International Journal of Thermofluids最新文献_第3页

Base pressure control through micro jets at supersonic mach numbers using experimental and machine learning approach 基于实验和机器学习方法的超音速马赫数微射流基压控制

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101533

Abdul Aabid , Sher Afghan Khan , Yasir Javed

Sudden expansion phenomena are prevalent in defense and automotive applications, where flow separation at the blunt base of structures such as fuselages, missiles, and rockets leads to low-pressure recirculation zones, significantly reducing base pressure and increasing drag. This study presents active control methods using microjets to regulate base pressure, employing experimental and machine learning approaches. Experiments were conducted using duct diameters of 16 mm, 18 mm, 22 mm, and 25 mm, level of expansion, the Nozzle pressure ratio ranging from 3 to 11, Mach numbers (1.25, 1.3, 1.48, 1.6, 2.0, and 3.0), and length-to-diameter ratios (10–1) were varied to evaluate their impact on flow evolution and base pressure. Active control was achieved using micro-jets of 0.5 mm radius, positioned at 90° intervals along a pitch circle with a radius of 0.65 times the nozzle exit diameter. Micro-jets significantly increased base pressure under favorable pressure-gradient conditions for the Mach numbers 1.25, 1.3, 1.48, 1.6, and 2.0. At Mach M = 3, the control is ineffective as the NPRs are such that the flow from the nozzle remained over-expanded. Furthermore, machine learning (ML) algorithms were utilized to predict base pressure outcomes and optimize control strategies. These algorithms demonstrated high predictive accuracy, as evidenced by low error rates, indicating their reliability in high-speed flow-control applications. The findings reveal that base pressure is strongly influenced by nozzle pressure ratio, Mach number, L/D ratio, and duct area ratio. The study presents cost-effective, energy-efficient methods to enhance base pressure, offering critical insights into the aerodynamic optimization of high-speed systems. This comprehensive approach integrates experimental techniques and ML–based predictions to achieve optimal results in flow control.

突然膨胀现象在国防和汽车应用中很普遍，其中在诸如机身，导弹和火箭等结构的钝基座处的流动分离导致低压再循环区，显着降低基座压力并增加阻力。本研究采用实验和机器学习方法，提出了利用微射流调节基压的主动控制方法。实验采用直径分别为16 mm、18 mm、22 mm和25 mm、膨胀水平、喷管压力比3 ~ 11、马赫数（1.25、1.3、1.48、1.6、2.0和3.0）和长径比（10-1）进行，以评估它们对流动演化和基压的影响。采用半径为0.5 mm的微射流，沿螺距圆以90°间隔定位，半径为喷嘴出口直径的0.65倍，实现了主动控制。在马赫数为1.25、1.3、1.48、1.6和2.0的有利压力梯度条件下，微射流显著提高了基压。在马赫数M = 3时，控制是无效的，因为npr是这样的，从喷嘴流出的流仍然过度膨胀。此外，利用机器学习（ML）算法预测基压结果并优化控制策略。这些算法具有较高的预测精度和较低的错误率，表明了它们在高速流量控制应用中的可靠性。结果表明，喷管压力比、马赫数、L/D比和风管面积比对基压影响较大。该研究提出了经济高效的方法来提高基压，为高速系统的气动优化提供了重要的见解。这种综合方法将实验技术和基于ml的预测相结合，以实现流量控制的最佳结果。

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引用次数: 0

Heat and mass transfer and irreversibilities of humid air flow over a flat plate operating under vacuum 真空条件下平板上湿空气流动的传热传质和不可逆性

