Building Renovation Projects Research Articles

Adapting Sustainability Certification Systems for Historic Buildings: A Qualitative Comparative Study in Denmark

Historical buildings are unique assets in any society, embodying cultural significance and architectural heritage. Denmark, with its rich architectural background, has taken steps to preserve these values. As the imperative of sustainability continues to grow, recognizing the social, economic, and environmental values of historic buildings is becoming increasingly important. As an important step towards adapting sustainability certification systems for historic buildings in order to identify and preserve their historical values, this paper aims to conduct a comparative analysis between the GBC and HB (Green Building Council–Historic Building), which has been adapted for historic buildings in Italy and the Danish GBC system (GBC-DK or so-called DGNB-DK). The study is based on a theoretical framework underpinned by a systematic approach utilizing a qualitative comparative analysis (QCA) alongside the triangulation method. This includes a systematic literature review comparing the GBC-DK and GBC-HB systems and an analysis of an actual building renovation project at a municipal hospital in Aarhus, Denmark. The findings indicate a notable absence of criteria and sub-criteria pertaining to the protection of tangible and intangible values in the application of the GBC-DK system. It is justified that in order to improve the sustainability of historic buildings in Denmark, a broader and more in-depth study on the adaptation of the GBC-DK system for historic buildings is needed.

Exploring the significance and priority of digital product passports implementation in building renovation projects targeting circular economy

PurposeThis study explores the significance and implementation priorities for Digital Product Passports (DPP) in the context of building renovation projects. It aims to reveal bottlenecks and how a data-driven workflow bridges the DPP understanding/implementation gap, facilitating the transition towards practices aligned with the EU Green Deal goals.Design/methodology/approachA mixed-methods embedded design was employed for a real-case study exploration. Desk research and field observations ground the two-level analysis combining project documentation, namely the Bill of Quantities (BoQ), with different criteria in digitalisation and sustainability, such as economic ratio, 3D modelling, waste management, hazards, energy performance and facility management. All results were interpreted from the DPP lens.FindingsThe analysis revealed a system for identifying building products representing a significant part of the renovation budget. About 11 priority DPPs were found. Some are crucial for both the deconstruction and construction phases, highlighting the need for an incremental and strategic approach to DPP implementation.Research limitations/implicationsThe study is limited to a single case study. Constraints are minimised given the sample's archetype representativeness. The outcomes introduce the need for strategic thinking for incremental DPP implementation. Future research will explore additional criteria and cases.Originality/valueThe research has resulted in a classification framework for DPPs' significance and priority, which is provided with case results. The outcome of the framework provides views on concept alignment to make the implementation in construction more straightforward. Its practical use can be replicated in other projects, emphasizing the importance of data structure and management for the circular economy.

Radial Basis Function (RBF) and Multilayer Perceptron (MLP) Comparative Analysis on Building Renovation Cost Estimation: The Case of Greece

Renovation of buildings has become a major area of development for the construction industry. In the building construction sector, generating a precise and trustworthy cost estimate before building begins is the greatest challenge. Emphasizing the value of using ANN models to forecast the total cost of a building renovation project is the ultimate objective. As a result, building firms may be able to avoid financial losses as long as there is as little discrepancy between projected and actual costs for remodeling works in progress. To address the gap in the research, Greek contractors specializing in building renovations provided a sizable dataset of real project cost data. To build cost prediction ANNs, the collected data had to be organized, assessed, and appropriately encoded. The network was developed, trained, and tested using IBM SPSS Statistics software 28.0.0.0. The dependent variable is the final cost. The independent variables are initial cost, estimated completion time, actual completion time, delay time, initial and final demolition-drainage costs, cost of expenses, initial and final plumbing costs, initial and final heating costs, initial and final electrical costs, initial and final masonry costs, initial and final construction costs of plasterboard construction, initial and final cost of bathrooms, initial and final cost of flooring, initial and final cost of frames, initial and final cost of doors, initial and final cost of paint, and initial and final cost of kitchen construction. The first procedure that was employed was the radial basis function (RBF). The efficiency of the RBFNN model was evaluated and analyzed during training and testing, with up to 6% sum of squares error and nearly 0% relative error in the training sample, which accounted for roughly 70% of the total sample. The second procedure implemented was the method called the multi-layer perceptron (MLP). The efficiency of the MLPNN model was assessed and examined during training and testing; the training sample, which made up around 70% of the overall sample, had a relative error of 0–7% and a sum of squares error ranging from 1% to 5%, confirming specifically the efficacy of RBFNN in calculating the overall cost of renovations.

