Large-scale Construction Projects Research Articles

A construction schedule management method of large-scale construction project based on BIM model

A construction schedule management method of large-scale construction project based on BIM model

Research on Detection and Safety Evaluation System of Huimin Lane Bridge based on BIM

With the continuous improvement of the national social and economic level the size and quantity of various types of infrastructure in our country have been improved and the community has put forward higher requirements on the level and quality of the construction. In recent years the bridge collapse accidents occur frequently, but our country bridge inspection and safety assessment of the system was established late, our country bridge structure health monitoring system research and application began in the 90. of the 20th century, the implementation of large-scale infrastructure construction projects, bridge health monitoring system also will be rapid development this paper discusses the based on BIM bridge inspection and safety assessment system, and puts forward some practical measures, provides the reference for improving bridge inspection and safety assessment of the system operation level.

Research on risk evaluation of logistics park construction project by FMEA based on hesitation environment

Logistics Park, as a large-scale construction project, has many risk factors that may affect the normal operation of the project in its construction. If the influence of risk factors is ignored, it will bring irreparable losses. Therefore, according to the characteristics of logistics park construction project (LPCP), it is of great practical significance to propose a new risk management model for the risk research of LPCP. Considering the whole project, this paper puts forward a new risk analysis model for construction projects, establishes a risk evaluation index system according to the causes and possible consequences of risks, describes the uncertainty and hesitation of failure mode and effects analysis (FMEA) team members’ risk evaluation information based on the uncertainty language Z number, calculates the expert weights by means of dynamic weight adjustment method, and then uses fuzzy C-means clustering algorithm to deal with the risk evaluation of LPCP.

A Novel and Intelligent Safety-Hazard Classification Method with Syntactic and Semantic Features for Large-Scale Construction Projects

To improve the efficiency of safety management, it is important to classify massive and complex construction site safety hazard texts in large-scale projects. High-precision safety hazard text classification is a lengthy and challenging process. Most existing safety hazard text classification methods capture semantic information using machine learning or deep learning, ignoring the syntactic dependency between words. However, syntactic dependency contains rich structural information that is useful to alleviate information loss and enrich text features. To address these issues, this study proposes a graph structure–based hybrid deep learning method to achieve the automatic classification of large-scale project safety hazard texts. The method uses syntactic dependency and Bidirectional Encoder Representation from Transformers to express the syntactic structure and semantic information of text, and a graph structure fusing the syntactic structure and semantic information is constructed to quantify text information. Further, an encoding-decoding mechanism is built using a graph convolutional neural network and bidirectional long short-term memory to address graph structure data and classify safety hazard texts. Our proposed method is used to classify hydraulic engineering construction safety hazard texts, and the classification accuracy reaches 86.56%. Meanwhile, the experimental results demonstrate that our model achieves superior performance compared to existing methods. This proves the ability of our model to capture and analyze text information and verifies the reliability and effectiveness of this method in large-scale project safety hazard management.

Construction Schedule Management System for Large-Scale Construction Projects Based on Multisensor Network.

As an important task of construction project management, construction schedule management is related to the realization of project period, cost, quality, and other objectives. However, in actual construction, problems such as difficulties in plan implementation and management are often encountered, and schedule delays often occur. Moreover, with the increase in the scale and complexity of modern buildings, the management of construction schedules has brought about larger issues and higher requirements have been put forward for the management level of the construction schedule. The traditional timetable management and scheduling is not highly relevant to the project entity. There is no entity change, the project information loss is serious, the tracking and control of the construction timetable is not in place, there is fine management, and the construction timetable management cannot meet the needs of modern construction. In order to ensure the smooth implementation of projects and objectives, it is urgent to explore new management ideas and methods to promote the smooth progress of construction process management. BIM technology has the advantages of visibility, simulation, adjustment, optimization, and advanced data integration, which helps to make up for the shortcomings of previous schedule management and improve the level of construction schedule management. Based on the research situation of large-scale construction project monitoring system and the analysis of information fusion technology, this paper proposes a large-scale construction project monitoring system scheme based on multisensor network information fusion. Through the investigation of the monitoring content, the composition of the multisensor network is determined. This paper is applicable to large-scale construction projects. Through the research and design of hardware modules, software modules, and fusion algorithms, the data acquisition, transmission, calculation, and display functions of the monitoring system based on multisensor network information fusion are realized, which can effectively monitor the entire process of large-scale construction projects.

