Search

Passive ultra-low energy buildings represent an effective strategy for energy conservation and emission reduction within the global building industry. The prolonged and cold winters in severely cold regions of China necessitate substantial heating energy consumption. The study utilized a combination of overall surveys and long-term tracking surveys to evaluate the indoor environment and energy consumption in a passive office building situated in severely cold region under different heating modes over 2 years. The results show that the average temperature and indoor air quality (IAQ) can meet the standards at most moments. However, the average relative humidity tends to fall below the specified lower limit. Nevertheless, the Predicted Mean Vote (PMV) index suggests that the indoor environment provides a comfortable thermal experience for humans. The heat pump air conditioning (HPAC) system operation revealed that when the outdoor air temperature fell below −7°C, the coefficient of performance (COP) of the air source heat pump units would deteriorate. Implementing intermittent heating during the second year can reduce heating energy consumption by 13.4 kWh/(m2·a), resulting in 38.9% energy savings. These findings will serve as a valuable reference for the design and operation of heating systems in passive buildings in severely cold regions. [ABSTRACT FROM AUTHOR]

In a fire, stairways are the primary avenues for building evacuation. Previous studies focused on investigating evacuation flow through evacuation drills in a high-rise office building to assess the accuracy of evacuation scenarios and compared them with evacuation dynamics. However, the effectiveness of evacuation drills in estimating many scenarios is limited by actual drills. The evacuation simulations present a promising approach to objectively evaluating evacuation scenarios. This study verifies whether evacuation simulations can faithfully replicate actual evacuation flow and effectively predict suitable evacuation scenarios or potentially involve parameter calibration. Through a comprehensive comparison analysis, this study scrutinized the reliability of evacuation simulations and calibrated the simulation parameters. The analysis revealed that factors, including adjustments to the door width, personal space considerations for occupants in both conflict and normal situations and variations in staircase structure configuration, can significantly influence the evacuation flow within staircases. Manipulating these parameters in simulations would enable a more precise replication of evacuation flow within staircases, thereby enhancing the simulation's accuracy in target evacuation scenarios. The findings of this research have underscored the significance of employing advanced simulation techniques to model evacuation dynamics accurately, facilitating a robust framework for devising effective emergency evacuation strategies in high-rise office buildings. [ABSTRACT FROM AUTHOR]

The purpose of this research is to investigate the impact of indoor environmental quality, behavioral, and functional factors on employee productivity and satisfaction in both open and closed office designs, as well as their relationship with building features and indoor environmental parameters. Literature review, questionnaire survey, and measurement of the indoor environment, were all used to collect data for this study. Statistical analysis was carried out using the SAS JMP program. It was found that employees in closed offices have higher levels of satisfaction with their indoor environment and behavioral aspects of their workplace, whereas employees in open workplaces have higher levels of satisfaction with their functional components and indoor air quality. As the study further reveals, Jordanian employees generally prefer working in closed offices since they provide privacy, which directly affects their satisfaction and productivity. Overall, the study emphasizes how occupant health, satisfaction, well-being, and productivity are affected by their office environment. When designing and selecting office spaces that prioritize employee satisfaction and productivity, architects and business owners can gain valuable insights from this study. [ABSTRACT FROM AUTHOR]

Since most people spend more time at work in recent times, this has led to more workplace issues and health problems. The well‐being of occupants and their overall health are strongly impacted by factors that determine the standard of indoor environments. These factors include the air quality, the level of thermal comfort, the inclusion of indoor plants, the admission of daylighting, and a variety of other factors. The absence of any of these may result in sick building syndrome (SBS). Therefore, well‐planned indoor workspaces are vital for occupants' health and productivity at work. The aim of this article is to investigate proactive measures for mitigating SBS in office buildings located within universities in the United Kingdom. The study administered a questionnaire to gather perceptions of office occupants, followed by a comparative case study analysis of two office buildings at the University of Greenwich located on different campuses to highlight the correlation among the physical parameters of indoor office spaces and the occurrence of SBS. The results showed that a notable percentage of participants reported experiencing at least two symptoms of SBS. This study provided clear evidence that symptoms of SBS are primarily associated with the physical characteristics of the building, and these elements significantly influence the occupants' experiences. The mitigation of potential adverse effects on the well‐being of inhabitants during the operating phase of a building resulting from physical variables can be achieved by the implementation of conscious design considerations during the initial planning stages of future buildings. One of the practical implications of this study is that it raises the urgency for built environment professionals to be fully aware of how their design decisions could either contribute to or prevent SBS symptoms. [ABSTRACT FROM AUTHOR]

