Retrofitting Of Buildings Research Articles

Navigating Delays: A Comprehensive Study of Public Building Retrofitting Projects in Kathmandu Valley

The objective of the study was to find out the present scenario of delays of retrofitting of public building with case of 11projects of Kathmandu valley. An observation and study of the project document is carried out along with questionnaire survey with 50 respondents. The maximum rate of delay in the retrofitting project is found to be 167% time overrun and minimum is found to be 42% of time overrun. Only one project among them is within the schedule with physical progress of 22%. A multiple linear regression analysis was performed to examine the influence of the variables Time overrun (Months) and Time extension with respect to initial contract (%) on the variable Physical Progress. A model summary model is obtained as follows: Physical Progress = 0.57 + 0.02 * Time overrun (Months) - 0.15 * Time extension with respect to initial contract (%) The top ranked specific delay contributing factors in a retrofitting project are as found as Impractical project schedule and duration (frequent changes in critical path), Unavailability of the numbers and skilled workforce for retrofitting projects, Delays occurred due to lack of coherence in architectural, structural, electrical, sanitary, and HVAC drawings, Approvals of shop drawings submitted by the contractor and Unavailability of the specific materials as per BOQ.

Benefit-Cost Analysis for Earthquake-Resilient Building Design and Retrofit: State of the Art and Future Research Needs.

This paper reviews the state of the art in using benefit-cost analysis (BCA) to inform earthquake risk reduction decisions by building owners and policymakers. The goal is to provide a roadmap for the application and future development of BCA methods and tools for earthquake risk reduction. Our review covers three earthquake risk reduction measures: adopting up-to-date building codes for new construction, designing new buildings to exceed code requirements, and retrofitting deficient existing buildings. We highlight the factors that influence the cost-effectiveness of building design and retrofit, as well as tactics for increasing the cost-effectiveness of risk reduction strategies. We also present BCA results, methods, and data sources used in the literature to help researchers and practitioners design and conduct a reliable and robust BCA study. In the process, we develop a set of opportunities and challenges for applying BCA to new areas of research, as well as key gaps and limitations in current BCA approaches, including further investigation of above-code design, incorporation of code implementation and enforcement into BCA, quantification of environmental benefits of seismic retrofits, and optimization of seismic retrofits with energy upgrades. Overall, our review provides practical guidance and useful insights into BCA with the goal of increasing the earthquake resilience and economic efficiency of buildings in the United States.

Informing building retrofits at low computational costs: a multi-objective optimisation using machine learning surrogates of building performance simulation models

Machine learning (ML) algorithms are increasingly used as surrogates for building performance simulation (BPS) models to leverage their energy predictive capabilities while reducing computational costs. In parallel, researchers are developing optimisation methods to inform building design and retrofit strategies but rarely employ ML-based BPS surrogates for this purpose. This study proposes a coupled modelling approach that leverages the capabilities of ML-based BPS surrogate models and multi-objective optimisation to inform holistic design and operation retrofits at low computational costs. The proposed methodology is demonstrated using an archetypal office building in Ottawa, Canada. The developed models achieved competitive predictive accuracies (adjusted R2: 0.90–0.99), identifying total and peak energy saving measures with up to 34% improvement in occupant thermal comfort at computational speeds 1266 times faster than a traditional BPS-based optimisation approach. Results offer a promising modelling workflow for design applications requiring extensive computations and scenario analyses, such as net-zero energy retrofits.

Seismic Risk Assessment in School Buildings: A Comparative Study of Two Assessment Methods

Seismic risk assessment in school buildings is critical for ensuring the safety and resilience of educational institutions against seismic events. This paper presents a new seismic risk methodology named MM Risk and comparative study with Adriseismic methodology used for seismic risk assessment. The study aims to provide insights into the effectiveness and reliability of these methods in evaluating the seismic vulnerability of school buildings. Through a comprehensive review of the existing literature and application on a dataset of 213 schools (367 buildings), this paper evaluates the strengths and limitations of each method in terms of accuracy, complexity, and practical applicability. The results show that by integrating the approach of Adriseismic methodology and incorporating extensions related to irregularities, the social risk component (number of users), and the ability to assess different types of structures, a comprehensive and tailored methodology for assessing seismic risk can be developed. This is important since these factors are strongly influencing the seismic risk of schools as connected systems. Furthermore, this paper explores the implications of these findings for improving seismic risk mitigation strategies in school buildings. MM Risk methodology places over 70% of school buildings in the medium seismic risk category and 27% in the high seismic risk category. On the other hand, the Adriseismic methodology is more stringent, classifying 60% of school buildings into high and very-high risk categories. This disparity undoubtedly influences the prioritization list for seismic risk mitigation measures. However, definitely the comparative analysis presented in this paper offers valuable guidance for engineers, policymakers, and stakeholders involved in the seismic retrofitting and design of school buildings, ultimately contributing to the enhancement of seismic resilience in educational infrastructure.