Exploring the Application of BIM Technology in the Whole Process of Construction Cost Management with Computational Intelligence.

The construction industry is a labor-intensive industry in China. In recent years, as people's living standards have risen, so have their requirements for the functionality, appearance, and comfort of buildings. The amount of information attached to construction projects is also increasing, especially for some modern large-scale construction projects. Due to the long construction period and a large amount of information in the construction process, the difficulty of project engineering management has also increased significantly. At the same time, with the gradual development and improvement of China's market economy system, the prices of labor and materials in the construction industry continue to rise, and the huge consumption of energy and resources no longer meets the strategic requirements of sustainable development. Therefore, construction project cost management is facing a huge impact, the actual effect of construction project cost management work is not good, and the phenomenon of uncontrolled construction project investment commonly occurs. The use of BIM software to build a building information model can integrate information from all stages of the project and facilitate the participation and cooperation of all project entities. Cost management is carried out before the actual construction of the project, thus realizing the whole process of cost management and effectively avoiding the occurrence of actual costs exceeding the budget after the project is completed. The study analyses the suitability of applying BIM technology to the whole process of construction project cost management with computational intelligence and explains the value and advantages of BIM in the whole process of construction project cost management. On this basis, this research provides a specific analysis of the application of BIM technology in the process of cost management at various stages of the whole process of construction projects and thus puts forward suggestions that can solve the obstacles that may be encountered in the whole process of cost management of construction projects in China.

SAR-based Subsidence Monitoring and Assessment of the Factors Involved in the Occurrence of Subsidence, Lahore City

The judicious use and management of natural resources is vital to achieve sustainable development. Land and water are prime natural resources, and their depletion and degradation can lead to serious threats like land subsidence. Land subsidence is a phenomenon of the alteration of elevation at a point on the earth through the sinking of the surface. It occurs when the earth's surface loses its support. The major causes of land subsidence include groundwater extraction, mining, construction overload, and other similar factors that increase pressure on the surface and eventually subsidize the land. Urban centers with excessive groundwater extraction and infrastructure development are at a high risk of subsidence. Lahore, the second-largest city in Pakistan, is undergoing an enormous increase in population density, uncontrolled urbanization with very large-scale construction projects, and intensive groundwater extraction which are responsible for subsidence directly or indirectly. Therefore, studies on groundwater status and unplanned urban appraisals have seriously urged monitoring of the subsidence in Lahore. Herein, we used freely available Sentinel-1 data for one year (from August 2018 to August 2019), with a high spatial and temporal resolution, to monitor subsidence in Lahore. The data were processed using the SNAP/StaMPS approach for Persistent Scatterer Interferometric Synthetic Aperture Radar (PSI) analysis, which is an advanced InSAR technique. The displacement velocity map from InSAR processing shows a significant land deformation in the area with values ranging from –114 to 15 mm yr–1. Along with the Sentinel-1 data, we also used supplementary data obtained from various government agencies of Pakistan to study the land cover map, transportation network and waterways of Lahore, soil types, population density, and field points for assessing the results and understanding the roles of various factors in the occurrence of uplift or subsidence. A strong correlation was established between subsidence and various parameters such as groundwater extraction and lowering of the water table, soil type variations, land cover changes, surface water channels, and population density. The deformation map confirms the greatest subsidence in the central part of Lahore, while the uplift is observed in the less populated and rural areas situated near Ravi River. The land subsidence and uplift could be attributed to groundwater extraction and recharge through the canal system and the river, respectively.

