This paper describes the first steps toward developing a highly-accurate multi-layered slug calorimeter for estimating the surface heat flux in high-enthalpy flows associated with hypersonic ground test campaigns. Slug geometry, material choices, test conditions, manufacturing method, mathematical modeling and instrumentation selection must be integrated into the design process in order to achieve the desired accuracy outcome. Integration is often overlooked in lieu of simplified data reduction equations that relate in-depth temperature measurements to the desired surface heat flux. Simplified models are often physics deficient and can lead to misleading interpretations. This paper illustrates the need for inclusive modeling in arriving at the data reduction equation for the heat flux gauge. Several important results are highlighted in this paper including the: (a) identification of data reduction model discrepancies; (b) significance of Volterra integral formulations for algorithm development; (c) implementation of a parameter-free preconditioner operated on data reduction model for low-pass filtering; (d) development of the approximation thread for uncertainty propagation; (e) achievement of stability through the future-time method; and, (f) extraction of the optimal regularization parameter through phase-plane and cross-correlation concepts for estimating the “best” heat flux.

本文介绍了开发高精度多层弹头热量计的第一步，以估算与高超声速地面试验活动相关的高焓流中的表面热通量。子弹的几何形状，材料选择，测试条件，制造方法，数学建模和仪器选择必须集成到设计过程中，以实现所需的精度结果。常常会忽略积分，而不是将深度温度测量与所需的表面热通量相关联的简化的数据缩减方程。简化的模型通常在物理上是不足的，并且可能导致误导性的解释。本文说明了在建立热通量表的数据缩减方程式时需要进行包容性建模的需求。本文重点介绍了以下重要结果：（a）识别数据缩减模型的差异；（b）Volterra积分公式对算法开发的意义；（c）实施以数据缩减模型运行的无参数预处理器，以进行低通滤波；（d）开发不确定性传播的近似线程；（e）通过未来时间方法实现稳定；（f）通过相位平面和互相关概念提取最佳正则化参数，以估算“最佳”热通量。（d）开发不确定性传播的近似线程；（e）通过未来时间方法实现稳定；（f）通过相位平面和互相关概念提取最佳正则化参数，以估算“最佳”热通量。（d）开发不确定性传播的近似线程；（e）通过未来时间方法实现稳定；（f）通过相位平面和互相关概念提取最佳正则化参数，以估算“最佳”热通量。