Integrated framework for space- and energy-efficient retrofitting in multifunctional buildings: A synergy of agent-based modeling and performance-based modeling

Integrated framework for space- and energy-efficient retrofitting in multifunctional buildings: A synergy of agent-based modeling and performance-based modeling

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.

Energy retrofitting of hospital buildings considering climate change: An approach integrating automated machine learning with NSGA-III for multi-objective optimization

In the context of sustainable development, energy-saving renovation of existing buildings can not only effectively reduce energy consumption but also improvement the residential comfort and office environments. This study proposes an optimization method for building energy-saving renovation based on automated machine learning and the NSGA-III algorithm, aiming at efficiently and accurately identifying the best energy-saving renovation schemes. The results showed that automated machine learning could provide a predictive model for multi-objective optimization analysis in a relatively short training time, with an average prediction accuracy of over 95%. And the Stacked Ensemble algorithm and Gradient Boosting Machine algorithm perform the best among all the algorithms considered in this study. Additionally, climate change significantly affects the energy-saving benefits and thermal comfort performance of renovation measures, thereby altering the choice of optimal schemes. The final renovation schemes obtained through the NSGA-III and entropy weight TOPSIS method can achieve an energy saving rate of 22.06% to 26.48% under typical climate scenarios, while also improving thermal comfort time by 31.87% to 43.73%. In future climate scenarios, an energy saving rate of 32.73% to 33.02% and a thermal comfort time of 40.20% to 42.29% can be achieved. Combining these two technologies can quickly and effectively find the best balance among energy consumption, whole life cycle cost, and thermal comfort time. The method proposed in this paper offers new perspectives and tools for researchers in the field of building energy conservation, demonstrating the application potential of automated machine learning and the NSGA-III algorithm in the energy-saving renovation of hospital buildings.

Performance of traditional Chinese courtyard buildings from a sustainability perspective and implications for contemporary green building design

Climate change, resource depletion, and biodiversity decline have prompted the construction industry to seek more sustainable solutions. While high-tech and often high-cost technologies and equipment support progress toward more sustainable built form, the sustainability performance of historical and vernacular buildings should also be reviewed. These buildings may offer advantages that are “hidden in plain sight.” This research focuses on the use of building information modeling technology to model and simulate a historical Chinese courtyard building. The outcomes of the simulation were evaluated using the green building council of Australia’s green star rating criteria to provide quantitative results. At the same time, relevant literature was explored to obtain a qualitative perspective. The final results indicate that courtyard buildings can serve as useful references for contemporary building design and retrofitting. The choice of building materials offers designers effective ideas for designing sustainable buildings. Courtyards can enhance ventilation, cooling, humidity control, light exposure, and connectivity to outdoor areas while ensuring privacy. In developing countries, this approach may be a viable way to promote sustainable development and energy conservation.

Passive Envelope Measures for Improving Energy Efficiency in the Energy Retrofit of Buildings in Italy

Passive Envelope Measures for Improving Energy Efficiency in the Energy Retrofit of Buildings in Italy

On the discrepancy of using annual or hourly emission factors for power generation to estimate CO2 reduction of building retrofitting

Buildings play a significant role in global carbon emissions, and offer substantial potential for energy savings and emission reduction. This research delves into the Emission Factor Discrepancy (EFD)—the variance in CO2 emission reduction projections obtained by employing either annual or hourly average Emission Factor (EF) for electricity generation. Through two detailed case studies in the Netherlands and incorporating emission data from the Netherlands, Sweden, and France, the study uncovers the potential magnitude and country-specific variability of the EFD.By demonstrating how the energy mix of a country influences the EFD, the research offers valuable insights into the accuracy of emission calculations for different circumstances, particularly in the context of transitioning to renewable energy sources. We have found that countries with energy sources having low load-following capability and low EFs exhibit a large EFD. Whereas, countries with high EFs and large deployment of Photovoltaics (PV) show a notably large EFD on emission reduction related to PV production. This highlights the importance of carefully selecting EFs when evaluating building retrofits in the context of smart city initiatives.This research highlights the need for establishing a uniform framework for calculating carbon emissions associated with retrofitting in buildings in conjunction with the granularity of data and the specific energy mix of a country.

