Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “forward sensitivity analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Periodic Material-Based Seismic Base Isolators for Small Modular Reactors

Important structures such as nuclear power plants should experience very little vibrations in order to maintain the safety of the nuclear facilities during seismic events. Protection of these structures by seismic isolators requires the isolators to provide seismic isolation irrespective of the direction of excitations and to develop a stable response without rocking. Conventional seismic isolation systems, however, can only fulfill partial requirements for the seismic protection. This study adopts the principle of periodic materials for seismic isolation. These materials exhibit unique properties of frequency band gaps, where incoming waves with frequencies falling inside the frequency band gaps are forbidden. The new isolation systems, known as periodic foundations, function both as a structural foundation to support the gravitational weight of the superstructure and also as a seismic isolator. The isolation mechanism, hypothetically, can easily fulfill all the requirements for seismic protection of the critical facilities. This study focuses on the design of one-dimensional (1D) and three-dimensional (3D) periodic foundations for seismic isolation of small modular reactor (SMR) buildings. The theoretical study was first conducted to reveal the fundamental behavior of periodic foundations. Then global sensitivity analysis was utilized to study the effect of design parameters on the frequency band gaps. In addition, simple straight-forward design equations based on the sensitivity analysis are proposed for the design of periodic foundations. Utilizing the proposed equations, prototypes of 1D and 3D periodic foundations were designed to isolate an SMR building. Scaled models were fabricated and experimentally tested to validate the hypothesis and design. The periodic foundation structural systems were tested under various input waves, including seismic waves, in the horizontal and vertical directions and the torsional mode. The shake table test results show that the periodic foundations can reduce the acceleration response of the SMR building up to 90% in the horizontal direction and the torsional mode. As much as a 40% response reduction in the vertical direction is also observed. Moreover, the periodic foundation-isolated structure exhibited stable response with negligible rocking on the structure. This study proved the capability of periodic foundations to enhance the seismic safety of critical structures.

42 ENGINEERING↗
NASA NTRS1990

Aeroelastic optimization of a helicopter rotor using an efficient sensitivity analysis

To reduce oscillatory hub loads in forward flight, a structural optimization analysis of a hingeless helicopter rotor has been developed and applied. The aeroelastic analysis of the rotor is based on a finite element method in space and time, and linked with automated optimization algorithms. For the optimization analysis two types of structural representation are used: a generic stiffness-distribution and a single-cell thin-walled beam. For the first type, the design variables are nonstructural mass and its placement, chordwise center of gravity offset from the elastic axis, and stiffness. For the second type, width, height and thickness of spar are used as design variables. For the behavior constraints, frequency placement, autorotational inertia and aeroelastic stability of the blade are included. The required sensitivity derivatives are obtained using a direct analytical approach. An optimum oscillatory hub load shows a 25-77 percent reduction for the generic blade, and 30-50 percent reduction for the box-beam.

Lim, Joon W.↗
DOE OSTI2024

ReactionMechanismSimulator.jl: A modern approach to chemical kinetic mechanism simulation and analysis

Abstract We present ReactionMechanismSimulator.jl (RMS), a modern differentiable software for the simulation and analysis of chemical kinetic mechanisms, including multiphase systems. RMS has already been applied to problems in combustion, pyrolysis, polymers, pharmaceuticals, catalysis, and electrocatalysis. RMS is written in Julia, making it easy to develop and allowing it to take advantage of Julia's extensive numerical computing ecosystem. In addition to its extensive library of optimized analytic Jacobians, RMS can generate and use Jacobians computed using automatic differentiation and symbolically generated analytic Jacobians. RMS is demonstrated to be faster than Cantera and Chemkin in several benchmarks. RMS also implements an extensive set of features for analyzing chemical mechanisms, including a library of easy‐to‐call plotting functions, molecular structure resolved flux diagram generation, crash analysis, traditional sensitivity analysis, transitory sensitivity analysis, and an automatic mechanism analysis toolkit. RMS implements efficient adjoint and parallel forward sensitivity analyses. We also demonstrate the ease of adding new features to RMS.

