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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted by number of followers
Review of Economics and Statistics     Hybrid Journal   (Followers: 154)
Statistics in Medicine     Hybrid Journal   (Followers: 149)
Journal of Econometrics     Hybrid Journal   (Followers: 83)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 72, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 53)
Biometrics     Hybrid Journal   (Followers: 52)
Sociological Methods & Research     Hybrid Journal   (Followers: 45)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 41)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 40, SJR: 3.664, CiteScore: 2)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 35)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 33)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 33)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 30)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 26)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 24)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 24)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
Journal of Forecasting     Hybrid Journal   (Followers: 20)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 18)
Statistical Modelling     Hybrid Journal   (Followers: 18)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 17)
Journal of Statistical Software     Open Access   (Followers: 16, SJR: 13.802, CiteScore: 16)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 16)
Risk Management     Hybrid Journal   (Followers: 16)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 15)
Computational Statistics     Hybrid Journal   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Demographic Research     Open Access   (Followers: 14)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 13)
Journal of Statistical Physics     Hybrid Journal   (Followers: 13)
International Statistical Review     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 11)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 11)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Journal of Probability and Statistics     Open Access   (Followers: 10)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Biometrical Journal     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Argumentation et analyse du discours     Open Access   (Followers: 8)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Current Research in Biostatistics     Open Access   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Stata Journal     Full-text available via subscription   (Followers: 8)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 8)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 7)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Lifetime Data Analysis     Hybrid Journal   (Followers: 7)
Significance     Hybrid Journal   (Followers: 7)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Statistical Methods and Applications     Hybrid Journal   (Followers: 6)
Law, Probability and Risk     Hybrid Journal   (Followers: 6)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Global Optimization     Hybrid Journal   (Followers: 6)
Applied Categorical Structures     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Engineering With Computers     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Statistical Papers     Hybrid Journal   (Followers: 4)
Sankhya A     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 3)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
Building Simulation     Hybrid Journal   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
Stochastic Models     Hybrid Journal   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
TEST     Hybrid Journal   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
International Journal of Stochastic Analysis     Open Access   (Followers: 2)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Statistics and Economics     Open Access  
Review of Socionetwork Strategies     Hybrid Journal  
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
Journal of the Korean Statistical Society     Hybrid Journal  
Sequential Analysis: Design Methods and Applications     Hybrid Journal  

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Building Simulation
Journal Prestige (SJR): 0.839
Citation Impact (citeScore): 2
Number of Followers: 2  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1996-8744 - ISSN (Online) 1996-3599
Published by Springer-Verlag Homepage  [2469 journals]
  • Evaluation of the relative differences in building energy simulation
           results

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      Abstract: Abstract Building energy modeling, also known as building energy simulation, has developed rapidly in recent years and plays a crucial role in building life-cycle analysis. It can be employed in the design phase to predict the energy consumption of different design schemes and evaluate various control and retrofitting measures at the operation stage. In such simulations, it is commonly understood and accepted that the simulated relative differences are more reliable than the predictions of absolute energy results. However, whether this common understanding is true is yet to be thoroughly investigated. In this study, we investigate the simulated relative differences and the extent to which they are affected by the degree of model input deviation. Simulation and Monte Carlo approaches are adopted for the analysis. The results indicate that the simulated relative differences are not as reliable as expected, and the outputs strongly depend on the degree of the model input deviation. When the degree of deviation is less than 15% or the model inputs are within reasonable ranges, the simulated relative differences match the baseline obtained using Monte Carlo simulations. Moreover, the model’s error indicators meet the requirements of the ASHRAE Guideline 14–2014 when the degree of input deviation is below 15%.
      PubDate: 2022-11-01
       
