Building Information Research Articles

Rapid remote volcanic ashfall impact assessment for the 2022 eruption of Hunga volcano, Tonga: a bespoke approach and lessons identified

When disasters occur, rapid impact assessments are required to prioritise response actions, support in-country efforts and inform the mobilisation of aid. The 15 January 2022 eruption of Hunga volcano, Tonga, and the resulting atmospheric shockwave, ashfall, underwater mass disturbance and tsunami, caused substantial impacts across the Kingdom of Tonga. Volcanic impacts on the scale observed after the eruption are rare, necessitating a reliance on international advice and assistance. The situation was complicated by the loss of Tonga’s international submarine fibreoptic cable (causing a complete loss of communications for approximately 20 days) along with border closures due to the COVID-19 pandemic. A need emerged for a rapid remote volcanic impact assessment and provision of specialist advice to help inform the response of international partners. Here we present a novel methodology for conducting rapid remote volcanic ashfall impact assessments, conducted over a 10-day period following the eruption. We used three different hazard models for ashfall thickness across the main island of Tongatapu and available asset information and vulnerability functions for buildings, agriculture, electricity networks, water supply and roads, to provide initial estimates of losses due to ashfall from the 15 January eruption. For buildings, we estimated losses both as total losses and as percentages of the total replacement cost of buildings on Tongatapu. For agriculture, we made probabilistic estimates of production losses for three different crop classes. For ashfall clean-up, we estimated ranges of ashfall volumes requiring clean-up from road surfaces and roofs. For water supply, electricity networks and roads, our analysis was limited to assessing the exposure of important assets to ashfall, as we had insufficient information on system configurations to take the analysis further. Key constraints on our analysis were the limited nature of critical infrastructure asset inventories and the lack of volcanic vulnerability models for tropical regions including Pacific Island nations. Key steps towards iteratively improving rapid remote impact assessments will include developing vulnerability functions for tropical environments as well as ground-truthing estimated losses from remote approaches against in-person impact assessment campaigns.

The Neglected Modern Architectural Heritage: Analysis of Housing Estates in the Second Half of the 20th Century from Izmir, Turkey, Case Study Area

Twentieth-century housing estates are an important part of the architectural heritage of the modern age, reflecting not only the evolution of housing forms, but also the technological advances and sociocultural dynamics of the twentieth century. However, awareness of the value of this heritage is still insufficient, resulting in a lack of legal protection and numerous threats in the form of transformation and negligence. In this research, we present the problem using the example of modernist Turkish architecture. The settlements of Izmir, a cosmopolitan port city with a diverse socio-cultural fabric and rapidly developing housing architecture, are chosen as the subject of the study. The main objective of the study is to evaluate the state of conservation and the degree of transformation of the selected estates. The overall assessment of the maintenance of the legibility of urban layouts and the form of individual buildings shows that, despite the lack of systematic protection, it is possible to preserve the existing architectural heritage in the examples analyzed and to provide recommendations for future policies to sustain the heritage values of modernism. The research aims to fill the existing gaps in the discourse on modern housing and contribute to a broader international dialogue on the conservation of modern architecture. By including these estates in the ongoing discussion, we recognize their historical significance and promote their preservation as important participants in contemporary urban life.

A Comprehensive Review of Thermal Transmittance Assessments of Building Envelopes

Improving the energy efficiency of buildings is an important element of the effort to address global warming. The thermal performance of building envelopes is the most important thermal and physical property affecting energy performance. Therefore, identifying the thermal performance of a building envelope is essential to applying effective energy-saving measures. The U-value is a quantitative indicator of the thermal performance of the building envelope quantitatively. Methods for determining the U-value are largely classified into passive methods, which use building information without measurement campaigns, and active methods, which conduct in situ measurements. This paper reviews and evaluates the most commonly used methods and experimental results of previous studies to determine the actual U-value of a building envelope. Accordingly, this paper focuses solely on field measurement studies, excluding laboratory measurements. Comparing the existing methods used to determine the U-value can help researchers choose appropriate field measurement methods and future research directions.

