Building Operation Research Articles

The Relevance of Automation in the Facility Management of Selected High-Rise Buildings in Lagos, Nigeria

Operators (owners/facility managers) of high-rise buildings are continuously faced with the challenge of finding innovative means of controlling and managing the facilities of high-rise buildings. This is due to consistent change in the nature and functions of building systems. Meanwhile, the use of computerized systems affords building operators the tools and methods that will enhance facility management activities. This study examined the importance of automation to the facility management of high-rise buildings in developing countries, using the case of Nigeria. The study adopted a survey research approach, administering a structured questionnaire to 53 facility managers of identified commercial high-rise buildings in Ikoyi, Lagos Island, and Victoria Island in Nigeria. It also applied regression analysis in determining the significance of automation on facility management activities. The findings of the study revealed that security services are the most automated facility management activity. Results also showed that automation had a positive effect on facility management practice, with R square of 0.66. The study concluded that although automation is seldom used in carrying out facility management activities, it has a positive impact on facility management services, with 66% significance level on facility management activities. It then recommended that steps should be taken by all stakeholders to develop the practice of facility management and research, as well as facility management education.

Using IoT in Double Skin Facades toward Thermal Comfort: A Review

Integrating the Internet of Things (IoT) into building design and operation has ushered in a new era of sustainable architecture and enhanced occupant comfort. This paper presents comprehensive case studies focused on the application of IoT technology in the context of double-skin facades, explicitly focusing on achieving and optimizing thermal comfort. These case studies, located in an urban setting, represent a paradigm shift in architectural design principles. Double skin facades, renowned for their potential to enhance energy efficiency and occupant well-being, are further empowered through the intelligent deployment of IoT devices. This synergy between architectural innovation and digital technology is instrumental in addressing the pressing challenges of energy consumption and occupant comfort in urbanized areas. It delves into the sensors, actuators, and data analytics systems employed to monitor and control the indoor environment. Special attention is given to the dynamic adaptation of the facade system in response to real-time environmental conditions, occupancy patterns, and user preferences. One of the case studies—PH01-BRK, projects the practical application of these principles in South Dakota’s first custom passive and net-zero home, completed in 2016, using advanced thermal analysis tools, software for heating and cooling requirements, and solar data assessment. Furthermore, the paper investigates the impact of IoT-enabled double-skin facades on thermal comfort, energy efficiency, and indoor air quality within the Brookings Passive House. Quantitative data and occupant feedback are analyzed to assess the effectiveness of the IoT-driven system in maintaining optimal thermal conditions while minimizing energy consumption. The findings of this case study underscore the potential of IoT technology in revolutionizing the design and operation of sustainable buildings. It demonstrates that integrating IoT into double-skin facades can significantly enhance thermal comfort, reduce energy consumption, and create healthier indoor environments.

The impact of BIM authoring tools on the architectural profession in Jordan

Building Information Modeling (BIM) technologies have attracted much research attention, especially in the last fifteen years. The prospects and benefits that BIM promises for all participants in the design, construction and operation of buildings are hopeful and enthusiastic. Nevertheless, the global adoption of BIM has been slow and uneven. A bibliometric analysis shows that BIM research is concentrated in a few centers and performed by a narrow group of specialists. As a result, there are research areas with few or no publications (“blind spots”). One such area is the economics of BIM implementation. Considering the transition to the use of BIM as an investment project, the authors of the article formulate the necessary conditions for BIM implementation to become investment attractive. It is shown that the participation of governmental structures is necessary for a wide transition to digital technologies in the architectural and construction sphere.

