Building Industry Research Articles

Development and experimental assessment of a multi-annual energy monitoring tool to support energy intelligence and management in telecommunication industry

Carbon-footprint reduction of key industrial buildings is addressed, by proposing methodologies for continuously monitoring telecommunication (TLC) central offices (COs). Main aim is classifying sites according to their efficiency and reliability, via the diagnosis of anomalous electricity consumptions. Such a goal is achieved through the definition of new key performance indicators (KPIs) based on TLC and cooling energy demand, improving the outcomes of pre-existing methods. While the reliability index and index of cluster reliability are specifically proposed to evaluate and physically assess the impact of climate control (CLC, i.e., the parasitic quota) electricity consumption with respect to the TLC one, the here introduced coefficient of variation of telecommunication energy allows for a more solid evaluation of energy measurements reliability. Another target of this study is to extend the afore-mentioned KPIs-based analysis to multi-annual periods of monitoring, thus allowing successfully meeting the currently in-force ISO 50001 standard. Specific central offices were then selected and analyzed to verify the results physical meaning. The method was proven effective in classifying central offices belonging to climate-homogenous fleets, according to the reliability level estimated over a triannual timeframe. Positive impacts in terms of attainable energy saving through improved thermal management, as well as methodology extendibility to other industrial sectors are finally presented and discussed.

Fostering the transition towards circular economy through collaborations: An open innovation perspective in the building industry

Fostering the transition towards circular economy through collaborations: An open innovation perspective in the building industry

A case study on optimizing industrial air conditioning with thermal solar energy in Egypt

This study investigates the feasibility of implementing a solar-assisted adsorption chiller in an industrial building at the Oriental Weavers International factory located in 10th of Ramadan City, Cairo, Egypt. The objective is to replace an inefficient split air conditioning system currently used to cool the Jacquard units during carpet manufacturing. The research begins by analyzing the performance of the existing cooling system to establish a baseline. It then explores the potential energy savings achievable by replacing the current system with a solar-assisted adsorption chiller. The existing oversized boiler will serve as an auxiliary heater for the new system. TRNSYS simulation tools are employed to model the building, simulate its thermal performance, and develop a solar-assisted cooling system. A parametric analysis investigates the impact of varying collector area and hot/cold-water storage tank volumes on key energy performance indicators. This analysis aims to determine the optimal component sizes needed for efficient system operation. Results indicate that a collector area of 90 m2 offers the optimal balance between performance and cost. There are minimal benefits to increasing the collector area beyond 100 m2. Larger hot water storage tanks demonstrate reduced outlet temperatures, reaching a maximum solar fraction at a capacity of 4 m³. The impact of cold-water storage tank volume on the system is minimal. The economic assessment reveals a payback period of 7.6 years, an Internal Rate of Return (IRR) of 14.3 %, and a Return on Investment (ROI) of 34.5 % over a 10-year period, indicating the financial viability of the proposed system. Furthermore, the solar-assisted adsorption chiller system has the potential for substantial environmental benefits. The system has the capacity to reduce CO2 emissions by up to 7200 metric tons. This highlights not only the technical feasibility of the system but also its economic and environmental advantages.

Mechanical and durability properties of polymer fiber reinforced one-part foam geopolymer concrete: A sustainable strategy for the recycling of waste steel slag aggregate and fly ash

This paper assesses the feasibility of geopolymers (GPs) for use as lightweight foamed concrete, a crucial step towards reducing the carbon footprint and conserving natural resources. A powder activator (i.e., sodium metasilicate) less harmful to the environment was used to activate the fly ash-based GPs, while the limestone aggregates were gradually replaced by up to 100 % waste slag materials to conserve natural resources. Polypropylene fibers were incorporated at high dosage rates of 1 % or 2 %, by volume, to reduce the concrete density and improve its durability properties. Tested properties include flow, density, water absorption, porosity, thermal conductivity, mechanical strengths, drying shrinkage, and resistance to sulfate attack, freeze/thaw cycles, and elevated temperature. Results showed that the concrete mechanical properties improved when the limestone aggregate was replaced by slag materials, but the density and thermal conductivity were slightly curtailed at higher addition rates. The use of polypropylene fibers proved efficient to improve the resistance to freeze/thaw cycles, drying shrinkage, and expansion due to sulphate attack. Such data can help sustain the green building industry development by reducing the carbon footprint and conserving natural resources in foamed concrete applications.