Energy-saving potential benchmarking method of office buildings based on probabilistic forecast

Building energy consumption represents a substantial portion of China's total energy usage profile. Conducting a quantitative assessment of the energy-saving potential in buildings is crucial, as it aids in estimating the investment risk and payback period for energy-efficient projects. This evaluation also informs the development and formulation of policies promoting building retrofits and energy conservation. However, this field's present state of research exhibits a significant gap. This study takes 8 typical office buildings as case objects and conducts relevant research on quantitative evaluation of energy-saving potential. On the basis of quantile regression, three corresponding probabilistic forecasting models for building energy consumption are established by combining the classic time series prediction algorithm Long Short-Term Memory (LSTM) in data-driven methods, Gradient Boosting Decision Tree (GBDT) in known building energy benchmarking, and a relatively simple linear model. The evaluation results demonstrate that the LSTM-QR model can serve effectively as a probabilistic forecasting model for estimating building energy-saving potential. Based on the LSTM-QR model results, a quantitative evaluation method for building energy-saving potential benchmarking is proposed, utilizing linearized Cumulative Distribution Function (CDF) curves. This method can quantitatively assess the energy-saving potential of the studied buildings. By analyzing and comparing these buildings' hourly energy consumption data over the past three years, it is evident that the quantitative scoring results from this method can provide directional guidance for building renovation projects to enhance energy efficiency.

Analysis of Delays and Time Acceleration Strategies in the Renovation of Grha JST Building

Effective construction project management necessitates adherence to cost, quality, and timeline objectives. However, delays frequently challenge project success, impacting both schedule and budget. This research investigates the causes and consequences of delays within the Grha JST building renovation project, exploring mitigation strategies. Utilizing the Earned Value and Crashing methods, the study analyzes project performance to identify efficient delay management approaches. Recommendations are provided to enhance future project execution and mitigate delays effectively.

The effectiveness of BIM features application strategies for building refurbishment project performance improvement

Abstract This research presents a study that explores the effectiveness of different strategies for implementing Building Information Modelling (BIM) features in enhancing the performance of building refurbishment projects. The study adopts a combined quantitative and qualitative approach to measure the significance of BIM features in relation to building refurbishment project performance improvement. It aims to uncover the correlation between BIM feature application strategies and building refurbishment project performance and provides recommendations on utilizing BIM features to improve project outcomes. The study encompasses a comprehensive review of existing literature on BIM and building refurbishment projects, followed by a mixed-methods approach. This approach involves quantitative analysis of data from refurbishment projects that have implemented BIM, as well as qualitative analysis of expert interviews with industry professionals. The findings of the expert interviews shed light on the factors influencing the effectiveness of BIM in building refurbishment projects, such as the level of BIM adoption, the availability of skilled personnel, and the integration of BIM into project workflows. The research contributes valuable insights to enhance the understanding of BIM utilization in building refurbishment projects, offering guidance to practitioners and decision-makers in leveraging BIM technologies for such endeavourrs.

A Final Cost Estimating Model for Building Renovation Projects

The construction sector in Greece has been developing radically in the field of building renovations. The foremost problem for projects in the building construction industry is producing an accurate and reliable cost estimate at the onset of construction. The artificial neural network (AΝΝ) approach, using data available at the early stages of the project, can help resolve or prevent any kind of difficulty that could make the successful completion of a building less likely. ANNs have been highly efficient in gaining results which could prevent the failure of building constructions projects. The ultimate goal is to highlight the usefulness of the adoption of ANNs models to predict the final cost of a building renovation project. Thus, construction companies could avoid financial failure, provided that the gap between cost prediction and final cost for renovation projects is minimized. This paper presents an artificial neural network (ANN) approach for predicting renovation costs in Greek construction projects. The study, based on a comprehensive literature review and real renovation data from construction companies, employs IBM SPSS Statistics software to build, train, and test the ANN model. The model, which uses initial cost, estimated time, and initial demolition cost as inputs, is based on the radial basis function procedure. The model presents high performance with up to 2% sum of squares error and near zero relative error, demonstrating the ANN’s effectiveness in estimating total renovation costs.

