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Results for “statistically designed experiments”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Quantitative knowledge acquisition for expert systems

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

Belkin, Brenda L.↗
NASA NTRS1997

The sun at minimum activity: Results from the CELIAS experiment on SOHO

The charge element and isotope analysis system (CELIAS) experiment, designed to continuously measure the composition of the solar wind and solar suprathermal particles, is presented. Information on proton velocity, kinetic temperature, density and out-of-ecliptic flow angle is obtained. A preliminary statistical analysis of proton parameters and freeze-in temperatures, obtained during the first 18 months of the operation of the Solar and Heliospheric Observatory (SOHO), is presented. The first determinations of neon isotopic abundances with CELIAS yielded an excellent agreement with the Apollo-foil experiment. The magnesium isotopic composition in the solar wind agrees with the data acquired from earth.

Bochsler, P.↗
DOE OSTI2019

On the importance of phase saturation heterogeneity in the analysis of laboratory studies of hydrate dissociation

Methane hydrates (MHs) have been considered as the future source of energy because of its vast resource volume and high energy density. Energy recovery from MH-bearing sediments has attracted intensifying research activities. Fundamentally, heat transfer, fluid flow through porous media, and the kinetics of hydrate reaction are the three key processes controlling the behavior of MH dissociation and the associated fluid production. Earlier studies have suggested that heterogeneous spatial distribution of SH is inevitable in MH-bearing samples synthesized in laboratory. In this paper, we extend our study to analyze numerically the simulation results from the two realizations of the samples (homogeneous and heterogeneous) to identify differences in the fluid production and to determine if they are sufficiently different. Additionally, we conduct a sensitivity analysis and a statistical analysis on the key transport and kinetic rate parameters that could affect hydrate dissociation and fluid production in the context of a heterogeneous hydrate-bearing sample, in an effort to provide insights that could lead to improved designs for laboratory experiments and (possibly) field applications. Our results suggest that the approximation of an artificial hydrate-bearing core with heterogeneous phase saturations by an assumption of uniform phase saturation distributions results in practically similar fluid production profile except for the very early stage with maximum 20.0% deviation in the water production. From the sensitivity and statistical analysis, we determine that gas production depends strongly on the kinetic rate constant, K d 0 and the composite thermal conductivity of the hydrate-bearing sediments, λ θ ; while, water production is very sensitive to K d 0 and the absolute permeability of the sandy medium, k. Understanding the effect of phase heterogeneity and the relative importance of key parameters on the production behavior of hydrate-bearing sediments could provide basis for novel production technologies that lead to enhanced gas production and energy efficiency in the energy recovery process.

42 ENGINEERING↗
DOE OSTI2018

An Efficient Pipeline for Abdomen Segmentation in CT Images

Computed tomography (CT) scans usually include some disadvantages due to the nature of the imaging procedure, and these handicaps prevent accurate abdomen segmentation. Discontinuous abdomen edges, bed section of CT, patient information, closeness between the edges of the abdomen and CT, poor contrast, and a narrow histogram can be regarded as the most important handicaps that occur in abdominal CT scans. Currently, one or more handicaps can arise and prevent technicians obtaining abdomen images through simple segmentation techniques. In other words, CT scans can include the bed section of CT, a patient’s diagnostic information, low-quality abdomen edges, low-level contrast, and narrow histogram, all in one scan. These phenomena constitute a challenge, and an efficient pipeline that is unaffected by handicaps is required. In addition, analysis such as segmentation, feature selection, and classification has meaning for a real-time diagnosis system in cases where the abdomen section is directly used with a specific size. A statistical pipeline is designed in this study that is unaffected by the handicaps mentioned above. Intensity-based approaches, morphological processes, and histogram-based procedures are utilized to design an efficient structure. Performance evaluation is realized in experiments on 58 CT images (16 training, 16 test, and 26 validation) that include the abdomen and one or more disadvantage(s). The first part of the data (16 training images) is used to detect the pipeline’s optimum parameters, while the second and third parts are utilized to evaluate and to confirm the segmentation performance. The segmentation results are presented as the means of six performance metrics. Thus, the proposed method achieves remarkable average rates for training/test/validation of 98.95/99.36/99.57% (jaccard), 99.47/99.67/99.79% (dice), 100/99.91/99.91% (sensitivity), 98.47/99.23/99.85% (specificity), 99.38/99.63/99.87% (classification accuracy), and 98.98/99.45/99.66% (precision). In summary, a statistical pipeline performing the task of abdomen segmentation is achieved that is not affected by the disadvantages, and the most detailed abdomen segmentation study is performed for the use before organ and tumor segmentation, feature extraction, and classification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗
DOE OSTI2019

