There is increasing implementation of digital technologies in construction. However, the transformation effects encompassing digital technology implementation are yet to be fully comprehended within ...the context of construction. Therefore, this study was aimed to provide a holistic understanding of digital transformation in construction. The study drew on extant literature by studying 36 journal publications published between 2016 when digital transformation emerged in construction from the information systems field and 2020. This led to the development of an inductive framework using a grounded theory methodology (GTM) to highlight digital transformation in construction as a process where the implementation of digital technologies creates transformation effects that trigger strategic considerations for putting in place the enablers that facilitate transformation effects and for suppressing the barriers to it. Building on the framework, this study described and presented the strategic considerations for facilitating specific enablers and those for suppressing specific barriers as digital transformation guideline in construction. This study demonstrated how the implementation of digital technologies has increased the understanding of and provided the basis for digital transformation in construction.
Dams are a critical infrastructure system for many communities, but they are also one of the most challenging to inspect. Dams are typically very large and complex structures, and the result is that ...inspections are often time-intensive and require expensive, specialized equipment and training to provide inspectors with comprehensive access to the structure. The scale and nature of dam inspections also introduce additional safety risks to the inspectors. Unmanned aerial vehicles (UAV) have the potential to address many of these challenges, particularly when used as a data acquisition platform for photogrammetric three-dimensional (3D) reconstruction and analysis, though the nature of both UAV and modern photogrammetric methods necessitates careful planning and coordination for integration. This paper presents a case study on one such integration at the Brighton Dam, a large-scale concrete gravity dam in Maryland, USA. A combination of multiple UAV platforms and multi-scale photogrammetry was used to create two comprehensive and high-resolution 3D point clouds of the dam and surrounding environment at intervals. These models were then assessed for their overall quality, as well as their ability to resolve flaws and defects that were artificially applied to the structure between inspection intervals. The results indicate that the integrated process is capable of generating models that accurately render a variety of defect types with sub-millimeter accuracy. Recommendations for mission planning and imaging specifications are provided as well.
The optimal and smart design of nonlinear building structures with and without passive dampers subjected to earthquake loading is of great concern in the structural design of building structures. The ...research started around 1980 and many investigations have been conducted. A comprehensive review on this subject is made in this article. After the description of essential features of the optimal design problem of nonlinear building structures under earthquake ground motions, analysis types of optimization problems are explained and the significance of the dynamic pushover analysis is discussed from the viewpoint of analysis of limit states under earthquake ground motions of magnitude larger than the code-specified level. Then, the categorization by the response of frames and dampers was made. In this categorization, several subjects are discussed first: 1) Optimal design of bare nonlinear building frames under seismic loading, 2) Optimal design of nonlinear dampers for elastic building frames under seismic loading, 3) Optimal design of linear dampers for nonlinear building frames under seismic loading, 4) Optimal design of nonlinear building frames with specified nonlinear dampers under seismic loading, 5) Optimal design of nonlinear dampers for specified nonlinear building frames under seismic loading, 6) Simultaneous optimization of elastic-plastic building structures and passive dampers. Finally, the classification of researches in view of solution strategies is conducted for providing another viewpoint.
In this study, the Multivariate Adaptive Regression Splines (MARS) model is employed to create a data-driven prediction for the bearing capacity of a strip footing on rock mass subjected to an ...inclined and eccentric load. The strengths of rock masses are based on the Hoek-Brown failure criterion. To develop the set of training data in MARS, the lower and upper bound finite element limit analysis (FELA) is carried out to obtain the numerical results of the bearing capacity of a strip footing with the width of
B
. There are six considered dimensionless variables, including the geological strength index (
GSI
), the rock constant/yield parameter (
m
i
), the dimensionless strength (
γB/σ
ci
), the adhesion factor (
α
), load inclined angle from the vertical axis (
β
), and the eccentricity of load (
e/B
). A total of 5,120 FELA solutions of the bearing capacity factor (
P/σ
ci
B
) are obtained and used as a training data set. The influences of all dimensionless variables on the bearing capacity factors and the failure mechanisms are investigated and discussed in detail. The sensitivity analysis of these dimensionless variables is also examined.
