Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “applied statistics”

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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Estimation of peak winds from hourly observations

Two closely related methods to obtain estimates of the hourly peak wind at Cape Kennedy were compared by statistical tests. The methods evaluated the Monin-Obukhov stability length and the standard deviation of the hourly observed wind speed, so as to augment the latter quantity by F standard deviations. F is an optimized factor. A third method utilizing an optimized gust factor was also applied to the hourly wind. The latter procedure estimated 2952 peak winds with an rms error of 2.81 knots, an accuracy which was not surpassed by the other methods. Peak ground wind speed data were developed for use in space shuttle design operation analyses.

Graves, M. E.↗
NASA NTRS1979

Landsat test of diffuse reflectance models for aquatic suspended solids measurement

Landsat radiance data were used to test mathematical models relating diffuse reflectance to aquatic suspended solids concentration. Digital CCT data for Landsat passes over the Bay of Fundy, Nova Scotia were analyzed on a General Electric Co. Image 100 multispectral analysis system. Three data sets were studied separately and together in all combinations with and without solar angle correction. Statistical analysis and chromaticity analysis show that a nonlinear relationship between Landsat radiance and suspended solids concentration is better at curve-fitting than a linear relationship. In particular, the quasi-single-scattering diffuse reflectance model developed by Gordon and coworkers is corroborated. The Gordon model applied to 33 points of MSS 5 data combined from three dates produced r = 0.98.

Munday, J. C., Jr.↗
NASA NTRS2011

Methodology for Determining Limit Torques for Threaded Fasteners

In aerospace design, where minimizing weight is always a priority, achieving the full capacity from fasteners is essential. To do so, the initial bolt preload must be maximized. The benefits of high preload are well documented and include improved fatigue resistance, a stiffer joint, and resistance to loosening. But many factors like elastic interactions and embedment tend to lower the initial preload placed on the bolt. These factors provide additional motivation to maximize the initial preload. But, to maximize bolt preload, you must determine what torque to apply. Determining this torque is greatly complicated by the large preload scatter generally seen with torque control. This paper presents a detailed methodology for generating limit torques for threaded fasteners. This methodology accounts for the large scatter in preload found with torque control, and therefore, addresses the statistical nature of the problem. It also addresses prevailing torque, a feature common in aerospace fasteners. Although prevailing torque provides a desired locking feature, it can also increase preload scatter. In addition, it can limit the amount of preload that can be generated due to the torsion it creates in the bolt. This paper discusses the complications of prevailing torque and how best to handle it. A wide range of torque-tension bolt testing was conducted in support of this research. The results from this research will benefit the design engineer as well as analyst involved in the design of bolted joints, leading to better, more optimized structural designs.

Hissam, Andy↗
NASA NTRS1994

TOPEX/POSEIDON tides estimated using a global inverse model

Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.

Egbert, Gary D.↗
NASA NTRS2003

A Survey of Logic Formalisms to Support Mishap Analysis

Mishap investigations provide important information about adverse events and near miss incidents. They are intended to help avoid any recurrence of previous failures. Over time, they can also yield statistical information about incident frequencies that helps to detect patterns of failure and can validate risk assessments. However, the increasing complexity of many safety critical systems is posing new challenges for mishap analysis. Similarly, the recognition that many failures have complex, systemic causes has helped to widen the scope of many mishap investigations. These two factors have combined to pose new challenges for the analysis of adverse events. A new generation of formal and semi-formal techniques have been proposed to help investigators address these problems. We introduce the term mishap logics to collectively describe these notations that might be applied to support the analysis of mishaps. The proponents of these notations have argued that they can be used to formally prove that certain events created the necessary and sufficient causes for a mishap to occur. These proofs can be used to reduce the bias that is often perceived to effect the interpretation of adverse events. Others have argued that one cannot use logic formalisms to prove causes in the same way that one might prove propositions or theorems. Such mechanisms cannot accurately capture the wealth of inductive, deductive and statistical forms of inference that investigators must use in their analysis of adverse events. This paper provides an overview of these mishap logics. It also identifies several additional classes of logic that might also be used to support mishap analysis.

