Showing papers in "Thermal science and engineering progress in 2023"
TL;DR: In this paper , the steady 3D flow of Cross nanofluid, having nano-particles, gyrotactic micro-organisms as well as bioconvection mechanism is scrutinized.
Abstract: The objective of current investigation is to scrutinize the steady 3D flow of Cross nanofluid, having nano-particles, gyrotactic micro-organisms as well as bioconvection mechanism. Bioconvection fluid is made via the collective influences of Lorentz forces a magnetic-field thru the link of motile micro-organisms with nano-particles. The significance of convection can be established in various micro-biological methods, for example bio-technology and biosensors connected to enhanced mixing and mass transference. The many uses of microbial bio-logical mobility and nano-particles within mechanical energy, biosensors, manufacturing and bio-informatics bio-technology have gain the consideration of scientists in current field. Furthermore, convective boundary conditions are briefly considered in this study. The set of non-linear PDEs of Cross model are converted into set of non-linear ODEs by mean of appropriate similarity alterations then these ODEs solved by built in shooting technique (bvp4c). The significances of the non-dimensional velocity profile, temperature distribution, concentration as well as motile micro-organisms density with sundry parameters are deliberate in this article. The comprehensive breakdown of non-dimensional parameters is defined. The present work simplifies that the temperature of the Cross-fluid boosts for the higher values of Brownian motion and thermophoresis forces. While thermal field declines for higher value of S1 (thermal stratification parameter). Pictorial depiction of the density of motile micro-organisms is executed and effects are determined. Moreover, it seeks for, the non-linear research through the procedure of the (bvp4c) solutions. The significance of many somatic variables consistent to curvature parameters, bio-convection Rayeigh number, Prandtl number (Pr), radiation parameter R, thermal field, concentration field and motile density field.
23 citations
TL;DR: In this article , the effects of utilizing MgO-CuO/water nanofluid on the energetic and exergetic performances of a heat pipe evacuated solar water collector have been analyzed experimentally.
Abstract: In this work, the effects of utilizing MgO-CuO/water nanofluid on the energetic and exergetic performances of a heat pipe evacuated solar water collector have been analyzed experimentally. In this regard, two identical heat pipe evacuated solar water collectors have been installed. In the first system, deionized water has been utilized. In the second collector, newly prepared nanofluid have been used and both collectors have been tested under the same climatic conditions at three flow rates containing 0.016, 0.033 and 0.050 kg/s. According to the experimentally obtained outcomes, mean thermal efficiencies of the system using deionized water were obtained between 49.62-56.18%. Also, average thermal efficiencies of the system with MgO-CuO/water as working fluid were obtained between 69.89-77.21%. Average sustainability index values were attained in the range of 1.0271-1.0676 for both investigated systems. Moreover, utilizing hybrid nanofluid in the system reduced the payback period between 25.14-27.74%. The yearly CO2 savings for the system with and without nanofluid were attained between 0.307-0.343 and 0.217-0.251 ton/year, respectively. General outcomes of this study exhibited notable effects of utilizing MgO-CuO/water on improving the thermal performance of the heat pipe evacuated solar water collector.
15 citations
8 citations
TL;DR: In this paper , the thermal performance of a solar air heater (SAH) with a C-shape finned absorber panel was analyzed using machine learning (ML) models, namely Random Forest (RF), Linear Regression (LR) and K-Nearest Neighbors (KNN).
Abstract: To predict the thermal performance of a solar air heater (SAH) with a C-shape finned absorber panel, Machine Learning (ML) models, namely Random Forest (RF), Linear Regression (LR) and K-Nearest Neighbors (KNN) are used. Experiments are carried out with air velocity ranging from 0.57 to 4.4 m/s and by varying the geometric parameters such as relative pitch-to-gap ratios, relative height ratios, and relative perforated ratios to study the effects on maximum heat transfer enhancement. The experiments produced 64 data sets, out of which 54 samples are used for training and 10 samples for testing the ML models. Eight input parameters (mass flow rate, wind speed, ambient air temperature, intake air temperature, mean exit air temperature, average plate temperature, test zone pressure differential, and solar intensity) are used as independent variables in the LR, RF, and KNN models. Three parameters (Nusselt number, friction factor, and thermal efficiency) are used as dependent variables. The RF model performed better than the KNN and LR models because of its lowest error and highest R2 value. The RF model’s MAE, RMSE, and R2 values are 2.202757, 3.382498, and 0.9783, respectively, with the model efficiency of 98 % being the most significant among the other models. This suggests that the RF model is a good fit for predicting the thermal performance of SAHs.
7 citations
TL;DR: In this paper , a control volume-based numerical study of laminar flow and heat transfer of a single-phase Covalently functionalized Graphene Nanoplatelets (CGNPs)/H2O green nanofluid in a liquid block heat sink with novel fin design and nature-based algorithms (honeycomb, ternate veiny, snowflake, and spider netted) was conducted for cooling of Central Processing Unit (CPU) in the electronic package.