Automated Reconstruction of Existing Building Interior Scene BIMs Using a Feature-Enhanced Point Transformer and an Octree

Building information models (BIMs) offer advantages, such as visualization and collaboration, making them widely used in the management of existing buildings. Currently, most BIMs for existing indoor spaces are manually created, consuming a significant amount of manpower and time, severely impacting the efficiency of building operations and maintenance management. To address this issue, this study proposes an automated reconstruction method for an indoor scene BIM based on a feature-enhanced point transformer and an octree. This method enhances the semantic segmentation performance of point clouds by using feature position encoding to strengthen the point transformer network. Subsequently, the data are partitioned into multiple segments using an octree, collecting the geometric and spatial information of individual objects in the indoor scene. Finally, the BIM is automatically reconstructed using Dynamo in Revit. The research results indicate that the proposed feature-enhanced point transformer algorithm achieves a high segmentation accuracy of 71.3% mIoU on the S3DIS dataset. The BIM automatically generated from the field point cloud data, when compared to the original data, has an average error of ±1.276 mm, demonstrating a good reconstruction quality. This method achieves the high-precision, automated reconstruction of the indoor BIM for existing buildings, avoiding extensive manual operations and promoting the application of BIMs for the maintenance processes of existing buildings.

In Search for Untapped Energy-Saving Potential in Green and Smart Higher Educational Buildings—An Empirical Case Study Involving the Building Occupants

Energy-intense activities and the unpredictable and complex behavior of building occupants lead to an increase in building energy demand. It is, therefore, crucial to study underlying factors for building energy demand related to the users. Higher educational buildings are relevant to study for several reasons: they host the future workforce and citizens, they are predicted to increase in numbers, and they represent a building type less studied. Furthermore, green-rated buildings equipped with smart building systems also represent a research gap that is relevant to address since such a building design involves IoT-functionalities and digital features for the building occupants to interact with. There is also a conceivable risk that if the users know that the building is green-rated and technologically advanced, this may alter their perception of the building operation and thus their behavior. To study the relationship between building occupants and such green and smart educational structure, a survey was conducted in a Swedish higher educational building; as a result, 300 responses were collected and analyzed. The responses revealed that the building occupants act with energy awareness, and they are conscious about energy-saving behaviors. One building feature in particular was studied: the Digital Room Panels (DRPs). The DRP allows the building occupants to modify the indoor temperature and is, therefore, essential for thermal comfort. One key finding from the survey revealed that 70% of the building occupants did not know how the DRPs operate. This study argues that this result can be explained with a lack of communication and user friendliness. Inadequate interactions with building systems could also result in opportunities for energy saving might not be realized. The findings of this case study led to valuable recommendations and suggestions for future research endeavors.

K-Means Clustering to Identity Twitter Build Operate Transfer (BOT) on Influential Accounts

Twitter is a popular social media with hundreds of millions of users, but some are not human. About 48 million accounts are created by Build Operate Transfer (BOT), which represents up to 15% of all accounts. BOTs are created for various purposes, one of which is to post information about news automatically. However, BOTs have also been abused, such as spreading hoaxes or influencing public perception of a topic. The research aimed to determine which Twitter accounts were identified as BOT accounts based on predefined attributes. The research used tweet data from 213 Twitter accounts. The accounts used as test data were accounts that had influence. After that, the data were clustered using k-means using the attributes of retweets + replies count, followers count, account age, friends count, status count, digits count in name, username length, name similarity, name ratio, and likes count. The results show the optimal number of clustering at k = 3 on the Sum of Squared Errors (SSE) evaluation and the Elbow method and the best quality and cluster power at k = 2 on the silhouette coefficient. It shows that the clustered accounts with the highest number of members on each attribute are places for accounts with high BOT scores from several aspects of the BOT score type.

