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Research background: With the rapid development of civil engineering, the traditional low rise building model can no longer meet the needs of urbanization, and high-rise building structure has become the future development direction. In recent years, earthquake disasters occur frequently in China, which has caused huge losses to high-rise buildings. Therefore, we must strengthen the relevant research of high-rise building structures, which can make the high-rise building structural columns meet the requirements of safety performance. Therefore, the health detection and seismic performance evaluation of high-rise buildings will be of great significance. Research method: Through static elastic-plastic evaluation, we can calculate the dissipated strain energy of the structural column, which will further obtain the damage index of the structural column and obtain relevant data. Through this calculation method, we can complete the seismic performance evaluation of high-rise buildings, which is a calculation mode different from the traditional finite element software analysis. Through static elastic-plastic analysis, the seismic performance evaluation of high-rise buildings will have higher accuracy, which will build a damage index. Therefore, this paper uses a variety of research methods, mainly literature survey and empirical analysis. Through literature analysis, this paper can fully and correctly understand the methods of health detection and seismic performance evaluation of high-rise building structures at home and abroad, which will further clarify the current research level at home and abroad. Through empirical research, this paper analyzes specific examples, which can obtain more accurate results. Conclusion: In this paper, the seismic performance of high-rise buildings is comprehensively evaluated according to the damage index value of building structural columns. The simulation results show that more ideal seismic evaluation results can be obtained. [ABSTRACT FROM AUTHOR]

Disaster Recovery (DR) providers define the main services as backup and restore, both with critical data and applications. Most clients of data and application backup, fully rely on DR's services to restore them in the disaster events. Furthermore, in the normal conditions, DR provider backs up data, sometimes with application in routine or regular basis. Thus, providers should deliver the services in sophisticated way through several Key Performance Indicators (KPIs). In this paper, development of KPIs is focused on performance and assurance, which a laboratory testing simulates backup and restore services. On the other hand, experimental data such as network and system parameters are analysed to build performance and assurance framework. Meanwhile, interdependence among each performance and assurance of DRCs was used to build a relationship model. It is acted as a part of service level agreement, that a DR providers can present services dynamically. They also should adapt the computing resources to deliver services to meet SLA (Service Level Agreement) in flexible strategy. In turn, they can negotiate SLA with the customers based on this new approach. [ABSTRACT FROM AUTHOR]

The construction sector is responsible for around 39% of global greenhouse gas emissions, with building envelopes playing a significant role in this carbon footprint. This is particularly relevant for building facades with large window-to-wall ratios (WWR), because higher proportions of glass increase both operational and embodied carbon. In light of the contemporary demand for such glazed envelopes, there is an emerging legislative trend that measures not only operational carbon, but also embodied via utilizing life-cycle assessment tools (LCA). To this effect, there is a great demand for techniques that can effectively lower the former carbon without increasing the latter. To contribute to this effort, this paper presents a whole LCA across seven cities for standard and advanced glazing solutions, including Water-Filled Glass (WFG). WFG is a novel technology that utilizes water in the cavity of insulated glass units (IGU), to improve thermal comfort, energy and acoustic performance of buildings. The paper utilizes energy simulation modelling through TRNSYS, and provides a comparative analysis of different glazing techniques. The significance of this paper is that a comprehensive cradle-to-grave LCA analysis of standard and advanced glass techniques is presented here for the first time, across all major Köppen-Geiger climates. The results show that WFG presents considerable carbon savings against all other options e.g., 31–53% compared to double glass, underlining the possibility of reducing operational and embodied carbon simultaneously. A second novel outcome of the paper is introducing the Glass Viability Index (GVI) for the first time, which presents the 'carbon payback' period required to offset an embodied carbon increase with operational savings. This is because the short lifespan of glass makes embodied carbon a large driver in LCA, and as such the prioritisation of operational carbon when selecting a technique can lead to a unsustainable practice. • Glass options should be ranked on LCA instead of just operational energy. • Paper presents life-cycle carbon for seven glass options across all major climates. • Viability of advanced glass options is affected by their high embodied carbon. • Glass option ranking depends on length of representative study period (RSP). • Glass Viability Index is created, which ranks carbon impact independently of RSP. [ABSTRACT FROM AUTHOR]

Due to the irreversibility of building structures in the construction process, unreasonable construction methods are likely to cause economic losses and great negative social impacts. Therefore, the study of scientific and efficient intelligent construction methods for building structures has become a research hotspot in recent years, mainly including intelligent building design, construction control and safety analysis methods. Therefore, it is very meaningful and necessary to carry out research on intelligent construction technology based on BIM technology. By applying BIM technology to the process of intelligent construction of structures, this paper intends to achieve six major objectives such as building performance analysis and parametric design of structures, and independently develop a BIM construction process management platform, which combines construction progress, quality, safety, cost and green construction through BIM technology for information management of projects, making it more convenient for owners and construction unit staff to software application, thus greatly improving the communication and use efficiency, and providing important guidance for the construction process control and progress control of the project. [ABSTRACT FROM AUTHOR]

The EU has set itself demanding objectives to achieve complete decarbonisation by 2050. The building sector plays an important role for this purpose, hence monitoring its progress towards decarbonisation is essential to identify measures that work and to readjust policies when necessary. However, collecting information to monitor the building sector is a complex task due to the scarcity and low quality of available data. The European digital building logbook (DBL) has great potential in this regard because it allows the collection of data at the building scale, which could be combined at a national level. Thus, this paper proposes a new functionality for the DBL -as an enabler for the collection of data for the assessment of the progress of the main EU policy objectives related to the building sector decarbonisation-, and it evaluates the potential of the DBL for it. To do so, the main policy objectives were associated to a set of progress indicators –mandatory and optional- and matched to DBL indicators. Mandatory indicators are for all Member States and they have been included in the 2023 amended version of the proposal for the Energy Performance of Buildings Directive recast. Optional indicators are considered country-specific in this paper and are sourced from various literature references. Here we have studied the optional progress indicators for the case of Spain. Results show that the DBL has great potential to contribute to the collection of more than half of the mandatory indicators and a very high share of the optional ones for Spain. • Monitoring the decarbonisation progress of national building sectors is crucial. • Mandatory and optional indicators are needed to monitor buildings decarbonisation. • The DBL has great potential for monitoring national building stocks decarbonisation. • The DBL will provide the majority of the decarbonisation progress indicators. [ABSTRACT FROM AUTHOR]

As passive control technology advances and building forms become increasingly diversified, traditional axial and shear dampers may no longer meet diverse structural application requirements. This paper introduces a novel rotational metallic damper, i.e. rotational steel rod damper (RSRD), as an alternative engineering solution. The RSRD comprises three steel plates rotating around a central pin and four low yield point steel rods as energy dissipators. The input seismic energy can be dissipated in the form of plastic rotation of the RSRD. Initially, the structural form, working mechanism, and design approach of the RSRD are presented. Subsequent cyclic quasi-static tests on two RSRD specimens under varied loading protocols demonstrated satisfactory energy dissipation capacity, with an equivalent viscous damping ratio exceeding 0.47. The cyclic behavior, rotational strength, and cumulative plastic deformation capacity are discussed following the tests. A finite element (FE) analysis on the RSRD using ABAQUS is conducted to further investigate its performance. A comparison between the hysteretic behavior and failure mode of tested and simulated results is presented to validate the FE model. Additionally, two new structural forms, with linear and arc-shaped weakening on the steel rod, are simulated and compared with the original. FE results indicate that the arc-shaped weakening of the steel rod effectively avoids plastic strain concentration, showcasing superior low-cycle-fatigue performance. Finally, nonlinear time history analyses on two RC frames, with and without RSRD, reveal that structural and non-structural damage can be controlled under the maximum considered earthquake (MCE) by utilizing RSRDs. • The rotational steel rod damper was proposed to enhance the seismic performance of buildings. • Cyclic behavior of the rotational steel rod damper was investigated through quasi-static tests and numerical simulations. • The proposed damper exhibits superior energy dissipation capacity with an equivalent viscous damping ratio exceeding 0.47. • Nonlinear response history analysis on two RC frames with and without the dampers was performed. [ABSTRACT FROM AUTHOR]

