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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.

Nguyen, Nhan T.↗
NASA NTRS2009

Brazed Joints Design and Allowables: Discuss Margins of Safety in Critical Brazed Structures

This slide presentation tutorial discusses margins of safety in critical brazed structures. It reviews: (1) the present situation (2) definition of strength (3) margins of safety (4) design allowables (5) mechanical testing (6) failure criteria (7) design flowchart (8) braze gap (9) residual stresses and (10) delayed failures. This presentation addresses the strength of the brazed joints, the methods of mechanical testing, and our ability to evaluate the margins of safety of the brazed joints as it applies to the design of critical and expensive brazed assemblies.

FLom, Yury↗
NASA NTRS2010

Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

Nguyen, Nhan T.↗
NASA NTRS2012

Marginally Stable Nuclear Burning

Thermonuclear X-ray bursts result from unstable nuclear burning of the material accreted on neutron stars in some low mass X-ray binaries (LMXBs). Theory predicts that close to the boundary of stability oscillatory burning can occur. This marginally stable regime has so far been identified in only a small number of sources. We present Rossi X-ray Timing Explorer (RXTE) observations of the bursting, high- inclination LMXB 4U 1323-619 that reveal for the first time in this source the signature of marginally stable burning. The source was observed during two successive RXTE orbits for approximately 5 ksec beginning at 10:14:01 UTC on March 28, 2011. Significant mHz quasi- periodic oscillations (QPO) at a frequency of 8.1 mHz are detected for approximately 1600 s from the beginning of the observation until the occurrence of a thermonuclear X-ray burst at 10:42:22 UTC. The mHz oscillations are not detected following the X-ray burst. The average fractional rms amplitude of the mHz QPOs is 6.4% (3 - 20 keV), and the amplitude increases to about 8% below 10 keV.This phenomenology is strikingly similar to that seen in the LMXB 4U 1636-53. Indeed, the frequency of the mHz QPOs in 4U 1323-619 prior to the X-ray burst is very similar to the transition frequency between mHz QPO and bursts found in 4U 1636-53 by Altamirano et al. (2008). These results strongly suggest that the observed QPOs in 4U 1323-619 are, like those in 4U 1636-53, due to marginally stable nuclear burning. We also explore the dependence of the energy spectrum on the oscillation phase, and we place the present observations within the context of the spectral evolution of the accretion-powered flux from the source.

Strohmayer, Tod E.↗
NASA NTRS2012

Model-Based Systems Engineering Approach to Managing Mass Margin

When designing a flight system from concept through implementation, one of the fundamental systems engineering tasks ismanaging the mass margin and a mass equipment list (MEL) of the flight system. While generating a MEL and computing a mass margin is conceptually a trivial task, maintaining consistent and correct MELs and mass margins can be challenging due to the current practices of maintaining duplicate information in various forms, such as diagrams and tables, and in various media, such as files and emails. We have overcome this challenge through a model-based systems engineering (MBSE) approach within which we allow only a single-source-of-truth. In this paper we describe the modeling patternsused to capture the single-source-of-truth and the views that have been developed for the Europa Habitability Mission (EHM) project, a mission concept study, at the Jet Propulsion Laboratory (JPL).

cloud comu↗
DOE OSTI2022

Biomass Production and Nutrient Removal by Perennial Energy Grasses Produced on a Wet Marginal Land

Growing dedicated bioenergy crops on marginal land can provide beneficial outcomes including biomass production and energy, resource management, and ecosystem services. We investigated the effects of harvest timing (peak standing crop [PEAK] or after killing frost [KF]) and nitrogen (N) fertilizer rates (0, 56, and 112 kg N ha -1 ) on yield, nutrient concentrations, and nutrient removal rates of perennial grasses on a wet marginal land. We evaluated three monocultures, including switchgrass (Panicum virgatum L., SW), Miscanthus x giganteus (MG), prairie cordgrass (Spartina pectinata Link, PCG), and a polyculture mixture of big bluestem (Andropogon gerardii Vitman), Indiangrass (Sorghastrum nutans (L.) Nash), and sideoats grama (Bouteloua curtipendula Torr., MIX). Increasing the application of N did correlate with increased biomass, concentration, and subsequent removal of nutrients across almost all treatment combinations. In all grass treatments except MG, PEAK harvesting increased yield and nutrient removal. At PEAK harvest, switchgrass is ideal for optimizing both biomass production and nutrient removal. While our results also suggest short-term plasticity for farmers when selecting harvest timing for optimal nutrient removal, KF harvest is recommended to ensure long-term stand longevity and adequate nutrient removal. If the KF harvest is adopted, MG would be the ideal option for optimizing biomass yield potential. Additionally, we found that the yield of polyculture did not vary much with harvest timing, suggesting better yield stability. Future studies should give consideration for long-term evaluation of polyculture mixtures to assess their biomass yields and nutrient removal capacities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development and application of marginal likelihood optimization for integral parameter adjustment