A Geometric Significance-Aware Deep Mutual Learning Network for Building Extraction from Aerial Images

Knowledge-driven building extraction method exhibits a restricted adaptability scope and is vulnerable to external factors that affect its extraction accuracy. On the other hand, data-driven building extraction method lacks interpretability, heavily relies on extensive training data, and may result in extraction outcomes with building boundary blur issues. The integration of pre-existing knowledge with data-driven learning is essential for the intelligent identification and extraction of buildings from high-resolution aerial images. To overcome the limitations of current deep learning building extraction networks in effectively leveraging prior knowledge of aerial images, a geometric significance-aware deep mutual learning network (GSDMLNet) is proposed. Firstly, the GeoSay algorithm is utilized to derive building geometric significance feature maps as prior knowledge and integrate them into the deep learning network to enhance the targeted extraction of building features. Secondly, a bi-directional guidance attention module (BGAM) is developed to facilitate deep mutual learning between the building feature map and the building geometric significance feature map within the dual-branch network. Furthermore, the deployment of an enhanced flow alignment module (FAM++) is utilized to produce high-resolution, robust semantic feature maps with strong interpretability. Ultimately, a multi-objective loss function is crafted to refine the network’s performance. Experimental results demonstrate that the GSDMLNet excels in building extraction tasks within densely populated and diverse urban areas, reducing misidentification of shadow-obscured regions and color-similar terrains lacking building structural features. This approach effectively ensures the precise acquisition of urban building information in aerial images.

A study on the digital restoration of an ancient city based on historic building information modeling of wooden architectural heritage: focusing on Suwon Hwaseong

This study describes the process of digitally reconstructing the ancient Korean city of Suwon Hwaseong in 3D utilizing Historic Building Information Modeling (HBIM) resources to accurately represent its wooden architectural heritage. Previous 3D reconstructions of cultural heritage have often prioritized appearance or remained partially disassembled. However, our reconstruction method offers a comprehensive representation of the appearance and the internal structure of wooden architectural heritage, which can be suitable for restoration maintenance. To ensure accuracy in digital restoration, we collected and utilized administrative records and historical materials, including the geography, fortress walls, folk houses, and Haenggung (the temporary palace of the Joseon Dynasty)—drawing from the archive of the Korean Cultural Heritage Service’s management records and the 1796 manuscript “Uigwe: Royal Protocols of the Hwaseong Fortress” which documents the construction of the ancient city of Suwon Hwaseong. Extensive architectural records were used to generate HBIM data, which digitized historical records, documents, and drawings to accurately represent the complex layout of the wooden architectural heritage. For the folk houses that lacked design records and the fortress walls that retained their original shape, we performed a digital restoration-based façade modeling. These elements of the ancient city of Suwon Hwaseong were assembled into a 3D model using Unreal Engine (version 5.1.1) to digitally reconstruct the city and enhance its visual representation. The digital restoration content, which utilizes visual effects and precise rendering from a game engine, can be used for the restoration, repair, and maintenance of both appearance and internal structures.

Semantic Enrichment of Non-Graphical Data of a BIM Model of a Public Building from the Perspective of the Facility Manager

Building information modeling (BIM) is undeniably the most important trend in the digitization of the construction sector in recent years. BIM models currently being built are extremely geometrically rich, that is, they are modeled at a high level of detail in terms of geometry. Thanks to object-oriented programming paradigms, BIM models include high-level relationships to ensure interactions between objects, rapid view generation, and documentation. However, these models are not always equally rich in non-graphical data. This is true for parameters at the library object level, with which building object models are saturated, but also at the project, site, building, or floor levels according to the structure of the interoperable industry foundation classes (IFC) format. The current state of knowledge also lacks a clear methodology for inputting such data. For this reason, experimental work was undertaken on semantic enrichment in non-graphical data of a public building (a public kindergarten, Secemin, Poland), which has its BIM model at a high level of geometric detail but is poor in non-graphical data. As a result of the research and development work, all levels of the IFC structure were saturated with non-graphical data and validated, and the possibilities of their use were shown from the perspective of the facility manager. Documentation from the manager was used to achieve this goal, and selected analyses and simulations were performed on the enriched model. This article contributes to the discussion on semantic enrichment from CAD3D to BIM by presenting a detailed process for entering non-graphical data into a BIM model. The presented data entry method can be used by both modelers and facility managers. Thus, this paper fills an important research gap related to semantic enrichment in non-graphical data at different levels of the IFC structure.