  • DeST 3.0: A new-generation building performance simulation platform

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      Abstract: Abstract Buildings contribute to almost 30% of total energy consumption worldwide. Developing building energy modeling programs is of great significance for lifecycle building performance assessment and optimization. Advances in novel building technologies, the requirements of high-performance computation, and the demands for multi-objective models have brought new challenges for building energy modeling software and platforms. To meet the increasing simulation demands, DeST 3.0, a new-generation building performance simulation platform, was developed and released. The structure of DeST 3.0 incorporates four simulation engines, including building analysis and simulation (BAS) engine, HVAC system engine, combined plant simulation (CPS) engine, and energy system (ES) engine, connected by air loop and water loop balancing iterations. DeST 3.0 offers numerous new simulation features, such as advanced simulation modules for building envelopes, occupant behavior and energy systems, cross-platform and compatible simulation kernel, FMI/FMU-based co-simulation functionalities, and high-performance parallel simulation architecture. DeST 3.0 has been thoroughly evaluated and validated using code verification, inter-program comparison, and case-study calibration. DeST 3.0 has been applied in various aspects throughout the building lifecycle, supporting building design, operation, retrofit analysis, code appliance, technology adaptability evaluation as well as research and education. The new generation building simulation platform DeST 3.0 provides an efficient tool and comprehensive simulation platform for lifecycle building performance analysis and optimization.
      PubDate: 2022-11-01
       
  • Regression tree ensemble learning-based prediction of the heating and
           cooling loads of residential buildings

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      Abstract: Abstract Building energy consumption is heavily dependent on its heating load (HL) and cooling load (CL). Therefore, an efficient building demand forecast is critical for ensuring energy savings and improving the operating efficacy of the heating, ventilation, and air conditioning (HVAC) system. Modern and specialized energy-efficient building modeling technologies may offer a fair estimate of the influence of different construction methods. However, deploying these tools could be time-consuming and complex for the user. Thus, in this article, an ensemble model based on decision trees and the least square-boosting (LS-boosting) algorithm known as the regression tree ensemble (RTE) is proposed for the accurate prediction of HL and CL. The hyper parameters of the RTE are optimized by shuffled frog leaping optimization (SFLA), which leads to SRTE. Stepwise regression (STR) and Gaussian process regression (GPR) based on different kernel functions are also designed for comparison purposes. Results demonstrate that the value of root mean squared error is reduced by 37%–68% and 30%–41% for HL and CL of residential buildings, respectively, by the proposed SRTE in comparison to other models. Furthermore, the findings from the real dataset support the proposed model’s effectiveness in predicting HVAC energy usage. It can be concluded that the proposed SRTE is more effective and accurate than other methods for predicting the energy consumption of HVAC systems.
      PubDate: 2022-11-01
       
  • Design optimisation of mean room surface exitance and total corneal
           illuminance using Monte Carlo simulation

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      Abstract: Abstract In lighting design, mean room surface exitance (MRSE) has been known as an indicator of the adequacy of illumination in an indoor space. Recent studies have suggested an exponential model relating MRSE and the observer’s retinal response. This is particularly applicable in a room with homogenous room surface reflectance and a constant total corneal illuminance, which is the total illuminance received at the eye. However, accuracy of the exponential model is yet to be assessed in detail. Furthermore, the implication on interior lighting design is also yet to be quantified. This study thus aims to assess the accuracy of the exponential model and to optimise the output variables. Random computations using Monte Carlo simulation are performed for various input variables, followed with sensitivity and uncertainty analyses and optimisation. Prediction errors of the exponential model are found between -10% and 6%. The MRSE is highly influenced by surface reflectance, whereas the total corneal illuminance is influenced by the source luminous flux. Optimum design parameters are obtained by minimising the ratio between total corneal illuminance and MRSE. Overall, this study provides guidelines in lighting design practice for enhancing room spatial brightness while minimising energy use.
      PubDate: 2022-11-01
       
  • An improved wall-mounted displacement ventilation system in a large-span
           machining workshop