The power consumption data in buildings can be viewed as a time series, where outliers indicate unreasonable energy usage patterns. Accurately detecting these outliers and improving energy management methods based on the findings can lead to energy savings. To detect outliers, an anomaly detection model based on time-series reconstruction, AF-GS-RandomForest, is proposed. This model comprises two modules: prediction and detection. The prediction module uses the Autoformer algorithm to build an accurate and robust predictive model for unstable nonlinear sequences, and calculates the model residuals based on the prediction results. Points with large residuals are considered outliers, as they significantly differ from the normal pattern. The detection module employs a random forest algorithm optimized by grid search to detect residuals and ultimately identify outliers. The algorithm's accuracy and robustness were tested on public datasets, and it was applied to a power consumption dataset of an office building. Compared with commonly used algorithms, the proposed algorithm improved precision by 2.2%, recall by 12.1%, and F1 score by 7.7%, outperforming conventional anomaly detection algorithms. [ABSTRACT FROM AUTHOR]

This study investigates the economic characteristics of green and conventional office buildings in selected nodes in Gauteng Province in South Africa. We estimated the gross rent, net rent and operating cost per square meter elasticities using hedonic regression models. Contrary to international research, which points to tenants willing to pay rent premiums and enjoy cost savings for green, compared to conventional buildings, our results show that in some nodes, green and conventional buildings of similar quality were not differentiable based on rents and operating costs. In one node, 3-star rated green buildings rented at a premium and their operating costs were higher, compared to conventional buildings of similar quality. Only in one node were 4-star rated green buildings characterized by rent premium and lower operating cost advantages for tenants. Differences in the attractiveness of nodes imply that tenants may forgo the expected cost savings from renting green offices in addition to paying a rent premium if the location is right. Since the dataset is archival, findings may not reflect market conditions caused by the COVID-19 Pandemic. In addition, the relatively limited size of the dataset may inhibit applicability of the insights across the South African office market. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has significantly altered how people work, with an increasing number transitioning to working from home (WFH). This paradigm shift has raised various challenges in adapting living spaces to meet the needs of remote work. Dedicated workspaces or home offices need to be customized for creativity and productivity. Thus, this systematic literature review explores the potential challenges and limitations of implementing modern office design features in residential environments. The study synthesizes findings from 108 peer-reviewed articles published within the last decade, focusing on ergonomics, productivity, work–life balance, and spatial constraints. The study found several challenges in translating office design features to home settings. Firstly, spatial limitations in residential areas often restrict the implementation of open-plan layouts and collaborative zones, which are hallmarks of modern office designs. Secondly, the integration of ergonomic furniture and adjustable workstations are limited by budget constraints and the dual-purpose nature of many home spaces. Furthermore, the review highlights the psychological challenges of maintaining work–life boundaries when professional and personal spaces overlap. Noise pollution and distractions emerge as significant factors impacting productivity in home offices, which contrasts controlled modern office environments. The review suggests that the complete replication of modern office design in homes may be impractical; a hybrid approach that adapts key features to residential constraints could enhance home office productivity. Potential solutions could include modular furniture designs, the simulation of collaborative spaces, and the development of noise-cancelling technologies specifically for home environments. This study contributes to the growing body of knowledge on remote work environments and provides valuable insights for enhancing work–life balance, environmental sustainability, and economic growth. [ABSTRACT FROM AUTHOR]