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101540

Vo Long Hai , Nguyen Duc Nam , Nguyen Minh Phu

This study presents a numerical investigation into the coupled heat and mass transfer phenomena and the associated thermodynamic irreversibilities (entropy generation) of humid air flowing over a flat plate under vacuum conditions (40 kPa to 100 kPa). A comprehensive mathematical model, incorporating the continuity, momentum, energy, and species transport equations, was established and solved using the finite difference method. The model's accuracy was validated by comparing the numerical local heat transfer coefficient results, which demonstrated excellent agreement with theoretical predictions. Key findings indicate that lower operating pressures significantly enhance mass transfer efficiency: the local mass transfer coefficient approached its maximum value of approximately 4.5 × 10⁻⁴ m/s at 40 kPa. This enhancement translates directly to water production, with the hourly condensation rate increasing from about 0.11 kg/m²-h at 100 kPa to approximately 0.19 kg/m²-h at 40 kPa. Examination of irreversibilities showed that thermal irreversibility is the predominant contributor to entropy generation. At 100 kPa, the local thermal irreversibility peaked at approximately 50 W/m³-K (compared to concentration irreversibility up to 10 W/m³-K and viscous irreversibility around 1.6 × 10⁻³ W/m³-K. On average, the total irreversibility increased with operating pressure, ranging from approximately 0.6 to 0.85 W/m³-K as the pressure rose from 40 kPa to 100 kPa. These quantitative insights offer valuable understanding for optimizing the design and improving the performance of humid air systems operating under vacuum by focusing on reducing thermal energy dissipation.

本文对真空条件下（40kpa至100kpa）平板上流动的湿空气的传热传质耦合现象和相关的热力学不可逆性（熵产）进行了数值研究。建立了包含连续性、动量、能量和物质输运方程的综合数学模型，并用有限差分法求解。通过对局部换热系数数值计算结果的比较，验证了模型的准确性，结果与理论预测结果非常吻合。关键研究结果表明，较低的操作压力显著提高了传质效率：在40 kPa时，局部传质系数接近最大值，约为4.5 × 10−4 m/s。这种增强直接转化为产水，每小时冷凝速率从100 kPa时的约0.11 kg/m2-h增加到40 kPa时的约0.19 kg/m2-h。对不可逆性的考察表明，热不可逆性是熵产生的主要因素。在100 kPa时，局部热不可逆性峰值约为50 W/m3-K（相比之下，浓度不可逆性高达10 W/m3-K，粘性不可逆性约为1.6 × 10−3 W/m3-K）。总的不可逆性随着操作压力的增加而增加，从40 kPa增加到100 kPa，其变化范围约为0.6 ~ 0.85 W/m3-K。这些定量的见解为优化设计和提高真空下湿空气系统的性能提供了有价值的理解，重点是减少热能耗散。

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引用次数: 0

Comparative data-driven modeling of thermal energy storage using artificial neural networks and multiple linear regression 基于人工神经网络和多元线性回归的热能存储数据驱动模型比较

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101539

Eman Abdelhafez , Nabeel Abu Shaban , Mohammad Hamdan , Maher Al-Maghalseh

Efficient thermal energy storage (TES) is essential for enhancing the reliability and sustainability of solar thermal systems, particularly under fluctuating solar radiation conditions. This study investigates the predictive performance of different data-driven approaches—Multiple Linear Regression (MLR), Multilayer Perceptron (MLP), and Radial Basis Function (RBF) neural networks—for estimating stored thermal energy in a solar thermal tank. Experimental data were obtained from a controlled solar simulator setup that incorporated halogen-lamp irradiation, a flat-plate collector, and nanoparticle-enhanced water as the storage medium. Eight independent variables—including collector inlet and outlet temperatures, tank and ambient temperatures, flow rate, solar radiation, nanoparticle concentration, and specific heat capacity—were used as model inputs. Results show that the MLP model significantly outperformed both MLR and RBF, achieving the highest correlation coefficient (R = 0.647), and the lowest RMSE (346.35) and MBE (152.49), demonstrating superior accuracy and generalization. By contrast, MLR exhibited limited predictive power due to its linear assumptions, while RBF suffered from high testing error and poor generalization. These findings underscore the suitability of neural network models, particularly MLP, for capturing the nonlinear dynamics of TES systems, providing a robust framework for system optimization and improved energy management strategies.