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      Abstract: Abstract A machining workshop requires ventilation that removes oil mist particles efficiently and conditions air to a comfortable temperature. Displacement ventilation has been reported to be highly efficient in removing airborne pollutants in a workshop. However, the traditional wall-mounted displacement ventilation system may be inadequate for delivering conditioned, clean air to the internal zone of a large-span workshop. This investigation proposed an improved wall-mounted displacement ventilation system in which machining equipment is elevated, relay fans are operated in corridors in the cooling season, and ceiling air exhausts are lowered. The proposed ventilation system was compared with the traditional wall-mounted displacement ventilation system and a displacement ventilation system with multiple local diffusers in the corridors, separately. A validated computational fluid dynamics (CFD) software program was used to investigate the three ventilation systems in both the cooling and heating seasons. The airflow, oil mist particle concentration, and air temperature under the three ventilation systems were evaluated. The results revealed that the traditional wall-mounted displacement ventilation system is inappropriate for use in a large-span workshop, particularly in the cooling season. The proposed improved wall-mounted displacement ventilation provided the lowest oil mist particle concentration in the breathing zone and an appropriate air temperature in the occupied zone in both the cooling and heating seasons. Notably in the cooling season, the proposed system reduced the oil mist particle concentration by 48.5% in the breathing zone as compared with the traditional system. Such an improved ventilation system is highly recommended for use in large-span workshops.
      PubDate: 2022-11-01
       
  • Comprehensive energy, economic, environmental assessment of a building
           integrated photovoltaic-thermoelectric system with battery storage for net
           zero energy building

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      Abstract: Abstract To realize the goal of net zero energy building (NZEB), the integration of renewable energy and novel design of buildings is needed. The paths of energy demand reduction and additional energy supply with renewables are separated. In this study, those two are merged into one integration. The concept is based on the combination of photovoltaic, thermoelectric modules, energy storage and control algorithms. Five types of building envelope systems, namely PV+TE (S1), Grid+TE (S2), PV+Grid+TE (S3), PV+Battery+TE (S4) and PV+Grid+Battery+TE (S5) are studied, from aspects of energy, economic and environmental (E3) performance. The new envelope systems can achieve thermal load reduction while providing additional cooling/heating supply, which can promote advance of NZEBs. It is found that there is a typical optimum setting of thermal energy load for each one of them with minimum annual power consumption. Except for the S1 system, the rest can realize negative accumulated power consumption in a year-round operation, which means the thermal load of building envelope could be zero. The uniform annual cost for S1 to S5 under interest rate of 0.04 are 19.78, 14.77, 23.83, 60.53, 64.94 $/m2, respectively. The S5 system has the highest environmental effect with 3.04 t/m2 reduction of CO2 over 30 years of operation.
      PubDate: 2022-11-01
       
  • Impact of window and air-conditioner operation behaviour on cooling load
           in high-rise residential buildings

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      Abstract: Abstract Space cooling is an important building energy end-use that was found in recent years to be significantly impacted by occupant behaviours. However, the majority of previous studies ignored the interplay between the operation of windows and air conditioners (ACs) on cooling load, particularly in building energy modelling. In addition, studies on the analysis of cooling load characteristics regarding high-rise buildings are insufficient. The vertical effect of high-rise buildings on cooling load remains vague. This study thus aims to examine how window and AC operation behaviours impact the cooling load of high-rise buildings in an urban context demonstrated by a real-life typical 40-floor residential building in Hong Kong. This study investigates window and AC operation behaviours jointly and examines the vertical effect on cooling load by using agent-based building energy modelling (BEM) techniques and initiating stochastic and diverse behaviour modes. A carefully designed questionnaire survey was conducted to help build behaviour modes and validate energy models. Ninety building energy models were established integrating meteorological parameters generated by the computational fluid dynamics (CFD) programme for ten typical floors and nine combinations of window and AC behaviour modes. The results show that comfort-based AC modes and schedule-based window modes yielded the lowest cooling load. Considering the combined effect of AC and window uses, the maximum difference in cooling loads could be 26.8%. Behaviour modes and building height induce up to 32.4% differences in cooling loads. Besides, a deviation between the behaviour modes and height on the cooling load was found. The findings will help develop a thorough energy model inferring occupants’ window and AC behaviour modes along with the building height in high-rise residential buildings. The findings indicate that the interaction impact of window and AC behaviour modes and height should be jointly considered in future high-rise building energy modelling, building energy standards, and policymaking.
      PubDate: 2022-11-01
       
  • Room thermal load prediction based on analytic hierarchy process and
           back-propagation neural networks

