Case Studies in Thermal Engineering最新文献_第4页

Analysis of thermal performance and irreversibility of double-diffusive buoyancy-driven nano-suspension subject to local thermal non-equilibrium model 受局部热非均衡模型影响的双扩散浮力驱动纳米悬浮的热性能和不可逆性分析

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-15 DOI: 10.1016/j.csite.2024.105294

In fact, local thermal equilibrium (LTE) would be unsuitable when it comes to nuclear reactors, electronic equipment, space devices, geothermal engineering, and high-conductivity foams, due to prominent temperature discrepancy between the two constituents (solid and nanofluid) in porous material. Local thermal non-equilibrium (LTNE) situation may be considered in above real world applications. In view of above relevance, the effects of LTNE model on double-diffusive natural convection (DDNC) within a fluid-saturated porous container loaded with the TiO₂-H₂O nanofluid and emplacing four cooling and hot channels in Forchheimer-Brinkman-extended Darcy medium have been investigated in the present study. The momentum, heat and mass equations are solved by finite element method. Irreversibility in the two constituents (nanofluid and solid) of the porous structure has been analyzed. The significant outcomes are that fluid circulations enhance due to rise in porosity of the medium. Fluid friction entropy

E n_{F F, T}

ameliorates significantly by 1514.16 % and 872.97 % with increase in Rayleigh number and porosity of the medium. It is clear that

N u_{l o c, n f}, N u_{a v e, n f}

,

N u_{l o c, s} & N u_{a v e, s}

enhance significantly with rise of buoyancy and thermal conductivity ratio, interstitial solid/fluid heat transfer coefficient.

事实上，由于多孔材料中两种成分（固体和纳米流体）之间存在显著的温度差异，局部热平衡（LTE）并不适用于核反应堆、电子设备、空间装置、地热工程和高导电性泡沫。上述实际应用中可能会出现局部热不平衡（LTNE）的情况。鉴于上述相关性，本研究探讨了 LTNE 模型对装有 TiO2-H2O 纳米流体的流体饱和多孔容器内双扩散自然对流（DDNC）的影响，并在 Forchheimer-Brinkman 扩展达西介质中设置了四个冷却和热通道。动量、热量和质量方程采用有限元法求解。分析了多孔结构中两种成分（纳米流体和固体）的不可逆性。分析结果表明，介质孔隙率的增加会促进流体循环。随着雷利数和介质孔隙率的增加，流体摩擦熵 EnFF,T 显著降低了 1514.16 % 和 872.97 %。很明显，Nuloc,nf、Nuave,nf、Nuloc,s&Nuave,s 会随着浮力和导热率、间隙固体/流体传热系数的增加而显著提高。

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引用次数: 0

A generalized refined Moore–Gibson–Thompson thermoelastic model based on the concept of memory-dependent higher-order derivatives 基于记忆依赖高阶导数概念的广义精炼摩尔-吉布森-汤普森热弹性模型

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-15 DOI: 10.1016/j.csite.2024.105291

The inclusion of memory-dependent derivatives (MDD) in constitutive models improves the ability to predict and analyze time-dependent responses of materials, providing a more detailed depiction of their mechanical properties and structural changes. In this paper, a new thermoelasticity model is created that combines the Moore-Gibson-Thompson (MGT) equation with higher-order memory-dependent derivatives (MDD), any optional kernel function, and time delay. The objective of this model is to provide a more accurate mathematical depiction of the thermal and mechanical reactions of materials, particularly those that exhibit complex behaviors over time. A theoretical study was conducted to provide additional clarification of the proposed concept. For this purpose, thermal-mechanical waves were studied in a semi-infinite region, surrounded by a magnetic field, and exposed to a direct heat source uniformly distributed on its outer surface. To solve the coupled partial differential equations governing the system, the Laplace transform methodology was used. The effects of different kernel functions, time delays, and higher-order (HO) derivatives on the behavior of thermoelastic materials are discussed and illustrated using figures and tables.