Reconstruction and Protection of Industrial Building Area: A Case Study of Beijing Shougang Park

Reconstruction and Protection of Industrial Building Area: A Case Study of Beijing Shougang Park

Research on Carbon Emission Pre-Assessment of Residential Buildings in Xi’an City during the Scheme Design Stage

The effect of energy saving and carbon reduction in the building industry is closely related to the realization of China’s double carbon goal. In this study, a two-dimensional framework for building life cycle carbon emissions was established, which takes into account the early stages of building design such as the feasibility study stage and scheme design stage. Taking 57 residential buildings in Xi’an City as examples, the life cycle carbon emission characteristics of residential buildings in cold areas were introduced. This study found that the life cycle carbon emission intensity is about 45~55 kgCO2/(m2·a). The operation and maintenance stage and building materials production stage accounted for the largest proportion of carbon emissions, and the sum of carbon emissions of the two stages accounted for 92.3% of the total carbon emissions. In addition, based on the probability density function, the carbon emission intensity distributions of the building life cycle, building material production stage, building material transportation stage, and operation and maintenance stage were analyzed, and it was found that each distribution fitting graph was generally in line with a lognormal distribution, and their expected value provided a reference index for carbon emission pre-assessment in the feasibility study stage. Based on the analysis and determination of 11 independent variables that affect the total carbon emissions, such as area, floor number, story height, and number of households, a multiple linear regression model for carbon emission pre-assessment in the design stage of building schemes is proposed. The R2adj of the model is 0.985 and the error is about 10%. The prediction model can provide beneficial guidance for the life cycle carbon emission prediction in the design stage of building projects, so as to reduce carbon emissions by changing building design.

Integrating energy simulations and analytical hierarchy process procedure in multi-criteria evaluation of heating systems for industrial buildings

Industrial buildings in Italy are generally aged and widely outdated from an architectural, technological, and environmental perspective. Despite the current limitations affecting both envelope and system installations, enhancement strategies are not frequently debated in the literature or addressed recurring to not adequately comprehensive approaches. This research examines space heating options for integrated retrofit interventions of manufacturing facilities using a novel methodology that combines multi-criteria decision analysis based on the Analytic Hierarchy Process (AHP) with building energy simulations. Interviews with representatives from medium-sized companies in Tuscany provide insights into the exigencies of industrial buildings, while on-site surveys identify common features of industrial buildings in the region leading to the identification of a representative case study building. This facility is examined producing several energy models to account for the different heating system alternatives to be evaluated according to criteria including economic, environmental, comfort, space, and reliability. Both qualitative judgments and quantitative outputs from energy simulations are considered to rank the technological alternatives encompassed in the analysis. In addition, sensitivity analyses are carried out to highlight the impact of boundary conditions on optimal configuration selection. Economic considerations weigh heavily for industrial owners, often outweighing environmental concerns due to higher initial investment requirements for low-impact solutions. Consequently, gas boiler generators and hot-water fan heaters emerge as preferred options for their flexibility, low initial cost, and ease of installation.

The thermal conductivity of graphite composite insulation boards: A theoretical and experimental study

