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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Surface Texture of Macroplastic Pollution in Streams Alters the Physical Structure and Diversity of Biofilm Communities

ABSTRACT Biofilms can develop on nearly any surface, and in aquatic ecosystems they are essential components of biogeochemical cycles and food webs. Plastic waste in waterways is a new type of surface for biofilm colonisation. To analyse the influence of plastic pollution on the development and diversity of microbial freshwater biofilms that colonised them, we incubated 388 cm 2 veneers of high‐density polyethylene (HDPE) with two veneer textures, smooth and rough, and tulip tree wood ( Liriodendron tulipifera ), in three rural headwater streams at the Savannah River Site (Aiken, SC, USA). We collected biofilms from veneers after 14, 28 and 56 days of incubation and analysed 16S rRNA genes and biofilm properties. We found that plastic negatively affected species richness of biofilms compared with wood, but that evenness was greatest on rough textured HDPE. Beta diversity was primarily influenced by stream site. Beta diversity differed more between wood and plastic veneers than with plastic surface texture and became more different over time. Wood had nine times more biomass than rough HDPE and 40 times more biomass than smooth HDPE. Given the projected increase of macroplastic pollution in aquatic ecosystems, our findings emphasise the need to further understand its effects on biofilm characteristics.

Lopez Avila, Fabiola [Odum School of Ecology Unive↗
DOE OSTI2023

Organic preservation of vase‐shaped microfossils from the late Tonian Chuar Group, Grand Canyon, Arizona, USA

Abstract Vase‐shaped microfossils (VSMs) are found globally in middle Neoproterozoic (800–730 Ma) marine strata and represent the earliest evidence for testate (shell‐forming) amoebozoans. VSM tests are hypothesized to have been originally organic in life but are most commonly preserved as secondary mineralized casts and molds. A few reports, however, suggest possible organic preservation. Here, we test the hypothesis that VSMs from shales of the lower Walcott Member of the Chuar Group, Grand Canyon, Arizona, contain original organic material, as reported by B. Bloeser in her pioneering studies of Chuar VSMs. We identified VSMs from two thin section samples of Walcott Member black shales in transmitted light microscopy and used scanning electron microscopy to image VSMs. Carbonaceous material is found within the internal cavity of all VSM tests from both samples and is interpreted as bitumen mobilized from Walcott shales likely during the Cretaceous. Energy dispersive X‐ray spectroscopy (EDS) and wavelength dispersive X‐ray spectroscopy (WDS) reveal that VSM test walls contain mostly carbon, iron, and sulfur, while silica is present only in the surrounding matrix. Raman spectroscopy was used to compare the thermal maturity of carbonaceous material within the samples and indicated the presence of pyrite and jarosite within fossil material. X‐ray absorption spectroscopy revealed the presence of reduced organic sulfur species within the carbonaceous test walls, the carbonaceous material found within test cavities, and in the sedimentary matrix, suggesting that organic matter sulfurization occurred within the Walcott shales. Our suite of spectroscopic analyses reveals that Walcott VSM test walls are organic and sometimes secondarily pyritized (with the pyrite variably oxidized to jarosite). Both preservation modes can occur at a millimeter spatial scale within sample material, and at times even within a single specimen. We propose that sulfurization within the Walcott Shales promoted organic preservation, and furthermore, the ratio of iron to labile VSM organic material controlled the extent of pyrite replacement. Based on our evidence, we conclude that the VSMs are preserved with original organic test material, and speculate that organic VSMs may often go unrecognized, given their light‐colored, translucent appearance in transmitted light.

