Energy Consumption In Regions Research Articles

Regional vehicle energy consumption evaluation framework to quantify the benefits of vehicle electrification in plateau city: A case study of Xining, China

Vehicle electrification holds significant potential for driving both decarbonization and improved energy efficiency within the realm of road transportation. However, accurate quantification of energy consumption advantages offered by electric vehicles (EVs) has remained elusive, thus impeding their long-term development due to variations across cities and vehicle types. To address this challenge, we propose a novel regional vehicle energy consumption assessment framework that integrates a region-specific driving cycle (DC) database and advanced high-precision energy consumption models. The regional DC database is constructed using a Markov chain approach. The database is stochastic and diverse, while taking into account real driving features and regional geographic environments. Energy consumption models for internal combustion engine vehicle (ICEV), plug-in hybrid electric vehicle (PHEV) and battery electric vehicle (BEV) are constructed based on machine learning approach. These models have good generalization ability and prediction accuracy, with R2 of 0.86, 0.86 and 0.77 on the test set, respectively. According to the interpretability of the models, vehicle acceleration and vehicle specific power are considered to be the most important features affecting vehicle energy consumption. According to the evaluation results, compared to using ICEV, the promotion of PHEV and BEV in Xining, a plateau city, can reduce energy consumption by 27.83 % and 32.05 %, respectively. The framework not only unifies the scale of energy consumption evaluation among different vehicle types, but also its good generalization ability can be migrated and extended to the evaluation of vehicle energy consumption in various regions. The establishment of this framework will contribute to the promotion and popularization of electric vehicles, as well as the advancement of energy-saving initiatives in the transportation sector.

In-situ U-value measurements of typical building envelopes in a severe cold region of China: U-value variations and energy Implications

Building energy consumption in the severe cold regions of China is an important consideration in building energy conservation because of the high amount of energy consumed by heating. As an important thermal parameter, the thermal transmittance (U-value) of building envelopes can directly affect the operational energy consumption of buildings. Understanding the U-values of buildings in severe cold regions is important to predict building energy accurately. However, the U-values of envelopes fluctuate constantly due to environmental impacts. Therefore, this study aimed to examine the influence of dynamic U-values on building energy efficiency. To achieve this, this study focused on the in-situ measurement of the U-values of two typical building envelopes in Harbin from winter to summer in 2023 to determine the average and dynamic U-values of the tested envelope, comprising a brick envelope and reinforced concrete (RC) envelope. The building energy simulation results based on theoretical U-values were compared with the measured average and dynamic U-values of the tested envelopes. The findings revealed that the fluctuations in the U-values were significant. In the dynamic U-values of tested brick and RC envelopes, the U-values in winter were 159.8% and 30.8% higher than those in summer, respectively. Furthermore, the dynamic U-values significantly influenced heating energy consumption, with an increase of up to 15.9%.

Effect of urban morphology on microclimate and building cluster energy consumption in cold regions of China

Building energy consumption (BEC) is influenced by the combination of urban morphology and microclimate. This study investigated the influence of urban neighborhood morphology on microclimate and building energy consumption through sixty representative street blocks in cold regions of China. The following conclusions were drawn from the multiple regression analysis, and random forest (RF) in this research: 1) The impact of urban morphology on microclimate and vice versa on energy use intensity (EUI) varies according to the season. 2) Annual temperature (TEMP.), solar radiation (SR), building site cover (BSC), average building height (BH), road area ratio (RAR), and block orientation (BO) were significantly positively correlated with EUI, and the floor area ratio (FAR) was negatively correlated. 3) The FAR is positively correlated with BEC and has a significant negative correlation with relative humidity (RH) which contribution rates are 82.3 % and 7.3 %, respectively. Based on the analysis, the research proposed feasible recommendations to optimize the layout of blocks. The results of this study can be used to predict the energy consumption of new and existing street blocks in cold-climate cities quickly and accurately. Additionally, it provides quantitative strategies for energy-saving and emission reduction in urban planning.