The 4th industrial revolution started in 2016 and referred to a new phase in the industrial revolution. One of the most significant technological evolvements during the 4th industrial revolution is ...Augmented Reality (AR) technology. AR superimposes interactional virtual objects/images to real environments. Because of the interaction and see-through characteristics, AR is better applied to engineering than Virtual Reality (VR). The application of AR in civil infrastructure can avoid artificial mistakes, improve efficiency, and saves budget. This article reviews AR applications in civil infrastructure, focusing on research studies in the latest five years (2016–2020) and their milestone developments. More than half of the AR research and implementation studies have focused on the construction domain in the last five years. Researchers deploy AR technologies in on-site construction to assist in discrepancy checking, collaborative communication, and safety checking. AR also uses building information models (BIMs) to produce detailed 3D structural information for visualization. Additionally, AR has been studied for structural health monitoring (SHM), routine and damage detection, energy performance assessment, crack inspection, excavation, and underground utility maintenance. Finally, AR has also been applied for architecture design, city plan, and disaster prediction as an essential part of smart city service. This article discusses the challenges of AR implementation in civil infrastructure and recommends future applications.
In recent years, our surface transportation infrastructure is suffering from overuse, extreme traffic congestion, and roadway disrepair. Instead of following the traditional infrastructure expansion ...policy, current transportation research focuses on developing innovative and novel solutions to the aforementioned issues. Current pathways to overcoming these issues include the gradual transition toward a number of emerging transportation technologies, such as, autonomous motor vehicles for human transport, as well as unmanned aerial vehicles (UAV's) and “drone” technologies for surveillance, and package deliveries. However, as a long-term solution, transportation scientists are also investigating the once-seemingly futuristic notion of flying car technology—a convergent form of ground/air vehicle transportation, and assessing associated regulations. In this paper, an extensive review of current literature is conducted to explore the technological capabilities of flying cars—each requiring appropriate regulations and governance—to become fully sustainable. Specifically, issues pertinent to training, safety, environment, navigation, infrastructure, logistics/sustainability, and cybersecurity and human factors are explored. This paper concludes with a preliminary quantitative analysis exploring the public perceptions associated with flying cars—including anticipated benefits, concerns, and willingness to both hire and acquire the technology once available to consumers. Insights offered by this data will help inform next-generation policies and standards associated with the gradual advancement of flying cars.
In the computational fluid dynamics simulation workflow, the geometry preparation step is often regarded as a tedious, time-consuming task. Many practitioners consider it one of the main bottlenecks ...in the simulation process. The more complex the geometry, the longer the necessary work, meaning this issue is amplified for urban flow simulations that cover large areas with complex building geometries. To address the issue of geometry preparation, we propose a workflow for automatically reconstructing simulation-ready 3D city models. The workflow combines 2D geographical datasets (e.g., cadastral data, topographic datasets) and aerial point cloud-based elevation data to reconstruct terrain, buildings, and imprint surface layers like water, low vegetation, and roads. Imprinted surface layers serve as different roughness surfaces for modeling the atmospheric boundary layer. Furthermore, the workflow is capable of automatically defining the influence region and domain size according to best practice guidelines. The resulting geometry aims to be error-free: without gaps, self-intersections, and non-manifold edges. The workflow was implemented into an open-source framework using modern, robust, and state-of-the-art libraries with the intent to be used for further developments. Our approach limits the geometry generation step to the order of hours (including input data retrieval and preparation), producing geometries that can be directly used for computational grid generation without additional preparation. The reconstruction done by the algorithm can last from a few seconds to a few minutes, depending on the size of the input data. We obtained and prepared the input data for our verification study in about 2 hours, while the reconstruction process lasted 1 minute. The unstructured computational meshes we created in an automatic mesh generator show satisfactory quality indicators and the subsequent numerical simulation exhibits good convergence behavior with the grid convergence index of observed variables less than 5%.