Graphite composite insulation boards (GCIB) have emerged as a promising solution in the construction industry, offering a combination of fire resistance, high temperature stability, and excellent insulation properties. As their usage continues to increase, it is crucial to develop and validate a more accurate theoretical model for the effective design and optimization of building insulation systems. Traditional models including series and parallel models are employed for estimating the thermal conductivity of GCIB but revealed higher relative errors and lower theoretical calculation accuracy. Therefore, the primary objective is to design and validate a more efficient theoretical model for thermal conductivity prediction in GCIB. This paper investigates the thermal conductivity of GCIB under varying composition ratios by designing a novel Parallel-Series Parallel (PSP) approach. The PSP model is designed based on a single basic cell where the graphite polystyrene particles are employed as the matrix material while cement, vitrified microspheres, and silica fume are used as inclusion materials. Then, the thermal conductivity unit is divided into three parallel heat conduction subunits where the matrix materials and inclusion materials in the three subunits are integrated in a series-parallel manner to provide a more realistic representation of the heat transfer mechanisms within the composite. For a comprehensive assessment, the study encompasses theoretical analysis, empirical assessment, and finite element (FE) simulations to illustrate its thermal properties. The predicted thermal conductivity reveals perfect consensus in comparison with the FE and experimental test outcomes by achieving lower relative errors of 2.7 %∼3.8 % and 1.9 %∼ 3.0 % respectively. The model validated through numerical simulations and sample experiments illustrates a significant improvement in accuracy of about 76.4 %∼94.3 % when compared to traditional series and parallel methods. Prominently, the findings indicate that the thermal conductivity of GCIBs declines considerably as the volumetric ratio of graphite polystyrene particles (Ф1/Ф3) increases and stabilizes when the proportion reaches 10, emphasizing the importance of optimizing material composition to enhance the thermal performance of GCIB. Overall, the validated PSP model by accurately determining the thermal conductivity of GCIB serves as a reliable tool for designing and optimizing high-performance insulation materials, contributing to energy efficiency and sustainability in building and construction industries.

Car wash noise reduction - case study

A car wash is installed in one corner of a large industrial building with the exit feeding into the building interior. The building interior is largely open space with a high roof. This houses multiple activities going on at any given time including part fabrication and vehicle retrofitting. The space available for the car wash necessitates the exit door to open during the drying cycle. The blower noise during the drying cycle with the exit door open is not loud enough to require hearing protection in the facility. The functions held within the space eventually expanded to include meetings requiring speech communication. The noise during the drying cycle was loud enough to disrupt audibility. An ad hoc team worked to reduce noise levels sufficiently to allow all other activities to continue without noise disruption during car wash operation. This paper addresses the diagnostic work and countermeasures put in place to achieve this goal.

Energy efficient and sustainable design of a multi-story building based on embodied energy and cost

Sustainable multi-story building designs are gaining increasing attention in light of the green development of the building industry. Recently, many studies have been conducted to determine the optimized embodied energy considering size of structural members and materials strength using a single objective function. In this context, the current study adopted a multi-objective function based on cost and Embodied Energy (EE) for the sustainable design of the entire multi-story building. A BuildingEnergy computer program is used to assess the energy consumption performance of a multi-story reinforcement cement concrete building. Based on the proposed method, an analysis is carried out to compare the optimal solutions for multi-story building. Furthermore, a detailed parametric study was conducted to explore the main factors for energy-efficient column and beam design. The results revealed that with a comparison of the most “carbon-friendly” and “cost-friendly” solutions, an added cost of 6–7% can contribute up to a 13% emission reduction. The sectional dimensions, steel rebar, concrete strengths, cost ratio, building height, and eccentricity remarkably influence sustainable design, cost optimization, and minimum carbon emission. Overall, this study could help to define cost-effective and energy-efficient structural members. Eventually, the EE is confirmed to be a feasible parameter for designing more sustainable multi-story RCC buildings.

Sustainable Structural System Selection Using Hybrid Fuzzy Multi-Criteria Decision Model Based on Seismic Performance

In the rapidly evolving field of sustainable construction, this study aims to address the critical need for advancement in the building industry, focusing on vital indicators like energy efficiency and cost-effectiveness, as well as improving occupant comfort. This research introduces a novel approach to support the choice of suitable structural systems for mass housing projects, with a case study on Iran’s national housing scheme. This methodology involves a four-phase process, beginning with compiling a database from existing studies to outline primary and secondary indicators affecting structural system selection. It utilizes the fuzzy AHP method for criteria prioritization and the fuzzy TOPSIS technique for alternatives (LSF, 3DP, ICF, TRC, and RCCF). The study identified the light steel framing (LSF) system as the optimal choice for Iran’s housing needs based on various criteria. Then, in the final phase, the study evaluates the seismic performance of cold-formed steel (CFS) frames with various sheathing panel types (OSB, DFP, CSP, and GWB) under monotonic loads, examining key seismic parameters across 38 frame setups. The findings reveal that LSF structures can effectively withstand seismic events within the elastic behavior range, suggesting that this construction approach is viable for enhancing mass housing production in Iran’s construction sector.

