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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Probability Distribution of von Mises Stress in the Presence of Pre-Load

Random vibration under preload is important in multiple endeavors, including those involving launch and re-entry. There are some methods in the literature to begin to address this problem, but there is nothing that accommodates the existence of preloads and the necessity of making probabilistic statements about the stress levels likely to be encountered. An approach to achieve to this goal is presented along with several simple illustrations.

Segalman, Daniel Joseph↗
DOE OSTI2017

Using Probability of Exceedance to Compare the Resource Risk of Renewable and Gas-Fired Generation

Of the myriad risks surrounding long-term investments in power plants, resource risk is one of the most difficult to mitigate, and is also perhaps the risk that most-clearly distinguishes renewable generation from natural gas-fired generation. For renewable generators like wind and solar projects, resource risk manifests as a quantity risk—i.e., the risk that the quantity of wind and insolation will be less than expected.i For gas-fired generators (i.e., a combined-cycle gas turbine or “CCGT”), resource risk manifests primarily as a price risk—i.e., the risk that natural gas will cost more than expected. Most often, resource risk—and natural gas price risk in particular—falls disproportionately on utility ratepayers, who are typically not well-equipped to manage this risk. As such, it is incumbent upon utilities, regulators, and policymakers to ensure that resource risk is taken into consideration when making or approving resource decisions, or enacting policies that influence the development of the electricity sector more broadly.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Probability Distributions for Effective Permeability of Potentially Leaking Wells at CO 2 Sequestration Sites

Wells with defects originating from either poor completions or subsequent damage arising from chemical, thermal and/or mechanical stresses provide potential pathways for leakage of carbon dioxide (CO 2 ) and brine from a CO 2 sequestration site. This report provides a methodology for analyzing data on the frequency of occurrence of defective wells and the effective permeability of the damaged wells. The results include bimodal, log-normal distributions of the effective permeability of wells in addition to other distributions designed to provide a measure of the likelihood of encountering a leaking well in a CO 2 storage project.

58 GEOSCIENCES↗
DOE OSTI2018

PrEP: Probability of Encounter between Ports of Entry A case study of the US-Mexico border

PrEP aims to explore the field of psychophysics as it applies to the movement of adversaries across international borders. This test experiment uses the US-Mexico border as a case study – beginning with certain assumptions regarding the adversary, the model utilizes environmental and population data to estimate risk perception, and predict routes that a smuggler may take. Additionally, I analyze the impact that destination-based attractive forces may have on agent movement. I found that these attractive forces may improve the validity of the model if they carry less influence that the repulsive forces.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The goal of this project is to develop statistical methods and tools that can be used to rigorously calculate achieved DPs on individual material strata and then aggregate these to the facility and state levels. In particular, this project is evaluating the utility of stochastic ("Monte Carlo") methods as a potentially more powerful and flexible option to the analytical solutions traditionally employed by IAEA statisticians.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Relationship Between the Marginal Probability of Failure for a CPP Test and the Recommended Corrosion Control Requirements for Hanford Double Shell Waste Tanks

The Hanford Site in Washington State currently stores millions of gallons of radioactive waste in underground, carbon steel, double shell tanks (DSTs) that were constructed between 1968 and 1986. A chemistry control and monitoring program has been established mitigate corrosion in order to extend the service life for the DSTs. The current waste temperatures in the DSTs are at historical lows (i.e., typically less than 50 °C). The previous chemistry control requirements were determined for conditions at temperatures significantly higher. SRNL undertook a statistically based investigation of the role of nitrate and halide ion (i.e., chloride and fluoride) induced pitting corrosion. The objective was to develop a comprehensive waste chemistry envelope for the simultaneous minimization of the pitting and SCC risks caused by halide and nitrate ions at the lower temperature conditions. On the basis of these tests, new chemistry control requirements were proposed and have since been implemented for pitting corrosion control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Using probability distribution function as a scaling approach to incorporate soil heterogeneity into biogeochemical models for greenhouse gas predictions (Final Technical Report)

The project investigated biogeochemical processes at terrestrial-aquatic interfaces (TAIs), focusing on soil microsite heterogeneity and its impact on greenhouse gas (GHG) fluxes. Using laboratory experiments, modeling, and data integration, researchers explored redox-driven microbial processes under fluctuating hydrological conditions. Key advancements included modifying the DAMM-GHG model to incorporateelectron acceptor availability and enhancing the AquaMEND model for improved microbial metabolism representation. Results highlighted microsite redox variability as a key driver of GHG fluxes, informing Earth system models. The project fostered interdisciplinary collaborations, student training, and the development of novel modeling frameworks to improve Earth'senergy budget.

54 ENVIRONMENTAL SCIENCES↗