Showing papers by "Samad M. E. Sepasgozar published in 2023"

BIM and Digital Twin for Developing Convergence Technologies as Future of Digital Construction

Abstract: The construction industry is slow to adopt new technologies. The implementation of digital technologies and remote operations using robots were considered farfetched affairs and unbelievable approaches. However, the effect of COVID-19 on clients and construction companies put high pressure on construction managers to seek digital solutions and justified the need for remote operating or distant controlling technologies. This paper aims to investigate the state of play in construction technology implementation and presents a roadmap for developing and implementing required technologies for the construction industry. The COVID-19 disruption required new methods of working safely and remotely and coincided with the advent of advanced automation and autonomous technologies. This paper aims to identify gaps and 11 disruptive technologies that may lead to upheaval and transformation of the construction sector, perhaps in this decade. A road map for technology implementation can be helpful in developing business strategies at the organizational level as a theoretical measure, and it can facilitate the technology implementation process at the industry level as a practical measure. The roadmap can be used as a framework for policymakers to set industry or company strategies for the next 10 years (2030).

Assessing Factors Affecting Construction Equipment Productivity Using Structural Equation Modeling

Abstract: The performance of the construction industry can be improved by understanding the factors that affect the productivity of its equipment. A hypothetical framework was used to analyze six vital construction equipment parameters to understand how they affect productivity in construction projects. Data collected through a survey of 110 respondents in the construction industry were analyzed using an exploratory factor analysis (EFA) and structural equation modeling (SEM). The final model obtained using SEM consisted of 31 attributes from six construction equipment productivity factors, namely management (MG), materials (MT), human (HM), technical (TN), environmental (EM), and other factors (OT). Construction equipment productivity was found to be significantly influenced by MT and OT in construction projects. This was mainly because of their corresponding subfactors, such as operating life and equipment age, and the occurrence of accidents during construction. Consequently, based on survey feedback from various construction professionals, present gaps in construction equipment productivity were analyzed, and recommendations were made to overcome the main limiting factors under MT and OT. This study identified and quantified the interrelationships between various construction equipment productivity constraints. Therefore, the results can help experts and specialists better comprehend how to overcome delays due to idle time and improve construction equipment productivity.

Construction Digital Technology Assimilation and Absorption Capability Using Measurement Invariance of Composite Modeling

Abstract: Digital technology is evolving, and construction companies now have various choices of these technologies to implement into daily business. This has, however, resulted in a growing argument on how digital technologies can be accepted in various contexts. However, most arguments are based on technology acceptance models with the core concept of individual behaviors, which ignores the influence of other stakeholders and organizational characteristics. This paper aims to present a novel model representing the successful practice of the assimilation process for digital construction technologies that should be considered before any technology acceptance analysis. The model was tested via empirical investigation with 372 practitioners from Australia involved in building and infrastructure construction projects. Structural equation modeling, measurement invariance of composite models, and some semistructured interviews were used to test and verify the relationships between key variables of the model. The results suggest that the capability of assimilation can be enhanced by improving innovativeness and the relevant operational processes, with a t-value of >6.27. The findings show that a project’s likelihood of successful technology assimilation can also be increased if vendors are supportive and the company improves its operating performance assessment and absorption capacity. The findings clarify theoretical and practical contributions for a better understanding of critical factors of assimilation and provide a tool to potential company users for predicting the success of technology assimilation.