高效的热能储存（TES）对于提高太阳能热系统的可靠性和可持续性至关重要，特别是在波动的太阳辐射条件下。本研究探讨了不同数据驱动方法的预测性能——多元线性回归（MLR）、多层感知器（MLP）和径向基函数（RBF）神经网络——用于估计太阳能热储箱中储存的热能。实验数据是从一个受控的太阳模拟器装置中获得的，该装置包括卤素灯照射，平板收集器和纳米粒子增强水作为存储介质。八个独立变量——包括集热器进出口温度、水箱和环境温度、流速、太阳辐射、纳米颗粒浓度和比热容——被用作模型输入。结果表明，MLP模型的相关系数最高（R = 0.647）， RMSE最低（346.35），MBE最低（152.49），显著优于MLR和RBF，具有较好的准确率和泛化能力。相比之下，MLR由于其线性假设而具有有限的预测能力，而RBF则存在较高的测试误差和较差的泛化能力。这些发现强调了神经网络模型（尤其是MLP）在捕获TES系统非线性动力学方面的适用性，为系统优化和改进的能源管理策略提供了一个强大的框架。

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引用次数: 0

Analysis of Plane Poiseuille flow of non-isothermal couple stress fluid between two parallel inclined plates using two reliable methods 用两种可靠的方法分析平行斜板间非等温偶应力流体的平面泊泽维尔流

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101520

Muhammad Farooq , Faisal Zia , Rashid Nawaz , Alamgeer Khan , Ilker Ozsahin , Hijaz Ahmad , Waleed Mohammed Abdelfattah

This study is motivated by the need to understand complex thermal and hydrodynamic behaviors of couple stress fluids, which commonly occur in lubrication systems, microfluidic devices, and polymeric material processing. Its significance lies in modeling non-isothermal couple stress fluid flow through an inclined Poiseuille channel bounded by two heated parallel plates, a configuration relevant to advanced heat and mass transfer applications. The aim is to determine the velocity profile, temperature distribution, volumetric flow rate, average velocity, and shear stress for the incompressible fluid. To achieve this, the highly nonlinear coupled ordinary differential equations governing the system are solved using the Optimal Homotopy Asymptotic Method and the Homotopy Perturbation Method, which provide accurate approximate solutions without linearization. The major findings show excellent agreement between the two approaches, confirming their validity, while parametric studies reveal how physical factors such as couple stress effects, plate inclination, and thermal gradients influence the flow. The specific applications of this work include lubrication processes, thermal energy devices, and fluid transport systems requiring precise control of flow and heat transfer.

这项研究的动机是需要了解耦合应力流体的复杂热和流体动力学行为，这通常发生在润滑系统，微流体装置和聚合物材料加工中。其意义在于模拟非等温偶应力流体通过由两个受热平行板包围的倾斜泊泽维尔通道的流动，这是一种与高级传热传质应用相关的构型。目的是确定不可压缩流体的速度分布、温度分布、体积流量、平均速度和剪切应力。为此，采用最优同伦渐近法和同伦摄动法对控制系统的高度非线性耦合常微分方程进行了求解，得到了不需要线性化的精确近似解。主要研究结果表明，两种方法之间的一致性非常好，证实了它们的有效性，而参数研究揭示了诸如耦合应力效应、板倾角和热梯度等物理因素如何影响流动。这项工作的具体应用包括润滑过程，热能装置和流体输送系统，需要精确控制流动和传热。

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引用次数: 0

Hydrogen absorption in metal hydrides: A dual-head tree-based framework for material class classification 金属氢化物中的氢吸收：材料类别分类的双头树框架