Optimization of optical properties of nanocomposite films incorporating CWO and ITO nanoparticles for energy-saving window applications

Cesium tungsten oxide (CWO) and indium tin oxide (ITO) nanoparticles are potential candidates for application in energy-saving windows. However, most optical studies on these nanocomposite films lack systematic evaluation and design methods. In this work, the optical properties of spherical and cylindrical CWO and ITO nanoparticles under different geometric parameters based on the Lorenz–Mie and T-matrix theories are investigated, and spectral responses of CWO-PDMS and ITO-PDMS windows are calculated by solving the radiative transfer equation (RTE) using the Monte Carlo method. By evaluating and optimizing the geometric parameters of the nanocomposite films, energy-saving windows exhibit excellent optical performance, with a visible light transmittance that meets the indoor needs of the human eye (Tlum is about 0.6), and can shield most near-infrared light, especially CWO-PDMS windows (TNIR=0.04). Finally, a building energy consumption simulation analysis based on Energy Plus is conducted in three different cities: Jinan, Hong Kong, and Singapore. The results indicate that by adjusting the geometric parameters of nanoparticles, energy-saving windows can effectively reduce energy consumption in tropical and subtropical regions. This work provides guidance for the subsequent commercialization and experimental analysis of spectral selective composite films.

Impact of Urban Morphology on High-Density Commercial Block Energy Consumption in Severe Cold Regions

In sustainable city development, urban form plays an important role in block energy consumption, and as different environmental contexts and block functions create differences in energy use, it is necessary to study the relationship between morphology and energy consumption under the dual constraints of special environments and special block functions. Urban high-density blocks have concentrated energy consumption, high energy intensity, and complex morphological layout, but the influencing mechanism of the block’s morphology on its energy consumption remains unclear. Accordingly, this study focuses on the mechanism and evaluation method of the influence of morphology on the energy consumption of high-density commercial blocks in severe cold regions. Through Grasshopper model extraction, EnergyPlus performance simulation, Pearson correlation analysis, and linear regression analysis, this study extracts and classifies high-density commercial blocks in Harbin, China, into six basic layout types (Courtyard, Courtyard-T, Slab, Slab-T, Point, Point-T) according to their horizontal and vertical morphology, analyzes the energy consumption characteristics of each basic type, examines the relationships between energy use intensity (EUI) and building density (BD) and between floor area ratio (FAR) and building height standard deviation (BHSD), and constructs theoretical models by controlling variables to study the effect of a single form parameter on block EUI. The research findings are as follows: (1) The annual energy consumption of Point and Slab blocks is relatively low, whereas that of Courtyard and Courtyard-T blocks is higher due to the lack of open space in Courtyards and the poor ventilation in summer. (2) FAR is significantly correlated with the energy consumption of high-density commercial blocks in severe cold regions, while the effects of BD and BHSD are weaker than those of FAR. For every 0.1 increase in BD, every 1 increase in FAR, and every 1(m) increase in BHSD, the Winter Daily EUI of the Slab block changes by +0.87, −2.26, and −0.22 (kWh/m2), respectively, whereas that of the Slab-T block changes by −0.38, +0.68, and +0.08 (kWh/m2), respectively. (3) Controlling other variables, a large BD is theoretically beneficial to energy performance in the blocks, and increasing BD in the range of 0.4–0.55 has a significant effect on lowering energy consumption in Point blocks. EUI increases with the increase in FAR, while the change depends on different block types with the increase in BHSD. This study provides design strategies for high-density commercial blocks in severe cold regions. Under different layout types, though EUI shows different relationships with BD, FAR, and BHSD, Slab-T and Point-T blocks can achieve excellent energy performance by appropriately increasing BD and decreasing FAR, whereas Slab blocks need to decrease BD while increasing FAR. The patterns found in this paper can provide strategic help for policymaking and early urban design.