Johnson, Chris↗
DOE OSTI2026

Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP)

Anthropogenic climate change is unfolding rapidly, yet its regional manifestation can be obscured by internal variability. A primary goal of climate science is to identify the externally forced climate response from among the noise of internal variability. Separating the forced response from internal variability can be addressed in climate models by using a large ensemble to average over different possible realizations of internal variability. However, with only one realization of the real world, it is a major challenge to isolate the forced response directly in observations. In the Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP), contributors used existing and newly developed statistical and machine learning methods to estimate the forced response over 1950–2022 within individual realizations of the climate system. Participants used neural networks, linear inverse models, fingerprinting methods, and low-frequency component analysis, among other approaches. These methods were trained using large ensembles from multiple climate models and then applied to observations. Here, we evaluate method performance within large ensembles and investigate the estimates of the forced response in observations. Our results show that many different types of methods are skillful for estimating the forced response in climate models, though the relative skill of individual methods varies depending on the variable and evaluation metric. Methods with comparable skill in models can give a wide range of estimates of the forced response pattern in observations, illustrating the epistemic uncertainty in forced response estimates. ForceSMIP gives new insights into the forced response in observations, its uncertainty, and methods for its estimation.

Climate attribution↗
DOE OSTI2022

Exploiting Machine Learning in Multiscale Modelling of Materials

Recent developments in efficient machine learning algorithms have spurred significant interest in the materials community. The inherently complex and multiscale problems in Materials Science and Engineering pose a formidable challenge. The present scenario of machine learning research in Materials Science has a clear lacunae, where efficient algorithms are being developed as a separate endeavour, while such methods are being applied as ‘black-box’ models by others. The present article aims to discuss pertinent issues related to the development and application of machine learning algorithms for various aspects of multiscale materials modelling. The authors present an overview of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed.

42 ENGINEERING↗
DOE OSTI2023

Hydrogen and deuterium permeation in Hastelloy N

Hastelloy N was chosen as the fluoride salt-contacting structural material for the Molten Salt Reactor Experiment due to its excellent compatibility with the fuel salt FLiBe. FLiBe is currently investigated for several advanced fusion and fission reactor concepts where tritium generation in the FLiBe is anticipated. Knowledge of hydrogen transport properties through Hastelloy N is important to understand how tritium would permeate through this material and result in an unintentional release. In this study, the hydrogen and deuterium permeability, diffusivity, and solubility were measured from 500 to 700 °C at a primary-side pressure of 10 kPa in a well-characterized sample of Hastelloy N. The prepared polycrystalline Hastelloy N had C and O impurities present on the surface. These impurities were investigated using Auger Emission Spectroscopy and Ar depth profiling. Here, the adventitious C was removed upon the first Ar sputter cycle whereas O persisted deeper into the sample. For permeation experiments, applied deuterium pressures ranged from 13 Pa to 100 kPa and deuterium transport remained in the diffusion-limited regime (J ∝ P 0.5 ) throughout the pressure range examined. Two methods are employed to measure the effective hydrogen and deuterium diffusivity: rise and decline. The decline method produced improved statistical model fits for calculating the effective diffusion coefficient compared to the rise method. The resultant transport properties compared well to published values for other nickel alloys.

08 HYDROGEN↗
DOE OSTI2024

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Dark energy survey year 3 results: Cosmology with peaks using an emulator approach

ABSTRACT We constrain the matter density Ωm and the amplitude of density fluctuations σ8 within the ΛCDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We take into account the uncertainty from the remaining, largely unconstrained ΛCDM parameters (Ωb, ns, and h). We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding $S_8~\equiv ~\sigma _8\sqrt{\Omega _{\mathrm{m}}/0.3}~=~0.797_{-0.013}^{+0.015}$ (68 per cent confidence limits), with a precision of 1.8 per cent, an improvement of 38 per cent compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in S8 is recorded. We find a mild tension of $1.5 \, \sigma$ between our study and the results from Planck 2018, with our analysis yielding a lower S8. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment AIA and S8, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: growth rate of structure measurement from cosmic voids

ABSTRACT We present a void clustering analysis in configuration-space using the completed Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 samples. These samples consist of Luminous Red Galaxies (LRGs) combined with the high-redshift tail of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) DR12 CMASS galaxies (called as LRG+CMASS sample), Emission Line Galaxies (ELGs), and quasars (QSOs). We build void catalogues from the three eBOSS DR16 samples using a ZOBOV-based algorithm, providing 2814 voids, 1801 voids, and 4347 voids in the LRG+CMASS, ELG, and QSO samples, respectively, spanning the redshift range 0.6 < z < 2.2. We measure the redshift space distortions around voids using the anisotropic void-galaxy cross-correlation function and we extract the distortion parameter β. We test the methodology on realistic simulations before applying it to the data, and we investigate all our systematic errors on these mocks. We find βLRG(z = 0.74) = 0.415 ± 0.087, βELG(z = 0.85) = 0.665 ± 0.125 and βQSO(z = 1.48) = 0.313 ± 0.134, for the LRG+CMASS, ELG, and QSO sample, respectively. The quoted errors include systematic and statistical contributions. In order to convert our measurements in terms of the growth rate fσ8, we use consensus values of linear bias from the eBOSS DR16 companion papers, resulting in the following constraints: fσ8(z = 0.74) = 0.50 ± 0.11, fσ8(z = 0.85) = 0.52 ± 0.10, and fσ8(z = 1.48) = 0.30 ± 0.13. Our measurements are consistent with other measurements from eBOSS DR16 using conventional clustering techniques.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dark Energy Survey Year 3 results: $w$CDM cosmology from simulation-based inference with persistent homology on the sphere

