The correct expression of temperature measurement results is of the utmost importance for experimental research in thermal sciences. Temperature measurements are used in heat transfer models to estimate various parameters, either in direct or inverse problems. The reliability of these parameter values depends mainly on the uncertainty associated with the measured temperature. This paper deals with the application of Monte Carlo method for uncertainty quantification, in an experimental model of heat transfer that describes the behavior of a homogeneous, isotropic and linear solid. Temperature measurements were carried out using a type K thermocouple, considering a nominal measuring range from − 5 °C to 110 °C, at a given point in an AISI 304 stainless steel sample, specifically a massive cylindrical billet. The sample was placed in an experimental setup, and it was submitted to a one-dimensional steady-state thermal field, with boundary conditions of prescribed temperature and prescribed heat flux. The uncertainty associated with temperature was assessed using the Monte Carlo method, and the obtained results were compared with those calculated by the Guide to the Expression of Uncertainty in Measurement (GUM). Noteworthy in this study was that the temperature simulated values follow a Gaussian probability distribution function. The expanded uncertainty (k =2.00) associated with temperature (in Kelvin) was 0.42 % about the measured average temperature. The results presented herein can be useful for those cases when the mechanical component is not fully accessible physically. Therefore, using the temperature measured in a particular region and since the heat conduction problem is unidimensional in a steady state, it is possible to estimate the temperature in any section.

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通过在一维导热实验中使用蒙特卡洛方法进行不确定性量化

温度测量结果的正确表达对于热科学实验研究至关重要。在传热模型中使用温度测量来估计各种参数，无论是正问题还是逆问题。这些参数值的可靠性主要取决于与测量温度相关的不确定性。本文介绍了蒙特卡罗方法在不确定性定量分析中的应用，该模型用于描述均质，各向同性和线性固体行为的传热实验模型中。温度测量是使用K型热电偶进行的，考虑到AISI 304不锈钢样品（特别是大块圆柱形钢坯）中给定点的标称测量范围为− 5°C至110°C。将样品置于实验装置中，并使其处于规定温度和规定热通量的边界条件下的一维稳态热场。使用蒙特卡洛方法评估与温度相关的不确定性，并将获得的结果与“测量不确定度表示指南”（GUM）计算的结果进行比较。在这项研究中值得注意的是，温度模拟值遵循高斯概率分布函数。扩大的不确定性（并将获得的结果与《测量不确定度表示指南》（GUM）计算的结果进行比较。在这项研究中值得注意的是，温度模拟值遵循高斯概率分布函数。扩大的不确定性（并将获得的结果与《测量不确定度表示指南》（GUM）计算的结果进行比较。在这项研究中值得注意的是，温度模拟值遵循高斯概率分布函数。扩大的不确定性（与温度相关的k  = 2.00）（以开尔文为单位）约为实测平均温度的0.42％。对于机械部件在物理上无法完全访问的情况，此处提供的结果可能有用。因此，使用在特定区域中测得的温度，并且由于在稳态下热传导问题是一维的，因此可以估计任何部分的温度。