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      Abstract: Abstract Accurate prediction of the heat load is the basic premise of intelligent regulation of the heating system, which helps to realize effective management of heating, ventilation, air conditioning system. For the problem that the weight of each influencing factor is not taken into account in the current heat load prediction and is not highly targeted, this article deeply explores the influence of different factors on the room heat load, and we propose a method to calculate room heat load prediction based on the combination of analytic hierarchy process (AHP) and back-propagation (BP) neural network. Firstly, eight environmental factors affecting the heat load are selected as prediction inputs through parametric analysis, and then the weights of each input are determined by AHP and normalize the prediction data by combining expert opinions, and finally do one-to-one training the quantified score and the room heat load to predict the future heat load by BP neural network. The simulation tests show that the mean absolute relative error (MARE) of the proposed prediction method is 5.40%. This article also verifies the influence of different expert opinions on the stability of the model. The results show that the proposed method can guarantee higher prediction accuracy and stability.
      PubDate: 2022-11-01
       
  • Challenges and opportunities for carbon neutrality in China’s building
           sector—Modelling and data

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      Abstract: Abstract The building sector is one of the largest energy user and carbon emitter globally. To achieve China’s national carbon target, the building sector in China needs to achieve carbon peaking and neutrality targets by 2030 and 2060, respectively. However, data deficiency on building energy and emissions become barriers for tracking the status of building energy and emissions, and identify potential opportunities for achieving dual carbon targets. To address these shortcomings, this study established an integrated China Building Energy and Emission Model (CBEEM). With CBEEM, this study evaluated the building-construction and building-operation energy and emissions in China, and revealed the status quo and potential challenge and opportunities. According to modelling results, building operation energy use of China was 1.06 billion tce in 2020, accounting for 21% of China’s total primary energy consumption. Building construction energy consumption was 0.52 billion tce in 2020, accounting for another 10% of total primary energy consumption. Key messages found on building carbon emissions are: building construction embodied emissions were 1.5 billion tCO2 in 2020 and are declining slowly, building operational carbon emissions were 2.2 billion tCO2 in 2020 and are still increasing. International comparisons between China and other countries on building stock, energy use intensity and carbon emission intensity were conducted as well, and help shed a light on the challenges for decarbonization of China’s building sector. Finally, technology perspectives to achieve carbon neutrality target were discussed and related policy suggestions were provided.
      PubDate: 2022-11-01
       
  • A building energy models calibration methodology based on inverse
           modelling approach

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      Abstract: Abstract Nowadays, building energy models (BEMs) are widely used, particularly in the assessment of energy consumption in buildings to address the potential savings that can be generated. The realisation of a dynamic energy model based on high-fidelity physics (white-box models) requires a tuning process to fit the model to reality, due to many uncertainties involved. Currently some research trends try to reduce this performance gap by modulating different types of experimental parameters such as: capacitances or infiltration. The EnergyPlus simulation software, in its latest versions, has implemented an object: HybridModel:Zone that calculates the infiltration and internal mass of buildings using an inverse modelling approach that employs only the measured indoor temperature data to invert the heat balance equation for the zone under study. The main objective of this paper is to reduce the execution time and uncertainties in the development of quality energy models by generating a new calibration methodology that implements this approach. This uses, as a starting point, a research created by the authors of this study, which was empirically and comparatively validated against the energy models developed by the participants in Annex 58. It is also worth highlighting the empirical validation of the HybridModel:Zone object, since it was activated in all scenarios where its execution is possible: periods of seven days or more of free oscillation and periods in which the building is under load. The findings are promising. The data generated with the new methodology, if compared with those produced by the baseline model, improve their resemblance to the real ones by 22.9%. While those of its predecessor did it by 15.6%. For this study, the two dwellings foreseen in Annex 58 of the IEA ECB project have been modelled and their real monitoring data have been used.
      PubDate: 2022-11-01
       
  • Building a greener future—Progress of the green building technology in
           the “13th Five-Year Plan” of China

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      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0915-y
       
  • Development of a bioheat model for older people under hot and cold
           exposures

