A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

              [Sort alphabetically]   [Restore default list]

  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted by number of followers
Review of Economics and Statistics     Hybrid Journal   (Followers: 150)
Statistics in Medicine     Hybrid Journal   (Followers: 136)
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: 52)
Biometrics     Hybrid Journal   (Followers: 50)
Sociological Methods & Research     Hybrid Journal   (Followers: 43)
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: 39, 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)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 28)
Statistical Methods in Medical Research     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: 23)
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)
Journal of Statistical Physics     Hybrid Journal   (Followers: 13)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
International Statistical Review     Hybrid Journal   (Followers: 12)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 12)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     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)
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)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 8)
Stata Journal     Full-text available via subscription   (Followers: 8)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 7)
Lifetime Data Analysis     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 7)
Significance     Hybrid Journal   (Followers: 7)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Journal of Global Optimization     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Statistical Methods and Applications     Hybrid Journal   (Followers: 6)
Law, Probability and Risk     Hybrid Journal   (Followers: 6)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 4)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
Statistical Papers     Hybrid Journal   (Followers: 4)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Stochastic Models     Hybrid Journal   (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)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
TEST     Hybrid Journal   (Followers: 2)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
AStA Advances in Statistical Analysis     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  

              [Sort alphabetically]   [Restore default list]

Similar Journals
Journal Cover
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]
  • Building a greener future—Progress of the green building technology in
           the “13th Five-Year Plan” of China

    • Free pre-print version: Loading...

      PubDate: 2022-10-01
       
  • Development of a bioheat model for older people under hot and cold
           exposures

    • Free pre-print version: Loading...

      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
       
  • Intelligent windows for electricity generation: A technologies review

    • Free pre-print version: Loading...

      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
       
  • Development of acoustic computer simulation for performance spaces: A
           systematic review and meta-analysis

    • Free pre-print version: Loading...

      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
       
  • Smart luminescent solar concentrator as a BICPV window

    • Free pre-print version: Loading...

      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
       
  • Digital ID framework for human-centric monitoring and control of smart
           buildings

    • Free pre-print version: Loading...

      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
       
  • Energy-saving and economic analysis of passive radiative sky cooling for
           telecommunication base station in China

    • Free pre-print version: Loading...

      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
       
  • A novel coordinated control for NZEB clusters to minimize their connected
           grid overvoltage risks

    • Free pre-print version: Loading...

      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
       
  • Direct capture efficiency of range hoods in the confined kitchen space

    • Free pre-print version: Loading...

      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
       
  • RETRACTED ARTICLE: IoT based residential energy management system for
           demand side response through load transfer with various types of domestic
           appliances

    • Free pre-print version: Loading...

      Abstract: The Editor-in-Chief has retracted this article. After publication, concerns were raised about the high similarity between this article and a previous publication from different authors (Duman et al. 2021). Specifically, similarities were identified in the text in the Literature Review and Methodology sections of this article and those in Duman et al. (2021). Additionally, Tables 2 and 3 appear to be copied from Duman et al. (2021). The authors were unable to provide satisfactory source data used in their analysis upon the Editor’s request. The Editor-in-Chief therefore no longer has confidence in the authenticity of the presented data and the originality of the work.
      Authors R Ganesh Babu and C Chellaswamy do not agree to this retraction.
      Authors V Amudha and K Senthil Kumar have not responded to any correspondence from the editor or publisher about this retraction. The online version of this article contains the full text of the retracted article as Supplementary Information.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-021-0817-4
       
  • Archetype identification and urban building energy modeling for city-scale
           buildings based on GIS datasets

    • Free pre-print version: Loading...

      Abstract: Abstract Urban building energy modeling has become an efficient way to understand urban building energy use and explore energy conservation and emission reduction potential. This paper introduced a method to identify archetype buildings and generate urban building energy models for city-scale buildings where public building information was unavailable. A case study was conducted for 68,966 buildings in Changsha city, China. First, clustering and random forest methods were used to determine the building type of each building footprint based on different GIS datasets. Then, the convolutional neural network was employed to infer the year built of commercial buildings based on historical satellite images from multiple years. The year built of residential buildings was collected from the housing website. Moreover, twenty-two building types and three vintages were selected as archetype buildings to represent 59,332 buildings, covering 87.4% of the total floor area. Ruby scripts leveraging on OpenStudio-Standards were developed to generate building energy models for the archetype buildings. Finally, monthly and annual electricity and natural gas energy use were simulated for the blocks and the entire city by EnergyPlus. The total electricity and natural gas use for the 59,332 buildings was 13,864 GWh and 23.6×106 GJ. Three energy conservation measures were evaluated to demonstrate urban energy saving potential. The proposed methods can be easily applied to other cities in China.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-021-0878-4
       
  • Developing occupant archetypes within urban low-income housing: A case
           study in Mumbai, India

    • Free pre-print version: Loading...

