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NASA NTRS2017

A Non-Intrusive Algorithm for Sensitivity Analysis of Chaotic Flow Simulations

We demonstrate a novel algorithm for computing the sensitivity of statistics in chaotic flow simulations to parameter perturbations. The algorithm is non-intrusive but requires exposing an interface. Based on the principle of shadowing in dynamical systems, this algorithm is designed to reduce the effect of the sampling error in computing sensitivity of statistics in chaotic simulations. We compare the effectiveness of this method to that of the conventional finite difference method.

Blonigan, Patrick J.↗

DOE OSTI2025

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

• Background noise from ionizing decay poses challenges for MKIDs due to their sensitivity to small energy depositions. • Our group bakes the MKID housing lid in radon to study effects of alphas from daughter isotopes in the decay chain. • The impact of alpha particles on the chip depends on their energy, making their distribution key to characterizing and reducing noise in superconducting quantum devices.

Hall, Matthew [Southern California U.]↗

DOE OSTI2025

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗

DOE OSTI2016

Uncertainty Quantification and Sensitivity Analysis Applications to Fuel Performance Modeling

Best-estimate fuel performance codes such as BISON currently under development at the Idaho National Laboratory, utilize empirical and mechanistic lower-length-scale informed correlations to predict fuel behavior under normal operating and accident reactor conditions. Traditionally, best-estimate results are presented using the correlations with no quantification of the uncertainty in the output metrics of interest. However, there are associated uncertainties in the input parameters and correlations used to determine the behavior of the fuel and cladding under irradiation. Therefore, it is important to perform uncertainty quantification and include confidence bounds on the output metrics that take into account the uncertainties in the inputs. In addition, sensitivity analyses can be performed to determine which input parameters have the greatest influence on the outputs. In this paper we couple the BISON fuel performance code to the DAKOTA uncertainty analysis software to analyze a representative fuel performance problem. The case studied in this paper is based upon rod 1 from the IFA-432 integral experiment performed at the Halden Reactor in Norway. The rodlet is representative of a BWR fuel rod. The input parameters uncertainties are broken into three separate categories including boundary condition uncertainties (e.g., power, coolant flow rate), manufacturing uncertainties (e.g., pellet diameter, cladding thickness), and model uncertainties (e.g., fuel thermal conductivity, fuel swelling). Utilizing DAKOTA, a variety of statistical analysis techniques are applied to quantify the uncertainty and sensitivity of the output metrics of interest. Specifically, we demonstrate the use of sampling methods, polynomial chaos expansions, surrogate models, and variance-based decomposition. The output metrics investigated in this study are the fuel centerline temperature, cladding surface temperature, fission gas released, and fuel rod diameter. The results highlight the importance of quantifying the uncertainty and sensitivity in fuel performance modeling predictions and the need for additional research into improving the material models that are currently available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Uncertainty quantification and sensitivity analysis applications to fuel performance modeling

Best-estimate fuel performance codes such as BISON currently under development at the Idaho National Laboratory, utilize empirical and mechanistic lower-length-scale informed correlations to predict fuel behavior under normal operating and accident reactor conditions. Traditionally, best-estimate results are presented using the correlations with no quantification of the uncertainty in the output metrics of interest. However, there are associated uncertainties in the input parameters and correlations used to determine the behavior of the fuel and cladding under irradiation. Therefore, it is important to perform uncertainty quantification and include confidence bounds on the output metrics that take into account the uncertainties in the inputs. In addition, sensitivity analyses can be performed to determine which input parameters have the greatest influence on the outputs. In this paper we couple the BISON fuel performance code to the DAKOTA uncertainty analysis software to analyze a representative fuel performance problem. The case studied in this paper is based upon rod 1 from the IFA-432 integral experiment performed at the Halden Reactor in Norway. The rodlet is representative of a BWR fuel rod. The input parameters uncertainties are broken into three separate categories including boundary condition uncertainties (e.g., power, coolant flow rate), manufacturing uncertainties (e.g., pellet diameter, cladding thickness), and model uncertainties (e.g., fuel thermal conductivity, fuel swelling). Utilizing DAKOTA, a variety of statistical analysis techniques are applied to quantify the uncertainty and sensitivity of the output metrics of interest. Specifically, we demonstrate the use of sampling methods, polynomial chaos expansions, surrogate models, and variance-based decomposition. The output metrics investigated in this study are the fuel centerline temperature, cladding surface temperature, fission gas released, and fuel rod diameter. The results highlighted the importance of the thermal conductivity of the fuel, the thermal conductivity of the cladding, the gap thickness, the fuel thermal expansion, and the system power factor as influential parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1987

Decoupled direct method for sensitivity analysis in combustion kinetics

An efficient, decoupled direct method for calculating the first order sensitivity coefficients of homogeneous, batch combustion kinetic rate equations is presented. In this method the ordinary differential equations for the sensitivity coefficients are solved separately from , but sequentially with, those describing the combustion chemistry. The ordinary differential equations for the thermochemical variables are solved using an efficient, implicit method (LSODE) that automatically selects the steplength and order for each solution step. The solution procedure for the sensitivity coefficients maintains accuracy and stability by using exactly the same steplengths and numerical approximations. The method computes sensitivity coefficients with respect to any combination of the initial values of the thermochemical variables and the three rate constant parameters for the chemical reactions. The method is illustrated by application to several simple problems and, where possible, comparisons are made with exact solutions and those obtained by other techniques.

