Even with specialized equipment, it is difficult to measure the thermal parameters of dam concrete during freeze–thaw testing. In addition, numerical calculations usually assume that freeze–thaw cycling does not change the thermal parameters of the aggregate and mortar of dam concrete, which makes it difficult to accurately determine how these parameters evolve during freeze–thaw deterioration. To address this challenge, we propose herein a new method to determine the thermal parameters of wet-screened dam concrete during freeze–thaw deterioration. This method involves freeze–thaw testing, temperature perturbation, numerical calculation, and optimization inversion. First, 200 rapid freeze–thaw tests and 5 temperature perturbation tests of 5 concrete specimens were carried out. Next, orthogonal design parameters were used to calculate the temperature field of the specimens via the finite-element method. A neural network was then established based on the difference between the measured and calculated temperatures. The expected difference and measured density were fed into the model to invert the thermal parameters of the concrete for different water–cement ratios, ages, and content of the air-entraining agent. The results show that, upon increasing the number of freeze–thaw cycles, the thermal conductivity of wet-screened dam concrete gradually decreases, the specific heat remains relatively constant, and the surface heat-transfer coefficient gradually increases.

中文翻译：

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不同冻融劣化后湿筛坝混凝土热力参数的演变

即使使用专门的设备，也很难在冻融试验期间测量大坝混凝土的热参数。此外，数值计算通常假设冻融循环不会改变大坝混凝土骨料和砂浆的热参数，这使得难以准确确定这些参数在冻融劣化过程中如何变化。为了应对这一挑战，我们在此提出了一种新方法来确定冻融恶化过程中湿筛坝混凝土的热参数。该方法涉及冻融测试、温度扰动、数值计算和优化反演。首先，对 5 个混凝土试件进行了 200 次快速冻融试验和 5 次温度扰动试验。下一个，正交设计参数用于通过有限元方法计算试样的温度场。然后根据测量温度和计算温度之间的差异建立神经网络。将预期差异和测量密度输入模型，以反演不同水灰比、年龄和引气剂含量的混凝土热参数。结果表明，随着冻融循环次数的增加，湿筛坝混凝土的导热系数逐渐降低，比热保持相对恒定，表面传热系数逐渐增大。将预期差异和测量密度输入模型，以反演不同水灰比、年龄和引气剂含量的混凝土热参数。结果表明，随着冻融循环次数的增加，湿筛坝混凝土的导热系数逐渐降低，比热保持相对恒定，表面传热系数逐渐增大。将预期差异和测量密度输入模型，以反演不同水灰比、年龄和引气剂含量的混凝土热参数。结果表明，随着冻融循环次数的增加，湿筛坝混凝土的导热系数逐渐降低，比热保持相对恒定，表面传热系数逐渐增大。