Johnson, Matthew S.↗
DOE OSTI2017

CO2 Push-Pull Dual (Conjugate) Faults Injection Simulations

This submission contains datasets and a final manuscript associated with a project simulating carbon dioxide push-pull into a conjugate fault system modeled after Dixie Valley- sensitivity analysis of significant parameters and uncertainty prediction by data-worth analysis. Datasets include: (1) Forward simulation runs of standard cases (push & pull phases), (2) Local sensitivity analyses (push & pull phases), and (3) Data-worth analysis (push & pull phases).

15 GEOTHERMAL ENERGY↗
DOE OSTI2011

Dark Photon Search at BABAR

Presented is the current progress of a search for the signature of a dark photon or new particle using the BaBar data set. We search for the processes e + e - → γ ISR A', A' → e + e - and e + e - → γ ISR γ,γ → A', A' → e + e - , where γ ISR is an initial state radiated photon of energy E γ >= 1 GeV. Twenty-five sets of Monte Carlo, simulating e + e - collisions at an energy of 10.58 GeV, were produced with different values of the A' mass ranging from 100 MeV to 9.5 GeV. The mass resolution is calculated based on Monte Carlo simulations. We implement ROOT's Toolkit for Multivariate Analysis (TMVA), a machine learning tool that allows us to evaluate the signal character of events based on many of discriminating variables. TMVA training is conducted with samples of Monte Carlo as signal and a small portion of Run 6 as background. The multivariate analysis produces additional cuts to separate signal and background. The signal efficiency and sensitivity are calculated. The analysis will move forward to fit the background and scan the residuals for the narrow resonance peak of a new particle.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling

PyApprox is a Python-based one-stop-shop for probabilistic analysis of numerical models such as those used in the earth, environmental and engineering sciences. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent a wide range of methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of new or existing algorithms for a wide range of model analyses. Here, this paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

PyApprox: Enabling efficient model analysis

PyApprox is a Python-based one-stop-shop for probabilistic analysis of scientific numerical models. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent the most popular methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. Simple interfaces are provided for the most commonly-used algorithms to limit a user’s need to tune the various hyper-parameters of each algorithm. However, more advanced work flows that require customization of hyper-parameters is also supported. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of different algorithms for a wide range of model analyses. This paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in ground water.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Final Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

QUEST (\url{www.quest-scidac.org}) is a SciDAC Institute that is focused on uncertainty quantification (UQ) in large-scale scientific computations. Our goals are to (1) advance the state of the art in UQ mathematics, algorithms, and software; and (2) provide modeling, algorithmic, and general UQ expertise, together with software tools, to other SciDAC projects, thereby enabling and guiding a broad range of UQ activities in their respective contexts. QUEST is a collaboration among six institutions (Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University) with a history of joint UQ research. Our vision encompasses all aspects of UQ in leadership-class computing. This includes the well-founded setup of UQ problems; characterization of the input space given available data/information; local and global sensitivity analysis; adaptive dimensionality and order reduction; forward and inverse propagation of uncertainty; handling of application code failures, missing data, and hardware/software fault tolerance; and model inadequacy, comparison, validation, selection, and averaging. The nature of the UQ problem requires the seamless combination of data, models, and information across this landscape in a manner that provides a self-consistent quantification of requisite uncertainties in predictions from computational models. Accordingly, our UQ methods and tools span an interdisciplinary space across applied math, information theory, and statistics. The MIT QUEST effort centers on statistical inference and methods for surrogate or reduced-order modeling. MIT personnel have been responsible for the development of adaptive sampling methods, methods for approximating computationally intensive models, and software for both forward uncertainty propagation and statistical inverse problems. A key software product of the MIT QUEST effort is the MIT Uncertainty Quantification library, called MUQ (\url{muq.mit.edu}).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Investigating uncertainties in human adaptation and their impacts on water scarcity in the Colorado river Basin, United States