This article provides an ethnomethodologically informed ethnographic investigation of visually recognisable aspects of shared work spots in co-working office rooms. We focus on the phenomenon of holding a place in such environments, and document the participants' practices which constitute distinguishing between empty and taken places. Our investigation leads to a conceptualisation of designed andad hocplaces, noting that objective assessments of rooms' occupation status are problematic. We propose the notion of markers of presence, i.e. the material objects and their configurations, which participants use to indicate to others that a certain place is taken. Finally, we identify an observation area within the office space which participants recurrently use to assess the availability of work spots. We conclude by pointing out that rather than being tied to static features of material objects, the evidently visible occupational status of shared work spots is dynamically re-produced in participants' ongoing courses of action. [ABSTRACT FROM AUTHOR]

With the rapid spread of telecommuting since the COVID-19 pandemic, companies have been relocating to high-end business centers, thereby enhancing the workplace experience for employees, a phenomenon called the "flight to quality." However, this trend's impact on rents and vacancy rates in individual office buildings has not been extensively studied. To determine the effects of the flight-to-quality phenomenon on individual buildings, we examine the impact of modern amenities, which directly influence employee lifestyles, on rents and vacancy rates in the Tokyo office market. Using a propensity score-based quasi-experimental method, we find that commercial properties with such modern amenities command higher rents and experience lower vacancy rates than those without. The difference in vacancy rates has increased since 2020. However, the significance of these amenities diminishes for properties less competitive in age, size, and location. The results indicate that the "flight to quality" may further polarize the office real estate market into two categories: one for high-end buildings experiencing increasing demand, and another for those with modest amenities experiencing decreasing demand. The findings have implications for office building owners/investors and the government, make educated decisions as to whether to invest in modern amenities, join the quality competition, or encourage urban restructuring. [ABSTRACT FROM AUTHOR]

Climate-adaptive building shells (CABS) are designed to dynamically respond to environmental parameters, unlike the static facades of traditional buildings, which cannot adjust to external conditions. Traditional building facades often fail to adapt to varying climatic conditions, negatively affecting thermal comfort, visual comfort, and energy efficiency. This limitation is particularly noticeable in office environments, where the quality of the internal environment significantly impacts both staff efficiency and user satisfaction, making it crucial to maintain optimal conditions. This paper aims to (I) explain the reasons for selecting CABS to enhance the performance of building facades and (II) design and present a new example of such a façade. To achieve this, a CABS was designed and evaluated on the facade of an office building in Kermanshah using Rhino-Grasshopper software. The performance of this facade was assessed based on its ability to maintain thermal comfort, provide visual comfort, prevent glare, and offer adequate lighting for office use. Simulation data analyzed using Grasshopper software revealed that implementing CABS in rooms with direct light exposure adjusted the radiant temperature within the comfort zone 73% of the time, representing a 35.3% improvement over conditions without CABS. These adaptive shells minimize solar heat absorption during peak heat hours, balance internal temperature fluctuations, and, depending on the room's orientation, reduce solar ray intensity, light glare, and the number of dazzling light hours per year. CABS convert sunlight into Useful Daylight Illuminance (UDI) suitable for office environments. Consequently, the use of CABS led to a 79.5% increase in useful light levels and improved UDI quality and efficiency compared to non-CABS situations. [ABSTRACT FROM AUTHOR]

