Applied Thermal Engineering最新文献

{"title":"Framework for prediction of two-phase R-744 ejector performance based on integration of thermodynamic models with multiphase mixture CFD simulations","authors":"Baris Burak Kanbur ,&nbsp;Ekaterini E. Kriezi ,&nbsp;Wiebke Brix Markussen ,&nbsp;Martin Ryhl Kærn ,&nbsp;Alexander Busch ,&nbsp;Jóhannes Kristófersson","doi":"10.1016/j.applthermaleng.2024.124888","DOIUrl":"10.1016/j.applthermaleng.2024.124888","url":null,"abstract":"<div><div>Current computational models of two-phase R-744 ejectors require defined outlet pressure conditions for convergence, this brings a strong dependence on experimental data or pre-guessed outlet pressure values. This study presents a framework combining a thermodynamic model and a computational fluid dynamics (CFD) model to predict two-phase R-744 ejector performance, minimizing reliance on experimental data or guessed outlet pressure values. The proposed framework is developed in a broad operating range with 137 different experimental cases from the motive inlet pressure of 51.9 bar to 101.1 bar. Three different approaches are developed for the thermodynamic model in the MATLAB environment; i) a model with global coefficients which are unchanged for the entire operating range, ii) a model with local coefficients, which have unique values for each experimental case, and iii) a model with predicted-local coefficients, which uses a prediction algorithm to find the local values for each experimental case. The local and predicted-local coefficient approaches estimate the mass flow rate from the motive inlet with a relative error of 5 %. However, the mass flow rate predictions from the suction inlet showed high deviations above 30 % for the predicted-local coefficient approach in transcritical operating conditions, while the local coefficient approach keeps the relative error still lower than 5 %. All approaches estimated the ejector outlet pressure with less than 10 % error, which is an acceptable error; therefore, the thermodynamic model-based outlet pressure was defined as the outlet boundary condition to the CFD domain. All thermodynamic model embedded CFD simulations computed the temperature and Mach number values with less than 1 % deviation at the motive nozzle exit. The results show that the prediction algorithm can estimate the ejector outlet pressure within an acceptable deviation range, offering a promising direction for future research to reduce dependence on experimental data.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"258 ","pages":"Article 124888"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of non-equilibrium phase transition on the aero-thermodynamic performance of supercritical carbon dioxide compressors","authors":"Xin Shen,&nbsp;Zhe Huang,&nbsp;Hua Ouyang,&nbsp;Zhaohui Du","doi":"10.1016/j.applthermaleng.2024.124890","DOIUrl":"10.1016/j.applthermaleng.2024.124890","url":null,"abstract":"<div><div>Phase transition is a prominent issue for the supercritical CO₂ compressors operating near the critical region. The non-equilibrium behavior of phase transition makes it difficult to accurately predict performance under these conditions. A non-equilibrium phase transition model is proposed to analyze the aero-thermodynamic performance of supercritical CO₂ centrifugal compressors with different inlet conditions. The model examines phase change characteristics and compressor performance under variable operating conditions. The results indicate that this model can effectively predict the aero-thermodynamic performance of compressor near critical conditions, with an average error of less than 2% in the performance curves. The inconsistency between low-temperature and low-pressure regions, along with the increase in liquid phase volume, are typical characteristics of non-equilibrium phase transition in supercritical CO₂ compressors. The non-equilibrium effect of phase transition can reduce the leakage loss at high flow rates, but also increases the likelihood of stall at low flow rates. Furthermore, the concept of “non-equilibrium degree” (NED) is introduced to quantify these effects. When NED exceeds 0.2, the isentropic efficiency of the compressor decreases by 15.1% compared to its maximum efficiency. Designing inlet conditions for supercritical CO₂ compressors with NED below 0.1 is more suitable because it has a larger inlet flowrate and higher efficiency.