Driving factors and decoupling analysis of carbon emissions from energy consumption in high energy-consuming regions: a case study of Liaoning province

Driving factors and decoupling analysis of carbon emissions from energy consumption in high energy-consuming regions: a case study of Liaoning province

State Management of Energy Efficiency Improvement in Agricultural Regions of the Russian Federation

The sustainable development of the Russian Federation and its subjects, associated with limiting the negative impact of economic entities on the environment and ensuring the rational use of natural resources of the territory, is not just following the modern trends of the international community to reduce the energy intensity of the national economy, but also economic expediency caused by increasing the competitiveness and energy efficiency of economic entities and regions of the country by reducing energy costs in production products. Agriculture as one of the energy-intensive sectors of the economy (the second after industry, which accounts for over 12% of electricity consumption in the country) is characterized by a significant diversity in the levels and rates of energy consumption in different regions of the country, which of course requires consideration in public administration and implementation of regional energy conservation policies. In this regard, the article proposes a typological grouping of agricultural regions of Russia, which is based on the growth rates of energy production, energy consumption, agricultural production and the share of agriculture in regional energy consumption. The originality of the study lies in the fact that on the basis of a geographically sectoral approach, the grouping of agricultural regions of the country is carried out not according to the actual volumes of agricultural products produced (as it is typical in such cases), but according to the amount of energy resources (electricity) consumed by agriculture in a particular subject of the Russian Federation, which allows obtaining more relevant data. The research results obtained in this way allow us to develop incident measures and additive mechanisms for improving energy efficiency, taking into account the specifics of the energy development of the industry and the trends of sustainable development of the region. The article contains elements of novelty in the formulation of the problem and the research methodology presented by the typology of agricultural regions of Russia. The article contributes to the evaluation of management decisions at the regional level in the framework of the implementation of energy conservation policy and the application of regional energy efficiency programs.

The combine impact of stock market, international investment and clean energy consumption on ecological footprint in emerging countries

PurposeEmerging nations strive to diminish their ecological impact to meet net-zero targets, yet encounter formidable hurdles in curbing their environmental footprint. This purpose necessitated the study into impact of stock market, renewable energy and international investment on the ecological footprint in emerging countries from 1990 to 2020.Design/methodology/approachThe study used augmented mean group (AMG) estimator, cointegration and heterogenous panel causality approach.FindingsResults from the AMG show that renewable energy consumption reduces environmental pollution in most countries except Mexico. The study disclosed that stock market capitalization decreases ecological footprint in emerging countries. Using both the Kao and Pedroni cointegration methods, the study affirms the existence of stable equilibrium relationship in the long term. The causality test concluded a bidirectional relationship between stock market and ecological footprint and a unidirectional link between international investment, clean energy and ecological footprint.Research limitations/implicationsThe research is limited to only emerging countries. Therefore, future research should examine the environmental impacts of renewable energy consumption in different countries and regions, taking into account the local environmental conditions, policies and practices. This would help to identify the best practices and standards for minimizing the ecological footprint of renewable energy technologies and maximizing their benefits for environmental sustainability.Practical implicationsThe study found that stock market capitalization reduces ecological footprint in Brazil, China, Turkey and India. To foster a culture of sustainability in stock market development impact, academic policies should emphasize the integration of environmental education across disciplines. By promoting awareness of the ecological consequences of stock market activities, societies can cultivate a mindset that values responsible economic practices. This, in turn, can lead to informed decision-making at individual and institutional levels.Social implicationsFirst, since the study found that clean energy reduces ecological footprint, advocating for utilization of clean energy sources could be a key priority in emerging countries. Governments should incentivize the development and adoption of renewable energy technologies, such as wind and solar power, by providing subsidies and tax benefits. Furthermore, increasing awareness among residents about the benefits of clean energy and promoting its utilization in both residential and commercial environments can expedite the transition to a more environmentally friendly energy combination.Originality/valueFirst, it pioneers an exploration into the interplay between stock market capitalization, international investment, clean energy and ecological footprint in emerging countries. Secondary unlike, unlike prior research, this study uses methodologies that account for cross-sectional dependencies and a unique characteristic specific to each country. In addition, by using common correlated effects mean group, AMG, cointegration and causality procedures, this study distinctly isolates and analyzes empirical findings for each country, leading to policy-oriented outcomes.