Abstract: A Control Volume-based numerical study of laminar flow and heat transfer of a single-phase Covalently functionalized Graphene Nanoplatelets (CGNPs)/H2O green nanofluid in a liquid block heat sink with novel fin design and nature-based algorithms (honeycomb, ternate veiny, snowflake, and spider netted) baseplate’s designs conducted for cooling of Central Processing Unit (CPU) in the electronic package. The User Defined Function (UDF) code was used to apply the temperature-dependent thermos-physical properties of CGNPs/H2O green nanofluid to the ANSYS-Fluent 2021 R2. The influence of Reynolds number variation, nanoparticles volume fraction, and the baseplate’s designs on the CPU temperature, pumping power, Heat Transfer Coefficient (HTC), and thermal efficiency of the heat sink have been analyzed. The spider netted baseplate design reduced the maximum temperature of the liquid block by about 8.5K in comparison with the Ternate veiny baseplate design. The heat transfer coefficient has a direct relationship with nanofluid concentration and Reynolds number and the best case in terms of HTC improvement is related to (CGNPs 0.100%wt/H2O,Re=2000) with HTC about 8582.3 W.m-2K-1. Moreover, the most thermal output improvement in comparison with the simple model liquid block heat sink is about 8.5% which is related to the liquid block with spider netted baseplate design and CGNPs 0.075%wt/H2O green nanofluid flow.
6 citations
TL;DR: In this article , a combined cooling heating and power system is proposed for the trigeneration of chilled water, process heat, and electricity, which comprises an intercooled-recuperative gas turbine cycle, an absorption cooling system and a heat recovery steam generator.
Abstract: In this paper, a combined cooling heating and power system is proposed for the trigeneration of chilled water, process heat, and electricity. It comprises an intercooled-recuperative gas turbine cycle, an absorption cooling system and a heat recovery steam generator. The absorption cooling system is driven by utilizing the low-grade heat rejected during the intercooling of compressed air and the heat recovery steam generator is operated by recapturing the same from the flue gas. The proposed system is modelled based on energy, exergy, exergoeconomic and environmental analyses. The simulation showed that the system provides a net power of 30 MW, process heat of 29.92 MW, and cooling of 4.72 MW at the base case operating state, with an energy and exergy efficiencies of 83.79 % and 50.60 %, respectively. The optimal case for a proposed system is then determined, with exergy efficiency, system cost, and environmental cost acting as the objective functions to maximise the first and minimise the other two. A parametric analysis is used to find the ideal values of the operating conditions that do not offer a trade-off solution. A tri-objective optimization using the Pareto envelope-based selection algorithm-II is applied to determine the ideal values of the reaming operational conditions that provide trade-off solutions. The technique for order preference by similarity to the ideal solution is also used to select the best optimal solutions from the Pareto front. It is found that the exergy efficiency increased by 2.53 %, and system and environmental costs were reduced by 13.62 % and 18.67 %, respectively.
5 citations
TL;DR: In this paper , the authors used wire mesh to improve the thermal and exergy efficiency of a tubular solar still (TSS) with jute cloth, iron pieces and wire mesh as potential energy storage materials.
Abstract: Higher productivity is considered an important parameter of solar still performance; tubular solar still (TSS) is being explored as a popular technique for improved productivity in recent days. Along with the improved shape of the solar still, the use of sensible heat storage materials in the solar still proved to be a beneficial way to increase productivity. The current study focuses on the experimental investigations on a TSS using jute cloth, iron pieces, and wire mesh as potential energy storage materials for improving its productivity. All experiments were carried out at a constant basin depth of 2 cm at Nagpur [21.1458° N, 79.0882° E] India. The TSS with wire mesh outperforms all other cases. When compared to a conventional tubular solar still, the use of wire mesh in TSS improves thermal and exergy efficiency by 35.1 % and 88.1 %, respectively. The experimental studies concluded that wire mesh has the highest productivity of all; an improvement of 41.35 %, 10.33 %, and 29.78 % was observed when compared to conventional solar stills, iron pieces, and jute cloth, respectively. The water cost per liter of fresh water obtained from TSS–Jute cloth, TSS-Iron pieces, and TSS-Wire mesh was about 0.00575, 0.00515, and 0.00499 US $/m2.
5 citations
TL;DR: In this article , the authors discuss the progress made regarding implementing artificial intelligence and its sub-categories for optimizing, predicting, and controlling the performance of energy systems that contain thermal energy storage facilities.