Accurate modelling of occupancy patterns is critical for reliable estimation of building stock energy demand, which is a key input for the design of district energy systems. Aiming to investigate the suitability of different occupancy-modelling approaches for the design of district energy systems, the present study examines a set of standard-based schedules (from the UK National Calculation Methodology), a widely used stochastic occupancy model, and a novel energy-data-driven occupancy model. To this end, a dynamic energy model of a higher education office building developed within a stock model of London's Bloomsbury district serves as a testbed to implement the occupancy models, explore their implications for the estimation of annual and peak heating and cooling demand, and extrapolate the findings to the computationally demanding building stock stimulations. Furthermore, the simulations were conducted in two years before and after the COVID-19 pandemic to examine the implications of hybrid working patterns after the pandemic. From the results, the energy-data-driven model demonstrated superior performance in annual heating demand estimations, with errors of ±2.5% compared to 14% and 7% for the standard-based and stochastic models. For peak heating demand, the models performed rather similarly, with the data-driven model showing 28% error compared to 29.5% for both the standard-based and stochastic models in 2019. In cooling demand estimations, the data-driven model yielded noticeably higher annual cooling demand and lower peak cooling demand estimations as compared with the standard-based and stochastic occupancy models. Given the adopted building-modelling approach, these findings can be extended to district-level investigations and inform the decision on the choice of occupancy models for building stock energy simulation. [ABSTRACT FROM AUTHOR]

The article presents an analysis of changes in energy efficiency of new office buildings designed and constructed during the implementation period of the Energy Performance of Buildings Directive (2014–2024). Common criteria on energy efficiency were collected from Energy Performance Certificates (EPCs) and processed. The changes in final and primary energy for space heating, cooling and hot water production of certified office buildings were determined, and the improvements in buildings, their energy systems and energy sources were analysed. It was determined that buildings of Class C, designed between 2006 and 2017, showed an average thermal energy consumption for heating of 61, for cooling of 13 and for hot water production of 30 kWh/(m2·year), while buildings of Class A++, designed after 2020, consumed, respectively, 6, 9 and 17 kWh/(m2·year). The main reasons for these changes in energy consumption are the significant improvement of thermal insulation, increase of renewable energy in the heat supplied by district heating, the use of heat pumps for cooling, more efficient hot water boilers and optimized and insulated distribution pipelines. Even better results were hindered by the increased area of glazing, insufficient use of solar protection, users' preference for buildings of complex shape, and technically complicated electricity production. The results revealed that EPCs are an appropriate database for the analysis of changes in energy efficiency of buildings and for setting tasks for further improvement. [ABSTRACT FROM AUTHOR]

The roof is the part of a building that is exposed to solar radiation for the longest period, making green roofs particularly effective in reducing air conditioning energy consumption during the summer. This study aims to assess the advantages of modular green roofs in terms of energy savings and cost reduction during the summer in Xuzhou. By conducting field measurements and surveys under both air-conditioned and non-air-conditioned conditions and utilizing building energy simulation tools, the performance of green roofs with different parameters was compared. Using EnergyPlus, factors such as soil thickness, thermal conductivity, and leaf area index were simulated. The results indicated that green roofs have superior thermal performance in summer, with the daily cooling load per unit area for top-floor rooms being 1.05 kWh/m2, 0.21 kWh/m2 lower than that for bare roofs, achieving an energy saving rate of 16.7%. It is recommended that soil thickness not exceed 0.3 m and insulation thickness not exceed 0.05 m or be set to 0 m. Take building no. 2 of the Xuzhou material market as an example: with the optimized green roof, the energy saving rate increased to 27.0%, which is 12.4% higher than that of the original green roof. The suggested cost for modular green roofs is 204 RMB/m2. [ABSTRACT FROM AUTHOR]