Novel MOF-based autonomous humidity control materials for energy-efficient indoor moisture regulation

The concept of autonomous humidity control material (AHCM) is inspired by phase change material. AHCM is a new type of functional sorbent material. It can adsorb/release sufficient water vapor at the target relative humidity level and autonomously maintain the indoor relative humidity at a set value/range without external intervention, which cannot be achieved by conventional sorbents (e.g., zeolite, silica gel, etc.). In this study, a novel metal-organic framework (MOF) based AHCM is prepared, and its application for energy-efficient indoor moisture control has been investigated. The new MOF-AHCM has an S-shaped water vapor isotherm, large porosity, and high moisture adsorption capacity. The trigger points for adsorption and desorption occur at 60 % and 40 % RH, respectively. It means MOF-AHCM can autonomously regulate the indoor relative humidity to fall within 40%–60 % RH, which fits the thermal comfort range recommended by ASHRAE well. The physicochemical and hygrothermal characteristics of the synthesized MOF-ACHM have been assessed. Full-scale chamber tests were carried out to verify the humidity control ability of the new material. The experimental results show that MOF-AHCM can significantly mitigate indoor humidity fluctuation and regulate the humidity level within the target range autonomously. Furthermore, numerical simulation has been performed to investigate the impact of MOF-AHCM on building energy consumption in different moisture regions globally, namely, arid, semiarid, dry, moist, and wet areas. The results reveal that MOF-AHCM has an excellent humidity control capacity and can reduce the latent cooling demand of HVAC systems in most climates, especially in arid, semiarid, dry, and moist areas.

Spatio-temporal prediction of total energy consumption in multiple regions using explainable deep neural network

Energy consumption forecasting is essential for energy system integration and management. However, existing studies mainly focus on temporal features of energy consumption, which neglects the spatial correlation of variables with time information. Capturing the spatio-temporal relationships helps to improve forecasting accuracy and further promote energy dispatch. To tackle this problem, an explainable Convolutional Neural Network-Long Short Term Memory forecasting model is employed to effectively predict the total energy consumption by capturing the spatial and temporal features of multivariate time series. In the model, the autoencoder is used to achieve the nonlinear dimensionality reduction and transfer the data to a low-dimensional space. Furthermore, a Convolutional Neural Network is used to extract more effective features from the decoded data, and long short-term memory is employed to identify the temporal dependencies between extracted features and total energy consumption. Shapley additive explanation is introduced to interpret the outputs of the black-box model. The superior performance of the proposed method with high accuracy and good adaptability is verified by the comparisons with conventional forecasting models. This method provides an insight into the regional energy consumption analyzing contributions of weather variables to energy consumption, which helps administers in understanding regional energy performance for enhancing energy efficiency.

Study on the Influence of the Application of Phase Change Material on Residential Energy Consumption in Cold Regions of China

As the impact of climate change intensifies, meeting the energy demand of buildings in China’s cold regions is becoming increasingly challenging, particularly in terms of cooling energy consumption. The effectiveness of integrating phase change material (PCM) into building envelopes for energy saving in China’s cold regions is unclear. The aim of this study is to assess the effectiveness of PCM integration in building enclosures for energy efficiency in these regions. The research monitored and recorded indoor temperature data from typical residential cases from May to September. This measured data was then used to validate the accuracy of EnergyPlus22-1 software simulation models. Subsequently, the calibrated model was utilized to conduct a comparative analysis on the effects of PCM on indoor temperatures and cooling energy consumption across these regions. The results of these comparative analyses indicated that PCM can alleviate indoor overheating to varying degrees in severe cold regions of China. Focusing on north-facing bedrooms, applying PCMs reduced the duration of overheating in non-air-conditioned buildings in severe cold regions of China by 136 h (Yichun), 340 h (Harbin), 356 h (Shenyang), and 153 h (Dalian). In terms of cooling energy consumption, the energy saved by applying PCMs ranged from 1.48 to 13.83 kWh/m2. These results emphasize that the performance of PCM varies with climate change, with the most significant energy-saving effects observed in severe cold regions. In north-facing bedrooms in Harbin, the energy-saving rate was as high as 60.30%. Based on these results, the study offers guidance and recommendations for feasible passive energy-saving strategies for buildings in severe cold and cold regions of China in the face of climate change. Additionally, it provides practical guidance for applying PCMs in different climatic zones in China.

