Search NASA⌕ Search

SEARCH · Search NASA

Results for “priority effects”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗
DOE OSTI2020

General Failure Modes and Effects Analysis for Accelerator and Detector Magnet Design at JLab

The aim of this article is to develop a risk management procedure, which could be applied to the magnet design process, for both superconducting and normal magnets at the Jefferson Laboratory (JLab). This procedure allowed us to identify the key risks at each of the critical phases of design and propose procedures, tests, and checks to mitigate each risk. In this article, we present a qualitative and quantitative risk management procedure commonly referred to a “failure modes and effects analysis.” As part of this procedure, we calculated a risk priority number (RPN) for each activity of the process, identified the most critical activities and proposed mitigation activities, which in turn resulted in a revised RPN. Additionally, another benefit of this procedure was the identification of appropriate “control and hold” points within the design process, which allowed one to review and approve a particular outcome before proceeding to the next sequential activity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Applying Social Science Methods to Assess and Improve Program Outcomes: A Case Study on the Gap Region Outreach Project

This paper outlines a replicable framework for assessing gaps, reach, and the impact of technical assistance (TA) programs, using the Energy to Communities (E2C) Gap Region Outreach Project as a case study. By applying qualitative social science methods, this framework provides tools for effectively engaging with underrepresented regions, identifying barriers to participation, and tailoring solutions to local needs. The study highlights the importance of leveraging stakeholder insights to address disparities in program engagement and participation, offering actionable recommendations to enhance program responsiveness and optimize resource allocation. This approach serves as a guide for practitioners seeking to expand the reach and effectiveness of federally funded TA programs while ensuring alignment with community priorities and capacity needs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Energy Technology Innovation Partnership Project [Slides]

This presentation introduces the Energy Technology Innovation Partnership Project (ETIPP) and outlines proposed technical assistance to support St. Vincent's House in developing a resilient community hub in Galveston, Texas. The project explores opportunities for on-site energy solutions to ensure continuity of critical services during coastal hazards and grid disruptions. The session aims to gather stakeholder input to refine priorities and inform next steps for resilient, reliable, and cost-effective energy strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

The Mitigation Hierarchy

The mitigation hierarchy is a widely used framework to inform conservation decisions. The hierarchy offers a structured set of steps for how projects can lessen negative impacts or lead to an increase in biodiversity. In its simplest form, the mitigation hierarchy includes three stages: (1) avoid creating impacts from the outset, (2) minimize the impacts that cannot be avoided, and (3) compensate for or offset the impacts that cannot be minimized. Proper application of the hierarchy should decrease impacts of the project over time, such that most of the impact is alleviated through avoidance, leaving a modest amount remaining to minimize, and only a residual to compensate. In practice, avoidance should be prioritized and can be a cost-effective means of mitigation. Whereas compensation should be considered the lowest priority and should only be applied in situations in which the previous mitigation steps were unable to fully alleviate undesirable impacts.

biodiversity↗
DOE OSTI2023

La Jerarquia de Mitigacion (Spanish)

The mitigation hierarchy is a widely used framework to inform conservation decisions. The hierarchy offers a structured set of steps for how projects can lessen negative impacts or lead to an increase in biodiversity. In its simplest form, the mitigation hierarchy includes three stages: (1) avoid creating impacts from the outset, (2) minimize the impacts that cannot be avoided, and (3) compensate for or offset the impacts that cannot be minimized. Proper application of the hierarchy should decrease impacts of the project over time, such that most of the impact is alleviated through avoidance, leaving a modest amount remaining to minimize, and only a residual to compensate. In practice, avoidance should be prioritized and can be a cost-effective means of mitigation. Whereas compensation should be considered the lowest priority and should only be applied in situations in which the previous mitigation steps were unable to fully alleviate undesirable impacts. This is the Spanish translation of NREL/FS-5000-85363, "The Mitigation Hierarchy."

biodiversity↗
DOE OSTI2020

Applying cumulative effects to strategically advance large-scale ecosystem restoration

Programs restoring large terrestrial-aquatic ecosystems are expected to increase in area and number over the next decade. Factors ensuring long-term effectiveness at the program scale differ from those at the individual restoration project scale, necessitating a new synthesis. Here we contextualize hydrological, geomorphological, and biological effects of large-scale ecosystem restoration activities within a cumulative-effects paradigm. Evidence of eight modes of cumulative effects benefiting species and ecosystems was elucidated by reviewing restoration efforts in the greater Florida Everglades, Gulf Coast, lower Columbia River and estuary, Puget Sound estuary, Missouri River, northeastern coastal states, San Francisco Bay and Sacramento Delta. Additive and nonlinear cumulative effects of interacting restoration projects propagated across landscape and regional geographic scales, and throughout trophic levels, affecting population structures. Applying a cumulative-effects paradigm to planning, implementing, and evaluating large-scale restoration will avoid countervailing effects and capitalize on positive feedback, advancing evidence-based programs to recover priority species and ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of anisotropy on TRISO fuel performance