Buildings are typically integrated with multiple distributed energy resources (DERs), enabling them to act as building prosumers engaged in both energy production and consumption. Peer-to-peer (P2P) energy trading among building prosumers is crucial to improve their benefits. However, further exploration is required to balance the benefits between building prosumers and the system operator (e.g., the integrated community energy system (ICES) operator) since they are different entities. In this context, this paper proposes a comprehensive network charge and energy sale pricing scheme for the ICES operator on heterogeneous building prosumers with P2P multi-energy trading. The interaction between the ICES operator and building prosumers is modelled as a bi-level optimization problem that belongs to the hierarchical structure, while considering the heterogeneity of thermal insulation performance of buildings. At the upper level, the ICES operator optimizes the electricity/heat network charge prices and electricity/heat sale prices to maximize its revenue. At the lower level, building prosumers with a parallel structure optimize the schedules including P2P multi-energy trading and buildings' heating loads to minimize their costs. Furthermore, to address the bi-level optimization problem with parallel and hierarchical coupling structures, an accelerated asynchronous distributed algorithm based on alternating direction method of multipliers (ADMM) is developed, integrating a warm start strategy and a dual update accelerated iteration strategy for further improving computational efficiency. Finally, case studies demonstrate that the proposed scheme can effectively benefit both the ICES operator and building prosumers in P2P multi-energy trading at the same time. Meanwhile, the feasibility and effectiveness of the proposed algorithm are validated. • An optimal pricing scheme for ICES operator on building prosumers is proposed. • A bi-level optimization is proposed for ICES operator and prosumers with P2P. • An accelerated asynchronous distributed algorithm based on ADMM is developed. • Benefits of ICES operator and prosumers through several scenarios are analyzed. [ABSTRACT FROM AUTHOR]

• Switchable insulation is an effective means of regulating heat through envelopes. • Current research on switchable insulation is fragmented across multiple domains. • We review existing technologies systematically and propose a classification system. • We assess their performance and improvement opportunities for building applications. Switchable thermal insulation, in the form of an opaque panel that alternates between thermally conductive and insulated states, can be an effective means of regulating the thermal environment by selectively transferring heat between the indoor and outdoor environments. Pioneering work has been undertaken by researchers to develop switchable insulation technologies intended for applications in the built environment, automotive, and aerospace, where conventional space heating and cooling technologies are either too bulky or too energy consuming to meet design requirements. Switchable insulation technologies are in their infancy and the emerging research on this topic is unstructured and fragmented across disparate application sectors and very few of the adaptive insulation concepts and technologies are actively being pursued by the buildings research community. The aim of this paper is therefore to advance the understanding of switchable insulation for possible applications in the building envelope, by reviewing and classifying the existing technologies systematically, with a particular focus on their working principles, theoretical performance and improvement opportunities. The paper provides a qualitative and quantitative assessment of the most promising switchable insulation technologies for building envelopes and identifies the opportunities for further research in each of the technologies. [ABSTRACT FROM AUTHOR]

Several studies have demonstrated the capability of data-driven modelling based on on-site measurements to characterise the thermal performance of building envelopes. Currently, such methods include steady-state and dynamic heating experiments and have mainly been applied to scale models and unoccupied test buildings. Nonetheless, it is proposed to upscale these concepts to characterise the thermal performance of in-use buildings based on on-board monitoring (OBM) devices which gather long-term operational data (e.g., room temperatures, gas and electricity consumption...). It remains, however, to be proven whether in-use data could be a cost-effective, practical and reliable alternative for the dedicated tests whose more intrusive measurements require on-site inspections. Furthermore, it is presently unclear what the optimal experimental design of the OBM would be and which data analysis methods would be adequate. This paper presents a first step in bridging this knowledge gap, by using on-board monitoring data to characterise the overall heat loss coefficient (HLC) [W/K] of an occupied, well-insulated single-family house in the UK. With the aid of a detailed building physical framework and specifically selected data subsets a sensitivity analysis is carried out to analyse the impact of the measurement set-up, the duration of the measurement campaign and the applied data analysis method. Although the exact HLC of the building is unknown and no absolute errors could hence be calculated, this paper provides a new understanding of the decisions that have to be made during the process from design of experiment to data analysis. It is demonstrated that such judgements can lead to differences in the mean HLC estimate of up to 89.5%. [ABSTRACT FROM AUTHOR]

• Affordable and adaptable VIP based internal and external retrofitting solutions. • Implementation of VIP based integral retrofitting solutions in two tertiary buildings. • Space heating energy saving analysis before and after VIP based retrofit. • Envelope heat loss coefficient reduction analysis before and after retrofitting. Vacuum insulation panels (VIPs) represent a huge opportunity to achieve nearly zero energy buildings, especially in the retrofitting of existing buildings. VIPs can be applied in conjunction with façade cladding elements, considerably reducing the heat losses or gains from the building by means of very slim wall construction systems or retrofit solutions. However, the fact that VIPs cannot be cut on-site, can be easily damaged during their handling, installation and use and have an envelope that can cause thermal bridging in the junction between panels or when combined with other materials, has hindered their penetration in the construction market. This paper presents two innovative façade retrofitting solutions, a rear ventilated façade and a stud mounted internal solution, that have tackled all these issues and provide thermal transmittances of 0.28 and 0.14 W/m2 K in relatively slim insulation systems of 10 cm widths. Solutions have been installed on the entire façade of two existing buildings located in Bilbao (Spain) and Malmö (Sweden) subjected to an integral rehabilitation process, covering 2100 m2. Buildings energy use have been monitored before and after the renovation, showing energy cuts of around 35% from pre-intervention status. This paper presents the lessons learnt during the design and installation process of the vacuum insulation integrating solutions in the façade of two existing buildings and the thermal performance results achieved after their retrofitting. [ABSTRACT FROM AUTHOR]

Highlights • Presented a model-predictive control strategy for radiant floor systems. • Developed data-driven building models with solid prediction accuracy. • Deployed a robust optimization formulation that achieves good solution quality. • Implemented the developed smart operation strategy in an actual building. • Presented a realistic evaluation and demonstrated significant energy savings. Abstract This paper introduces a smart operation strategy based on model predictive control (MPC) to optimize the performance of hydronic radiant floor systems in office buildings and presents results from its implementation in an actual building. Our MPC approach uses dynamic estimates and predictions of zone loads and temperatures, outdoor weather conditions, and HVAC system models to minimize energy consumption and cost while meeting equipment and thermal comfort constraints. It includes data-driven building models estimated and validated using data from an actual building, and deploys an optimizer based on constraint linear/quadratic programming with hard comfort bounds that yields a global minimum with predicted exogenous disturbances. The MPC results show 34% cost savings compared to baseline feedback control during the cooling season and 16% energy use reduction during the heating season. Also, the radiant floor system with the predictive controller shows 29–50% energy savings when compared with a baseline air delivery system serving two identical thermal zones located in the same building. [ABSTRACT FROM AUTHOR]

• Application of fractal geometry in damage quantification of cracking and crushing of rectangular RC shear walls is presented. • A database including 236 images of 72 concrete shear walls at various drift ratios are collected and the crack pattern is extracted. • Predictive equations to assess the damage of RC shear walls using the crack pattern. • Fragility curves are proposed directly based on the parameters of crack patterns. • Fragility curves subsequently provide an estimation of the loss, repair cost and time. The purpose of this paper is to quantify the extent of damage of rectangular reinforced concrete shear walls after an earthquake using surface crack patterns. One of the most important tasks after an earthquake is to assess the safety and classify the performance level of buildings. This assessment is usually performed by visual inspection that is prone to significant errors. In this research, an extensive database on the images of damaged rectangular reinforced concrete shear walls is collected from the literature. This database includes more than 200 images from experimental quasi-static cyclic tests. Using the concept of fractal geometry, several probabilistic models are developed by extracting and regenerating the surface crack patterns of the collected walls. These models can estimate the peak drift ratio that the structure has experienced. The peak drift ratio predicted by the proposed models of this paper can be used to calculate the probability of exceedance of different damage states using existing fragility models. Furthermore, new fragility models are directly developed using the images of the damaged walls of the collected database. The proposed fragility curves calculate the probability of exceedance of damage states using the crack pattern of the damaged shear walls and consequently provide an estimation of the loss, repair cost, and repair time of the walls. [ABSTRACT FROM AUTHOR]