Abstract: Energy storage is one of the core concepts demonstrated incredibly remarkable effectiveness in various energy systems. Energy storage systems are vital for maximizing the available energy sources, thus lowering energy consumption and costs, reducing environmental impacts, and enhancing the power grids' flexibility and reliability. Artificial intelligence (AI) progressively plays a pivotal role in designing and optimizing thermal energy storage systems (TESS). Recently, plenty of studies have been conducted to examine the feasibility of applying artificial intelligence techniques, such as particle swarm optimization (PSO), artificial neural networks (ANN), square vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS), in the energy storage sector. This study introduces the classifications, roles, and efficient design optimization of energy systems in various applications using different artificial intelligence approaches. This study discusses the progress made regarding implementing artificial intelligence and its sub-categories for optimizing, predicting, and controlling the performance of energy systems that contain thermal energy storage facilities. In addition, the performance of these technologies is thoroughly analyzed, highlighting their noticeable accuracy while carrying out different objectives. Recommendations and future research points are introduced to offer new concepts and inspiration for the application of AI in TESS.
5 citations
4 citations
TL;DR: In this paper , the effect of various climatic conditions on the thermal environment inside an automobile cabin soaked under direct sunlight is described with the help of temperature contours using three-dimensional soaking simulations of the in-cabin flow and heat interactions.
Abstract: The present work describes the effect of various climatic conditions on the thermal environment inside an automobile cabin soaked under direct sunlight. Three-dimensional soaking simulations of the in-cabin flow and heat interactions have been carried out using the commercial solver ANSYS Fluent 18.1. The influence of external climatic conditions has been incorporated into the computations through three parameters, viz. ambient temperature, solar flux, and wind speed. The effects of each of these parameters have been investigated by considering a rich parametric space consisting of different values and combinations of these parameters. The influence of these variables on the thermal environment inside the cabin is described with the help of temperature contours. The MRT at the driver’s location has been evaluated, and its dependence on each of the external climatic parameters is reported. The results from the CFD simulations have been further used to train three supervised machine learning algorithms, viz. linear regression with stochastic gradient descent (LR), random forests (RF), and artificial neural network (ANN) to predict MRT at the driver’s location. The MRT predictions made by these models have also been compared based on the performance metrics such as mean absolute error and Wilcoxon signed-rank test. The machine learning model’s performance has been tested using climatic data of different cities. These results indicated that the machine learning models make predictions above 99% accuracy. This methodology enables MRT estimation without relying on experiments or CFD simulations and subsequently allows better control and automation of automobile air-conditioning systems.
4 citations
TL;DR: In this article , the authors present a comprehensive investigation of lithium batteries for electric and hybrid-electric UAV applications, including lithium battery technologies and development trends, issues of UAV powered by pure lithium batteries, hybrid power systems combining lithium batteries with other energy sources for solving the issues of the pure lithium battery power system, topology design of lithium battery-based hybrid power system for UAVs, and performance optimization of the Lithium batterybased hybrid Power systems in various UAV application.
Abstract: Unmanned aerial vehicles (UAVs) are very promising and convenient flying devices that can be used to execute various missions in both civil and military areas. Especially, they have incomparable advantages to execute tracking, transportation, and even fighting missions in remote areas or severe environments. For UAV applications, Lithium batteries are the most widely used power supply devices. However, the low energy/power density of Lithium batteries would greatly limit the flight endurance or load capacity of UAVs, respectively. Thus, hybrid power systems including Lithium batteries and other energy sources are recommended for high-performance UAVs. This review presents a comprehensive investigation of Lithium batteries for electric and hybrid-electric UAV applications. The investigation includes Lithium battery technologies and development trends in UAV applications, issues of UAVs powered by pure Lithium batteries, hybrid power systems combining Lithium batteries with other energy sources for solving the issues of the pure Lithium battery power system, topology design of Lithium battery-based hybrid power systems for UAVs, and performance optimization of the Lithium battery-based hybrid power systems in various UAV applications. At last, the recommendations for future research priorities are given, which would be very significant for the research and development of high-performance Lithium battery-based power systems for UAVs.
TL;DR: In this article , an experimental test using a drop tube furnace (DTF) is conducted to represent the actual combustion, and probe observation, scanning electron microscopy - energy dispersive X-ray spectroscopy (SEM-EDS), and X-Ray diffraction (XRD) analysis are carried out to determine the propensity of slagging and fouling.
Abstract: Slagging and fouling risks from solid fuel combustion in a boiler can be determined using an experimental investigation, ash observation, or prediction indices based on theoretical calculation. The latter is widely developed and preferred due to its convenience, practicality, and time-saving. However, these indices are commonly based on ash composition alone and may have low accuracy. This study aims to overview and evaluate the prediction indices by employing experimental combustion tests and ash observation methods. An experimental test using a drop tube furnace (DTF) is conducted to represent the actual combustion. In addition, probe observation, scanning electron microscopy - energy dispersive X-ray spectroscopy (SEM-EDS), and X-ray diffraction (XRD) analysis are carried out to determine the propensity of slagging and fouling. Sizeable samples, 59 slagging samples, and 45 fouling samples have been used and analyzed, consisting of Indonesian-Indonesian coal blends and Indonesian-Australian coal blends. The results show that the silica ratio, base-to-acid ratio, simplified base-to-acid ratio, and composite index are proper slagging prediction methods. New slagging criteria are also proposed for better prediction accuracy. In addition, sodium content in the ash can effectively evaluate fouling propensity. Some fouling indices will also have better accuracy if the proposed fouling criteria can be applied. Moreover, the developed approach can be adopted for evaluating other solid fuels, including biomass.
