Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Parameter Identifiability”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

A quasi-Newton procedure for identifying pilot-related parameters of the optimal control model

The development and application of a quasi-Newton gradient search procedure for identifying independent pilot related parameters of the optimal control model for pilot/vehicle systems is reported. A sensitivity analysis procedure which determines whether a given model parameter is required to match a specific experimental result, and which experimentally induced parameter changes are required to account for behavioral and performance differences, is described. Application of the identification scheme to training effects in a manual control task is described.

Levison, W. H.↗
DOE OSTI2013

Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information]

Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling, the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Electroweak vacuum stability in classically conformal B - L extension of the standard model

Here, we consider the minimal U(1) B - L extension of the standard model (SM) with the classically conformal invariance, where an anomaly-free U(1) B - L gauge symme- try is introduced along with three generations of right-handed neutrinos and a U(1) B - L Higgs field. Because of the classi- cally conformal symmetry, all dimensional parameters are forbidden. The B - L gauge symmetry is radiatively bro- ken through the Coleman–Weinberg mechanism, generating the mass for the U(1) B - L gauge boson (Z' boson) and the right-handed neutrinos. Through a small negative coupling between the SM Higgs doublet and the B - L Higgs field, the negative mass term for the SM Higgs doublet is gener- ated and the electroweak symmetry is broken. We investigate the electroweak vacuum instability problem in the SM in this model context. It is well known that in the classically conformal U(1) B - L extension of the SM, the electroweak vacuum remains unstable in the renormalization group anal- ysis at the one-loop level. In this paper, we extend the anal- ysis to the two-loop level, and perform parameter scans. We also identify a parameter region which not only solve the vacuum instability problem, but also satisfy the recent ATLAS and CMS bounds from search for Z ' boson resonance at the LHC Run-2. Considering self-energy corrections to the SM Higgs doublet through the right-handed neutrinos and the Z ' boson, we derive the naturalness bound on the model parameters to realize the electroweak scale without fine-tunings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Spacecraft control/flexible structures interaction study

An initial study to begin development of a flight experiment to measure spacecraft control/flexible structure interactions was completed. The approach consisted of developing the equations of motion for a vehicle possessing a flexible solar array, then linearizing about some nominal motion of the craft. A set of solutions is assumed for array deflection using a continuous normal mode method and important parameters are identified. Interrelationships between these parameters, measurement techniques, and input requirements are discussed which assure minimization of special vehicle maneuvers and optimization of data to be obtained during the normal flight sequence. Limited consideration is given to flight data retrieval and processing techniques as correlated with the requirements imposed by the measurement system. Results indicate that inflight measurement of the bending and torsional mode shapes and respective frequencies, and damping ratios, is necessary. Other parameters may be measured from design data.

Kaplan, M. H.↗
NASA NTRS1976

An experimental study of helicopter rotor rotational noise in a wind tunnel

The rotational noise of model helicopter rotors in forward flight was studied in an anechoic wind tunnel. The parameters under study were the rotor thrust (blade loading), blade number and advance ratio. The separate effects of each parameter were identified with the other parameters being held constant. The directivity of the noise was also measured. Twelve sets of data for rotational noise as a function of frequency were compared with the theory of Lowson and Ollerhead. In general, the agreement is reasonably good, except for the cases of (1) low and high disk loadings, (2) the four bladed rotor, and (3) low advance ratios. The theory always under-estimates the rotational noise at high harmonics.

Lee, A.↗
NASA NTRS1996

Thermal Model of the Promoted Combustion Test

Flammability of metals in high pressure, pure oxygen environments, such as rocket engine turbopumps, is commonly evaluated using the Promoted Combustion Test (PCT). The PCT emphasizes the ability of an ignited material to sustain combustion, as opposed to evaluating the sample's propensity to ignite in the first place. A common arrangement is a rod of the sample material hanging in a chamber in which a high pressure, pure oxygen environment is maintained. An igniter of some energetically combusting material is fixed to the bottom of the rod and fired. This initiates combustion, and the sample burns and melts at its bottom tip. A ball of molten material forms, and this ball detaches when it grows too large to be supported by surface tension with the rod. In materials which do not sustain combustion, the combustion then extinguishes. In materials which do sustain combustion, combustion re-initiates from molten residue left on the bottom of the rod, and the melt ball burns and grows until it detaches again. The purpose of this work is development of a PCT thermal simulation model, detailing phase change, melt detachment, and the several heat transfer modes. Combustion is modeled by a summary rate equation, whose parameters are identified by comparison to PCT results. The sensitivity of PCT results to various physical and geometrical parameters is evaluated. The identified combustion parameters may be used in design of new PCT arrangements, as might be used for flammability assessment in flow-dominated environments. The Haynes 214 nickel-based superalloy, whose PCT results are applied here, burns heterogeneously (fuel and oxidizer are of different phases; combustion takes place on the fuel surface). Heterogeneous combustion is not well understood. (In homogeneous combustion, the metal vaporizes, and combustion takes place in an analytically treatable cloud above the surface). Thermal modeling in heterogeneous combustion settings provides a means for linking test results more directly to detailed combustion mechanics, leading to improved data analysis, and improved understanding of heterogeneous combustion phenomena.

