Low molybdenum ultra-pure ferritic stainless steel for solar water heaters

In order to meet the demands of service life and the synthetical performance/price ratio of stainless steel in the solar water heater industry, the low molybdenum ultra-pure ferritic stainless steel （FSS） B445J1M was developed at Baosteel. In this study, comparative studies were carried out on the mechanical properties, the formability and the corrosion resistance of B445J1M ,304 and 444 ,and the advantages and application fields of B445J1M were summarized.

Performance of Water in Glass Evacuated Tube Solar Water Heater under Kenya Climatic Condition

Solar water heaters which provide a cost-effective and environmental friendly approach to hot water generation are in widespread application. Evacuated tube solar water heaters perform better than flat plate solar water heaters as a result of their greater surface area exposed for sunlight absorption. Water-in-glass evacuated tube solar water heaters are widely used as compared to heat-pipe solar water heaters due to their short payback periods. In this study, the performance of water-in-glass evacuated tube solar water heater is investigated through experiments under the climatic conditions in Kenya. The results revealed a daily efficiency range of 0.58 - 0.65 and a daily final outlet temperature greater than 55°C given an initial temperature of 25°C.

Adaptive overheating cover for a solar water heater

Solar water heating systems have been widely used around the world.However,exposure to sunlight can overheat the device,affecting the efficiency and durability of the system.This article proposes an adaptive deck controller that protects the system from overheating without compromising the availability of domestic hot water.Solar water heaters are considered one of the most effective ways to reduce a home’s carbon footprint.They are a renewable energy source that reduces reliance on fossil fuels and saves money.Thus,this paper aims to develop a dynamic cover for solar water heaters that prevent overheating using an artificial neural network to optimize the design of control systems.Based on a self-organizing map network,the controller automatically adjusts the temperature of the solar collector through a fabric screen covering the main subsystems,depending on many parameters such as weather conditions,collector temperature and domestic hot water depending on demand.A suggested technique of four different shade percentages(0%,20%,25%or 32%)can avoid overheating and maintain the amount of hot water the home needs.Although renewable energy is free,proper controls are required to ensure maximum efficiency or proper use.In addition,the control of renewable energy leads to longer service life.

Evaluation of stearic acid/coconut shell charcoal composite phase change thermal energy storage materials for tankless solar water heater

This work presents a cost-effective and environment-friendly form-stabilized phase change material(PCM)and corresponding solar thermal application in the tankless solar water heater(TSWH).Coconut shell charcoal(CSC)as supporting material was modified by moderate oxidant of H_(2)O_(2)with different concentrations,and then sta-bilized stearic acid(SA)to prepare composite PCMs through vacuum impregnation.It found that CSC support causes a 15.70%improvement of SA loadage after treated by 15%H_(2)O_(2)due to coefficient enhancement by phys-ical interaction and surface modification.The modified CSC 15 support appears more super macropores which contribute to the impregnation of SA than non-modified CSC 0 support verifying from SEM and BET results.And the content of oxygen functional groups was increased after oxidation modification,also motivating SA stabiliza-tion by hydrogen bond interaction in XPS analysis.FTIR results proved there is no chemical reaction happened between SA and CSC.Moreover,the latent heat and phase transition temperature of the as-prepared SA/CSC 15 composite are 76.69 J g^(−1)and 52.52℃,respectively.All composites exhibit excellent thermal stability under a working temperature of 180℃and form stability during phase change.Thermal energy storage-release test within 70℃presents the composite has fast heat transfer efficiency than pure SA.The composite filled in TSWH system has 0.75 W m^(−1)K^(−1)thermal conductivity which is 2.88 times higher than that of pure SA(0.26 W m^(−1)K−1).Besides,the TSWH system with a flow rate of 0.004 kg s^(−1)could heat water effectively after sunset and the energy obtained from the thermal storage system within 1830 s testing times is about 0.15 kW h.In all,SA/CSC composite with good physical-thermo properties has potential in thermal energy storage application,especially in solar energy storage.

Primary Function of Microcontroller EM78P458 and Research on Applications of Its ADC on Chip

The build-in structure of microcontroller EM78P458 and its application in supervising the water level of solar water heater are introduced. The circuit and the flow chart of AD conversion program are depicted. In the end, the design of assembly language program about the AD conversion is introduced.

Identification of rural courtyards’utilization status using deep learning and machine learning methods on unmanned aerial vehicle images in north China

The issue of unoccupied or abandoned homesteads(courtyards)in China emerges given the increasing aging population,rapid urbanization and massive rural-urban migration.From the aspect of rural vitalization,land-use planning,and policy making,determining the number of unoccupied courtyards is important.Field and questionnaire-based surveys were currently the main approaches,but these traditional methods were often expensive and laborious.A new workflow is explored using deep learning and machine learning algorithms on unmanned aerial vehicle(UAV)images.Initially,features of the built environment were extracted using deep learning to evaluate the courtyard management,including extracting complete or collapsed farmhouses by Alexnet,detecting solar water heaters by YOLOv5s,calculating green looking ratio(GLR)by FCN.Their precisions exceeded 98%.Then,seven machine learning algorithms(Adaboost,binomial logistic regression,neural network,random forest,support vector machine,decision trees,and XGBoost algorithms)were applied to identify the rural courtyards’utilization status.The Adaboost algorithm showed the best performance with the comprehensive consideration of most metrics(Accuracy:0.933,Precision:0.932,Recall:0.984,F1-score:0.957).Results showed that identifying the courtyards’utilization statuses based on the courtyard built environment is feasible.It is transferable and cost-effective for large-scale village surveys,and may contribute to the intensive and sustainable approach to rural land use.