在构成模型中加入记忆相关导数（MDD）可提高预测和分析材料随时间变化的响应的能力，从而更详细地描述材料的机械特性和结构变化。本文创建了一个新的热弹性模型，该模型将摩尔-吉布森-汤普森（MGT）方程与高阶记忆相关导数（MDD）、任意可选核函数和时间延迟相结合。该模型的目的是对材料的热反应和机械反应进行更精确的数学描述，尤其是那些随时间变化表现出复杂行为的材料。为了进一步阐明所提出的概念，我们进行了一项理论研究。为此，我们研究了半无限区域中的热机械波，该区域被磁场包围，并暴露于均匀分布在其外表面的直接热源中。为了求解支配该系统的耦合偏微分方程，使用了拉普拉斯变换方法。文中讨论了不同核函数、时间延迟和高阶导数对热弹性材料行为的影响，并用图和表进行了说明。

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引用次数: 0

Computational analysis of heat transport dynamics in viscous dissipative blood flow within a cylindrical shape artery through influence of autocatalysis and magnetic field orentation 圆柱形动脉内粘性耗散血流受自催化和磁场作用影响的热传输动力学计算分析

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-12 DOI: 10.1016/j.csite.2024.105281

Nanofluids consisting of tetra nanoparticles are crucial in bio medical sciences due to their improved thermal transport characteristics. The advanced tailored properties of tera nanoparticles make them useful in several medical interventions, such as hyperthermia treatment, where the targeted tissue can be heated more efficiently, leading to better treatment outcomes. The current study investigates the heat transfer enhancement in a hemodynamic system using tetra nanoparticles. The physical configuration of the blood flow is assumed with in a permeable cylindrical shape stenosed artery. The model incorporates the Carreau model with inclusion of diverse factors such as, exponential space-based heat source, viscous dissipation, infinite shear rate and permeability of surface. Additionally, impact of chemical reaction (autocatalysis) and magnetohydrodynamic (MHD) consequences is also integrated into the system. The framed partial differential equations (PDEs) generated by physical problem are converted into new dimensionless form of an ordinary differential system (ODEs). Bvp4c MATLAB procedure is fetched for numerical investigation. It is observed that, velocity profile of the fluid is reduced due to intensification in inclined magnetic effect, whereas autocatalysis effect promotes the concentration of nanoparticles in blood flow mixture, which increases the temperature field of fluid. Furthermore, augmentation in the values of Wassenberg number increased the elasticity in blood which enables it to deform and stretch more readily in reaction to alterations in flow conditions and hence reduction is seen in overall blood flow rate. The results revealed the significance of these integrated factors for accurate modelling of blood flow passing through a stenosed artery, which is crucial in medical interventions.

由四纳米粒子组成的纳米流体具有更好的热传输特性，因此在生物医学领域至关重要。四纳米粒子的先进定制特性使其在热疗等多种医疗干预中大显身手，可以更有效地加热目标组织，从而获得更好的治疗效果。目前的研究调查了四纳米粒子在血液动力学系统中的热传导增强作用。血流的物理结构假定是在可渗透的圆柱形狭窄动脉中。该模型采用了 Carreau 模型，并加入了多种因素，如指数空间热源、粘性耗散、无限剪切速率和表面渗透性。此外，化学反应（自催化）和磁流体力学（MHD）后果的影响也被纳入系统。由物理问题产生的框架偏微分方程 (PDE) 被转换成新的无量纲形式的常微分方程系统 (ODE)。采用 Bvp4c MATLAB 程序进行数值研究。结果表明，由于倾斜磁效应增强，流体的速度曲线减小，而自催化作用促进了血流混合物中纳米粒子的浓度，从而增加了流体的温度场。此外，瓦森伯格数值的增加提高了血液的弹性，使其在流动条件发生变化时更容易变形和拉伸，从而降低了总体血流量。研究结果表明，这些综合因素对于准确模拟通过狭窄动脉的血流具有重要意义，这在医疗干预中至关重要。

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引用次数: 0

Internal temperature prediction and control strategy design of anode-supported solid oxide fuel cell for hot start-up process 阳极支撑型固体氧化物燃料电池热启动过程的内部温度预测和控制策略设计