Spatial–temporal evolution of ESV and its response to land use change in the Yellow River Basin, China

The value of ecosystem services, as well as their temporal and spatial characteristics, can be used to help areas develop focused and localized sustainable ecological management plans. Thus, this study conducted in the Yellow River Basin (YRB) of China, analyzed the ecosystem service value (ESV) and its spatial–temporal variation characteristics. This study used the equivalent factor and geospatial exploration methods, introduced the elasticity coefficient, and explored the response of ESV change to land-use change, based on the land use cover data from 1990 to 2020. The results showed that from 1990 to 2020, YRB ecosystem service value showed an overall increasing trend, mainly because the ecological construction project increased forest and grasslands in this region. In the past 30 years, spatial characteristics of ESV in YRB was relatively stable. The high-value areas were mainly distributed in the upper Yellow River Basin, while the low-value areas were mainly distributed in the lower Yellow River Basin, as the cold and hot spots were reduced. The ESV barycenter coordinates showed the direction of the transfer trajectory, which is first to southwest, northeast, and then to southwest. From 2000 to 2010, YRB land-use change had greater impact on ESV. Since 2010, the disturbance of ecosystem services by land-use change has decreased. Consequently, the elastic index of the upstream and Loess Plateau regions were significantly higher than that of other regions, and the impact of land-use change on ecosystem services was more obvious, due to improved large-scale ecological construction projects implementation. Conclusively, this study recommends the use of comprehensive spatial–temporal assessment of ESV for sustainable development and ecological protection in the YRB.

An earned-value-analysis (EVA)-based project control framework in large-scale scaffolding projects using linear regression modeling

In large-scale industrial construction projects, scaffolding activities account for a large amount of the construction budget, and overlooking the scaffolding management can lead to budget overruns and schedule delays. The scaffolding activities can be categorized by classifications and types based on the nature of the scaffold builds. To ensure the project progress on track, it is critical to measure project performance based on project progress data. However, given the nature of scaffolding activities, it has been challenging to track and utilize the scaffolding data for analytical purposes. Therefore, this paper proposes a project control framework based on Earned-value analysis (EVA), in which linear regression models are used for productivity prediction. Three scenarios of productivity based on historical data (i.e., low, medium, and high productivity) are introduced. The proposed framework is implemented in a real construction project for validation. The results have shown that the proposed framework can efficiently evaluate the project progresses integrated with the EVA. The construction companies, such as general contractors and scaffolding sub-contractors, can use this method for site progress tracking. For future work, the EVA can be integrated with other non-linear predictive models (e.g., neural network) for productivity prediction. The EVA results can be integrated with data visualization to create situational awareness for construction practitioners.

Exploring rumor combating behavior of social media on NIMBY conflict: Temporal modes, frameworks and strategies

With the development of social media, mass unreliable information is circulated which amplifies the impact on NIMBY conflict, which is caused by public concern about the negative externalities of development projects. Understanding the behavior of rumor combating provides significant insights for crisis management relating to public acceptance of large-scale infrastructure initiatives, construction projects or energy facilities. However, few studies have addressed how rumor combating behavior develops due to the online rumors in such crises. Accordingly, this study aimed to investigate the formation and the effect of rumor combating behavior on NIMBY conflict with the analytical framework by content analysis and curve fitting method based on Situational Crisis Communication Theory. In this framework, the temporal modes and frameworks evolution of the counter-rumors are illustrated, the influences and behaviors tendency of multiple rumor refuters are examined, and the effects of the rumor combating strategies are explored via acceptance analysis. The results show that there are two key diffusion cycles in the progress of rumor combating, and early counter-rumors can pre-emptively protect the users' attitude. The interactive features of the framework between rumors and counter-rumors vary at different stages and an Assessment framework can provide a quick response to combat rumors. In addition, Media practitioners and News organizations act as the bellwether in rumor combating action, while Individuals and Elites are the main forces as the rumor refuters. Refutation and Guide, fact-based rumor combating strategies, show great persuasive impact. These findings will help the government and relevant entities to implement rumor combating strategies to minimize the potential exacerbation of NIMBY conflict.

