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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: 277)
Statistics in Medicine     Hybrid Journal   (Followers: 142)
Journal of Econometrics     Hybrid Journal   (Followers: 85)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 77, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Biometrics     Hybrid Journal   (Followers: 49)
Sociological Methods & Research     Hybrid Journal   (Followers: 49)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 42)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 41, SJR: 3.664, CiteScore: 2)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 37)
Annals of Applied Statistics     Full-text available via subscription   (Followers: 36)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 36)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 34)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 30)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 25)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 23)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 19)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 18)
Statistical Modelling     Hybrid Journal   (Followers: 18)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 18)
Journal of Statistical Software     Open Access   (Followers: 18, SJR: 13.802, CiteScore: 16)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Computational Statistics     Hybrid Journal   (Followers: 16)
Risk Management     Hybrid Journal   (Followers: 16)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Demographic Research     Open Access   (Followers: 14)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Journal of Statistical Physics     Hybrid Journal   (Followers: 12)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 11)
International Statistical Review     Hybrid Journal   (Followers: 10)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 10)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 10)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Current Research in Biostatistics     Open Access   (Followers: 9)
Stata Journal     Full-text available via subscription   (Followers: 9)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Lifetime Data Analysis     Hybrid Journal   (Followers: 6)
Significance     Hybrid Journal   (Followers: 6)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Statistical Methods and Applications     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
Statistical Papers     Hybrid Journal   (Followers: 4)
TEST     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 3)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
Stochastic Models     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)
Building Simulation     Hybrid Journal   (Followers: 2)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
International Journal of Stochastic Analysis     Open Access   (Followers: 2)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Sequential Analysis: Design Methods and Applications     Hybrid Journal   (Followers: 1)
Wiley Interdisciplinary Reviews - Computational Statistics     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  

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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  [2468 journals]
  • Erratum to: Research on the influence of outdoor trees on natural
           ventilation performance of an academic building

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      PubDate: 2024-04-01
       
  • Experimental study on the CO2 concentration and age of air distribution
           inside tiny sleeping spaces

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      Abstract: Abstract In recent years, rapid urban development has led to capsule hotels, sleep pods, and other tiny sleeping spaces that adapt to people’s fast-paced lives, achieving maximum functionality with a very small footprint. However, due to the small space, human metabolic pollutant (such as CO2) is more likely to accumulate, and the air is not easily circulated. In this paper, a full-size experimental platform is set up with three types of ventilation modes to explore the exclusion efficiency of metabolic pollutants and the overall distribution of age of air under these ventilation modes. The conclusions showed that the mean values of metabolic pollutant exclusion rates for the different ventilation modalities varied very little across the spatial dimensions of the confined space but varied considerably in the area around the head. The double-side attached ventilation method was the most effective in removing human metabolic pollutants, especially in the head region (CN ≥ 0.92), while the single-wall attached ventilation method had the best air exchange efficiency (η ≥ 0.85). This suggests an inconsistent distribution of CO2 and age of air, which is contrary to general common sense. The conclusions of this paper can guide the design of ventilation for tiny sleeping spaces.
      PubDate: 2024-04-01
       
  • An optimization-oriented modeling approach using input convex neural
           networks and its application on optimal chiller loading

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      Abstract: Abstract Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller plants. The optima obtained by model-based optimization algorithms are dependent on precise and solvable objective functions. The classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities, resulting in a reduction in the robustness of model-based optimization. In this paper, we leverage the input convex neural networks (ICNN) to identify the chiller model to construct a convex mapping between control variables and the objective function, which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading (OCL). Approximation performances are evaluated through a four-model comparison based on an experimental data set, and the statistical results show that, on the premise of retaining prior convexities, the proposed model depicts excellent approximation power for the data set, especially the unseen data. Finally, the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization strategies. Compared with conventional and meta-heuristic methods, the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.
      PubDate: 2024-04-01
       
  • Potential application of radiant floor cooling systems for residential
           buildings in different climate zones

