Frontiers in Built Environment

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EISSN : 2297-3362
Current Publisher: Frontiers Media SA (10.3389)
Total articles ≅ 643
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Charlotte E. L. Gilder, Rama Mohan Pokhrel, Flavia De Luca,
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.646009

Seismic hazard assessment often relies on static piezocone penetration tests (CPTu) to estimate the cyclic resistance ratio (CRR) and for the evaluation of in situ soil behavior. This article presents CPTu data acquired in the Kathmandu valley sediments and makes use of established CPTu interpretation procedures to assess the soil in situ properties. Up to this point predominantly SPT data and limited shear wave velocity measurements have been relied upon to assess the variability and seismic response of soil deposits underlying Kathmandu. This article provides 1) additional data to add to the existing SAFER/GEO-591 database, 2) new shear-wave velocity measurements, and 3) initial estimates of CRR at the sites visited. Based on the work presented in this article, it is concluded that a more detailed methodology is needed for liquefaction assessment mainly due to the presence of saturated silts in the valley.
, Carol Friedland, Christofer Harper, Isabelina Nahmens
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.636000

Relational and social behaviors of construction project team members explain relationship embeddedness. The literature review revealed three social behaviors (i.e., past experience, benevolence, and integrity) and seven relational behaviors (i.e., harmonization of conflict, propriety of means, restraint of power, reliance and expectation, contractual solidarity, flexibility, and reciprocity) commonly exhibited by construction project team members. Through a binomial logistic regression, research findings revealed that past experience was a significant (p < 0.01) predictor for five of the seven relational behaviors while benevolence and integrity were each significant (p < 0.01) predictors for three of the seven relational behaviors. Overall, out of the seven relational behaviors, only propriety of means is predicted by all the three social behaviors. Through internal validation, the prediction models performed well based on both positive predictive values and negative predictive values. From a relationship management standpoint, this research introduces relational and social behaviors of team members as triggers of relationship embeddedness. The results contribute to understanding the effect of social behaviors on the relational behaviors found in construction project teams where eleven statistically significant models that predict relational behaviors using the social behaviors were validated. The implication of this is that construction industry practitioners can use these prediction models to predict relationship interdependencies of team members.
, Seizo Tanaka
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.669601

Based on the experience of the 2011 Great East Japan Earthquake and the following tsunami, this study aims to develop effective analytical tools that can comprehensively be applied to buildings under multi-phase hazardous loads such as seismic motion, fluid force, and debris impact. Simulations by two kinds of analytical tools were conducted. First, a structural collapse analysis of a steel frame building under successive applications of varying loads was performed using the ASI (Adaptively Shifted Integration)-Gauss code, which simulates behaviors of structures by simple modeling. The steel frame building model was first excited under an acceleration record observed in Kesennuma-shi during the earthquake, and fluid forces due to a tsunami wave were applied. Then, the collapse behavior of the building was investigated by implementing a sophisticated contact algorithm in the numerical code to express a collision between debris and a building. It became evident that the damage to the building intensifies if a head-on collision occurs under a tsunami flow with a lower inundation height, and the damage to the building becomes larger if sideway collisions occur under a tsunami flow with a higher inundation height and higher velocity. The second simulation was conducted by using the stabilized finite element method based on the volume of fluid method, to estimate a drag coefficient of an actual tsunami evacuation building with openings. The practicability of an estimated wave force using the drag coefficient was confirmed by comparing with the wave force obtained from the fluid analysis. Finally, a sequential structural analysis, with a debris collision phase at the end, was conducted using the ASI-Gauss code to simulate the washout behavior of the building.
Jianxiang Huang, , Anqi Zhang, Shan Shan Hou, Jian Hang, John D. Spengler
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.666923