In on the Ground Floor: Involving IP in New Hospital Design and Development

Background Infection Prevention is a critical element underlying every aspect of the healthcare environment, but it is often overlooked during the design of a new facility, leading to decisions being made in a vacuum without proper expertise. By reversing this paradigm and involving Infection Prevention as a key stakeholder from the outset, far-reaching decisions can be made holistically, influencing everything from flow of clean and dirty equipment to placement of airborne infection isolation rooms and beyond. Methods To develop two new facilities for a major hospital system, leadership established a multidisciplinary team to shape a bottoms-up approach. Maturing from space allocation to department-specific requirements to operational logistics and the day-to-day user experience, this team is working to optimize design from a staff and patient perspective. Crucially, while this team incorporates representation on a unit-by-unit basis, it is founded upon a core group of system leaders, architects, and infection prevention and regulatory subject matter experts, ensuring a high standard of quality across the enterprise. Results Halfway through the initial design phase, this approach has yielded a number of pivotal decisions. For example, the team designated separate clean and dirty elevators while mapping a travel path to minimize cross-contamination. They provisioned for a breakdown room in departments with voluminous deliveries to segregate packaging material from clean supplies. They ensured that sanitization stations were logically allocated throughout each unit, removing barriers from the hand hygiene process. These and other choices would not have been possible without Infection Prevention being a foundational stakeholder. Conclusions The unique contributions enabled by this bottoms-up, multidisciplinary approach demonstrate that this paradigm for facility design presents distinct strengths. Establishing a core leadership group that prioritizes subject matter experts as key stakeholders inherently drives higher quality standards for facility development, and key lessons learned should be extracted and implemented for other large-scale construction projects. Infection Prevention is a critical element underlying every aspect of the healthcare environment, but it is often overlooked during the design of a new facility, leading to decisions being made in a vacuum without proper expertise. By reversing this paradigm and involving Infection Prevention as a key stakeholder from the outset, far-reaching decisions can be made holistically, influencing everything from flow of clean and dirty equipment to placement of airborne infection isolation rooms and beyond. To develop two new facilities for a major hospital system, leadership established a multidisciplinary team to shape a bottoms-up approach. Maturing from space allocation to department-specific requirements to operational logistics and the day-to-day user experience, this team is working to optimize design from a staff and patient perspective. Crucially, while this team incorporates representation on a unit-by-unit basis, it is founded upon a core group of system leaders, architects, and infection prevention and regulatory subject matter experts, ensuring a high standard of quality across the enterprise. Halfway through the initial design phase, this approach has yielded a number of pivotal decisions. For example, the team designated separate clean and dirty elevators while mapping a travel path to minimize cross-contamination. They provisioned for a breakdown room in departments with voluminous deliveries to segregate packaging material from clean supplies. They ensured that sanitization stations were logically allocated throughout each unit, removing barriers from the hand hygiene process. These and other choices would not have been possible without Infection Prevention being a foundational stakeholder. The unique contributions enabled by this bottoms-up, multidisciplinary approach demonstrate that this paradigm for facility design presents distinct strengths. Establishing a core leadership group that prioritizes subject matter experts as key stakeholders inherently drives higher quality standards for facility development, and key lessons learned should be extracted and implemented for other large-scale construction projects.

Identification of the main causes of risks in engineering procurement construction projects

Abstract Many risks have adverse consequences for construction projects’ objectives such as quality, schedule, and cost. As engineering procurement construction (EPC) contracts gradually become one of the most common types used in implementing major large-scale construction projects, identifying common risk types and analyzing their root causes is important for developing measures to decrease and eliminate future risks in these types of contracts. The information about the main causes of risks was collected via well-structured questionnaires addressed to construction sector professionals and preparing lists of main potential risks in EPC/construction projects through reviewing literature studies, books, and articles related to this topic. The findings indicate that several causes of risks are more critical for the project including causes related to contract, design and execution, subcontractors, systems, and equipment. The study’s results revealed that the absence of risk management implementation in the EPC construction project is a root cause of the lack of planning and control of the project.