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      Abstract: Abstract A radiant floor cooling system (RFCS) is a high-comfort and low energy consumption system suitable for residential buildings. Radiant floor systems usually work with fresh air, and their operating performance is affected by climatic conditions. Indoor and outdoor environmental disturbances and the system’s control strategy affect the indoor thermal comfort and energy efficiency of the system. Firstly, a multi-story residential building model was established in this study. Transient system simulation program was used to study the operation dynamics of three control strategies of the RFCS based on the calibrated model. Then, the performance of the control strategies in five climate zones in China were compared using multi-criteria decision-making in combination. The results show that control strategy has a negligible effect on condensation risk, but the thermal comfort and economic performance differ for different control strategies. The adaptability of different control strategies varies in different climate zones based on the consideration of multiple factors. The performance of the direct-ground cooling source system is better in Hot summer and warm winter zone. The variable air volume control strategy scores higher in Serve cold and Temperate zones, and the hours exceeding thermal comfort account for less than 3% of the total simulation period. Therefore, it is suggested to choose the RFCS control strategy for residential buildings according to the climate zone characteristics, to increase the energy savings. Our results provide a reliable reference for implementing RFCSs in residential buildings.
      PubDate: 2024-04-01
       
  • Optimizing urban block morphologies for net-zero energy cities: Exploring
           photovoltaic potential and urban design prototype

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      Abstract: Abstract The morphology of urban areas plays a crucial role in determining solar potential, which directly affects photovoltaic capacity and the achievement of net-zero outcomes. This study focuses on the City of Melbourne to investigate the utilization of solar energy across different urban densities and proposes optimized morphologies. The analysis encompasses blocks with diverse population densities, examining medium and high-density areas. By utilizing a multi-objective genetic optimization approach, the urban morphology of these blocks is refined. The findings indicate that low-density blocks exhibit photovoltaic potential ranging from 1 to 6.6 times their total energy consumption. Medium and high-density blocks achieve photovoltaic potential levels approximately equivalent to 40%–85% of their overall energy consumption. Moreover, significant variations in photovoltaic potential are observed among different urban forms within medium and high-density blocks. An “elevated corners with central valley” prototype is proposed as an effective approach, enhancing the overall photovoltaic potential by approximately 14%. This study introduces novel analytical concepts, shedding light on the intricate relationship between urban morphologies and photovoltaic potential.
      PubDate: 2024-04-01
       
  • The effects of cool materials, fa├žade orientation, and morphological
           parameters on energy consumption at the residential neighborhood scale

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      Abstract: Abstract Building surface cool materials are novel materials that can reduce urban heat island intensity and decrease building energy consumption. This study investigated the impact of radiative properties of materials, façade orientation, and morphological parameters on energy consumption in six typical residential neighborhoods in Nanjing, China. The neighborhood energy consumption of 16 application schemes considering the façade orientation factor is compared to determine the best energy-saving scheme. Seasonal and annual energy-saving rates, savings in electricity costs, and the price ceiling for materials per unit area are analyzed. The results show that for low-rise buildings, using cool materials only on the roof can reduce the annual energy consumption by 1%. When cool or super cool materials are also used on the building façade, the annual energy saving rate can be up to 3.4% and 4.3%, respectively. Using cool materials on the south façade of buildings is not recommended due to significant heat loss in winter. Considering savings in electricity costs and the price ceiling for materials per unit area, the price of cool and super cool materials should be less than 3.0 and 3.7 RMB/m2, respectively, assuming a lifespan of eight years in Nanjing.
      PubDate: 2024-04-01
       
  • Enhancing source domain availability through data and feature transfer
           learning for building power load forecasting

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      Abstract: Abstract During the initial phases of operation following the construction or renovation of existing buildings, the availability of historical power usage data is limited, which leads to lower accuracy in load forecasting and hinders normal usage. Fortunately, by transferring load data from similar buildings, it is possible to enhance forecasting accuracy. However, indiscriminately expanding all source domain data to the target domain is highly likely to result in negative transfer learning. This study explores the feasibility of utilizing similar buildings (source domains) in transfer learning by implementing and comparing two distinct forms of multi-source transfer learning. Firstly, this study focuses on the Higashita area in Kitakyushu City, Japan, as the research object. Four buildings that exhibit the highest similarity to the target buildings within this area were selected for analysis. Next, the two-stage TrAdaBoost.R2 algorithm is used for multi-source transfer learning, and its transfer effect is analyzed. Finally, the application effects of instance-based (IBMTL) and feature-based (FBMTL) multi-source transfer learning are compared, which explained the effect of the source domain data on the forecasting accuracy in different transfer modes. The results show that combining the two-stage TrAdaBoost.R2 algorithm with multi-source data can reduce the CV-RMSE by 7.23% compared to a single-source domain, and the accuracy improvement is significant. At the same time, multi-source transfer learning, which is based on instance, can better supplement the integrity of the target domain data and has a higher forecasting accuracy. Overall, IBMTL tends to retain effective data associations and FBMTL shows higher forecasting stability. The findings of this study, which include the verification of real-life algorithm application and source domain availability, can serve as a theoretical reference for implementing transfer learning in load forecasting.
      PubDate: 2024-04-01
       