Structural response of half-scale pumice concrete masonry building: shake table/ambient vibration tests and FE analysis

Seismic performance evaluation of masonry structures is of paramount importance for ensuring the safety and resilience of buildings in earthquake-prone regions. There are limited number of studies on pumice elements in the literature. In addition, there are almost no studies investigating the earthquake behavior of pumice masonry building as a whole structure. In this context, a comprehensive understanding of their seismic response and dynamic characteristics has been lacking. To address this knowledge gap, a shake-table experimental campaign was undertaken, wherein half-scale pumice masonry building was exposed to simulated seismic forces. To enhance the experimental findings, numerical simulations were performed to confirm and expand our comprehension of how the pumice masonry structure responds to dynamic forces. Integrating both experimental and numerical outcomes provides a holistic understanding of how pumice masonry buildings behave during seismic events. At the end of the experimental study, the frequency values of the pumice model were observed to decrease up to 23.5% in the modes compared to the undamaged state. In the numerical model, this value decreases up to 19.85%. For the undamaged and damaged model, the first three experimental mode shapes were similar to the numerical mode shapes. Both experimental and numerical results show that the expected damages occur in the same regions. These results show that nonlinear FE models can be helpful in determining potential damage model locations. The findings have implications for the seismic design and retrofitting of similar traditional masonry buildings, facilitating the development of resilient and sustainable engineering solutions in seismic-prone regions.

FEASIBILITY STUDY OF RETROFITTING ASSESSMENT FRAMEWORK FOR SUSTAINABLE MULTI-STOREY RESIDENTIAL BUILDINGS: A CASE STUDY OF CHINA

The construction industry is one of the primary sources of carbon emissions. In the context of the global response to reduce greenhouse gas emissions and the impacts of climate change,China implements the Carbon Peaking and Carbon Neutralisation policy. The policy vigorously promotes energy conservation and emission reduction in the construction industry, particularly housing. Due to the large stock of existing old multi-storey residential buildings in China, most of which are not energy-saving, and the lack of a sustainable assessment framework to retrofit such buildings, it is deemed essential to analyse the shortcomings of the current assessment standards and frameworks and formulate a better alternative. Therefore, this paper aims to provide the rationale for proposing a sustainability assessment framework for retrofitting old multi-storey residential buildings in China. It first explains the concepts of sustainable development and housing, then combs the current Chinese government’s commitments to sustainable housing agenda. The unsustainable state of this housing type is then reviewed, followed by the issues and gaps in the existing sustainable building assessment standards in China and overseas to justify the necessity of developing a sustainability assessment framework for retrofitting multistorey residential buildings in China. This framework would assist the retrofit of old multistorey residential buildings in reducing energy consumption, improving efficiency and achieving sustainable development. It also contributes to the body of knowledge in sustainable building assessments and helps in the planning and design processes within the public and private sectors related to the construction industry.

ANALISIS AIR CONDITIONER PADA KOMPLEK PERUMAHAN DI KOTA DENPASAR

Green building retrofit is an approach that involves modifying or enhancing existing buildings to achieve higher standards of sustainability and energy efficiency. By conducting an energy audit first, it's possible to identify potential energy savings in the housing, as well as components that need to be upgraded to reach the desired level of sustainability. Retrofit solutions may include the use of implementation of efficient HVAC systems, energy-saving lighting, and better energy management. The aim of this research is to explore the potential improvements that can be applied through Green Building Retrofit with a focus on energy efficiency and sustainability in Jadi Pesona II Barat Housing, comparing the energy consumption conditions of houses before and after the energy audit, as well as calculating the payback period for occupants after the retrofit implementation. After the energy audit and Green Building Retrofit, daily energy usage in homes in Perumahan Jadi Pesona II Barat decreased from 47.45 kWh per day to 36.91 kWh per day. This indicates a reduction of 10.54 kWh per day or approximately 22.22% from the previous conditions, and the payback period analysis results show that almost all air conditioners show values in line with the project investment feasibility parameter, which is below 4.2 years.