Modular Systems for Building Renovation

The article discusses the methodology and technology of installing a new facade system on the old facade of the building, improving the appearance of the building and protecting the old facade, including the prevention of many problems. This research employs an analytical descriptive approach by gathering information on the methodology and technology used in installing modular facade systems on existing buildings. Data is collected through literature review and case studies of successfully implemented building renovation projects. The analysis results indicate that the use of modular systems in building renovation provides numerous benefits, including improved construction efficiency, cost and time reduction, as well as enhanced durability and aesthetics of the building. Moreover, the use of modular systems enables more flexible design adjustments according to the existing architectural context. The utilization of modular systems in building renovation brings positive impacts in enhancing the building's appearance while safeguarding the original facade and preventing various construction issues. By providing more efficient and flexible solutions, modular systems unlock significant potential in sustainably and aesthetically renewing existing building structures.

Workflow for Window Composition Detection to Aid Energy-Efficient Renovation in Low-Income Housing in Korea

Enhancing the efficiency of windows is important for improving the energy efficiency of buildings. The Korean government has performed numerous building renovation projects to reduce greenhouse gas emissions and mitigate energy poverty. To reduce the costs and manpower requirements of conventional field surveys, this study presents a deep-learning model to examine the insulation performance of windows using photographs taken in low-income housing. A smartphone application using crowdsourcing was developed for data collection. The insulation performance of windows was determined based on U-value, derived considering the frame-material type, number of panes, and area of windows. An image-labeling tool was designed to identify and annotate window components within photographs. Furthermore, software utilizing open-source computer vision was developed to estimate the window area. After training on a dataset with ResNet and EfficientNet, an accuracy of approximately 80% was achieved. Thus, this study introduces a novel workflow to evaluate the insulation performance of windows, which can support the energy-efficient renovation of low-income housing.

Edukasi tentang Keselamatan dan Kesehatan Kerja pada Pekerja di Proyek Perbaikan Gedung Sekolah X di Jakarta

The construction work sector is one of the work sectors that has a high risk of experiencing work accidents because work in this sector uses a lot of machines, materials, workplaces, and a dangerous work environment. Many workers in this sector do not know and understand about occupational safety and health (OHS), while OHS knowledge is a basic need for construction workers. Without basic knowledge of OSH, workers will not realize that there are many hazard factors that can cause accidents or work-related illnesses. This Community Service activity is expected to enable workers to recognize dangerous factors in the workplace and how to control them to minimize the occurrence of work accidents. Educational activities about occupational safety and health for construction workers were held for construction workers on the X school building renovation project in Jakarta, totaling 15 workers. After this activity is held, workers can understand K3, such as the definition and objectives of K3, definition of hazards and risks, risk control and are able to identify hazards in their current work. In the future, it is hoped that K3 training will be held with a more specific theme regarding construction work

An ontology-based tool for safety management in building renovation projects

Managing deep renovation projects is challenging due to the interactions with their surroundings, the issues of limited access and space, and the uncertainty around the composition and conditions of existing buildings. The interplay between the building areas, the building elements involved in the deep renovation, and the renovation scenarios and activities present challenging situations for managing safety risks. Research on enhancing safety in building projects using digital approaches such as BIM has mainly focussed on new construction works, yet limited research is available for deep building renovation projects. Using a Design Science Research (DSR) methodology, this paper develops an ontology for representation and identification of hazards in deep building renovations, instantiates the ontology through the development of a digital tool, and demonstrates its usefulness in hazard representation and identification by performing tests with real industry data from deep renovation projects, as part of a Horizon Europe 2020 research project, called RINNO. The testing involved a multi-residence apartment case study and three different renovation scenarios and successfully demonstrated the ability to automatically identify potential hazards relating to a particular renovation strategy. While the proposed ontology can be used to reduce the risk of accidents and injuries in building retrofit projects, its main implication is in laying the foundation for future digitally enabled approaches for managing safety in building renovation projects.

