Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “PROBABILISTIC ESTIMATION”

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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

WE-E-BRE-05: Ensemble of Graphical Models for Predicting Radiation Pneumontis Risk

Purpose: We propose a prior knowledge-based approach to construct an interaction graph of biological and dosimetric radiation pneumontis (RP) covariates for the purpose of developing a RP risk classifier. Methods: We recruited 59 NSCLC patients who received curative radiotherapy with minimum 6 month follow-up. 16 RP events was observed (CTCAE grade ≥2). Blood serum was collected from every patient before (pre-RT) and during RT (mid-RT). From each sample the concentration of the following five candidate biomarkers were taken as covariates: alpha-2-macroglobulin (α2M), angiotensin converting enzyme (ACE), transforming growth factor β (TGF-β), interleukin-6 (IL-6), and osteopontin (OPN). Dose-volumetric parameters were also included as covariates. The number of biological and dosimetric covariates was reduced by a variable selection scheme implemented by L1-regularized logistic regression (LASSO). Posterior probability distribution of interaction graphs between the selected variables was estimated from the data under the literature-based prior knowledge to weight more heavily the graphs that contain the expected associations. A graph ensemble was formed by averaging the most probable graphs weighted by their posterior, creating a Bayesian Network (BN)-based RP risk classifier. Results: The LASSO selected the following 7 RP covariates: (1) pre-RT concentration level of α2M, (2) α2M level mid- RT/pre-RT, (3) pre-RT IL6 level, (4) IL6 level mid-RT/pre-RT, (5) ACE mid-RT/pre-RT, (6) PTV volume, and (7) mean lung dose (MLD). The ensemble BN model achieved the maximum sensitivity/specificity of 81%/84% and outperformed univariate dosimetric predictors as shown by larger AUC values (0.78∼0.81) compared with MLD (0.61), V20 (0.65) and V30 (0.70). The ensembles obtained by incorporating the prior knowledge improved classification performance for the ensemble size 5∼50. Conclusion: We demonstrated a probabilistic ensemble method to detect robust associations between RP covariates and its potential to improve RP prediction accuracy. Our Bayesian approach to incorporate prior knowledge can enhance efficiency in searching of such associations from data. The authors acknowledge partial support by: 1) CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and 2) The Terry Fox Foundation Strategic Training Initiative for Excellence in Radiation Research for the 21st Century (EIRR21)

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

Evolving Understanding of Antarctic Ice-Sheet Physics and Ambiguity in Probabilistic Sea-Level Projections

Mechanisms such as ice-shelf hydrofracturing and ice-cliff collapse may rapidly increase discharge from marine-based ice sheets. Here, we link a probabilistic framework for sea-level projections to a small ensemble of Antarctic ice-sheet (AIS) simulations incorporating these physical processes to explore their influence on global-mean sea-level (GMSL) and relative sea-level (RSL). We compare the new projections to past results using expert assessment and structured expert elicitation about AIS changes. Under high greenhouse gas emissions (Representative Concentration Pathway [RCP] 8.5), median projected 21st century GMSL rise increases from 79 to 146 cm. Without protective measures, revised median RSL projections would by 2100 submerge land currently home to 153 million people, an increase of 44 million. The use of a physical model, rather than simple parameterizations assuming constant acceleration of ice loss, increases forcing sensitivity: overlap between the central 90% of simulations for 2100 for RCP 8.5 (93-243 cm) and RCP 2.6 (26-98 cm) is minimal. By 2300, the gap between median GMSL estimates for RCP 8.5 and RCP 2.6 reaches >10 m, with median RSL projections for RCP 8.5 jeopardizing land now occupied by 950 million people (versus 167 million for RCP 2.6). The minimal correlation between the contribution of AIS to GMSL by 2050 and that in 2100 and beyond implies current sea-level observations cannot exclude future extreme outcomes. The sensitivity of post-2050 projections to deeply uncertain physics highlights the need for robust decision and adaptive management frameworks.