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105282

Anode-supported solid oxide fuel cell (SOFC) has a high energy efficiency while suffering from a poor transient performance such as start-up. In this study, a model-based design method is proposed to develop a suitable strategy for the rapid hot start-up of anode-supported SOFC (AS-SOFC). First, a mathematical model is established for a 25-kW SOFC system and the internal temperature is predicted. Subsequently, three different strategies are compared during hot start-up process. The results indicate that the positive-electrolyte-negative (PEN) temperature variation magnitude is 50 K and the response time is 1300 s when the hydrogen and the air flow rates are fixed for the afterburner and the cathode. If a PID controller is employed to regulate the flow rate of H₂ to the afterburner, the PEN temperature variation magnitude decreases to 16 K with a shorter response time of 158 s. When increasing the air flow rate synchronously, the PEN temperature variation magnitude is merely 8 K, reduced by 84 % and 50 % compared with the previous strategies. Additionally, the gas temperature exiting from the afterburner declines significantly for the third control strategy. Thus, the lifetime and reliability of AS-SOFC is enhanced. The results provide a reference for the SOFC systems control such as domestic combined heat and power (CHP) and mobile applications.

阳极支撑型固体氧化物燃料电池（SOFC）能量效率高，但启动等瞬态性能较差。本研究提出了一种基于模型的设计方法，为阳极支撑型固体氧化物燃料电池（AS-SOFC）的快速热启动制定合适的策略。首先，建立了 25 千瓦 SOFC 系统的数学模型，并对内部温度进行了预测。随后，比较了热启动过程中的三种不同策略。结果表明，当后燃器和阴极的氢气和空气流量固定时，正电解质-负极（PEN）温度变化幅度为 50 K，响应时间为 1300 s。如果采用 PID 控制器来调节后燃烧器的氢气流量，则 PEN 温度变化幅度会减小到 16 K，响应时间也会缩短到 158 秒；如果同步增加空气流量，则 PEN 温度变化幅度仅为 8 K，与之前的策略相比，分别降低了 84% 和 50%。此外，在第三种控制策略下，后燃烧器排出的气体温度也显著下降。因此，AS-SOFC 的使用寿命和可靠性得到了提高。这些结果为 SOFC 系统控制提供了参考，如家用热电联产（CHP）和移动应用。

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引用次数: 0

An experimental and ANN analysis of ammonia energy integration in biofuel powered low-temperature combustion engine to enhance cleaner combustion 生物燃料驱动的低温内燃机中氨能量集成的实验和 ANN 分析，以提高燃烧清洁度

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105284

In the pursuit of global net-zero emissions targets and cleaner combustion technologies, researchers are increasingly turning to innovative solutions. Ammonia, as a carbon-free fuel, holds promise for achieving low emissions and efficient combustion. This study explores the potential synergies of various ammonia shares (20 %, 40 %, and 60 %) combined with Citronella biofuel in a Low-Temperature Combustion (LTC) Reactivity Controlled Compression Ignition (RCCI) engine. Comparative analysis between a 40 % ammonia blend Citronella biofuel (A40) and a Standard Diesel (SDL) in an RCCI engine demonstrates significant reductions in oxides of nitrogen (by 17 %), carbon dioxide (by 6.6 %), and smoke (by 9.8 %), along with a notable enhancement in Brake Thermal Efficiency (BTE) by 5.4 % for A40. The validation of results using an Artificial Neural Network (ANN) model shows robust coefficients of determination (97 %), high R values (0.9945–0.9995), and low Root Mean Square Error values (ranging from 0.0219 to 0.0483). These findings strongly support the efficacy of the A40 blend, positioning it as a promising and viable alternative fuel for achieving cleaner combustion in LTC-RCCI engines.

为了实现全球净零排放目标和清洁燃烧技术，研究人员越来越多地转向创新解决方案。氨作为一种无碳燃料，有望实现低排放和高效燃烧。本研究探讨了在低温燃烧（LTC）反应控制压燃（RCCI）发动机中将不同比例的氨（20%、40% 和 60%）与香茅生物燃料结合使用的潜在协同效应。在 RCCI 发动机中，40% 的氨混合香茅生物燃料（A40）与标准柴油（SDL）之间的比较分析表明，A40 的氮氧化物（减少 17%）、二氧化碳（减少 6.6%）和烟雾（减少 9.8%）显著减少，制动热效率（BTE）显著提高 5.4%。使用人工神经网络（ANN）模型对结果进行的验证表明，该模型具有稳健的决定系数（97%）、较高的 R 值（0.9945-0.9995）和较低的均方根误差值（0.0219-0.0483）。这些研究结果有力地证明了 A40 混合燃料的功效，并将其定位为在 LTC-RCCI 发动机中实现更清洁燃烧的一种有前途且可行的替代燃料。