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      Abstract: Abstract Physiological modeling is important to evaluate the effects of heat and cold conditions on people’s thermal comfort and health. Experimental studies have found that older people (above 65 year old) undergo age-related weakening changes in their physiology and thermoregulatory activities, which makes them more vulnerable to heat or cold exposure than average aged young adults. However, addressing the age-related changes by modeling has been challenging due to their wide variability among the older population. This study develops a two-node physiological model to predict the thermal response of older people. The model is built on a newly developed two-node model for average-age young adults by accounting for the age-related attenuation of thermoregulation and sensory delays in triggering thermoregulatory actions. A numerical optimization method is developed to compute the model parameter values based on selected benchmark data from the literature. The proposed model is further validated with published measurement data covering large input ranges. The model predictions are in good agreement with the measurements in hot and cold exposure conditions with a discrepancy 0.60 °C for the mean skin temperature and of 0.30 °C for the core temperature. The proposed model can be integrated into building simulation tools to predict heat and cold stress levels and the associated thermal comfort for older people in built environments.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0890-3
       
  • Intelligent windows for electricity generation: A technologies review

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      Abstract: Abstract Buildings are responsible for over 40% of total primary energy consumption in the US and EU and therefore improving building energy efficiency has significant potential for obtaining net-zero energy buildings reducing energy consumption. The concurrent demands of environmental comfort and the need to improve energy efficiency for both new and existing buildings have motivated research into finding solutions for the regulation of incoming solar radiation, as well as ensuring occupant thermal and visual comfort whilst generating energy onsite. Windows as building components offer the opportunity of addressing these issues in buildings. Building integration of photovoltaics permits building components such as semi-transparent façade, skylights and shading devices to be replaced with PV. Much progress has been made in photovoltaic material science, where smart window development has evolved in areas such as semi-transparent PV, electrochromic and thermochromic materials, luminescent solar concentrator and the integration of each of the latter technologies to buildings, specifically windows. This paper presents a review on intelligent window technologies that integrate renewable energy technologies with energy-saving strategies contributing potential solutions towards sustainable zero-energy buildings. This review is a comprehensive evaluation of intelligent windows focusing on state-of-the-art development in windows that can generate electricity and their electrical, thermal and optical characteristics. This review provides a summary of current work in intelligent window design for energy generation and gives recommendations for further research opportunities.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0895-y
       
  • Development of acoustic computer simulation for performance spaces: A
           systematic review and meta-analysis

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      Abstract: Abstract This article aims to review the development of acoustic computer simulation for performance spaces. The databases of Web of Science and Scopus were searched for peer-reviewed journal articles published in English between 1960 and 2021, using the keywords for “simulation”, “acoustic”, “performance space”, “measure”, and their synonyms. The inclusion criteria were as follows: (1) the searched article should be focused on the field of room acoustics (reviews were excluded); (2) a computer simulation algorithm should be used; (3) it should be clearly stated that the simulated object is a performance space; and (4) acoustic measurements should be used for comparison with the simulation. Finally, twenty studies were included. A standardised data extraction form was used to collect the modelling information, software/algorithm, indicators for comparison, and other information. The results revealed that the most used acoustic indicators were early decay time (EDT), reverberation time (T30), strength (G), and definition (D50). The accuracy of these indicators differed greatly. For non-iterative simulation, the simulation accuracies of most indicators were outside their respective just noticeable differences. Although a larger sample size was required for further validation, simulations of T30, EDT, and D50 all showed an increase in accuracy with increasing time from 1979 to 2020, except for G. In terms of frequency, the simulation was generally less accurate at lower frequencies, which occurred at T30, G, D50 and T20. However, EDT accuracy did not exhibit significant frequency sensitivity. The prediction accuracy of inter-aural cross-correlation coefficients (IACC) was even higher at low frequencies than it was at high frequencies. The average value of most indicators showed a clear systematic deviation from zero, providing hints for future algorithm improvements. Limitations and the risks of bias in this review were discussed. Finally, various types of benchmark tests were suggested for various comparison goals.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0901-4
       
