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At least 253 records · Page 14

Results of an integrated structure-control law design sensitivity analysis

Next generation air and space vehicle designs are driven by increased performance requirements, demanding a high level of design integration between traditionally separate design disciplines. Interdisciplinary analysis capabilities have been developed, for aeroservoelastic aircraft and large flexible spacecraft control for instance, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changess in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient that finite difference methods for the computation of the equivalent sensitivity information.

Gilbert, Michael G.↗

Sensitivity analysis of add-on price estimate for select silicon wafering technologies

The cost of producing wafers from silicon ingots is a major component of the add-on price of silicon sheet. Economic analyses of the add-on price estimates and their sensitivity internal-diameter (ID) sawing, multiblade slurry (MBS) sawing and fixed-abrasive slicing technique (FAST) are presented. Interim price estimation guidelines (IPEG) are used for estimating a process add-on price. Sensitivity analysis of price is performed with respect to cost parameters such as equipment, space, direct labor, materials (blade life) and utilities, and the production parameters such as slicing rate, slices per centimeter and process yield, using a computer program specifically developed to do sensitivity analysis with IPEG. The results aid in identifying the important cost parameters and assist in deciding the direction of technology development efforts.

Mokashi, A. R.↗

High-Fidelity Multidisciplinary Sensitivity Analysis Framework for Multipoint Rotorcraft Optimization

A multidisciplinary, gradient-based sensitivity-analysis methodology is evaluated for optimization of rotorcraft configurations. The tightly coupled discipline models include physics-based fluid dynamics and rotorcraft comprehensive analysis. A discretely-consistent adjoint method accounts for sensitivities of the unsteady flow and unstructured, dynamic, over set grids, while sensitivities of structural responses to aerodynamic loads are computed using a complex-variable method. The methodology is applied to optimize the shape of UH-60A Blackhawk helicopter blades for hover and forward flight conditions. The objective of the multipoint design is to simultaneously increase the rotorcraft figure of merit in a hover flight and reduce the rotor power in a forward flight. Trimmed loose-coupling solutions for the baseline configuration are used to initiate the tight-coupling multidisciplinary analysis. Target thrust and rolling and pitching moments are enforced as optimization constraints. The optimized configuration improves the optimization metrics at both design points. The improved performance and all constraints are maintained over many revolutions beyond the optimization interval, satisfying the required flight conditions. Computational cost of the optimization cycle is assessed in a high-performance computing environment and found affordable for design of rotorcraft in general level-flight conditions.

Wang, Li↗

Critical Parameter Identification of Fuel-Cell Models Using Sensitivity Analysis

Numerical modeling has been a vital tool in proton-exchange-membrane fuel-cell (PEMFC) analysis; however, the predictive capabilities of these models depend on the input physical parameters, several of which are either not experimentally measured or have large scatter in measured values. This article presents an uncertainty propagation-based sensitivity analysis to identify the model parameters that impact the model predictions most. A comprehensive 2-D membrane electrode assembly (MEA) model is used to perform local sensitivity analysis at multiple operating conditions, which encompass the range of environments and operating conditions a cell can encounter. While at lower humidities, cathode kinetics and membrane-ohmic-loss related parameters are crucial, gas transport and porous-media saturation behavior are more important at humidified conditions. Several of these findings are different from previous studies presented in literature. Identifying the crucial parameters helps focus future material and cell optimization studies as well as experimental studies to quantify these parameters with higher accuracy.

25 ENERGY STORAGE↗

Adjoint design sensitivity analysis of reduced atomic systems using generalized Langevin equation for lattice structures

An efficient adjoint design sensitivity analysis method is developed for reduced atomic systems. A reduced atomic system and the adjoint system are constructed in a locally confined region, utilizing generalized Langevin equation (GLE) for periodic lattice structures. Due to the translational symmetry of lattice structures, the size of time history kernel function that accounts for the boundary effects of the reduced atomic systems could be reduced to a single atom’s degrees of freedom. For the problems of highly nonlinear design variables, the finite difference method is impractical for its inefficiency and inaccuracy. However, the adjoint method is very efficient regardless of the number of design variables since one additional time integration is required for the adjoint GLE. Through numerical examples, the derived adjoint sensitivity turns out to be accurate and efficient through the comparison with finite difference sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Uncertainty and sensitivity analysis for photovoltaic system modeling.

We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.