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite, specifically designed to mimic DES Y3 data properties, we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins. After neural network compression of these statistics, we estimate the likelihood function and validate our analysis against baryonic feedback effects, finding minimal biases (under $0.3σ$) in the $Ω_\mathrm{m}-S_8$ plane. Assuming the $w$CDM model, our combined Betti numbers and second moments analysis yields $S_8 = 0.821 \pm 0.018$ and $Ω_\mathrm{m} = 0.304\pm0.037$-constraints 70% tighter than those from cosmic shear two-point statistics in the same parameter plane. Our results demonstrate that topological methods provide a powerful and robust framework for extracting cosmological information, with our spherical methodology readily applicable to upcoming Stage IV wide-field galaxy surveys.

Prat, J. [Nordita; Royal Inst. Tech., Sodertalje; ↗
DOE OSTI2026

Deep-field analytical calibration

The next generation of imaging surveys, including the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Euclid, and the Nancy Grace Roman Space Telescope, will provide unprecedented constraints on cosmology using weak gravitational lensing. To fully exploit this statistical power, shear measurement methods must achieve sub- per cent accuracy while mitigating systematic biases from noise, the point-spread function (PSF), blending, and shear-dependent detection. The analytical calibration framework (AnaCal) has demonstrated such accuracy but requires adding noise to images, reducing effective depth. We introduce Deep-Field Analytical Calibration (DEEP-FIELD AnaCal), an extension of AnaCal that uses deep-field images to compute shear responses while preserving the statistical power of wide-field data. We validate DEEP-FIELD AnaCal on isolated and blended galaxy image simulations with LSST-like conditions, finding it meets the stringent requirement of multiplicative bias $|m| < 3\times 10^{-3}$ at 99.7 per cent confidence. Compared to standard AnaCal applied to wide-field images, DEEP-FIELD AnaCal increases the effective galaxy number density from 17 to 30 arcmin$^{-2}$ for simulated 10-yr LSST data. With deep fields $10\times$ longer than the wide field, we find pixel noise variance in shear estimation is reduced by 30 per cent and overall uncertainty by $\sim 25~{{\ \rm per\ cent}}$. Finally, using the LSST Deep Drilling Fields strategy, we assess sample variance and find an equivalent calibration uncertainty of $\lesssim 0.3~{{\ \rm per\ cent}}$. These results demonstrate that DEEP-FIELD AnaCal offers a promising path to achieve the required shear calibration for upcoming weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Hardware-Accelerated Ray Tracing of CAD-Based Geometry for Monte Carlo Radiation Transport

Monte Carlo radiation transport (MCRT) methods have been used to simulate radiation environments for many decades by tracking individual particles through a model to accumulate statistical information. MCRT geometry is historically formed using the constructive solid geometry (CSG). Recently, significant work has been performed to support simulations using computer-aided design (CAD)-based tessellated surfaces to support highly complex geometries. Ray tracing acceleration data structures from the rendering and visualization community are applied to accelerate particle tracking in CAD-based models. Despite these efforts, CSG representations provide the superior performance in surface intersection operations during particle flight. Concurrently, pseudo Monte Carlo methods have become prevalent in rendering applications to support more realistic models for scattering media, motivating innovations that are advantageous for MCRT simulations. Finally, the authors’ work extends these innovations by employing Intel’s Embree ray tracing kernel within a geometry toolkit for Monte Carlo to improve the simulation performance using CAD-based models by factors of 1.5 to 2.