      Abstract: Abstract Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-022-0889-9
       
  • Robustness of ventilation systems in the control of walking-induced indoor
           fluctuations: Method development and case study

    • Free pre-print version: Loading...

      Abstract: Abstract Walking-induced fluctuations have a significant influence on indoor airflow and pollutant dispersion. This study developed a method to quantify the robustness of ventilation systems in the control of walking-induced fluctuation control. Experiments were conducted in a full-scale chamber with four different kinds of ventilation systems: ceiling supply and side return (CS), ceiling supply and ceiling return (CC), side supply and ceiling return (SC), and side supply and side return (SS). The measured temperature, flow and pollutant field data was (1) denoised by FFT filtering or wavelet transform; (2) fitted by a Gaussian function; (3) feature-extracted for the range and time scale disturbance; and then (4) used to calculate the range scale and time scale robustness for different ventilation systems with dimensionless equations developed in this study. The selection processes for FFT filtering and wavelet transform, FFT filter cut-off frequency, wavelet function, and decomposition layers are also discussed, as well as the threshold for wavelet denoising, which can be adjusted accordingly if the walking frequency or sampling frequency differs from that in other studies. The results show that for the flow and pollutant fields, the use of a ventilation system can increase the range scale robustness by 19.7%–39.4% and 10.0%–38.8%, respectively; and the SS system was 7.0%–25.7% more robust than the other three ventilation systems. However, all four kinds of ventilation systems had a very limited effect in controlling the time scale disturbance.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-022-0888-x
       
  • Analysing user daylight preferences in heritage buildings using virtual
           reality

    • Free pre-print version: Loading...

      Abstract: Abstract Technology has always been creating effective ways to support human decisions. Immersive virtual reality (IVR) has emerged to engage users in a simulated world, and this has gained the interest of a wide variety of users in the heritage industry. A historical case study built in the early 19th century is considered for an adaptive reuse exhibition. The palace is located in Cairo, Egypt, and named after Prince Omar Tosson. The current palace state incorporates a smashed top-lit zone, which is being studied and analyzed for daylighting adequacy. Three simulated distinct optimum skylight configurations are suggested for the redesign where the selection should not be based solely on simulation data, but should consider real-user preferences. Most daylight design criteria are previously based on simulation data that do not necessarily indicate the users’ preferences. But utilizing user interactive tools such as IVR to test daylight redesign options, a whole new dimension is provided. In this study, the VR users’ survey data is statistically analyzed using Statistical Package for Social Sciences (SPSS), where results revealed that the assessment attributes succeeded in reflecting the users’ preferences; which, motivated designers to consider potential users’ daylight preferences in reused spaces. The paper highlights the most significant emotional attributes that provide cost-effective and reliable information concerned with the performance of daylight in IVR before design implementation. This study compares and analyzes the effect of three skylight designs (Cases A, B & C) on the users’ perception before design implementation using (IVR) post-survey. Forty-eight participants have contributed to the study, providing their feedback on six attributes namely: Pleasant, Contrasting, Brightness, Uniform Distribution, Visual Comfort, and Satisfaction. Those attributes are evaluated for the three cases in space using five scale rating values to reveal that the “Pleasant” attribute is most reliable in the study to reflect the users’ preferences for design Case B.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-021-0873-9
       
  • Spatio-temporal distribution of gaseous pollutants from multiple sources
           in industrial buildings with different flow patterns

    • Free pre-print version: Loading...