14 SOLAR ENERGY↗

A sensitivity analysis of volcanic aerosol dispersion in the stratosphere

A computer sensitivity analysis was performed to determine the uncertainties involved in the calculation of volcanic aerosol dispersion in the stratosphere using a 2 dimensional model. The Fuego volcanic event of 1974 was used. Aerosol dispersion processes that were included are: transport, sedimentation, gas phase sulfur chemistry, and aerosol growth. Calculated uncertainties are established from variations in the stratospheric aerosol layer decay times at 37 latitude for each dispersion process. Model profiles are also compared with lidar measurements. Results of the computer study are quite sensitive (factor of 2) to the assumed volcanic aerosol source function and the large variations in the parameterized transport between 15 and 20 km at subtropical latitudes. Sedimentation effects are uncertain by up to a factor of 1.5 because of the lack of aerosol size distribution data. The aerosol chemistry and growth, assuming that the stated mechanisms are correct, are essentially complete in several months after the eruption and cannot explain the differences between measured and modeled results.

Butler, C. F.↗

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42 x compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines.

Biochemistry & Molecular Biology↗

Leaf-scale carbon assimilation simulated by the multi-assumption architecture & testbed for process sensitivity analysis

Raw and processed output from the Multi-Assumption Architecture & Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_walker2020; Walker et al., 2018). The dataset contains leaf-scale carbon assimilation data from three MAAT simulations and their post-processing and plotting scripts. Simulation 1, labelled "FvC_4proc_proc," is a four-process, process sensitivity analysis (Dai et al., 2017) of carbon assimilation based on the Farquhar et al. (1980) photosynthesis model, and its variant proposed by Collatz et al. (1991). Simulation 2, labelled "FvC_4proc_salt," is a 14 parameter sensitivity analysis (Saltelli et al., 2010) of carbon assimilation based on the Farquhar and Collatz photosynthesis models. Simulation 3, labelled "FvC," is a factorial combination of the alternative process representations and parameter values presented in those original papers across a factorial combination of incident photosynthetically active radiation (50-2000 µmol m-2 s-1, in increments of 50) and atmospheric CO2 concentration (50-1500 µmol m-2 s-1, in increments of 50). Additional scripts/functions for post-processing and plotting are part of the MAAT repository. These data were generated to evaluate and compare the Farquhar and Collatz models of leaf-scale photosynthesis across a range of CO2 and incident light conditions. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures; .RDS files, a binary format specific to R and read with the 'readRDS' function, to store raw MAAT output; R and bash scripts (.bs) that help to run a MAAT simulation, .XML files that are output from MAAT describing a run, and .csv files which contain the calculated sensitivity indexes published in Walker et al. (2020).

54 ENVIRONMENTAL SCIENCES↗

Design of 3-D Nacelle near Flat-Plate Wing Using Multiblock Sensitivity Analysis (ADOS)

One of the major design tasks involved in reducing aircraft drag is the integration of the engine nacelles and airframe. With this impetus, nacelle shapes with and without the presence of a flat-plate wing nearby were optimized. This also served as a demonstration of the 3-D version of the recently developed aerodynamic design optimization methodology using sensitivity analysis, ADOS. The required flow analyses were obtained by solving the three-dimensional, compressible, thin-layer Navier-Stokes equations using an implicit, upwind-biased, finite volume scheme. The sensitivity analyses were performed using the preconditioned version of the SADD scheme (sensitivity analysis on domain decomposition). In addition to demonstrating the present method's capability for automatic optimization, the results offered some insight into two important issues related to optimizing the shapes of multicomponent configurations in close proximity. First, inclusion of the mutual interference between the components resulted in a different shape as opposed to shaping an isolated component. Secondly, exclusion of the viscous effects compromised not only the flow physics but also the optimized shapes even for isolated components.

Eleshaky, Mohamed E.↗

Sensitivity analysis of aeroelastic response of a wing using piecewise pressure representation

A sensitivity analysis scheme of the static aeroelastic response of a wing is developed, by incorporating a piecewise panel-based pressure representation into an existing wing aeroelastic model to improve the model's fidelity, including the sensitivity of the wing static aeroelastic response with respect to various shape parameters. The new formulation is quite general and accepts any aerodynamics and structural analysis capability. A program is developed which combines the local sensitivities, such as the sensitivity of the stiffness matrix or the aerodynamic kernel matrix, into global sensitivity derivatives.