Radhakrishnan, Krishnan↗

NASA NTRS1986

A domain method for shape design sensitivity analysis of built-up structures

A numerical method of obtaining accurate shape design sensitivity information for built-up structures is developed and demonstrated through examples. The method utilizes the basic character of the finite element method that gives accurate information not on the boundary, but in the domain. The method is shown to drastically simplify the derivation of shape design sensitivity formulas for complex built-up structures.

Choi, Kyung K.↗

NASA NTRS1988

Shape sensitivity analysis of wing static aeroelastic characteristics

A method is presented to calculate analytically the sensitivity derivatives of wing static aeroelastic characteristics with respect to wing shape parameters. The wing aerodynamic response under fixed total load is predicted with Weissinger's L-method; its structural response is obtained with Giles' equivalent plate method. The characteristics of interest include the spanwise distribution of lift, trim angle of attack, rolling and pitching moments, wind induced drag, as well as the divergence dynamic pressure. The shape parameters considered are the wing area, aspect ratio, taper ratio, sweep angle, and tip twist angle. Results of sensitivity studies indicate that: (1) approximations based on analytical sensitivity derivatives can be used over wide ranges of variations of the shape parameters considered, and (2) the analytical calculation of sensitivity derivatives is significantly less expensive than the conventional finite-difference alternative.

Barthelemy, Jean-Francois M.↗

NASA NTRS1988

Shape sensitivity analysis of wing static aeroelastic characteristics

A method is presented to calculate analytically the sensitivity derivatives of wing static aeroelastic characteristics with respect to wing shape parameters. The wing aerodynamic response under fixed total load is predicted using Weissinger's L-method; its structural response is obtained with Giles' equivalent plate method. The characteristics of interest in this study include the spanwise distribution of lift, trim angle of attack, rolling and pitching moments, wing induced drag as well as the divergence dynamic pressure. The shape parameters considered are the wing area, aspect ratio, taper ratio, sweep angle and tip twist angle. Results of sensitivity studies indicate that (1) approximations based on analytical sensitivity derivatives can be used for wide ranges of variations of the shape parameters considered and (2) the analytical calculation of sensitivity derivatives is significantly less expensive than the conventional finite difference alternative.

Barthelemy, Jean-Francois M.↗

DOE OSTI2022

Log-N/Period Sensitivity Analysis

The Log-N/Period system utilizes a compensated ion chamber to measure neutron radiation in the reactor core. This analysis focuses on determining a more accurate value for the sensitivity of the installed compensated ion chambers for the Log-N/Period system at the ATR. Using calibration procedures a formula for indirectly calculating the sensitivity of the chambers was derived. Using historical data from approximately ten reactor cycles a new average sensitivity for both channels of the Log-N/Period system was determined.

42 ENGINEERING↗

DOE OSTI2024

Sensitivity Analysis of Irradiated Fueled Experiments using the MOOSE Framework [Slides]

Modeling and simulation (M&S) methods are able to predict uncertainties in experimental parameters (e.g., power and fission density) during irradiation. A shortfall exists in predicting how sensitive some of the parameters will behave during the experimental process. Sensitivity and Uncertainty Quantification (SUQ) is critical in support of qualification and licensing reactor fuels. The application of a method to quantify the uncertainty in these experiments is critical to the prediction of their performance. In this work, we propose the use of a polynomial chaos expansion (PCE) method to quantify the sensitive parameters in these simulations and, in an extension, their experimental surrogates. We propose to perform M&S using PCE uncertainty quantification on a previously irradiated fueled experiment in order to provide a validation case for Griffin and expand its use as a verification and validation (V&V) tool for experiments with a neutronics component. Griffin is an advanced, deterministic neutronics analysis code built using the MOOSE (multiphysics object-oriented simulation environment) framework which can provide state-of-the-art neutronic analysis on M&S of experiments. We will use the stochastic tools module (STM) in MOOSE to provide PCE uncertainty quantification on the proposed experimental setup. Idaho National Laboratory (INL) does not yet have an in-house developed code with V&V approval for experiments performed on-site; this work would provide a necessary addition of support for experiments performed at INL. The Nuclear Regulatory Commission (NRC) has explicitly requested uncertainties in calculated values such as fuel power and burnup, and the development of this capability would benefit the relationship between INL and the NRC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1986

Shock-tube pyrolysis of acetylene - Sensitivity analysis of the reaction mechanism for soot formation

The impact of thermodynamic parameters on the sensitivity of model predictions of soot formation by shock-tube pyrolysis of acetylene were assessed analytically. The pyrolysis process was treated as having three components: initiation, the initial pyrolysis stages; cyclization, formation of larger molecules and radicals and small aromatic molecules; and polymerization, further growth of aromatic rings. Rate equations are reviewed for each component. Thermodynamic effects were assessed by varying the C2H-H and C2H3-H bond energies and the Ct-(Ct) group additivity value. Any change in the C2H-H bond energy had a significant impact on the temperature and the maximum amount of the soot yield. The findings underscore the necessity of using accurate thermodynamic data for modeling high-temperature chemical kinetics.