Jones, Peter D.↗
NASA NTRS2004

Application of Non-Deterministic Methods to Assess Modeling Uncertainties for Reinforced Carbon-Carbon Debris Impacts

The Space Shuttle Columbia Accident Investigation Board (CAIB) made several recommendations for improving the NASA Space Shuttle Program. An extensive experimental and analytical program has been developed to address two recommendations related to structural impact analysis. The objective of the present work is to demonstrate the application of probabilistic analysis to assess the effect of uncertainties on debris impacts on Space Shuttle Reinforced Carbon-Carbon (RCC) panels. The probabilistic analysis is used to identify the material modeling parameters controlling the uncertainty. A comparison of the finite element results with limited experimental data provided confidence that the simulations were adequately representing the global response of the material. Five input parameters were identified as significantly controlling the response.

Lyle, Karen H.↗
DOE OSTI2023

Identification and localization of rotational spectra using recurrent neural networks

A method of identifying molecular parameters in a complex mixture may include receiving a set of combined transition frequencies and analyzing the set of combined transition frequencies using a first trained artificial neural network to generate a plurality of separated transition frequency sets. Each of the plurality of separated frequency sets may be analyzed using a second trained artificial neural network to generate a respective set of estimated spectral parameters. The method may include identifying a set of molecular parameters corresponding to the set of separated transition frequencies.

Prozuments, Kirills↗
NASA NTRS1983

Adaptive control of a flexible beam using least square lattice filters

This paper presents an indirect adaptive control scheme for the control of flexible structures using recursive least square lattice filters. The identification scheme uses lattice filters which provide an on-line estimate of the number of modes, mode shapes and modal amplitudes. These modes are coupled and a transformation to decouple them in order to obtain the natural modes is presented. The decoupled modal amplitude time series are then used in an equation error identification scheme to identify the model parameters in an autoregressive moving average (ARMA) form. The control is based on modal pole placement scheme with the objective of vibration suppression. The control gains are calculated based on the identified ARMA parameters. Before using the identified parameters for control, detailed testing and validation procedures are carried out on the identified parameters. The full adaptive control scheme is demonstrated using the simulation for the 12 foot free-free beam apparatus at NASA Langley Research Center.

Sundararajan, N.↗
DOE OSTI2021

Identification of crystal plasticity model parameters by multi-objective optimization integrating microstructural evolution and mechanical data

Crystal plasticity models evolve a polycrystalline yield surface using meso-scale descriptions of deformation mechanisms. The activation of deformation mechanisms is governed by crystallography and a set of model parameters, which are typically calibrated through the fitting of mechanical data such as stress–strain curves and elastic lattice strains. Microstructural data such as phase fractions and texture evolution are used for verifying crystal plasticity parameters. In this study, we use a multi-objective genetic algorithm to identify hardening parameters from flow stress curves with an option to incorporate texture into the optimization approach. Robust, generalized objective functions are developed and used to identify sets of parameters pertaining to dislocation density-based hardening laws in visco-plastic and elasto-plastic self-consistent (VPSC and EPSC) homogenization models. First, the parameters are identified for pure Nb directly from texture using an objective function based on generalized spherical harmonics. Since texture evolution is driven by the relative contribution of active slip systems, the parameters governing the evolution of slip resistance ratios can be recovered from fitting discrete textures at a series of strains. Next, a comprehensive set of load reversal data for dual phase (DP) 780 steel is used to fit a hardening law and a back-stress law in EPSC. Finally, parameters pertaining to a complex hardening law for the evolution of slip and twinning in pure α-Ti are identified. Remarkably, using texture as an objective in combination with stress–strain objectives constrains the model of Ti to fully reproduce not only stress–strain and texture evolution but also hierarchical twinning measurements as a function of initial grain size and texture. Furthermore, given an appropriate model fit to representative experimental texture evolution, underlying twin volume fractions contributing to texture evolution can be predicted.