Kopp, Robert E.↗
DOE OSTI2022

Human reliability analysis studies from simulator experiments using Bayesian inference

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

PRA methodology is one of the probabilistic analysis methods that NASA brought from the nuclear industry to assess the risk of LOM, LOV and LOC for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability and statistical data to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: What can go wrong? How likely is it? What is the severity of the degradation? Since 1986, NASA, along with industry partners, has conducted a number of PRA studies to predict the overall launch vehicles risks. Planning Research Corporation conducted the first of these studies in 1988. In 1995, Science Applications International Corporation (SAIC) conducted a comprehensive PRA study. In July 1996, NASA conducted a two-year study (October 1996 - September 1998) to develop a model that provided the overall Space Shuttle risk and estimates of risk changes due to proposed Space Shuttle upgrades. After the Columbia accident, NASA conducted a PRA on the Shuttle External Tank (ET) foam. This study was the most focused and extensive risk assessment that NASA has conducted in recent years. It used a dynamic, physics-based, integrated system analysis approach to understand the integrated system risk due to ET foam loss in flight. Most recently, a PRA for Ares I launch vehicle has been performed in support of the Constellation program. Reliability, on the other hand, addresses the loss of functions. In a broader sense, reliability engineering is a discipline that involves the application of engineering principles to the design and processing of products, both hardware and software, for meeting product reliability requirements or goals. It is a very broad design-support discipline. It has important interfaces with many other engineering disciplines. Reliability as a figure of merit (i.e. the metric) is the probability that an item will perform its intended function(s) for a specified mission profile. In general, the reliability metric can be calculated through the analyses using reliability demonstration and reliability prediction methodologies. Reliability analysis is very critical for understanding component failure mechanisms and in identifying reliability critical design and process drivers. The following sections discuss the PRA process and reliability engineering in detail and provide an application where reliability analysis and PRA were jointly used in a complementary manner to support a Space Shuttle flight risk assessment.

Safie, Fayssal M.↗
DOE OSTI2015

Probabilistic geomechanical analysis of compartmentalization at the Snøhvit CO 2 sequestration project

Abstract Pressure buildup caused by large‐scale CO 2 injection is a key concern during a carbon sequestration project. Large overpressures can compromise seal integrity, reactivate faults, and induce seismicity. Furthermore, pressure buildup is directly related with storage capacity. In this work we study the geomechanical response to CO 2 injection at Snøhvit, to understand the potential for fault reactivation, leakage, and contamination of the producing interval through 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 rigorous sensitivity analysis. Large stress uncertainties are present and reflected in the modeling results. It was found that under the most likely stress state the faults are fairly stable and caprock hydrofracturing 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 variations in S Hmax orientation. In those cases, fault reactivation could be expected before caprock failure if injection continued. However, if the pressure increase did reach the critical values for seal failure estimated under the worst case (and least likely) stress state, no indication of such failure can be observed in the measured pressure response. Finally, the potential role of a structural component in the compartmentalization and fluid migration is difficult to assess due to the stress state uncertainty.

Chiaramonte, Laura↗
DOE OSTI2023

Quantifying the effect of late bombardment on terrestrial zircons

The first 500 million years of Earth history is thought to be a period of intense planetary bombardment, but the timing and flux of this meteorite bombardment is poorly understood. In particular, on the basis of an inferred lunar impact history, some workers have hypothesized a ~3.9 Ga terminal cataclysm (TC) in which there was marked increase in the impact flux affecting the Moon, the Earth and possibly other terrestrial planets. Minerals that survived this enigmatic period offer a way to test early planetary bombardment models as they may contain telltale micro- to nanoscale shock features. Here, we present results from a numerical modeling calculation that assesses the probability that a zircon residing in the crust would escape shock melting or shock deformation during a TC bombardment event. Even with conservative pressure estimates for zircon shock deformation and intermediate bombardment intensities, we find that only ~6% of ≥4.0 Ga crust would be expected to survive a 3.9 Ga cataclysm without experiencing either complete melting or zircon shock metamorphism. In this study, we couple this modeling with a search for shock effects in the oldest zircons from the Acasta Gneiss Complex, which would have been present in the Earth's crust during a putative 3.9 Ga TC. Spatially correlated electron and NanoSIMS ion microscopy of 4.02 Ga igneous zircons from Acasta reveals no evidence of ancient shock. These data, together with similar results from other Hadean zircon suites, confirm that a post-Hadean TC is unlikely to have occurred. We suggest that the dearth of pre-3.9 Ga terrestrial crust and zircons is instead best explained by endogenic processes related to the mechanisms of early crust formation. Our modeling allows us to evaluate bombardment scenarios from the terrestrial zircon record by applying probabilistic interpretations to zircon shock deformation data. This approach will be valuable for other planetary bodies, allowing broader conclusions to be drawn from geographically limited datasets.