Advances and Significances of Nanoparticles as Concrete Additives: A Comprehensive Review

Nanotechnology, a significant technological advancement in the current century, has brought about revolutionary changes in numerous fields by manipulating matter at the nanoscale. This review paper examines the various applications of nanoparticles in the concrete industry, emphasizing their potential to improve mechanical qualities, thermal performance and sustainability. This study investigates multiple synthesis strategies, such as grafting, sol–gel, chemical and biological procedures, which offer concrete engineers a diverse range of options to tailor the properties of nanoparticles. The utilization of this particular material results in notable enhancements in many mechanical properties of concrete, including its compressive and flexural strength, toughness, thermal conductivity and self-sensing capabilities. These improvements ultimately contribute to the overall enhancement of the concrete’s structural integrity and energy efficiency. Adding nanoparticles to concrete has also been shown to help it develop self-healing properties. This means that structures last longer and require less maintenance. Making building materials more resistant to chemical corrosion, wear and environmental forces is also a big step in making them last longer. The growing emphasis on sustainability within the building industry has generated heightened attention toward utilizing self-healing concrete, which frequently incorporates nanoparticles. To make the building industry more environmentally friendly, using less traditional cement and recycling personal safety equipment (PPE) like vinyl and latex gloves can help protect the environment. This review also highlights the significant problems in employing nanoparticles in concrete: obtaining equal dispersion, handling-costs and addressing environmental and health concerns. However, nanotechnology is advancing construction concrete research to improve mechanical properties and durability.

New guidelines on radiation survey and sanitary assessment of residential, public and industrial buildings and facilities in terms of radiation safety indicators. Part 1

The paper (in two parts) presents an overview of the new guidelines MR 2.6.1.0333-23 (approved on 01 December 2023) that supersede guidelines MU 2.6.1.2838-11, which were used for organizing radiation surveys of residential, public and industrial buildings and facilities and their sanitary assessment in terms of radiation safety indicators over the past 12 years. Due to a large number of critical comments on the document received during this period, a need for significant revision emerged. The scope of the revised document was expanded and now covers all stages of the life cycle of buildings and facilities: commissioning; operation period; overhaul and reconstruction; demolition. In the first part of the paper, the structure and legal status of the new guidelines are considered, as well as the main innovations in terms of measuring the ambient dose equivalent rate of gamma radiation, searching and identifying local radiation anomalies and sites of radioactive contamination, measuring surface contamination levels, and determining the minimum number of premises to be surveyed. The reasons for the introduction of certain changes are outlined. The issues of evaluation of measurement uncertainty, reporting of measurement results and registration of test reports are covered in detail. In the second part of the paper, numerous innovations will be considered in terms of estimating the indoor average annual equilibrium equivalent concentration of radon isotopes.

GIS-Based Risk Assessment on Sea Level Rise and Flooding in Alsancak Harbour Behind Area

According to climate change projections outlined in the Intergovernmental Panel on Climate Change 6th Assessment Report, sea levels are expected to rise between 0.37 and 1.88 meters by 2150. The rise in sea level poses a significant threat to coastal areas, including industrial heritage zones frequently developed around ports. Alsancak Harbour Behind Area is a significant location due to its essential industrial heritage. The main objective of the research is to evaluate the potential risks related to floods and long-term sea level rises in the Alsancak Harbour Behind Area. Thus, the research aims to assess the potential risks associated with flooding and long-term sea level rise in the Alsancak Harbour Behind Area within the context of industrial heritage. It also measures the area's resilience to these risks and discusses planning decisions. The ‘Coastal Risk Screening Tool’ was used to create a coastal flood map according to determined three different scenarios. The result shows that the valuable industrial heritage buildings such as the Coal Gas Factory, Old Flour Mill-II and Tariş Alcohol Factory, new high-rise residential areas, port facilities and transportation arteries are at high or medium risk, especially in 2100 and 2150.