Reducing uncertainty of building shape information in urban building energy modeling using Bayesian calibration

This study proposes urban building energy modeling that extends beyond single-building-level models to the urban level. However, most urban building energy models use representative buildings that may not accurately reflect the diversity of building shapes, systems, and envelope performance when conducting building energy evaluations at the urban scale. To address this issue, previous studies have utilized representative buildings and Bayesian calibration to estimate uncertain building information parameters without considering building shape information. Therefore, the primary objective of this study is to estimate building shape information using artificial neural networks and Bayesian calibration based on building energy consumption data to identify the shape information uncertainty of representative buildings. The results indicate that some shape information can be estimated by comparing the overall distribution of the building stock using the two-sample Kolmogorov–Smirnov test. Furthermore, we found that the proposed energy modeling methodology yields energy consumption patterns similar to those of the target building stock. This preliminary investigation addresses the uncertainty of representative buildings in urban-scale modeling, elucidates the relationship between building form and energy consumption, and introduces a method for inferring shape information from energy consumption data.

Consolidating building greening: Integrating mobile modular vertical greening systems into prefabricated building

Vertical greening systems increase green plant coverage within built environments, enhancing urban air quality while reducing building energy consumption. But they encounter challenges related to intensive maintenance and significant costs. As a mainstream future building form, the characteristics of modularization and factory customization inherent in prefabricated buildings can effectively address the demands of vertical greening system. This study employs structural equation model and cloud model to examine the feasibility of integrating mobile modular vertical greening system into prefabricated structures, based on a survey of 403 respondents in Shandong Province, China. The study highlights the supportive roles and mediating effects of two maintenance management measures. It confirms the strong correlations between cost control strategies and the successful integration of mobile modular vertical greening system into prefabricated building. The results indicate that integrating intelligent technology and plant-microalgae combined systems are essential exogenous and endogenous maintenance management strategies. They exert a positive influence on prefabricated modular vertical greening systems. A positive interconnection exists between integrating intelligent technology and the plant-microalgae combined system. Carbon credit trading incentive proves more advantageous in reducing mobile modular vertical greening system costs. Plant-microalgae combined system playing a partial mediating role. Although crowdfunding-community participation does not significantly reduce the costs of mobile modular vertical greening system, integrated intelligent technology mediates this relationship. This highlights the indirect role of crowdfunding-community participation in facilitating cost control for these systems.

Career resources and securing quality work: graduate perspectives

ABSTRACT Empowering graduates to secure quality post-graduation employment is a key goal for higher education institutions and their students. University support in developing career resources may aid transition to work by enhancing social support and networks, fostering a strong sense of professional self, promoting career self-management, and instilling career confidence. Yet there lacks empirical understanding of these resources and the role they play, including how they interrelate, how they vary by personal characteristics, and how they are developed. This study examines how graduates fare in the labour market, characterises their career resources, and explores the relationship between career resources and graduate-level employment. These insights will contribute to theoretical understanding of building employability and inform effective employability programmes in higher education. The mixed-method approach encompasses an online survey of 324 bachelor graduates of Australian universities, followed by focus groups to further explore participants’ experiences. Employed graduates felt that their work did not align adequately with their degree-based knowledge and skills. Those with greater career confidence, social support, and career self-management experienced better outcomes, with these resources showing strong interconnections. Universities should consider a multi-faceted approach in developing employability, addressing multiple dimensions of career resources from the beginning of students’ degrees.