A Qualitative Study on Factors Influencing Technology Adoption in the Architecture Industry

Abstract: The architecture service industry has typically been slow in accepting new digital technologies widely due to many reasons, such as the industry’s complexity, the diverse sizes of companies, client types, and stakeholders’ technical skills. The combination of these business service factors with those that affect the intention of a user to use a technology offers a novel model for predicting the success of technology adoption in this business. This study aims to identify the factors in the architecture industry that influence the process of technology adoption. The process of qualitative data collection was conducted using semi-structured interviews with the participation of 30 architecture and design managers to explore the factors that they consider important when adopting digital technology in their organizations. This was conducted to compare these factors with those identified by users as influential in the adoption of digital technology. The analysis was conducted in three stages, namely transcribing, coding, and extracting major themes. This study starts by discussing demographic factors such as gender and their influence on the technology adoption process in the selected organizations. This study will further help in identifying whether managers viewed the factors identified in the quantitative study as significant in affecting their decisions to adopt the technology. The major findings of this study revealed that several factors influence the adoption of technology in the architecture industry at the managerial level. These factors include cost, brief preparation, service quality, result demonstrability, project time, environmental considerations, training considerations, and user-friendliness.

Exploring the Integration of Architectural Design and Advanced Structural Analysis for Steel–Glass Structures: A Comparative Study of Different Case Scenarios

Abstract: It is well known that finite element analysis (FEA) is a powerful tool when it comes to the design and analysis of complex structures for various load combinations, including light steel curve members. This abstract provides an overview of the FEA simulation process for designing such members (cure members), which involves constructing a 3D model, discretising the member into small elements, assigning material properties, defining boundary conditions, conducting the simulation, analysing the results, and making any necessary modifications to the design. FEA simulations can provide valuable insights into the behaviour of light steel curved members under different load combinations. This enables designers to optimise designs for strength, safety, and cost-effectiveness. This article proposes using two commercial 3D software programs, Rhino 7 and Strand7, to complete the FEA simulation of light steel curved members. The 3D model is created in Rhino 7, and the individual elements are discretised into more minor elements using Strand7 for assigning material properties, defining boundary conditions, running simulations, and analysing the results. The paper presents five case studies of steel–glass façades and applies the proposed methodology to each. Examples include Phoenix International Media Center in Beijing, Kazakhstan Pavilion and Science Museum in Astana, Moynihan Train Hall in New York City, Chadstone Shopping Centre in Melbourne, and the central light rail station in The Hague.

Architectural Design Criteria Considering the Circular Economy and Buildability for Smart Disaster Relief Shelter Prototyping

Abstract: The frequency of natural disasters is exacerbated by the escalating impacts of climate change with the need for effective relief shelters for victims and displaced individuals. Providing accessible and easy-to-assemble relief shelters is essential in addressing these needs. Due to climate-related challenges and the need for sustainable solutions, the integration of circularity principles in shelter design has become imperative. Circular economy principles promote the efficient use of resources, minimising waste generation and the cost of shelters. Moreover, a considerable number of people usually suffer from homelessness, and an increasing number of families live in slums in every part of the globe. All such people are entitled to be housed in affordable, safe, and appropriate shelters for at least several months after a disaster until they can either rebuild their former houses or find somewhere decent to settle after recovering from the hardship. With the aim of investigating the immediate housing needs of people after a disaster, this paper identifies the essential factors that must be taken into account during shelter design. The paper also presents the prototype developed on the basis of theoretical criteria and the identified factors. The paper’s main objectives were to design an easy-to-assemble emergency shelter on circular economy principles, identify critical factors for the circularity and buildability of the shelter, and present a proposed smart shelter acceptance model. The methodology behind the research involves conducting an intensive literature review and creating a novel prototype of a smart disaster relief shelter on the basis of long-run laboratory work and various prototype iterations. The paper presents the details of the novel prototype and shows materials that enhance the circularity of the shelter, according to a unique architectural design strategy of ‘reusing’ materials to enhance circularity practice in the design and construction sectors. The prototype was developed in a workshop after 6 months of reiterations using plastic water bottles, basic pipes, and other reusable materials. Then, by incorporating the essential factors, a set of criteria was designed that can be used as a guide for the architectural design of shelters. The criteria offered in this paper are useful to evaluate each factor’s importance in shelter design. In total, 51 effective factors in designing and constructing such accommodation are presented, clustered into five design strategy groups: social–cultural, physical–technical, environmental, economic, and organisational.