Manufacturing of tristructural isotropic (TRISO) particles involves the deposition of pyrolytic carbon (PyC) and silicon carbide (SiC) layers using the fluidized bed chemical vapor deposition (CVD) process. The CVD process is known to generate polycrystalline layers with crystallographic textures, which imparts anisotropic thermophysical properties to the layers. Past studies have shown the risk for particle failure increases with an increase in anisotropy. The limit beyond which the anisotropy of PyC layers becomes unacceptable due to failure risk has been identified as a high-priority knowledge gap. This work presents a first systematic study on the effects of anisotropic thermal and mechanical properties on TRISO fuel performance. This computational study, performed using the fuel performance code BISON, investigates how the anisotropy in elasticity and thermal properties affect the stresses, temperature, and failure of a TRISO particle. The influence of other factors, such as operating temperature and particle geometry on the anisotropy effects, also has been analyzed. The studies utilize the recently published anisotropic elasticity and thermal behavior models for TRISO PyC and SiC layers implemented using tensors with full anisotropic capability. The spherical TRISO particles with anisotropic properties were found to have greater maximum tensile stress and significantly higher failure probability than the spherical particles with isotropic properties. In conclusion, the fuel performance predicted using these recently developed models was found to be comparable with the performance obtained using the historical models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Small-Molecule Catalysis by Transition-Metal Isocyanide Monomers, Clusters and Materials

DOE Catalysis Science Award DE-SC0018243 focused on the development and mechanistic understanding of small-molecule-activation and catalysis by monomeric and multinuclear transition-metal complexes supported by encumbering m-terphenyl isocyanide ligands. An additional goal of this award was the development of solid-state network materials featuring low-valent metal centers and ditopic m-terphenyl isocyanide ligands into functional platforms for catalytic chemical transformations. The emphasis on m-terphenyl isocyanides stems from a sustained effort by our research team that has shown these ancillary ligands to be particularly adept at stabilizing electronically or coordinately unsaturated metal centers. These metal centers in turn have been shown to effect catalytic and/or stoichiometric chemical transformations of substrates relevant to high-priority energy science goals. In addition, the stabilizing environment provided by these encumbering ligands has in several instances aided the detailed mechanistic elucidation of substrate activation process and/or have enabled important electronic structure insights to be uncovered.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-Burnup Spent Fuel Data Project: Sister Rod Final Phase II Test Plan

The Sibling Pin test campaign is a Department of Energy (DOE) research activity within the Spent Fuel and Waste Science and Technology (SFWST) program that is tasked with characterization of high burnup (HBU) fuel in support of the High Burnup Spent Fuel Data Project. Of the 25 fuel rods in the Sibling Pin inventory, approximately 9 rod lengths have been consumed during the first phase (Phase I) of the test campaign leaving approximately 16 rod lengths for the second phase (Phase II) of testing. This plan outlines the Phase II testing and the motivations for performing these tests. Priorities for Phase II testing are based on previously identified knowledge gaps, lessons-learned from Phase I work, the original objectives of the High Burnup Spent Fuel Data Project and the Sibling Pin test campaign, and input from external stakeholders. The priorities for Phase II testing are to obtain data to characterize the effects of annealing on cladding mechanical properties and fuel rod performance, to quantify the creep behavior of cladding materials and fuel rods and the effects of creep deformations on the performance of cladding and fuel rods, and to gather data to support the final closure of the hydride reorientation and radial hydride induced embrittlement gap for HBU fuel rods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

2020 State of the Science Report, Chapter 14: Summary and Path Forward

The 2020 State of the Science report collates and presents the current understanding of interactions between marine renewable energy (MRE) systems and the marine environment, with an emphasis on their effects on marine animals, habitats, and oceanographic systems, using publicly available information. The report places this information in context through lessons learned from research studies in the laboratory and in the field, modeling simulations, and deployments; monitoring around demonstration, pilot, and small commercial MRE projects; and identifies gaps in knowledge and makes recommendations for filling those gaps. In addition, strategies for moving toward a consistent and effective consenting or permitting (hereafter consenting) process and management of the potential effects of MRE development are highlighted. The status and recommendations from each of the priority interactions between MRE devices and the environment are summarized here, and the management strategies for facilitating development are discussed. Finally, a path forward toward commercial MRE development is explored. https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-14-summary-path-forward

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Large ecosystem-scale effects of restoration fail to mitigate impacts of land-use legacies in longleaf pine savannas

