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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Statistical emulation↗
DOE OSTI2024

Flavor-violating Higgs and Z boson decays at a future circular lepton collider

Recent advances in b , c , and s quark tagging coupled with novel statistical analysis techniques will allow future high energy and high statistics electron-positron colliders, such as the FCC-ee, to place phenomenologically relevant bounds on flavor violating Higgs and Z decays to quarks. We assess the FCC-ee reach for Z / h → b s , c u decays as a function of jet tagging performance. We also update the standard model (SM) predictions for the corresponding branching ratios, as well as the indirect constraints on the flavor violating Higgs and Z couplings to quarks. Using the type III two Higgs doublet model as an example of beyond the standard model physics, we show that the searches for h → b s , c u decays at FCC-ee can probe new parameter space not excluded by indirect searches. We also reinterpret the FCC-ee reach for Z → b s , c u in terms of the constraints on models with vectorlike quarks. Published by the American Physical Society 2024

Kamenik, Jernej F. (ORCID:0000000151838637)↗
NASA NTRS1975

Radar Derived Spatial Statistics of Summer Rain: Data Reduction and Analysis - Volume 2

Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.

Konrad, T. G.↗
NASA NTRS1980

Some adaptive filtering techniques applied to the passive remote sensing problem

A review is made of recursive statistical regression techniques incorporating past or past and future observations through smoothing and Kalman filtering, respectively; with results for the cases of the Tiros-N/MSU and Nimbus-6/Scams remote sensing satellite experiments. In response to the lack of a satisfactory model for the medium sounded, which is presently a major limitation on retrieval technique performance, a novel, global approach is proposed which casts the retrieval problem into the framework of adaptive filtering. A numerical implementation of such an adaptive system is presented, with a multilayer, semi-spectral general circulation model for the atmosphere being used to fine-tune the sensor as well as the dynamical equations of a Kalman filter. It is shown that the assimilation of radiometric data becomes a straightforward subproblem.

Toldalagi, P. M.↗
NASA NTRS1982

The intercrater plains of Mercury and the Moon: Their nature, origin and role in terrestrial planet evolution. Measurement and errors of crater statistics

Planetary imagery techniques, errors in measurement or degradation assignment, and statistical formulas are presented with respect to cratering data. Base map photograph preparation, measurement of crater diameters and sampled area, and instruments used are discussed. Possible uncertainties, such as Sun angle, scale factors, degradation classification, and biases in crater recognition are discussed. The mathematical formulas used in crater statistics are presented.

Leake, M. A.↗
NASA NTRS1999

A Superposition Technique for Deriving Photon Scattering Statistics in Plane-Parallel Cloudy Atmospheres

Photon transport in a multiple scattering medium is critically dependent on scattering statistics, in particular the average number of scatterings. A superposition technique is derived to accurately determine the average number of scatterings encountered by reflected and transmitted photons within arbitrary layers in plane-parallel, vertically inhomogeneous clouds. As expected, the resulting scattering number profiles are highly dependent on cloud particle absorption and solar/viewing geometry. The technique uses efficient adding and doubling radiative transfer procedures, avoiding traditional time-intensive Monte Carlo methods. Derived superposition formulae are applied to a variety of geometries and cloud models, and selected results are compared with Monte Carlo calculations. Cloud remote sensing techniques that use solar reflectance or transmittance measurements generally assume a homogeneous plane-parallel cloud structure. The scales over which this assumption is relevant, in both the vertical and horizontal, can be obtained from the superposition calculations. Though the emphasis is on photon transport in clouds, the derived technique is applicable to any scattering plane-parallel radiative transfer problem, including arbitrary combinations of cloud, aerosol, and gas layers in the atmosphere.

Platnick, S.↗
NASA NTRS1994

Search Space Characterization for a Telescope Scheduling Application

This paper presents a technique for statistically characterizing a search space and demonstrates the use of this technique within a practical telescope scheduling application. The characterization provides the following: (i) an estimate of the search space size, (ii) a scaling technique for multi-attribute objective functions and search heuristics, (iii) a "quality density function" for schedules in a search space, (iv) a measure of a scheduler's performance, and (v) support for constructing and tuning search heuristics. This paper describes the random sampling algorithm used to construct this characterization and explains how it can be used to produce this information. As an example, we include a comparative analysis of an heuristic dispatch scheduler and a look-ahead scheduler that performs greedy search.

Bresina, John↗
NASA NTRS1989

Chi-squared and C statistic minimization for low count per bin data

Results are presented from a computer simulation comparing two statistical fitting techniques on data samples with large and small counts per bin; the results are then related specifically to X-ray astronomy. The Marquardt and Powell minimization techniques are compared by using both to minimize the chi-squared statistic. In addition, Cash's C statistic is applied, with Powell's method, and it is shown that the C statistic produces better fits in the low-count regime than chi-squared.