58 GEOSCIENCES↗
DOE OSTI2023

Safety Benefits Assessment for Accident Tolerant Fuels in Consideration of Steam Generator Tube Degradation Using Dynamic Event Tree Analysis

Accident tolerant fuel (ATF) is expected to delay or prevent core damage by providing additional coping time under accidents involving loss of core cooling. The effect of extended coping time may vary depending on the plant response to accidents. Age-related component degradation that deteriorates plant performance over time could have an impact on the actual advantages of ATF. The potential safety benefits of two near-term ATF candidates, including Cr-coated Zr cladding and FeCrAl cladding, are assessed for a 2-in. loss-of-coolant accident with failed high-pressure safety injection using the dynamic event tree (DET) approach considering possible stress corrosion cracking of steam generator (SG) tubing under aging. The DET approach allows likelihood quantification of accident sequences leading to core damage, including stochastic variation of system response and human actions during accident mitigation. The safety benefits of the selected ATF claddings in terms of additional coping time and the core damage frequency reduction rate under specified accident situations were quantitatively estimated. The results show that the deployment of the two selected ATF claddings is expected to lead to longer coping times and lower core damage frequency due to the wider safety margin to peak cladding temperature they provide. The safety advantages would be greater as SG tube degradation proceeds. Thus, the two ATF candidates would lead to less severe consequences in terms of likelihood of core damage and susceptibility to the SG tube degradation than UO 2 -Zr fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

User’s Manual for RESRAD-BUILD Code V.4: Vol. 1 – Methodology and Models Used in RESRAD-BUILD Code

The RESRAD-BUILD computer code models radionuclide release and transport in indoor environments and performs pathway analyses to evaluate the potential radiological dose and risk incurred by an individual who works or lives in a building contaminated with radioactive material or housing radioactively contaminated furniture or equipment. The code provides four geometries to characterize a radiation source: point, line, area, and volume, in which radionuclides are homogeneously distributed. Radionuclides contained in a source are considered to be released to the indoor air due to various processes including erosion (mechanically or weathering), diffusion (for tritium and radon in a volume source), or emanation (radon in a point, line, or area source). The release can proceed through different time phases with different rates. In RESRAD-BUILD Version 4.0, a dynamic ventilation model is implemented to simulate the fate and transport of source material particles and radionuclides after their releases. This dynamic ventilation model considers (1) air exchange between rooms in the building and between the rooms and the outdoor environment, (2) deposition from air to floor, (3) resuspension from the floor to the air, and (4) periodical vacuuming that reduces the floor deposition. The fate and transport modeling provides estimates of radionuclide concentrations in the source, in the air, and on the floor at different times, which are then integrated over the exposure duration for the calculation of radiation doses and cancer risks. A single run of the RESRAD-BUILD code can model a building with up to 9 rooms, 10 sources, and 10 receptors. The potential radiation dose and cancer risk incurred by each receptor are calculated for seven exposure pathways: (1) external radiation directly from the sources (accounting for shielding), (2) external radiation from radioactive particles deposited on the floors, (3) external radiation from airborne radionuclides, (4) inhalation of airborne radionuclides, (5) inhalation of radon and radon progenies, (6) inadvertent ingestion of radioactive particles directly from the source, and (7) ingestion of radioactive particles deposited on the floors. Various exposure scenarios can be modeled with RESRAD-BUILD, including but are not limited to, office worker, renovation worker, decontamination worker, building visitor, and resident. Both deterministic and probabilistic analyses can be performed to obtain results in both text reports and graphic displays.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2003

Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

Rais-Rohani, Masoud↗
DOE OSTI2015

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

ODIN: Characterizing the Three-dimensional Structure of Two Protocluster Complexes at z = 3.1

