TY  - JOUR
A1  - Molkenthin, Christian
A1  - Scherbaum, Frank
A1  - Griewank, Andreas
A1  - Kühn, Nicolas
A1  - Stafford, Peter J.
A1  - Leovey, Hernan
T1  - Sensitivity of Probabilistic Seismic Hazard Obtained by Algorithmic Differentiation: A Feasibility Study
JF  - Bulletin of the Seismological Society of America
N2  - Probabilistic seismic-hazard analysis (PSHA) is the current tool of the trade used to estimate the future seismic demands at a site of interest. A modern PSHA represents a complex framework that combines different models with numerous inputs. It is important to understand and assess the impact of these inputs on the model output in a quantitative way. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters, and obtaining insight about the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs; however, obtaining the derivatives of complex models can be challenging.
 In this study, we show how differential sensitivity analysis of a complex framework such as PSHA can be carried out using algorithmic/automatic differentiation (AD). AD has already been successfully applied for sensitivity analyses in various domains such as oceanography and aerodynamics. First, we demonstrate the feasibility of the AD methodology by comparing AD-derived sensitivities with analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. Second, we derive sensitivities via AD for a more complex PSHA study using a stochastic simulation approach for the prediction of ground motions. The presented approach is general enough to accommodate more advanced PSHA studies of greater complexity.
Y1  - 2015
U6  - https://doi.org/10.1785/0120140294
SN  - 0037-1106
SN  - 1943-3573
VL  - 105
IS  - 3
SP  - 1810
EP  - 1822
PB  - Seismological Society of America
CY  - Albany
ER  -