Renewable energy consumption - financial globalization-tourism nexus with nonlinearity and cross-sectional dependence during Asia's carbon-free transition.

Adopting renewable energy consumption is one of the most important aspects of international efforts to combat climate change, improve energy security, and encourage the shift to a more robust and sustainable energy system. Therefore, the empirics and policymakers worldwide are searching for factors that can promote renewable energy consumption. This analysis intends to investigate the role of financial globalization and tourism on renewable energy consumption in Asia and sub-regions such as Central Asia, East Asia, South Asia, Southeast Asia, and West Asia. The analysis utilized the linear and nonlinear CS-ARDL methods. Long-run outcomes of the linear and nonlinear models confirm that a rise in financial globalization and tourism promotes renewable energy consumption in Asia and all sub-regions. However, the nonlinear model highlights that a fall in financial globalization hurts renewable energy consumption in Central and South Asian regions, and tourism only hurts renewable energy consumption in Asia. In addition, ICT, GDP, and GHG emissions help promote renewable energy consumption. These results suggest that Asian policymakers must increase collaboration in the financial sectors and promote sustainable tourism in the regions to promote renewable energy consumption.

Research on energy-saving strategies in the architectural design of the Eastern Railway in the era of artificial intelligence

Abstract This paper takes the air conditioning energy consumption in railroad building design as the main object of analysis and uses an orthogonal experimental design method to study the influencing factors and effects of energy consumption in the Middle East railroad construction design. Stochastic working condition simulation is carried out for the typical models of passenger stations in five climate zones to obtain the data set of the passenger station energy consumption model, and the multiple linear regression prediction models of air conditioning energy consumption in different regions are established. Combined with the hour-by-hour average outdoor temperature, hour-by-hour passenger flow and lighting and related equipment data in the waiting hall of a city in July, the air-conditioning cold load of railroad passenger stations is simulated and analyzed. Explore the implementation effect of energy-saving strategies for railroad passenger station air-conditioning system, and for the traditional PID control strategy, put forward the control strategy based on model prediction, analyze the change of centralized air-conditioning system cold load and the change of the actual performance coefficient of the chiller unit under different control strategies. The data show that compared with the traditional PID control, the model prediction control reduces the total energy consumption by 0.2063, which realizes the energy-saving optimization of the air conditioning system for railroad building design.

Multi objective optimization for house roof using artificial neural network model

Roof models with low heat loss and low heating costs for buildings are crucial for reducing energy consumption and greenhouse gas emissions in cold regions. This study aimed to calculate the heat loss for various roof models with low heat loss, which are widely used in houses in Europe and other cold regions. We created 324 models for three types of roofs (light, medium, and heavy) with different materials and thicknesses using the HAP program. We then trained a neural network (ANN) to generate a mathematical function that can be used to calculate the optimal surface using a multi-objective genetic algorithm method. The resulting optimal roof design was simulated using the Ansys program on a January day. We compared the heat loss results for the optimal roof for HAP, ANN, and transient thermal analysis by Ansys, respectively, showing a close agreement among the methods.

Comprehensive assessment of building energy consumption in hot summer and cold winter areas based on carbon tax considerations