When adjusting nuclear data with integral experiments, care must be taken that spurious adjustments are not made by assimilating poorly characterized integral parameters. If there are unaccounted for biases or poorly estimated uncertainties in the calculated and experimental values for an integral parameter, the Bayesian data assimilation may adjust the nuclear data in a manner that does not reflect the physics of the integral parameter. To identify and lessen the impact of these inconsistent integral parameters, in this study we present a Marginal Likelihood Optimization algorithm. In a data-driven way, the marginalized likelihood is used to modulate hyperparameter terms that decrease the influence of inconsistent integral parameters on the adjustment. The advantage of this approach over other methods in the literature is that it incorporates correlation information and does not remove an integral parameter from the adjustment. Herein, we present and motivate the algorithm, and apply it to an integral data assimilation case study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A tri-level distribution locational marginal price-based demand response framework

Here, in this paper, we propose a tri-level, nested, two-stage price-based demand response (PBDR) framework that considers distribution locational marginal price (DLMP) as DR enabler between load-serving entities (LSE), demand response providers (DRPs), and customers in the day-ahead distribution market. It enables LSE and customer interactions by using multiple DRPs, positioned in-between, and independently optimizes their objectives. The problem is formulated using linear power flow with approximated power losses and its application in DLMP as DR pricing. The tri-level problem is solved using a nested reformulation & decomposition (R&D) method and tested on the real Indian-108 bus distribution system under various dynamic pricings. Further, the temporal–spatial variations in DLMPs are assessed using fairness criteria. Numerical analyses demonstrate that DLMP applications can effectively improve economic efficiency, and transparency in DR programs valuation with a favorable fairness margin. The results show that DLMP as DR pricing signal induces (0-2) % variation in DLMP for DR participation up to 10 %. Further, it gives over 90 % fairness over temporal–spatial variation for all the customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Non -degenerate marginal-likelihood calibration with application to quantum characterization

Here, we propose a marginal likelihood strategy within the Kennedy-O’Hagan (KOH) Bayesian framework, where a Gaussian process (GP) models the discrepancy between a physical system and its simulator. Our approach introduces a novel marginalized likelihood by integrating out the degenerate eigenspace of the covariance matrix, rather than approximating the original likelihood. Unlike approximation methods that compromise accuracy for computational efficiency, our method defines an exact likelihood—distinct from the original but preserving all relevant information. This formulation achieves computational efficiency and stability, even for large datasets where the covariance matrix nears degeneracy. Applied to the characterization of a superconducting quantum device at Lawrence Livermore National Laboratory, the approach enhances the predictive accuracy of the Lindblad master equations for modeling Ramsey measurement data by effectively quantifying uncertainties consistent with the quantum data.

general physics↗
DOE OSTI2022

Boosting climate change mitigation potential of perennial lignocellulosic crops grown on marginal lands

Nitrogen fertilizer (N F ) is a major uncertainty surrounding the greenhouse gas (GHG) emissions of lignocellulosic biofuels. NF enhances agronomic yields and soil C inputs via plant litters, but results in soil organic carbon (SOC) decomposition, soil N 2 O fluxes, and a large fossil energy footprint. Thus, whether NF is beneficial or detrimental to the GHG mitigation of biofuels is unknown. Here, we show the potential GHG mitigation of fertilizing switchgrass (Panicum virgatum) at the NF rate that minimizes net GHG emissions across 7.1 million ha of marginal lands in the Midwest US, with long-term production advantages surpassing emitted GHG by 0.66 Mg CO 2 e ha –1 yr –1 on the aggregate. Marginal lands limited by poor N fertility could see a much greater benefit, but not SOC-rich lands, limited by low precipitation, or short growing seasons. The objectives of maximizing yield and minimizing GHG overlap only in a few environments, suggesting that maximum yield will reduce the climate benefit of cellulosic biofuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Diminishing marginal effect in estimating the dissolved organic carbon export from a watershed

