckling load of composite cylinders with different types of filament-winding patterns was presented in this paper.