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首页> 外文期刊>International journal of numerical methods for heat & fluid flow >Strategies for solving inverse problems in thermal processes and systems
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Strategies for solving inverse problems in thermal processes and systems

机译：解决热处理和系统中逆问题的策略

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Purpose - This paper aims to discuss inverse problems that arise in a variety of practical thermal processes and systems. It presents some of the approaches that may be used to obtain results that lie within a small region of uncertainty. Therefore, the non-uniqueness of the solution is reduced so that the final design and boundary conditions may be determined. Optimization methods that may be used to reduce the uncertainty and to select locations for experimental data and for minimizing the error are presented. A few examples of thermal systems are given to illustrate the applicability of these methods and the challenges that must be addressed in solving inverse problems. Design/methodology/approach - In most analytical and numerical solutions, the basic equations that describe the process, as well as the relevant and appropriate boundary conditions, are known. The interest lies in obtaining a unique solution that satisfies the equations and boundary conditions. This may be termed as a direct or forward solution. However, there are many problems, particularly in practical systems, where the desired result is known but the conditions needed for achieving it are not known. These are generally known as inverse problems. In manufacturing, for instance, the temperature variation to which a component must be subjected to obtain desired characteristics is prescribed, but the means to achieve this variation are not known. An example of this circumstance is the annealing, tempering or hardening of steel. In such cases, the boundary and initial conditions are not known and must be determined by solving the inverse problem to obtain the desired temperature variation in the component. The solutions, thus, obtained are generally not unique. This is a review paper, which discusses inverse problems that arise in a variety of practical thermal processes and systems. It presents some of the approaches or strategies that may be used to obtain results that lie within a small region of uncertainty. It is important to realize that the solution is not unique, and this non-uniqueness must be reduced so that the final design and boundary conditions may be determined with acceptable accuracy and repeatability. Optimization techniques are often used for minimizing the error. This review presents several methods that may be applied to reduce the uncertainty and to select locations for experimental data for the best results. A few examples of thermal systems are given to illustrate the applicability of these methods and the challenges that must be addressed in solving inverse problems. By considering a variety of systems, the paper also shows the importance of solving inverse problems to obtain results that may be used to model and design thermal processes and systems. Findings - The solution of inverse problems, which frequently arise in thermal processes, is discussed. Different strategies to obtain the conditions that lead to the desired result are given. The goal of these approaches is to reduce uncertainty and obtain essentially unique solutions for different circumstances. The error of the method can be checked against known conditions to see if it is acceptable for the given problem. Several examples are given to illustrate the use of these methods. Originality/value - The basic strategies presented here for solving inverse problems that arise in thermal processes and systems, as well as the optimization techniques used to reduce the domain of uncertainty, are fairly original. They are used for certain challenging problems that have not been considered in detail earlier. Several methods are outlined for considering different types of problems.
机译：目的 - 本文旨在讨论各种实用热过程和系统中出现的逆问题。它呈现了一些可用于获得位于不确定性的小区域内的结果的方法。因此，降低了解决方案的非唯一性，从而可以确定最终设计和边界条件。呈现可用于减少不确定性和选择实验数据的位置和最小化误差的优化方法。给出了一些热系统的示例，以说明这些方法的适用性以及必须在解决逆问题时解决的挑战。设计/方法/方法 - 在大多数分析和数字解决方案中，已知描述该过程的基本方程以及相关和适当的边界条件。利息在于获得满足方程和边界条件的唯一解决方案。这可以称为直接或转发解决方案。然而，存在许多问题，特别是在实际系统中，其中所需的结果是已知的，但实现其所需的条件是未知的。这些通常被称为逆问题。例如，在制造中，规定了必须进行组分获得所需特性的温度变化，但是达到该变化的装置是不知道的。这种情况的一个例子是钢的退火，回火或硬化。在这种情况下，边界和初始条件未知，并且必须通过求解逆问题以获得组件中所需的温度变化来确定。因此，得到的解决方案通常不是唯一的。这是一篇审查纸张，讨论了各种实用热过程和系统中出现的逆问题。它介绍了一些方法或策略，可用于获得位于不确定性的小区域内的结果。重要的是要认识到解决方案不是唯一的，并且必须减少这种非唯一性，从而可以以可接受的精度和可重复性确定最终设计和边界条件。优化技术通常用于最小化误差。此述评提供了几种可应用于减少不确定性的方法，并为最佳结果选择实验数据的位置。给出了一些热系统的示例，以说明这些方法的适用性以及必须在解决逆问题时解决的挑战。通过考虑各种系统，本文还显示了解决逆问题以获得可用于模拟和设计热过程和系统的结果的重要性。研究结果 - 讨论了常见问题的逆问题的解决方案。给出了不同的策略，以获得导致所需结果的条件。这些方法的目标是减少不确定性，并在不同情况下获得基本上的解决方案。可以针对已知条件检查该方法的错误，以查看给定的问题是否可接受。给出了几个例子来说明这些方法的使用。原创性/值 - 用于解决热处理和系统中出现的逆问题的基本策略以及用于减少不确定性领域的优化技术，是公平的原始问题。它们用于某些挑战性问题，这些问题尚未详细考虑。考虑不同类型的问题，概述了几种方法。

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