Second-order adjoint sensitivity analysis methodology (2nd-asam) for large-scale nonlinear systems: I. Theory
It provides a rigorous theoretical framework for second-order sensitivity analysis, which is foundational for uncertainty quantification and optimization in complex nonlinear systems.
This work develops the Second-Order Sensitivity Analysis Methodology (2nd-ASAM) for computing second-order functional derivatives of system responses to model parameters in large-scale nonlinear systems. The methodology is exact and efficient, enabling comprehensive sensitivity analysis.
This work presents the Second-Order Sensitivity Analysis Methodology (2nd-ASAM) for nonlinear systems. This methodology yields exactly and efficiently the second-order functional derivatives of system responses (associated with physical, engineering, biological, etc., systems) to the system's model parameters.