  • Comparison of models to predict air infiltration rate of buildings with
           different surrounding environments

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      Abstract: Abstract The air infiltration rate of buildings strongly influences indoor environment and energy consumption. In this study, several traditional methods for determining the air infiltration rate were compared, and their accuracy in different scenarios was examined. Additionally, a method combining computational flow dynamics (CFD) with the Swami and Chandra (S-C) model was developed to predict the influence of the surrounding environment on the air infiltration rate. Two buildings in Dalian, China, were selected: one with a simple surrounding environment and the other with a complex surrounding environment; their air infiltration rates were measured. The test results were used to validate the accuracy of the air infiltration rate solution models in different urban environments. For the building with a simple environment, the difference between the simulation and experimental results was 0.86%–22.52%. For the building with a complex environment, this difference ranged from 17.42% to 159.28%. We found that most traditional models provide accurate results for buildings with simple surrounding and that the simulation results widely vary for buildings with complex surrounding. The results of the method of combining CFD with the S-C model were more accurate, and the relative error between the simulation and test results was 10.61%. The results indicate that the environment around the building should be fully considered when calculating the air infiltration rate. The results of this study can guide the application of methods of determining air infiltration rate.
      PubDate: 2024-04-01
       
  • Seasonal thermal energy storage using natural structures: GIS-based
           potential assessment for northern China

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      Abstract: Abstract Seasonal thermal energy storage (STES) allows storing heat for long-term and thus promotes the shifting of waste heat resources from summer to winter to decarbonize the district heating (DH) systems. Despite being a promising solution for sustainable energy system, large-scale STES for urban regions is lacking due to the relatively high initial investment and extensive land use. To close the gap, this study assesses the potentials of using two naturally available structures for STES, namely valley and ground pit sites. Based on geographical information system (GIS) methods, the available locations are searched from digital elevation model and selected considering several criteria from land uses and construction difficulties. The costs of dams to impound the reservoir and the yielded storage capacities are then quantified to guide the choice of suitable sites. The assessment is conducted for the northern China where DH systems and significant seasonal differences of energy demand exist. In total, 2,273 valley sites and 75 ground pit sites are finally identified with the energy storage capacity of 15.2 billion GJ, which is much larger than the existing DH demand in northern China. The results also prove that 682 valley sites can be achieved with a dam cost lower than 20 CNY/m3. By conducting sensitivity analysis on the design dam wall height and elevations, the choices of available natural structures are expanded but practical issues about water pressures and constructions are also found. Furthermore, the identified sites are geographically mapped with nearest urban regions to reveal their roles in the DH systems. In general, 560 urban regions are found with potential STES units and most of them have STES storage capacities larger than their own DH demand. The novel planning methodology of this study and publicly available datasets create possibilities for the implementations of large-scale STES in urban DH systems.
      PubDate: 2024-04-01
       
  • A theoretical study on gaseous pollutant flushing of natural ventilation
           driven by buoyancy forces in industrial buildings

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      Abstract: Abstract The acceleration of industrialization worsening indoor environments of industrial buildings has drawn more attention in recent years. Natural ventilation can improve indoor air quality (IAQ) and reduce carbon emissions. To evaluate gaseous pollutant levels in industrial buildings for the development of buoyancy-driven natural ventilation, two theoretical models of pollutant flushing (Model I and Model II) are developed based on the existing thermal stratification theory in combination with the mixing characteristics of lower pollutant. The results show that indoor pollutant flushing is mainly dependent on the pollution source intensity and effective ventilation area. The mixing characteristics of lower pollutant has an important effect on pollutant stratification and evolution during ventilation, but it does not change the prediction results at steady state. When the dimensionless pollution source intensity is larger than 1, the pollution source should be cleaned up or other ventilation methods should be used instead to improve IAQ. In addition, the comparisons between Model I and Model II on instantaneous pollutant concentration are significantly influenced by the pollution source intensity, and the actual pollutant concentration is more likely to be between the predicted values of Model I and Model II. To reduce pollutant concentration to a required level, the pollution source intensity should be in a certain range. The theoretical models as well as the necessary conditions for ventilation effectiveness obtained can be used for the ventilation optimization design of industrial buildings.
      PubDate: 2024-04-01
       