Making inertial confinement fusion models more predictive

Computer models of inertial confinement fusion (ICF) implosions play an essential role in experimental design and interpretation as well as our understanding of fundamental physics under the most extreme conditions that can be reached in the laboratory. Building truly predictive models is a significant challenge, with the potential to greatly accelerate progress to high yield and ignition. One path to more predictive models is to use experimental data to update the underlying physics in a way that can be extrapolated to new experiments and regimes. We describe a statistical framework for the calibration of ICF simulations using data collected at the National Ignition Facility (NIF). We perform Bayesian inferences for a series of laser shots using an approach that is designed to respect the physics simulation as much as possible and then build a second model that links the individual-shot inferences together. We show that this approach is able to match multiple X-ray and neutron diagnostics for a whole series of NIF “BigFoot” shots. Within the context of 2D radiation hydrodynamic simulations, our inference strongly favors a significant reduction in fuel compression over other known degradation mechanisms (namely, hohlraum issues and engineering perturbations). This analysis is expanded using a multifidelity technique to pick fuel-ablator mix from several candidate causes of the degraded fuel compression (including X-ray preheat and shock timing errors). Finally, we use our globally calibrated model to investigate the extra laser drive energy that would be required to overcome the inferred fuel compression issues in NIF BigFoot implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Discontinuities in effective permeability due to fracture percolation

Motivated by a triaxial coreflood experiment with a sample of Utica shale where an abrupt jump in permeability was observed, possibly due to the creation of a percolating fracture network through the sample, we perform numerical simulations based on the experiment to characterize how the effective permeability of otherwise low-permeability porous media depends on fracture formation, connectivity, and the contrast between the fracture and matrix permeabilities. While a change in effective permeability due to fracture formation is expected, the dependence of its magnitude upon the contrast between the matrix permeability and fracture permeability and the fracture network structure is poorly characterized. We use two different high-fidelity fracture network models to characterize how effective permeability changes as percolation occurs. The first is a dynamic two-dimensional fracture propagation model designed to mimic the laboratory settings of the experiment. The second is a static three-dimensional discrete fracture network (DFN) model, whose fracture and network statistics are based on the fractured sample of Utica shale. Once the network connects the inflow and outflow boundaries, the effective permeability increases non-linearly with network density. In most networks considered, a jump in the effective permeability was observed when the embedded fracture network percolated. We characterize how the magnitude of the jump, should it occur, depends on the contrast between the fracture and matrix permeabilities. For small contrasts between the matrix and fracture permeabilities the change is insignificant. However, for larger contrasts, there is a substantial jump whose magnitude depends non-linearly on the difference between matrix and fracture permeabilities. A power-law relationship between the size of the jump and the difference between the matrix and fracture permeabilities is observed. In conclusion, the presented results underscore the importance of fracture network topology on the upscaled properties of the porous medium in which it is embedded.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding window Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Graduate engineering research participation in aeronautics

The Aeronautics Graduate Research Program commenced in 1971, with the primary goal of engaging students who qualified for regular admission to the Graduate School of Engineering at Old Dominion University in a graduate engineering research and study program in collaboration with NASA Langley Research Center, Hampton, Virginia. The format and purposes of this program are discussed. Student selection and program statistics are summarized. Abstracts are presented in the folowing areas: aircraft design, aerodynamics, lift/drag characteristics; avionics; fluid mechanics; solid mechanics; instrumentation and measurement techniques; thermophysical properties experiments; large space structures; earth orbital dynamics; and environmental engineering.

Roberts, A. S., Jr.↗
NASA NTRS1997

CARES/Life Software for Designing More Reliable Ceramic Parts

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion, and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CAPES/Life software eases this task by providing a tool to optimize the design and manufacture of brittle material components using probabilistic reliability analysis techniques. Probabilistic component design involves predicting the probability of failure for a thermomechanically loaded component from specimen rupture data. Typically, these experiments are performed using many simple geometry flexural or tensile test specimens. A static, dynamic, or cyclic load is applied to each specimen until fracture. Statistical strength and SCG (fatigue) parameters are then determined from these data. Using these parameters and the results obtained from a finite element analysis, the time-dependent reliability for a complex component geometry and loading is then predicted. Appropriate design changes are made until an acceptable probability of failure has been reached.

Nemeth, Noel N.↗
NASA NTRS1985

Aerospace spacecraft-charging guidelines document

A short summary document on spacecraft charging was prepared for use by engineers in the various Aerospace Corporation program offices that support Air Force Space Division programs. The magnetospheric charging environment at near-geosynchronous altitudes is outlined and the mechanisms of charging and discharging are discussed. Statistical results from the P78-2 (SCATHA) satellite engineering experiments are given. The document is intended to be a layman's source for charging information and for design guidance and criteria.

Fennell, J. F.↗
NASA NTRS1999

Moisture Forecast Bias Correction in GEOS DAS

Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

Dee, D.↗
NASA NTRS2019

Refinement of Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Computational simulations of the flow within a streamline-traced, external-compression supersonic inlet for Mach 1.664 without and with vortex generators were performed to refine the characterization of the inlet performance as measured by the total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. The refinement of the simulations concerned two aspects: 1) refinement of the grid for the simulations to evaluate and reduce uncertainty, and 2) refinement of the modeling and design of the vortex generators. The vortex generators studied were rectangular vane-type vortex generators arranged in co-rotating arrays within the subsonic diffuser. The vortex generator geometric factors of interest included the height, circumferential spacing, and angle-of-incidence. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vortex generators were simulated using either a vortex generator model or with grids generated about each vortex generator. Statistical methods were used to compute confidence intervals and grid convergence indices to establish the uncertainties of the analyses with respect to grid refinement. Design-of-experiments methods were applied to quantify the effects of the geometric factors of the vortex generators. The analyses of the computed results illustrate the complexities of quantifying the uncertainties of the inlet performance and the implications of the uncertainties for the design of a vortex generator array for the STEX inlet.