Carbon emissions analysis of office building renovation: a case study in China’s hot summer and cold winter zone

Abstract Building renovations in climates characterized by a hot summer and cold winter (HSWC) pose significant challenges in managing carbon emissions due to increased energy demands and material use. Despite advances in sustainable design, the carbon footprint of renovation activities remains a critical concern, particularly regarding the balance between initial emissions from construction and long-term operational efficiency. This study addresses these pressing issues through analyzing the carbon emissions associated with a building complex renovation in an HSWC zone of China. The research examines both the construction stage, where material production and transportation contribute significantly to emissions, and the operational stage, where energy consumption and equipment degradation influence long-term carbon output. By evaluating the effectiveness of renovation strategies and integrating building-integrated photovoltaic systems, this study demonstrates a reduction in annual carbon emissions from 1176.28 tCO2 to 1007.25 tCO2, a reduction of approximately 14.4%. The findings showed that the renovation process would achieve a carbon payback period of 7.46 years and a 24.9%–37.8% reduction in carbon emission intensity. This work underscores the potential significant environmental benefits of innovative materials and efficient design, offering valuable insights for future low-carbon building renovation projects.

Application of lean principles for building refurbishment projects in Sri Lanka

PurposeA comprehensive literature review was conducted to identify the lean principles and the challenges of building refurbishment. To have an in-depth investigation of the application of lean principles to address the challenges of refurbishment projects, ten expert interviews following a qualitative research approach were utilised in this research. Data were analysed using manual content analysis to derive the framework.Design/methodology/approachThe refurbishment of buildings has attracted the attention of the present construction industry. However, uncertain project characteristics, information deficiency, limited space for construction activities and less stakeholder involvement make it complex. Since the lean concept effectively deals with complex and uncertain projects, this study focusses to investigate the application of lean principles to overcome the challenges of refurbishment projects in Sri Lanka by developing a framework.FindingsIt was found that the five main lean principles of customer value, value stream, value flow, pull and perfection are appropriate for building refurbishment projects in Sri Lanka. Precise identification of clients and end-users, value adding and non-value adding activities, interruptions and stakeholder communication chains, setting scope, examining the possible technologies and taking measures to deliver the exact product to ensure the successful application of lean principles for refurbishment projects. Further, 27 benefits of five lean principles were identified which can be used to address the 13 identified challenges of building refurbishment of projects. Finally, a framework has developed portraying the application of lean principles in building refurbishment.Practical implicationsThe framework developed is beneficial for the building refurbishment project team to address the barriers of refurbishment projects by applying lean principles.Originality/valueThis framework can be used as a guideline for the implementation of building refurbishment projects by addressing their challenges with lean principles.

The Integration of Critical Risk with Building Information Modelling Application Strategies in Building Refurbishment Project Lifecycle

Building refurbishment project has rapidly becoming a significant part of the construction industry in Malaysia. Refurbishment projects are typically higher risk, more complex, and require more coordination than new construction projects. Therefore, the aim of this research is to establish the integration of critical risk with Building Information Modelling (BIM) application strategies for building refurbishment project lifecycle improvement. This study is conducted through a quantitative method using the questionnaire which is distributed by employing a self-administrated approach as a research medium to obtain feedback from contractor grade 7 (G7) from construction organization who are registered with Construction Industry Development Board (CIDB) Malaysia. As a result, 96.5 percent of the response rate are accepted. The analysis shows that the integration of critical risk with BIM application strategies is recognized as important factors and strategies towards building refurbishment projects lifecycle improvement and found that the mean is in very high range. Additionally, the results indicate that the level of critical risk and BIM application strategies have been measured through descriptive analysis. The findings of this study are expected to establish a foundation for future research in order to develop an adequate framework for managing building refurbishment projects and improve the quality of decision making among the building industry professionals.