The application of hysteretic damper has gained major attention in seismic resistant design of buildings. It provides an efficient and cost-effective solution to reduce the level of damage induced on the building due to seismic excitations. The efficiency of the damper is influenced by parameters such as yield strength, yield displacement and brace-damper assembly system stiffness. The premise of this paper is to investigate the effect of the uncertainty associated with the hysteretic damper design parameters on the probabilistic seismic performance of steel buildings. Two steel buildings which are designed in accordance with the European Standard design code are evaluated. The uncertainties associated with the damper design parameters are incorporated using the Optimised Latin Hypercube sampling method for different confidence levels. The building response is obtained by conducting nonlinear time history analyses in OpenSEES. The annual frequency of exceeding a damage limit state, which is quantified by integrating the seismic fragility curves and hazard curves, is computed for the steel buildings with and without consideration of the design parameter uncertainties. • This paper provides a detail seismic performance assessment of steel building with hysteretic steel damper. • The effect of uncertainty in damper parameters on seismic demand on the building was quantified using probabilistic approach. • Seismic fragility curves were developed for steel buildings with and without dampers and variability in drift hazard curves were derived. • Uncertainty of damper properties affect the annual probability of exceedance significantly for immediate occupancy limit state up to 24%. • The effect of damper parameter uncertainty is less conclusive for variability up to 10%. [ABSTRACT FROM AUTHOR]

Abstract Digitalised models can play a key role in the management of building life-cycle. This paper focuses on the challenges connected to the operation phase of buildings, when the adoption of BIM can make information retrieval and management easier and more efficient. More specifically, a BIM-based cyber-physical system for the automated monitoring of buildings during their regular operation is proposed and tested by means of a customised simulator. The system automatically works out key performance indicators based on the overall throughput effectiveness (OTE) metric, assessing both the overall efficiency and the efficiency of every sub-system integrated in the building. Thus, assessments of the contribution of every sub-system to the operation of the building are performed in real-time. In addition, the metric proposed can help manage multi-objective real-time control. The system is self-reconfigurable thanks to the self-similarity assumption of the computational structure that is designed as a holarchy of holonic systems. The first application reported in this paper shows that when intelligence is embedded at both lower and higher levels, it is possible to generate information that is then used to update the digital model, developed as a BIM. As a result, the digital model becomes the mirror of the physical system and stores the actual performances recorded by the building to support facility managers in making decisions. Highlights • A cyber-physical system (CPS) for the automated assessment of building performances and potential improvements in their life-cycle was developed • The CPS integrates the OTE/OEE approach and self-configuration and adaptation capabilities thanks to its holonic architecture • The CPS is directly linked to the building information model (BIM) to support facility managers in the management and long-term improvement of the operational phase of the building [ABSTRACT FROM AUTHOR]

The design of a building is a collaborative process among experts from multiple disciplines. Using Building Information Modeling (BIM), a model is developed through multiple refinement stages to satisfy various design and engineering requirements. Such refinements of geometric and semantic information are described as levels of development (LOD). Thus far, there is no method to explicitly define an LOD's requirements nor to precisely specify the uncertainties involved. Furthermore, despite the insufficient information in the early design stages, a BIM model appears precise and certain, which can lead to false assumptions and model evaluations, for example, in the case of energy efficiency calculations or structural analyses. Hence, this paper presents a multi-LOD meta-model to explicitly describe an LOD's requirements, incorporating the potential fuzziness of both, geometric and semantic information of individual elements. The explicitly defined fuzziness can be taken into account when applying simulations or analyses for assessing the performance of different building design variants. To support the continuous elaboration of a building from the conceptual to the detailed design stages, the multi-LOD model makes it possible to ensure the consistency of the geometric and semantic information as well as the topological coherence across the different LODs. The feasibility of the approach is demonstrated by its prototypical implementation as a web-server and user-interface, providing a means for managing and checking the exchange requirements both at the meta-level and for concrete building model instances. The paper is concluded with a case study of a real-world construction project that demonstrates the use of the meta-model to support model analysis and the decision-making process. [ABSTRACT FROM AUTHOR]

Abstract Recently developed generation of high-performance skins greatly leads to the emersion of innovative manufactures integrating real-time environmental response, enhanced materials, dynamic automation with built in microprocessors, wireless sensors and actuators, and design-for-manufacture techniques. This application has basically alter the thinking way of architects in the early design stages of the building with a shifting in importance from form to performance, from structure to envelope. In the field of high-performance buildings, the envelope begins to be the setting of research and development. The aim of the paper is to discuss the design of three strategies used in constructing adaptive building envelopes of multistory buildings, integrating improved energy performance and architectural innovation, in order to Control the physical environmental factors (heat, light, sounds), as well as improving occupants' comfort. Finally, three case studies are analyzed to unveil the implementation of these strategies on constructing structures and study their effects on the building energy savings. Scope and objective The objective of this paper is to illustrate and discuss new conceptual ways of designing adaptive building envelopes of multistory structures that respond to environmental changes in the surrounding climate of different places in the world, and how the usage of such adaptive envelopes can help reduce the energy consumption of the building. Methodology The literature survey will first discuss the characteristics and properties of high performance facades. After that, the paper present and analyze existing examples and ideas of adaptive envelopes, gaining an overall understanding of the concept of three adaptive building envelopes. In addition, at the same time develop knowledge of the materials commonly used and how they perform. Finally, three case studies are presented to analyze the implementation of the three adaptive envelopes strategies and observe their effects on the building energy savings. [ABSTRACT FROM AUTHOR]

Highlights • To our knowledge this is the first journal paper to include in-depth thematic analysis of expert interviews regarding the use of building performance simulation in Australia, with a particular focus on lower quality office buildings. • In this paper, the typical simulation and upgrade process operating in practice in Australia is compared with a previously outlined optimal strategy, and a 'Revised Systematic Approach' to sustainable building retrofits is proposed. • The thematic analysis of interview responses identified many of the drivers and barriers influencing the user of building simulation tools. • Several practices employed by practitioners that are likely to greatly increase the uncertainty associated with simulation results were identified. • The lack of reliable and accurate data was highlighted as a key issue facing this sector, and the implications of the uncertainty introduced by the necessary use of assumptions, particularly concerning innovative financing initiatives, is discussed. Abstract Building Performance Simulation (BPS) has become an important tool in the upgrading of the existing commercial building stock. It allows a user to predict energy savings from upgrades, and thereby optimise the energy, financial or other benefits of an energy efficiency upgrade. The current paper presents the findings from a qualitative investigation into the use of BPS in the Australian commercial building retrofitting industry. The interviews had a particular focus on challenges for lower quality (known as secondary grade or mid-tier) office buildings. Twelve semi-structured interviews were undertaken with stakeholders in the building energy retrofitting industry, including consultants, government administrators and building managers. Thematic analysis of the interview data revealed numerous challenges for BPS users, primarily related to the lack of reliable, accessible data regarding building operations and energy use in Australia. The poor data availability encouraged the use of simulation to inform decisions but required the modeller to use assumptions and heuristics to develop the model. This, in turn, necessitated a reliance on the expert knowledge of the simulation user, and made the interrogation of a building model by a third party problematic. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • New method for generating and using BIM for energy retrofitting of old buildings. • The proposed method comprises 3 interrelated tasks: Anamnesis, Diagnosis, Therapy. • Templates help to fill in modeling gaps in the needed system identification cycle. • A variation model enables the use of templates for retrofitting design variants. • The developed framework can be reused in other domains such as bridge retrofitting. Abstract Building Information Modeling (BIM) is rapidly advancing as an efficient new approach to cooperative building design and construction. However, BIM methodology is still mainly developed and applied for new building projects. The strong societal needs to improve the quality and the overall performance of the existing building stock, especially with regard to energy use, are yet insufficiently supported by BIM. In this paper we propose a structured approach towards the creation of a building information model of an existing building and its use for the purpose of retrofitting or renovation, based on the standard IFC specification (ISO 16739). It implies a process we define as BIMification. This process undergoes two major stages: (1) Anamnesis, dedicated to the survey and collection of facts about the building, and (2) Diagnosis, dedicated to the analysis and interpretation of the collected facts to obtain the necessary understanding of the building and its performance and prepare for the retrofitting design. The paper outlines the broader research aim that triggered the development of the suggested approach and presents the overall concept and methodology, the ICT platform under implementation and the current state of the work. Discussed are also the scope of the approach, envisaged perspectives and further development efforts. [ABSTRACT FROM AUTHOR]