The Colorado River Basin (CRB) supports the water supply for seven states and forty million people in the Western United States (US) and has been suffering an extensive drought for more than two decades. As climate change continues to reshape water resources distribution in the CRB, its impact can differ in intensity and location, resulting in variations in human adaptation behaviors. The feedback from human systems in response to the environmental changes and the associated uncertainty is critical to water resources management, especially for water-stressed basins. This paper investigates how human adaptation affects water scarcity uncertainty in the CRB and highlights the uncertainties in human behavior modeling. Our focus is on agricultural water consumption, as approximately 80% of the water consumption in the CRB is used in agriculture. We adopted a coupled agent-based and water resources modeling approach for exploring human-water system dynamics, in which an agent is a human behavior model that simulates a farmer’s water consumption decisions. We examined uncertainties at the system, agent, and parameter levels through uncertainty, clustering, and sensitivity analyses. The uncertainty analysis results suggest that the CRB water system may experience 13 to 30 years of water shortage during the 2019–2060 simulation period, depending on the paths of farmers’ adaptation. The clustering analysis identified three decision-making classes: bold, prudent, and forward-looking, and quantified the probabilities of an agent belonging to each class. The sensitivity analysis results indicated agents whose decision-making models require further investigation and the parameters with the higher uncertainty reduction potentials. Here, by conducting numerical experiments with the coupled model, this paper presents quantitative and qualitative information about farmers’ adaptation, water scarcity uncertainties, and future research directions for improving human behavior modeling.

Agent-based modeling↗
DOE OSTI2022

Toward reducing uncertainty quantification costs in DEM models of particulate flow: Testing simple, sensitivity-based, forward uncertainty propagation techniques

The performance of two conceptually-simple uncertainty quantification techniques are tested against the rigorous nested-loop sampling technique of Roy and Oberkampf (Comput Methods Appl Mech Eng, 200: 2131–2144, 2011) (herein called full-sampling) using two very small-scale DEM-based models of particulate flow (one gas-solid flow and one granular flow). The first simplified forward uncertainty propagation technique, reduced-sampling, uses a sensitivity analysis to eliminate uncertain inputs that have little impact on the model output prior to nested-loop sampling. The second technique, boundary-sampling, uses a sensitivity analysis to inform the selection of two bounding cases for each key model output. In conclusion, the uncertainties in the model outputs obtained via the reduced- and boundary-sampling methods agree well with those from full-sampling for both the gas-solid and granular flow models while yielding computational savings of 65–75% (reduced sampling) and 94–97% (boundary sampling).

42 ENGINEERING↗
NASA NTRS1988

Stability sensitivity analysis for the aeroelastic optimization of a helicopter rotor

A sensitivity study of blade stability in forward flight for a hingeless rotor with respect to structural design variables is carried out using a direct analytical method. Structural design variables include nonstructural mass distribution (spanwise and chordwise), chordwise offset of center of gravity, and blade bending stiffnesses (flap, lag and torsion). The formulation for blade steady response is based on a finite element method in space and time. The vehicle trim and blade steady response are calculated iteratively as one coupled solution using a modified Newton method. Eigenvalues corresponding to different blade modes are calculated using Floquet transition matrix theory. The formulation for derivatives of the eigenvalues with respect to design variables is implemented using a direct analytical approach (chain rule differentiation), and constitutes an integral part of the regular stability analysis. The stability sensitivity derivatives were obtained at a fraction of computation time compared to the frequently adopted finite difference method. A parametric study showed that nonstructural mass and chordwise cg offset of outboarad elements, and lag bending stiffness of inboard elements, have powerful influence on blade stability.

Lim, Joon W.↗
NASA NTRS1981

Supersonic stall flutter of high-speed fans

An analytical model is proposed for predicting the onset of supersonic stall bending flutter in high-speed rotors. The analysis is based on a modified two-dimensional, compressible, unsteady actuator disk theory. The stability boundary predicted by the analysis is shown to be in good agreement with the measured boundary of a high speed fan. The prediction that the flutter mode would be a forward traveling wave sensitive to wheel speed and aerodynamic loading is confirmed by experimental measurements. In addition, the analysis shows that reduced frequency and dynamic head also play a significant role in establishing the supersonic stall bending flutter boundary of an unshrouded fan.