A BIM based tool for evaluating building renovation strategies: the case of three demonstration sites in different European countries

Purpose Buildings are among the biggest contributors to environmental impacts. To achieve energy-saving and decarbonisation objectives while also improving living conditions, it is imperative to undertake large-scale renovations of existing buildings, which constitute the greater part of building stock and have relatively low energy efficiency. However, building renovation projects poses significant challenges owing to the absence of optimised tools and methods for planning and executing renovation works, coupled with the need for a high degree of interaction with occupants. Design/methodology/approach This paper describes the development of an automated process, based on building information modelling (BIM) and the principal component analysis method, for overcoming building renovation challenges. The process involves the assessment and simulation of renovation scenarios in terms of duration, cost, effort needed and disruptive potential. The proposed process was tested in three case studies; multi-residence apartment buildings comprising different construction components and systems, located in Greece, France and Denmark, on which six different renovation strategies were evaluated using sensitivity analysis. Findings The developed tool was successfully able to model and simulate the six renovation scenarios across the three demonstration sites. The ability to simulate various renovation scenarios for a given project can help to strategise renovation interventions based on selected key performance indicators as well as their correlation at two different levels: the building level and the renovated surface area level. Originality/value The objectives of this paper are twofold: firstly, to present an automated process, using BIM, for evaluating and comparing renovation scenarios in terms of duration, cost, workers needed and disruptive potential; next, to show the subsequent testing of the process and the analysis of its applicability and behaviour when applied on three live demonstration sites located in three different European countries (France, Greece and Denmark), involving six renovation scenarios.

Lean and interpretable digital twins for building energy monitoring – A case study with smart thermostatic radiator valves and gas absorption heat pumps

The transition to low carbon energy systems poses challenges in terms of energy efficiency. In building refurbishment projects, efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings, together with other benefits. Measured building performance, however, often reveals a significant gap between the predicted energy use (design stage) and actual energy use (operation stage). For this reason, lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement. In this research, interpretable regression models are built with data at multiple temporal resolutions (monthly, daily and hourly) and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves (TRVs) and gas absorption heat pumps (GAHPs) as well as giving insights on the performance of the building as a whole. Further, as part of modelling research, time of week and temperature (TOWT) approach is reformulated and benchmarked against its original implementation. The case study chosen is Hale Court sheltered housing, located in the city of Portsmouth (UK). This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS. The results obtained are used to illustrate possible extensions of the use of energy signature modelling, highlighting implications for energy management and innovative building technologies development.

The Integration of Critical Risk with Building Information Modelling (BIM) Application Strategies in Building Refurbishment Project Lifecycle

Building refurbishment project is rapidly becoming a significant part of the construction industry in Malaysia. Refurbishment projects are typically higher risk, more complex, and require more coordination than new construction projects. The refurbishment industry has the potential to expand and contribute to Malaysia’s overall building output. The growing demand for refurbishment work in Malaysia will be driven by the increasing number of old and failing structures, as well as the limited space available for new development. Therefore, the aim of this research is to establish the most significance integration Building Information Modelling (BIM) application strategies in managing the risk for building refurbishment project lifecycle improvement. In this regard, this study was conducted through a quantitative method using the questionnaire which was distributed by employing a self-administrated approach as a research medium to obtain feedback from project manager who has been a representative from G7 registered construction organization with Construction Industry Development Board (CIDB) Malaysia. As a result, 96.7 percent of the response rate were accepted. The analysis showed that the integration of critical risk with BIM application strategies was recognized as important factors and strategies towards building refurbishment projects lifecycle improvement and found that the mean is in very high range. Additionally, the results indicate that the level of critical risk and BIM application strategies have been measured through descriptive analysis. The findings of this study are expected to establish a foundation for future research in order to develop an adequate framework for managing building refurbishment projects and improve the quality of decision making among the building industry professionals.