42 ENGINEERING↗
DOE OSTI2020

Modeling the Functional Forms of Grid Disturbances

This report introduces a functional form that may be used to quantitatively predict the impacts of new grid tools and changing system qualities on the likelihoods, durations, and depths of various grid disturbances. Each disturbance scenario is modeled to have three component stages—avoidance, reactance and recovery, which together parametrically estimate one disturbance’s impacts. The modeled scenario is then placed and replicated within an analysis period to represent the likelihood or frequency of the scenario and its consequent impacts. Whereas analysts have struggled to define and apply metrics for grid resilience, the functional form introduced by this report shares units of measurement with accepted grid-status measures (e.g., numbers of customers currently experiencing a service outage). Furthermore, the integrated and averaged functional form over an analysis period provides a meaningful normalized performance metric (e.g., customer outage minutes per year) that is ultimately independent of the duration of the period of. The approach may be applied similarly regardless of the severity or frequency of the disturbances that are being analyzed. Because metrics can be chosen to be identical in both the hypothetical future and the actual historical past, the historical past eventually becomes the test of the future predictions, at least in a statistical sense. The authors originally developed this approach to facilitate analysis of the effects of transactive energy (TE) systems effects on electric power grid resilience. TE systems invite energy suppliers and consumers to actively collaborate toward the discovery of, and their responses to, the locational value of energy. The findings from this process are often embodied as energy prices, the dynamics of which indicate the locational value of energy and can further represent important grid service needs. While some academic papers claim to quantify the value of a specific TE system design toward grid resilience, the answer, in general, has been elusive. Not only do multiple and conflicting definitions of resilience and reliability exist, but countless TE systems are being invented. We conclude the following: (1) The ideal analysis should harmonize rather than differentiate resilience and reliability. Therefore, this report uses the more general term disturbance whenever the overloaded terms resilience and reliability can be avoided. (2) The effectiveness of TE systems must be mapped to underlying qualities of a TE system, thereby avoiding presumptions that every TE design offers similar advantages. The authors seek to evaluate the parametric effects of TE system qualities (e.g., spatial granularity, granularity of time steps, length of future prediction horizon) on avoiding, reacting to, and recovering from grid disturbances. Furthermore, any advantages (or disadvantages) must be fairly compared with the many alternative tools, systems, and strategies that might offer comparable benefits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Ancilla-free continuous-variable SWAP test

We propose a continuous-variable (CV) SWAP test that requires no ancilla register, thereby generalizing the ancilla-free SWAP test for qubits. In this ancilla-free CV SWAP test, the computational basis measurement is replaced by photon number-resolving measurement, and we calculate an upper bound on the error of the overlap estimate obtained from a finite Fock cutoff in the detector. As an example, we show that estimation of the overlap of pure, centered, single-mode Gaussian states of energy E and squeezed in opposite quadratures can be obtained to error ϵ using photon statistics below a Fock basis cutoff O(Elnϵ –1 ). This cutoff is greatly reduced to E + O(√ Elnϵ –1 ) when the states have rapidly decaying Fock tails, such as coherent states. We show how the ancilla-free CV SWAP test can be extended to many modes and applied to quantum algorithms such as variational compiling and entanglement spectroscopy in the CV setting. For the latter we also provide a new algorithm which does not have an analog in qubit systems. The ancilla-free CV SWAP test is implemented on Xanadu's 8-mode photonic processor in order to estimate the vacuum probability of a two-mode squeezed state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1973

Far field effects of weak spatially periodic inhomogeneities.

Small variations in the properties of an acoustic medium produce cumulative effects that significantly alter wave forms propagating over long distances. To investigate some aspects of these effects, without statistical models, the one-dimensional wave equation with a weak spatially periodic variation in the sound speed is treated. An approximation is developed valid for such weak inhomogeneities over large distances based upon the approximate treatment of a linear differential equation with a periodic coefficient. It is applied to the propagation of an initial step wave and identifies the dispersive nature of the medium which accounts for the cumulative effects.

Friedman, M. B.↗
NASA NTRS1988

Development of a satellite SAR image spectra and altimeter wave height data assimilation system for ERS-1

The applicability of ERS-1 wind and wave data for wave models was studied using the WAM third generation wave model and SEASAT altimeter, scatterometer and SAR data. A series of global wave hindcasts is made for the surface stress and surface wind fields by assimilation of scatterometer data for the full 96-day SEASAT and also for two wind field analyses for shorter periods by assimilation with the higher resolution ECMWF T63 model and by subjective analysis methods. It is found that wave models respond very sensitively to inconsistencies in wind field analyses and therefore provide a valuable data validation tool. Comparisons between SEASAT SAR image spectra and theoretical SAR spectra derived from the hindcast wave spectra by Monte Carlo simulations yield good overall agreement for 32 cases representing a wide variety of wave conditions. It is concluded that SAR wave imaging is sufficiently well understood to apply SAR image spectra with confidence for wave studies if supported by realistic wave models and theoretical computations of the strongly nonlinear mapping of the wave spectrum into the SAR image spectrum. A closed nonlinear integral expression for this spectral mapping relation is derived which avoids the inherent statistical errors of Monte Carlo computations and may prove to be more efficient numerically.

Hasselmann, Klaus↗