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A tandem trust-region optimization approach for ill-posed falling weight deflectometer backcalculation
Computers & Structures ( IF 4.4 ) Pub Date : 2022-11-18 , DOI: 10.1016/j.compstruc.2022.106935
Ryan C. Romeo , R. Benjamin Davis , Hyung S. Lee , Stephan A. Durham , S. Sonny Kim

Falling weight deflectometer backcalculation is a structural health monitoring approach for estimating the dynamic modulus of flexible pavements. It consists of two key aspects: a computational pavement model and an optimization routine. When using gradient-based methods, the optimization problem is commonly ill-posed, whereby a unique solution does not necessarily exist. In this paper, a new tandem trust-region optimization algorithm is proposed for ill-posed falling weight deflectometer backcalculation. The algorithm’s performance is tested against existing optimization methods in the context of dynamic modulus estimation for flexible pavements, and the performance tests are simulated computationally using practical values for material properties and geometry. The tandem trust-region algorithm combines the relative strengths of the subspace trust-region interior reflective method with those of the Levenberg–Marquardt algorithm. The increased computational expense of executing these two methods in parallel is negligible compared to the expense of other essential steps in backcalculation. For ill-posed problems, the performance tests indicate the tandem trust region algorithm has an overall reliability that is 33.9% higher than using only the subspace trust-region interior reflective method, and 56.9% higher than using only the Levenberg–Marquardt algorithm. Further, the new optimizer is 13.5% more reliable than a robust commercial option.



中文翻译:

一种用于不适定落锤挠度计反算的串联信赖域优化方法

落锤弯沉反算法是一种结构健康监测方法,用于估算柔性路面的动态模量。它由两个关键方面组成:计算路面模型和优化程序。当使用基于梯度的方法时,优化问题通常是病态的,因此不一定存在唯一解。在本文中,提出了一种新的串联信赖域优化算法,用于不适定的落锤挠度计反算。在柔性路面的动态模量估计的背景下,针对现有优化方法测试了该算法的性能,并使用材料特性和几何形状的实际值对性能测试进行了计算模拟。串联信赖域算法结合了子空间信赖域内部反射方法与 Levenberg–Marquardt 算法的相对优势。与回算中其他基本步骤的开销相比,并行执行这两种方法所增加的计算开销可以忽略不计。对于病态问题,性能测试表明串联信赖域算法的整体可靠性比仅使用子空间信赖域内部反射方法高 33.9%,比仅使用 Levenberg-Marquardt 算法高 56.9%。此外,新的优化器比强大的商业选项可靠 13.5%。与回算中其他基本步骤的开销相比,并行执行这两种方法所增加的计算开销可以忽略不计。对于病态问题,性能测试表明串联信赖域算法的整体可靠性比仅使用子空间信赖域内部反射方法高 33.9%,比仅使用 Levenberg-Marquardt 算法高 56.9%。此外,新的优化器比强大的商业选项可靠 13.5%。与回算中其他基本步骤的开销相比,并行执行这两种方法所增加的计算开销可以忽略不计。对于病态问题,性能测试表明串联信赖域算法的整体可靠性比仅使用子空间信赖域内部反射方法高 33.9%,比仅使用 Levenberg-Marquardt 算法高 56.9%。此外,新的优化器比强大的商业选项可靠 13.5%。比仅使用 Levenberg–Marquardt 算法高 9%。此外,新的优化器比强大的商业选项可靠 13.5%。比仅使用 Levenberg–Marquardt 算法高 9%。此外,新的优化器比强大的商业选项可靠 13.5%。

更新日期:2022-11-18
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