  • Smart luminescent solar concentrator as a BICPV window

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      Abstract: Abstract Building integrated concentrating photovoltaic (BICPV) windows have attracted numerous studies in recent years. However, there is a tradeoff between the light transmittance and power generation efficiency in the design of BICPV window. In this paper, a smart luminescent solar concentrator (LSC) is introduced as the BICPV window. The proposed smart LSC system features on the combination of fluorescent dyes with thermochromic materials to enhance photoelectric conversion efficiency as well as form a dynamic response mechanism to ambient solar radiation and environmental temperature. In this study, a BICPV smart window system consists of the waveguide doped with organic dye Lumogen F Red-305 (BASF) and the thermochromic hydrogel membrane has been developed. The research on analytic design parameters is executed through optical simulation by ray tracing technology along with outdoor comparative experiments. From simulations for a smart LSC of 100 mm × 100 mm × 3 mm with a bottom-mounted solar cell of 100 mm × 10 mm, the optical effective concentration is found to be with the range of 1.23 to 1.31 when a highest gain of 1.26 in power over the bare solar cell is obtained from experiments.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0896-x
       
  • Digital ID framework for human-centric monitoring and control of smart
           buildings

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      Abstract: Abstract Smart offices can help employers attract and retain talented people and can positively impact well-being and productivity. Thanks to emerging technologies and increased computational power, smart buildings with a specific focus on personal experience are gaining attraction. Real-time monitoring and estimation of the human states are key to achieving individual satisfaction. Although some studies have incorporated real-time data into the buildings to predict occupants’ indoor experience (e.g., thermal comfort and work engagement), a detailed framework to integrate personal prediction models with building systems has not been well studied. Therefore, this paper proposes a framework to predict and track the real-time states of each individual and assist with decision-making (e.g., room assignment and indoor environment control). The core idea of the framework is to distinguish individuals by a new concept of Digital ID (DID), which is then integrated with recognition, prediction, recommendation, visualization, and feedback systems. The establishment of the DID database is discussed and a systematic prediction methodology to determine occupants’ indoor comfort is developed. Based on the prediction results, the Comfort Score Index (CSI) is proposed to give recommendations regarding the best-fit rooms for each individual. In addition, a visualization platform is developed for real-time monitoring of the indoor environment. To demonstrate the framework, a case study is presented. The thermal sensation is considered the reference for the room allocation, and two groups of people are used to demonstrate the framework in different scenarios. For one group of people, it is assumed that they are existing occupants with personal DID databases. People in another group are considered the new occupants without any personal database, and the public database is used to give initial guesses about their thermal sensations. The results show that the recommended rooms can provide better thermal environments for the occupants compared to the randomly assigned rooms. Furthermore, the recommendations regarding the indoor setpoints (temperature and lighting level) are illustrated using a work engagement prediction model. However, although specific indoor metrics are used in the case study to demonstrate the framework, it is scalable and can be integrated with any other algorithms and techniques, which can serve as a fundamental framework for future smart buildings.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0902-3
       
  • Energy-saving and economic analysis of passive radiative sky cooling for
           telecommunication base station in China

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      Abstract: Abstract The widespread application of 4G and the rapid development of 5G technologies dramatically increase the energy consumption of telecommunication base station (TBS). Remarkably, the air conditioning system accounts for a significant part of energy consumption in TBS. In this work, passive radiative sky cooling technology has been studied to explore its application potential for TBS. We built a simulation model in DeST to investigate the effect of various envelope thermophysical properties on TBS energy saving. The main influencing factors of the radiative sky cooling on TBS energy saving have been concluded and guidance has been raised for further application. An optimized envelope design combining radiative sky cooling with appropriate heat transfer coefficients has been proposed. The energy-saving and economic analysis of the optimized envelope design at different areas shows that, except for the low heat density TBS in severe cold areas, the annual energy-saving rate is 6.77%–64.29%, and the annual total energy saving is 21.94 kWh/m2–52.74 kWh/m2. The payback period is 1.55–4.67 years, and the maximum acceptable cost limited to a 5-year payback period is $3.21/m2–$9.67/m2.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0894-z
       