The present article aims to provide an overview of the consequences of dynamic soil-structure interaction (SSI) on building structures and the available modelling techniques to resolve SSI problems. ...The role of SSI has been traditionally considered beneficial to the response of structures. However, contemporary studies and evidence from past earthquakes showed detrimental effects of SSI in certain conditions. An overview of the related investigations and findings is presented and discussed in this article. Additionally, the main approaches to evaluate seismic soil-structure interaction problems with the commonly used modelling techniques and computational methods are highlighted. The strength, limitations, and application cases of each model are also discussed and compared. Moreover, the role of SSI in various design codes and global guidelines is summarized. Finally, the advancements and recent findings on the SSI effects on the seismic response of buildings with different structural systems and foundation types are presented. In addition, with the aim of helping new researchers to improve previous findings, the research gaps and future research tendencies in the SSI field are pointed out.
Mitigation of losses due to coastal hazards has become an increasingly urgent and challenging problem in light of rising seas and the continued escalation of coastal population density. ...Unfortunately, stakeholders responsible for assuring the safety of these coastal communities are not equipped with the engineering research community’s latest tools for high-fidelity risk assessment and geospatial decision support. In the event of a hurricane or nor’easter, such capabilities are exceptionally vital to project storm impacts on critical infrastructure and other municipal assets and to inform preemptive actions that can save lives and mitigate property damage. In response, a web-based visualization environment was developed using the GeoNode content management system, informed by the needs of municipal stakeholders. Within this secure platform, registered users with roles in planning, emergency management and first response can simulate the impact of hurricanes and nor’easters using the platform’s storm Hazard Projection (SHP) Tool. The SHP Tool integrates fast-to-compute windfield models with surrogate models of high-fidelity storm surge and waves to rapidly simulate user-defined storm scenarios, considering the effects of tides, sea level rise, dune breaches and track uncertainty. In the case of a landfalling hurricane, SHP tool outputs are automatically loaded into the user’s dashboard to visualize the projected wind, storm surge and wave run-up based on the latest track information published by the National Hurricane Center. Under either use case, outputs of the SHP Tool are visualized within a robust collaborative geospatial environment supporting the seamless exploration of centralized libraries of geographic information system (GIS) data from federal, state, county and local authorities, with tools to add user-supplied annotations such as notes or other geospatial mark-ups. This paper will overview the development and deployment of this platform in the State of New Jersey, detailing the cyberinfrastructure design and underlying computational models, as well as the user stories that inspired the platform’s functionalities and interfaces. The study concludes with reflections from the process of piloting this project with stakeholders at the state and municipal level to support more risk-responsive and data-informed decision making.
Large-scale risk assessments relevant to natural hazards are commonly based on very poor exposure and vulnerability data, often drawn from census data. In fact, obtaining a detailed knowledge of the ...built heritage is a very hard task especially for those countries, like Italy, characterized by very high urban density and large variety of building typologies, where a building-by-building knowledge can sound as a utopian ambition. Nevertheless, exposure and vulnerability are two of the four factors governing, along with hazard and capacity, risk convolution, and hence their uncertainties yield to corresponding uncertainties in the resulting expected losses. The lack of suitable information on building typologies is responsible of very strong simplifications in risk analyses, like the assumption of the same building typologies, indistinctly scattered all over the Country territory, without distinctions at a local or at a regional level. With the goal of improving exposure description and reducing such uncertainties, since 2014 the Italian Civil Protection Department (ICPD) has undertaken a new research branch in the framework of ReLUIS (Network of University Laboratories in Earthquake Engineering) projects, dedicated to territorial analyses, by funding also the CARTIS project. The project has the goal to characterize the building structural typologies trough a data collection at a local and an extensive scale in Italy, with the final aim to improve the reliability of seismic risk analyses. The paper describes the method and some first statistics so far elaborated.
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