TL;DR: In this paper , the authors conduct system identification and impulse response analysis of a swirling thermoacoustic combustor with an array of acoustic pressure sensors and a loudspeaker applied to controllabe acoustics perturbations at different amplitudes over a certain frequency range.
Abstract: Self-excited combustion instabilities are characterized by large-amplitude limit cycle oscillations of thermodynamic properties such as pressure, velocity and heat release. In practice, such instability is prone to occur in a swirling thermoacoustic combustor due to the interaction between swirling flame and acoustic perturbations. To shed lights on the dynamic interaction, we conduct system identification and impulse response analysis of a swirling thermoacoustic combustor with an array of acoustic pressure sensors and a loudspeaker applied. It provides controllabe acoustics perturbations at different amplitudes over certain frequency range. The dynamic response of the swirling flame to forcing acoustics perturbations is experimentally measured by using a photomultiplier tube (PMT) implemented with a bandpass OH* filter and a high-speed camera with an image intensifier and bandpass filter(430 + 10 nm, Asahi-spectra Inc.). For this, flame describing function (FDF) is obtained, as 1) the swirling number, 2) the equivalence ratio or 3) the inlet bulk air flow velocity is varied. The experimentally identified FDF is then approximated by rational functions with adaptive Antoulas-Anderson (AAA) method to obtain the system’s poles, zeros and DC gains. Further order reduction approximation is then performed by applying least-square (LS)-based AAA method, which has great potential for combustion control design and simplified analysis of swirling thermoacoustic combustors. Both Nyquist and phase plot analyses are conducted. It is found that good agreements are observed between the AAA, AAA-LS method and the measurements. The swirling thermoacoustic combustion system response is finally examined by using the AAA-LS identified reduced order approximation of the FDF. It is found that 8th order reduction and approximation is good enough over the interested Strouhal number range of 0.275 to 2.5. The present work opens up an alternative approach of system identification and impulse response studies of swirling thermoacoustic combustors. The reduced order approximation could then be combined with acoustic waves model to simulate the generation of self-excited thermoacoustic oscillations in practical engines.
TL;DR: In this article , a review of the jet impingement heat transfer process is presented, which includes the effects of Reynolds number, flow velocity, and impact ratio on the heat transfer performance.
Abstract: The jet impingement heat transfer process promises exceptional heat transfer performances, attracting worldwide attention for cooling potential industrial applications. This cooling or heat transfer process has been determined by various factors and parameters. The several affecting factors include Reynolds number, flow velocity, and impact ratio, are responsible for achieving this goal and are critically reviewed in the present article. Jet impingement heat transfer parameters such as heat transfer coefficient, heat flux, Nusselt number, and cooling rate are also discussed in detail. There are many conflicting results of affecting factors on the heat transfer characteristics found in the literature, but the behavior in the resultant trend of the parameters is the same. In the present review, all the factors and parameters are analyzed for various coolant conditions and surface conditions. Various Nusselt number and heat flux correlations for all conditions corresponding to single and two-phase heat transfer published in the literature are also mentioned in the present review.
TL;DR: In this paper , the authors examined the usefulness of radiation phenomena with magnetic effects micro-polar nanofluid by use of impermeable surface and the concept of microorganism's notion is used to make suspended nano-particles stable by using effect of bioconvection influenced by synchronizing deliberation of suitable magnetic field.
Abstract: Research on nanotechnology took interest of scientists as well as researchers because of its vast range of applications like curing cancer, medicines, aircraft manufacturing industry, use of nano-robot technology, bio-nano, heat exchanger instruments, used as coolants in engines of vehicles, microelectronics, water distillation, pharmaceutical procedures and rubber materials. Major purpose of this inspection is to examine the usefulness of radiation phenomena with magnetic effects micro-polar nanofluid by use of impermeable surface. The concept of microorganism’s notion is used to make suspended nano-particles stable by using effect of bioconvection influenced by synchronizing deliberation of suitable magnetic field. Since bioconvection is also an appealing research field for bioengineering and biotechnology, in recent year’s variety of bio-convection models are studied for production of microorganisms. The determination of current exploration is to compute the 2-dimensional flow of Williamson ferrofluid under the influence of magnetic dipole. Characteristics of Brownian motion parameter and thermophoresis diffusion for Williamson ferrofluid model apprehending the properties of convective boundary conditions, thermal motile as well as thermal gradients are considered. The system of nonlinear PDEs is transformed in form of ODEs with the help of apt transformations; additionally obtained ODEs are then solved with the help of bvp4c numerical scheme. Impacts of some important physical parameters are expressed pictorially. Results perceived that fluids temperature increases by increasing thermal radiation as well as thermophoresis parameter moreover shows declining behavior in case of Prandtl number. Moment of motile microorganism rises for larger δ1 and Pe whereas microorganism have opposite trend againstLb.