Slater, John W.↗
NASA NTRS1997

Development of Large Area Emulsion Chamber Methods with a Super Conducting Magnet for Observation of Cosmic Ray Nuclei from 1 GeV to 1,000 TeV (Emulsion Techniques)

The research developed the fundamental techniques of the emulsion chamber methods that permit measurements of the composition and energy spectra of cosmic rays at energies ranging from 1 GeV/n to over 1,000 TeV/n. The research program consisted of exploring new principles and techniques in measuring very high energy cosmic nuclei with large-area emulsion chambers for high statistics experiments. These tasks have been accomplished and their use was essential in successful analysis of the balloon-borne emulsion chamber experiments up to 10(exp 14) eV. It also provided the fundamental technologies for designing large-area detectors that are aimed at measuring the composition at above 1015 eV region. The latter is now partially succeeded by a NASA Mission Concept, Advanced Cosmic Composition Experiments on the Space Station (ACCESS). The cosmic ray group at the University of Alabama in Huntsville has performed technological R & D as well as contributing to the Japanese-American-Emulsion-Chamber-Experiments (JACEE) Collaboration with the regular data analysis. While primary research support for other institutions' efforts in the JACEE experiments came from NSF and DOE, primary support for the University of Alabama in Huntsville was this contract. Supplemental tasks to standardize the data base and hardware upgrades (automatized microscope) had this institutions cooperation. Investigation of new techniques in this program consisted of development of a fast calorimetry, magnetic/scattering selection of high momentum tracks for a pairmeter, and high statistics momentum measurements for low energy nuclei (E < 1 TeV/n). The highest energy calorimetry and a pairmeter have been considered as strawman instruments by the GOAL (Galactic Origin and Acceleration Limit) proposal of the NASA Cosmic Ray Working Group for long- duration balloon flights. We accomplished the objectives of the GOAL program with three circumpolar, Antarctic JACEE balloon flights during 1992 - 1994.

Takahashi, Yoshiyuki↗
DOE OSTI2021

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

The Roles of Large- and Small-Scale Structures in Turbulent Free Shear Layers

The occurrence of large-scale coherent structures in turbulent free shear flows (especially the planar mixing layer) has been recognized for some time. Indeed, the observation of such structures in mixing layers did much to promote interest in the study of coherent structures in turbulence. It has been widely assumed that the large-scale structures in these flows are responsible for the entrainment of free-stream fluid and the overall growth of the layer, while the small-scale structures provide mixing and dissipation. A model of scalar mixing based on these ideas was proposed for these flows. However, recent experimental and computational evidence suggests that the dominance of the large-scale structures in turbulent mixing layers is not universal. In addition, there is a substantial variation among experiments in several statistical measures of self-similar mixing layers, for example growth rate and velocity variances. To investigate the importance of large-scale structures, several free shear flows (mixing layers and wakes) have been simulated via direct numerical simulation. The simulations are designed to mimic experimental mixing layers in which the splitter plate boundary layers are turbulent. Different levels of two-dimensional forcing are included resulting in large-scale structures of differing strength and importance. These simulations are used to investigate the role of large-scale coherent structures in free shear layers and the effect of these structures on relevant turbulence statistics and scalar mixing. It is found that the statistics and structures in several experiments involving turbulent mixing layers are in better agreement with simulations that do not exhibit dominant large-scale structures than those in which the common mixing layer structures do dominate. It is also found that the level of forcing can have a profound effect on the qualitative and quantitative features of these shear layer, even when they are nominally self-similar.

Moser, Robert D.↗
DOE OSTI2018

Estimating the joint distribution of rate parameters across multiple reactions in the absence of experimental data

Here, a procedure for determining the joint uncertainty of Arrhenius parameters across multiple combustion reactions of interest is demonstrated. This approach is capable of constructing the joint distribution of the Arrhenius parameters arising from the uncertain measurements performed in specific target experiments without having direct access to the underlying experimental data. The method involves constructing an ensemble of hypothetical data sets with summary statistics consistent with the available information reported by the experimentalists, followed by a fitting procedure that learns the structure of the joint parameter density across reactions using this consistent hypothetical data as evidence. The procedure is formalized in a Bayesian statistical framework, employing maximum-entropy and approximate Bayesian computation methods and utilizing efficient Markov chain Monte Carlo techniques to explore data and parameter spaces in a nested algorithm. We demonstrate the application of the method in the context of experiments designed to measure the rates of selected chain reactions in the H 2 -O 2 system and highlight the utility of this approach for revealing the critical correlations between the parameters within a single reaction and across reactions, as well as for maximizing consistency when utilizing rate parameter information in predictive combustion modeling of systems of interest.

97 MATHEMATICS AND COMPUTING↗