With the rapid development of economy and urbanization in China, cities are expanding rapidly and more constructions are being built, then lead to the fast-growing part in urban residential energy consumption. In China’s hot summer and cold winter regions, many buildings are not centrally heated and commonly rely on electrical equipment such as air conditioners which are all energy-inefficient thermoregulation devices. In order to analyze the relationship between building energy consumption and the energy efficiency ratio (EER) of air conditioning and the area of photovoltaic (PV) on the roof, the influence of the building envelope on building energy consumption in hot summer and cold winter regions in China is clarified. This paper uses energy plus software to analyze the impact of different EER and PV area on building energy consumption using a typical case study of a public health upgrading project in the eastern part of the Wuxing district, Huzhou, Zhejiang province in China. The simulation results show that the factor that has a greater impact on the energy consumption of the health center in summer is the PV area parameter of the building compared to the performance parameters of the air conditioning equipment. The PV area parameter settings and air conditioning equipment performance adjustments are dependent on the actual situation and the comprehensive energy saving rate of the outpatient building for public health in the eastern part of Tai Wu Xing District can exceed 50%. Finally, an economic analysis of the carbon tax and input costs is carried out, and the best combination is of which 60% of the area covered by Longi Green PV panels and an air conditioning efficiency ratio of 4.87. The research result combines renewable energy and efficient equipment to achieve dual optimization of environmental and economic aspects of building energy consumption, while providing reference opinions on the comprehensive evaluation method of building energy consumption from the perspective of carbon tax.

Historical peak situation of building carbon emissions in different climate regions in China: Causes of differences and peak challenges

The climatic conditions in different regions of China are complex and diverse, and the characteristics of building energy consumption in different climatic regions are quite different, leading to significant differences in the historical peak situation of building carbon emissions (BCE). Based on the statistical Mann–Kendall (MK) trend test method, this study evaluates the historical peak situation of BCE in different climate regions in China and discusses the reasons for the differences in the growth trends and peak situations of BCE in these regions. Furthermore, according to the characteristics of building energy consumption in different climate regions, the challenges faced by each climate region in promoting the peaking of BCE are highlighted. The research results show that owing to the continuous increase in the proportion of electrification and clean energy power generation, the electricity emission factor and carbon emissions per unit of energy consumption continue to decline, and the growth rates of BCE in the transitional and southern regions are significantly lower than the growth rate of building energy consumption, and the carbon emissions per unit floor area in the southern region has reached its peak. The main obstacles to promoting the peaking of BCE in the northern heating region are the high‑carbon heating energy structure and the unrestrained heating behavior of residents, while the challenges faced by the transitional and southern regions are the southward migration of the population and economic centers of gravity and the gradual increase in residents' requirements for living environment comfort. Government decision-makers should formulate differentiated BCE peaking strategies according to the characteristics of building energy consumption in different climate regions.

Permeable reactive composite approaching cathode enhanced Cr removal in soil using the byproduct of electrokinetic technology: emphasized energy utilization efficiency.

Cost-effective techniques with significant removal rates and low energy consumption are urgently required for in-situ Cr-contaminated soil remediation to reduce potential environmental toxicity to the ecosystem and human bodies. Electrokinetic technology is a valuable and promising soil remediation technology; however, the acidic and alkaline fronts evolutioninduced by the electrokinetic byproducts (H+, OH-) has significant hindering characteristics for ion removal. To effectively utilize the byproducts for enhancing Cr elimination, this paper proposed the permeable reactive composite approaching cathode with rhamnolipid-modified biochar as reactive material. Power utilization efficiency (η) was presented to comprehensively evaluate the target species elimination effect, considering removal rate and energy consumption. Results suggested that biosurfactant rhamnolipid stimulated Cr removal in acid and base fronts. Acid front induced rhamnolipid protonation reducing anolyte Cr(VI) to Cr(III), and base front induced rhamnolipid deprotonation complexing with Cr(III) and expediting Cr(VI) dissolution by electrostatic repulsion. Permeable reactive composite approaching cathode induced the maximum removal rate of Cr(VI) and Cr(III) in each section by impelling the alkaline front. Approaching cathode caused increased resistance and energy consumption in the near-anode regions, ultimately decreasing energy utilization efficiency. Optimized moving frequency and applied potential magnitude could adjust power consumption distribution in a single soil layer to obtain better electrokinetic removal performance of contaminates. This work provided essential scientific and practical importance for in-situ electrokinetic remediation of Cr(VI) and Cr(III), considering elimination efficiency and energy consumption in the future.