TL;DR: In this article , a reliable 3D numerical simulation to scrutinize the charging process of paraffin as the phase change material (PCM) in an innovative heat exchanger called double spirally coiled tube (DSCTHE) with two separated paths is presented.
Abstract: The current research attempts to illustrate results of a reliable 3-D numerical simulation to scrutinize the charging process of paraffin as the phase change material (PCM) in an innovative heat exchanger called double spirally coiled tube heat exchanger (DSCTHE) with two separated paths. The water as a heat-transfer fluid (HTF) streams through the double spiral tubes embedded throughout the latent thermal energy storage (LTES) system. The PCM melting characteristics under three different geometries are investigated. After validating the proposed numerical simulation model, the impacts of operational and geometrical factors including inlet temperature of HTF and radius of the inner spiral tube on the behavior of the LTES system in the course of the melting process are investigated in detail. In order to achieve better insight into practical aspects of the presented LTES system, the transient behavior of a PCM for all three considered cases under various working conditions is discussed. Moreover, the 3-D temperature and liquid fractions contours at various time frames are obtained. The findings reveal that a decrement in the radius of the inner spiral tube resulted in a lower capability to melt PCM at the commencement of the charging procedure but more efficiency at the final stages. Generally, the overall time essential for melting of 95 wt% PCM in the storage diminishes up to 126 % by reducing the radius of the inner spiral tube from 90 mm to 50 mm.
TL;DR: In this article , the influence of second degree velocity slip and thermal jump conditions on water-based nanofluid flow and heat transfer over a permeable bidirectional moving surface under a porous medium environment is investigated.
Abstract: The influence of second degree velocity slip and thermal jump conditions on water-based nanofluid flow and heat transfer over a permeable bidirectional moving surface under a porous medium environment are investigated. The intention is to secure closed form analytical solutions, locate domains for existence and also the nonexistence of dual or triple solutions, and analyze the behavior of governing parameters such as the mass transfer, stretching or shrinking sheet, nanofluid volume fraction, first and second degree velocity slips, and thermal jump on the water nanofluid mixture flow and heat transfer. It is observed in the process of boundary layer that the velocity profile decreases when both the suction or injection increases. The presence of nanoparticles slows down linear velocity as well as the temperature distribution. Moreover, the first velocity slip, as it should, depletes axial velocity, whereas the effect of second slip is on the opposite. Thermal jump as can be noticed from the formula of temperature distribution minimizes the role of temperature on the wall. The parametric effects on skin friction and temperature gradient are analyzed and shown graphically. Finally, we consider special parametric values and asymptotic situations that produces special exact solutions.
TL;DR: In this paper , a critical comparative analysis of the many applied and promising optimization methodologies is presented, which are categorized as traditional, modern and hybrid on the basis of identified objective functions, decision variables, and evaluation indicators.
Abstract: Exponentially rising hydrocarbon fuel consumption creates several environmental issues that have necessitated the integration of renewable energy systems (RES) into the grid. Solar photovoltaic and wind energy constitutes the most matured hybrid renewable energy system (HRES) alternative technology against conventional fossil fuels as it is pollution-free, easily available, low-price, and available in abundance. The intermittent nature of solar irradiation and fluctuation in wind speed makes the system design inappropriate, making it either oversized or undersized. Due to this, deploying solar PV-Wind-based HRES is becoming either expensive or inefficient. Thus, there is an immediate requirement for optimization problem-solving methodologies to minimize the HRES costs. This paper mainly focuses on a critical comparative analysis of the many applied and promising optimization methodologies. The methodologies used to design the optimal capacity of HRES, are categorized as traditional, modern, and hybrid on the basis of identified objective functions, decision variables, and evaluation indicators. While most of the present studies have been based on the technical reliability and economical perspective of HRES, in this paper the environmental indicators have got major emphasis. The facts emerging out of the study indicate that application of hybrid meta-heuristic optimization techniques for engineering applications is growing significantly due to their flexibility and efficiency. The application of economical indicators was observed to be more prevalent compared to other reliability and environmental indicators. However, the percentage of multi-objective functions of economical and reliability is a growing trend for the optimal design process of HRES.
TL;DR: In this paper , a machine learning-based multi-objective optimization approach of an integrated solar energy-driven polygeneration and CO2 capture system for meeting a greenhouse's power, freshwater, and CO 2 demands was introduced.