Digital preservation of heritage urban facades: An integrated approach using historic building information modeling and shape grammar analysis

Traditional heritage architecture is renowned for its unique characteristics, which are shaped by local climatic, social, and construction requirements, as well as specific architectural styles that contribute to a sense of identity and place. Preserving the aesthetic and cognitive values inherent in traditional styles poses a significant challenge compared to other tangible assets. However, the digitization of built heritage offers a proactive approach to conservation. In this regard, the management of heritage building information through Building Information Modeling (BIM) plays a crucial role in preventive conservation. The utilization of multi-dimensional digital information models, known as Historic Building Information Modeling (HBIM), is one such approach. This study aims to explore the application of HBIM in representing built heritage, focusing specifically on the research gap pertaining to the need for an effective and integrated methodology for modeling information related to heritage urban facades. The objective is to generate parametric models within the framework of HBIM information management, thereby contributing to preventive preservation mechanisms. The methodology employed in this study consists of two main parts. Firstly, information is derived by analyzing the structural characteristics of heritage facades using Shape Grammar. Secondly, the acquired information is utilized to develop a comprehensive library of HBIM for heritage architectural elements. The results of this study demonstrate the proposed methodology's effectiveness in determining heritage urban facades' morphological, mathematical, relational, and Euclidean characteristics.

Federating cross-domain BIM-based knowledge graph

Despite decades of the digitization of the construction industry, interoperability challenges prevail. One of which is the lack of sufficient integration between domain-specific BIM models. Therefore, the paper proposes a novel methodology for federating cross-domain BIM-based knowledge graphs. The approach leverages the integration of multiple models into a single knowledge graph, aiming to bridge the existing gaps in data exchange and enhance the semantic richness of building information models. Through a detailed exploration of existing data exchange mechanisms, popular ontologies, and schema limitations, this research addresses the interoperability dilemma. A practical demonstration, encapsulated in the “LBD-Online-Merge” demo application, validates the methodology’s efficacy in real-world scenarios, illustrating its potential to revolutionize building operations management and data preparation for the operational phase of a building’s lifecycle. This study significantly contributes to the academic and practical discourse by providing a robust framework for achieving a more integrated, intelligent building information management ecosystem, setting a new benchmark for future research and applications in constructing semantically rich digital twins of the built environment.

Legal Protection for Creditors Due to Problem Credit with Collateral Rights Guarantee

Legal consequences of the implementation of the Power of Attorney to Charge Mortgage Rights in the implementation of the Sale and Purchase Agreement by a Notary based on the main agreement, namely the Credit Agreement in Banking which is not followed by the making of a Deed of Granting Mortgage Rights and analyzing legal protection for creditors in credit agreements with the execution of mortgage guarantees if the debtor is in default for settlement due to problematic credit. Based on Article 8 of Law No. 10 of 1998 concerning Amendments to Law No. 7 of 1992 concerning Banking in providing credit, banks apply the principle of "5C" which is mainly to see the customer's ability to accept the credit applied for. If the debtor defaults so that problematic credit occurs, then they can file for the execution of the Mortgage Guarantee if the collateral is in the form of land or buildings for the implementation of the SKMHT along with the APHT by a Notary. The purpose of this study was to determine the regulations for debtors who are in default in credit agreements with the imposition of Mortgage Rights and legal protection for creditors in the event that the debtor is in default. By using normative-empirical research methods, data collection techniques in the form of primary data by interviewing informants as informants and secondary data in the form of documents related to the problems studied to obtain conclusions if the debtor defaults in a credit agreement with the imposition of Mortgage Rights, based on the regulations of Law No. 4 of 1996 concerning Mortgage Rights, it states that the imposition is carried out by making a credit agreement first, then the imposition of mortgage rights and registration of the Deed of Granting Mortgage Rights with a predetermined time limit. So that there is legal protection for creditors so that the debtor's debt repayment can be carried out in accordance with the provisions of the Mortgage Law concerning the creditor's right to sell the object of the mortgage right

Utilizing building information modeling (BIM) in the operation phase of civil infrastructure to analyze reinforcement corrosion induced by carbonation

