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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Sensitivity of optimum solutions to problem parameters

Derivation of the sensitivity equations that yield the sensitivity derivatives directly, which avoids the costly and inaccurate perturb-and-reoptimize approach, is discussed and solvability of the equations is examined. The equations apply to optimum solutions obtained by direct search methods as well as those generated by procedures of the sequential unconstrained minimization technique class. Applications are discussed for the use of the sensitivity derivatives in extrapolation of the optimal objective function and design variable values for incremented parameters, optimization with multiple objectives, and decomposition of large optimization problems.

Sobieszczanski-Sobieski, J.↗
NASA NTRS1978

On-line parameter estimation using a high sensitivity estimator

An on-line parameter identification method is presented. The method is based on a recursive formulation of the maximum likelihood method, with a significant modification on the gains of the state estimator. In the conventional maximum likelihood method, the Kalman gains are used in the state estimator. This produces unbiased, minimum variance parameter estimates in the presence of process noise and measurement noise, but it also slows the convergence rate when the identification is done on-line. Here we suggest choosing the gains to maximize a measure of the sensitivities of the state estimates to parameter variations. One such criterion is to minimize the trace of the inverse information matrix. This increases the convergence rate significantly. After one or two time constants, the gains are switched to the Kalman values to assure unbiased, minimum-variance estimates. The state estimate will initially be nonoptimal, and may not be adequate for control purposes. In this case, a parallel Kalman filter which uses the identifier's parameter estimates can be used. This method is applied here for the identification of a simple first-order system, and for the identification of short-period stability derivatives of an F-8 aircraft from simulated data.

Mishne, D.↗
NASA NTRS1994

The sensitivity to parametric variation in direct minimization techniques

Solutions of some objective analysis techniques are known to depend upon the subjective values of internal parameters. The change in the solution per change in the parameter is the sensitivity. Parameters with low sensitivity can be varied with large increments during preliminary searches for near-optimal parameter values. Only terms with high sensitivity must be thoroughly investigated once the parameters are determined to be close to optimal. Both absolute and relative sensitivities are discussed and a sensitivity-based definition of the solution uncertainty is proposed. The sensitivity of direct minimization analysis to parametric variation is evaluated using a set of 'response functions' that characterize different aspects of the solution. It is shown that solutions of direct minimization techniques have low absolute sensitivity. Two examples are used to illustrate the usefulness of the technique. Both involved measurements of air-sea quantities (e.g., wind stress and latent heat flux) from a variety of data sources using a direct minimization technique. The examples demonstrate that sensitivity analysis is capable of quantifying regional sensitivities as well as indicating the magnitude and relationship between the various parameters.

Meyers, S. D.↗
NASA NTRSDate not supplied

Parameter, Post-Processing Sensitivities, and Qualification Approach of Laser Powder Bed Fusion Hydrogen Resistant Alloy NASA HR-1

Metal additive manufacturing (AM) processes are being used to enable economical manufacturing of legacy alloys as well as advancing new alloys. Laser powder bed fusion (L-PBF) is a metal AM process that has high maturity and being used to produce a variety of parts for space applications including complex propulsion components. The National Aeronautics and Space Administration (NASA) has identified the need to develop and advance new materials in unique space applications such as high-pressure hydrogen environments. NASA HR-1 is a high strength Fe-Ni based superalloy designed to resist high pressure hydrogen environment embrittlement (HEE), oxidation, and corrosion that has been successfully adapted to laser powder directed energy deposition (LP-DED). Insights gained from the NASA HR-1 development for LP-DED have guided the development process for L-PBF. However, adapting NASA HR-1 to L-PBF posed new challenges due to the distinct differences between the additive manufacturing processes. During parameter development, sensitivities were observed in post-processing that necessitated additional optimization of heat treatments. Additionally, the variations in thickness and how it influenced the microstructural response during heat treatment was characterized. Understanding these sensitivities is important to qualification of the material in a L-PBF machine. This ensures that the microstructures and properties of the material maintain consistency in production. This presentation will cover parameter development along with post-processing challenges and solutions will be discussed in addition to key material properties as it pertains to application performance and qualification per NASA-STD-6030. Improvements made by developing a derivative alloy, NASA HR-2, will be highlighted through preliminary small scale parameter development, material characterization, and initial property testing.

NASA HR-1↗
NASA NTRS1971

A parametric study of motor starting for a 2- to 10-kilowatt Brayton power system

A study of the motor starting of a Brayton cycle power system was conducted to provide estimates of system sensitivity to several controllable parameters. These sensitivity estimates were used as a basis for selection of an optimum motor-start scheme to be implemented on the 2- to 10-kilowatt Brayton power system designed and presently under test. The studies were conducted with an analog simulation of the Brayton power system and covered a range of frequencies from 400 Hz (33 percent design) to 1200 Hz (design), voltage-to-frequency ratios of 0.050 (50 percent design) to 0.100 (design), turbine-inlet temperatures of 800 K (1440 R, 70 percent design) to 1140 K (2060 deg R, design), and prestart pressure levels of 14.5 psia to 29.0 psia. These studies have shown the effect of selected system variables on motor starting. The final selection of motor-start variables can therefore be made on the basis of motor-start inverter complexity, battery size and weight, desired steady-state pressure level after startup, and other operational limitations. In general, the study showed the time required for motor starting to be inversely proportional to motor frequency, voltage, turbine-inlet temperature, and pressure level. An increase in any of these parameters decreases startup time.