Abstract: Renewable energy-driven decentralized polygeneration systems herald great potential in tackling climate change issues and promoting sustainable development. In this light, this study introduces a new machine learning-based multi-objective optimization approach of an integrated solar energy-driven polygeneration and CO2 capture system for meeting a greenhouse’s power, freshwater, and CO2 demands. The integrated solar-assisted polygeneration system comprises a 486-kW gas turbine, two steam turbines, two organic Rankine cycles, a humidification-dehumidification desalination unit to recover waste heat while producing freshwater, and a post-combustion CO2 capture unit. The proposed system is mathematically modelled and evaluated via a dynamic simulation approach implemented in MATLAB software. Moreover, sensitivity analysis is conducted to identify the most influential decision variables on the system performance. The machine learning-based multi-objective optimization strategy combines Genetic Programming (GP) and Artificial Neural Networks (ANN) to minimize total costs, environmental impacts, and economic and environmental emergy rates whilst maximizing the system exergy efficiency and freshwater production. Finally, the system performance is further investigated through comprehensive Energy, Exergy, Exergoeconomic, Exergoenvironmental, Emergoeconomic, and Emergoenvironmental (6E) analyses. The three-objective optimization of the integrated system reduces total costs, environmental impacts, and monthly environmental emergy rate by 11.4%, 34.31% and 6.38%, respectively. Furthermore, reductions up to 56.81%, 50.19% and 77.07%, respectively, are obtained for the previous indicators by the four-objective optimization model. Hence, the proposed multi-objective optimization methodology represents a valuable tool for decision-makers in implementing more cost-effective and environment-friendly solar-assisted integrated polygeneration and CO2 capture systems.
TL;DR: In this paper , the authors investigated the bubble generation and its behavior during two-phase interaction using the Volume of Fluid (VOF) method for interface capturing and reconstruction, and the conservation equations of mass and momentum are computed in real time taking into account surface tension and gravity.
Abstract: This work aims to investigate the bubble generation and its behavior during two-phase interaction using the Volume of Fluid (VOF) method for interface capturing and reconstruction. The conservation equations of mass and momentum are computed in real time taking into account surface tension and gravity. Pressure-velocity coupling is achieved through the PISO scheme and the interface was reconstructed using the geo-reconstruct PLIC scheme. The obtained results of bubble behaviors are in solidarity with the available literature. Gas (air) was injected in the liquid water through an orifice of 1 mm diameter located in the bottm wall. Influence of surface tension and orifice properties including inlet orifice velocity, orifice diameter on bubble generation and dynamics were analyzed considering the orifice on the bottom wall. The increase in surface tension is directly proportional to bubble diameter and the time taken for detachment. Detachment time behaves inversely with increasing gas velocity. The presence of two orifices and the influence of the spacing between them on bubble dynamics was also investigated.
TL;DR: In this article , the effect of blending percentage, equivalence ratio, and start of ignition (SOI) timing has been considered to analyze the engine performance using response surface methodology (RSM).
Abstract: Biomass and agricultural waste can be used to generate electricity in remote areas through a Gasifier-engine-generator set. However, producer gas-fueled engines have low power and thermal efficiency. In this view, the objective of this study is to determine optimum operation setting of a spark ignition (SI) engine with improved efficiency, reduced emissions, and fuel consumption. Hence, in the present study, initially, SI engine performance and emission have been simulated through a comprehensive quasi-dimensional thermodynamic model. Thereafter, parametric optimization has been performed to improve the performance of SI engines fueled with peach-based producer gas (PG) and propane blend. The effect of blending percentage, equivalence ratio, and start of ignition (SOI) timing has been considered to analyze the engine performance using response surface methodology (RSM). The experiments were designed according to the design of experiment (DoE) tool based on RSM and optimized using the desirability approach. The use of ANOVA to form regression models resulted high accuracy in forecasting output response variables with a 95% confidence interval. RSM results depict, optimum input parameters to be 90 blend percentage, 1.002 equivalence ratio (ER), and 33.83 SOI at 1500 rpm. Corresponding to these optimal inputs, response output performances were found to be 2.41 kW, 0.3003 kg/kW-hr, 27.19 %, 0.809 (vol.%), 2026.05 (ppm) for brake power (BP), Brake specific fuel consumption (BSFC), Brake thermal efficiency (BTE), CO, and NO respectively, with a composite desirability of 0.868. Thus, RSM has the potential to optimize the performance and emission characteristics of engines fuelled with propane and PG.
TL;DR: In this article , the impact of thermal radiation as well as the Navier-Stokes condition upon the two-dimensional flow of second-grade and ternary nanoliquids through a permeable shrinking flat surface was analyzed.
Abstract: Due to its extensive applicability and employment in different systems, the study of thermal transport is a significant area of research. The main goal of this investigation is to analyse the impact of thermal radiation as well as the Navier-Stokes condition upon the two-dimensional flow of second-grade as well as Walter’s B ternary nanoliquids through a permeable shrinking flat surface. The phrase “ternary nanofluid” refers to a suspension of three different types of nanoparticles, notably silver (Ag), SWCNTs, and graphene particles, in water as the base fluid. The inverse Darcy phenomenon has an effect on the momentum equation as well. The energy equation also accounted for nonlinear thermal radiations as well as heat source and sink components. The phenomenon is portrayed as a nonlinear system of partial differential equations. The model equations are transformed into a non-dimensional series of ordinary differential equations by replacing similarity. Afterwards, the transformed ODEs were tackled analytically in order to establish an analytical solution of the energy equation in terms of a confluent hyper-geometric function by utilizing similarity conversion. This research reveals that the velocity field is reduced significantly by the slip parameter. The benefits of a few emerging factors, such as the viscoelastic parameter, inverse Darcy number, slip parameter, solid volume fraction, radiation, Prandtl number, and skin friction coefficient effects on solution, have been displayed through plots and discussed. Additionally, it has been concluded from this analysis that ternary nanofluids have a higher thermal flow rate than hybrid or standard nanofluids.