Utilizing building information modeling (BIM) in the operation phase of civil infrastructure to analyze reinforcement corrosion induced by carbonation

Multi-objective optimization of building energy consumption and thermal comfort based on SVR-NSGA-II

It is necessary to reduce the huge energy consumption of buildings while ensuring indoor thermal comfort. The building envelope design notably affects the energy consumption and indoor thermal comfort. This study proposes a framework of support vector regression non-dominated sorting genetic algorithm-II (SVR-NSGA-II) to study the multi-objective optimization of buildings and discover the best building envelope design. First, the data are obtained by OpenStudio 1.1.0 simulation. Then SVR is used to describe the relationships between the parameters and the two objectives. Using SVR models as the objective functions, NSGA-II is applied to optimize the objectives. Finally, taking a proposed office building as an example, the developed framework is applied, verifying its feasibility and effectiveness. The optimized parameters of the building envelope are as follows: the exterior wall U-value, roof U-value, exterior wall U-value, solar heat gain coefficient value (SHGC), and south, north, east, west window-to-wall ratios are respectively equal to 0.664 , 0.393 , 1 , 0.381, 0.697, 0.7, 0.273, and 0.254. The design of the proposed building can be modified to provide a more energy efficient and comfortable building. The proposed model saves time and simplifies operation compared with traditional building information modeling methods.

Depth-informed point cloud-to-BIM registration for construction inspection using augmented reality

Augmented reality (AR) is increasingly being used to assist construction inspection onsite. Underpinning this AR-assisted inspection is a technique called registration, which aims to align the physical world with a digital building information model (BIM) so that the as-built can be intuitively compared with the as-designed. Despite its importance, how to precisely and efficiently register BIM to the physical world still remains a challenge. This paper contributes to tackling the challenge by proposing a novel depth-informed point cloud-to-BIM registration (D-PC2BIM) algorithm. The idea is to enhance registration performance by estimating the depth of a sparse point cloud to inform interpolation of the missing points and to extract the endpoints that matter most in a registration. A novel integration algorithm is proposed to improve the success rate of final registration. Experiments demonstrate the effectiveness of the proposed algorithm, which outperformed existing approaches with higher accuracy and faster speed. The contribution of the study resides in the development of the D-PC2BIM algorithm and a demonstration of its applicability in enabling construction inspection using AR.

A status digital twin approach for physically monitoring over-and-under excavation in large tunnels

Accurate assessments of over-and-under-excavation volumes during tunnel construction are critical for stability and structural safety. Over-and-under-excavation assessment is typically time-consuming as it is undertaken manually and is prone to inaccuracies that adversely impact quality, safety, and costs. To overcome this problem, a status digital twin (to monitor physical conditions) is developed to assess over-and-under excavation during tunneling, enabling a robust and automated assessment of volumes of earth to be determined. The development of the status digital twin comprises three stages: (1) creating an as-designed building information model and as-built point cloud model; (2) producing an automated status update with newly added data; and (3) calculating the of over-and-under excavation volume by building a Triangulated Irregular Network (TIN). The status digital twin is tested in a large-scale tunnel project to evaluate its feasibility and effectiveness. The average over-and-under excavation thickness is 0.05 m, and the mean error of volume calculation is 4.54 %. The results demonstrate that the status digital twin can accurately assess over-and-under excavation during the construction of large-scale tunnel projects by providing instant feedback concerning over/under excavation, thus enabling quality to be effectively managed and costs to be controlled.

