ABSTRACT
Air conditioning (AC) systems for tropical countries like India account for sixty percent of the total energy needs of a building. With the onset of COVID-19, the increase of fresh air ventilation rate has been recommended by various guidelines for indoor spaces which increase the load on the AC system. The present study attempts to reduce this burden through retrofitting a phase change material (PCM) embedded pin fin heat exchanger into an air-conditioning system. The heat exchanger is designed to cater to the peak load fluctuations for cities in three hot climatic zones of India, viz., Jaisalmer, Kolkata, and Delhi. Dodecanol with a melting temperature of 24 °C, is chosen as the appropriate PCM material for these locations. The optimal pin fin diameters are estimated through an entropy generation minimization analysis for the three locations. A heat transfer analysis of the PCM embedded heat exchanger is further presented through an analytical approach to estimate the PCM mass requirement and energy savings potential. The masses of the PCM estimated for Jaisalmer, Kolkata, and Delhi are 11.36 kg, 22.42 kg, and 19.35 kg, respectively for their respective peak load fluctuations of 0.25 kW, 0.28 kW and 0.48 kW. Energy savings of up to 4.7 % for Delhi, 2 % for Kolkata, and 2.75 % for Jaisalmer are identified with the PCM embedded heat exchanger incorporation. The results show the potential of such PCM thermal storage in reducing the peak energy demands of buildings amidst various environmental and health concerns.
ABSTRACT
The building sector continues to play an essential role in reducing worldwide energy consumption. The reduced consumption is accompanied by stricter regulation for the thermotechnical design of the building envelope. The redefined nearly Zero Energy Building levels that will come into force for each member state will pressure designers to rethink the constructive details so that mandatory levels can be reached, without increasing the construction costs over an optimum level but at the same time reducing greenhouse gas emissions. The paper aims to illustrate the main conclusions obtained in assessing the thermo-energy performance of a steel-framed building representing a holistically designed modular laboratory located in a moderate continental temperate climate, characteristic of the south-eastern part of the Pannonian Depression with some sub-Mediterranean influences. An extensive numerical simulation of the main junctions was performed. The thermal performance was established in terms of the main parameters, the adjusted thermal resistances and global thermal insulation coefficient. Further on, the energy consumption for heating was established, and the associated energy rating was in compliance with the Romanian regulations. A parametric study was done to illustrate the energy performance of the investigated case in the five representative climatic zones from Romania. An important conclusion of the research indicates that an emphasis must be placed on the thermotechnical design of Light Steel Framed solutions against increased thermal bridge areas caused by the steel’s high thermal conductivity for all building components to reach nZEB levels. Nevertheless, the results indicate an exemplary behaviour compared to classical solutions, but at the same time, the need for an iterative redesign so that all thermo-energy performance indicators are achieved.
ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19) has affected millions of people worldwide. The infection is mostly spread through the inhalation of infected droplets. Saudi Arabia is a vast country having different climatic conditions. METHODS: The study evaluated the influence of environmental factors on the spread of COVID-19. Six zones (A to F) were classified depending on the climatic conditions. The study was conducted by retrospective analysis of COVID-19 records from the ministry of health between the months of September 2020 and August 2021. The environmental data such as average temperature (°C), humidity (%), wind speed (m/s) and sun exposure (kwh/m2) were retrieved from official sites. The data was analyzed to determine the effect of these factors on the spread of COVID-19. SPSS IBM 25 software was used to conduct the analysis and p < 0.05 was considered to indicate the significance of the results. RESULTS: According to the findings, the rate of infection was greater between April and July 2021. Six climatic zones experienced high temperatures, little humidity, consistent wind flow, and intense sun exposure throughout this time. The correlation study revealed a significant (p < 0.05) relationship between the environmental factors and the spread of COVID-19. The data suggested that during summer condition when the weather is hot, less humid, and steady wind flow with lots of sun exposure, the COVID-19 infection rate got augmented in Saudi Arabia. Poor ventilation and closed-door habitats in an air-conditioned atmosphere during this period could have played a role in human transmission. More research on air quality, population mobility and diseased condition is essential, so that precise proactive measures can be designed to limit the spread of infection in specific climatic seasons.
ABSTRACT
• Hybrid ELM models (PSO-ELM, GA-ELM and ABC-ELM) were proposed for estimating ET 0 in different climate zones of China. • PSO-ELM model had the highest accuracy, followed by GA-ELM and ABC-ELM. • Hybrid ELM models outperformed standalone ELM and empirical models in different climate zones. • PSO-ELM model with T max , T min and RH obtained accurate ET 0 estimates in TCZ, SMZ and TMZ. • PSO-ELM model with only T max and T min was better performance on ET 0 estimates in MPZ. Accurate prediction of reference crop evapotranspiration (ET 0) is important for regional water resources management and optimal design of agricultural irrigation system. In this study, three hybrid models (PSO-ELM, GA-ELM and ABC-ELM) integrating the extreme learning machine model (ELM) with three biological heuristic algorithms, i.e., PSO, GA and ABC, were proposed for predicting daily ET 0 based on daily meteorological data from 2000 to 2019 at twelve representative stations in different climatic zones of China. The performances of the three hybrid ELM models were further compared with the standalone ELM model and three empirical models (Hargreaves, Priestley-Talor and Makkink models). The results showed that the hybrid ELM models (R 2 = 0.973–0.999) all performed better than the standalone ELM model (R 2 = 0.955–0.989) in four climatic regions in China. The estimation accuracy of the empirical models was relatively lower, with R2 of 0.822–0.887 and RMSE of 0.381–1.951 mm/d. The R 2 values of PSO-ELM, GA-ELM and ABC-ELM models were 0.993, 0.986 and 0.981 and the RMSE values were 0.266 mm/d, 0.306 mm/d and 0.404 mm/d, respectively, indicating that the PSO-ELM model had the best performance. When setting T max , T min and RH as the model inputs, the PSO-ELM model presented better performance in the temperate continental zone (TCZ), subtropical monsoon region (SMZ) and temperate monsoon zone (TMZ) climate zones, with R 2 of 0.892, 0866 and 0.870 and RMSE of 0.773 mm/d, 0.597 mm/d and 0.832 mm/d, respectively. The PSO-ELM model also performed in the mountain plateau region (MPZ) when only T max and T min data were available, with R2 of 0.808 and RMSE of 0.651 mm/d. All the three biological heuristic algorithms effectively improved the performance of the ELM model. Particularly, the PSO-ELM was recommended as a promising model realizing the high-precision estimation of daily ET 0 with fewer meteorological parameters in different climatic zones of China. [ FROM AUTHOR] Copyright of Journal of Hydrology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)