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101521

Zaid Allal , Hassan N. Noura , Flavien Vernier , Ola Salman , Khaled Chahine

Metal hydrides represent a highly promising alternative for hydrogen storage due to their favorable absorption properties and relatively moderate requirements in terms of temperature and pressure during the uptake stage. Furthermore, their ability to undergo multiple absorption–desorption cycles without significant degradation makes them particularly well-suited for repeated charge–discharge operations. In this work, we propose a two-headed machine learning framework for the classification of metal hydrides. The first head determines whether a material belongs to the AB family of hydrides. If not, the second head classifies it into one of the remaining categories: MIS, SS, MG, or complex hydrides. This hierarchical modeling strategy, inspired by fault detection and diagnosis in biphasic systems, proved effective in improving classification accuracy. The framework was trained using six tree-based estimators: Random Forest, LightGBM, XGBoost, CatBoost, Gradient Boosting, and Extra Trees. Strong imputation techniques, including the KNN imputer, were also employed to address missing data and ensure robustness. The results demonstrate that for the first head, the Random Forest model achieved an accuracy of 88.6% in identifying the AB family class. For the second head, Gradient Boosting reached 91.61% accuracy, which was further improved to 92.56% after hyperparameter tuning. When compared to previous studies using the same dataset, our framework exhibits significantly stronger performance. Moreover, its predictions were validated through the integration of explainable artificial intelligence (XAI) methods, ensuring both interpretability and reliability. This framework will be further optimized to extend beyond class-level identification toward the precise prediction of hydride composition formulas, with the aim of better supporting the design of materials with enhanced hydrogen absorption capacities.

由于金属氢化物具有良好的吸收特性，并且在吸收阶段对温度和压力的要求相对适中，因此金属氢化物是一种非常有前途的储氢方法。此外，它们经历多次吸收-解吸循环而没有明显降解的能力使它们特别适合重复充放电操作。在这项工作中，我们提出了一个用于金属氢化物分类的双头机器学习框架。第一个头确定材料是否属于AB族氢化物。如果不是，第二个头部将其分类为其余类别之一：MIS， SS， MG或复合氢化物。这种分层建模策略受到双相系统故障检测和诊断的启发，有效地提高了分类精度。该框架使用六个基于树的估计器进行训练：Random Forest， LightGBM, XGBoost, CatBoost， Gradient Boosting和Extra Trees。强输入技术，包括KNN输入器，也被用来解决缺失的数据和确保鲁棒性。结果表明，对于第一个头部，随机森林模型在识别AB族类方面达到了88.6%的准确率。对于第二个头部，Gradient Boosting的准确率达到了91.61%，经过超参数调优后进一步提高到92.56%。与之前使用相同数据集的研究相比，我们的框架表现出明显更强的性能。此外，通过可解释人工智能（XAI）方法的集成验证了其预测，确保了可解释性和可靠性。该框架将进一步优化，以超越类别级别的识别，扩展到氢化物组成公式的精确预测，以更好地支持具有增强吸氢能力的材料的设计。

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引用次数: 0

Exploring the impact of unit cell size on fluid dynamics in lattice structures: Experimental and numerical insights 探索单元胞大小对晶格结构中流体动力学的影响：实验和数值见解

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101543

Leonardo Bernardini , Stefano Piacquadio , Kai-Uwe Schröder , Mauro Mameli , Paolo Di Marco , Sauro Filippeschi

Advanced manufacturing techniques have made it possible to customize the geometry of solids unit cells, creating various architected materials. One type of such material is the strut or surface-based lattice. In this work, we investigated fluid flow through two lattice structure topologies, body-centered cubic (bcc) and face-centered cubic with vertical strut (f₂ccz). The goal is to understand the effect of the unit cell size and cell orientation on pressure drops and permeability. By doing this, we aim to clarify how the scale of the unit cell influences the treatment of lattice structures as porous media. Through the experimental campaign, we characterized the pressure drops across these structures and performed dimensionless analyses of the measurements. The investigation involved a numerical model to simulate fluid flow behavior at low velocities and determine permeability using the Darcy equation. Finally, we coupled the experimental results with numerical simulations to assess the inertial coefficient in the Darcy-Forchheimer correlation. The results showed that, given the cell topology, porosity and flow direction, it is possible to uniquely determine the relationship between velocity and pressure losses as a function of hydraulic diameter. Additionally, the permeability ratio to the square of the hydraulic diameter, with fixed topology, porosity and flow direction, resulted in a constant.