Building Energy Performance Modeling through Regression Analysis: A Case of Tyree Energy Technologies Building at UNSW Sydney

Abstract: Addressing clients’ demands, designers have become increasingly concerned about the operation phases of buildings and, more specifically, energy consumption. This issue has become more prominent as people realize that the Earth’s resources are limited and depleted, and buildings are major energy consumers. Building Information Modelling (BIM) has gained popularity in recent years and is now widely used by architects, engineers, and construction teams to collaborate and provide a comprehensive design that follows a sustainable strategy. The objective of this research is to examine how building variables are linked to energy consumption in various building shapes, achieved by building prototypes. The accuracy of the regression models is evaluated by undergoing a validation process. Consequently, this study created building information models of selected education facility office rooms and used Autodesk Insight 360 and Green Building Studio (GBS) to perform energy simulations. A 6 Green Star education building in Australia is chosen as the case study of this paper. Thirteen variables related to building internal design were examined, and five were found to endure a substantial effect on building energy consumption. The study also looked at the window-to-wall ratio (WWR), which was analyzed by multi-linear regression; however, the results showed that the model did not fit well, and the error obtained during the validation process ranged from 1.0% to 26.0%, which is unacceptable for this research. These findings highlight some limitations in using BIM tools and linear regression methods and discuss some potential improvements that can be achieved in future studies.

Recycling Waste Construction Material and Industry Involvement in University Investigations: Developing a Framework

Abstract: This study developed novel metrics and utilized content analysis in terms of keywords selected, scholarly publications, and social media posts to identify trends and industry involvement. A data set of publications was created based on collected materials from Scopus and social media and analyzed using statistical tests, rigorous content analysis, and network analysis. The data set was used to develop a framework for assessing the maturity of research topics and a classification system for labeling publications. The framework includes some indicators, such as total publications and a variety of applications, which are assessed based on a scale of 4. The classification system suggests four components: (1) product, (2) construction and demolition waste, (3) additives, and (4) experiments to be considered by authors. The framework and the categorization system may assist academics and practitioners in predicting topic trends and offer a set of indicators for conducting systematic reviews to identify gaps in the literature. Also, total publications as one of the framework indicators reveals that 46% of Canadian publications and 20.7% of US publications exhibited industry involvement compared with 15% of Australian publications and 15% of UK publications. The analysis shows that the top-occurring keyword in the data set is recycled asphalt pavement, which is linked to 22.2% of the data set, followed by recycled concrete and recycled aggregate concrete appearing in 12%. Aside from keywords related to materials, two of the most commonly occurring techniques in the data set of keywords are building information modeling and life cycle assessment, which still need further investigation along with GIS for waste minimization.

Circular economy strategies in modern timber construction as a potential response to climate change

Abstract: This paper aims to present recent circular economy (CE) cases used for modern methods of timber construction (MMTC) and examine the CE strategies in this context. The research problem of CE strategies in timber construction is explored, emphasizing its importance in addressing global climate change challenges. Based on a practical perspective, a two-phase research method was used. First, some key reports from the MMTC grey literature are selected based on an extensive internet search by entering relevant keywords related to the CE and timber or wood. Second, a systematic search within the Scopus database was conducted to identify the most relevant publications focusing on CE applications and case studies in the MMTC context. The review of the selected literature shows that the most frequently repeated strategies are those related to the recycling and reusing of CE-related strategies for timber construction. Key CE design principles and their related strategies in MMTC were identified and explained. Based on the findings, it can be concluded that using timber as a reusable and recyclable material for offsite construction is one of the most efficient ways in which to apply CE to creating dedicated benefits and is a key aspect of MMTC. An in-depth examination of CE strategies in MMTC is the key contribution of this review paper. Scholars are assisted in identifying knowledge gaps by the findings of this paper since the paper outlines the key strategies and challenges of MMTC. The paper also provides unique practical information, familiarizing practitioners with the required strategies for enhancing the circularity of buildings made of timber during the design and construction phases.

Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes

Abstract: Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height.