Post-occupancy evaluation (POE) is necessary to evaluate the building's performance in order to formulate future design development after its utilisation. This paper evaluates indoor thermal performance, sound pressure level, and illuminance in a multipurpose auditorium by combining zoning and activity-based POE. The evaluation was done in three activities: (A) student graduation, (B) theater performance, and (C) public lecture with different types of clothing preferences. Three different zones were used to define the precise location of the building improvement. Field measurements were taken for thermal performance, including Operative Temperature (T op), Humidity (Rh), Sound Pressure Level (dB), and Illuminance (lux). User perceptions were collected from 171 respondents (89 men and 82 women). The field measurement showed that average operative temperature varied across the activities with 26.15–25.68 °C, 25.47–24.95 °C, and 23.74–23.17 °C on activities A, B, and C, respectively. Activity A's (1 clo) room's operative temperature showed that 65% of data are outside the ASHRAE standard, indicating that the room condition is unsuitable for 1 clo. Activity A's TSV shows a slightly warm sensation (0.21 to 0.93) and is still in the comfort range. With the same clothing value (0.6 clo), Activity B's T op indicates a more suitable condition than Activity C's. The average TSV in Activity B indicates slightly cool (-0.54 to −0.90), with the lowest TSV found in Activity C (-1.09 to −1.41). Although TSV positively correlates with PMV , Thermal Preference (TP) revealed that the occupant expects cooler conditions in all activities. Sound pressure level and illuminance performed well according to all activities. This paper recommends chiller setting adjustment in the multipurpose auditorium based on activity characteristics. Combined POE based on zoning and activity can indicate which aspects of the auditorium need to be improved. [ABSTRACT FROM AUTHOR]

This paper analyzes electricity use in buildings and explores key research questions related to assessing, rating, labeling, and benchmarking building energy use. The analysis reviews annual Energy Use Intensity (EUI) data from 3060 fully electric-powered buildings across six categories: residential, educational, offices, hospitals, hotels and restaurants, and wholesale and retail trade services. One-fifth of the analyzed buildings is derived from an energy dataset that offers a higher time-scale resolution, providing more detailed insights into energy usage patterns. The analysis employs various factors, including the seasonal variation factor (SVF), daily variation factor (DVF), monthly factor (M f), and hourly factor (H f), to gain a detailed understanding of actual energy usage at different time scales. The findings indicate that electricity use is less sensitive to seasonal variations than other energy carriers that provide heating and cooling. The paper provides hourly and monthly peak load percentages (PPL), which can indirectly assist in assessing hourly schedules for building energy performance simulations. The monthly energy use pattern varies between building categories, with high-energy months alternating between winter and summer. For non-residential buildings, high-energy hours correspond directly to the daytime, while for residential buildings, there is a shift towards the evening, and the daily amplitude is lower. Furthermore, the analysis of daily and monthly variability of heating energy carriers, even if non-electric, sheds light on the implications of electrification for these loads. • The study evaluates annual electricity data from 3060 fully electric-powered buildings. • Median EUIs are meaningful energy performance benchmarks by building category. • Residential and educational buildings exhibit EUIs of 90-120 kW h/m2. • Offices and hospitals demonstrate EUIs of 160-170 kW h/m2. • Monthly and hourly factors establish energy benchmarks for finer time resolution. [ABSTRACT FROM AUTHOR]

Building performance simulation is a powerful tool applied both in research and for building design including heating, ventilation, and air-conditioning systems. Several research studies have used this tool to investigate the potential of energy savings measures for swimming facilities. However, in these facilities the technical complexity is a considerable challenge in modelling since many complex phenomena occur in the various sub-systems. The building industry traditionally plans and design these complex buildings by heuristic rules of thumb, and these empirical design rules may lead to significant differences between real and predicted performance. Therefore, it's important to develop simplified models with acceptable accuracy for simulation-based design of swimming facilities. The scientific literature introduces different simplifications for the air handling unit modelling, but the impact of these simplifications is hardly analyzed. Therefore, the paper investigates the model complexity of the air handling unit in a Norwegian swimming facility by comparing a novel simplified model and a detailed model which serves as a digital replica of a real unit. The simplified decoupled model is found to have an acceptable accuracy for early-stage design, bearing in mind the overall uncertainty at this design stage. However, when carrying out a detailed investigation of a swimming facility, the detailed model should be applied, since this complex heuristic rule-based model, is taking into account phenomena like thermal-coupling effects between the swimming pool and the air handling unit and the control errors of the real internal controller. In conclusion, the paper derives useful guidelines for building performance simulation design of air handling unit, which is the main energy-intensive component in indoor swimming pool facilities. [ABSTRACT FROM AUTHOR]

[Display omitted] • Discusses the concept of building performance simulation versus new digital trends. • Reviews Artificial Intelligence, Machine Learning, Digital Twins, Cyber-Physical Systems, Internet of Things, Data Mining. • Explores common notions about differences, similarities, strengths and limitations of each concept. • Reviews emerging work on the interface between these concepts. • New concepts enjoy traction and energize the building performance research area. In an increasingly digital world, there are fast-paced developments in fields such as Artificial Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the Internet of Things. This paper reviews and discusses how these new emerging areas relate to the traditional domain of building performance simulation. It explores the boundaries between building simulation and these other fields in order to identify conceptual differences and similarities, strengths and limitations of each of these areas. The paper critiques common notions about these new domains and how they relate to building simulation, reviewing how the field of building performance may evolve and benefit from the new developments. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

• A set of theoretical framework of building seismic performance evaluation has been formed, and the automatic evaluation of actual seismic performance of buildings has been realized. • This framework meets the evaluation requirements of various performance indicators in the existing FEMA P-58, and can make rapid and accurate predictions, which greatly improves the evaluation efficiency and quality, and provides fundamental support for the rapid assessment and prediction of regional and city-level building groups. • A set of discrete size variable multi-objective optimization model is proposed. The multi-objective optimization model proposed in this paper establishes a one-to-one correspondence between the design scheme and the two major costs from the perspective of structural size variables, which realizes the micro-level optimization design and improves the optimization level. Seismic loss prediction and performance assessment for buildings have already been hot spots for resilience after earthquakes with the emergence of the concepts of digital twins. However, because a large amount of multisource heterogeneous data and a real-time accurate prediction model are required to implement the process, the popularization and implementation of these technologies are hampered. Based on performance-based seismic design (PBSD) theory, this study introduces BIM and ontology and other emerging technologies to carry out methodology research on intelligent earthquake damage prediction and seismic performance evaluation for individual buildings. First, based on FEMA P-58 (Seismic Performance Assessment of Buildings), this paper uses BIM technology to integrate and transmit component-level engineering information. Ontology method is used to express the assessment content and logic, and a multidimensional semantic ontology model based on IFC is proposed to form the linked data foundation to organize, store, associate and interact the multisource heterogeneous data required for assessment in a unified way to realize the semi-automated seismic performance assessment for individual RC frame building. On this basis, the seismic optimization design under the guidance of the "investment - benefit" criterion is regarded as the problem of seeking the balance between the initial construction cost and the expectation of seismic loss. The multi-objective genetic algorithm (NSGA-II) is used to realize the optimization iteration at the component level. According to the results of the case study, the new method in this paper significantly improves the quality of seismic performance assessment and seismic design optimization. [ABSTRACT FROM AUTHOR]