先进的制造技术使得定制固体单元格的几何形状成为可能，从而创造出各种建筑材料。这种材料的一种是支撑或基于表面的晶格。在这项工作中，我们研究了流体在两种晶格结构拓扑中的流动，即体心立方（bcc）和面心立方（f2ccz）。目的是了解单位孔的尺寸和孔的方向对压降和渗透率的影响。通过这样做，我们的目的是澄清单位胞的规模如何影响晶格结构作为多孔介质的处理。通过实验，我们对这些结构的压降进行了表征，并对测量结果进行了无因次分析。该研究涉及一个数值模型来模拟流体在低速下的流动行为，并使用达西方程确定渗透率。最后，我们将实验结果与数值模拟相结合，评估了Darcy-Forchheimer相关中的惯性系数。结果表明，在给定池的拓扑结构、孔隙度和流动方向的情况下，可以唯一地确定速度和压力损失之间的关系，作为水力直径的函数。此外，在拓扑结构、孔隙度和流动方向固定的情况下，渗透率与水力直径的平方比为常数。

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引用次数: 0

Analysis of thermal and concentration transport in unsteady MHD squeezing nanofluid flow under the influence of chemical reaction and joule heating 化学反应和焦耳加热影响下非定常MHD压缩纳米流体的热输运和浓度输运分析

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101537

Sharad Sinha , Prachi Gupta , Saleem Nasir , K. Loganathan , Kavita Jat , Abdallah Berrouk

This research investigates the unsteady magnetohydrodynamic (MHD) squeezing flow of a viscous incompressible nanofluid enclosed between two parallel plates and affected by an inclined magnetic field. Suction/injection at the lower plate is also considered to enhance control over the flow. Such flow occurs in microfluidics, lubrication, material processing, and cooling devices, which indicates the need to introduce transport mechanisms at small scales. The flow is driven by the motion of the lower plate translating in its own plane, while the upper plate moves perpendicularly. The flow governing equations are converted to a set of coupled, nonlinear ordinary differential equations through similarity transformations. These reduced equations are then numerically solved using the bvp4c MATLAB solver. Validation is achieved for the obtained outcomes by comparing with existing literature. The study presents comprehensive parametric analyses of velocity, temperature, and concentration profiles through their graphical representations under varying parameter conditions. When the squeezing parameter increases, the velocity profile improves in both suction and injection cases. For the Schmidt parameter (0.1 ≤ Sc≤ 1.0), the concentration profile decreases ϕ(η = 0.3) = 0.200695 to ϕ(η = 0.3) = 0.163544) in the injection case. The temperature profile enhances, but the concentration profile declines when distance parameter goes from δ=0.1 to δ=0.8. Furthermore, detailed analyses of skin friction, Nusselt number, and Sherwood number are provided at both plates to offer more profound insights into the physical phenomena, with potential implications for applications in microfluidic systems, cooling technologies, and industrial fluid processes.

本文研究了粘滞不可压缩纳米流体在倾斜磁场作用下的非定常磁流体压缩流动。下部板的吸入/喷射也被认为可以加强对流动的控制。这种流动发生在微流体、润滑、材料加工和冷却装置中，这表明需要在小尺度上引入输送机制。流动是由下板在其自身平面内平移的运动驱动的，而上板是垂直运动的。通过相似变换将流动控制方程转化为一组耦合的非线性常微分方程。然后使用bvp4c MATLAB求解器对这些简化方程进行数值求解。通过与已有文献的比较，对所得结果进行验证。该研究通过在不同参数条件下的图形表示，对速度、温度和浓度剖面进行了全面的参数分析。随着挤压参数的增大，吸入和喷射工况下的速度分布都有所改善。当Schmidt参数为0.1≤Sc≤1.0时，注入情况下的φ (η = 0.3) = 0.200695减小到φ (η = 0.3) = 0.163544。当距离参数从δ=0.1增大到δ=0.8时，温度曲线增大，浓度曲线减小。此外，在两个板上提供了皮肤摩擦，努塞尔数和舍伍德数的详细分析，以提供对物理现象的更深刻的见解，对微流体系统，冷却技术和工业流体过程的应用具有潜在的意义。

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引用次数: 0

Numerical and artificial neural network time-series modeling of Casson–Jeffrey nanofluid flow over linear and nonlinear stretching surfaces in porous media 多孔介质中线性和非线性拉伸表面上Casson-Jeffrey纳米流体流动的数值和人工神经网络时间序列建模

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101534

Yogesh K. , Varatharaj K. , Tamizharasi R.