  • A novel coordinated control for NZEB clusters to minimize their connected
           grid overvoltage risks

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      Abstract: Abstract The increasing applications of net-zero energy buildings (NZEBs) will lead to more frequent and larger energy interactions with the connected power grid, thereby being able to result in severe grid overvoltage risks. Control optimization has been proven effective to reduce such risks. Existing controls have oversimplified the overvoltage quantification by simply using the aggregated power exchanges to represent the connected grid overvoltages. Ignoring the complex voltage influences among the grid nodes, such oversimplification can easily result in low-accuracy impact evaluations of the NZEB-grid energy interactions, thereby causing non-optimal/unsatisfying overvoltage mitigations. Therefore, this study proposes a novel coordinated control method in which a power-distribution-network model has been adopted for more accurate overvoltage quantification. Meanwhile, the battery operations of individual NZEBs are iteratively coordinated using a sequential optimization approach for achieving the global optimum with substantially reduced computation complexity. For verifications, the proposed coordinated control has been systematically compared with an uncoordinated control and a conventional coordinated control in grid overvoltage minimization. The study results show that the overvoltage improvements can reach 23.5% and 12.3% compared with the uncoordinated control and the conventional coordinated control, respectively. The reasons behind the improvements have also been analyzed in detail. The proposed coordinated control can be used in practice to improve NZEB-clusters’ grid friendliness.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0892-1
       
  • Direct capture efficiency of range hoods in the confined kitchen space

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      Abstract: Abstract Range hood is a local ventilation device applied widely in residential kitchen for maintaining healthy environment. This study firstly defines the direct capture efficiency (DCE) based on the two-zone model in a confined kitchen space. A mass flux ratio of the secondary captured pollutant to the entrained pollutant from the room zone is proposed for the determination of DCE, where the distribution coefficient is firstly solved, and then its sensitivity analysis on the DCE is carried out. To validate the mass flux ratio and concisely identify the DCE, a virtual purification method that artificially sets the escaped pollutant to zero, is further applied. Compared with the newly developed DCE, the existing indexes, such as contaminant removal efficiency (CRE), total capture efficiency (TCE), fail to differentiate the direct capture from the total capture. Finally, the effects of such factors as makeup airflow pattern, exhaust flow rate, cooking source temperature and the individual occupied/unoccupied on the DCE are fully studied. It is confirmed that different makeup airflow pattern results in distinguished airflow distribution, which makes a significant difference of more than 30% in DCE. Over 50% increase of DCE can be achieved when the exhaust flow rate is increased from 300 to 600 m3/h. About 30% decrease of DCE is observed with the increased cooking source temperature from 100 to 300 °C, and 10% increase of DCE is appeared in the individual occupied case. This reasonable definition and determination of DCE would help to improve the real capture performance of range hoods.
      PubDate: 2022-10-01
      DOI: 10.1007/s12273-022-0898-8
       
  • Thermal performance and evaluation of a novel stratified and mixed
           flexible transformation solar heat storage unit

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      Abstract: Abstract It is necessary to satisfy the flexible requirements of solar heat storage systems to provide efficient heating and constant-temperature domestic hot water at different periods. A novel heat storage tank with both stratified and mixing functions is proposed, which can realize the integration of stable stratification and rapid mixing modes. In this research, a three-dimensional heat transfer model of the heat storage tank with stratified and mixed dual modes was established, and a thermal performance test system for the tank was built in the State Key Laboratory of Green Building in Western China. Moreover, a new evaluation index representing the mixing speed is proposed. The stratification effect and mixing characteristics of the tank were studied under different comprehensive conditions. The results show that the exergy efficiency of the tank with a stratified pipe can be increased by 10%–15% compared to that of a conventional tank. Additionally, the recommended optimal flow rate range for well-stratified tanks is 4–6 L/min. The mixing nozzle of the tank reduces the mixing reaction coefficient by 0.27 and significantly reduces the mixing time. This study provides critical guidance to meet the flexible thermal needs of users and implement high-performance applications using the stratified and mixing modes of heat storage tanks.
      PubDate: 2022-09-20
       
 
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