Adamczyk, J. J.↗
DOE OSTI2020

Biological Valorization of Natural Gas for the Production of Lactic Acid: Techno-Economic Analysis and Life Cycle Assessment

Due to the availability of natural gas, shale gas, and flared gas, there is increased interest in converting methane in these gases into commodity chemicals via cost-effective and sustainable processes. Recently, we have demonstrated an efficient process concept converting methane to lactic acid (LA) by methanotrophic bacteria with high carbon flux, pivoting potentials for commercialization. Herein, we present a first-of-kind conceptual design and a techno-economic analysis (TEA) of a biorefinery process with calculated minimum selling prices. This study includes both sensitivity analysis and scenario analysis for key cost drivers and for projecting path forwards in research and development. The analyses reveal that the conversion efficiency, LA product titer, LA productivity, and gas flow rate have the most significant impacts on cost. The MSP varies from $5.83-$2.17/kg LA depending on these key process attributes. Further, a life cycle assessment of this process concept is evaluated and compared to understand the sustainable aspects. In this TEA study, the bio-upgrading process from natural gas to LA presents a potentially promising approach in terms of the feedstock versatility, economic viability, and environmental impact.

BIOMASS FUELS,NATURAL GAS↗
NASA NTRS1989

Design sensitivity analysis of boundary element substructures

The ability to reduce or condense a three-dimensional model exactly, and then iterate on this reduced size model representing the parts of the design that are allowed to change in an optimization loop is discussed. The discussion presents the results obtained from an ongoing research effort to exploit the concept of substructuring within the structural shape optimization context using a Boundary Element Analysis (BEA) formulation. The first part contains a formulation for the exact condensation of portions of the overall boundary element model designated as substructures. The use of reduced boundary element models in shape optimization requires that structural sensitivity analysis can be performed. A reduced sensitivity analysis formulation is then presented that allows for the calculation of structural response sensitivities of both the substructured (reduced) and unsubstructured parts of the model. It is shown that this approach produces significant computational economy in the design sensitivity analysis and reanalysis process by facilitating the block triangular factorization and forward reduction and backward substitution of smaller matrices. The implementatior of this formulation is discussed and timings and accuracies of representative test cases presented.

Kane, James H.↗
NASA NTRS1988

Active control of helicopter air resonance in hover and forward flight

A coupled rotor/fuselage helicopter analysis is presented. The accuracy of the model is illustrated by comparing it with experimental data. The sensitivity of the open loop damping of the unstable resonance mode to such modeling effects as blade torsional flexibility, unsteady aerodynamics, forward flight, periodic terms, and trim solution is illustrated by numerous examples. Subsequently, the model is used in conjunction with linear optimal control theory to stabilize the air resonance mode. The influence of the modeling effects mentioned before on active resonance control is then investigated.

Takahashi, M. D.↗
DOE OSTI2014

A setup for simultaneous measurement of infrared spectra and light scattering signals: Watching amyloid fibrils grow from intact proteins

A setup for the simultaneous measurement of mid-infrared spectra and static light scattering is described that can be used for the analysis of the formation of nanoscale and microscopic aggregates from smaller molecules to biopolymers. It can be easily integrated into sample chambers of infrared spectrometers or combined with laser beams from tunable infrared lasers. Here, its use for the analysis of the formation of amyloid fibrils from intact proteins is demonstrated. The formation of amyloid fibrils or plaques from proteins is a widespread and pathogenetic relevant process, and a number of diseases are caused and correlated with the deposition of amyloid fibrils in cells and tissues. The molecular mechanisms of these transformations, however, are still unclear. We report here the simultaneous measurement of infrared spectra and static light scattering for the analysis of fibril formation from egg-white lysozyme. The transformation of the native form into non-native forms rich in β-sheet structure is measured by analysis of the amide I spectral region in the infrared spectra, which is sensitive for local structures. At the same time, light scattering signals at forward direction as well as the forward/backward ratio, which are sensitive for the number of scattering centers and their approximate sizes, respectively, are collected for the analysis of fibril growth. Thermodynamic and kinetic parameters as well as mechanistic information are deduced from the combination of the two complementary techniques.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Iterative methods for design sensitivity analysis

A numerical method is presented for design sensitivity analysis, using an iterative-method reanalysis of the structure generated by a small perturbation in the design variable; a forward-difference scheme is then employed to obtain the approximate sensitivity. Algorithms are developed for displacement and stress sensitivity, as well as for eignevalues and eigenvector sensitivity, and the iterative schemes are modified so that the coefficient matrices are constant and therefore decomposed only once.

Belegundu, A. D.↗