Despite the variety of landscape software available, new tools keep being developed in order to improve the existing analytical capabilities. Scripts, packages, or standalone software are built to enhance performance, add features or fulfil specific needs. This paper introduces LDT4QGIS, an open-source tool built exclusively to operationalize the Landscape Dynamics Typology method. LDT4QGIS is a Python-based tool developed to assess the landscape composition and configuration and to classify different land cover / land-use changes using QGIS. By combining the metrics 'area' and 'number of patches', it is possible to define different patterns of landscape changes (types of dynamics). The tool, which uses vectorial binary landscapes, allows squares or irregular polygons to be used as analytical units. The end goal of the procedure is to assign a type of dynamic to each analytical unit. To do this, metrics and their variations are calculated and then combined through a series of queries and selections that operationalize the type of dynamic assignment. LDT4QGIS has additional functionalities that are computed at the class level; they are related to the calculation and spatially explicit representation of gained and lost areas, as well as perforations in the land cover under study. Depending on what functionalities are being used, two or three analytical moments are required as inputs. The outputs produced by LDT4QGIS can be used in landscape assessment procedures and therefore can be helpful to decision-makers, allowing them to better understand and anticipate the consequences of policies related to the use of the land. LDT4QGIS will be updated regularly and improved whenever we develop a new functionality, but the real strength of LDT4QGIS is that it is free and open-source, and it can be adapted by each user according to their own needs. This paper describes LDT4QGIS and includes three illustrative practical examples to demonstrate the variety of scripts and outputs. The first case study concerns the dynamics of grasslands in Slovenia, and it uses two analytical moments and squares as analytical units. The second example focuses on olive groves in Portugal; it uses administrative boundaries as analytical units and three analytical moments. The last example concerns forests in Germany and showcases additional features like the detection of gained areas, lost areas, and the associated dynamics. • We developed LDT4QGIS, a free and open-source landscape analysis tool for QGIS. • LDT4QGIS identifies types of dynamics based on landscape metrics' variations. • The outputs, filled attribute tables and maps, are easy to interpret. • LDT4QGIS will be continuously updated and improved. [ABSTRACT FROM AUTHOR]

Thermochromic technology has exciting potential for building applications as it passively modulates its solar transmittance. Existing smart window technologies lead to unnecessary increases in lighting energy consumption during spectral modulation and limited application scenarios. Therefore, spectrally selective modulation is a key direction to improve the performance of smart windows. In this paper, a three-story office building is established in EnergyPlus, and how the characteristic parameters and spectral modulation properties affect the effectiveness of thermochromic windows are thoroughly investigated through actual spectra and hypothetical split-band modulation spectra. A comprehensive human-centered evaluation system is proposed, multiple light zones are divided to investigate in detail the light and thermal environment and comfort performance of office spaces with different orientations of near-window areas and verify the energy-saving effect. The impact of thermochromic adaptive windows on building part loads and equipment efficiency is discussed and the matching of this passive technology with renewable photovoltaics is briefly mentioned. Based on the two-way synergistic perspective of materials and buildings, the results inform the application of smart windows in specific scenarios, throwing light on more cross-cutting research. • Split-band modulation is an idea for improving the performance of smart windows. • Evaluate the environment and comfort in different oriented areas near the window. • Discuss the part-load characterization and PV matching. [ABSTRACT FROM AUTHOR]

Commercial buildings during operation are dynamic environments where changes to control strategies and space usage regularly occur. As a result of these and other issues, a performance gap between design intent and actual building performance emerges. This paper seeks to address the operational performance gap and enhance operational building performance through statistically-based fault detection. Additionally, this paper seeks to remedy the knowledge gap building managers face in the identification of key building faults based on minimal quantities and streams of time-series building data. A new methodology is presented that incorporates simulation and breakout detection to address these issues. Residual based exponentially weighted moving average (EWMA) charts and Shewhart charts are compared against a breakout detection algorithm to identify shifts or faults in building performance data. Artificial faults are introduced into the measured time-series data to test the validity of the chosen statistical techniques. Statistical metric sensitivity and precision are calculated to quantify the performance of the new methodology. A summary of results demonstrate that the breakout detection algorithm was the most effective method in detecting meaningful faults in building performance data, followed by residual based EWMA and Shewhart models. [ABSTRACT FROM AUTHOR]

The need for improved building performance is global and has led to numerous international collaborations. Since 2000, the International Energy Agency (IEA) Energy in Buildings and Communities Program (EBC, formerly ECBCS ) has completed two building commissioning research annexes, recognizing the role of the building commissioning process in meeting energy conservation goals. Annex 40 established a common understanding of the commissioning process and initiated research that became the basis for the development of national guidelines and automated tools. Subsequently, Annex 47 focused on advancing the use of technology in commissioning and the work developed and ideas exchanged in Annex 47 were foundational in enabling numerous positive impacts internationally. This paper describes research results from these annexes 1 1 Certain commercial entities, equipment, or materials may be identified in this document in order to describe an experimental procedure or concept adequately. Such identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose. and discusses the impact of both in four areas: 1) commissioning support software tools, 2) cost-benefit methodology, 3) guidelines and standards, and 4) industry associations and research conferences. The paper concludes with a discussion of current commissioning industry research and policy needs. [ABSTRACT FROM AUTHOR]

Although contemporary architectural design education adopts the parametric design approach, which involves complex iterations between the arrangement of form components and building performance, this method limits students' exploration of the optimal matches between generated form and the behaviours of prospective users. Therefore, as a solution, this study hypothesises the effects of human behaviour simulation on students' exploration of user-centric values in the parametric design process. This paper compares the self-evaluation scores of 90 undergraduate students before and after simulation. Data were collected during an authentic digital design course that examined shopfront façade prototypes. Statistical analysis and interpretation indicate that simulation better facilitates students' search for matches between initially value-isolated forms, created using a parametric design tool, and useful user-centric values. However, simulation is not relevant for discovering unexpected forms. This study addresses the unknown affordances in simulation when assigning user-related value to form generation that lacks value. • The study investigates the impact of human behaviour simulation on enhancing user-centric values in parametric design. • In a digital design course, students engaged in shopfront façade design using a parametric tool and a simulation platform. • An empirical quasi-experiment was adopted to compare students' self-assessments with and without using the simulation. • The simulation promoted the search for usefulness and user-centric values, but not for original form and social interaction. • The simulation is interpreted to offer an iterative approach, error detection, and value speculation in parametric design. [ABSTRACT FROM AUTHOR]

The continuous improvement of the energy and sustainability performances of buildings is stimulated by mandatory rules, economic incentives and voluntary sustainability pathway of which energy efficiency is one of the most important components. The tools to evaluate the energy, sustainability, automation and energy metering performances of buildings, to check the status and lead the investments, are often complex, slow, expensive and related to the specific Countries, making difficult the job for the facility management departments of national or international organizations in EU. The present paper wants to give a contribute to existing literature by providing a new energy, sustainability, automation and energy metering label system to quickly, simply and economically evaluate the performances of office buildings in Europe. This tool has been tested on a case study, a research center of the European Space Agency (ESA-ESRIN) in Rome, Italy. The results of the test show that the tool has been successfully applied on the buildings of the research center using the data provided by the facility management department of ESA-ESRIN and the energy audit of the center. The labels can correctly represent the state of the buildings in a more cost-effective way if compared to the national energy certification and to international sustainability protocols. This study provides the facility management departments of public and private companies in EU - especially if they manage buildings in different EU nations - a reliable tool to quicky evaluate the energy, sustainability, automation and energy metering performances of their buildings. [Display omitted] • Energy and sustainability performances of buildings are evaluated through protocols. • Facility managers need quick tools: the proposed labeling tool for offices can help. • It labels energy, sustainability, automation and energy metering performances. • This tool considers Trans-national European Union differences (primary energy, CO 2). • The first application has been on the European Space Agency Italian research center. [ABSTRACT FROM AUTHOR]

Vibration control technologies have been widely implemented for the seismic retrofitting of buildings in high seismic regions. Among various vibration control devices, the tuned viscous mass damper (TVMD) has proven effective in mitigating both lateral inter-story drifts and floor accelerations. This paper presents the seismic design and performance assessment of a retrofitted structure located in a highly seismic area. The existing masonry building is being retrofitted into a steel frame-jacketed masonry wall interacting structural system installed with TVMDs. A simplified iterative design process is proposed for the tuning design of TVMDs used in the retrofitted structure, which is based on the fixed-point method. The seismic responses of the buildings are calculated using non-linear dynamic analysis in OpenSees. Applying the FEMA P-58 approach, the seismic performance of the buildings as measured by the repair cost and repair time is evaluated. The findings reveal that the majority of the structural damage is focused within the masonry walls, coupling beams, and non-structural components. Use of TVMDs results in reduced maximum inter-story drifts that when subjected to very rare earthquake (VRE) shaking are up to approximately 40% lower in both transverse and longitudinal directions compared with the uncontrolled structure. Owing to the effective control of seismic damage to both structural and non-structural components, the TVMD-equipped structure achieves a 42% reduction in median repair cost and a 46% reduction in median repair time at VRE compared with the uncontrolled building. The seismic performance assessment results also illustrate the advantages of TVMD control compared with conventional viscous dampers. • A real-world case study for a retrofitted building using TVMD is presented. • A simplified iterative process is proposed for optimal design of TVMD. • TVMDs effectively control inter-story drift and floor acceleration responses. • Control advantages of TVMDs are illustrated by comparison with viscous dampers. • Use of TVMDs leads to significant reduction of post-quake repair cost and time. [ABSTRACT FROM AUTHOR]