Monitoring the Sustainability of Building Renovation Projects—A Tailored Key Performance Indicator Repository

This study aims to assist in the identification of suitable key performance indicators (KPIs) that can be used to assess the sustainability performance of buildings given their transition into zero-carbon, resource-efficient, and resilient structures. To that end, a four-step methodology is proposed in this work; the first step includes the development of a KPI repository, which builds upon commonly accepted targets derived from the needs of different stakeholders as well as targets imposed by external factors. The second step refers to the expansion of the initial KPI repository, capitalizing on information from the literature. The third step includes the refinement of the repository based on predefined criteria (relevance, availability, measurability, reliability, and familiarity) and tailored feedback from key stakeholders. The final step concerns the development of KPI cards, which include all the necessary information for understanding and estimating the KPIs included in the final repository. This four-step methodological approach implementation was tested during the EU-funded HORIZON project ‘InCUBE’. The implementation of the first two steps of the proposed methodology resulted in a pool of 68 KPIs. Nearly half of these KPIs were extracted from Step 1 to fully support the monitoring of all InCUBE outcomes, while the rest of the KPIs were extracted from highly relevant Horizon frameworks, the B4P partnership, Level(S) framework, publications, and ETSI standards (Step 2). The implementation of Step 3 resulted in a shortlisted KPI pool which eventually defined the final InCUBE KPI repository, including 31 KPIs. To help with the coordination of the data gathering process and a shared understanding of the sort of information to be monitored among various stakeholders, selected KPI cards (Step 4) are presented.

Building Information Modelling (BIM) Application as Risk Mitigation Strategies in Building Refurbishment Project Life Cycle

Towards the implementation of inclusive sustainable cities development as one of the Sustainable Development Goals, the imbalance ratio of existing buildings to new construction became overwhelming challenges. Therefore, refurbishment of existing buildings is considered the possible solution to minimizes the environmental impact and upgrading the performance of an existing building to meet new requirements. However, building refurbishment is well-known as a project that comprehends riskier compared to new building projects which lead to limited applicability in current risk management implementation. Thus, in line with an era of digitization construction of the fourth industrial revolution (IR 4.0), the traditional risk management needs improvement from a manual basis to magnifying efficiency using integration of Building Information Modelling (BIM) application. BIM is defined as an advanced technology that assists construction players to produce, communicate, and analyse building models by providing visual tools and a set of data. Therefore, the objective of this research is to identify the potential building refurbishment risk categories and to determine the most critical project lifecycle phase in implementing the BIM applications in order to mitigate the potential building refurbishment project risk. Also, to discover the relationship strength between these two variables. The quantitative method is applied by using a questionnaire form to the certified BIM experts. This research contributes a solid understanding and useful guideline for future practice reference and improvement within the Building Refurbishment Project.

RISK IDENTIFICATION AND ALLOCATION OF BUILDING CONTRUCTION RENOVATION PROJECT IN THE PARTE CLUB SURABAYA BUILDING

The Parte Club Surabaya Building Renovation Project has encountered various problems. These issues arise from multiple factors, primarily due to the complex nature of the structure as it involves renovating an old building. This research aims to identify the dominant risks and allocate the responsibility for managing these risks to the most appropriate party involved. Quantitative research methods were employed for this study. The sample consisted of 18 individuals, including expert staff from the implementing contractor and supervisory consultant. Data collection involved primary data obtained through purposive sampling, with 18 respondents selected. Secondary data included a review of previous similar research literature studies and historical data from earlier projects with similarities. The results of the data processing stage indicated the presence of dominant risks during project implementation and risk allocation. Consequently, project implementation is susceptible to risks identified by analyzing 27 selected risk variables. Six risk variables were dominant in project implementation: construction changes, additional expenses (overheads), project delays, material damage/loss, design errors, and changes to the work schedule. Risk allocation assessment results indicated that 19 risks were allocated to contractors, 3 to owners, and 5 jointly between the owner and contractor (shared). The percentage distribution of risk allocation is as follows: 70% to the contractor, 11% to the owner, and 19% allocated jointly (shared) between the two parties.