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引用次数: 0

Determination of heat transfer characteristics of tube bundles over heating plate by machine learning 通过机器学习确定加热板上管束的传热特性

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105280

In this study machine learning is used with the aid of a deep neural network algorithm to predict convective heat transfer characteristics for inline and staggered tube bundles, and correlation equations for Nusselt number and friction factor are derived. Machine learning algorithm's data were obtained from experimental work for various transverse pitch of the tube bundles, longitudinal pitch of the tube bundles and Reynolds number. 276 experimental data points were taken for both inline and staggered tube bundles. However, considering that the data obtained from the experimental study may be insufficient for training, a two-step data augmentation method and retraining with cross-validation was used to prevent data deficiency in the deep neural network structure. Thus, the unseen data in the experimental work were also predicted. The coefficient of determination for the DNN model predictions was obtained greater than 0.96. One correlation equation for Nusselt Number and three correlation equations for friction factor were proposed from the augmented data with machine learning. The R² values of the correlation equations varied between 89 % and 99 %. As a result, machine learning methods successfully applied to predict the Nusselt number and friction factor of tube bundles consistent with the experimental data.

本研究利用深度神经网络算法进行机器学习，预测直列和交错管束的对流传热特性，并推导出努塞尔特数和摩擦因数的相关方程。机器学习算法的数据来自不同管束横向间距、管束纵向间距和雷诺数的实验工作。直列管束和交错管束的实验数据点均为 276 个。但是，考虑到实验研究获得的数据可能不足以进行训练，因此采用了两步数据增强法和交叉验证再训练法，以防止深度神经网络结构中的数据不足。因此，实验工作中未见的数据也被预测出来了。DNN 模型预测的判定系数大于 0.96。根据机器学习的增强数据，提出了一个努塞尔特数相关方程和三个摩擦因数相关方程。相关方程的 R2 值介于 89 % 和 99 % 之间。因此，机器学习方法成功地应用于预测管束的努塞尔特数和摩擦因数，并与实验数据保持一致。

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引用次数: 0

Energy-economic-environmental analysis of bifacial photovoltaic thermal (BPVT) solar air collector with jet impingement 双面光伏热（BPVT）太阳能空气集热器与喷流冲击的能源-经济-环境分析

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105257

Jet impingement cooling enhances photovoltaic (PV) system efficiency by using high-speed fluid jets to reduce panel temperatures, improving performance and longevity. The effectiveness depends on factors like fluid flow rate, nozzle placement, and distance from the panel. While it boosts energy output, it may increase energy use for fluid circulation and add complexity to the system. This research explores a groundbreaking approach to enhancing the efficiency of bifacial photovoltaic thermal (BPVT) systems by integrating jet impingement technology. A novel design featuring a jet plate reflector is introduced, offering the dual benefit of cooling the PV panels while simultaneously reflecting light to optimize energy capture. The study comprehensively analyses the system’s performance, including energy output and a detailed techno-economic and environmental-economic evaluation. The modelling in this study was validated and reasonably consistent with experimental results. The system's output air temperature and thermal efficiency are 302.07–318.75 K and 33.83–62.28 %, respectively. The temperature and electrical efficiency range for PV systems are 304.39–339.54 K and 9.39–11.22 %. Reduced mass flow rate and increased solar irradiation are the most economically advantageous operating parameters for the proposed system, resulting in lower annual pumping costs and more significant annual energy gains for the system. CBR variations range from 0.1363 to 9.3445, with an average of 2. Additionally, by using BPVT with jet impingement to generate electricity rather than fossil fuels, it is possible to reduce annual carbon dioxide emissions by approximately 1.61 tons and save RM93.51 annually. In general, the proposed method should be used to minimize environmental pollution.