PROJECT DELAY PREDICTION WITH EARNED VALUE METHOD: A CASE ON THE CSS-APARTMENT PROJECT IN SURABAYA-INDONESIA

The risk of delay is very likely to occur in a construction project. Especially in large-scale infrastructure projects that are accompanied by high complexity. Careful planning and prediction both related to aspects of design, implementation, including scheduling are very important. Problems that often arise in large-scale and complex construction projects are early predictions related to delays in the final completion of a project. This study aims to predict the occurrence of delays in project completion. Based on secondary data obtained from construction contractors and by using appropriate analytical procedures, the result is that the CSS-Apartment project is predicted to experience a delay of 57 weeks from the planned 146 weeks. The data is obtained directly from the project site. After all the data has been obtained, the processing is carried out using the Earned Value Method. Literature study is done by reading literature related to this writing Based on the case of an apartment project called CSS-Apartment Project in Surabaya - Indonesia, and using the Earned Value method.

Models, mock-ups and materials: artefacts of collaboration in the planning of large-scale construction projects

ABSTRACT This paper explores the dynamic nature of collaborations in construction projects by analysing the artefacts built environment professionals develop, use and transform over the project course. The authors introduce the concept of ‘artefacts of collaboration’ that systematizes different artefacts types, to provide insights into how collaborations emerge and unfold across distinct disciplines and different project stages. Empirically, the concept is derived from 35 in-depth interviews with professionals involved in four large-scale construction projects. Theoretically, the concept is based on a pluralistic approach combining productively the concepts of boundary and epistemic objects to address better the specificities of collaborations in construction projects. More specifically, the concept of artefacts of collaboration allows exploring how collaborations transform across the ‘design-construction’ divide that largely defines the interactions and relationships between built environment professionals. Hereby, through the analysis of artefacts of collaboration the paper reveals different modes of collaboration and how the roles and responsibilities of project partners change through these modes of collaboration.

Research and Analysis of Global Weather Extremes Affecting Civil Engineering Construction Schedules Based on LSTM Algorithm

The occurrence of extreme weather events will cause serious harm to natural ecosystems, human social economy and construction sites. Large-scale construction projects have a long cycle and complex construction environment, and the schedule control is obviously disturbed by meteorological and other factors. Risk control of schedule delays is an important part of project risk management. The study of extreme weather events has become a key focus and hotspot in meteorological and climate science research in the context of global change. This paper proposes a more objective approach to defining extreme climate events from the study of extreme climate event uncertainty. On this basis, the spatial and temporal characteristics of extreme temperature and precipitation in recent decades are analysed. Considering the variability of precipitation and temperature, an idea is proposed to study extreme continuous precipitation events, and the mechanism of extreme precipitation occurrence in the region is explored. Finally, the LSTM model data are used to carry out studies and projections of changes in extreme climate events under different future scenarios.

Cost Early-Warning Model System of Large-Scale Construction Project.

China's construction industry has been suffering from high cost, high efficiency, and maladjustment of management. The traditional management mode makes the construction project face the risk of cost overruns and delays, which cannot achieve the effect of cost control. Therefore, by summarizing the characteristics of construction projects and the classification of costs, this paper analyzes the foundation of earned value management method in construction and combines it with cost management; in addition, the actual development of Company A is taken as an example, where a cost early-warning system suitable for construction projects is constructed, including the design of the organizational structure, operation platform, and early-warning model of this system, which can improve the cost management level of construction enterprises to a certain extent.

Additively manufactured thermoplastic polyurethane (TPU) mold for concrete casting of complex structure

PurposeIrregularly shaped architectural designs with surfaces curved in multiple directions, known as free-form designs, have gained significant public interest in recent decades. However, it is challenging to convert complex designs into real structures. This paper aims to realize free-form construction by developing a novel workflow in which additively manufactured thermoplastic polyurethane (TPU) molds are used.Design/methodology/approachThe workflow is developed through mechanical tests on additively manufactured TPU specimens, determination of TPU mold design criteria and exploration of mold preparation methods. Two concrete elements with free-form geometries are fabricated using the proposed workflow.FindingsTPU is a thermoplastic elastomer that is strong and inexpensive, making it an ideal mold material for casting complex concrete structures. An innovative workflow is developed in which TPU molds are used, appropriate release agents are selected for different concrete casting conditions and a mold subdivision method is proposed to facilitate the demolding process. Furthermore, the integrity of TPU molds can be maintained by following the proposed workflow, enabling repetitive use of molds. The fabrication of the two free-form structures shows that complex concrete members with high dimensional accuracy and excellent surface quality can be manufactured using the proposed method.Originality/valueTo the best of the authors’ knowledge, this is the first systematic study on using additively manufactured TPU molds for concrete casting of complex structures. The new techniques developed in this research can be applied to large-scale architectural, engineering and construction projects.