This study investigates the synergistic influence of magnetohydrodynamics, thermal radiation and porous medium on the transport of Casson–Jeffrey hybrid nanofluid over both linear and nonlinear stretching sheets. The governing equations are solved numerically using the Runge–Kutta with Shooting method and the outcomes are validated with a multilayer perceptron artificial neural network in neural network time series. The key controlling parameters include magnetic number, Casson parameter, Jeffrey parameter, buoyancy ratio, radiation parameter, Brownian motion, thermophoresis, Prandtl number and heat generation. The results demonstrate that increasing the magnetic parameter from 0.1 to 0.4 enhances the skin friction magnitude by approximately 12% for linear stretching and 15% for nonlinear stretching. Similarly, raising the radiation parameter from 0.1 to 0.4 increases skin friction magnitude by about 10% in the linear case and 25% in the nonlinear case. In contrast, the Nusselt number decreases when the Brownian motion parameter rises from 0.1 to 0.4, leading to an almost 11% reduction in both linear and nonlinear flows. Thermophoresis effects further suppress the heat transfer rate, showing a 5% decline when its value increases from 0.1 to 0.4. Neural network validation confirms the accuracy of the solver, with regression coefficients very close to unity

R \approx 0.9999

and mean square error values as low as

1.84 \times 1 0^{- 6}

. These findings underline the physical importance of magnetic, radiative, and porous medium effects in hybrid nanofluid transport and demonstrate the effectiveness of artificial intelligence tools for predictive modeling. Future research can extend this framework to unsteady, three-dimensional and experimentally validated configurations.

本文研究了磁流体力学、热辐射和多孔介质对卡森-杰弗里混合纳米流体在线性和非线性拉伸片上输运的协同影响。采用龙格-库塔射击法对控制方程进行数值求解，并用多层感知器人工神经网络在神经网络时间序列中对结果进行验证。关键控制参数包括磁数、卡森参数、杰弗里参数、浮力比、辐射参数、布朗运动、热游、普朗特数和产热。结果表明，将磁参量从0.1增加到0.4，在线性拉伸情况下，表面摩擦强度提高约12%，在非线性拉伸情况下，表面摩擦强度提高约15%。同样，将辐射参数从0.1提高到0.4，在线性情况下，皮肤摩擦值增加约10%，在非线性情况下，皮肤摩擦值增加约25%。相反，当布朗运动参数从0.1上升到0.4时，努塞尔数减少，导致线性和非线性流动都减少了近11%。热泳效应进一步抑制了传热速率，当传热速率从0.1增加到0.4时，传热速率下降5%。神经网络验证证实了求解器的准确性，回归系数非常接近单位R≈0.9999，均方误差值低至1.84×10−6。这些发现强调了磁性、辐射和多孔介质效应在混合纳米流体输运中的物理重要性，并证明了人工智能工具用于预测建模的有效性。未来的研究可以将该框架扩展到非定常、三维和实验验证的构型。

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引用次数: 0

Results of experimental research on drying Occimum basilicum 罗勒干燥的实验研究结果

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101536

Sh.A. Sultanova , J.E. Safarov , A.A. Mambetsheripova , M.M. Pulatov , A.B. Usenov , B.M. Jumaev , Gunel Imanova

The aim of this paper is to summarize the results obtained experimentally by determining the characteristic drying curve based on the tests performed. The method adopted is to study the variation of the standardized drying rate f as a function of the reduced water content W. This leads to the convergence of the different values obtained around one average curve, which is the characteristic drying curve. The equation expressing the drying kinetics of the product is written as follows: f*=f(W). The dimensionless water content (-dW/dt) represents the continuity of relative humidity fluctuations during drying.