Life cycle energy and greenhouse gas emissions of a traditional and a smart HVAC control system for Australian office buildings

In recent years, many novel smart technologies have been proposed to reduce the energy consumption and greenhouse gas (GHG) emissions attributed to the building sector. One such application of these technologies is the reduction of the Heating, Ventilation and Air Conditioning (HVAC) energy needs and GHG emissions using smart control systems. The environmental benefits of smart control systems during building operation have been explored in many studies, however, their embodied effects, associated with the extraction of raw materials, manufacturing and replacement are often overlooked. Accordingly, this study quantifies the life cycle energy needs and GHG emissions of a smart HVAC control system and assesses its potential for reducing the HVAC operational energy and GHG emissions in an Australian office building. A comparative assessment is performed, considering a traditional HVAC control system and an equivalent smart HVAC control system. The components of both the traditional and smart control systems are specified based on the characteristics of these systems as well as the layout of the serviced spaces in the reference building. The embodied energy and GHG emissions of both the traditional and smart control systems are quantified through a hybrid life cycle inventory (LCI) approach. To evaluate the effects of these control systems on the building HVAC operational energy, a building energy simulation is performed by applying the control logics of both systems. The results show that energy and GHG emissions savings in the HVAC operational offset the additional energy needs and GHG emissions of deploying the smart HVAC control system.

Analysis of Investment Feasibility for the Wonderlife Hotel Development Project in Pangandaran Based on Financial Aspect

The increasing tourism activities in Pangandaran Tourist Destination must be supported by adequate facilities and infrastructure, particularly accommodation. Pondok Seni Pangandaran, owned by the Department of Culture and Tourism of West Java Province, needs to be revitalized to compete with other hotels. Through the Build Operate Transfer (BOT) cooperation scheme, private sector involvement is expected in investing in the revitalization of Pondok Seni Pangandaran. However, a feasibility study is required to determine the financial viability of the investment, including calculations of NPV, Profitability Index, Payback Period, and IRR. From the feasibility analysis, the investment shows a cash inflow of Rp. 555,712,698,655.00; projected profit and loss of Rp. 45,026,582,596.00 over a 30-year operating period; NPV of IDR 17,962,228,160.00; Profitability Index of 2.53; Payback Period of 10 years from the construction period and 8 years from the operational period; and IRR of 13.17%. In conclusion, the investment in the Wonderlife Hotel development project in Pangandaran is deemed feasible.

Cost Optimization and Estimation of Embodied Carbon in Reinforced Concrete Frame Structure

Reinforced concrete (RC) structures are one of the most common building systems around the world. Measures are being taken to reduce the construction industry’s contribution to the greenhouse gas emissions. The contribution of embodied energy of structures is also considered for more efficient operation of buildings. This study investigates the embodied carbon content for the different grades of concrete used for the design and an optimization approach for an economic design. Analysis and design of RC frame structures are done using STAAD-PRO software and cost optimization is carried out using Genetic Algorithm (GA) in MATLAB software. The considered design constraints are geometric, strength and reinforcement areas confirming to Indian Standard codes. The optimized result is used to model the RC structure in Revit Software to determine its embodied carbon content. Candidate structures are then assessed for embodied energy to determine individual relationships. This study shows the possibility to reduce the embodied carbon content of RC frame structure and the proposed optimum design model can be adopted to design commercial buildings as it yields reliable, economical, time-saving and practical designs whilst remaining compliant to given design codes.

Deployment of real-time building automation system-integrated inverse-model-based fault detection and diagnostics algorithms

The complex operation of HVAC systems in large commercial buildings warrants regular implementation of advanced analytical approaches to operations and maintenance, and subsequent corrective measures to improve and maintain optimal energy performance. Despite the established capabilities of data-driven fault detection and diagnostics (FDD) to identify suboptimal controls policies and mechanical faults resulting in poor energy performance, few attempts have been made to deploy scalable solutions around these approaches. Furthermore, real-time BAS-integrated FDD methods are predominantly rule-based, offering limited insights to faults with gradual negative impacts to energy performance. This paper demonstrates the application of various established data-driven, inverse-model-based FDD methodologies in a BAS-integrated environment. Traditionally implemented sparingly, the novelty of recursive and automatic execution of advanced FDD methodologies, facilitated through a direct data pipeline to an existing BAS, capitalizes on the BAS’s real-time monitoring capabilities to enable continuously refreshed inverse model generation that can capture the gradual degradation of building performance, and provide up-to-date actionable visualizations and key performance indicators (KPI) to building operators. Since deployment, the application has successfully identified a scheduling fault on two separate occasions in a case study building in Ottawa, Canada, and the visualizations were presented to the building operators who resolved the issues.