While IEA EBC Annexes usually are focused on R&D about single energy technologies, their broad scale use in practice is of even higher importance to contribute to global energy goals. This practical application of low-carbon technologies on community scale has been the subject of Annex 51, carried out from 2010 to 2013. In this Annex, evaluating 25 community energy case studies of the 10 participating countries, a ‘Guidebook on Successful Urban Energy Planning’ has been extracted from these evaluations to directly address practical urban/energy planners and municipal decision makers. The main content of the Guidebook with respect to planning approaches is summarized in this paper, distinguishing between the different planning fields of ‘urban energy planning’, which is addressing whole cities and communities, and ‘local energy planning’, oriented to neighbourhoods or building clusters. The necessary link between both is emphasized, considering a city as an interconnected energy system requiring a holistic approach rather than a compartmented consideration. As a side effect, a general method to calculate the primary energy performance of buildings and neighbourhoods employing different energy systems, including energy efficiency or energy conservation technologies, was derived. Using appropriate system characteristics, such as seasonal performances, this approach can be applied for every energy system, and for every building or neighbourhood. It is presented in this paper supplying an example from one of the case studies. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) for heating, ventilation and air conditioning (HVAC) in buildings requires accurate controller models of the building envelope and its HVAC systems. Controller models are typically obtained by means of black- or grey-box system identification or using a white-box modelling approach. However, the necessary level of model complexity used by each method in order to obtain good MPC performance remains a priori unknown and no systematic method or examples showing the optimal complexity is available. This paper systematically investigates the required controller model complexity necessary to obtain optimal control performance for a given building. First, a 6-room house is modeled in detail using building energy simulation software. The building model is then linearized to obtain a linear time invariant (LTI) state-space model (SSM) and the upper bound of the control performance is computed using an MPC with the SSM both as controller and as plant model. The accuracy of the SSM (containing more than 250 states) is then artificially decreased by reducing its number of states to different orders ranging from 4 to 100 using balanced truncation model order reduction technique. The performances of MPCs using these controller models are then compared with the upper bound for both a standard MPC formulation (S-MPC) and an offset-free formulation (OSF-MPC) and with the performance of a rule-based-controller (RBC). The procedure is repeated for the same house model with a higher level of insulation and for a lighter weight construction. This paper shows that the controller model should contain a minimum of states to model each zone separately, and that the walls and floors separating the zones should also have enough states to act as a low pass filter with correct cut-off frequency. The minimum number of states further increases with the building mass content. In the case of the investigated 6-room house, the thermal comfort achieved by MPC using a controller model with a minimum of 30 states instead of 20 states was improved with a factor 2–6 without significant increase of the energy use, showing that good MPC performances require controller models with a significantly higher number of states than the order used by most of the black- and grey-box system identification techniques. The minimum required number of states might be chosen lower when OSF-MPC is used instead of conventional MPC. However, OSF-MPC might significantly increase the energy use when poor controller models (high model mismatch) are used. Furthermore, if the controller model is an LTI model, this paper shows that the CPU time necessary to solve the MPC optimization problem becomes independent of the number of states of the controller model when a dense approach is used. The controller model can thus be as complex as necessary to produce accurate predictions without increasing the computation time of the optimization. [ABSTRACT FROM AUTHOR]

Traditional buildings will lead to a series of problems such as high energy consumption, high pollution, and serious waste of resources and environmental damage. It is of great significance to construct a green building evaluation system based on the physical building framework to achieve energy saving and consumption reduction and to fit the sustainable development. In this study, a building greenness evaluation system combining BIM data model and prior knowledge of experts is constructed and the applicability of the method has been verified. IFC information is expressed and transmitted in terms of components, materials, equipment, environmental quality impact, etc., and BIM based building performance design data information conversion and greenness evaluation process is constructed; Based on the comparison and summary of the existing green building evaluation systems at home and abroad, the evaluation model of building greenness is determined; Based on the ideas and steps of establishing the index system proposed in the research, the index system of building greenness evaluation is established from the aspects of environmental quality (Q) and building load (L) on the basis of questionnaire, prior knowledge of experts and other methods; Combined with the mathematical model of greenness evaluation, the paper analyzes the indexes of different levels, determines the structural calculation methods of different indexes, and carries on the quantitative classification of the overall greenness evaluation. Finally, taking a citizen's house as an engineering case, the paper makes an empirical analysis on the greenness evaluation of green buildings. The results show that the green degree of the building is excellent(class A), which is consistent with the project positioning, and provides the basis for the efficient and accurate evaluation of green building. [ABSTRACT FROM AUTHOR]

[Display omitted] • A split-degree days index is proposed for building energy use/climate classification. • Split-degree days index is shown to better estimate solar radiation and humidity data. • The estimation of building energy end-uses is improved using the split-degree days. • Split-degree days also showed improved results for high thermal mass and 24-hr models. • Split-degree days index maintains a high accuracy for varying base temperatures. Degree days have been widely used in different applications in buildings, such as estimating building energy use and climate classification for building energy standards. However, there are limitations with the use of conventional degree days that result in inaccuracies in estimating building energy consumption using degree day-based methods. This paper proposes a new method, the split-degree day method, that shows substantially improved results in the accuracy of the building energy use estimation compared to the conventional degree day methods. The analysis in 801 locations in the U.S. using regression models showed that the new, proposed split-degree day method in this paper, compared to the conventional degree day method, better accounts for the weather parameters and more accurately estimates end-uses. The split-degree days showed an improvement of over 5% in the accuracy of the total annual energy use prediction, 8% for predicting the heating energy use, 0.3% for predicting the cooling energy use, and 33% for predicting the fan energy use. Additionally, the analysis showed improved results for the model with higher thermal mass and the model with a 24-hour operating schedule. These improvements were due to the fact that the split-degree day method includes more information related to the weather characteristics of a location, which is missing in a conventional degree day calculation procedure that relies on aggregated data at daily intervals. Furthermore, as opposed to the conventional degree days, the accuracy of the estimations using the split-degree days are shown to maintain their high accuracy when the base temperature deviates from the optimal base temperature. The proposed method can be used as a more accurate alternative to the conventional degree days in different applications, including but not limited to building climate classification, building energy estimation, and weather normalization for building energy savings calculation. [ABSTRACT FROM AUTHOR]

[Display omitted] • 33 worldwide open datasets of city-level building energy consumption are summarized. • Representative applications of 198 papers using the collected datasets are analyzed and compared. • Policy implications are presented for using the open datasets to support policymaking. • Useful non-energy datasets about weather, building features, urban forms, and occupant-related factors are recommended. • Solutions to privacy issues are explored, including anonymizing methods and proper data aggregation. Data related to building energy use fuels the research and applications on building energy efficiency, which is an essential measure to address global energy and environmental challenges. However, in most cities, there is a lack of comprehensive and publicly accessible building energy use datasets with necessary temporal and spatial granularities to support urban building energy modeling, regional energy planning, city-level building performance benchmarking, and policymaking on building energy efficiency. Data owners and governments are facing challenges in determining which and how building energy use data should be disclosed at the city level and how to protect data privacy. This review paper provides insights to answer these questions based on a comprehensive and critical review of worldwide open datasets and their applications in the built environment context. Detailed information about the collected 33 building energy datasets is summarized and categorized. Studies identified into 11 subdomains using these open datasets are critically analyzed and compared. Potential policy implications based on the studies are also proposed. Moreover, non-energy datasets that are frequently used in research relevant to urban building energy use are also introduced. Solutions to privacy issues are discussed to address concerns from data publishers. Finally, significant conclusions are made to support the proper disclosure of city-level building energy data. This review study is valuable to urban building energy data disclosure, urban building energy modeling, and data-driven energy policymaking. [ABSTRACT FROM AUTHOR]