本文的目的是总结实验所得的结果，在进行试验的基础上确定特性干燥曲线。所采用的方法是研究标准化干燥速率f作为减少含水量w的函数的变化，从而使得到的不同值收敛在一条平均曲线周围，这就是特征干燥曲线。表示产物干燥动力学的方程为：f*=f(W)。无因次含水量（-dW/dt）表示干燥过程中相对湿度波动的连续性。

引用次数: 0

Evaluation of Thermal Performance of Innovative Insulation Materials for Energy-Efficient Buildings in Cold Climates 寒冷气候下节能建筑新型保温材料的热性能评价

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 DOI: 10.1016/j.ijft.2025.101544

Ali Maboudi Reveshti , Farid Hosseini Mansoub , Jhila Nasiri Reveshti , Karim Farajeyan Bonab

This study investigates the thermal performance of four innovative insulation materials phase change materials (PCM), aerogel, vacuum insulated panels (VIP), and autoclaved aerated concrete (AAC)for cold-climate buildings in Varzaqan, Iran. Using 24 years of hourly climate data, five wall configurations (uninsulated reference, PCM, aerogel, VIP, and AAC) were simulated in EnergyPlus, with PCM behavior modeled via an enthalpy-temperature phase change routine. Key indicators included annual heating energy demand, wall surface temperature stability, time lag, and comfort hours. Results show that VIP achieved the greatest reduction in annual heating demand (36.6%), followed by aerogel (29.5%), AAC (24.1%), and PCM (21.4%). PCM and AAC provided substantial thermal inertia, delaying heat transfer by150–180 min and90–120 min, respectively, thereby enhancing night-time comfort. In contrast, VIP and aerogel maintained nearly constant surface temperatures (fluctuations <3ºC). Hybrid configurations offered the most favorable outcomes: a VIP+PCM wall reduced annual demand by 40.3% and achieved∼6510 comfort hours (74% of the year). Passive solar gains, when integrated into the analysis, improved PCM effectiveness by ∼12% in sunny winter days, while AAC showed moderate benefit and VIP remained largely unaffected. Sensitivity analysis highlighted VIP’s vulnerability to vacuum loss ∼12% performance degradation and AAC’s dependence on moisture, whereas aerogel and PCM proved more robust. Overall, the findings underscore the complementarity of ultra-low conductivity materials (VIP, aerogel) and high thermal mass/storage materials (PCM,AAC). While economic and practical barriers remain, hybrid approaches represent a promising pathway to significantly reducing heating energy demand and improving thermal comfort in cold climates.

本研究调查了四种新型保温材料相变材料（PCM）、气凝胶、真空隔热板（VIP）和蒸压加气混凝土（AAC）在伊朗Varzaqan寒冷气候建筑中的热性能。利用24年的每小时气候数据，在EnergyPlus中模拟了五种壁面构型（非绝热参考、PCM、气凝胶、VIP和AAC），并通过焓温相变程序模拟了PCM的行为。主要指标包括年供暖能源需求、壁面温度稳定性、时间滞后和舒适时间。结果表明，VIP的年采暖需求降幅最大（36.6%），其次是气凝胶（29.5%）、AAC（24.1%）和PCM（21.4%）。PCM和AAC提供了大量的热惯性，分别将传热延迟150 - 180分钟和90 - 120分钟，从而提高了夜间舒适性。相比之下，VIP和气凝胶的表面温度几乎保持恒定（波动<；3ºC）。混合配置提供了最有利的结果：VIP+PCM墙减少了40.3%的年需求，实现了6510舒适小时（一年的74%）。当纳入分析时，被动式太阳能增益在阳光明媚的冬季将PCM效率提高了约12%，而AAC显示出中等效果，VIP基本未受影响。敏感性分析强调VIP易受真空损失~ 12%的性能下降和AAC对水分的依赖，而气凝胶和PCM被证明更坚固。总的来说，这些发现强调了超低电导率材料（VIP，气凝胶）和高热质量/存储材料（PCM，AAC）的互补性。尽管经济和实际障碍仍然存在，但混合方法代表了一种有希望的途径，可以显著减少供暖能源需求，改善寒冷气候下的热舒适。

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