喷射撞击冷却通过使用高速流体喷射来降低面板温度，提高性能和使用寿命，从而提高光伏（PV）系统的效率。冷却效果取决于流体流速、喷嘴位置以及与面板的距离等因素。在提高能量输出的同时，可能会增加流体循环的能耗，并增加系统的复杂性。这项研究探索了一种突破性的方法，通过整合喷射撞击技术来提高双面光伏热系统（BPVT）的效率。该系统采用了以喷流板反射器为特色的新颖设计，在冷却光伏板的同时还能反射光线以优化能量捕获，具有双重优势。研究全面分析了该系统的性能，包括能量输出以及详细的技术经济和环境经济评估。本研究中的建模经过验证，与实验结果基本一致。系统的输出空气温度和热效率分别为 302.07-318.75 K 和 33.83-62.28%。光伏系统的温度和电效率范围分别为 304.39-339.54 K 和 9.39-11.22%。降低质量流量和增加太阳辐照度是拟议系统最具经济优势的运行参数，可降低每年的泵送成本，并为系统带来更显著的年度能源收益。CBR 变化范围为 0.1363 至 9.3445，平均值为 2。此外，通过使用带喷射撞击的 BPVT 发电而非化石燃料，每年可减少约 1.61 吨二氧化碳排放，每年可节省 93.51 马币。总之，应采用所建议的方法来尽量减少环境污染。

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引用次数: 0

A transient network model for cross-regional layered fire smoke diffusion in high-rise buildings 高层建筑跨区域分层火灾烟气扩散瞬态网络模型

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105269

At present, research on smoke diffusion in high-rise building fires mainly focuses on the single smoke layer propagation within a limited area, with less attention paid to the smoke propagation under the joint action of the fire floor and the vertical shaft area. Moreover, research on fire spread often focuses on the composition of combustible materials and building structures, neglecting natural ventilation. To address the above issues, we propose a transient network model for layered smoke diffusion (CLDTN) based on multi-region integration and complex control parameters. This model considers the smoke stratification mode of the fire floor affected by the fire source and ventilation, as well as the vertical stratification mode of the shaft affected by the stack effect, achieving cross-regional smoke stratification and diffusion modeling through smoke coupling. Then, a time-dependent transient network model is used to analyze furniture materials and open ventilation conditions of doors and windows, and a differential equation for energy conservation in multiple scene layers is constructed to analyze the dynamic behavior of smoke propagation.

The comparative experiment of smoke propagation between CLDTN and the Fire Dynamics Simulator (FDS) shows that CLDTN is more efficient in computation time and the model is more accurate.

目前，对高层建筑火灾中烟雾扩散的研究主要集中在有限区域内的单层烟雾扩散，较少关注着火层和竖井区域共同作用下的烟雾扩散。此外，有关火灾蔓延的研究往往侧重于可燃材料和建筑结构的组成，而忽视了自然通风。针对上述问题，我们提出了一种基于多区域集成和复杂控制参数的分层烟雾扩散瞬态网络模型（CLDTN）。该模型考虑了受火源和通风影响的着火层烟气分层模式，以及受烟囱效应影响的竖井垂直分层模式，通过烟气耦合实现了跨区域烟气分层和扩散建模。CLDTN与火灾动力学模拟器（FDS）的烟气传播对比实验表明，CLDTN的计算时间效率更高，模型精度更高。

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引用次数: 0

Artificial intelligence and numerical study of the heat transfer and entropy generation analysis of NEPCM-MWCNTs-Water Hybrid Nanofluids inside a quadrilateral enclosure 四边形围墙内 NEPCM-MWCNTs-Water 混合纳米流体传热和熵生成分析的人工智能和数值研究

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105258

In the present investigation, the primary objective is to assess the synergistic impact of a novel hybrid nanofluid composed of nano-enhanced phase change material, multi-walled carbon nanotubes, and water. The governing equations are transformed into dimensionless forms for a more generalized analysis. To solve the problem, the Galerkin finite element method is employed, offering a robust numerical approach. A dataset of 1000 records was created by numerically solving the model for various combinations of control parameters. Using the dataset, a neural network was trained to learn the relationship between control parameters and heat transfer rate. The evaluation outcomes are comprehensively illustrated through key parameters, including local and average Nusselt numbers, total entropy generation, contours, and streamlines in the range of 10³<Rayleigh number<10⁵, 0<nanotube concentration<0.025, 0<nano capsule concentration <0.025, and 0.1<non-dimensional fusion temperature <0.7. Remarkably, the results indicate a substantial improvement in the heat transfer rate of the suspension for a hybrid concentration of 5 %, showcasing an impressive 13 % enhancement in contrast to the water host fluid's performance. Notably, the observed rise in entropy generation is relatively moderate, only a 5 % increase.