Dissolved organic carbon (DOC) can be initially moved from soils to inland waters with surface runoff, and then mineralized, buried, or eventually delivered to the coastal ocean. This land-to-ocean phase of the DOC flux must be accounted for to comprehensively understand the global carbon cycle. To estimate the terrestrial-aquatic DOC leaching, calculating the product of the riverine DOC concentration and the corresponding river discharge measured at the watershed outlet is a common method. However, it is challenging to frequently and exactly record riverine DOC concentrations, thus the relationship between DOC concentrations and discharges (C-Q relationship) are established and used to interpolate the time-series of DOC concentrations. We found that the widely used time-dependent and time-independent C-Q regression models are weak in representing their altered relationship when the discharge is extremely high, which was named as diminishing marginal effect. In this study, we evaluated the performance of two C-Q regression models and discussed possible reasons for the diminishing marginal effect. We suggest that repeated and long-term measurements of the DOC concentration are required to adequately analyze their relationships, especially during the early spring and seasons with heavy precipitations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate-Mediated Changes to Linked Terrestrial and Marine Ecosystems across the Northeast Pacific Coastal Temperate Rainforest Margin

Coastal margins are important areas of materials flux that link terrestrial and marine ecosystems. Consequently, climate-mediated changes to coastal terrestrial ecosystems and hydrologic regimes have high potential to influence nearshore ocean chemistry and food web dynamics. Research from tightly coupled, high-flux coastal ecosystems can advance understanding of terrestrial–marine links and climate sensitivities more generally. In the present article, we use the northeast Pacific coastal temperate rainforest as a model system to evaluate such links. We focus on key above- and belowground production and hydrological transport processes that control the land-to-ocean flow of materials and their influence on nearshore marine ecosystems. We evaluate how these connections may be altered by global climate change and we identify knowledge gaps in our understanding of the source, transport, and fate of terrestrial materials along this coastal margin. Finally, we propose five priority research themes in this region that are relevant for understanding coastal ecosystem links more broadly.

temperate rainforest, coastal margin, climate chan↗
DOE OSTI2020

A Data-Driven Nonparametric Approach for Probabilistic Load-Margin Assessment Considering Wind Power Penetration

A modern power system is characterized by an increasing penetration of wind power, which results in large uncertainties in its states. These uncertainties must be quantified properly; otherwise, the system security may be threatened. Facing this challenge, here we propose a cost-effective, data-driven approach to assessing a power system's load margin probabilistically. Using actual wind data, a kernel density estimator is applied to infer the nonparametric wind speed distributions, which are further merged into the framework of a vine copula. The latter enables us to simulate complex multivariate and highly dependent model inputs with a variety of bivariate copulae that precisely represent the tail dependence in the correlated samples. Furthermore, to reduce the prohibitive computational time of traditional Monte-Carlo simulations that process a large amount of samples, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model through a Bayesian-learning framework. To accelerate the convergence rate of this Bayesian algorithm, a truncated polynomial chaos surrogate, which serves as a highly efficient, parametric Bayesian prior, is developed. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. Results of simulations that are performed on several test systems reveal the impressive performance of the proposed method in the probabilistic load-margin assessment.

17 WIND ENERGY↗
DOE OSTI2024

Regulatory Treatment of Low Frequency External Events under a Risk-Informed Performance-Based Licensing Pathway: Enhanced SPRA-based Margins Assessment

Recently there has been development in the field of risk-informed performance-based (RIPB) design and licensing approaches, which leverage detailed risk assessments and performance-based metrics to allow flexibility and innovation. These RIPB approaches include the probabilistic treatment of external hazards, including low frequency events that are beyond the design basis. However, there are certain challenges that have been identified to the probabilistic treatment of low frequency external events, primarily due to uncertainty in the hazard curve and the associated plant response to rare, severe events. The NRC is currently developing 10 CFR Part 53 that would establish a technology-inclusive regulatory framework for use by applicants for new commercial advanced nuclear reactors. By examining the regulatory safety criteria contained within draft 10 CFR Part 53 and associated draft RIPB seismic design guidance, potential challenges were identified in demonstrating satisfaction of the safety criteria for low frequency external events, with specific difficulties associated with demonstrating compliance with the quantitative health objectives (QHOs). Non-LWRs are expected to utilize the direct calculation of offsite consequence, rather than use surrogates, for comparison to the QHOs, which can be particularly challenging as the previously identified uncertainties are compounded by uncertainties in the response of the neighboring population. The central recommendation from this effort is that it is necessary to develop an approach for demonstrating compliance with the safety criteria in draft Part 53 that addresses the key challenges while providing flexibility to applicants. This paper summarizes key findings, establishes a series of high-level goals, and reviews a newly developed approach to address the major challenges associated with assessing compliance with QHOs, with avenues to demonstrate compliance based on either the estimated consequence or the available margin to event occurrence, while also building on existing experience of seismic margins assessments. The paper also provides examples to demonstrate the application of the approach, as well as recommendations and potential future work.