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124890"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimisation of PCM passive cooling efficiency on lithium-ion batteries based on coupled CFD and ANN techniques","authors":"Weiheng Li ,&nbsp;Ao Li ,&nbsp;Anthony Chun Yin Yuen ,&nbsp;Qian Chen ,&nbsp;Timothy Bo Yuan Chen ,&nbsp;Ivan Miguel De Cachinho Cordeiro ,&nbsp;Peng Lin","doi":"10.1016/j.applthermaleng.2024.124874","DOIUrl":"10.1016/j.applthermaleng.2024.124874","url":null,"abstract":"<div><div>Ever since the lithium-ion batteries (LIBs) outbreak, there has been an exponential bloom of application over the last decade, especially for electric vehicles, automobiles and other transportation systems. Nonetheless, as the first-generation LIBs eventually aged and became increasingly thermally unstable, the utilisation of thermal management cooling systems is essential to maintain the safe operation of LIB packs in the long term. Compared to active cooling methods, passive cooling often offers a cost-effective, easy-to-install and energy-saving solution without significant changes to the design complexity. This article focuses on the thermal management of prismatic battery packs and proposes a coupling passive cooling method that combines phase change material (PCM) cooling and immersion cooling, which proves to be cost-effective and efficient. Furthermore, the study incorporates an artificial neural network (ANN) model into computational fluid dynamics (CFD) simulations to optimize a specific battery cooling system. This optimization takes into account the PCM package method and the properties of PCM and immersion liquid. The results demonstrate that the immersion liquid exhibits different behaviours under various PCM conditions than natural convection. Overall, this modelling framework presents an innovative approach by utilizing high-fidelity CFD numerical results as inputs for establishing a numerical dataset. Through ANN optimisation, eleven input parameters are considered, and the optimised scenario confirmed that PCM material with a density of 760 kg/m³, thermal conductivity 32 W/(m K), specific heat 1691 (J/kg K), latent heat 80,160 (J/kg), liquidus temperature 302.93 K, solidus temperature 315.15 K and direct liquid density 1.4 (g/ml), thermal conductivity 0.4 (W/m K), specific heat 1220 (J/kg K) with side thickness 5 (mm) and mid thickness 2.5 (mm). With this combination, the optimised performance demonstrated considerable decreases in the maximum temperature and the temperature difference by 4.26 % and 10.8 %, respectively. This approach has the potential to enhance the state-of-the-art thermal management of LIB systems, reducing the risks of thermal runaway and fire outbreaks.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124874"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The synergistic effect of micro/nanostructure length scale and fluid thermophysical properties on pool boiling heat transfer","authors":"Leymus Yong Xiang Lum ,&nbsp;Kai Choong Leong ,&nbsp;Jin Yao Ho","doi":"10.1016/j.applthermaleng.2024.124878","DOIUrl":"10.1016/j.applthermaleng.2024.124878","url":null,"abstract":"<div><div>Facile surface micro/nanostructuring techniques for additively-manufactured (AM) aluminum alloy (AlSi10Mg) have recently been developed. The structuring techniques are not only highly scalable, but they also enable the tailoring of structure length scale and morphology to enhance pool boiling heat transfer coefficient. Our past study revealed that the structure cavity size of 5 µm is favorable for bubble nucleation during pool boiling of dielectric fluid, HFE-7100, resulting in significant enhancements in the heat transfer coefficients (<em>h</em>). However, owing to the differences in thermophysical properties between different coolant fluids, including saturation temperature, latent heat of vaporization and surface tension, the required structure size range for bubble nucleation and capillary wicking force for liquid re-supply are expected to differ significantly. To explore the effect of structure length scale on the pool boiling performance of coolants with different thermophysical properties, this work develops a new surface structuring technique consisting of a dual-stage metallurgic heat treatment process and single-stage crystallographic etching process to tune the structure length scale across nearly two orders of magnitude, <em>viz.</em>, from 0.3 to 15 μm. Using coolant media of vastly different thermophysical properties, i.e., dielectric fluid HFE-7100 and deionized water, we show that while microcavities with sizes ranging from 3 to 8 μm are favorable bubble nucleation sites for boiling of HFE-7100, which result in the enhancement of the maximum heat transfer coefficient (<em>h_max</em>) by 83.4 to 103.8 % as compared to a conventional plain Al6061 surface, larger microcavity sizes of 10 to 15 μm are required to effectively promote bubble nucleation of water. This large microcavity size range of 10 to 15 μm, produced through rational nanoparticle agglomeration of the rich Si-phase in AM AlSi10Mg in elevated temperature, followed by an indirect removal process using a chemical process, is found to significantly increase <em>h_max</em> of water by up to 259.9 % as compared to conventional nanostructures formed on Al6061. In addition, the new AM structured surfaces also exhibit up to 26.6 % enhancement in critical heat flux (CHF) as compared to highly-wicking conventional nanostructured Al6061. In summary, by utilizing scalable fabrication techniques to tailor the structure length scale on AM AlSi10Mg, this work not only reveals the favorable microcavity sizes for bubble nucleation of different coolant fluids to enhance boiling, but it also provides useful micro/nanostructure design guidelines that can be adopted to enhance boiling of other coolants and phase change applications.