本研究的主要目的是评估由纳米增强相变材料、多壁碳纳米管和水组成的新型混合纳米流体的协同影响。为进行更广泛的分析，将控制方程转换为无量纲形式。为了解决这个问题，采用了 Galerkin 有限元方法，提供了一种稳健的数值方法。通过对各种控制参数组合的模型进行数值求解，创建了一个包含 1000 条记录的数据集。利用该数据集，对神经网络进行了训练，以学习控制参数与传热率之间的关系。在 103<雷利数<105、0<纳米管浓度<0.025、0<纳米胶囊浓度<0.025 和 0.1<非维度融合温度<0.7 的范围内，通过关键参数（包括局部和平均努塞尔特数、总熵生成、等值线和流线）全面说明了评估结果。值得注意的是，结果表明，当混合浓度为 5% 时，悬浮液的传热率大幅提高，与水主流体的性能相比，提高了 13%，令人印象深刻。值得注意的是，观察到的熵增相对较小，仅增加了 5%。

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引用次数: 0

Development and characterisation of myristic acid-paraffin wax, silica fume and zinc oxide cementitious composites for thermal control in buildings 用于建筑物热控的肉豆蔻酸-石蜡、硅灰和氧化锌水泥基复合材料的开发与特性分析

IF 6.4 2区工程技术 Q1 THERMODYNAMICS

Case Studies in Thermal Engineering

Pub Date : 2024-10-11 DOI: 10.1016/j.csite.2024.105283

This study focuses on the development of a cement-based phase change material (CBPCM) to improve thermal performance in construction applications. The CBPCM was synthesised by blending 90 wt% of myristic acid with 10 wt% of paraffin wax, absorbed into 10 wt% of silica fume to prevent leakage. Additionally, 5 wt% of zinc oxide was added to improve thermal conductivity. A leakage test conducted with 10 wt% of SF exhibited no signs of leakage during thermal cycling. Scanning electron microscopy (SEM) established the uniform dispersion of the nano-enhanced phase change material (NEPCM) within the cement. Fourier transform infrared spectroscopy (FTIR) analysis revealed no chemical structure changes after 100 thermal cycles. Thermogravimetric analysis (TGA) confirmed thermal stability in the temperature range of 74.8–236.64 °C with a mass loss of 6.3 wt%. The material demonstrated minimal variation in phase change temperatures and latent heats after 100 cycles. The latent heat of the CBPCM was 1.09 J/g during melting and 1.887 J/g during solidification. Incorporating NEPCM into the cement increased the thermal conductivity of the cement matrix to 0.559 W/m K. These findings underline the potential of the CBPCM for energy-efficient construction, offering enhanced thermal storage, stability, and conductivity.

本研究的重点是开发一种水泥基相变材料（CBPCM），以改善建筑应用中的热性能。CBPCM 的合成方法是将 90 wt% 的肉豆蔻酸与 10 wt% 的石蜡混合，并吸收到 10 wt% 的硅灰中以防止泄漏。此外，还添加了 5 wt%的氧化锌以提高导热性。使用 10 wt% 的 SF 进行的泄漏测试表明，在热循环过程中没有泄漏迹象。扫描电子显微镜（SEM）证实了纳米增强相变材料（NEPCM）在水泥中的均匀分散。傅立叶变换红外光谱（FTIR）分析表明，经过 100 次热循环后，化学结构没有发生变化。热重分析 (TGA) 证实了在 74.8-236.64 °C 温度范围内的热稳定性，质量损失为 6.3 wt%。经过 100 次循环后，该材料的相变温度和潜热变化极小。CBPCM 的熔化潜热为 1.09 焦耳/克，凝固潜热为 1.887 焦耳/克。将 NEPCM 掺入水泥中可将水泥基体的导热系数提高到 0.559 W/m K。这些研究结果凸显了 CBPCM 在节能建筑方面的潜力，它可提供更强的热存储、稳定性和导热性。

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引用次数: 0