58 GEOSCIENCES↗
DOE OSTI2020

Microbial sulfate reduction and organic sulfur formation in sinking marine particles

Climate change is driving an expansion of marine oxygen-deficient zones, which may alter the global cycles of carbon, sulfur, nitrogen, and trace metals. Currently, however, we lack a full mechanistic understanding of how oxygen deficiency affects organic carbon cycling and burial. In this work, we show that cryptic microbial sulfate reduction occurs in sinking particles from the eastern tropical North Pacific oxygen-deficient zone and that some microbially produced sulfide reacts rapidly to form organic sulfur that is resistant to acid hydrolysis. Particle-hosted sulfurization could enhance carbon preservation in sediments underlying oxygen-deficient water columns and serve as a stabilizing feedback between expanding anoxic zones and atmospheric carbon dioxide. A similar mechanism may help explain more-extreme instances of organic carbon preservation associated with marine anoxia in Earth history.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The Effect of Diel Temperature and Light Cycles on the Growth of Nannochloropsis oculata in a Photobioreactor Matrix

A matrix of photobioreactors integrated with metabolic sensors was used to examine the combined impact of light and temperature variations on the growth and physiology of the biofuel candidate microalgal species Nannochloropsis oculata. The experiments were performed with algal cultures maintained at a constant 20 °C versus a °15 C to 25 °C diel temperature cycle, where light intensity also followed a diel cycle with a maximum irradiance of 1920 mmol photons m -2 s -1 . No differences in algal growth (Chlorophyll a) were found between the two environmental regimes; however, the metabolic processes responded differently throughout the day to the change in environmental conditions. The variable temperature treatment resulted in greater damage to photosystem II due to the combined effect of strong light and high temperature. Cellular functions responded differently to conditions before midday as opposed to the afternoon, leading to strong hysteresis in dissolved oxygen concentration, quantum yield of photosystem II and net photosynthesis. Overnight metabolism performed differently, probably as a result of the temperature impact on respiration. Our photobioreactor matrix has produced novel insights into the physiological response of Nannochloropsis oculata to simulated environmental conditions. This information can be used to predict the effectiveness of deploying Nannochloropsis oculata in similar field conditions for commercial biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2012

Assssment and Mapping of the Riverine Hydrokinetic Resource in the Continental United States

The U.S. Department of Energy (DOE) funded the Electric Power Research Institute and its collaborative partners, University of Alaska Anchorage, University of Alaska Fairbanks, and the National Renewable Energy Laboratory, to provide an assessment of the riverine hydrokinetic resource in the continental United States. The assessment benefited from input obtained during two workshops attended by individuals with relevant expertise and from a National Research Council panel commissioned by DOE to provide guidance to this and other concurrent, DOE-funded assessments of water based renewable energy.

13 HYDRO ENERGY↗
DOE OSTI2013

Abrasion Testing of Critical Components of Hydrokinetic Devices

The objective of the Abrasion Testing of Critical Components of Hydrokinetic Devices (Project) was to test critical components of hydrokinetic devices in waters with high levels of suspended sediment – information that is widely applicable to the hydrokinetic industry. Tidal and river sites in Alaska typically have high suspended sediment concentrations. High suspended sediment also occurs in major rivers and estuaries throughout the world and throughout high latitude locations where glacial inputs introduce silt into water bodies. In assessing the vulnerability of technology components to sediment induced abrasion, one of the greatest concerns is the impact that the sediment may have on device components such as bearings and seals, failures of which could lead to both efficiency loss and catastrophic system failures.

16 TIDAL AND WAVE POWER↗
DOE OSTI2015

A Research Roadmap for Computation-Based Human Reliability Analysis

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is often secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Risk-Informed External Hazards Analysis for Seismic and Flooding Phenomena for a Generic PWR

This report describes the activities performed during the FY2017 for the US-DOE Light Water Reactor Sustainability Risk-Informed Safety Margin Characterization (LWRS-RISMC), Industry Application #2. The scope of Industry Application #2 is to deliver a risk-informed external hazards safety analysis for a representative nuclear power plant. Following the advancements occurred during the previous FYs (toolkits identification, models development), FY2017 focused on: increasing the level of realism of the analysis; improving the tools and the coupling methodologies. In particular the following objectives were achieved: calculation of buildings pounding and their effects on components seismic fragility; development of a SAPHIRE code PRA models for 3-loops Westinghouse PWR; set-up of a methodology for performing static-dynamic PRA coupling between SAPHIRE and EMRALD codes; coupling RELAP5-3D/RAVEN for performing Best-Estimate Plus Uncertainty analysis and automatic limit surface search; and execute sample calculations for demonstrating the capabilities of the toolkit in performing a risk-informed external hazards safety analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Status Report on Modelling and Simulation Capabilities for Nuclear-Renewable Hybrid Energy Systems