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124878"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heat transfer enhancement in vehicle cabin heating system with hybrid nanofluid: An experimental and artificial intelligence approach","authors":"Emre Askin Elibol","doi":"10.1016/j.applthermaleng.2024.124892","DOIUrl":"10.1016/j.applthermaleng.2024.124892","url":null,"abstract":"<div><div>In louvered fin-and-flat-tube aluminum heat exchangers, the interrupted surfaces of the louvered fin channel, through which air flows, enhance heat transfer by growing and degrading laminar boundary layers, while the large surface-to-cross-section flow area ratio of the flat tube further enhances heat transfer. Consequently, due to their relatively good heat transfer performance and compact design, louvered fin-and-flat-tube aluminum heat exchangers are often utilized for cabin heating systems. Considering previous studies involving louvered fin-and-flat-tube aluminum heat exchangers with conventional fluids and with mono-nanofluids, this is the first study employing Al₂O₃-TiO₂/water hybrid nanofluid experimentally in this context, and utilizing a forward-looking ANN forecasting model for scenarios that cannot be experimentally conducted in such systems. Accordingly, the heat transfer enhancement in the louvered fin-and-flat-tube heat exchanger is experimentally investigated for both pure water alone and for different volume concentrations of Al₂O₃-TiO₂/water hybrid nanofluid. Heat transfer rate, convection heat transfer coefficient, Nusselt number, effectiveness, overall heat transfer coefficient, pressure drop, and performance evaluation index were assessed for different inlet temperatures (50 °C, 60 °C, 70 °C) and volume flow rates (3.65 LPM, 5.65 LPM, 7.65 LPM) in the range 0–0.2 % volume concentration. The experimental results show that the highest heat transfer rate enhancement was 113.32 % using the hybrid nanofluid at φ = 0.2 % compared to pure water at a 50 °C inlet temperature and 7.65 LPM flow rate. It was further shown that even using only the hybrid nanofluid, the effectiveness can be increased up to 0.422 at a constant fan speed without the need to enlarge the heat exchanger size, at a flow rate of 7.65 LPM and an inlet temperature of 70 °C. It has also been found that the maximum values of the performance evaluation index calculated according to two different formulas are 2.260 and 2.049 at φ = 0.2 %. In the following part of the study, heat transfer rate, effectiveness, and pressure drop values in the instances of 0.3 % and 0.4 % volume concentrations were forecast using an artificial neural network model trained with the Levenberg-Marquardt algorithm using experimental data. With the proposed artificial neural network model, the forecast heat transfer rates were as expected, while the expected trend could not be achieved in terms of the effectiveness and pressure drop predictions. The study ultimately found that the utilization of a Al₂O₃-TiO₂/water hybrid nanofluid in cabin heating systems, even at a relatively low concentration value of 0.2 %, is capable of achieving very high heat transfer enhancement in exchange for only a very minor pressure drop.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124892"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning analysis for heat transfer enhancement in nano-encapsulated phase change materials within L-shaped enclosure with heated blocks","authors":"H. Thameem Basha ,&nbsp;Bongsoo Jang","doi":"10.1016/j.applthermaleng.2024.124803","DOIUrl":"10.1016/j.applthermaleng.2024.124803","url":null,"abstract":"<div><div>Phase change materials(PCMs) are crucial to energy storage systems due to their enhanced thermal properties. They significantly boost energy efficiency and promote sustainability. Nevertheless, the low thermal conductivity of PCMs presents a significant challenge, which is addressed by utilizing nano-encapsulation to enhance energy efficiency in energy storage systems. Motivated by this, the current study conducts a theoretical investigation to explore the heat transfer characteristics in a buoyancy-driven Nano-Encapsulated Phase Change Materials(NEPCM) nanofluid within an L-shaped porous enclosure with the impacts of a heated block and magnetic field. Furthermore, the fusion temperature plays a crucial role in initiating phase change in NEPCM, thereby impacting the heat transfer process. Hence, identifying the optimal fusion temperature is essential. To accomplish this, a machine learning approach was employed to identify the ideal fusion temperature. A dataset of 160 data points across four different fusion temperature values was used in this analysis. Additionally, the machine learning model analyzed how variations in fusion temperatures impact physical parameters. An in-house Matlab code is utilized to solve the dimensionless fluid transport equations employing the finite difference method. The results indicate that increasing the nanoparticle volume fraction significantly enhances the