Artificial intelligence in the construction sector

The application of artificial intelligence in the construction industry is divided into two main areas: 1. Using new technologies such as big data, cloud computing and the Internet of Things to optimise building design and management and provide users with a better living environment and service experience. 2. Using artificial intelligence technology to carry out intelligent building operation and maintenance, reduce the number of construction site operators and improve the efficiency of the construction site. Based on the analysis of the application scenarios in these two aspects, the application of artificial intelligence in the field of construction has a broad prospect. Especially with the continuous development and improvement of the Internet of Things and big data technology, artificial intelligence can better enhance the quality of intelligent buildings.

Development of a framework to forecast the urban residential building CO2 emission trend and reduction potential to 2060: A case study of Jiangxi province, China

Investigating the CO2 abatement potential of urban residential building from systematic perspective is essential to reach the urban carbon neutrality target. However, previous studies on building CO2 emission trend forecasting were mainly focused on the building operational phase. In this study, a new framework that includes four building stages under a system dynamic model is developed to simulate urban residential building carbon emission changes and the related reduction potentials under three scenarios in Jiangxi Province up to 2060. Results showed that the overall process carbon emission dynamic had already peaked in 2014 under the three scenarios, with a peak value of 38.52 Mt. It then fell to 9.56 Mt in 2060 under the baseline (BAU) scenario. More importantly, seven carbon abatement measures were adopted during four building activities in this study, and the total carbon reduction was not the sum of the carbon reduction potential of the individual measures. Some carbon abatement strategies displayed synergistic effects such as low-carbon electrification where the combination of electrification and clean energy power generation was the largest contributor to reduced carbon emissions during building operation as a comprehensive carbon reduction measure. By contrast, extending a building's lifetime restrained the carbon abatement potential during the demolition stage, and it inhibited the carbon emission reduction by 24.84 Mt. These results highlight the significant need for effective policy interventions for clean production and the need to improve prefabricated building proportions, promote electrification, improve energy efficiency, strengthen recycling practices, and extend building lifetimes to promote decarbonization of urban residential building system development.

Semantic correction, enrichment and enhancement of social and transport infrastructure BIM models

The use of Building Information Modelling (BIM) models in the design, construction and operation of buildings and infrastructure is leading to a stronger focus on the quality of the models. Models may need correction, enrichment or enhancement to meet the expectations for quality and completeness, especially if models are to be taken as legal documents, for example for regulatory approval. Past work on semantic development has looked at specific scenarios such as scanned geometry or missing classification. This paper describes an innovative unified approach to the documentation of semantic expectations by actors in the AECO (Architectural, Engineering, Construction and Operations) domain and the means to put them into effect. RASE (Requirements, Applications, Selections and Exceptions) semantic mark-up is used to make both the requirements and any supporting resources both human-readable and machine-operable. Two example models from industry, a motorway bridge and a healthcare space, are used to demonstrate applying geometric, schema and classification knowledge. This knowledge is represented in a number of different styles. This extends our understanding of the nature of the knowledge found in dictionaries, classifications and development specifications, demonstrating how this knowledge can be made operable. This bridges the gap between the application of static compliance knowledge and the accurate and efficient application of correction, enrichment and enhancement knowledge.

