Determination of optimum injection flow rate to achieve maximum micro bubble drag reduction in ships; an experimental approach

AbstractReduction in ship resistance, in order to decrease fuel consumption and also achieve higher speeds, has been the topic of major research over the last three decades. One of the most attractive ideas in this field is micro bubble drag reduction, which attempts to obtain optimum injection flow rate based on ship specifications. The model test results of a 70 cm catamaran model was used to quantify the effect of air injection rate on drag reduction, and to estimate a simple formulation for calculating an efficient injection rate by considering the main parameters of the ship, such as: length, width and speed. The test results show that excessive air injection decreases the drag reduction effect, while suitable injection reduces total drag by about 5%–8%

Enhancing the renewable energy payback period of a photovoltaic power generation system by water flow cooling

A photovoltaic system which enjoys water flow cooling to enhance the performance is considered, and the impact of water flow rate variation on energy payback period is investigated. The investigation is done by developing a mathematical model to describe the heat transfer and fluid flow. A poly crystalline PV module with the nominal capacity of 150 W that is located in city Tehran, Iran, is chosen as the case study. The results show that by increasing water flow rate, EPBP declines first linearly, from the inlet water flow rate of 0 to 0.015 kg.s-1, and then, EPBP approaches a constant value. When there is no water flow cooling, EPBP is 8.88, while by applying the water flow rate of 0.015 kg.s-1, EPBP reaches 6.26 years. However, only 0.28 further years decrement in EPBP is observed when the inlet water mass flow rate becomes 0.015 kg.s-1. Consequently, an optimum limit for the inlet water mass flow rate could be defined, which is the point the linear trend turns into approaching a constant value. For this case, as indicated, this value is 0.015 kg.s-1

Hysteresis Nonlinearity Identification Using New Preisach Model-Based Artificial Neural Network Approach

Preisach model is a well-known hysteresis identification method in which the hysteresis is modeled by linear combination of hysteresis operators. Although Preisach model describes the main features of system with hysteresis behavior, due to its rigorous numerical nature, it is not convenient to use in real-time control applications. Here a novel neural network approach based on the Preisach model is addressed, provides accurate hysteresis nonlinearity modeling in comparison with the classical Preisach model and can be used for many applications such as hysteresis nonlinearity control and identification in SMA and Piezo actuators and performance evaluation in some physical systems such as magnetic materials. To evaluate the proposed approach, an experimental apparatus consisting one-dimensional flexible aluminum beam actuated with an SMA wire is used. It is shown that the proposed ANN-based Preisach model can identify hysteresis nonlinearity more accurately than the classical one. It also has powerful ability to precisely predict the higher-order hysteresis minor loops behavior even though only the first-order reversal data are in use. It is also shown that to get the same precise results in the classical Preisach model, many more data should be used, and this directly increases the experimental cost

Energy and Exergy Analyses on Seasonal Comparative Evaluation of Water Flow Cooling for Improving the Performance of Monocrystalline PV Module in Hot-Arid Climate

Solar irradiation in hot-arid climatic countries results in increased temperatures, which is one of the major factors affecting the power generation efficiency of monocrystalline photovoltaic (PV) systems, posing performance and degradation challenges. In this paper, the efficiency of a water-flow cooling system to increase the output of a monocrystalline PV module with a rated capacity of 80 W is studied from both energy and exergy perspectives. The energy and exergy tests are performed for each season of the year, with and without cooling. The energy and exergy efficiencies, as well as the commodity exergy values, are used to compare the photovoltaic device with and without cooling. The findings are based on the experimental data that were collected in Tehran, Iran as an investigated case study in a country with a hot-arid climate. The findings show that when water-flow cooling is used, the values of the three efficiency metrics change significantly. In various seasons, improvements in regular average energy efficiency vary from 7.3% to 12.4%. Furthermore, the achieved increase in exergy efficiency is in the 13.0% to 19.6% range. Using water flow cooling also results in a 12.1% to 18.4% rise in product exergy

The road to developing economically feasible plans for green, comfortable and energy efficient buildings

Owing to the current challenges in energy and environmental crises, improving buildings, as one of the biggest concerns and contributors to these issues, is increasingly receiving attention from the world. Due to a variety of choices and situations for improving buildings, it is important to review the building performance optimization studies to find the proper solution. In this paper, these studies are reviewed by analyzing all the different key parameters involved in the optimization process, including the considered decision variables, objective functions, constraints, and case studies, along with the software programs and optimization algorithms employed. As the core literature, 44 investigations recently published are considered and compared. The current investigation provides sufficient information for all the experts in the building sector, such as architects and mechanical engineers. It is noticed that EnergyPlus and MATLAB have been employed more than other software for building simulation and optimization, respectively. In addition, among the nine different aspects that have been optimized in the literature, energy consumption, thermal comfort, and economic benefits are the first, second, and third most optimized, having shares of 38.6%, 22.7%, and 17%, respectively

Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis

Adaptive neural fuzzy model Simulated annealing algorithm A B S T R A C T In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates of 5, 10, 15 and 20 C/min. The TG experiments indicated that the virgin and the waste PE pyrolysis processes mainly underwent in the temperature range of 390-510 C. Subsequently, the adaptive neural fuzzy model was adopted to predict the conversions and the pyrolysis rates of the virgin and the waste PE. The optimal operating conditions in different temperature ranges were optimized by the simulated annealing algorithm (SA). Moreover, the R-squared values of the virgin PE conversions (~1) and pyrolysis rates (> 0.999), and the waste PE conversions (~1) and pyrolysis rates (> 0.999) revealed the high accuracy of the adaptive neural fuzzy model predicted results

Effect of working fluids on the performance of phase change material storage based direct vapor generation solar organic Rankine cycle system

Working fluids can play a critical role in the working of an organic Rankine cycle system. A direct vapor generation solar organic Rankine cycle embedded with phase change material storage is analyzed in this study. The system comprised of an array of evacuated flat plate collectors, phase change material based thermal storage, expander, condenser, and organic working fluid pump. The storage tank model is modeled using a finite difference method in MATLAB programming environment while the 1D model of ORC system is used to evaluate the system performance. After a careful screen, 12 dry and isentropic working fluids were selected and their impact on the performance of the heat storage tank and the overall system is evaluated. The results show that the system efficiencies increase and decrease with the increment and decrement in the critical temperature of the working fluid. Moreover, the rise and fall of working fluid temperature, phase change material temperature, and the quantity of energy stored and released generally increase with an increase in the critical temperature of the working fluid. At the evaporation temperature of 10 °C higher and lower than the melting point temperature of the phase change material, Benzene has achieved the highest system efficiencies of 10.7% & 10.4% during charging and discharging mode, respectively. However, the maximum the rise and fall of working fluid temperature, phase change material temperature, and the quantity of energy stored and released during charging and discharging mode is attained by Heptane which is found to be 5.35 °C & 7.34 °C, 0.48 °C & 0.44 °C and 13.81 MJ & 23.04 MJ, respectively. Heptane has shown overall best performance among the selected working fluids and found to be feasible for phase change material storage based direct vapor generation solar ORC system