      Abstract: Abstract Energy consumption of industrial buildings has remained continuously high, and the environmental quality requirements are also constantly improving. Only by improving industrial environmental control technology based on the transport mechanism of the pollution, can the energy consumption of industrial building environmental control be further reduced, and the environmental quality of industrial buildings can be improved as well. Therefore, after verifying the numerical simulation by experiments, this study uses a self-label method to investigate the spatio-temporal distribution of gaseous pollutants from multiple time-series sources in industrial plants with different length—span ratios. The results show that, the polluted flow in plants with different aspect ratios have different flow patterns: (i) the “Back-mixing” flow pattern occurs when the ratio of ventilation rate G and polluted flow rate at the exhaust height LP is less than 1, i.e., G/LP < 1, and (ii) the “One-way” flow pattern occurs when G/LP > 1. For plants with the “Back-mixing” pattern, the following source pollutants enter a density stratified environment induced by the retained pre-source pollutants. The flow of following source pollutants released at the same intensity as the precursor source can reach the roof, while those with low velocity and density difference may be blocked during the ascending process. The maximum height zm of the flow of the following source is related to both the initial Froude number Fr0 of the following source and the unsteady vertical density gradient of the fluid in the indoor environment dρa/dz. For plants with the “One-way” pattern, the flow from the following source enters into an environment with approximately uniform density. Under the condition of positive buoyancy, design parameters of ventilation corresponding to the vicinity of G/LP = 1 may be the optimal solution for safety and energy conservation.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-022-0886-z
       
  • Comparison of detached eddy simulation and standard k—ε RANS model for
           rack-level airflow analysis inside a data center

    • Free pre-print version: Loading...

      Abstract: Abstract High computing demands and data privacy regulations from many countries in the world have resulted in the expansion of data centers. With this, energy consumption by data centers has increased to an alarming level. Data centers are highly dynamic due to time-dependent server heat generation and cold-hot aisle arrangements, making it difficult to have real-time control for efficient thermal management. Traditional cooling strategies based on conservative set points affect energy consumption. Instead of expensive field measurements, CFD analysis of the flow field inside the data center can provide insightful data to assist the heat release from the racks. The detailed rack-level flow field inside the data center is missing in the literature as most of the studies are based on approximate results using the RANS-based k—ε model. However, DES-based models have shown the ability to resolve complex flow fields. With this finding, rack-level CFD analysis of the data center is performed using DES and standard k—ε techniques. At first, average rack inlet and outlet air temperatures in steady-state were validated with experiments within the accuracy of 1.4 µC. The distributions of turbulent kinetic energy and mean velocity inside the cold aisle were examined. The recirculation region in the cold aisle was well-captured by the DES and qualitatively validated with the experiments compared to the k—ε model. The k—ε model failed to predict SHI, RTI, and β metrics, whereas the DES model successfully captured recirculation and self-heating of the upper servers. An acceptable trade-off between computational cost and accuracy for the simulations would be a pivotal parameter for the selection of either DES or the k—ε model for the data center CFD analysis. The porous media assumption of the servers can bring uncertainties for turbulent quantities and hence further DES model for a data center can provide additional insights in this study.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-021-0879-3
       
  • Energy analysis of a wood or pellet stove in a single-family house
           equipped with gas boiler and radiators

    • Free pre-print version: Loading...

      Abstract: Abstract In the residential sector, biomass appliances are widely used for space heating and often combined with other systems. This work aims at comparing the final and primary energy consumption of different configurations, including a conventional and a ducted pellet stove and a wood log stove using air as heat transfer fluid. A dynamic analysis of the interaction between biomass stoves and conventional heating systems, such as gas boilers and radiators, is carried out within a typical single-family house in a mild climate, using TRNSYS software. In addition, natural ventilation of the building is considered using CONTAM, with a focus on external infiltrations and internal air circulation due to the buoyancy effect. Results show that the biomass device in one room promotes the airflows between adjacent thermal zones, enhancing the heat distribution through door openings, in particular when an air ducted stove is present. The final energy consumption resulting from simulations with wood-burning stoves is 21% higher than pellet stoves. The pellet stove results in similar final energy and a 30% increase in overall primary energy, while the wood stove increases the final energy by 22% and approximately 40% of overall primary energy compared to the case of a traditional gas system coupled to radiators which is considered as reference. Nevertheless, non-renewable primary energy savings are higher than 50% with pellet stoves and 60% with wood-log stoves.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-022-0884-1
       
  • CFD simulation of wind and thermal-induced ventilation flow of a roof
           cavity

    • Free pre-print version: Loading...