Several frameworks are introduced to address occupancy-based building performance. However, the performance predictions obtained using these frameworks deviate from real performance. So, this study's aim is to represent a new framework for the automatic assessment of occupants' comfort and building indoor performance using BIM and the SD-ABM platform. Initially, an office space in Hong Kong, consisting of 10 occupants, was considered for the BIM model construction. The occupancy, indoor data and required equations are defined using the SD-ABM model. Essential data from the BIM model can be transferred using the Dynamo-Excel platform. Furthermore, a validation study was conducted using a paper-based survey from the occupants and sensor data for environmental data monitoring while error metrics were also calculated. The framework actively predicts occupant presence, comfort level, temperatures, and CO 2 concentration in the office space. However, a comprehensive usability and feasibility study is required to assess the efficiency of the framework. [ABSTRACT FROM AUTHOR]

This paper examines the ways architects negotiate new early stage design energy modelling tools in their design practice. Energy modelling tools have traditionally mostly been usedby building services engineers with their engagement often occurring at late stages in design to largely verify and validate already established ideas. Recently, however, with a growing international energy agenda and development of new modelling technologies there has been a greater need for broadening use particularly with architects early in design. Yet despite the broadening of use, and increased importance placed on building performance, few studies account for the ways new groups of users such as architects negotiate use of new energy modelling tools in their design practice. Research on the topic of energy modelling has tended to focus on addressing improvements within a particular professional domain or in enhancing features within tools and providing better analysis parameters. The data draws on semi structured interviews and focus group sessions with 26 participants across 4 large international architecture firms in the UK. Preliminary findings indicate differing organizational principles as well as team identities and project assumptions on the ways energy modelling contributes or detracts from fulfilling overall project needs. The implications of the findings are twofold. First, the analysis provides an initial overview of how early stage design energy modelling is considered in design in architecture practice in the UK. Second, the paper provides an understanding of how architects negotiate meaning on energy in design. There are also implications for energy policy development in the context of the built environment particularly concerning building performance. [ABSTRACT FROM AUTHOR]

Reducing space heating energy demand supports the UK’s legislated carbon emission reduction targets and requires the effective characterisation of the UK’s existing housing stock to facilitate retrofitting decision-making. Approximately 6.6 million UK dwellings pre-date 1919 and are predominantly of suspended timber ground floor construction, the thermal performance of which has not been extensively investigated. This paper examines suspended timber ground floor heat-flow by presenting high resolution in-situ heat-flux measurements undertaken in a case study house at 15 point locations on the floor. The results highlight significant variability in observed heat-flow: point U-values range from 0.56 ± 0.05 to 1.18 ± 0.11 Wm −2 K −1 . This highlights that observing only a few measurements is unlikely to be representative of the whole floor heat-flow and the extrapolation from such point values to whole floor U-value estimates could lead to its over- or under- estimation. Floor U-value models appear to underestimate the actual measured floor U-value in this case study. This paper highlights the care with which in-situ heat-flux measuring must be undertaken to enable comparison with models, literature and between studies and the findings support the unique, high-resolution in-situ monitoring methodology used in this study for further research in this area. [ABSTRACT FROM AUTHOR]

Hong Kong buildings account for 90% of total electricity consumption and over 60% of greenhouse gas emissions. Therefore buildings present both a challenge and an opportunity for reduction in energy use and greenhouse gas emissions. Net Zero Energy Building (NZEB) and Net Zero Carbon Building (NZCB) are recognised as feasible strategies to reduce energy use and carbon emissions leading to a more sustainable built environment. While there is a growing number of NZEBs and NZCBs in relatively cool or temperate climates, there are relatively few examples in the subtropical climate, and in a densely populated city such as Hong Kong. This paper will examine the current progress towards a low carbon built environment in Hong Kong, zero energy/carbon design strategies and technologies applicable to building in a subtropical climate, and examines a case study of Hong Kong's first zero carbon building ZCB. ZCB's energy and carbon performance, experiences and lessons learned, and future directions are discussed. The paper will conclude with the challenges and opportunities for wider adoption of NZEBs and NZCBs in the Hong Kong construction industry. [ABSTRACT FROM AUTHOR]

Building performance and assessment tools are not new to the global audience. What are new however are the concerns, on the part of policy makers and building practitioners, with their adaptation to the Nigerian context. These concerns have become especially salient in the face of continued climate change and excessive environmental perturbations. This paper presents the development of a building performance and design tool that is intended to assist the Nigerian government with its building codes and policies and also building practitioners with the design process. The methodology is based on a review of existing building rating systems such as LEED and BREEAM, from which a system adapted to the requirements of the Nigerian National Building Code for residential buildings is proposed. The methodology is further developed into a design tool whose features include a schematic design serving as a reference building validated through energy simulation. The underlying proposal of this paper will assist the Nigerian National Building Code in establishing policies favourable to the built environment and aid designers in the creation of sustainable buildings in Nigeria, as well as serving as an exemplar to other developing African countries. [ABSTRACT FROM AUTHOR]

• A BIM-supported energy performance analysis for green building design is proposed. • This systematic analytical framework integrates explainable machine learning and multi-objective optimization. • It can serve as a data-driven decision tool to guide green building development even under uncertainty. • The top important features that greatly affect the building energy performance can be quantitatively identified. • Building energy performance can be improved by 13.43% using the obtained optimal strategy. Supported by the combination of the advanced BIM technique with intelligent algorithms, this paper develops a systematic framework using explainable machine learning and multi-objective optimization to realize the automatic prediction and optimization of building energy performance towards the sustainable development goal. There are three critical parts incorporated, including the DesignBuilder simulation, BO-LGBM (Bayesian optimization-LightGBM) and an explainable method SHAP (SHapley Additive explanation)-based prediction and explanation of building energy performance, and AGE-MOEA algorithm-based multi-objective optimization (MOO) under sources of uncertainty. It has been verified in a case study for green building design. Results show that: (1) The predictive BO-LGBM model can make a highly precise prediction in agreement with the simulation data, reaching up the R2 larger than 93.4% and MAPE smaller than 2.13%. From the SHAP calculation, features related to the HAVC (Heating Ventilation and Air Conditioning) system tend to contribute more to affecting the prediction results. (2) The AGE-MOEA-based optimization can identify a set of Pareto optimal solutions in simultaneously minimizing the building energy consumption, CO 2 emission, and indoor thermal discomfort degree, arriving at the highest optimization rate of 13.43% under proper adjustment of certain features. (3) In the MOO task, the consideration of model and data uncertainty by prediction intervals and Monte-Carlo simulation can further increase the optimization rate by around 4.0% than the deterministic scenario, resulting in more desired strategies in optimizing the green building performance. In short, this paper enriches the area of green building development. For one thing, it raises the transparency and interpretability of machine learning to make the prediction more convincing. For another, it efficiently determines the passive and active design solutions along with the detailed profile of influential factors for green building design. [ABSTRACT FROM AUTHOR]

[Display omitted] • Building policies must be rooted in a good understanding of the targeted population. • Building performance standards may benefit from creating databases of weather files. • A thermal performance analysis should consider multiple key performance indicators. • Building performance policies should address the thermal resilience of buildings. This paper presents the main challenges faced and lessons learned when developing a new method to assess the thermal performance of residential buildings for the recently updated Brazilian building performance standard, NBR 15575–1:2021. It touches on subjects related to the representation of occupant behavior, climate, and thermal acceptability in building performance simulation, as well as the use of reference models, key performance indicators, and performance levels in policies. NBR 15575 provides a thorough procedure to analyze thermal performance, allowing buildings to be assessed while in passive operation mode and also accounting for energy needs when active operation is necessary. Multiple key performance indicators are introduced to provide a comprehensive evaluation. The main difficulty found was dealing with diversity. Given the vast scale of Brazil's territory, a high variation in culture, climate and construction techniques is expected, thus requiring a compromise between detail and scalability. There are still many opportunities for improvement, especially regarding the representation of occupants, and adjustments of the characteristics of reference models to promote high thermal performance, considering the diverse climates, regional practices, and economic needs. This paper might help researchers and other stakeholders to develop and improve other local standards and protocols, especially for warm climates. [ABSTRACT FROM AUTHOR]