Development and experimental validation of a novel double-stage yield steel slit damper-buckling restrained brace

This research is focused on the development and experimental validation of a novel double-stage yield steel slit damper-buckling restrained brace (SSD-DYB) system designed for seismic resistance of steel structures. The SSD-DYB integrates the energy dissipation capability of a steel slit damper (SSD) in its initial segment, enhancing performance in the case of lower seismic intensities levels while employing a larger segment for higher load resistance to maintain structural stability. The results of the study show that the proposed SSD-DYB is capable to reduce the weight of similar all-steel buckling restrained braces (BRBs) successfully addressing critical points through stiffeners and top and bottom plates. Additionally, the U-shaped element exhibits resilience during seismic loads, indicating its potential for replacing cores without failure which would be beneficial for seismic retrofitting of buildings. Experimental tests show that varying the number and shape of SSD strips significantly impacts the hysteresis curve's maximum load and dissipated energy (i.e., adding strips increased energy dissipation by 33.48 % for SSD-DYB-1), which can be used to control the proposed device for a specific performance target. Stopper mechanisms within the SSD-DYB regulate load distribution between segments and can be used to control the device and its transmitting capacities. Finally, an optimized SSD-DYB has been proposed with promising performance to be used by researchers for designing new structures or retrofit old ones.

Adapting Street Profile Design by Using Nature-Based Solutions in New Neighbourhoods and the Retrofit of Buildings

The aim of this paper is to analyse ways to upgrade the existing urban and architectural features in the built environment by incorporating and enhancing the use of nature-based solutions (NbSs) in relation to the city of Bucharest, which lacks green spaces mapping and quality studies and literature. The paper draws a comparison between the design elements used in other cities, namely Lisbon, Vienna and Rome. These are also analysed and compared in relation to the integration in a mixed urban development plan for a research-to-business neighbourhood design competition in Măgurele, situated near Bucharest. A matrix of five criteria is used for the analysis: historical context, urban context, nature versus design, use and climate context. In Lisbon, examples range from new green walls, modern green Mediterranean courtyards, NbS in scaffolding and temporary walls, the placing of Miradores around the city to green-and-healthy marketing tools for restaurants. For Vienna, a street is being remodelled in an innovative way using independent green infrastructure designs in existing retrofitted parking units, hotels and residential constructions. For Bucharest, emergent pop-up, small scale, bottom-up solutions push the city’s urban fabric beyond the greyish look of socialist-communist background and eclectic late 19th, early 20th century built heritage. For Măgurele, different versions of a modern neighbourhood and street profile design issues are analysed, using 3D renderings that incorporate NbS at various insertion scales. Existing example cases showcase new dimensions and toolsets of the adaptation of the urban fabric based on a more ecosystem-based approach of architectural-urban research by design, as possible instruments that facilitate a Green Transition in urban settings. Covering more cities in the future would add to the impact and contribution of this study.

Leveraging explainable AI for informed building retrofit decisions: Insights from a survey

Accurate predictions of building energy consumption are essential for reducing the energy performance gap. While data-driven energy quantification methods based on machine learning deliver promising results, the lack of Explainability prevents their widespread application. To overcome this, Explainable Artificial Intelligence (XAI) was introduced. However, to this point, no research has examined how effective these explanations are concerning decision-makers, i.e., property owners. To address this, we implement three transparent models (Linear Regression, Decision Tree, QLattice) and apply four XAI methods (Partial Dependency Plots, Accumulated Local Effects, Local Interpretable Model-Agnostic Explanations, Shapley Additive Explanations) to an Artificial Neural Network using a real-world dataset of 25,000 residential buildings. We evaluate their Prediction Accuracy and Explainability through a survey with 137 participants considering the human-centered dimensions of explanation satisfaction and perceived fidelity. The results quantify the Explainability-Accuracy trade-off in building energy consumption forecasting and how it can be counteracted by choosing the right XAI method to foster informed retrofit decisions. For research, we set the foundation for further increasing the Explainability of data-driven energy quantification methods and their human-centered evaluation. For practice, we encourage using XAI to reduce the acceptance gap of data-driven methods, whereby the XAI method should be selected carefully, as the Explainability within the methods varies by up to 10 %.