TL;DR: A comprehensive review of cooling technologies for greenhouses, especially ones deployed in hot climates, is presented and discussed in this paper , which also explains existing strategies to save energy and improve the efficiency of greenhouses.
Abstract: The demand for food items is increasing to match population growth rates. Meanwhile, many countries struggle to guarantee a full year-round production of crops because of the harsh weather conditions in cold and hot seasons. Greenhouses are used to mitigate the harsh weather conditions and allow for a full year-round production of crops by controlling the microclimate and ensuring that the crops acquire the required level of temperature, humidity, water, and light. Several design factors play a crucial role in the successful deployment of the greenhouse. These parameters include shape, orientation, structure, cover material, and climate control technologies. Climate control strategies include cooling and heating technologies. This paper presents a comprehensive review of cooling technologies for greenhouses, especially ones deployed in hot climates. Technologies such as natural ventilation, shading and reflection, evaporative cooling, desiccant cooling, and combined cooling technologies are presented and discussed. Moreover, this paper explores recent advancements in the field of cooling technologies and systems. The paper also explains existing strategies to save energy and improve the efficiency of greenhouses. The results of this review are expected to guide researchers in the process of selecting the most suitable cooling technology for their specific regions.
TL;DR: In this article , a liquid immersion cooling scheme based on SF33 has been proposed and tested for cooling the six different types of cylindrical lithium-ion batteries (LIBs) under fast charging conditions.
Abstract: In this study, the liquid immersion cooling scheme based on SF33 has been proposed and tested for cooling the six different types of cylindrical lithium-ion batteries (LIBs) under fast charging conditions. Firstly, the voltage and temperature responses of LIBs under fast charging conditions with natural convection and SF33 immersion cooling were explored. It is found that the SF33 immersion cooling has a significant advantage over natural convection on controlling the battery temperature, thus ensuring the stability and safety of LIBs in the fast charging process. Subsequently, the high-speed photography was used to observe the bubble behaviors in the cooling process of SF33, and the heat transfer mechanism in the two-phase heat transfer process corresponding to immersion cooling of LIB was preliminary analyzed and discussed. It can be concluded that when the charging current is higher, the phenomenon of subcooled boiling as well as saturation boiling is generated in the SF33. The transition from single-phase convective heat transfer to boiling heat transfer greatly increases the heat transfer coefficient.
TL;DR: In this article , the performance of a U-tube based evacuated tube collector (ETC) for a forced circulation system is tested and a computational fluid dynamics (CFD) based thermal model is developed in Ansys-fluent R14.5 platform and validated with in-house experimental datasets.
Abstract: In the present study, the performance of a U-tube based evacuated tube collector (ETC) for a forced circulation system is tested. The collector tilt angle is varied to analyse the optimum tilt angle to get the higher thermal performance of the solar U-tube ETC regardless of the sun's location. Different flow conditioning inserts are introduced, and its feasibility study is accomplished for the ETC in the place of a conventional plain U-tube ETC to obtain higher system performance. Further, a computational fluid dynamics (CFD) based thermal model is developed in Ansys-fluent R14.5 platform and validated with in-house experimental datasets. Based on the developed CFD model, a detailed parametric study is carried out to optimize the model geometry and operating parameters of solar ETC. CFD results revealed that increasing U-tube diameter from 1/8“ to 3/8” enhances the net temperature gain by about 39%. Consequently, the proposed flow conditioning inserts models showed a better performance with higher net temperature gain and thermal efficiency under the same condition with acceptable pressure drop penalty. Among the different studied geometries, twisted taped with square holes proved to be the most effective design for obtaining a higher thermal efficiency compared to the plain U-tube design. The temperature contour with streamlines and pressure contour of the best flow conditioning model is also discussed. Furthermore, a trade-off study is accomplished to visualize the thermal efficiency in contrast to pressure drop and net temperature gain.
TL;DR: In this paper , a taper-type manifold channel heat sink with multi-channel passes is proposed to improve battery temperature uniformity and reduce power consumption of BTMSs, in which the maximum battery temperature and temperature difference, temperature maldistribution parameter and power consumption performance of eight different designs are analyzed and compared.