  • The recirculation flow after different cross-section shaped high-rise
           buildings with applications to ventilation assessment and drag
           parameterization

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      Abstract: Abstract The building cross-section shape significantly affects the flow characteristics around buildings, especially the recirculation region behind the high-rise building. Eight generic building shapes including square, triangle, octagon, T-shaped, cross-shaped, #-shaped, H-shaped and L-shaped are examined to elucidate their effects on the flow patterns, recirculation length L and areas A using computational fluid dynamics (CFD) simulations with Reynolds-averaged Navier-Stokes (RANS) approach. The sizes and positions of the vortexes behind the buildings are found to be substantially affected by the building shapes and subsequently changing the recirculation flows. The recirculation length L is in the range of 1.6b–2.6b with an average of 2b. The maximum L is found for L-shaped building (2.6b) while the shortest behind octagon building (1.6b). The vertical recirculation area Av is in the range of 1.5b2–3.2b2 and horizontal area Ah in 0.9b2–2.2b2. The L, Av and Ah generally increase with increasing approaching frontal area when the wind direction changes but subject to the dent structures of the #-shaped and cross-shaped buildings. The area-averaged wind velocity ratio (AVR), which is proposed to assess the ventilation performance, is in the range of 0.05 and 0.14, which is around a three-fold difference among the different building shapes. The drag coefficient parameterized by Ah varies significantly, suggesting that previous models without accounting for building shape effect could result in large uncertainty in the drag predictions. These findings provide important reference for improving pedestrian wind environment and shed some light on refining the urban canopy parameterization by considering the building shape effect.
      PubDate: 2024-04-01
       
  • Numerical modeling of all-day albedo variation for bifacial PV systems on
           rooftops and annual yield prediction in Beijing

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      Abstract: Abstract Bifacial PV modules capture solar radiation from both sides, enhancing power generation by utilizing reflected sunlight. However, there are difficulties in obtaining ground albedo data due to its dynamic variations. To address this issue, this study established an experimental testing system on a rooftop and developed a model to analyze dynamic albedo variations, utilizing specific data from the environment. The results showed that the all-day dynamic variations in ground albedo ranged from 0.15 to 0.22 with an average of 0.16. Furthermore, this study evaluates the annual performance of a bifacial PV system in Beijing by considering the experimental conditions, utilizing bifacial modules with a front-side efficiency of 21.23% and a bifaciality factor of 0.8, and analyzing the dynamic all-day albedo data obtained from the numerical module. The results indicate that the annual radiation on the rear side of bifacial PV modules is 278.90 kWh/m2, which accounts for only 15.50% of the front-side radiation. However, when using the commonly default albedo value of 0.2, the rear-side radiation is 333.01 kWh/m2, resulting in an overestimation of 19.40%. Under dynamic albedo conditions, the bifacial system is predicted to generate an annual power output of 412.55 kWh/m2, representing a significant increase of approximately 12.37% compared to an idealized monofacial PV system with equivalent front-side efficiency. Over a 25-year lifespan, the bifacial PV system is estimated to reduce carbon emissions by 8393.91 kgCO2/m2, providing an additional reduction of 924.31 kgCO2/m2 compared to the idealized monofacial PV system. These findings offer valuable insights to promote the application of bifacial PV modules.
      PubDate: 2024-03-25
       
  • Extraction method of typical IEQ spatial distributions based on low-rank
           sparse representation and multi-step clustering