We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at z = 3.1. These protocluster "complexes," designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of z = 3.1 Lyα emitters (LAEs) identified in the COSMOS field by the One-hundred-deg$^{2}$ DECam Imaging in Narrowbands survey. These protocluster complexes have been followed up with extensive spectroscopy from Keck, Gemini, and DESI. Using a probabilistic method that combines photometrically selected and spectroscopically confirmed LAEs, we reconstruct the 3D structure of these complexes on scales of ≈50 cMpc. We validate our reconstruction method using the IllustrisTNG300-1 cosmological hydrodynamical simulation and show that it consistently outperforms approaches relying solely on spectroscopic data. The resulting 3D maps reveal that both complexes are irregular and elongated along a single axis, emphasizing the impact of sightline on our perception of structure morphology. The complexes consist of multiple density peaks, 10 in COSMOS-z3.1-A and 4 in COSMOS-z3.1-C. The former is confirmed to be a proto-supercluster, similar to Hyperion at z = 2.4 but observed at an even earlier epoch. Multiple "tails" connected to the cores of the density peaks are seen, likely representing cosmic filaments feeding into these extremely overdense regions. The 3D reconstructions further provide strong evidence that Lyα blobs preferentially reside in the outskirts of the highest density regions. Descendant mass estimates of the density peaks suggest that COSMOS-z3.1-A and COSMOS-z3.1-C will evolve to become ultramassive structures by z = 0, with total masses log ( M / M ,⊙ ,) ≳ 15.3 , exceeding that of Coma.

Ramakrishnan, Vandana [Purdue U., West Lafayette] ↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

What Is the Value of Alternative Methods for Estimating Ramping Needs?

Power system operators procure and deploy flexibility reserves or ramping products to address balancing needs caused by uncertainty and variability of load and generation. Existing methods estimate ramping needs using calendar information and historical forecast errors. Novel methods investigate if real-time weather information could inform ramping and other balancing requirements. This paper compares estimation methods for ramping requirements in theory and practice. The theoretical framework indicates when an alternative method could yield improved economic or reliability performance than existing methods by requiring lower or higher levels of ramping products. Preliminary simulations on a 118-bus test system for 4 days in May 2019 illustrate how system performance improves or deteriorates when ramping requirements are weather-informed (alternative) instead of calendar-based (baseline). Preliminary results suggest high variability in change of performance and underline the impact of additional factors, such as system conditions, on the realized performance change.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS2010

NASA Tech Briefs, March 2010

Topics covered include: Software Tool Integrating Data Flow Diagrams and Petri Nets; Adaptive Nulling for Interferometric Detection of Planets; Reducing the Volume of NASA Earth-Science Data; Reception of Multiple Telemetry Signals via One Dish Antenna; Space-Qualified Traveling-Wave Tube; Smart Power Supply for Battery-Powered Systems; Parallel Processing of Broad-Band PPM Signals; Inexpensive Implementation of Many Strain Gauges; Constant-Differential-Pressure Two-Fluid Accumulator; Inflatable Tubular Structures Rigidized with Foams; Power Generator with Thermo-Differential Modules; Mechanical Extraction of Power From Ocean Currents and Tides; Nitrous Oxide/Paraffin Hybrid Rocket Engines; Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents; Probabilistic Multi-Factor Interaction Model for Complex Material Behavior; Foldable Instrumented Bits for Ultrasonic/Sonic Penetrators; Compact Rare Earth Emitter Hollow Cathode; High-Precision Shape Control of In-Space Deployable Large Membrane/Thin-Shell Reflectors; Rapid Active Sampling Package; Miniature Lightweight Ion Pump; Cryogenic Transport of High-Pressure-System Recharge Gas; Water-Vapor Raman Lidar System Reaches Higher Altitude; Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes; Wide-Field-of-View, High-Resolution, Stereoscopic Imager; Electrical Capacitance Volume Tomography with High-Contrast Dielectrics; Wavefront Control and Image Restoration with Less Computing; Polarization Imaging Apparatus; Stereoscopic Machine-Vision System Using Projected Circles; Metal Vapor Arcing Risk Assessment Tool; Performance Bounds on Two Concatenated, Interleaved Codes; Parameterizing Coefficients of a POD-Based Dynamical System; Confidence-Based Feature Acquisition; Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery; Universal Decoder for PPM of any Order; Algorithm for Stabilizing a POD-Based Dynamical System; Mission Reliability Estimation for Repairable Robot Teams; Processing AIRS Scientific Data Through Level 3; Web-Based Requesting and Scheduling Use of Facilities; AutoGen Version 5.0; Time-Tag Generation Script; PPM Receiver Implemented in Software; Tropospheric Emission Spectrometer Product File Readers; Reporting Differences Between Spacecraft Sequence Files; Coordinating "Execute" Data for ISS and Space Shuttle; Database for Safety-Oriented Tracking of Chemicals; Apparatus for Cold, Pressurized Biogeochemical Experiments; Growing B Lymphocytes in a Three-Dimensional Culture System; Tissue-like 3D Assemblies of Human Broncho-Epithelial Cells; Isolation of Resistance-Bearing Microorganisms; Oscillating Cell Culture Bioreactor; and Liquid Cooling/Warming Garment.