To accurately assess the carbon emissions associated with assembled steel structure office buildings, this study develops a comprehensive life cycle carbon emission calculation. Utilizing advanced tools such as Autodesk Revit, Tekla Structures, and DeST-C, the model offers a detailed methodology for calculating emissions. This approach adheres to the guidelines set forth in the “Standard for the Calculation of Carbon Emission from Buildings” (GB/T 51366—2019). By applying this model to the Wuxi CEC PARK case study, the research quantifies the carbon footprint of such structures and compares these findings with those of assembled precast concrete structures and cast-in-place steel–concrete structures. The model encompasses all six stages of a building’s life cycle: material preparation and component production, logistics, operation and maintenance, renovation and reuse, and finally, dismantling and recycling. This comprehensive scope ensures that the model captures the carbon emissions linked to every aspect of “human, machine and material” interactions throughout the building’s life cycle. The accuracy of the calculation results is thus guaranteed. Specifically, the analysis highlights the carbon emission factors from steel structure components within the context of Wuxi CEC PARK. The results show that the average annual carbon emission intensity for the building is 59.47 kg·m−2·a−1. This figure is approximately 5.46 kg·m−2·a−1 and 13.59 kg·m−2·a−1 lower than that of the assembled PC structure and the cast-in-place steel–concrete structure, respectively. These results underscore the beneficial impact of assembled steel structures in reducing carbon emissions. The operation stage is the largest contributor to carbon emissions, accounting for 58.79% of the total. This is followed by carbon emissions from material preparation and component production, which represent 29.58%. The study finds a negative carbon emission value of −3295.27 t in the dismantling and reuse phase, indicating a significant reduction in emissions in this phase of the building’s life cycle. Additionally, the incorporation of renewable energy sources and plant carbon sinks into the building’s design further offsets carbon emissions, contributing an additional reduction of 389.33 t. The method proposed in this paper addresses the gap in existing methodologies for full life cycle carbon emission calculations for assembled steel structure office buildings. It provides a solid foundation for such buildings, promoting the adoption of assembled steel structure office buildings. It lays a foundational framework for assessing the carbon reduction potential of these structures, thereby facilitating their wider adoption within the construction industry. It provides a reference for future research on the prediction of carbon emissions for similar office buildings and advancing carbon reduction initiatives in the construction industry.

Simultaneously with the development of technology, the use of modeling techniques has gained popularity among actors in their sectors. However, although Building Information Modeling (BIM) is widely used in most design disciplines, its usage rate in the field of fire safety is not yet at the same level as in other fields. In this study, the office building modeled with Revit, one of the most well-known software in the BIM environment, was examined using CYPEFIRE Design and FINEFIRE software according to the determined fire safety criteria. The fire safety criteria that the office building must meet have been established based on the Regulation on Fire Protection of Buildings and relevant standards. The software was evaluated according to the parameters of learnability, proficiency, memorability, errors and satisfaction in terms of "usability" in accordance with the EN ISO 9241-11 standard. As a result of the studies carried out, CYPEFIRE Design achieved 13 (52%) of the 25 fire safety criteria determined according to the regulations and standards; FINEFIRE provided 10 (40%) compliance checks. Among the usability parameters, CYPEFIRE Design stands out in the evaluation of adequacy and errors parameters, while FINEFIRE stands out in terms of learnability and memorability parameters. There are applications where both software provide superiority over each other regarding fire safety. As a result, the use of these software, which allows the application of fire safety measures in the entire structure in the BIM environment, ensures that the project process is carried out faster and more interactively. The use of BIM technology in the implementation of fire safety measures, which must be carried out together with the architectural project process of the building, will become more widespread and comprehensive in the near future. [ABSTRACT FROM AUTHOR]