METHODOLOGY OF BUILDING INFORMATION MODELING OF URBAN STREETS AND ROADS

Problem statement. New challenges in road construction require the application of modern and globally recognized best practices in the design and management of road infrastructure construction processes, involving the use of the latest Building Information Modeling (BIM) technologies. The implementation of BIM technologies necessitates conducting research to systematize information, forecast and evaluate outcomes, and develop a modeling methodology. The purpose of the article is to develop a methodology for Building Information Modeling of urban streets and roads. Research Results. The proposed methodology for Building Information Modeling is demonstrated using sections of the street and road network in the city of Dnipro. Digital terrain and site models were created in the InfraWorks software based on geospatial data from remote sensing. Conceptual models of urban streets and roads were developed. The conceptual models were exported to Civil 3D, where the terrain model was refined using ground survey data, analyzed, and used to develop route plans, longitudinal and cross profiles of streets and roads. The detailed and coordinated road design solutions in Civil 3D were exported to InfraWorks to build an integrated road infrastructure. An analysis of the spatial smoothness of routes and sight distances on roads was conducted using the building information model. Models of an overpass and bridge developed in Revit were exported to the road infrastructure model. Traffic management measures were modeled. Using the “Traffic Simulation” tools in InfraWorks, vehicle traffic flows on roads and interchanges of the studied street and road network were simulated, taking into account the actual traffic intensity. The building information models were checked for structural deficiencies using Navisworks software. Conclusion. The proposed methodology for designing urban streets and roads using BIM technology involves the step-by-step development of a digital model utilizing software for the automated design of road infrastructure with the required level of detail at each stage of the design process.

Research and Application Status of Soft Steel Dampers

Soft steel dampers have stable hysteresis characteristics and can effectively dissipate energy under repeated loads, providing good shock absorption effects for structures. It can be used for both seismic design of new buildings and seismic reinforcement of existing buildings. Suitable for various structural forms of buildings, including concrete structures, steel structures, and heavy-duty wooden structures. It is also applied in bridge structures, which can effectively reduce the vibration response of bridges under earthquake, wind vibration, etc., and improve the seismic performance and safety of bridges. Countries with rapid development in the application of structural control technology, such as the United States, Japan, Canada, New Zealand, and Mexico, are the main ones. Italy, France, Russia, Singapore, and other countries are also actively applying it in practical engineering. More than a hundred buildings abroad have adopted soft steel dampers.

Estimating casualties from urban fires: A focus on building and urban environment information

This study developed two prediction models for urban fire occurrence and related casualties via a fire accident dataset from Seoul, South Korea, from 2017 to 2021. Our models exhibit improved predictive performance by incorporating built environment features, such as building characteristics and the urban context, alongside weather and demographic data. This approach showed improved predictive performance suitable for public health implementation. Compared with the weather- and demographic-only models, our models had an 18.1 % greater fire occurrence prediction accuracy and a 10.4 % greater casualty prediction accuracy. Major variables affecting fire occurrence include building characteristics, e.g., the floor area ratio (FAR), building age, and commercial building number. Important features affecting casualty occurrence include demographic aspects, e.g., income level and weather, and network-based features, e.g., road connectivity and fire station proximity. These findings suggest that fire prevention strategies and fire casualty prevention strategies may need to differ. Furthermore, we identify high-risk zones by conducting spatial analysis and fire risk and casualty prediction on all buildings by applying our models to Seoul's Gangnam District. These contributions can promote safe and healthy urban environments by improving fire risk prediction accuracy and providing important insights into urban planning for appropriate urban fire accident response and prevention.

State-of-art review of resilience of bridges and bridge networks

In recent years, many attempts have been made to incorporate resilience frameworks into decision making, establish the best use of available resources and reduce the impact of hazards on bridges and bridge networks. However, scholarly research in this area is still in its early phases, with minimal exploration of research gaps and future prospects. A state-of-the-art review of bridge and bridge network resilience studies using a science mapping approach is presented here. Research on the topic was obtained from the Scopus literature database. The literature database was then analysed using VOSviewer and Nvivo tools to display the domain-specific body of knowledge. The study then focused on the most prolific researchers and disaster types, bridge resilience assessment approaches, current research trends, future directions and theoretical and practical implications. The research paradigm on the resilience of bridges and bridge networks is changing toward the usage of digital tools and technologies. In this context, a framework id proposed by integrating building information modelling/geographic information systems and digital twin models. The proposed framework can aid bridge owners in accumulating iterative data, creating multi-hazard disaster preparedness policies and designing and enhancing life-cycle management and maintenance tasks of bridges and bridge networks.