This report summarizes the current status of the modeling and simulation capabilities developed for the economic assessment of Nuclear-Renewable Hybrid Energy Systems (N-R HES). The increasing penetration of variable renewables is altering the profile of the net demand, with which the other generators on the grid have to cope. N-R HES analyses are being conducted to determine the potential feasibility of mitigating the resultant volatility in the net electricity demand by adding industrial processes that utilize either thermal or electrical energy as stabilizing loads. This coordination of energy generators and users is proposed to mitigate the increase in electricity cost and cost volatility through the production of a saleable commodity. Overall, the financial performance of a system that is comprised of peaking units (i.e. gas turbine), baseload supply (i.e. nuclear power plant), and an industrial process (e.g. hydrogen plant) should be optimized under the constraint of satisfying an electricity demand profile with a certain level of variable renewable (wind) penetration. The optimization should entail both the sizing of the components/subsystems that comprise the system and the optimal dispatch strategy (output at any given moment in time from the different subsystems). Some of the capabilities here described have been reported separately in [1, 2, 3]. The purpose of this report is to provide an update on the improvement and extension of those capabilities and to illustrate their integrated application in the economic assessment of N-R HES.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

2018 Annual Site Environmental Report Summary

We are committed to act as stewards of our environment to achieve our mission in accordance with all applicable environmental requirements. We set continual improvement objectives and targets, measure and document our progress, and share our results with our workforce, sponsors, and public. We reduce our environmental risk through legacy cleanup, pollution prevention, and long-term sustainability programs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Acquire and Test IDAES Framework Components

The cooperation under the Grid Modernization Initiative and the Applied Energy Tri-Laboratory umbrellas requires mutual understanding of capabilities and a common effort to identify gaps existing in the available computational modeling and analysis tools. In this work, we report acquisition and testing of the National Energy Technology Laboratory’s Institute for the Design of Advanced Energy Systems (IDAES) framework, particularly including both electric power systems production cost model simulator Prescient as well as system optimization IDAES itself. Further, we consider the methods in which developments in Prescient and IDAES for grid-energy simulation and optimization may be included in the Framework for Optimization of ResourCes and Economics (FORCE) ecosystem that has been under collaborative development by Idaho National Laboratory, Argonne National Laboratory, and Oak Ridge National Laboratory. We propose two integration methods to introduce Prescient and IDAES into existing FORCE automated workflows. One integration involves using Prescient as a market reduced-order model and IDAES models similar to how existing Modelica models are used. The other integration involves wrapping the Prescient-IDAES dispatch optimization process with the stochastic capacity optimization workflow in FORCE.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Signal Decomposition for Intrusion Detection in Reliability Assessment in Cyber Resilience (Summary Report)

The complexity of assuring cyber resilience for physical process interactions in connected systems such as energy grids increases dramatically as the coupling between processes becomes more direct and responsive. An example of this growing complexity is provided by Integrated Energy Systems (IES), in which various processes such as nuclear heat generation and commodity production are being directly coupled for increased responsiveness to highly variable signals such as market pricing or electricity demand. As such, the potential attack surface of the coupled processes is larger than the two processes independently. Securing these complex systems requires two-fold monitoring: cybersecure monitoring for potential malicious incursion, and physics monitoring for system tampering. Physics monitoring includes analyzing the behavior of the signals within the system for anomalous behavior. This analysis has been shown to be insufficient if approached by only data-driven machine learning and artificial intelligence (MLAI) techniques or only low-level model comparison. Previous efforts at Purdue University suggested combining high-fidelity models with MLAI algorithms as a basis for a software tool for detecting anomalies in physical processes. This work built on that suggestion, developing an advanced library for signal decomposition and analysis using both MLAI and high-fidelity physics algorithms for greatly improved anomaly detection, especially false data injection. This software can be used as part of a secure imbedded intelligence (SEI) system designed under Consequence-driven Cyber-informed Engineering (CCE) for complex coupled systems. This library established a foundation for online and posteriori analysis of digital signals for the purpose of detecting potential malicious tampering in digital signals representing physical processes. Demonstrations carried out throughout the development highlight the effective use of characterization algorithms to detect signal perturbations, particularly triangle attack-style perturbations, in three wide-ranging applications: seismic monitoring, nuclear thermal hydraulics system simulation, and custom manufacturing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Full-scale Demonstration of Pressurized Water Reactor Core Design Optimization using Multi-Cycle Optimization Methodology