Eldred, Lloyd B.↗

Sensitivity Analysis of OECD ATLAS A5.1 Test using MARS-KS code

The ATLAS was designed to model a reduced-height primary system of a typical APR1400 which was developed by the Korean Nuclear Industry. The ATLAS has the 1/2-height, 1/144-area and 1/288-volume scales for the APR 1400 and it is scaled for full pressure and temperature conditions. A benchmark test, test A5.1, was performed to analyze and quantify the extent of scaling distortion in the ATLAS, as a part of a OECD-ATLAS project. The SB-CL-32 test which was conducted using the Large Scale Test Facility (LSTF) of the Rig-of-Safety Assessment-V (ROSA-V) Program was selected as the counterpart test to address the scaling issue. The detailed description of the LSTF test facility and the SB-CL-32 test can be found in the literature. The objective of the A5.1 test is to investigate the thermal hydraulic phenomena during cold leg small break LOCA with steam generator secondary side depressurization as the Accident Management action. In addition to that, the scaling effect analysis of ATLAS was performed in the several viewpoints. In this study, sensitivity analysis of A5.1 test was performed using MARS-KS code. Several experimental conditions of A5.1 test were varied to study effects on the reactor coolant system during the SBLOCA transient. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SOFE2023 Presentation: "Tritium Safety and Sensitivity Analysis of Tritium Extraction eXperiment (TEX) PbLi Loop Using MELCOR-TMAP"

The efficient extraction of tritium from the breeder blanket (BB) in a fusion reactor is vital for maintaining the tritium economy for a sustainable and self-sufficient fusion power plant. The vacuum permeator (VP) design is one of several promising technology platforms for extracting tritium from the BB with the advantages of being capable of operating continuously at high temperatures with the aim of achieving high tritium extraction efficiencies. The Tritium Extraction eXperiment (TEX), under construction at the Safety and Tritium Applied Research (STAR) Facility at Idaho National Laboratory (INL), is designed to test the viability of VP technology by introducing atomic hydrogen (H, D, and T) from a source permeator (SP) into a forced convection lead lithium eutectic (PbLi) loop and determining the hydrogen extraction rates from the vanadium VP. Presented here is a computational analysis of the hydrogen inventory and permeation behavior in TEX using the hydrogen transport and accident analysis code MELCOR-TMAP developed at INL. The results of a sensitivity analysis based on MELCOR-TMAP simulations of hydrogen extraction efficiencies from the TEX test section using varying PbLi flow rates, hydrogen source rates from the SP, and material property uncertainties are also reported. Operation scenarios for TEX in consideration of the analyses based on results from MELCOR-TMAP are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Extension of SCALE/Sampler’s sensitivity analysis

Nuclear data are a major source of uncertainties in reactor physics calculations. The propagation of nuclear data uncertainties to important system responses is instrumental when determining appropriate safety margins in reactor safety analyses. It is also important to understand the major contributors to the observed uncertainties to make recommendations for further measurements and evaluations and aid in the understanding of the studied system. The SCALE code system allows for nuclear data uncertainty analysis based on the random sampling approach as implemented in SCALE’s Sampler sequence. Sampler was recently extended by a sensitivity analysis in terms of the calculation of two correlation-based sensitivity indices. This analysis allows for the identification of the top contributing nuclear reactions to any analyzed output uncertainty. This paper presents the sensitivity indices, along with their interpretation and limitations. It demonstrates the application in an eigenvalue and decay heat analysis for a boiling water reactor fuel assembly.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Sensitivity Analysis of Launch Vehicle Debris Risk Model

As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.

Gee, Ken↗

Geostationary Coastal and Air Pollution Events (GEO-CAPE) Sensitivity Analysis Experiment

Geostationary Coastal and Air pollution Events (GEO-CAPE) is a NASA decadal survey mission to be designed to provide surface reflectance at high spectral, spatial, and temporal resolutions from a geostationary orbit necessary for studying regional-scale air quality issues and their impact on global atmospheric composition processes. GEO-CAPE's Atmospheric Science Questions explore the influence of both gases and particles on air quality, atmospheric composition, and climate. The objective of the GEO-CAPE Observing System Simulation Experiment (OSSE) is to analyze the sensitivity of ozone to the global and regional NOx emissions and improve the science impact of GEO-CAPE with respect to the global air quality. The GEO-CAPE OSSE team at Jet propulsion Laboratory has developed a comprehensive OSSE framework that can perform adjoint-sensitivity analysis for a wide range of observation scenarios and measurement qualities. This report discusses the OSSE framework and presents the sensitivity analysis results obtained from the GEO-CAPE OSSE framework for seven observation scenarios and three instrument systems.

Lee, Meemong↗