Nousek, John A.↗
DOE OSTI2020

Simulation of Particle-Material Interactions

This paper gives an overview of the particle transport theory essentials, the basics of particle-material interaction simulation, physical quantities needed to simulate particle transport and interactions in materials, Monte Carlo simulation flow, response of additive detectors, statistical weights and other techniques to minimize statistical errors. Effects in materials under irradiation, materials response related to component lifetime and performance are considered with a focus on high-energy and high-power accelerator applications. Implementation of simulation of particle-material interactions in the modern Monte Carlo codes along with the code s main features and results of recent benchmarking are described.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Hydrogen Dispersion Modeling for Development of Smart Distributed Monitoring

Studying hydrogen dispersion is crucial for ensuring the safe and effective deployment of hydrogen as an energy carrier. This study presents a comprehensive CFD modeling framework for simulating hydrogen dispersion at a real-world hydrogen production, storage, and utilization facility. Utilizing the Hydrogen Research Facility under the Advanced Research on Integrated Energy Systems (ARIES) at the National Renewable Energy Laboratory's (NREL) Flatirons campus, controlled hydrogen releases at 27 kg-H2/hr were simulated. The model incorporated site-specific atmospheric conditions, including hourly wind speeds and temperatures recorded between 8 AM and 8 PM from October to December 2023. To reduce computational demands, a statistical reduction technique was applied to condense the dataset to 100 representative scenarios, validated by statistical tests for wind speeds and power law coefficients. Simulations were conducted using the Reynolds-Averaged Navier-Stokes equations. Results demonstrated that wind speed substantially influences hydrogen dispersion, with low wind conditions forming concentrated clouds and higher wind speeds stretching the plume. Additionally, clustering analysis informed optimal sensor placement at various elevations with up to 10 sensor locations on each elevation. This framework offers a robust approach for understanding hydrogen behavior in ambient conditions and informing detection strategies.

08 HYDROGEN↗
DOE OSTI2024

Evaluating downscaled products with expected hydroclimatic co-variances

Abstract. There has been widespread adoption of downscaled products amongst practitioners and stakeholders to ascertain risk from climate hazards at the local scale (e.g., ∼ 5 km resolution). Such products must nevertheless be consistent with physical laws to be credible and of value to users. Here we evaluate statistically and dynamically downscaled products by examining local co-evolution of downscaled temperature and precipitation during convective and frontal precipitation events (two mechanisms testable with just temperature and precipitation). We find that two widely used statistical downscaling techniques (Localized Constructed Analogs version 2, LOCA2, and Seasonal Trends and Analysis of Residuals Empirical Statistical Downscaling Model, STAR-ESDM) generally preserve expected co-variances during convective precipitation events over the historical and future projected intervals as compared to European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) and two observation-based data products (Livneh and nClimGrid-Daily). However, both techniques dampen future intensification of frontal precipitation that is otherwise robustly captured in global climate models (i.e., prior to downscaling) and with process-based dynamical downscaling across five different regional climate models. In the case of LOCA2, this leads to appreciable underestimation of future frontal precipitation event intensity. This study is one of the first to quantify a likely ramification of the stationarity assumption underlying statistical downscaling methods and identify a phenomenon where projections of future change diverge depending on data production method employed. Finally, our work proposes expected co-variances during convective and frontal precipitation as useful evaluation diagnostics that can be universally applied to a wide range of statistically downscaled products.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Statistical crystallography of surface micelle spacing

The aggregation of the recently reported surface micelles of block polyelectrolytes is analyzed using techniques of statistical crystallography. A polygonal lattice (Voronoi mosaic) connects center-to-center points, yielding statistical agreement with crystallographic predictions; Aboav-Weaire's law and Lewis's law are verified. This protocol supplements the standard analysis of surface micelles leading to aggregation number determination and, when compared to numerical simulations, allows further insight into the random partitioning of surface films. In particular, agreement with Lewis's law has been linked to the geometric packing requirements of filling two-dimensional space which compete with (or balance) physical forces such as interfacial tension, electrostatic repulsion, and van der Waals attraction.

Noever, David A.↗
NASA NTRS1987

Characterization of fault recovery through fault injection on FTMP

The development of fault-injection procedures and statistical analysis techniques to characterize the fault recovery of fault-tolerant systems is described. Pin-level fault-injection was conducted on a fault-tolerant microprocessor computer in order to generate data to assess the utility of current fault-injection sampling methods. The validity of common reliability-modeling assumptions concerning the statistical distribution of recovery times is investigated. A multiple comparison analysis for detecting behavior variations, and a distribution fitting for determining the best fit for the data were conducted. It is observed that the detection behavior is not homogeneous across all data sets, and that none of the factors under experimental control can account for the observed groupings of behavior. It is determined that no single distribution fits all the data sets, and that stratified random sampling and statistically robust parameter-estimation techniques are required to characterize fault detection time.

Finelli, George B.↗