Analyzing and Comparing Global Sustainability Standards: LEED, BREEAM, and PBRS in Green Building arch article topic

Since the year 2000, a heightened environmental awareness has led to the emergence of global trends in forefront countries, prompting the need for standardized practices in the environmental building industry. This paper explores various experiments on buildings, demonstrating trends through examinations and tests conducted by governmental or private organizations. Notable among these trends are the standards set by global evaluation systems such as BREEAM, LEED, PBRS, and SSBS. The paper highlights the recent adoptaion of Arab standards in Abu Dhabi, positioning the emirate as a pioneer in sustainable development. The research focuses on the city of Kirkuk, where building regulations lack consideration for environmental standards. The study aims to identify applicable international standards, emphasizing the importance of residential standards in comparison to other criteria. The World Green Building Council's universal standards for existing buildings are discussed, with the recognition that these standards may need customization to align with the local environment and architectural characteristics of Kirkuk. The paper delves into the methodology used, employing a theoretical framework, analytical methodology, and a deductive approach to formulate recommendations tailored to meet local standards. The Abu Dhabi experience with the Pearl Rating System is explored, outlining its three evaluation stages and the specific criteria for building assessment. A comparison between sustainability standards reveals disparities in evaluation criteria, emphasizing the challenge in establishing global standards. The study calls for a transparent and globally applicable evaluation basis, considering discrepancies among diverse countries and their respective tools. The paper concludes by underlining the importance of establishing local standards, serving as a benchmark for quality and operational efficiency within the real estate market. It also emphasizes the crucial role of existing residential buildings in proposed solutions for sustainable development, highlighting their significance in local markets.

A summative user evaluation of connected thermostats

Thermostats are the nexus of human comfort within buildings. However, the building industry has prioritized a “product-centered” approach over a “human-centered” approach when developing thermostats. As technology advances, we have seen a proliferation of connected thermostats developed to provide a more convenient way to manage thermal comfort. However, if connected thermostats are not designed based on user needs, their benefits will not be fully realized. To understand how connected thermostats meet or do not meet user needs, this summative evaluation study employed text-mining of 130,237 user reviews from Amazon (n = 35,275), and Apple App Store (n = 94,962) to systematically evaluate users' perception of 52 connected thermostats and their 37 associated iOS apps using a grounded theory approach. The analysis revealed emergent themes from Amazon reviews, including “usability,” “functionality,” “user support,” “connection and compatibility” “overall impression,” and “cost and value”. Similarly, Apple App Store reviews highlighted the themes “usability,” “functionality,” “update and maintenance,” “reliability and performance,” “overall impression,” and “user support” in order of their importance. Usability emerged as the most frequent and important theme in both Amazon and Apple App Store reviews, highlighting the role of human-technology interactions. While users extensively discussed concepts like “ease” and “comfort,” “energy” was not as prominently featured. In addition, the analysis found that “usage data privacy” was a significant concern for users. This study's approach can be employed to enhance human factors knowledge in connected building interface design, and this methodological approach could be an effective supplement for other human-building product evaluations.

Advancing industrial building energy measurement and verification (M&V) with deep learning: Evaluating data size and feature selection impact

This study explores the potential of advancing industrial building energy Measurement and Verification (M&V) using Deep Learning techniques, with a focus on the impact of data size and feature selection methods on model performance. Traditional M&V practices in the industry require extensive datasets, typically spanning 24 months, to ensure accurate energy savings verification post energy conservation measures (ECMs). This research challenges the norm by investigating whether a condensed four-month dataset could suffice for reliable M&V, thereby accelerating the verification process which is crucial for industrial applications. Utilizing a dataset with 30-minute intervals, the study first applies multi-linear regression across twelve feature selection methods to identify the most effective techniques based on a comprehensive set of performance metrics including Training Time, RMSE, MAE, R-squared, CVRMSE, NMBE, Mean MSE (via k-fold cross-validation), and the Standard Deviation of MSE (over 10-fold cross-validation). The top three methods—LASSO regression, Sequential Feature Selector, and Recursive Feature Elimination—were further analyzed as input features for a Deep Neural Network (DNN) model. The DNN’s performance was evaluated across varying data sizes (20 %, 40 %, 50 %, 60 %, 80 %, and 100 %) and configurations ranging from one to ten hidden layers. The findings reveal that LASSO regression, when integrated with DNN, consistently outperforms in terms of CVRMSE and NMBE metrics across different data sizes and model complexities. Notably, increasing the dataset size from 20 % to 80 % markedly improves the model’s predictive accuracy, underscoring the significance of larger datasets in enhancing DNN generalization and performance. Additionally, the study highlights a critical trade-off in DNN architecture: while models with fewer hidden layers (1–3) show greater performance variability in smaller datasets, increasing the number of layers does not linearly translate to better performance, illustrating the nuanced balance between model complexity and efficacy. This research contributes to the energy M&V field by demonstrating that shorter duration datasets, previously considered insufficient, can indeed provide accurate energy savings verification when analyzed with advanced deep learning techniques. This advancement not only paves the way for quicker, more efficient M&V processes in industrial settings but also offers valuable insights into the optimization of DNN models for energy data analysis.