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      Abstract: Abstract Indoor environment quality (IEQ) is one of the most concerned building performances during the operation stage. The non-uniform spatial distribution of various IEQ parameters in large-scale public buildings has been demonstrated to be an essential factor affecting occupant comfort and building energy consumption. Currently, IEQ sensors have been widely employed in buildings to monitor thermal, visual, acoustic and air quality. However, there is a lack of effective methods for exploring the typical spatial distribution of indoor environmental quality parameters, which is crucial for assessing and controlling non-uniform indoor environments. In this study, a novel clustering method for extracting IEQ spatial distribution patterns is proposed. Firstly, representation vectors reflecting IEQ distributions in the concerned space are generated based on the low-rank sparse representation. Secondly, a multi-step clustering method, which addressed the problems of the “curse of dimensionality”, is designed to obtain typical IEQ distribution patterns of the entire indoor space. The proposed method was applied to the analysis of indoor thermal environment in Beijing Daxing international airport terminal. As a result, four typical temperature spatial distribution patterns of the terminal were extracted from a four-month monitoring, which had been validated for their good representativeness. These typical patterns revealed typical environmental issues in the terminal, such as long-term localized overheating and temperature increases due to a sudden influx of people. The extracted typical IEQ spatial distribution patterns could assist building operators in effectively assessing the uneven distribution of IEQ space under current environmental conditions, facilitating targeted environmental improvements, optimization of thermal comfort levels, and application of energy-saving measures.
      PubDate: 2024-03-18
       
  • Predicting the clothing insulation through machine learning algorithms: A
           comparative analysis and a practical approach

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      Abstract: Abstract Since indoor clothing insulation is a key element in thermal comfort models, the aim of the present study is proposing an approach for predicting it, which could assist the occupants of a building in terms of recommendations regarding their ensemble. For that, a systematic analysis of input variables is exposed, and 13 regression and 12 classification machine learning algorithms were developed and compared. The results are based on data from 3352 questionnaires and 21 input variables from a field study in mixed-mode office buildings in Spain. Outdoor temperature at 6 a.m., indoor air temperature, indoor relative humidity, comfort temperature and gender were the most relevant features for predicting clothing insulation. When comparing machine learning algorithms, decision tree-based algorithms with Boosting techniques achieved the best performance. The proposed model provides an efficient method for forecasting the clothing insulation level and its application would entail optimising thermal comfort and energy efficiency.
      PubDate: 2024-03-16
       
  • Investigation of acoustic attributes based on preference and perceptional
           acoustics of Korean traditional halls for optimal design solutions

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      Abstract: Abstract Immersed in the rich tapestry of traditional culture, Gugak, the traditional Korean music stands as a captivating embodiment of artistic expression. This study embarked on a comprehensive evaluation of a Gugak hall, employing acoustic measurements, computer simulations, and subjective perception surveys. The evaluation focused on the reverberance, clarity, spatial impression, and preference, unravelling the secrets that shape the immersive Gugak experience. Through intricate computer simulations and auralization, the experience of Gugak performances was meticulously brought to life, allowing exploration under diverse conditions by adjusting stage volume ratios from −20% to +20% and modifying the interior materials, including the walls, ceiling, and lateral reflectors. Although Gugak halls exhibited relatively low values of reverberation time (RT), early decay time (EDT), and binaural quality index (BQI) the dominant factor influencing the acoustic environment was the effect of sound strength (G). Musical clarity (C80) value did not show an inverse proportionality to the reverberation time. Furthermore, genre differences between traditional Korean and Western classical music did not significantly affect listeners’ perception and satisfaction with regards to reverberance, clarity, and spatial impression. As a result, Gugak halls can adhere to the same acoustic design criteria as Western orchestra halls, since this study found that people perceived them the same way. In this study, sound strength was found to be strongly correlated with perception indicators. It was possible to enhance listeners’ perception and preference regarding the acoustic environment through material and structural changes to the sidewalls and ceiling. These changes improved the reinforcement of low frequencies and simultaneously enhanced the relative effect of side reflections. Additionally, enhancing the reflection and spatial characteristics of the materials effectively improved listener preference. Based on these findings, an optimal design solution was proposed.
      PubDate: 2024-03-15
       
  • Climate change induced heat stress impact on workplace productivity in a
           net zero-carbon timber building towards the end of the century