The inspection of building components plays a crucial role in reducing maintenance costs throughout the building's life cycle. Many buildings suffer from defects in the building elements, such as surface problems, cracks, and moisture problems. Building Information Modeling (BIM) has become a widely used digital tool for the construction industry, allowing for the virtual visualization, design, and simulation of structures. At the same time, progress in neural networks, a branch of artificial intelligence, presents encouraging potential for classification and evaluation. This article explores the fusion of BIM and neural networks to improve and simplify the building inspection procedure. Neural networks are implemented with BIM to conduct real-time analysis and predictions as part of an inspection framework. A data set consisting of 500 wall samples with defects from different buildings was collected through fieldwork. These data were then classified into five categories, ranging from D1 (No damage) to D5 (Collapse), based on expert opinions. A neural network was used to create a model that can show the severity of degradation of building elements. The BIM platform is utilized in the implementation of the proposed model to facilitate the exchange of information and enhance documentation during inspection. The visualization provided by BIM allows the facility management team and building owners to assess building elements through causality analysis using distinct color codes. A case study of an office building is featured in the paper to showcase the application of the proposed model for asset management. The color-coded system used in this study denotes low-performance conditions as red, medium performance conditions as yellow, and high-performance conditions as green. This article outlines the procedures for categorizing and ranking defects in building elements, specifically focusing on walls. Practical Applications: This study explores innovative methods for assessing the condition of buildings, aiming to improve accuracy, efficiency, and predictive capabilities. Traditional building inspections are often subjective, time-consuming, and labor-intensive, making it challenging to generate consistent and comprehensive evaluations. Our research addresses these limitations by integrating BIM and neural networks. BIM provides detailed digital models of buildings, which include comprehensive information about each component. This technology enables precise and consistent assessments, reducing the subjectivity inherent in manual inspections. Neural networks, a type of artificial intelligence, can analyze complex data patterns and detect potential issues early, allowing for proactive maintenance. By combining these two technologies, our approach offers a more efficient and objective method for building condition assessment. This integration not only saves time and resources but also enhances the ability to predict and prevent future issues, ultimately extending the lifespan of building components and improving overall building performance. These advancements are particularly relevant for property managers, maintenance teams, and construction professionals seeking to optimize building maintenance and management practices. The findings of this study can significantly benefit the construction and facilities management industries by providing a more reliable and advanced method for maintaining building health and safety, thereby ensuring sustainable and cost-effective building management. [ABSTRACT FROM AUTHOR]

In the ever-changing realm of the contemporary workplace, adaptability and flexibility have emerged as crucial attributes for office buildings. The method of axes system design, in conjunction with modular structures, fosters a workspace that can seamlessly adapt to the evolving needs of offices. This system embodies a comprehensive approach to office design, emphasizing the integration of four important principles: modularity, adaptability, interconnectedness, and flexibility. The modular nature of the structural axes design allows for swift and cost-effective adjustments, facilitating customer needs. The dynamism of this system ensures that office spaces are in a perpetual state of evolution, reflecting the changing dynamics of the contemporary workplace as to be shown in this paper. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore an emerging collection of smart building technologies, known as smart workplace solutions (SWS), in the context of facilities management (FM). Design/methodology/approach: This study is based on semi-structured interviews with facility managers in Finland, Norway and Sweden who have deployed SWSs in their organizations. SWS features, based on empirical data from a previous study, were also used to further analyse the interviews. Findings: It analyses the benefits that SWSs bring from the facility management point of view. It is clear that the impetus for change and for deploying SWS in the context of FM is primarily driven by cost savings related to reductions in office space. Research limitations/implications: This research has been conducted with a focus on office buildings only. However, other building types can learn from the benefits that facility managers receive in the area of user-centred smart buildings. Practical implications: SWSs are often seen as employee experience solutions that are only related to "soft" elements such as collaboration, innovation and learning. Understanding the FM business case can help make a more practical case for their deployment. Originality/value: SWSs are an emerging area, and this study has collected data from facility managers who use them daily. [ABSTRACT FROM AUTHOR]

This paper describes a two-year high-fidelity dataset for an ultra-low energy office building and living laboratory called HouseZero®. The building integrates multiple low-energy technologies, such as natural ventilation with automatic windows, ground source heat pump, and thermally activated building systems. The building's performance is continuously monitored with an extensive sensor network. The dataset consists of breakdown energy end uses, photovoltaic (PV) production, zone-level indoor environment including indoor air temperature, CO2 concentration, and relative humidity, micro-climatical conditions, building façade temperature, and detailed system operations including zone-level BTU meter, valve status, slab temperature, window/skylight opening status, heat pump, and geothermal well operations. The data can be used to support data analytics of ultra-low-energy building operations, and data-driven modeling of low-energy building systems. [ABSTRACT FROM AUTHOR]