Increasing the Energy Performance of Existing Buildings in Cold Climate Regions

High energy consumption in regions with harsh climatic conditions makes it difficult to reach energy consumption targets. This study considers design decisions affecting energy consumption for cold climate regions; the position of the building, its orientation, building envelope elements and building materials were examined. In line with these decisions, a field study was conducted by researching the energy-efficient renovation of existing social housing structures in cold climate regions. For the field study, social housing in Erzurum was selected, and the current heating energy consumption of the building was simulated using the Design Builder program. By creating energy-efficient renewal scenarios that can be economically and physically enacted, the U-values and thicknesses of the building envelope elements were changed, and 14 renewal simulations were carried out for five scenarios. The effects of each renovation scenario on the current heating energy consumption were examined, and the results were compared. With the most efficient replacement scenario, it was observed that the heating energy consumption decreased by an average of 31%. The data obtained informed decisions for building envelope element selection within the scope of energy-efficient renewal studies in cold climate regions and their impact on energy consumption.

The Impact of Residential Cluster Layout on Building Energy Consumption and Carbon Emissions in Regions with Hot Summers and Cold Winters in China

Since the early 2010s, building energy consumption in regions in China with hot summers and cold winters has experienced an average annual growth rate of 6.5%, while building carbon emissions demonstrated an average annual growth rate of 3.7%. This underscores the pressing need to reduce building energy consumption and carbon emissions. The layout of residential clusters plays a critical role in determining the effective shading coefficient, which directly impacts solar radiation gain and subsequently affects energy consumption and carbon emissions. To explore this correlation and optimize the layout configuration of residential clusters to achieve the objective of minimizing energy consumption and carbon emissions in buildings, our study employed ECOTECT 2011 software to assess the layout attributes of different residential clusters through an analysis of the effective shading coefficient. Furthermore, using VirVil-HTB2 17_04_21 software, we simulated the solar radiation, building energy consumption, and carbon emissions for different residential cluster layouts. To examine the interplay between solar radiation, energy consumption, and carbon emissions, SPSS 27 software was used. The findings revealed that different residential cluster configurations exhibit unique effective shading coefficients, substantially influencing the solar radiation received by buildings and, consequently, their thermal performance. Our research reveals that adopting a staggered layout can lead to a reduction in average operating energy consumption by up to 2.23% and cooling energy consumption by up to 7.17%, compared to an enclosed layout. Similarly, enclosed layouts can contribute to a decrease in heating energy consumption by up to 4.06%, in contrast to courtyard layouts. Additionally, scattered layouts can effectively reduce carbon emissions by up to 0.95% when compared to courtyard layouts.

Numerical explorations of the vortex-induced vibration of a streamlined box girder with water-filled barriers

The present study aims to investigate the charactefristics of vortex-induced vibrations (VIVs) of a streamlined box girder equipped with water-filled barriers (WFBs) through two-dimensional computational fluid dynamics (CFD) simulations. Initially, the VIV behavior of the bridge section is examined by considering various positions of WFBs and angles of attack (α), focusing on parameters involving vibration amplitude, surface pressure distribution, and flow field. Subsequently, in order to reveal the underlying VIV mechanism, the bridge section with WFBs commonly positioned was chosen to evaluate the contribution or inhibition of wind loads on specific regions around the bridge's surface to VIV, based on the pressure distribution and energy input process characteristics. The numerical results demonstrate that if the WFBs are positioned closer to the railing on the windward side of the bridge, as α shifts from negative to positive, the separated vortex on the upper surface of the bridge section tends to be larger. Additionally, the shedding of vortices at the tail of the deck becomes more pronounced, creating a greater periodic force on the bridge section and making it more vulnerable to VIV. The mean and standard deviations of pressure coefficients, as well as the predominant frequencies of the distributed pressures, are closely correlated with various stages of the VIV development process. The occurrence of VIV is actively triggered by the wind load acting on the upper surface upstream and lower surface downstream, while conversely, the wind load acting on the downstream of the upper surface and the upstream of the lower surface tends to inhibit the VIV. Moreover, it is worth noting that the growth rate of energy consumption on the downstream of upper surface is more significant than that of energy consumption in other regions, which makes a main effect on limiting the amplitude of VIV.