RESUMEN
Our world has had difficulty meeting humans' needs in recent years. To ensure that the world can sustain its inhabitability and self-sufficiency in terms of natural resources, it is required to make the total amount of biocapacity areas equal to or higher than the ecological footprint. An analytical study has been carried out to remedy the biocapacity deficit by utilizing this information for Turkey and then these areas are optimized with heuristic optimization techniques. As a result, Artificial Bee Colony provides better objective function results (fewer errors) compared to Particle Swarm Optimization and Global Optimization Method Based on Clustering and Parabolic Approximation in terms of minimum, maximum, average value, and standard deviation. The rates of change according to the current situation of the biocapacity areas in 2016 are 277.97 %, 30.28 %, -29.28 %, 14.97 %, and -44.85 % for cropland, grazing land, forestland, fishing grounds, and built-up land, respectively. Depending on the population growth, these rates should additionally change by 83.24 %, -0.69 %, 3.97 %, 6.22 %, and -14.24 % respectively in 2050. The developed model can be used in industry or within the frame of government development policy and thus the balance between ecological footprint and biocapacity can be kept under control.
Asunto(s)
Conservación de los Recursos Naturales , Turquía , Conservación de los Recursos Naturales/métodos , Ecosistema , EcologíaRESUMEN
Solar assisted heat pump (SAHP) systems aim to increase the performance of heat pumps by supporting with solar energy using various heating modes, whose performances depend on ambient conditions. In the literature, SAHP systems are classified by structure types, and the heating mode options are not considered as the main priority of the design but a result of the structure of the system. This paper aimed to investigate the effect of ambient conditions on heating modes, and identify the preferable ambient condition ranges for each SAHP system depends on their heating modes, by using a narrative review of 47 recent studies, that shed light on the problem. For this purpose, direct solar heating (DSH), air source heat pump (ASHP), solar source heat pump (SSHP) and solar-air source heat pump (S/ASHP) modes were stated as the basic heating modes of SAHP systems. In accordance with the literature, SAHP systems were classified as direct expansion solar assisted heat pump (DX-SAHP) and series, parallel and dual source indirect expansion solar assisted heat pumps (IDX-SAHP). Solar irradiation, ambient temperature, relative humidity and wind speed has been taken as major ambient conditions to investigate. Reviewed studies indicated that, parallel and series IDX-SAHP are preferable in high solar irradiations about 800 W/m2 with their DSH mode options. Frosting on evaporator is prevented in DX-SAHP with its S/ASHP mode, and even in the presence of frosting, unlike IDX-SAHPs ASHP mode, freezing is a factor that improves performance on flat evaporator in cold and humid conditions. This study indicates that there are obscure areas for future studies to focus on for a better comparison between SAHP types. Moreover, proposed novel designs of this paper, such as solar preheating of air in IDX-SAHP systems to add S/ASHP mode as an option, might enhance the performance and applicability of SAHP systems.
RESUMEN
In this study, confirmed COVID-19 cases of Denmark, Belgium, Germany, France, United Kingdom, Finland, Switzerland and Turkey were modeled with Auto-Regressive Integrated Moving Average (ARIMA), Nonlinear Autoregression Neural Network (NARNN) and Long-Short Term Memory (LSTM) approaches. Six model performance metric were used to select the most accurate model (MSE, PSNR, RMSE, NRMSE, MAPE and SMAPE). According to the results of the first step of the study, LSTM was found the most accurate model. In the second stage of the study, LSTM model was provided to make predictions in a 14-day perspective that is yet to be known. Results of the second step of the study shows that the total cumulative case increase rate is expected to decrease slightly in many countries.
RESUMEN
Everyday a large amount of sewage sludge is produced in cities and proper and environmentally friendly municipal wastewater treatment is needed. Finding a convenient and affordable way for sewage sludge refinement to reduce environmental pollution or even utilization of sewage sludge will be a very attractive challenge for scientists. In the recent years, sustainable and renewable energy sources like solar energy are extensively utilized in different fields including heating, electricity generation, and drying applications. In this study, V-groove triple-pass (V-TPSAH) and V-groove quadruple-pass (V-QPSAH) solar air heaters have been designed, manufactured and tested for drying municipal sewage sludge. Also, two different types of drying chambers (DC-I: conventional, DC-II: solar absorber) have been integrated with each solar heater. Experimental and numerical methods have been applied to analyze the efficiency of developed solar air heater assisted drying systems. The system's performance has been tested in different working conditions to clarify the utilization potential of manufactured system. According to the experimental results solar air heater's average efficiency are in the range of 70.12-81.70%. In addition, obtained experimental findings are in line with numerical results. The outcomes of this study present the potential of using the developed systems in drying municipal sewage sludge to be used in multi purposes.