The Impact of the Location of Temperature Sensors on the Accuracy of Transient-State Temperature Distribution Identification

M. Konieczny
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Abstract

Extended Abstract Many structures in various technical applications operate under strong thermal conditions. Steadyor transient-state heat transfer phenomena can create substantial temperature differences which should not exceed the allowable limit. The common problem of calculating the temperature field is the difficulty in accessing some of the thermal boundary conditions in operated elements. This usually concerns internal surfaces, where the fluid is in contact with the element. Numerical analysis of phenomena taking place in a flowing fluid is very time-consuming. Another way to determine the temperature distribution is to find the solution of the inverse heat conduction problem (IHCP) in the device under analysis [1-4] and verify it experimentally [5]. Despite the unknown boundary condition, the proposed method makes it possible to determine the temperature field using “measured” temperature histories determined in easily accessible points on the component outer surface, using energy balance equations. Unfortunately, the accuracy of the method is strongly dependent on the distance between the temperature sensors and the unknown boundary. The second factor creating the final error is the uncertainty of the thermocouple input data. For bigger distances, e.g. in a thick-walled pressure component burdened with measurement errors, oscillations appear in the solutions and the solution error can rise to unacceptable values. Information about the error size is crucial in determining the potential use of specific applications. As a result of a series of transient-state numerical analyses, the final error value was determined as a function of the wall thickness and measurement inaccuracy. “Measurement” errors of ±0.25, ±0.5, and ±1°C were assumed and implemented in the analysis as disturbance. Numerical tests were conducted for two types of a thick-walled pipe with the inner diameter of 160 mm and the wall thickness values of 40 and 60 mm, respectively. It is assumed that the pipe with a uniform initial temperature distribution is partially flooded by the hot medium, which simulates the system heating process. The outer surface is exposed to ambient air. Additionally, in order to overcome instabilities, the influence of smoothing digital filters was investigated. It may be stated that the expected standard deviation σ < 2 (relative error measure RE < 0.5%) of the final result can be achieved for the input error of ±0.5°C for the 40-mm-thick wall, but the input data acceptable error for the wall thickness of 60 mm should be ±0.25°C and smoothing filters must be used additionally. Both levels of temperature measurement accuracy are achievable for industrial thermocouples. For the wall thickness of 60 mm and the input error of ± 0.5°C (no filters applied), the standard deviation value is much higher: σ ≈ 5.1 (RE ≈ 36%). The algorithm is stable even for thick walls. However, for thicknesses over 50mm, it becomes more sensitive to input errors and requires additional filters to ensure stability.
温度传感器位置对瞬态温度分布识别精度的影响
在各种技术应用中,许多结构都在强热条件下工作。稳态或瞬态传热现象会产生不应超过允许极限的巨大温差。计算温度场的常见问题是难以获得运行元件的某些热边界条件。这通常涉及流体与元件接触的内表面。对流动流体中发生的现象进行数值分析是非常耗时的。另一种确定温度分布的方法是在被分析器件中找到逆热传导问题(IHCP)的解[1-4],并进行实验验证[5]。尽管存在未知的边界条件,但所提出的方法可以使用能量平衡方程,利用在组件外表面易于接近的点上确定的“测量”温度历史来确定温度场。不幸的是,该方法的精度强烈依赖于温度传感器与未知边界之间的距离。产生最终误差的第二个因素是热电偶输入数据的不确定性。对于较大的距离,例如在测量误差较大的厚壁压力元件中,溶液中出现振荡,溶液误差可能上升到不可接受的值。有关错误大小的信息对于确定特定应用程序的潜在用途至关重要。通过一系列的瞬态数值分析,确定了最终误差值是壁厚和测量精度的函数。假设“测量”误差为±0.25、±0.5和±1°C,并将其作为干扰进行分析。对内径为160 mm、壁厚分别为40和60 mm的两种厚壁管进行了数值试验。假设初始温度分布均匀的管道部分被热介质淹没,模拟系统加热过程。外表面暴露在环境空气中。此外,为了克服不稳定性,研究了平滑数字滤波器的影响。对于40 mm厚壁,当输入误差为±0.5℃时,最终结果的期望标准差σ < 2(相对误差测量RE < 0.5%),但对于60 mm厚壁,输入数据可接受误差应为±0.25℃,并且必须另外使用平滑滤波器。对于工业热电偶来说,这两种温度测量精度都是可以实现的。当壁厚为60mm,输入误差为±0.5°C(不加滤波器)时,标准差值更高:σ≈5.1 (RE≈36%)。该算法即使对厚壁也很稳定。然而,对于超过50mm的厚度,它对输入误差变得更加敏感,并且需要额外的滤波器来确保稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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