Proper design and operation of buildings are expected to result in optimal thermal comfort and energy performance at the same time. If occupants are not satisfied with thermal conditions, corrective actions by building managers and maintenance staff may lead to elevated room temperatures with evident energy penalties. Because of complicated technical systems and control logic, it is worth studying how well the design intent has been realised in new office buildings. In this study, thermal comfort was analysed by measurements of draught, room, and supply air temperature as well as with occupant questionnaire surveys in five modern office buildings. Both short‐ and long‐term measurements were conducted to demonstrate problems in the operation and to find potential solutions for improvement. The results revealed an issue of excessive overheating during the heating season despite generally low air velocities. Radiant ceiling panels had the lowest velocities in both summer and winter, while buildings with active chilled beams showed the potential to meet Category II air velocity and temperature requirements. The building with thermally activated building systems experienced the most overheating during the heating season. Occupants were satisfied with the heating season temperatures of 23°C–25°C that can be attributed to lighter clothing (0.7 clo) instead of the standard 1.0 clo. Ventilation supply air and indoor temperature analyses indicate that elevated setpoints have been used to compensate for draught, resulting in overheating. As a measure of improvement to avoid overheating, we propose control curves for room temperature based on the outdoor running mean temperature and for supply air temperature based on the extract air temperature. [ABSTRACT FROM AUTHOR]

Architecture is a science that studies the basics and design of buildings. The concept used in architecture becomes a foundation or initial foundation used to direct what the shape of the building design that is designed in the future will be like. Therefore, the determination or selection of the concept is very important during the initial stage of development design. Zero carbon architecture is one of the many concepts used in the architectural world. The advantage that exists in the concept of Islamic architecture is that it prioritizes the characteristics of Islamic values which are then applied to the architectural design of the building that will be designed later. The application of zero carbon architecture can be applied to various types of building designs, one of which is office buildings. Work in the office that people often get dizzy when working on it also requires a comfortable, safe and clean place with a balance in the needs that building users need to do the work. This study aims to understand the application of the concept of zero carbon architecture, especially in office buildings. The method carried out in this study is qualitative with a descriptive approach to the case study of zero carbon architecture. The results obtained from this study show that the application of the concept of zero carbon architecture has several kinds of principles that can affect the good or bad form of the results of this study on case studies. This study is expected to be an overview or reference in designing buildings using the concept of zero carbon architecture, especially in office buildings. [ABSTRACT FROM AUTHOR]

In Jordanian building sector, a high percentage of cooling and heating energy is consumed. However, the occupants´ satisfaction regarding indoor thermal comfort is low as mentioned in previous studies. This study investigated the indoor thermal comfort and energy consumption at three zones in the office block before and after implementing corrective actions (CA) for enhancing thermal comfort level. Therefore, it is assumed that implementing CA will increase employees' satisfaction without increasing energy consumption, Subsequently, that improve their health, performance, and productivity. A mixed approach is used to collect data by using experimental investigations and interviews. The employees' satisfaction was evaluated in two phases: before and after the implementation of CA. The study showed that employees' satisfaction increased, while the indoor ambient temperature (IAT) decreased to become closer to thermal comfort level without increasing the energy consumption ratio. Furthermore, changing functions during the construction phase represents a major challenge that affecting occupants' thermal comfort negatively. Finally, using isolated aluminum window frame or PVC windows instead of using traditional aluminum window frame is recommended as the results showed. [ABSTRACT FROM AUTHOR]

