A smart load-speed sensitive cooling map to have a high- performance thermal management system in an internal combustion engine

Considering the fact that electrification is increasingly used in internal combustion engines, this paper aims at presenting a smart speed-load sensitive cooling map for better thermal management. For this purpose, first, thermal boundary conditions for the engine cooling passage were obtained by thermodynamic and combustion simulation. Next, the temperature distribution of the cooling passage walls was determined using conjugate heat transfer method. Then, the effect of engine load on wall temperature distribution was investigated, and it was observed that in the conventional mode where the cooling flow is only affected by the engine speed, the engine is faced with over-cooling and under-cooling. Therefore, the optimum flow for cooling the engine was achieved in such a way that the engine is hot enough and kept free from damage, while the engine has a more uniform temperature distribution. These calculations were performed by considering the boiling phenomenon. The results showed using the cooling map leads to a significant reduction in coolant flow, which in turn reduces the power consumption of the water pump and size of the radiator. Moreover, fuel consumption, hydrocarbon emission production, and the needed power of the coolant pump are enhanced by 2.1, 8.6, and 44.3%, respectively.Irankhodro Powertrain Company (IPCo)http://www.elsevier.com/locate/energy2022-04-22hj2021Mechanical and Aeronautical Engineerin

Machine learning prediction approach for dynamic performance modeling of an enhanced solar still desalination system

An enhanced design for a solar still desalination system which has been proposed in the previously conducted study of the research team is considered here, and the experimental data obtained during a year are employed to develop ANN models for that. Different types of artificial neural network (ANN), as one of the most popular machine learning approaches, are developed and compared together to find the best of them to predict the hourly produced distillate and water temperature in the basin, which are two key performance criteria of the system. Feedforward (FF), backpropagation (BP), and radial basis function (RBF) types of ANN are examined. According to the results, by having the coefficients of determination of 0.963111 and 0.977057, FF and RBF types are the best ANN structures for estimation of the hourly water production and water temperature in the basin, respectively. In addition, the annual error analysis done for the data not used to develop ANN models demonstrates that the average error in prediction of the hourly distillate production and water temperature in the basin varies from 9.03 and 5.13% in January (the highest values) to 4.06 and 2.07% in July (the lowest values), respectively. Moreover, the error for prediction of the daily water production is in the range of 2.41 to 5.84% in the year.http://link.springer.com/journal/109732022-04-13hj2021Mechanical and Aeronautical Engineerin

Using computational fluid dynamics for different alternatives water flow path in a thermal photovoltaic (PVT) system

Please read abstract in the article.https://www.emerald.com/insight/publication/issn/0961-5539hj2021Mechanical and Aeronautical Engineerin

Using Building Integrated Photovoltaic Thermal (BIPV/T) Systems to Achieve Net Zero Goal: Current Trends and Future Perspectives

The rising world population and increasing shift toward reducing greenhouse gas (GHG) emissions have highlighted the importance of cleaner and more-efficient technologies such as solar energy harvesting systems. Among these, building integrated photovoltaic (BIPV) and building integrated photovoltaic thermal (BIPV/T) systems are considered to be superior in supplying electrical and thermal demands while also enhancing the attractiveness of the buildings to which they are attached. This chapter introduces this technology and explains its role in achieving both net zero energy buildings (NZEBs) and net zero emission (NZE) targets. First, the BIPV/T concept is introduced, and then the processes of simulating BIPV/T system performance in both free and forced convection conditions are explained. Next, net zero targets are defined, and a number of studies that have tried to help meet net zero goals using BIPV and BIPV/T systems are reviewed. The chapter ends with concluding remarks and suggestions for future work.KeywordsEnergy efficiencyNet zero emissionNet zero energy buildingDesignMulti-objective optimizationBuilding facadeEnvironmental protectionPerformance modelin