Did electrification of the building sector achieve carbon mitigation? A provincial retrospection in China

Electrification of end-use energy consuming sectors is becoming a widespread choice to combat climate change, yet the decarbonization of electricity determines the quality of carbon emissions reductions from electrification. This study evaluates the changes in carbon emissions from building operations due to electrification in China's 30 provinces over the period 2004–2020. Considering electricity decarbonization, electricity consumption, population and floor area, an assessment framework for carbon emissions reductions from building electrification has been built by Kaya-LMDI method. The results show that (1) The promotion of building electrification causes an increase of approximately 46.88 MtCO2 over the period 2004–2020. The urban residential buildings contribute the largest share, about 54.78%; (2) Almost half of the provinces have failed to achieve carbon emissions reductions with promotion of building electrification; (3) The change in carbon emissions caused by the promotion of building electrification shows a clustering effect in space, with the northern region characterized by high-high clusters and the southern region by low-low clusters. In addition, this study reviews the strategy for power decarbonization and building electrification in China. The overall strategy for building electrification is to accelerate the proportion of electricity consumption in existing buildings and to promote the electrification of new public buildings across the board. Overall, this study provides a reference for other economies and end-use energy sectors to evaluate electrification for carbon emissions reductions, and provides insights and strategies for policy makers on the promotion of building electrification.

How many trees are required to offset the CO2 emissions from building operations? A case study of energy efficiency initiatives in Wisma R&D, Universiti Malaya building

Malaysia has pledged to GHG emissions by 45% by 2030 in light of the urgent need to reduce global emissions. One approach used by the government is to concentrate on energy sustainability programs, such as energy efficiency (EE). The success of this approach relies on the support from various parties. Persuading non-technical management and staff, however, might be particularly difficult. Hence, besides the technical-based impact, it is important to analyse the environmental and financial-based impact too. This paper portrayed the EE initiatives that could assist in reducing energy (kWh), cost (RM), and CO2 (tonne) simultaneously. The number of trees needed to neutralise or offset an emission might later be related to a reduction in CO2. A case study of Wisma R&D, UM was referred. The environmental-based impact of the lighting retrofitting projects at Wisma R&D was used in this study to illustrate the importance of EE approaches. Both parameters are obtained from the online Greentech carbon calculator. A 144,386 kWh annual savings resulted in RM 52,701 in cost savings, and a decrease of 100.2 tonnes of CO2 emissions was achieved. Ultimately, based on the decrease in CO2, 2569 fewer trees are needed to offset the emission.

The Evolution of Structural Systems in Tall Buildings: From Ancient Skyscrapers to Future Megatowers of the Future

Tall buildings have undergone significant structural evolution throughout history, driven by advancements in engineering, materials, and design concepts. The construction and operation of tall buildings pose challenges related to safety, transportation, and infrastructure. The development of seismic-resistant structural systems for tall buildings, especially in earthquake-prone regions, is a critical aspect of ensuring the safety and stability of structures during seismic events. The integration of these structural systems and design strategies is crucial for creating safe and resilient tall buildings in regions vulnerable to earthquakes. This paper focuses on the historical development of structural systems in tall buildings, from ancient skyscrapers to the design and construction of sustainable and eco-friendly innovative megatowers of the future. This review will highlight the diverse ways in which tall buildings can integrate sustainability-focused structural systems, contributing to environmental conservation and energy efficiency. Key words: Tall buildings, sustainable, energy efficient, structural systems, seismic resistant

Applying Dynamic U-Value Measurements for State Forecasting in Buildings

Abstract In the present day, monitoring and automated control stand as pivotal factors for the energy-efficient and comfortable operation of buildings. As the demand for indoor climate control grows, building management systems have become more intricate, making their control challenging due to the increasing number of controllable elements. Replacing manual human analysis of complex systems can be achieved through the utilization of algorithms like model-based control. It is important to note that performance of this method usually relies on the accuracy of neural network-based building state forecasts. Studying the internal dynamics of climate as influenced by temperature changes necessitates a brief record of measurements, whereas evaluating structural modifications through moisture transfer demands data covering a more extended period. Neural networks such as Long Short-Term Memory have the potential to lose information within lengthy time-series data, and the intricate nature of moisture transfer further adds complexity to the task of approximating functions, ultimately leading to a reduction in energy efficiency. In order to improve the precision of indoor climate predictions, our suggestion involves not only assessing changes in temperature but also considering alterations in U-values triggered by temperature variations and moisture transfer. Our preliminary assessment of the influence of U-value, conducted through numerical simulations using WUFI6, exposes variations of up to 10 % of U-value in certain scenarios. Dealing with these computations in real time using physical models proves to be demanding due to computational requirements and limited data availability. To tackle this issue, we present an innovative preprocessing approach for on-the-fly evaluation of U-values. Empirical trials involving three years of monitoring data indicate that the suggested technique led to an approximate 8 % reduction in the average mean squared error of climate predictions based on neural network models, in specific instances.