Ecological restoration is a global priority, with potential to reverse biodiversity declines and promote ecosystem functioning. Yet, successful restoration is challenged by lingering legacies of past land-use activities, which are pervasive on lands available for restoration. Although legacies can persist for centuries following cessation of human land uses such as agriculture, we currently lack understanding of how land-use legacies affect entire ecosystems, how they influence restoration outcomes, or whether restoration can mitigate legacy effects. Using a large-scale experiment, we evaluated how restoration by tree thinning and land-use legacies from prior cultivation and subsequent conversion to pine plantations affect fire-suppressed longleaf pine savannas. In this work, we evaluated 45 ecological properties across four categories: 1) abiotic attributes, 2) organism abundances, 3) species diversity, and 4) species interactions. The effects of restoration and land-use legacies were pervasive, shaping all categories of properties, with restoration effects roughly twice the magnitude of legacy effects. Restoration effects were of comparable magnitude in savannas with and without a history of intensive human land use; however, restoration did not mitigate numerous legacy effects present prior to restoration. As a result, savannas with a history of intensive human land use supported altered properties, especially related to soils, even after restoration. The signature of past human land-use activities can be remarkably persistent in the face of intensive restoration, influencing the outcome of restoration across diverse ecological properties. Understanding and mitigating land-use legacies will maximize the potential to restore degraded ecosystems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗
DOE OSTI2023

Setting Priorities for Photovoltaic Reliability Research Using Criticality Analysis

A forward-looking research opportunity number (RON) is defined for photovoltaic reliability researchers. The RON enables researchers to prioritize their efforts toward the highest impact. For a given degradation mode, the RON is based on three factors: the effect on levelized cost of electricity, the susceptibility of future module products, and the maturity of accelerated tests that can detect and quantify the mode. Reporting bias is avoided because the RON does not rely on polls. The RON is derived for three example cases: light and elevated temperature degradation, backsheet cracking, and antireflective coating abrasion. Finally, these examples demonstrate that targeted research has reduced the risk for these modes over the last several years.

14 SOLAR ENERGY↗
DOE OSTI2022

Demand Response Analysis for Different Residential Personas in a Comfort-Driven Behavioral Context

Low demand response (DR) participation and high program drop-out rates continue to impede DR goals that could save up to $13 billion in annual grid expansion and electricity demand costs. Yet, the literature lacks a thorough understanding of how different residential customer segments enrolled in DR programs respond to utility signals in view of occupant comfort considerations. The objective of this study is to gain a clear understanding of the effects of four different customer personas on residential DR. Given current data limitations, this work developed an array of hypothetical personas with varied priorities, activity levels, and comfort thresholds based on demographic variables that have been found in previous studies to influence energy consumption. A BEopt DR model for a reference residential single-family building located in Colorado was built to isolate the effect of differences in buildings or climate. The results provide useful evidence on how persona-comfort differences lead to significant deviations in DR goals (especially peak demand reduction), ranging from 0.1% to 20%. This work presents a novel framework representing comfort preferences in DR models. The data generated, albeit synthetic, and the results could inform DR program design considerations of how different people respond to different comfort priorities.

BEopt↗
DOE OSTI2022

R&D Towards CUPID, a Tonne-Scale Bolometric 0νββ Experiment (Collaborative Proposal)

As endorsed by the 2015 Long Range Plan for Nuclear Science, development of the ton-scale 0νββ experiment with the sensitivity to the effective neutrino mass at the level of 15 meV is one of the highest priorities for the nuclear physics. Bolometric detector based on CUORE design is very well matched to this goal. We have assembled a Collaboration to develop CUPID, a next-generation bolometric 0νββ detector based on CUORE experience and design, but improving upon CUORE sensitivity by more than an order of magnitude.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

CCUS Perspectives: Assessing Historical Contexts, Current Realities, and Future Prospects

CCUS technologies are crucial solutions for mitigating climate change by reducing CO2 emissions from industrial operations and energy sectors. This review critically examines the current state of CCUS technologies, and highlights advancements, challenges, regulatory frameworks, and future directions. It comprehensively analyzes carbon capture methods, such as pre-combustion, post-combustion, and oxy-fuel combustion capture, while comparing their efficiencies and limitations. The review also explores carbon utilization techniques, such as direct and indirect utilization, emphasizing their potential applications and technological constraints. Additionally, it assesses various carbon storage methods, focusing on geological, ocean, and mineralization storage, and discusses their capacity, feasibility, and environmental implications. The study reviews the policy and regulatory frameworks, economic viability, market trends, and environmental sustainability of CCUS. By identifying research gaps and recommending future research priorities, this review aims to guide the development of more efficient/effective, and cost-effective CCUS technology, ensuring their role in a sustaining low-carbon future. This review provides a forward-looking perspective, a critical and interdisciplinary analysis that assesses the current state of CCUS technologies, and further provides a roadmap for future development.

Energy & Fuels↗