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      Abstract: Abstract Changing climate intensifies heat stress, resulting in a greater risk of workplace productivity decline in timber office buildings with low internal thermal mass. The impact of climate change induced heat exposure on indoor workplace productivity in timber office buildings has not been extensively researched. Therefore, further investigation to reduce the work capacity decline towards the end of the century is needed. Here, heat exposure in a net zero-carbon timber building near Brussels, Belgium, was evaluated using a reproducible comparative approach with different internal thermal mass levels. The analysis indicated that strategies with increased thermal mass were more effective in limiting the effects of heat exposure on workplace productivity. The medium and high thermal mass strategies reduced workplace productivity loss to 0.1% in the current, 0.3% and 0.2% in the midfuture, and 4.9% and 3.9% for future scenarios. In comparison, baseline with low thermal mass yielded a decline of 2.3%, 3.3%, and 8.2%. The variation in maximum and minimum wet-bulb globe temperatures were also lower for medium and high thermal mass strategies than for low thermal mass baseline. The study findings lead to the formulation of design guidelines, identification of research gaps, and recommendations for future work.
      PubDate: 2024-03-13
       
  • Systematic review of the efficacy of data-driven urban building energy
           models during extreme heat in cities: Current trends and future outlook

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      Abstract: Abstract Energy demand fluctuations due to low probability high impact (LPHI) micro-climatic events such as urban heat island effect (UHI) and heatwaves, pose significant challenges for urban infrastructure, particularly within urban built-clusters. Mapping short term load forecasting (STLF) of buildings in urban micro-climatic setting (UMS) is obscured by the complex interplay of surrounding morphology, micro-climate and inter-building energy dynamics. Conventional urban building energy modelling (UBEM) approaches to provide quantitative insights about building energy consumption often neglect the synergistic impacts of micro-climate and urban morphology in short temporal scale. Reduced order modelling, unavailability of rich urban datasets such as building key performance indicators for building archetypes-characterization, limit the inter-building energy dynamics consideration into UBEMs. In addition, mismatch of resolutions of spatio–temporal datasets (meso to micro scale transition), LPHI events extent prediction around UMS as well as its accurate quantitative inclusion in UBEM input organization step pose another degree of limitations. This review aims to direct attention towards an integrated-UBEM (i-UBEM) framework to capture the building load fluctuation over multi-scale spatio–temporal scenario. It highlights usage of emerging data-driven hybrid approaches, after systematically analysing developments and limitations of recent physical, data-driven artificial intelligence and machine learning (AI-ML) based modelling approaches. It also discusses the potential integration of google earth engine (GEE)-cloud computing platform in UBEM input organization step to (i) map the land surface temperature (LST) data (quantitative attribute implying LPHI event occurrence), (ii) manage and pre-process high-resolution spatio–temporal UBEM input-datasets. Further the potential of digital twin, central structed data models to integrate along UBEM workflow to reduce uncertainties related to building archetype characterizations is explored. It has also found that a trade-off between high-fidelity baseline simulation models and computationally efficient platform support or co-simulation platform integration is essential to capture LPHI induced inter-building energy dynamics.
      PubDate: 2024-03-11
       
  • Deep learning to develop zero-equation based turbulence model for CFD
           simulations of the built environment

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      Abstract: Abstract This study aims to improve the accuracy and speed of predictions for thermal comfort and air quality in built environments by creating a coupled framework between computational fluid dynamics (CFD) simulations and deep learning models. The coupling approach is showcased by the development of a data-driven turbulence model. The new turbulence model is built using a deep learning neural network, whose mapping structure is based on a zero-equation turbulence model for built environment simulations, and is coupled with the CFD software OpenFOAM to create a hybrid framework. The neural network is a standard shallow multi-layer perceptron. The number of hidden layers and nodes per layer was optimized using Bayesan optimization algorithm. The framework is trained on an indoor environment case study, as well as tested on an indoor office simulation and an outdoor building array simulation. Results show that the deep learning based turbulence model is more robust and faster than traditional two-equation Reynolds average Navier-Stokes (RANS) turbulence models, while maintaining a similar level of accuracy. The model also outperforms the standard algebraic zero-equation model due to its superior ability to generalize to various flow scenarios. Despite some challenges, namely the mapping constraint, the limited training dataset size and the source of generation of training data, the hybrid framework demonstrates the viability of the coupling technique and serves as a starting point for future development of more reliable and advanced models.
      PubDate: 2024-03-01
      DOI: 10.1007/s12273-023-1083-4
       
