Performances and properties of steel and composite prestressed tendons - A review.

The primary drawback of concrete lies in its low tensile strength, prompting the development of various solutions to enhance this aspect. A notable approach is the utilization of Prestressed Reinforced Concrete (PRC) with tendons, aimed at bolstering its tensile strength. As the use of diverse tendon types in the PRC continues to surge, a review becomes imperative to delve into this evolution. Therefore, this study delved into the engineering characteristics, performance, and evolution of different tendon varieties, encompassing both steel and composite options. Despite certain drawbacks associated with employing composite materials such as Fiber Reinforced Polymer (FRP) tendons - such as heightened costs, limited availability of composite materials, and intricate manufacturing processes - there are distinct advantages and merits to incorporating FRP composite tendons in the realm of construction. In this respect, Carbon FRP tendons exhibited superior strength, comparable to their steel counterparts. Glass FRP tendons, lacking metallic components, possessed non-magnetic properties, rendering them resistant to corrosion. Additionally, Aramid FRP tendons boasted low flammability and exceptional resistance to elevated temperatures. Lastly, Basalt FRP tendons offered sustainability, rust resistance, and non-corrosiveness. The findings derived from this review study serve as a valuable resource for researchers seeking to advance the applications of steel tendons and FRP composite materials within the construction industry.

A review of interconnected challenges in the water-energy-food nexus: Urban pollution perspective towards sustainable development.

The swift growth of cities worldwide poses significant challenges in ensuring a sufficient water, energy, and food supply. The Nexus has innovated valuable systems to address these challenges. However, a crucial issue is the potential for pollution resulting from these systems, which directly and indirectly impacts public health and the overall quality of urban living. This study comprehensively reviews the interconnected challenges of the water-energy-food (WEF) nexus and various forms of pollution in cities. The primary focus of this review article is to showcase the findings of WEF nexus studies regarding various pollutions across different geographical regions and spatial scales. It aims to examine the problems resulting from these pollutions, specifically their effects on human health and urban life. It also delves into the sources of pollution as identified in these studies. Furthermore, the article will highlight the proposed solutions from the research aimed at effectively mitigating pollution in each sector studied. This article is a systematic review which analyses research sources from the Scopus database. It extensively reviewed 2463 peer-reviewed published articles and focused explicitly on articles related to the WEF nexus that discussed pollution. Our study emphasizes, firstly, raising awareness about the crucial link between the WEF nexus, pollution, urban environments, and human health among policymakers and key stakeholders, including urban planners, industry partners and municipalities. This is to promote the development of policies that encourage sustainable practices and key stakeholders. Secondly, it evaluates WEF nexus and pollution research methods and findings, aiding in identifying research gaps technological innovation and potential, as well as enhancing decision-making. Lastly, it outlines future research challenges, providing a roadmap for researchers and policymakers to advance understanding in this domain and identify opportunities for resource efficiency and collaboration between different sectors.

Developing an Ensemble Predictive Safety Risk Assessment Model: Case of Malaysian Construction Projects.

Occupational Health and Safety (OHS)-related injuries are vexing problems for construction projects in developing countries, mostly due to poor managerial-, governmental-, and technical safety-related issues. Though some studies have been conducted on OHS-associated issues in developing countries, research on this topic remains scarce. A review of the literature shows that presenting a predictive assessment framework through machine learning techniques can add much to the field. As for Malaysia, despite the ongoing growth of the construction sector, there has not been any study focused on OHS assessment of workers involved in construction activities. To fill these gaps, an Ensemble Predictive Safety Risk Assessment Model (EPSRAM) is developed in this paper as an effective tool to assess the OHS risks related to workers on construction sites. The developed EPSRAM is based on the integration of neural networks with fuzzy inference systems. To show the effectiveness of the EPSRAM developed, it is applied to several Malaysian construction case projects. This paper contributes to the field in several ways, through: (1) identifying major potential safety risks, (2) determining crucial factors that affect the safety assessment for construction workers, (3) predicting the magnitude of identified safety risks accurately, and (4) predicting the evaluation strategies applicable to the identified risks. It is demonstrated how EPSRAM can provide safety professionals and inspectors concerned with well-being of workers with valuable information, leading to improving the working environment of construction crew members.

Distinguishing Characteristics of Corruption Risks in Iranian Construction Projects: A Weighted Correlation Network Analysis.

The construction industry consistently ranks amongst the highest contributors to global gross domestic product, as well as, amongst the most corrupt. Corruption therefore inflicts significant risk on construction activities, and overall economic development. These facts are widely known, but the various sources and nature of corruption risks endemic to the Iranian construction industry, along with the degree to which such risks manifest, and the strength of their impact, remain undescribed. To address the gap, a mixed methods approach is used; with a questionnaire, 103 responses were received, and these were followed up with semi-structured interviews. Results were processed using social network analysis. Four major corruption risks were identified: (1) procedural violations in awarding contracts, (2) misuse of contractual arrangements, (3) neglect of project management principles, and, (4) irrational decision making. While corruption risks in Iran align with those found in other countries, with funds being misappropriated for financial gain, Iran also shows a strong inclination to champion projects that serve the government's political agenda. Root cause identification of corruption risks, namely, the noticeable impact of authoritarianism on project selection in Iran, over criterion of economic benefit or social good, is a significant outcome of this study.

Data in support of energy performance of double-glazed windows.

This paper provides the data used in a research project to propose a new simplified windows rating system based on saved annual energy ("Developing an empirical predictive energy-rating model for windows by using Artificial Neural Network" (Shakouri Hassanabadi and Banihashemi Namini, 2012) [1], "Climatic, parametric and non-parametric analysis of energy performance of double-glazed windows in different climates" (Banihashemi et al., 2015) [2]). A full factorial simulation study was conducted to evaluate the performance of 26 different types of windows in a four-story residential building. In order to generalize the results, the selected windows were tested in four climates of cold, tropical, temperate, and hot and arid; and four different main orientations of North, West, South and East. The accompanied datasets include the annual saved cooling and heating energy in different climates and orientations by using the selected windows. Moreover, a complete dataset is provided that includes the specifications of 26 windows, climate data, month, and orientation of the window. This dataset can be used to make predictive models for energy efficiency assessment of double glazed windows.