Frenklach, M.↗

NASA NTRS1993

Sensitivity analysis of discrete systems

A selection is presented of methods used in the calculation of sensitivity derivatives of behavior and response of discretely modeled structure. Attention is given to methods for the selection of finite-difference step sizes for structural constraint derivatives, and techniques for finite difference derivatives in iteratively-solved problems. Also noted are methods for sensitivity of linear static response, and methods for second derivatives of structural response, derivatives of stresses, and nonlinear response; an emerging area of interest concerns the derivatives of transient response.

Adelman, Howard M.↗

DOE OSTI2017

Sensitivity analysis for best-estimate thermal models of vertical dry cask storage systems

Loading requirements for dry cask storage of spent nuclear fuel are driven primarily by decay heat capacity limitations, which themselves are determined through recommended limits on peak cladding temperature within the cask. This study examines the relative sensitivity of peak material temperatures within the cask to parameters that influence both the stored fuel residual decay heat as well as heat removal mechanisms. Here, these parameters include the detailed reactor operating history parameters (e.g., soluble boron concentrations and the presence of burnable poisons) as well as factors that influence heat removal, including non-dominant processes (such as conduction from the fuel basket to the canister and radiation within the canister) and ambient environmental conditions. By examining the factors that drive heat removal from the cask alongside well-understood factors that drive decay heat, it is therefore possible to make a contextual analysis of the most important parameters to evaluation of peak material temperatures within the cask.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1985

A sensitivity analysis of central flat-plate photovoltaic systems and implications for national photovoltaics program planning

The sensitivity of the National Photovoltaic Research Program goals to changes in individual photovoltaic system parameters is explored. Using the relationship between lifetime cost and system performance parameters, tests were made to see how overall photovoltaic system energy costs are affected by changes in the goals set for module cost and efficiency, system component costs and efficiencies, operation and maintenance costs, and indirect costs. The results are presented in tables and figures for easy reference.

Crosetti, M. R.↗

NASA NTRS1986

First- and second-order sensitivity analysis of linear and nonlinear structures

This paper employs the principle of virtual work to derive sensitivity derivatives of structural response with respect to stiffness parameters using both direct and adjoint approaches. The computations required are based on additional load conditions characterized by imposed initial strains, body forces, or surface tractions. As such, they are equally applicable to numerical or analytical solution techniques. The relative efficiency of various approaches for calculating first and second derivatives is assessed. It is shown that for the evaluation of second derivatives the most efficient approach is one that makes use of both the first-order sensitivities and adjoint vectors. Two example problems are used for demonstrating the various approaches.

Haftka, R. T.↗

NASA NTRS1979

Performance sensitivity analysis of Department of Energy-Chrysler upgraded automotive gas turbine engine, S/N 5-4

The performance sensitivity of a two-shaft automotive gas turbine engine to changes in component performance and cycle operating parameters was examined. Sensitivities were determined for changes in turbomachinery efficiency, compressor inlet temperature, power turbine discharge temperature, regenerator effectiveness, regenerator pressure drop, and several gas flow and heat leaks. Compressor efficiency was found to have the greatest effect on system performance.

Johnsen, R. L.↗

NASA NTRS1979

Near-term hybrid vehicle program, phase 1. Appendix D: Sensitivity analysis resport

Parametric analyses, using a hybrid vehicle synthesis and economics program (HYVELD) are described investigating the sensitivity of hybrid vehicle cost, fuel usage, utility, and marketability to changes in travel statistics, energy costs, vehicle lifetime and maintenance, owner use patterns, internal combustion engine (ICE) reference vehicle fuel economy, and drive-line component costs and type. The lowest initial cost of the hybrid vehicle would be $1200 to $1500 higher than that of the conventional vehicle. For nominal energy costs ($1.00/gal for gasoline and 4.2 cents/kWh for electricity), the ownership cost of the hybrid vehicle is projected to be 0.5 to 1.0 cents/mi less than the conventional ICE vehicle. To attain this ownership cost differential, the lifetime of the hybrid vehicle must be extended to 12 years and its maintenance cost reduced by 25 percent compared with the conventional vehicle. The ownership cost advantage of the hybrid vehicle increases rapidly as the price of fuel increases from $1 to $2/gal.

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