• A data-informed building energy management (DiBEM) framework was proposed. • It was demonstrated in an office/laboratory building with two-years' experimental data. • The impacts of energy efficient interventions were quantified through data-driven models. • The energy use intensity was reduced from 54.1 kWh/m2 to 42.8 kWh/m2. To support building operations in reaching ultra-low energy targets, this paper proposes a data-informed building energy management (DiBEM) framework to improve energy efficiency systematically and continuously at the operation stage. Specifically, it has two key features including data-informed energy-saving potential identification and data-driven model-based energy savings evaluation. The paper demonstrates the proposed DiBEM with a detailed case study of an office and living laboratory building located in Cambridge, Massachusetts called HouseZero. It focuses on revealing the performance of the energy-efficient interventions from two-years' building performance monitoring data, as well as evaluating energy savings from the interventions based on the data-driven approach. With Year 1 as baseline, several interventions are proposed for Year 2 including improvements to controls and operation settings, encouragement of occupants' behavior for energy savings, and hardware retrofitting. These were deployed to heating/cooling, domestic hot water, lighting, plug and other loads, and photovoltaic (PV) systems. To quantify the impacts of different interventions on energy end uses, several data-driven models are developed. These models utilize linear regression, condition model, and machine learning techniques. Consequently, the heating/cooling energy consumption that was already ultra-low in Year 1 (12.8 kWh/m2) is further reduced to 9.7 kWh/m2 in Year 2, while the indoor thermal environment is well maintained. The domestic hot water energy is reduced from 2.3 kWh/m2 to 1.2 kWh/m2. The lighting energy is only increased from 0.3 kWh/m2 in pandemic operations without occupancy in Year 1 to 0.8 kWh/m2 in partial normal operations in Year 2, while the indoor illuminance level meets occupants' requirements. Combined with other relatively constant loads and the reduction of plug and other loads due to COVID building operation restrictions, the total energy use intensity is thereby reduced from 54.1 kWh/m2 to 42.8 kWh/m2, where 5.4 kWh/m2 of energy reduction for Year 2 is estimated to be contributed by the energy-efficient interventions. PV generation is 36.1 kWh/m2, with an increase of 1.4 kWh/m2 from a new inverter. In summary, this paper demonstrates the use of DiBEM through a detailed case study and long-term monitoring data as evidence to achieve ultra-low energy operations. [ABSTRACT FROM AUTHOR]

Numerous buildings fall short of expectations regarding occupant satisfaction, sustainability, or energy efficiency. In this paper, the performance of buildings in terms of occupant comfort is evaluated using a probabilistic model based on Bayesian networks (BNs). The BN model is founded on an in-depth analysis of satisfaction survey responses and a thorough study of building performance parameters. This study also presents a user-friendly visualization compatible with BIM to simplify data collecting in two case studies from Norway with data from 2019 to 2022. This paper proposes a novel Digital Twin approach for incorporating building information modeling (BIM) with real-time sensor data, occupants' feedback, a probabilistic model of occupants' comfort, and HVAC faults detection and prediction that may affect occupants' comfort. New methods for using BIM as a visualization platform, as well as a predictive maintenance method to detect and anticipate problems in the HVAC system, are also presented. These methods will help decision-makers improve the occupants' comfort conditions in buildings. However, due to the intricate interaction between numerous equipment and the absence of data integration among FM systems, CMMS, BMS, and BIM data are integrated in this paper into a framework utilizing ontology graphs to generalize the Digital Twin framework so it can be applied to many buildings. The results of this study can aid decision-makers in the facility management sector by offering insight into the aspects that influence occupant comfort, speeding up the process of identifying equipment malfunctions, and pointing toward possible solutions. [ABSTRACT FROM AUTHOR]

This paper explores the effects of residential neighborhood types on building energy consumption and solar energy trade-offs with the goal of developing an operational methodology to achieve the best conditions towards a zero nonrenewable energy neighborhood. Six typical Chongming neighborhood types are identified, termed the Farmhouse, Linear-village, Nucleated-village, Townhouse, Slab and High-rise types with the effects of increased installation of solar energy panels estimated by Monte Carlo simulation. To achieve a more comprehensive view of cost-effective opportunities to improve the performance of buildings at the neighborhood scale, we use actual energy use data obtained from both the survey and electricity bills’ analysis to show that considerable variations exist due to hitherto unrecorded socioeconomic factors relating to the type of occupants involved. By concluding that the associated variables are interdependent, the paper continues with an empirical study in which the solar energy potential of each neighborhood is quantified to show that, in the case of Chongming, the Nucleated-village and Slab neighborhood types have the greatest retrofitting potential. These investigations into energy trade-offs with existing retrofitting and construction technologies therefore provide a metric for other eco-cities to use as a tool for future policy guidance. [ABSTRACT FROM AUTHOR]

Research has shown the large effect that occupants have on buildings' performance. Uncertainties related to the actual energy consumption of buildings increase the risks for the investments in low carbon technologies. Monitoring building occupancy can potentially decrease these uncertainties by providing more information about the occupants and their behaviour. The objective of the investigation is to establish an approach to inform the design process (e.g. building simulation) by addressing the complexity of occupants behaviour. The approach integrates information on occupants' behaviour and attitudes regarding energy use and indoor conditions to determine the requirements for building simulation and energy calculations. This paper presents the results of two monitoring campaigns in which the approach was employed. The monitoring campaigns focused on two owner-inhabited apartments in Spain and three social rental dwellings in The Netherlands. The results have given first insights of the power of the methodology to obtain detailed and understandable data on the occupancy patterns. This investigation highlighted the importance socio-economical status and attitudes towards energy conservation on occupants' behaviour in residential buildings. The methods described in this paper can be readily used to develop occupancy and heating profiles for monitored households to be used in building simulation programs. [ABSTRACT FROM AUTHOR]

Inequities in the built environment have long persisted in communities around the world. Prior studies have exposed that energy retrofit programs invest inequitably in residential buildings, leaving racial minorities with disproportionately less energy inefficient homes, regardless of income level. This inequity in energy performance and retrofit investments has yet to be studied for commercial and institutional buildings. Further research has shown that tree canopy coverage and vegetation is less dense in historically disadvantaged communities, contributing to a greater urban heat island effect and corresponding higher energy consumption for cooling compared to historically advantaged communities. Moreover, there is limited albeit emerging research that utilizes granular socioeconomic data with fine temporal scale energy consumption data to help identify energy inequalities among race and income groups. This paper examines the differential impact of energy efficiency retrofit installation on energy performance between advantaged vs. disadvantaged groups using data from U.S. public school buildings. Additionally, it studies how the effect of retrofits is compounded by the presence of vegetation surrounding the building. Utilizing hourly interval smart meter data from primary and secondary school buildings in California, the impact of retrofits are quantified using three energy metrics. Then the disparities in retrofit impact for advantaged vs. disadvantaged groups (as defined by three equity metrics) are evaluated using school-level demographic data. Lastly, regression on the percent change in monthly energy consumption from the pre-retrofit to post-retrofit period is used to quantify the incremental benefits of retrofits compounded by vegetation. Findings show that energy efficiency retrofits can improve energy performance and reduce energy inequities. Specifically, retrofits significantly increase energy efficiency and reduce the energy efficiency equity gap by up to 198%. Evidence shows that vegetation surrounding a building has a synergistic effect with mechanical retrofits for reducing energy consumption in respect to reduced cooling loads, even in cases where mechanical retrofits alone resulted in significant increases in energy consumption. Dense vegetation provides around 6% energy savings, similar in magnitude to savings from mechanical retrofit installation. This validates the effectiveness of retrofits for reducing energy consumption and improving energy equity, and demonstrates the ability of vegetation to provide additional energy savings beyond mechanical interventions. [ABSTRACT FROM AUTHOR]

Engaging with performance feedback in early building design often involves building a custom parametric model and generating large datasets, which is not always feasible. Alternatively, large parametric datasets of general design problems and filtering methods could be used together to explore specific design decisions. This paper investigates the generalizability of a method that dynamically assesses variable importance and likely influence on performance objectives as a precomputed design space is filtered down. The method first trains linear model trees to predict building performance objectives across a generic design space. Leaf node models are then aggregated to provide feedback on variable importance in different design space regions. This approach is tested on three design problems that vary in number of variables, samples, and design space structure to reveal advantages and potential limitations of the method. Algorithm improvements are proposed, and general recommendations are developed to apply it on future datasets. • New methods are required to identify distinct variable behavior in the design space. • The sensitivity method supports real-time decision making as design criteria emerge. • It is important to account for the robustness of the leaf node models. • This method provides ranges to design within and supports design freedom. • The sampling technique impacts the ability to accurately capture local behaviors. [ABSTRACT FROM AUTHOR]