42 ENGINEERING↗
NASA NTRS2015

Detection of Operator Performance Breakdown as an Automation Triggering Mechanism

Performance breakdown (PB) has been anecdotally described as a state where the human operator "loses control of context" and "cannot maintain required task performance." Preventing such a decline in performance is critical to assure the safety and reliability of human-integrated systems, and therefore PB could be useful as a point at which automation can be applied to support human performance. However, PB has never been scientifically defined or empirically demonstrated. Moreover, there is no validated objective way of detecting such a state or the transition to that state. The purpose of this work is: 1) to empirically demonstrate a PB state, and 2) to develop an objective way of detecting such a state. This paper defines PB and proposes an objective method for its detection. A human-in-the-loop study was conducted: 1) to demonstrate PB by increasing workload until the subject reported being in a state of PB, and 2) to identify possible parameters of a detection method for objectively identifying the subjectively-reported PB point, and 3) to determine if the parameters are idiosyncratic to an individual/context or are more generally applicable. In the experiment, fifteen participants were asked to manage three concurrent tasks (one primary and two secondary) for 18 minutes. The difficulty of the primary task was manipulated over time to induce PB while the difficulty of the secondary tasks remained static. The participants' task performance data was collected. Three hypotheses were constructed: 1) increasing workload will induce subjectively-identified PB, 2) there exists criteria that identifies the threshold parameters that best matches the subjectively-identified PB point, and 3) the criteria for choosing the threshold parameters is consistent across individuals. The results show that increasing workload can induce subjectively-identified PB, although it might not be generalizable-only 12 out of 15 participants declared PB. The PB detection method based on signal detection analysis was applied to the performance data and the results showed that PB can be identified using the method, particularly when the values of the parameters for the detection method were calibrated individually.

multi-task environment↗
NASA NTRS2007

Modeling Spacecraft Fuel Slosh at Embry-Riddle Aeronautical University

As a NASA-sponsored GSRP Fellow, I worked with other researchers and analysts at Embry-Riddle Aeronautical University and NASA's ELV Division to investigate the effect of spacecraft fuel slosh. NASA's research into the effects of fuel slosh includes modeling the response in full-sized tanks using equipment such as the Spinning Slosh Test Rig (SSTR), located at Southwest Research Institute (SwRI). NASA and SwRI engineers analyze data taken from SSTR runs and hand-derive equations of motion to identify model parameters and characterize the sloshing motion. With guidance from my faculty advisor, Dr. Sathya Gangadharan, and NASA flight controls analysts James Sudermann and Charles Walker, I set out to automate this parameter identification process by building a simple physical experimental setup to model free surface slosh in a spherical tank with a simple pendulum analog. This setup was then modeled using Simulink and SimMechanics. The Simulink Parameter Estimation Tool was then used to identify the model parameters.

Schlee, Keith L.↗
NASA NTRS1984

Proposed input for determining longitudinal aerodynamic parameters for the space shuttle

A control input form to improve the identification of longitudinal aerodynamic parameters for the Space Shuttle, especially at low Mach numbers, has been proposed. This input combines features of several inputs currently used with the Shuttle to improve the response in angle-of-attack without exceeding pitch rate limits. The responses of the proposed input were generated using a simple three-degree-of-freedom simulation. An examination of the power spectral densities of these responses showed them to have more power near the vehicle natural frequency than doublet inputs previously used with the Shuttle. When the responses to the proposed input were corrupted with noise and processed using a maximum likelihood parameter extraction program, the identifiability of the parameters was improved over the identifiability of the same parameters using actual Shuttle responses from doublet input of a similar magnitude. This preliminary study indicates that the proposed input form should result in improved identifiability of longitudinal static and control parameters for the Shuttle vehicle.

