Electricity generation around the world is mainly produced by using non-renewable energy sources especially in the commercial buildings. However, Rooftop solar Photovoltaic (PV) system produced a significant impact on environmental and economical benefits in comparison to the conventional energy sources, thus contributing to sustainable development. Such PV’s system encourages the production of electricity without greenhouse gas emissions that leads to a clean alternative to fossil fuels and economic prosperity even in less developed areas. However, efficiency of rooftop solar PV systems depends on many factors, the dominant being geographical (latitude, longitude, and solar intensity), environmental (temperature, wind, humidity, pollution, dust, rain, etc.) and the type of PV (from raw material extraction and procurement, to manufacturing, disposal, and/or recycling) used. During the feasibility analysis of the environment, geographical conditions are keep in well consideration, but the pollution level of the city is always overlooked, which significantly influences the performance of the PV installations.     

Therefore, this research work focused on the performance of rooftop solar PV installed in one of the most polluted city in India. Here, the loss in power generation of rooftop solar PV has been studied for the effect of deposited dust particles, wind velocity before and after the cleaning of the panels. The actual data has been utilized for the calculation of the energy efficiency and power output of the PV systems. According to the results, it has been concluded that dust deposition, wind speed and pollution level in city significantly reduces the efficiency of solar photovoltaic panel. Hence, an overview of social and environmental impacts of PV technologies is presented in this paper along with potential benefits and pitfalls.

This paper presents a coupling of the Monte Carlo method with computational fluid dynamics (CFD) to analyze the flow channel design of an irradiated target through numerical simulations. A novel series flow channel configuration is proposed, which effectively facilitates the removal of heat generated by high-power irradiation from the target without necessitating an increase in the cooling water flow rate. The research assesses the performance of both parallel and serial cooling channels within the target, revealing that, when subjected to equivalent cooling water flow rates, the maximum temperature observed in the target employing the serial channel configuration is lower. This reduction in temperature is ascribed to the accelerated flow of cooling water within the serial channel, which subsequently elevates both the Reynolds number and the Nusselt number, leading to enhanced heat transfer efficiency. Furthermore, the maximum temperature is observed to occur further downstream, thereby circumventing areas of peak heat generation. This phenomenon arises because the cooling water traverses the target plates with the highest internal heat generation at a lower temperature when the flow channels are arranged in series, optimizing the cooling effect on these targets. However, it is crucial to note that the pressure loss associated with the serial structure is two orders of magnitude greater than that of the parallel structure, necessitating increased pump power and imposing stricter requirements on the target container and cooling water pipeline. These findings can serve as a reference for the design of the cooling channels in the target station system, particularly in light of the anticipated increase in beam power during the second phase of the China Spallation Neutron Source (CSNS Ⅱ).

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

Introduction, purpose of the study: In Central Europe, in Hungary, the state guarantees access to health care and basic health services partly through the Semmelweis Plan adopted in 2011. The Health Plan aims to optimize and transform the health system. The objectives of hospital integration, as set out in the Plan, started with the state ownership of municipal hospitals in 2012, continued with the launch of integration processes in 2012–2013 and culminated today. The transformation of a health system can have an impact on health services and thus on meeting the needs of the population. We aim to study the effectiveness of integration through access to CT diagnostic testing. Our hypothesis is that integration has resulted in increased access to modern diagnostic services. The specialty under study is computed tomography (CT) diagnostic care. Our research shows that the number of people receiving CT diagnostic care has increased significantly because of integration, which has also brought a number of positive benefits, such as reduced health inequalities, reduced travel time, costs and waiting lists. Test material and method: Our quantitative retrospective research was carried out in the hospital of Kalocsa through document analysis. The research material was comparing two time periods in the Kalocsa site of Bács-Kiskun County, Southern Hungary. The number of patients attending CT examinations by area of duty of care according to postal codes was collected: Pre-integration period 2014.01.01–2017.11.30. (Kalocsa did not have CT equipment, so patients who appeared in Kecskemét Hospital but were under the care of Kalocsa), post-integration period 2017.12.01–2019.12.31. (period after the installation of CT in Kalocsa). The target group of the study consisted of women and men together, aged 0–99 years, who appeared for a CT diagnostic examination. The study sample size was 6721 persons. Linear regression statistics were used to evaluate the results. Based on empirical experience, a SWOT analysis was carried out to further investigate the effectiveness of integration. Results: As a result of the integration, the CT scan machine purchased in the Kalocsa District Hospital has enabled an average of 129.7 patients per month to receive CT scans on site without travelling. The model used is significant, explaining 86% of the change in the number of patients served (F = 43.535; p < 0.001, adjusted R² = 0.860). The variable of integration in the model is significant, with an average increase in the number of patients served of 129.7 per month (t = 22.686; p < 0.001) following the introduction of CT due to integration. None of the month variables representing seasonal effects were found to be significant, with no seasonal effect on care. The SWOT analysis has clearly identified the strengths, weaknesses, opportunities and threats related to the integration, the main outcome of which is the acquisition of a CT diagnostic tool. Conclusions: Although we only looked at one segment of the evidence for the effectiveness of hospital integration, integration in the study area has had a positive impact on CT availability, reducing disparities in care.