      Abstract: Abstract The hygrothermal performance of a ventilated roof cavity is greatly affected by the airflow passing through it. This ventilation flow is mainly driven by the wind pressure difference between openings and the thermal-induced buoyancy. However, the wind effect is not well understood as it is often neglected in previous studies. The present study investigates the properties of such airflows, including the flow pattern, flow regime, and flow rate, using a CFD method. The target building is a large-span commercial building with a low-pitched roof. To study the wind-induced airflows, the onset atmospheric boundary layer wind flow was modelled, and the results were compared with the site-measured data recorded in the literature. To study the thermal-induced buoyancy effects, a roof cavity model found in the literature with experimental data was adopted. The findings show that the flow pattern in the roof cavity varied with the airflow driven factors. The flow separation at the windward eave inlet of the thermally induced flows are more pronounced compared with those of the wind-induced flows. Furthermore, the wind-induced airflows can generate around two times more ventilation flow rate through the roof cavity compared to the thermal-induced airflow. The findings indicate that wind-induced ventilation flows are the dominant factor of the roof cavity ventilation in a large-span, low-pitched building.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-021-0880-x
       
  • Daily power demand prediction for buildings at a large scale using a
           hybrid of physics-based model and generative adversarial network

    • Free pre-print version: Loading...

      Abstract: Abstract Power demand prediction for buildings at a large scale is required for power grid operation. The bottom-up prediction method using physics-based models is popular, but has some limitations such as a heavy workload on model creation and long computing time. Top-down methods based on data driven models are fast, but less accurate. Considering the similarity of power demand patterns of single buildings and the superiority of generative adversarial network (GAN), this paper proposes a new method (E-GAN), which combines a physics-based model (EnergyPlus) and a data-driven model (GAN), to predict the daily power demand for buildings at a large scale. The new E-GAN method selects a small number of typical buildings and utilizes EnergyPlus models to predict their power demands. Utilizing the prediction for those typical buildings, the GAN then is adopted to forecast the power demands of a large number of buildings. To verify the proposed method, the E-GAN is used to predict 24-hour power demands for a set of residential buildings. The results show that (1) 4.3% of physics-based models in each building category are required to ensure the prediction accuracy; (2) compared with the physics-based model, the E-GAN can predict power demand accurately with only 5% error (measured by mean absolute percentage error, MAPE) while using only approximately 9% of the computing time; and (3) compared with data-driven models (e.g., support vector regression, extreme learning machine, and polynomial regression model), E-GAN demonstrates at least 60% reduction in prediction error measured by MAPE.
      PubDate: 2022-09-01
      DOI: 10.1007/s12273-022-0887-y
       
  • Temporal-spatial risk assessment of COVID-19 under the influence of urban
           spatial environmental parameters: The case of Shenyang city

    • Free pre-print version: Loading...

      Abstract: Abstract Respiratory infection is the main route for the transmission of coronavirus pneumonia, and the results have shown that the urban spatial environment significantly influences the risk of infection. Based on the Wells-Riley model of respiratory infection probability, the study determined the human respiratory-related parameters and the effective influence range; extracted urban morphological parameters, assessed the ventilation effects of different spatial environments, and, combined with population flow monitoring data, constructed a method for assessing the risk of Covid-19 respiratory infection in urban-scale grid cells. In the empirical study in Shenyang city, a severe cold region, urban morphological parameters, population size, background wind speed, and individual behavior patterns were used to calculate the distribution characteristics of temporal and spatial concomitant risks in urban areas grids under different scenarios. The results showed that the correlation between the risk of respiratory infection in urban public spaces and the above variables was significant. The exposure time had the greatest degree of influence on the probability of respiratory infection risk among the variables. At the same time, the change in human body spacing beyond 1 m had a minor influence on the risk of infection. Among the urban morphological parameters, building height had the highest correlation with the risk of infection, while building density had the lowest correlation. The actual point distribution of the epidemic in Shenyang from March to April 2022 was used to verify the evaluation results. The overlap rate between medium or higher risk areas and actual cases was 78.55%. The planning strategies for epidemic prevention and control were proposed for the spatial differentiation characteristics of different risk elements. The research results can accurately classify the risk level of urban space and provide a scientific basis for the planning response of epidemic prevention and control and the safety of public activities.
      PubDate: 2022-08-10
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 3.238.225.8
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-