heat transfer rate across all physical parameters. Specifically, under higher thermal buoyancy force, increasing the volume fraction from 1% to 5% results in a 90.04% increase in the heat transfer rate. The numerical analysis demonstrates that heat transfer rates improve significantly when the fusion temperature is adjusted to 0.5, a result further validated by machine learning techniques. At this temperature, thermal buoyancy force increases by 0.98% and 2.68% compared to values of 0.1 and 0.9, respectively, while the Stefan number shows increases of 159.42% and 87.48% under these conditions; thereby, the heat transfer rate increases at this value. This computational study provides important insights into the significance of fusion temperature, emphasizing the need to determine its optimal value for improving heat transfer. Identifying this optimal value can enhance the efficiency of thermal energy storage systems and improve cooling performance in electronic devices.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124803"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance research on a CO2 heat pump system with novel control strategy in electric vehicle","authors":"Haixu Teng ,&nbsp;Jun Wang ,&nbsp;Yuncong Wang ,&nbsp;Zhanzhuo Song ,&nbsp;Dong Liu ,&nbsp;Zhikun Liu ,&nbsp;Xiaoye Xue ,&nbsp;Wei Chang ,&nbsp;Ming Li","doi":"10.1016/j.applthermaleng.2024.124877","DOIUrl":"10.1016/j.applthermaleng.2024.124877","url":null,"abstract":"<div><div>The efficiency of the thermal management system is crucial for electric vehicles (EVs). This study proposes a novel dual electronic expansion valve (EXV1 and EXV2) sub-area control strategy to improve the heating performance of the CO₂ heat pump (HP) system in low temperatures. The study analyzed the impact of the EXV1 opening on the system’s operating parameters. A comparison assessment was subsequently conducted on the heating capacity, COP, and gas cooler (GC) outlet air temperature before and after optimizing the control strategy at −20 °C. A method for evaluating performance under heating and refrigerating conditions was proposed and validated using a real vehicle in the environmental chamber. Additionally, the study compared the energy consumption differences between the CO₂ and R134a systems at −20 °C. The effects of these two systems on vehicle range at various temperatures were also compared using the WLTC (World-Light-Vehicle-Test-Cycle). The results show that when the EXV1 opening is exceeds 300 steps (30 %), it has less influence on the operating parameters of the system components. Furthermore, at −20 °C, the optimized control strategy improved the average heating capacity, and COP by 11.6 %, and 9.8 %, respectively, and the GC average outlet air temperature by 8.2 °C. The target thermal management system can meet the heating and refrigerating demands. The minimum temperature of the outlet air can be 5.24 °C at 40 °C and the maximum temperature of the outlet air can be 57.16 °C at −15 °C. The CO₂ HP system saves about 34.7 % of energy consumption compared with the R134a system at −20 °C. Under the WLTC, the range of the CO₂ HP system is improved by 9.3 % and 16.6 % compared to the R134a system at −20 °C and −10 °C, respectively.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124877"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimally designing a perovskite solar cell/thermoelectric generator coupling system toward efficient and stable operation","authors":"Qin Zhao ,&nbsp;Ziyang Hu ,&nbsp;Jianming Li ,&nbsp;Houcheng Zhang","doi":"10.1016/j.applthermaleng.2024.124854","DOIUrl":"10.1016/j.applthermaleng.2024.124854","url":null,"abstract":"<div><div>Integrating perovskite solar cells with thermoelectric generators can effectively enhance photoelectric efficiency and consolidate working stability. However, no attempt has been made to optimally design this potential integration, particularly at the structural level. Herein, using simulation methods, a novel coupling system that sandwiches a solar selective absorber between perovskite solar cells and thermoelectric generators is designed, where the absorber functions both as a photothermal converter and a heat exchanger. The operational conditions that thermoelectric generators intervene in electricity generation are determined in detail. Under typical conditions, the system achieves a maximum energy efficiency of 20.89 %, and its performance can be further maximized by optimizing three structural parameters of thermoelectric generators (<em>X</em>₁, <em>X</em>₂, and <em>X</em>₃), along with the operating voltage, operating temperature, and absorption layer thickness of perovskite solar cells. Their optimum values are, respectively, determined as 361 m⁻², 0.151, 0.19, 0.895 V, 330 K, and 970 nm. Besides, system performance sensitivities on thermal conductivity of solar selective absorber and thermal contact resistances between subsystems are evaluated. The optimized system achieves 21.94 % peak energy efficiency, 11.54 % above unoptimized single perovskite solar cells and 5.03 % above the unoptimized system. Some valuable insights and suggestions for optimally designing such real systems are highlighted.