Abstract: A liquid-cooled battery thermal management systems (BTMS) has been widely employed as an effective approach for electronic vehicles to ensure battery safety. However, the common linear flow channel structure induces a serious non-uniform temperature distribution. In this study, the novel taper-type manifold channel heat sink with multi-channel passes is proposed to improve battery temperature uniformity and reduce power consumption of BTMSs. The maximum battery temperature and temperature difference, temperature maldistribution parameter and power consumption performance of eight different designs are analyzed and compared. Moreover, the effectiveness of delayed cooling strategy on the temperature uniformity based on liquid-cooled system were analyzed as well. The results show that adopting the taper-type manifold structure can improve the cooling performance of BTMSs, while increasing the number of channel passes improves the thermal performance at the cost of increased power consumption. The taper-type manifold structure with three channel passes has the best cooling performance, in which its power consumption is reduced by 86.3% compared to the base case within the battery temperature and temperature difference limits. Furthermore, delayed cooling scheme is not found to be a good strategy for BTM since it will accumulate a large temperature difference in a very short period when the coolant starts to turn on. These results are of great significance to the design of advanced liquid cooling BTMS.
TL;DR: In this article , the effect of structural hybridization was found statistically significant in defining thermal comfort and bursting characteristics, the pilling resistance also had a p-value < 0.05 for material variation.
Abstract: Interlock structures with double-faced architectures are chiefly preferred for spring wear clothing where mild thermal comfort is a crucial constraint. Knitted structural hybridization, an innovative technique of simultaneously knitting two structural derivatives in a single fabric, promises to be an effective solution for achieving optimal thermal comfort. The study employs cotton and PC blended yarn to architect hybrid interlock structures. Four basic interlock patterns, i.e., Plain, Honeycomb, Half Milano, and Cross Miss, were hybridized into specific portions of fabrics. Differential shrinkages and porosities of the derivatives synchronously governed adequate thermal comfort and mechanical characteristics, which could not be accomplished using sole patterns. The effect of structural hybridization was found statistically significant in defining thermal comfort and bursting characteristics, the pilling resistance also had a p-value < 0.05 for material variation. Pearson analysis was also conducted to determine the strength of the associations between the continuous output variables, positive and negative correlation coefficients were derived corresponding to the association strength.
TL;DR: In this article , the authors estimate a specific manufacturing cost and an end-user price for Silica gel adsorption chillers and show that at a maximum Coefficient of Performance (COP) of 1 and maximum Specific Cooling Power (SCP) of 300 W kg−1, the specific selling price of a silica gel adaption chiller is €1018 per kW of cooling power.
Abstract: Adsorption chillers are more environmentally sustainable than other types of chillers but the trade-off between price and performance makes it impossible for them to seize a significant market share in cooling. The performance increase of adsorption chillers has been the primary focus so far, neglecting to assess if it would lead to a reduced manufacturing cost. This study estimates a specific manufacturing cost and an end-user price for Silica gel adsorption chillers. At a maximum Coefficient of Performance (COP) of 1 and maximum Specific Cooling Power of 300 W kg−1, the specific selling price of a Silica gel adsorption chiller is €1018 per kW of cooling power. The analysis is extended first across a range of different (COP; SCP) combinations and then on the most significant factors influencing the price. We identify a minimum annual selling volume of 14 units and the possibility for the profit to increase by 75 % if higher selling volumes are achieved. The Silica gel results define a market-accepted benchmark that is finally used to assess the economic viability of adsorption chillers integrating advanced adsorption materials, i.e. Metal-Organic Frameworks (MOFs) and zeotypes. None of the chillers integrating advanced adsorption materials can rival Silica gel chillers in cost. The simple correlations developed should be used for checking if any future innovative adsorption material will be able compete with Silica gel when the whole chiller is considered.
TL;DR: In this paper , the authors investigated the effect of honeycomb cell wall thickness (0.2 - 2 mm), cell diameter (2 - 16 mm), and honeycomb material types (cellulose, graphite, polyethylene, stainless steel, magnesium alloy, aluminum and copper) on heat transfer rate of paraffin.
Abstract: This manuscript focuses on comprehensive investigation of entropy analysis and improve energy storage of phase change material (PCM) using a honeycomb material. In the last decade, the honeycomb structure has quickly emerged as a major tool for improving heat transfer rate, particularly for the back of solar radiation PV panels. The aim of this study was to investigate the effect of honeycomb cell wall thickness (0.2 - 2 mm), cell diameter (2 - 16 mm), and honeycomb material types (cellulose, graphite, polyethylene, stainless steel, magnesium alloy, aluminum, and copper) on heat transfer rate of paraffin. These parameters have significant impact on paraffin's energy storage. The variables were optimized numerically using the CFD techniques according to phase change behavior, kinetic energy storage, and total energy storage of composite/paraffin. The results showed that the embedded metal cage had no effect on the total heat storage capacity of paraffin (27.89 W) for 0.33 mm wall thickness of honeycomb. The other optimal geometrical specifications of a honeycomb were determined to be 10mm cell diameter, and stainless-steel material. The ideal honeycomb cell has a uniform distribution of temperature and phase change in all cells at the same time. The entropy study confirmed that the phase transition of PCM with stainless steel honeycomb fins happened homogeneously and promptly. Furthermore, the heat transfer can be improved with changing the geometry of honeycomb structure, and addition fins inside cell.