external hazards↗
DOE OSTI2021

Development and Application of a Data-Driven Methodology for Validation of Risk-Informed Safety Margin Characterization Models

The document is the Final Technical Progress Report for the Nuclear Energy University Program’s Integrated Research Project (IRP) on “Development and Application of a Data-Driven Methodology for Validation of Risk-Informed Safety Margin Characterization Models” that supports the LWR Sustainability Program’s RISMC R&D Pathway. The project goal is to develop and demonstrate a data-driven methodology for validation of advanced computer models used in nuclear power plant safety analysis. Specifically, the advanced computer models are those in the toolkit developed to support risk-informed safety margin characterization (RISMC), an integrated deterministic/probabilistic safety analysis methodology developed in the Department of Energy’s Light Water Reactor Sustainability (LWR-S) program. The report reflects the progress made towards the project’s stated goal by contributions by researchers and graduate students from universities, with support from researchers from national laboratories and industry companies. The project organization, effort coordination and technical implementation are summarized, followed by discussion of main findings, issues, and path forward. Selected chapters provide a more detailed description of tasks, approaches and respective findings and recommendations. Noteworthy are contributions that serve as guidelines for methodology development. It is also noted that this report is complemented by other milestone reports (as stand-alone deliverables) that provide detailed discussion of the technical developments. The project results have been documented in a number (12) dissertations and these, 50+ peer-reviewed publications in technical journals and conference proceedings.

42 ENGINEERING↗
DOE OSTI2024

Evaluating Compliance Inspection Data to Understand Emissions from Marginal Conventional Oil & Gas Wells in New York State

It is estimated that over half (~66%) of active oil and gas wells are marginally productive, producing less than 15 barrels of oil equivalent per day. This presentation showcases an evaluation of New York State compliance inspection reports and discusses the current capabilities of machine learning to identify high-risk MCWs that could be targeted during methane emission reduction efforts and future model deployments. Findings are valuable to the New York Department of Environmental Conservation and other state oil and gas regulatory agencies seeking to prioritize the spending of Methane Emission Reduction Program funds to plug marginal conventional wells with emissions.

compliance inspection data↗
DOE OSTI2021

Deep Learning-Based Adaptive Remedial Action Scheme with Security Margin for Renewable-Dominated Power Grids

The Remedial Action Scheme (RAS) is designed to take corrective actions after detecting predetermined conditions to maintain system transient stability in large interconnected power grids. However, since RAS is usually designed based on a few selected typical operating conditions, it is not optimal in operating conditions that are not considered in the offline design, especially under frequently and dramatically varying operating conditions due to the increasing integration of intermittent renewables. The deep learning-based RAS is proposed to enhance the adaptivity of RAS to varying operating conditions. During the training, a customized loss function is developed to penalize the negative loss and suggest corrective actions with a security margin to avoid triggering under-frequency and over-frequency relays. Simulation results of the reduced United States Western Interconnection system model demonstrate that the proposed deep learning–based RAS can provide optimal corrective actions for unseen operating conditions while maintaining a sufficient security margin.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

Review and Assessment of JPL's Thermal Margins

JPL has captured its experience from over four decades of robotic space exploration into a set of design rules. These rules have gradually changed into explicit requirements and are now formally implemented and verified. Over an extended period of time, the initial understanding of intent and rationale for these rules has faded and rules are now frequently applied without further consideration. In the meantime, mission classes and their associated risk postures have evolved, coupled with resource constraints and growing design diversity, bringing into question the current "one size fits all" thermal margin approach. This paper offers a systematic review of the heat flow path from an electronic junction to the eventual heat rejection to space. This includes the identification of different regimes along this path and the associated requirements. The work resulted in a renewed understanding of the intent behind JPL requirements for hot thermal margins and a framework for relevant considerations, which in turn enables better decision making when a deviation to these requirements is considered.

derating↗