Suit, W. T.↗
NASA NTRS2020

Visible - Near Infrared Spectral Indices for Mapping Mineralogy and Chemistry with OSIRIS-REx

The primary objective of the Origins, Spectral Interpretation, Resource Identification, SecurityRegolith Explorer (OSIRIS-REx) mission is to return to Earth a pristine sample of carbonaceous material from the primitive asteroid (101955) Bennu. To support compositional mapping as part of sample site selection and characterization, we tested 95 spectral parameters on visible to near infrared laboratory reflectance data of minerals and carbonaceous meteorites to find which of these parameters reliably identified spectral features of interest. Most spectral parameters had high positive detection rates when used on spectra of pure, single component materials. The meteorite spectra have fewer and weaker absorption features and, as a result, fewer detections with the spectral parameters. Parameters targeting absorptions at 0.7 and 2.7 – 3 µm, which arise due to hydrated minerals, were most successful for the meteorites. Based on these results, we have identified a set of 17 parameters that are most likely to be useful at Bennu and spectral analogs. These parameters detect olivines, pyroxenes, carbonates, water/OH-bearing minerals, serpentines, ferric minerals, and organics. Particle size and albedo are known to affect band depth but had a negligible impact on parameter accuracy. The effect of instrument-like noise added to the laboratory spectra can result in more false positive detections, but these exhibit large errors. Our study has determined the prioritization of spectral parameters used for OSIRISREx spectral analysis and mapping and informs the reliability of all parameter-derived data products.

Hannah H Kaplan↗
DOE OSTI2026

Robust calibration of non-perturbative models with history matching

We apply, for the first time, Bayes Linear Emulation and History Matching to the calibration of non-perturbative models in Monte Carlo event generators. In contrast to the usual approach of "Monte Carlo tuning", History Matching does not result in best-fit plus ellipsoidal parameter uncertainty estimates but instead identifies all parameter space regions that are consistent with data. This approach leads to a systematic and robust quantification of parametric uncertainties in the models, especially in those challenging cases where different, possibly disjoint, regions of parameter space deliver similar results, which are usually not properly treated with current methodology. We highlight the power of this method with the hadronisation models available through Sherpa : the built-in cluster fragmentation Ahadic and string fragmentation through an interface to Pythia .

Iskauskas, Andrew [Durham U. (main)] (ORCID:000000↗
DOE OSTI2015

Analysis of critically refracted longitudinal waves

Fabrication processes, such as, welding, forging, and rolling can induce residual stresses in metals that will impact product performance and phenomena such as cracking and corrosion. To better manage residual stress tools are needed to map their distribution. The critically refracted ultrasonic longitudinal (LCR) wave is one such approach that has been used for residual stress characterization. It has been shown to be sensitive to stress and less sensitive to the effects of the texture of the material. Although the LCR wave is increasingly widely applied, the factors that influence the formation of the LCR beam are seldom discussed. This paper reports a numerical model used to investigate the transducers' parameters that can contribute to the directionality of the LCR wave and hence enable performance optimization when used for industrial applications. An orthogonal test method is used to study the transducer parameters which influence the LCR wave beams. This method provides a design tool that can be used to study and optimize multiple parameter experiments and it can identify which parameter or parameters are of most significance. The simulation of the sound field in a 2-D 'water-steel' model is obtained using a Spatial Fourier Analysis method. The effects of incident angle, standoff, the aperture and the center frequency of the transducer were studied. Results show that the aperture of the transducer, the center frequency and the incident angle are the most important factors in controlling the directivity of the resulting LCR wave fields.

42 ENGINEERING↗
DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Sensitivity Analysis of the Bone Fracture Risk Model

Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including environmental factors, factors associated with the fall event, mass and anthropometric values of the astronaut, BMD characteristics, characteristics of the relationship between BMD and bone strength and bone fracture characteristics. The uncertainty in these factors is captured through the use of parameter distributions and the fracture predictions are probability distributions with a mean value and an associated uncertainty. To determine parameter sensitivity, a correlation coefficient is found between the sample set of each model parameter and the calculated fracture probabilities. Each parameters contribution to the variance is found by squaring the correlation coefficients, dividing by the sum of the squared correlation coefficients, and multiplying by 100. Results: Sensitivity analyses of BFxRM simulations of preflight, 0 days post-flight and 365 days post-flight falls onto the hip revealed a subset of the twelve factors within the model which cause the most variation in the fracture predictions. These factors include the spring constant used in the hip biomechanical model, the midpoint FRI parameter within the equation used to convert FRI to fracture probability and preflight BMD values. Future work: Plans are underway to update the BFxRM by incorporating bone strength information from finite element models (FEM) into the bone strength portion of the BFxRM. Also, FEM bone strength information along with fracture outcome data will be incorporated into the FRI to fracture probability.

mathematical models↗