The U.S. nuclear sector encounters a difficulty in upholding essential safety standards while also securing economic viability for continued operation. Safety stands as a pivotal factor across all facets of operations within light-water reactor nuclear power plants. Achieving economic feasibility alongside safety can be facilitated through the utilization of a risk-informed framework, exemplified by the ongoing development within the Risk-Informed Systems Analysis Pathway under the auspices of the U.S. Department of Energy's LWRS Program. This initiative advocates for a diverse array of research and development endeavors aimed at optimizing both safety and economic efficacy within nuclear power plants, particularly pertinent as many plants contemplate second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: deploy methodologies and technologies that better represent safety margins and cost and safety factors and develop advanced applications that enable cost-effective plant operation. This report assesses the potential for resolving multi-cycle plant reload challenges through real-world scenarios utilizing the Plant ReLoad Optimization (PRLO) framework. This framework offers reactor core design developers analytic tools of reactor safety and fuel performance with the assistance of artificial intelligence (AI) to enhance core design solutions. Multi-objective genetic algorithm alongside acceleration techniques is explored as an enabling technology for improving fuel efficiency while upholding safety thresholds. The demonstration of multi-cycle core design optimization is performed. This report investigates the practical application of the PRLO platform in addressing real-world core design challenges, supporting AI efforts, and contrasting outcomes with those derived from heuristic or conventional algorithms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Chemical and Isotopic Evidence for Organic Matter Sulfurization in Redox Gradients Around Mangrove Roots

Coastal environments like mangrove forests are increasingly recognized as potential hotspots for organic carbon burial, giving them a crucial and yet poorly constrained role in the global carbon cycle. Mangrove sediments are frequently anoxic, which facilitates elevated organic matter (OM) burial via several mechanisms, including sulfurization – abiotic reactions between dissolved (poly)sulfide and OM that decrease its lability. Although sulfurization was estimated to account for roughly half of OM preservation in a Bermuda mangrove forest, both its mechanisms and its global significance remain poorly understood. In this study, we investigate S cycling in mangrove forest sediments from Little Ambergris Cay, Turks and Caicos Islands, an environment with predominantly microbial OM inputs and no major source of terrestrial iron. We characterize the S- and C-isotope composition and organic S speciation of sedimentary OM fractions with varying degrees of resistance to acid hydrolysis, along with other inorganic S phases. Near the surface of a 3-mm-diameter, O 2 -releasing root, abundant organic and elemental S with a 34 S-depleted composition indicates microbial sulfur cycling and OM sulfurization. A mixture of pyrite, elemental S, and organic S form a plaque within the outer 50 μm of the root, which also contains strongly 34 S-depleted sulfate in its xylem. OM sulfurization products in the sediments include both the alkyl sulfides and disulfides associated with the root plaque and more oxidized forms, especially sulfonates. Hydrolysis-resistant organic S in the sediments is consistently 3–5‰ more 34S-enriched than coexisting elemental S, matching the reported kinetic isotope fractionation factor for OM sulfurization via reaction with polysulfides. These sediments also contain a substantial pool of solid-phase, hydrolyzable organic S with a seawater sulfate-like isotope composition, largely in the form of sulfate esters, which may represent excretions from abundant gastropods. The coexistance of sulfurized OM and aerobic macrofauna highlights how understanding spatial scales and/or temporal cycles in local redox state is critical for predicting net OM preservation, especially in dynamic, coastal environments. Future attempts to mechanistically predict changes in carbon storage in coastal systems will benefit from incorporating OM sulfurization as both a sink for microbially produced sulfide and a mechanism for enhanced carbon sequestration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