Effectiveness of Facility Management in Achieving Carbon Neutrality in the Green Building Industry Supply Chain

Effectiveness of Facility Management in Achieving Carbon Neutrality in the Green Building Industry Supply Chain

A TOE-DCV approach to green supply chain adoption for sustainable operations in the semiconductor industry

Semiconductor industry plays a critical role for the global economy. Semiconductor industry provides various necessary technologies such as IoT, AI, modern fabrication technologies and so on to various industries including automotive industry, electronic and communication industry, healthcare industry, construction and building industry, space industry, and so on. However, semiconductor supply chain experiences various supply chain related risks and challenges because of its procedural complexities, global supply chain integrations, government policy and regulations, competitiveness, technological complexities, and so on. Not many studies available which investigated the risk, resilience, and complexities regarding green supply chain adoption by semiconductor industry. In this context, the objective of this study is to examine the risks, resilience, and complexities for managing the green supply chain adoption for higher sustainability in the semiconductor industry. Utilizing the TOE framework (Technology-Organization-Environment) and DCV (Dynamic Capability View), we developed a research model to achieve this purpose. Subsequently, this model was validated through structural equation modelling, involving 356 respondents affiliated with the semiconductor industry. This study highlights that technological risk aspects comprising of technological turbulence and risk, compatibility and complexity, organizational dynamic capabilities, and resilience along with appropriate policy and regulations could help successful adoption of green supply chain management in the semiconductor industry.

Strategic Approaches to Design Teams for Construction Quality Management and Green Building Performance

Buildings exert a profound influence on the environment, with the design phase recognized as the pivotal determinant of a building’s overall performance. Green building design, in particular, introduces heightened complexity, where the attributes of the design team play a pivotal role in shaping performance outcomes. Consequently, the characteristics of the design team emerge as crucial factors in the enhancement of both green building design performance and client attributes. This study aims to empirically examine a model formulated to gauge the extent to which Effective Design Team Attributes contribute to the enhancement of performance in designing green buildings and influencing client attributes. To achieve this objective, a comprehensive questionnaire survey was administered to professionals within the architecture and engineering domains actively engaged in the design and consulting sectors of the building industry. The collected data underwent meticulous scrutiny for authenticity and dependability using the WINSTEPS 5.2.5 software before undergoing subsequent analysis. Statistical analyses were conducted using SPSS version 19, with Principal Components Analysis (PCA) and the Structural Equation Modeling (SEM) approach implemented through Amos version 18 to derive the most robust model. The findings underscore the pivotal role of an adeptly managed design team in significantly improving both the performance of green building designs and the qualities of clients. Rasch’s analysis confirmed the validity of our 5-point Likert scale for Design Green Building Performance (DGBP), Effective Design Team Attributes (EDTA), and Client Qualities (CQ). All items demonstrated excellent reliability, separation, and discrimination, ensuring robust data quality. Dimensionality tests revealed the appropriateness of response categories, indicating satisfactory scale performance. The Effective Design Team Model, validated through Principal Components Analysis (PCA), exhibited a satisfactory fit, supported by significant chi-square statistics, high goodness-of-fit indices, and acceptable root mean square residual values. Client attributes displayed a strong association with effective design team management, validating key model elements. The intricacies inherent in the design process can be mitigated by adopting the green design charrette approach. Consequently, the establishment of an effective design team, coupled with green design leadership, active participation, and clarity in roles and responsibilities, emerges as a potent strategy for elevating the performance level of green building designs.