In order to address the issues of significant energy and resource waste, low-energy management efficiency, and high building-maintenance costs in hot-summer and cold-winter regions of China, a research project was conducted on an office building located in Nantong. In this study, a data-driven golden jackal optimization (GJO)-based Long Short-Term Memory (LSTM) short-term energy-consumption prediction and optimization system is proposed. The system creates an equivalent model of the office building and employs the genetic algorithm tool Wallacei to automatically optimize and control the building's air conditioning system, thereby achieving the objective of reducing energy consumption. To validate the authenticity of the optimization scheme, unoptimized building energy consumption was predicted using a data-driven short-term energy consumption-prediction model. The actual comparison data confirmed that the reduction in energy consumption resulted from implementing the air conditioning-optimization scheme rather than external factors. The optimized building can achieve an hourly energy saving rate of 6% to 9%, with an average daily energy-saving rate reaching 8%. The entire system, therefore, enables decision-makers to swiftly assess and validate the efficacy of energy consumption-optimization programs, thereby furnishing a scientific foundation for energy management and optimization in real-world buildings. [ABSTRACT FROM AUTHOR]

An office building in Trondheim, Norway, was used as a case study to test the influence of Predictive Control (PC) for the optimization of energy use on the employees' thermal comfort. A predictive control was implemented in the Building Energy Management System (BEMS) by operating on the supply temperature of the radiator circuit. A questionnaire was given to the employees to evaluate to what extent the operation of the predictive control influenced their perceived thermal comfort. Several factors known to influence employees' satisfaction (such as office type, perceived noise level, level of control, perceived luminous environment, perceived indoor air quality, adaptation strategies, well-being) were investigated in the questionnaire. The evaluation shows that the occupants rated the perceived thermal comfort as equally good compared to the business-as-usual operation. This is an important finding toward the user acceptance of such predictive control schemes. [ABSTRACT FROM AUTHOR]

This simulation study explores the potential of a novel façade design with integrated control system comprising a dynamic photovoltaic (PV) facade integrated with dimming lighting control to enhance the work environment in office buildings and achieve energy-efficient solutions. Parametric modeling using the Grasshopper plug-in for Rhino software 7, coupled with energy simulation through the Honeybee environmental plug-in for the EnergyPlus program, are used in the methodology. The integrated control strategy was simulated to study in a single office space, utilizing the Daysim engine to assess indoor daylight quality and focusing on Daylight Factor (DF) and Daylight Glare Probability (DGP). Additionally, two artificial lighting control systems were examined for potential integration with the dynamic PV facade to minimize lighting load. The study employs the Galapagos evolutionary solver function embedded within Grasshopper to identify optimum solutions. The dynamic PV façade achieves substantial reductions in overall energy consumption, cutting it by 73% in June, 54% in July, 54.5% in August, and 52.55% in September. The results demonstrate substantial reductions in total energy consumption, with notable savings in heating and cooling due to the dynamic facade's ability to balance and control solar radiation during working hours. Moreover, the dynamic PV facade contributes to electricity generation, demonstrating its potential to improve visual comfort, decrease energy consumption, and generate electric energy through rotational adjustments and varying transparency levels. [ABSTRACT FROM AUTHOR]

Co‐working spaces have emerged as cost‐effective office space management solutions for workers from diverse industries who share space, which generates cost savings and facilitates networking opportunities. Past studies have mainly focused on needs for and benefits of co‐working spaces and range in emphasis from design preferences to potential social and economic impacts. However, limited attention has been given to the temporal clustering and geographical distribution patterns of co‐working spaces. This study examines the spatial distribution patterns of co‐working spaces establishments in terms of building floor plans. We discern the subcategory of 'co‐working office space' from the floor space and employment survey data, spanning 2007, 2012, and 2017 as collected by the City of Sydney, a municipal government in Australia. Both co‐working offices offered by conventional enterprises and co‐working providers are identified, and the spatial associations between co‐working spaces and their relationships with industry composition are analysed. Using establishment analysis, three co‐working spaces are identified: (1) dedicated co‐working enterprises providing office service and well‐design spaces; (2) conventional office rental enterprises diversifying into co‐working style office; and (3) standard enterprises converting fixed office spaces to co‐working office configurations. The spatial analysis reveals an outward diffusion of co‐working spaces from the centre of Sydney CBD, which is of importance in geographical research focused on urban, social, and economic change. [ABSTRACT FROM AUTHOR]