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124854"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graphene functionalized nano-encapsulated composite phase change material based nanofluid for battery cooling: An experimental investigation","authors":"S. Sainudeen Shijina,&nbsp;S. Akbar,&nbsp;V. Sajith","doi":"10.1016/j.applthermaleng.2024.124893","DOIUrl":"10.1016/j.applthermaleng.2024.124893","url":null,"abstract":"<div><div>The graphene-nano encapsulated composite phase change material (GnePCM) based nanofluid holds great potential as a coolant for batteries in electric vehicles. The current work focuses on the synthesis and study of the cooling performance of GnePCM-based nanofluid. Few layered graphene (FLG) was synthesized via the liquid phase exfoliation method. Mini-emulsion polymerization was adopted to encapsulate composite PCM (octadecane: paraffin wax) within polystyrene shell and distribute these nanoballs across the graphene flakes of FLG to obtain GnePCM. Differential Scanning Calorimetry (DSC) was used to optimize the composition of composite PCM based on the melting range and latent heat. GnePCM was characterized by Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), DSC, Fourier Transform Infrared (FTIR) spectroscopy, and Raman Spectroscopy. Nanofluid was made by mixing GnePCM slurry with the base fluid (ethylene glycol − water mixture) and its thermo-physical properties were estimated. The analysis of thermal conductivity and specific heat capacity showed a 14.7 % and 56 % increase for the nanofluid compared to the base fluid. The optimal concentration of nanofluid for maximum stability was 10 % v/v based on zeta potential measurements. The heat transfer studies and pressure drop studies were conducted on a set of 10 cylindrical heaters, mimicking a 18,650 battery cell pack. The nanofluid could potentially achieve a maximum reduction of 5 °C in average surface temperatures of the cells as compared to the base fluid. The enhanced cooling efficiency of nanofluid could be related to the increased thermal conductivity and heat capacity of GnePCM, as well as the absorption of latent heat during its melting process. Enhancement in heat transfer parameters was found to be more prominent at lower flow rates for the nanofluids. The results reveal that the flow rate and power input play a significant role in the cooling performance of the nanofluid. Due to the increased viscosity of the nanofluid, a slight increase in the pressure drop and pumping power was observed at higher flow rates, as compared to base fluid.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124893"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimised scheduling of a cogenerative subnetwork based on a micro gas turbine and thermal storage with the addition of an innovative solar assisted heat pump and Ni-Zn battery","authors":"M. Raggio,&nbsp;M.L. Ferrari,&nbsp;P. Silvestri","doi":"10.1016/j.applthermaleng.2024.124889","DOIUrl":"10.1016/j.applthermaleng.2024.124889","url":null,"abstract":"<div><div>The Innovative Energy Systems (IES) laboratory at the University of Genoa features a plant configuration comprising a micro gas turbine, latent heat thermal energy storage, an innovative heat pump system connected to solar façade panels, and a NiZn battery. This study presents the optimization of four distinct sub-plant configurations, focusing on their economic and environmental performance across different seasons (January, April, July, and October) under two market scenarios (no selling price or selling price equal to buying price). A genetic algorithm-based tool is developed for the optimized energy scheduling of these configurations, taking into account the operational characteristics of programmable, non-programmable energy sources and energy storage devices. The analysis highlighted that when the selling price is equal to zero, the system is optimised to improve sell-consumption. The addition of the battery or the heat pump to the system always leads to reduction of operational costs compared to the baseline case with only the micro gas turbine and thermal energy storage. Notably, the heat pump alone provides greater cost benefits than the battery, although the combined use of both systems yields the highest cost reductions ranging, depending on the month, up to −16.9% in the “no sell” scenario and up to −12.3% when selling and buying prices are equal. Regarding the CO₂ emissions, both components lead to an emission reduction in the “no sell” scenario while only the HP guarantees an emission reduction during the “equal to buy” scenario, in both cases up to −20.5% less. This analysis highlights the economic and environmental advantages of integrating NiZn battery storage and a solar-assisted heat pump into the energy system, demonstrating cost savings and emission reductions across various market conditions and seasonal demands.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"259 ","pages":"Article 124889"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}