Organizational and technological platform of construction

Introduction. At present, due to the active introduction of digital technologies, technological platforms are actively developing, the purpose of which is the implementation of various products. The presented study considers the organizational and technological platform of large-scale construction projects — a set of material and labor resources, organizational and technological solutions that allow, through their interaction, using modern information modeling technologies, to create construction objects with specified technical and economic characteristics.
 
 Materials and methods. For the formation of the organizational and technological platform, the methods of the goal tree and the analysis of hierarchies are used. A decomposition of a complex system is presented, presented at three levels of the goal tree and described using the analysis of hierarchies. At the top level, the goal of the project, followed by the problem (task), and at the last, lower level of the tree of goals are directions for solutions.
 
 Results. For the most adequate analytical description, it is proposed to use the hierarchy analysis method, which makes it possible to decompose the above factors that make up the goal tree and obtain specific criteria and alternatives inherent in large-scale construction projects, based on the principle of smart criteria formation. The creation of a mathematical model of an organizational and technological platform should be carried out using the possibility of constructing priority weight vectors that take into account the significance of all criteria, and each criterion is weighted based on these data. The integral assessment of indicators weighted for each criterion can be the final weight in the criterion structure. Detailed development of the mathematical apparatus for obtaining an integral estimate will be the subject of further research.
 
 Conclusions. The organizational and technological platform of large-scale projects in construction is a tool for the interaction of all participants in the implementation of such projects, aimed at the successful implementation of the set goals — achieving design indicators in terms of duration.

Predicting financial losses due to apartment construction accidents utilizing deep learning techniques

This study aims to generate a deep learning algorithm-based model for quantitative prediction of financial losses due to accidents occurring at apartment construction sites. Recently, the construction of apartment buildings is rapidly increasing to solve housing shortage caused by increasing urban density. However, high-rise and large-scale construction projects are increasing the frequency and severity of accidents occurring inside and outside of construction sites, leading to increases of financial losses. In particular, the increase in severe weather and the surge in abnormal weather events due to climate change are aggravating the risk of financial losses associated with accidents occurring at construction sites. Therefore, for sustainable and efficient management of construction projects, a loss prediction model that prevents and reduces the risk of financial loss is essential. This study collected and analyzed insurance claim payout data from a main insurance company in South Korea regarding accidents occurring inside and outside of construction sites. Deep learning algorithms were applied to develop predictive models reflecting scientific and recent technologies. Results and framework of this study provide critical guidance on financial loss management necessary for sustainable and efficacious construction project management. They can be used as a reference for various other construction project management studies.

An Optimization Framework for Power Infrastructure Planning

The ubiquitous expansion and transformation of the energy supply system involves large-scale power infrastructure construction projects. In view of investments of more than a million dollars per kilometre, planning authorities aim to minimize the resistances posed by multiple stakeholders. Mathematical optimization research offers efficient algorithms to compute globally optimal routes based on geographic input data. We propose a framework that utilizes a graph model where vertices represent possible locations of transmission towers, and edges are placed according to the feasible distance between neighbouring towers. In order to cope with the specific challenges arising in linear infrastructure layout, we first introduce a variant of the Bellman-Ford algorithm that efficiently computes the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">minimal-angle</i> shortest path. Secondly, an iterative procedure is proposed that yields a locally optimal path at considerably lower memory requirements and runtime. Third, we discuss and analyse methods to output <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k$</tex-math></inline-formula> diverse path alternatives. Experiments on real data show that compared to previous work, our approach reduces the resistances by more than 10% in feasible time, while at the same time offering much more flexibility and functionality. Our methods are demonstrated in a simple and intuitive graphical user interface, and an open-source package (LION), available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://pypi.org/project/lion-sp/</uri>