Cantoni, D. A.↗
NASA NTRS1993

The sensitivity of identified modal parameters to sensor placement errors and construction tolerances

This paper examines the sensitivity of experimentally measured modal frequencies and mode shapes to structural reassembly and sensor placement errors on a suspended three-bay truss. The statistical variations of identified mode shapes and frequencies are measured by repeated experiments. Both parameters are shown to vary measurably more with reassembly than sensor placement errors. Also, a directional stiffness in the truss joints was found to cause a parameter dependence on member orientation during reconstruction.

Hinkle, Jason↗
NASA NTRS2022

Comparison of U.S. and Russian Slow Crack Growth Data and Models

Both the US and Russian space programs use similar predictive models for design of fused silica windows on the International space station. The Russian model can be derived from the power expression for slow crack growth (SCG) or “static fatigue.” The US uses both power and exponential models. Despite the similarity of models and data fitting approach (linear regression and right censoring), different SCG parameters have been derived by US and Russian parties for the same material (Russian fused silica) tested in a similar manner. The difference appears to be related to the use of short-term strength data along with the longer-term static fatigue data, with the power law parameter n being very sensitive to the conversion of strength data into equivalent static data. This hybrid approach is feasible if strength data is measured with a constant stress rate and is appropriately converted to a static equivalent. More research into the approach is needed. However, because of the nonlinear behavior of fused silica in log(v) – log(K(I) ) space and the sensitivity of parameter estimation to fit range, the exponential model is a better choice regardless of test method. Functions are given to convert parameters from the Russian model to those in the US model. However, accurate conversion is hampered by the lack of inert strength data. When the same test technique is used, US and Russian materials exhibit very similar parameters.

Silica, strength, impact, crack growth, windows, I↗
NASA NTRS1982

Sensitivity analysis results of the effects of various parameters on composite design

Sensitivity analysis results are presented to assess the effects of a multitude of important parameters on fiber composite design and structural response. These results were obtained by using optimum design procedures in conjunction with sensitivity analyses. Sensitivity analyses were performed to assess the effects on composite optimum design and structural response of parameters such fiber transverse and shear properties, in situ matrix elastic and strength properties, correlation coefficients used in composite micromechanics and in combined strength predictions, processing variables, and perturbations of loading conditions. The results show that matrix properties, fiber volume ratio and small perturbations of the loading conditions have significant effects on certain composite structural responses. The remaining parameters have negligible effect.

Chamis, C. C.↗
NASA NTRS1987

Application of design sensitivity analysis for greater improvement on machine structural dynamics

Methodologies are presented for greatly improving machine structural dynamics by using design sensitivity analyses and evaluative parameters. First, design sensitivity coefficients and evaluative parameters of structural dynamics are described. Next, the relations between the design sensitivity coefficients and the evaluative parameters are clarified. Then, design improvement procedures of structural dynamics are proposed for the following three cases: (1) addition of elastic structural members, (2) addition of mass elements, and (3) substantial charges of joint design variables. Cases (1) and (2) correspond to the changes of the initial framework or configuration, and (3) corresponds to the alteration of poor initial design variables. Finally, numerical examples are given for demonstrating the availability of the methods proposed.

Yoshimura, Masataka↗
NASA NTRS1995

A Probabilistic Design Method Applied to Smart Composite Structures

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Shiao, Michael C.↗
NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗
NASA NTRS1981

Design of control systems with uncertain parameters

A design method for control systems with uncertain parameters is presented. The method utilizes a generalized sensitivity approach which separates the parameter space into regions which produce a system response that satisfies given design criteria and regions which do not. Nonparametric statistics and confidence limits for the binomial distribution are used to determine degree of parameter sensitivity and to locate regions in the parameter space which maximize the probability of producing a desirable system response. In an example it is shown that a given parameter may have to be known to a lesser degree of uncertainty to be able to specify a satisfactory design.

Auslander, D. M.↗
NASA NTRS1982

A simulation-based approach to the design of control systems with uncertain parameters

A design method for control systems with uncertain parameters is presented. The method utilizes a generalized sensitivity approach which separates the parameter space into regions which produce a system response that satisfies given design criteria and regions which do not. Nonparametric statistics and confidence limits for the binomial distribution are used to determine degree of parameter sensitivity and to locate regions in the parameter space which maximize the probability of producing a desirable system response. In an example it is shown that a given parameter may have to be known to a lesser degree of uncertainty to be able to specify a satisfactory design.

Auslander, D. M.↗
NASA NTRS1993

New parameterizations and sensitivities for simple climate models

This paper presents a reexamination of the earth radiation budget parameterization of energy balance climate models in light of data collected over the last 12 years. The study consists of three parts: (1) an examination of the infrared terrestrial radiation to space and its relationship to the surface temperature field on time scales from 1 month to 10 years; (2) an examination of the albedo of the earth with special attention to the seasonal cycle of snow and clouds; (3) solutions for the seasonal cycle using the new parameterizations with special attention to changes in sensitivity. While the infrared parameterization is not dramatically different from that used in the past, the albedo in the new data suggest that a stronger latitude dependence be employed. After retuning the diffusion coefficient the simulation results for the present climate generally show only a slight dependence on the new parameters. Also, the sensitivity parameter for the model is still about the same (1.25 C for a 1 percent increase of solar constant) for the linear models and for the nonlinear models that include a seasonal snow line albedo feedback (1.34 C). One interesting feature is that a clear-sky planet with a snow line albedo feedback has a significantly higher sensitivity (2.57 C) due to the absence of smoothing normally occurring in the presence of average cloud cover.

Graves, Charles E.↗