Barriers and drivers for implementation of automatic fault detection and diagnosis in buildings and HVAC systems: An outlook from industry experts

This study aimed to assess the current status of Fault Detection and Diagnosis (FDD) implementation in building and Heating, Ventilation and Air Conditioning (HVAC) systems in the building industry. Semi-structured qualitative interviews were conducted with 29 experts from different HVAC company types in the building industry. In addition, a literature review was performed to investigate academic research on FDD implementation. The study identified barriers and drivers to implementing FDD systems, these included; technological and technical, economic and business, users, social and societal, and regulatory. An Automatic Fault Detection and Diagnosis (AFDD) implementation matrix was developed to evaluate FDD implementation in building systems, and all interviewed companies were classified based on their FDD knowledge, services, and type. Results show that expert-rule systems are still prevalent in the industry. The literature review revealed a scarcity of FDD implementation studies in academic research due to challenges in testing and validating results in actual building operation conditions. Lastly, this study discusses the key findings: 1) FDD does not sell, 2) Lack of actively engaging and promoting FDD services, 3) FDD seems to be an academic definition, 4) The bottlenecks: The fault handling process and user’s mindset towards FDD, and 5) Governmental regulations and legislatives drive the implementation focus.

ENERGY PERFORMANCE INDICATOR FOR HEALTH CARE BUILDING: A CASE STUDY OF A SMALL SIZED HOSPITAL IN INDONESIA

Energy is needed to guarantee the reliable and safe operation of healthcare buildings. The hospitals and other healthcare building energy performance have been investigated using several sets of energy performance indicators (EnPIs) formulation in several contexts. Often, those EnPIs are meaningless compared to other healthcare buildings, or they are restricted in their ability to guide energy investment planning or operation. This study examined four approaches—kWh/sqm/year, kWh/bed-day, kWh/overnight inpatient, and kWh/sum of inpatient and outpatient—for calculating EnPIs of a small-sized government hospital. The analysis focused on methods for defining EnPIs in the healthcare industry. With a value of 4.62 kWh/patient, it was found that the kWh/sum of in and outpatient was the optimal EnPI model.

From Zero Energy to Zero Power Buildings: A new framework to define high-energy performance and carbon-neutral buildings

The definition of Zero Energy Building (ZEB) has often been controversial both in regulation and research. This work explores a new evaluation framework introducing the Zero Power Building (ZPB) concept, a novel method that studies the relationship of buildings to the physical boundary, weighting system and analysis timeframe, approaching performance assessment at reduced time intervals. The methodology proposed in this paper showcases how the limitations of the ZEB can be overcome by adopting the ZPB concept on a reference commercial building. The case study was analysed under two different scenarios, with and without an electric storage system. The application of the ZPB concept on an hourly basis poses a challenge to the case study performance, considering both final energy use and CO2 emissions. Specifically, the building commonly accepted as a ZEB turns as a ZPB for only 54.76% of annual hours and as carbon-neutral building for 55.58% of annual hours. The paper presents an innovative methodology that aims to assist in the design and operation of future buildings, as well as provide guidance for policymakers and regulators. The findings emphasize the significance of using dynamic assessment strategies to accurately evaluate the buildings performances and enable meaningful comparisons in various contexts.