The coronaviruses have inflicted health and societal crises in recent decades. Both SARS CoV-1 and 2 are suspected to spread through outdoor routes in high-density cities, infecting residents in apartments on separate floors or in different buildings in many superspreading events, often in the absence of close personal contact. The viability of such mode of transmission is disputed in the research literature, and there is little evidence on the dose–response relationship at the apartment level. This paper describes a study to examine the viability of outdoor airborne transmission between neighboring apartments in high density cities. A first-principles model, airborne transmission via outdoor route (ATOR), was developed to simulate airborne pathogen generation, natural decay, outdoor dispersion, apartment entry, and inhalation exposure of susceptible persons in neighboring apartments. The model was partially evaluated using a smoke tracer experiment in a mock-up high-density city site and cross-checking using the computational fluid dynamics (CFD) models. The ATOR model was used to retrospectively investigate the relationship between viral exposure and disease infection at an apartment level in two superspreading events in Hong Kong: the SARS outbreak in Amoy Gardens and the COVID-19 outbreak in Luk Chuen House. Logistic regression results suggested that the predicted viral exposure was positively correlated with the probability of disease infection at apartment level for both events. Infection risks associated with the outdoor route transmission of SARS can be reduced to <10%, if the quanta emission rate from the primary patient is below 30 q/h. Compared with the indoor route transmission, the outdoor route can better explain patterns of disease infection. A viral plume can spread upward and downward, driven by buoyancy forces, while also dispersing under natural wind. Fan-assistant natural ventilation in residential buildings may increase infection risks. Findings have implication for public health response to current and future pandemics and the ATOR model can serve as planning and design tool to identify the risk of airborne disease transmission in high-density cities.
, Marcin Pawel Jarzebski, Martin Gomez-Garcia, Kensuke Fukushi
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.622382

Climate change causing an increase of frequency and magnitude of heat waves has a huge impact on the urban population worldwide. In Indonesia, the Southeast Asian country in the tropical climate zone, the increasing heat wave duration due to climate change will be also magnified by projected rapid urbanization. Therefore, not only climate change mitigation measures but also adaptation solutions to more frequent extreme weather events are necessary. Adaptation is essential at local levels. The projected increase of the heat wave duration will trigger greater health-related risks. It will also drive higher energy demands, particularly in urban areas, for cooling. New smart solutions for growing urbanization for reducing urban heat island phenomenon are critical, but in order to identify them, analyzing the changing magnitude and spatial distribution of urban heat is essential. We projected the current and future spatial variability of heat stress index in three cities in Indonesia, namely, Medan, Surabaya, and Denpasar, under climate change and land-cover change scenarios, and quantified it with the Universal Thermal Climate Index (UTCI) for two periods, baseline (1981–2005) and future (2018–2042). Our results demonstrated that currently the higher level of the UTCI was identified in the urban centers of all three cities, indicating the contribution of urban heat island phenomenon to the higher UTCI. Under climate change scenarios, all three cities will experience increase of the heat, whereas applying the land-cover scenario demonstrated that in only Medan and Denpasar, the UTCI is likely to experience a higher increase by 3.1°C; however, in Surabaya, the UTCI will experience 0.84°C decrease in the period 2018–2042 due to urban greening. This study advanced the UTCI methodology by demonstrating its applicability for urban heat warning systems and for monitoring of the urban green cooling effect, as well as it provides a base for adaptation measures’ planning.
, , Marcus Stoffel, Bernd Markert
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.679488

The evaluation of the structural response statistics constitutes one of the principal tasks in engineering. However, in the tail region near structural failure, engineering structures behave highly non-linear, making an analytic or closed form of the response statistics difficult or even impossible. Evaluating a series of computer experiments, the Monte Carlo method has been proven a useful tool to provide an unbiased estimate of the response statistics. Naturally, we want structural failure to happen very rarely. Unfortunately, this leads to a disproportionately high number of Monte Carlo samples to be evaluated to ensure an estimation with high confidence for small probabilities. Thus, in this paper, we present a new Monte Carlo simulation method enhanced by a convolutional neural network. The sample-set used for this Monte Carlo approach is provided by artificially generating site-dependent ground motion time histories using a non-linear Kanai-Tajimi filter. Compared to several state-of-the-art studies, the convolutional neural network learns to extract the relevant input features and the structural response behavior autonomously from the entire time histories instead of learning from a set of hand-chosen intensity inputs. Training the neural network based on a chosen input sample set develops a meta-model that is then used as a meta-model to predict the response of the total Monte Carlo sample set. This paper presents two convolutional neural network-enhanced strategies that allow for a practical design approach of ground motion excited structures. The first strategy enables for an accurate response prediction around the mean of the distribution. It is, therefore, useful regarding structural serviceability. The second strategy enables for an accurate prediction around the tail end of the distribution. It is, therefore, beneficial for the prediction of the probability of failure.
Krunal Gajera, , Luca Capacci, Fabio Biondini
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.631360