  • Mechanistic modeling of copper corrosions in data center environments

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      Abstract: Abstract Air-side economizers are increasingly used to take advantage of “free-cooling” in data centers with the intent of reducing the carbon footprint of buildings. However, they can introduce outdoor pollutants to indoor environment of data centers and cause corrosion damage to the information technology equipment. To evaluate the reliability of information technology equipment under various thermal and air-pollution conditions, a mechanistic model based on multi-ion transport and chemical reactions was developed. The model was used to predict Cu corrosion caused by Cl2-containing pollutant mixtures. It also accounted for the effects of temperature (25 °C and 28 °C), relative humidity (50%, 75%, and 95%), and synergism. It also identified higher air temperature as a corrosion barrier and higher relative humidity as a corrosion accelerator, which agreed well with the experimental results. The average root mean square error of the prediction was 13.7 Å. The model can be used to evaluate the thermal guideline for data centers design and operation when Cl2 is present based on pre-established acceptable risk of corrosion in data centers’ environment.
      PubDate: 2024-03-01
      DOI: 10.1007/s12273-023-1088-z
       
  • Evaluating different levels of information on the calibration of building
           energy simulation models

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      Abstract: Abstract A poorly calibrated model undermines confidence in the effectiveness of building energy simulation, impeding the widespread application of advanced energy conservation measures (ECMs). Striking a balance between information-gathering efforts and achieving sufficient model credibility is crucial but often obscured by ambiguities. To address this gap, we model and calibrate a test bed with different levels of information (LOI). Beginning with an initial model based on building geometry (LOI 1), we progressively introduce additional information, including nameplate information (LOI 2), envelope conductivity (LOI 3), zone infiltration rate (LOI 4), AHU fan power (LOI 5), and HVAC data (LOI 6). The models are evaluated for accuracy, consistency, and the robustness of their predictions. Our results indicate that adding more information for calibration leads to improved data fit. However, this improvement is not uniform across all observed outputs due to identifiability issues. Furthermore, for energy-saving analysis, adding more information can significantly affect the projected energy savings by up to two times. Nevertheless, for ECM ranking, models that did not meet ASHRAE 14 accuracy thresholds can yield correct retrofit decisions. These findings underscore equifinality in modeling complex building systems. Clearly, predictive accuracy is not synonymous with model credibility. Therefore, to balance efforts in information-gathering and model reliability, it is crucial to (1) determine the minimum level of information required for calibration compatible with its intended purpose and (2) calibrate models with information closely linked to all outputs of interest, particularly when simultaneous accuracy for multiple outputs is necessary.
      PubDate: 2024-02-24
       
 
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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: 277)
Statistics in Medicine     Hybrid Journal   (Followers: 142)
Journal of Econometrics     Hybrid Journal   (Followers: 85)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 77, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Biometrics     Hybrid Journal   (Followers: 49)
Sociological Methods & Research     Hybrid Journal   (Followers: 49)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 42)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 41, SJR: 3.664, CiteScore: 2)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 37)
Annals of Applied Statistics     Full-text available via subscription   (Followers: 36)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 36)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 34)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 30)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 25)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 23)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 19)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 18)
Statistical Modelling     Hybrid Journal   (Followers: 18)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 18)
Journal of Statistical Software     Open Access   (Followers: 18, SJR: 13.802, CiteScore: 16)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Computational Statistics     Hybrid Journal   (Followers: 16)
Risk Management     Hybrid Journal   (Followers: 16)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Demographic Research     Open Access   (Followers: 14)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Journal of Statistical Physics     Hybrid Journal   (Followers: 12)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 11)
International Statistical Review     Hybrid Journal   (Followers: 10)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 10)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 10)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Current Research in Biostatistics     Open Access   (Followers: 9)
Stata Journal     Full-text available via subscription   (Followers: 9)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Lifetime Data Analysis     Hybrid Journal   (Followers: 6)
Significance     Hybrid Journal   (Followers: 6)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Statistical Methods and Applications     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
Statistical Papers     Hybrid Journal   (Followers: 4)
TEST     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 3)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
Stochastic Models     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)
Building Simulation     Hybrid Journal   (Followers: 2)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
International Journal of Stochastic Analysis     Open Access   (Followers: 2)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Sequential Analysis: Design Methods and Applications     Hybrid Journal   (Followers: 1)
Wiley Interdisciplinary Reviews - Computational Statistics     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  

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School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


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