【摘要】 为了研究岩石裂隙中的渗流传热耦合作用机制，基于物理信息神经网络方法，将表征流体渗流流动的Navier-Stokes方程与传热过程的对流-扩散方程作为物理约束嵌入神经网络的训练过程，并引入温度依赖的运动黏度动态反馈机制建立了模拟流体渗流流动与传热过程耦合作用的数值计算模型。结合经典Poiseuille流传热问题，验证了计算模型的准确性，并与有限元计算结果对比，证明了其在处理不规则几何边界问题时的稳定性。最后，研究了流体运动黏度、渗流流速（水力梯度、裂隙开度、壁面粗糙程度等）和裂隙壁面温度等因素对流体渗流传热耦合作用机制的影响。研究结果表明：若考虑温度对流体运动黏度的影响，则裂隙中心区最大流速从0.53 mm/s提升至1.92 mm/s，增大了262.3%。流速差异进一步影响温度场分布，导致裂隙中心温度从160.1℃下降至110.2℃，降低了31.2%。水力梯度从1 Pa/m增加至4 Pa/m的过程中，对流热通量峰值显著增大，且增幅远高于扩散热通量，导致核心区流体温度下降了42.3%。裂隙开度增加引起的流速提升能够有效削弱边界层厚度，显著增强传热效率。裂隙壁面分形维数增加，使得流动阻力增大，有利于裂隙通道的热传递，导致裂隙出口处流体温度提高。当裂隙壁面温度从100℃升至200℃时，流体运动黏度峰值降低了55.7%，渗流流速峰值增幅达126.7%，核心区温差增大了372.4%。更多还原

【Abstract】 To investigate the coupling mechanism of seepage and heat transfer in rock fractures, a numerical model was developed based on the physics-informed neural networks method. The Navier-Stokes equations governing fluid seepage and the convection-diffusion equation describing heat transfer were embedded as physical constraints into the neural network training process. Additionally, a dynamic feedback mechanism for temperature-dependent kinematic viscosity was introduced to propose a numerical model simulating the coupled effects of fluid seepage and heat transfer. The accuracy of the proposed model was validated against the classical Poiseuille flow heat transfer problem. Furthermore, comparison with finite element method results demonstrated its superior stability in handling problems with irregular geometric boundaries. Finally, the effects of fluid kinematic viscosity, seepage velocity(hydraulic gradient, fracture aperture, wall roughness, etc.), and fracture wall temperature on the coupling mechanism of fluid seepage and heat transfer were investigated. The results indicate that if the effect of temperature on the fluid kinematic viscosity is considered, the maximum velocity in the fracture center increases from 0.53 mm/s to 1.92 mm/s, representing an increase of 262.3%. This velocity difference further alters the temperature distribution and reduces the central fracture temperature from 160.1 ℃ to 110.2 ℃(a 31.2% decrease). As the hydraulic gradient increases from 1 Pa/m to 4 Pa/m, the convective heat flux peak rises significantly, far exceeding the increase in diffusive heat flux, leading to a 42.3% decrease in the core fluid temperature. An increase in fracture aperture enhances fluid velocity, which effectively reduces boundary layer thickness and significantly improves heat transfer efficiency. An increase in the fractal dimension of the fracture wall leads to greater flow resistance, which enhances heat transfer through the fracture channel and results in a higher fluid temperature at the outlet. When the fracture wall temperature increases from 100 ℃ to 200 ℃, the peak fluid kinematic viscosity decreases by 55.7%, while the peak seepage velocity rises by 126.7%, and the core region temperature difference expands by 372.4%.更多还原