Source record↗
DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗
NASA NTRS1998

Deterministic and Probabilistic Creep and Creep Rupture Enhancement to CARES/Creep: Multiaxial Creep Life Prediction of Ceramic Structures Using Continuum Damage Mechanics and the Finite Element Method

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep ripture criterion However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of stress, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of this methodology and the CARES/Creep program.

Jadaan, Osama M.↗
NASA NTRS2000

A Probabilistic Technique for Improving the Mid-Swath Wind Direction Accuracy of Scanning Pencil Beam Scatterometers

The SeaWinds on QuikSCAT scatterometer is a device developed by NASA JPL to measure the speed and direction of ocean surface winds. Simulations performed in order to determine the expected performance of the instrument prior to its launch have indicated that the accuracy of the retrieved wind vectors varies across the swath. In particular the mid-swath accuracy is worse than that of the rest of the swath. This behavior is a general characteristic of scanning pencil beam scatterometers. For SeaWinds, the accuracy of the rest of the swath, and the size of the swath are such that the instrument meets its science requirements despite mid-swath shortcomings. However, by understanding the problem at mid-swath, we can improve the performance there as well, yielding even better coverage and accuracy than was originally intended. The mid-swath performance degradation is due to suboptimal viewing geometry. In particular mid-swath measurements contains measurements from two azimuths, roughly 180 degrees apart. With the standard wind retrieval technique, mid-swath root mean square (RMS) wind direction errors are approximately 30 degrees for low wind speeds (3 - 5.5 m/s) and 20 degrees for moderate to high wind speeds (5.5 - 30 m/s). We discuss the underlying causes of this phenomenon in detail and propose a modification to the wind retrieval technique in order to improve mid-swath performance. By estimating the range of likely wind directions for each measurement cell, one can optimally apply information from neighboring cells in order to reduce random wind direction errors without significantly degrading the resolution of the resultant wind field. In this manner we are able to achieve mid-swath RMS wind direction errors as low as 15 degrees for low winds and 10 degrees for moderate to high winds, while at the same time preserving high resolution structures such as cyclones and fronts. Since our results are based on simulated data, we also outline a procedure for making use of real data to optimize the technique after launch.

Stiles, Bryan↗
NASA NTRS1994

The Impact Hazard

The Earth has been subject to hypervelocity impacts from comets and asteroids since its formation, and such impacts have played an important role in the evolution of life on our planet. We now recognize not only the historical role of impacts, but the contemporary hazard posed by such events. In the absence of a complete census of potentially threatening Earth-crossing asteroids or comets (called collectively Near Earth Objects, or NEOs), or even of a comprehensive cur-rent search program to identify NEOs, we can consider the hazard only from a probabilistic perspective. We know the steep power-law relationship between NEO numbers and size, with many more small bodies than large ones. We also know that few objects less than about 50 m in diameter (with kinetic energy near 10 megatons) penetrate the atmosphere and are capable of doing surface damage. But there is a spectrum of possible impact hazards associated with objects from this 10-megaton threshold all the way up to NEOs 5 km or larger in diameter, which are capable of inflicting severe damage on the environment, leading to mass extinction's of species. Detailed analysis has shown that, in general, the larger the object the greater the hazard, even when allowance is made for the infrequency of large impacts. Most of the danger to human life is associated with impacts by objects roughly 2 km or larger (energy greater than 1 million megatons), which can inject sufficient submicrometer dust into the atmosphere to produce a severe short-term global cooling with subsequent loss of crops, leading to starvation. Hazard estimates suggest that the chance of such an event occurring during a human lifetime is about 1:5000, and the global probability of death from such impacts is of the order of 1:20000, values that can be compared with risks associated with other natural hazards such as earthquakes, volcanic eruptions, and severe storms. However, the impact hazard differs from the others in that it can be largely prevented by a comprehensive survey for threatening objects and the application of technological solutions to deflect or destroy objects that are found to have orbits that will lead to collision with the Earth.

Morrison, David↗