Evaluating the response modification factor (R) for reinforced concrete and steel structures equipped with TADAS devices designed for high seismic hazard in Colombia

Colombia is a country with high seismic activity due to its location at the convergence of the Nazca and South American tectonic plates, making structural safety a key priority in the design, construction, and retrofit of buildings. Currently, one of the most used seismic resistance systems are moment-resisting frames, due to their easy construction and good behavior under vertical loads, however, they are susceptible to structural damage when subjected to moderate to high-intensity earthquakes, which makes the use of seismic protection systems an adequate alternative to prevent damage during seismic events. The Colombian seismic design code NSR-10 proposes a design methodology using a linear structure that represents a non-linear behavior of the building when the expected design earthquake occurs through the response modification factor R. However, the NSR-10 seismic design code does not contemplate the response modification factor for structures with seismic protection systems. Therefore, in this research, a design procedure was configured for buildings with moment-resisting frames of reinforced concrete and steel equipped with TADAS (triangular-plate added damping and stiffness) dampers. The procedure evaluated the developed response modification factor of structures located in high seismic hazard areas in Colombia and considered regular buildings with varying numbers of stories and special energy dissipation capacity. The capacity of the structures was evaluated through nonlinear static analysis using the Pushover method in SAP2000 software. Finally, the response modification factors were calculated for regular buildings with moment-resisting frames and different numbers of stories.

Seismic probabilistic assessment of steel and reinforced concrete structures including earthquake-induced pounding

Recent earthquakes demonstrate that prioritizing the retrofitting of buildings should be of the utmost importance for enhancing the seismic resilience and structural integrity of urban structures. To have a realistic results of the pounding effects in modeling process of retrofitting buildings, the present research provides seismic Probability Factors (PFs), which can be used for estimating collision effects without engaging in intricate and time-intensive analysis. To include the low-, to mid-rise buildings, the 3-Story, 5-Story, and 9-Story adjacent steel and Reinforced Concrete (RC) moment-resisting frames were modeled in OpenSees software capable to take into account the structure in a state of collapse during the analysis, which can provide the real condition of buildings under seismic excitations. Results of analysis confirmed that the impact force can considerably affect the moment–rotation curve of beams and columns, in which, it can affect the structural response of structures during earthquakes. Therefore, seismic PFs proposed to examine the possibility of changes in the performance levels and fragility assessments. Moreover, proposed PFs can be used as coefficient factors to facilitate the retrofitting process of buildings and improve the environmental effects.

To renovate or build with wood? Results from Finnish citizen survey data

Finland shows strong support for reducing its climate footprint originating from the built environment as part of the national carbon neutrality goal by 2035. Two prime examples are increasing wood use in construction and favoring building renovation to alleviate emissions from the use of virgin construction materials. However, the open question remains whether citizens also support these decarbonization pathways. By using national-level data from a randomly sampled citizen survey in Finland (n = 1448), we model citizen preferences to these two decarbonization pathways. The results suggest that a preference to renovate rather than to build anew is shown by respondents of the female gender; over 55 years of age; with a lower household equivalent income; and possessing housing property investment. Wood material is positively favored by respondents with higher age; a lower household equivalent income; living in smaller population centers in the countryside; and owning forestland. Interestingly, the effect of climate agency was negative in both models. This can be interpreted in the wood material case as reflecting conflicting views of negative environmental effects from forest harvesting to produce renewable building materials. In the renovation model case, we argue that the climatic impact of renovations remain weakly understood by citizens in Finland, given that the media and national regulations emphasize operational emissions. These results benefit both policy makers and municipal-level decision making in understanding of acceptability of wood material use and building retrofits among the general public.

Unlocking energy and economic benefits of integrated green envelopes in office building retrofits

Green envelopes show significant potential in energy conservation and thermal comfort enhancement in office buildings. This study presents a comprehensive method integrating field tests, building energy simulations, and optimization in office buildings in Chongqing, China. A 20-year life-cycle cost analysis was conducted to evaluate the benefits of green roofs (using sedum lineare container-type planting modules) and green façades (featuring vertical kudzu greenery systems). The results indicate that green roofs could reduce peak temperatures by up to 34.3 °C, leading to daily energy savings of 12.5 % during summer. Green façades decreased the wall exterior surface temperatures by up to 3.4 °C and 5.1 °C on the test cold and hot days, respectively. The maximum annual building electricity savings per green-modified area was 22.8 kWh/m2 for the poorly-insulated building and 5.4 kWh/m2 for the well-insulated one. This study highlights the cost-effectiveness of green envelopes in improving building efficiency. The optimal retrofit measure for the poorly-insulated building was the combination of green roofs and daylighting dimming control systems, yielding a 20-year life-cycle net savings per floor area of 81.5 CNY/m2. For the well-insulated building, the daylighting dimming control system alone provided optimal net savings per floor area of 26.4 CNY/m2.