Following the empirical observation of widespread collapses of cladding panel connections of precast industrial buildings under recent seismic events, new design solutions have been developed in the framework of the European project SAFECLADDING, including isostatic systems effectively decoupling the seismic response of frame structure and cladding panels. The present paper is aimed at evaluating the seismic response and vulnerability of precast frame structures employing pendulum, cantilever, and rocking cladding connection systems. Within the framework of the research project RINTC–Implicit seismic risk of code-conforming structures funded by the Italian Civil Protection Department within the ReLUIS program, the seismic performance of a typical precast industrial building has been assessed with a probabilistic approach based on the results of static and multi-stripe dynamic non-linear analyses. The seismic vulnerability assessment of each structural system has been carried out with reference to life safety and damage limit states considering three sites of increasing seismic hazard in Italy. The effect of distributed panel mass modeling vs. more common lumped mass modeling has been analyzed and critically commented based on the results of demand over capacity (D/C) ratios. Moreover, biaxial seismic D/C ratios have been evaluated for realistic strong hinge connections for cladding panels.
, Bernhard Blümel, Katrin Ellermann
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.658363

Within the [email protected] project, funded by the Horizon 2020 program, a concept for a floating island was developed. The main idea is to create space in the offshore environment, which can be used to harvest renewable energy, grow food or build a maritime transport and logistic hub. The island is designed as an assembly of platforms, which are connected by ropes and fenders. These connection elements are considered critical, as they have to carry extreme loads in the severe offshore environment. At the same time, any failure in the connecting elements might put the entire platform structure at risk. This paper presents a feasibility study for the fault detection in the connection elements using Extended Kalman filters. For various test cases, typical parameters of the connecting elements are estimated from motion data of the structure. Thus, the technique reveals changes in the connections. For various test cases, it is shown that fault detection is possible. Not only a failure of a single connecting rope but also multiple faults in the system can be detected.
Makram Bou Hatoum, Ali Faisal, Hala Nassereddine, Hadi Sarvari
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.688495

The coronavirus outbreak has created a global health crisis that has disrupted all industries, including the construction industry. Following the onset of the pandemic, construction workers faced and continue to face unprecedented safety and health challenges. Therefore, construction employers established new safety precautions to protect the health and safety of the workforce and minimize the spread of the virus. The new precautions followed the advice and guidelines offered by different health and safety agencies like the Occupational Safety and Health Administration (OSHA), Centers of Disease Control and Prevention (CDC), and the Associated General Contractors of America (AGC). With construction projects resuming operations, it becomes important to analyze the coronavirus-related health and safety concerns of construction workforce and understand how the new safety procedures can assist on jobsites. Existing studies mostly focused on interviews and surveys with construction companies to understand the impact on project performance and supply chains. However, no study has yet to analyze the United States construction workforce. This paper fills the gap by providing a qualitative descriptive analysis of the COVID-19 complaints data gathered by OSHA from construction jobsites. Information gathered by OSHA includes the jobsite location, the North American Industry Classification System (NAICS) of the construction company, the type of the complaint (i.e., formal or non-formal), and a thorough description of the complaint. N-grams were employed to analyze the complaints, detect trends, and compile a list of the most frequent concerns reported by the workforce. The analysis of the complaints data identifies safety practices that were most violated, highlights major safety and health concerns for construction workers, and pinpoints geographical areas that have seen a surge in complaints. The study also synthesized the existing research corpus and compiled a list of 100 best practices that construction employers can adopt to mitigate the concerns of the workforce. The findings of this study provide insights into the safety and health trends on construction sites, lay the foundation for future work of academicians and practitioners to address the concerns faced by construction workers, and serve as lessons learned for the industry in the case of any future pandemic.
Ying Qi, Xingyue Fang, ,
Frontiers in Built Environment, Volume 7; doi:10.3389/fbuil.2021.664442

Several studies have proven that soundscape in blue space is conducive to human health and well-being, but few studies have explored which blue space characteristics would contribute to a better soundscape and visiting experience. Therefore, an on-site questionnaire investigation was conducted at two artificial lakes in Xi’an, China. The eight Perceived Sensory Dimensions (PSDs) as a landscape assessment tool were applied to identify the characteristics of artificial lake space in urban parks. The results showed that (1) In artificial lake space, overall environment and soundscape reached a very satisfactory level in general, while the respondents’ perceived level of overall restorativeness and soundscape restorativeness as just medium, which indicated that the quality of artificial lake space needs to be improved. (2) According to people’s perceptions, artificial lake spaces had the most obvious characteristics of prospect, social and space; serene and nature were medium; refuge, rich in species, and culture were the least. (3) The eight PSDs of artificial lake space, except for social, were positively correlated with soundscape satisfaction, overall satisfaction, soundscape restorativeness, and overall restorativeness. Moreover, among them, serene was the most significant characteristic in artificial lake space. These findings could be instructive to the design of urban parks with artificial lakes for improving users’ visiting satisfaction and restorativeness.
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