Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “probabilistic”

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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Probabilistic Photometric Redshifts in the Era of Petascale Astronomy

With the growth of large photometric surveys, accurately estimating photometric redshifts, preferably as a probability density function (PDF), and fully understanding the implicit systematic uncertainties in this process has become increasingly important. These surveys are expected to obtain images of billions of distinct galaxies. As a result, storing and analyzing all of these photometric redshift PDFs will be non-trivial, and this challenge becomes even more severe if a survey plans to compute and store multiple different PDFs. In this thesis, we have developed an end-to-end framework that will compute accurate and robust photometric redshift PDFs for massive data sets by using two new, state-of-the-art machine learning techniques that are based on a random forest and a random atlas, respectively. By using data from several photometric surveys, we demonstrate the applicability of these new techniques, and we demonstrate that our new approach is among the best techniques currently available. We also show how different techniques can be combined by using novel Bayesian techniques to improve the photometric redshift precision to unprecedented levels while also presenting new approaches to better identify outliers. In addition, our framework provides supplementary information regarding the data being analyzed, including unbiased estimates of the accuracy of the technique without resorting to a validation data set, identification of poor photometric redshift areas within the parameter space occupied by the spectroscopic training data, and a quantification of the relative importance of the variables used during the estimation process. Furthermore, we present a new approach to represent and store photometric redshift PDFs by using a sparse representation with outstanding compression and reconstruction capabilities. We also demonstrate how this framework can also be directly incorporated into cosmological analyses. The new techniques presented in this thesis are crucial to enable the development of precision cosmology in the era of petascale astronomical surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Probabilistic Characterization of Partial Volume Effects in Imaging of Rectangular Objects

In imaging, a partial volume effect refers to the problem that arises when the system resolution is low relative to the size of the object being imaged. In this setting, it is likely that most voxels occupied by the object are only partially covered, and that the fraction covered in each voxel is low. This makes the problem of object detection and image segmentation very difficult because the algorithms designed for these purposes rely on pixel summary statistics. If the area covered by the object is very low in relatively many of the total number of the voxels the object occupies, these summary statistics may not reach the thresholds required to detect this object. It is thus important to understand the extent of partial volume effect for a given object size and resolution. This technical report focuses on rectangular objects and derives the probability distributions for three quantities for such objects: 1) the number of fully covered voxels, 2) the number of partially covered voxels, and 3) the fractions of the total volume covered in the partially covered voxels. The derivations are first shown for 2-D settings and are then extended to 3-D settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Validation Metrics for Deterministic and Probabilistic Data

The purpose of this document is to compare and contrast metrics that may be considered for use in validating computational models. Metrics suitable for use in one application, scenario, and/or quantity of interest may not be acceptable in another; these notes merely provide information that may be used as guidance in selecting a validation metric.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Probabilistic predictions and uncertainty estimation for radiological and nuclear effects modeling

Better characterization of meteorological uncertainty is needed to predict the effects of radiological and nuclear releases in the atmosphere. Multi-physics ensembles of atmospheric simulations can estimate uncertainty of physical processes, but they are often limited for computational reasons. Because weather uncertainty is important for emergency response applications, but the conventional way of running multi-physics ensembles is infeasible, we have developed new machine learning-based methods that quickly estimate and identify key sources of meteorological uncertainty. Machine learning accelerates the analysis of weather uncertainty by iteratively learning about model physics options that affect plume predictions. We have demonstrated the power of machine learning by creating a large multi-physics weather and dispersion ensemble dataset containing 1,200 simulations for two hypothetical radiological release scenarios. By training on less than 10% of the ensemble, we can quickly and accurately predict different outcomes, including the mass of radiological material deposited and spatial distribution and extent of contaminated areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Probabilistic Topography Project Update 5/20 [Slides]

Problem/Goal: Earth System Models (ESMs) do not accurately predict fire spread. There are no effects from topography/vegetation heterogeneity below the model’s scale (100-200km). Use physics based models (FIRETEC and QUICFIRE) to produce an archive of correction factors for SPITFIRE (chosen ESM). This project will: Use datasets to create PDFs of slope & aspect, vegetation distribution; Create joint distribution and sample to make new domain; Run FIRETEC & QUICFIRE on created domain, record output (area burned, intensity, etc.); and Use output to create PDF of correction factors for SPITFIRE runs.

58 GEOSCIENCES↗
DOE OSTI2014

Probabilistic Geomechanical Analysis of Compartmentalization at the Snøhvit CO 2 Sequestration Project

Pressure build-up caused by large-scale CO 2 injection is one of the key concerns during a carbon sequestration project. Large overpressures can potentially compromise seal integrity, reactivate faults, and induce concerning seismicity, among other hazards. Furthermore, pressure build-up is directly related with storage capacity. In this work we study the geomechanical response to CO 2 injection in the Tubåen Fm at Snøhvit, with the objective of understanding the potential for fault reactivation, leakage, and contamination of the producing interval in an adjacent block through the bounding faults. Furthermore, we evaluate the potential contribution of a structural component to reservoir compartmentalization. We combine simplified analytical models, based on critically stressed fracture theory and a Mohr-Coulomb failure criterion, with a quantitative risk assessment methodology to perform a rigorous uncertainty quantification. Large stress uncertainties are present and are reflected in the modeling results. It was found that under the “most likely” stress state (Strike-Slip and North-South maximum horizontal stress (S Hmax ) azimuth) the faults are fairly stable, and tensile hydrofracturing of the caprock would be expected before fault reactivation. In most of the analyzed cases, the critical pressure perturbation needed for reactivation is above 13 MPa, which was the limiting pressure increase before reaching the fracture pressure. Faults were found to be ~ 20% less stable when considering plausible variations in the orientation of S Hmax . In those cases, fault reactivation could be expected before caprock failure if injection continued, posing risks of induced seismicity, CO 2 leakage and/or contamination of the gas producing reservoir. Finally, a potential structural component in the compartmentalization and fluid migration is difficult to assess due to stress orientation uncertainty.

54 ENVIRONMENTAL SCIENCES↗