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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mitigating CO 2 Corrosion of Natural Gas Steel Pipelines by Thermal Spray Aluminum Coatings

We report internal pipeline corrosion due to carbon dioxide (CO 2 ) is a major challenge facing the oil and gas industry. The objective of this study was to investigate the corrosion behavior of aluminum (Al)-based alloys as sacrificial coatings to protect pipelines in a CO 2 -saturated aqueous electrolyte (3.5 wt% NaCl) at 4 bar CO 2 partial pressure (3 bar) and 40°C. The corrosion resistance of Al-based alloys and thermal spray coatings was evaluated in an electrochemical reaction autoclave using electrochemical methods (potentiodynamic polarization, linear polarization resistance, and electrochemical impedance spectroscopy). Post-corrosion surface characterization was performed by scanning electron microscopy equipped with energy-dispersive x-ray spectroscopy. The obtained data show Al-based alloys demonstrated promising protection against CO 2 corrosion with no breakaway degradation issues.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synchrophasor-Based Zonal Current Differential Protection for Secondary Low Voltage Networks

This report describes an approach to utilizing phasor measurement unit (PMU) data from multiple Intelligent Electronics Devices (IEDs) in a low-voltage network to produce a differential scheme for protecting the medium-voltage feeder and low-voltage network transformers. The proposed protection scheme is designed and prototyped on a real-time automation controller. Its performance is evaluated using real-time controller hardware-in-the-loop simulation. Lab testing results indicate that the proposed protection scheme allows significant distributed energy resources (DER) backfeed and enables selective and fast protection of medium voltage feeders.

42 ENGINEERING↗
DOE OSTI2020

Approach to Quality Assurance for Complex Environmental Modeling - 20407

A strong Quality Assurance (QA) program for complex environmental modeling is essential for regulatory and public acceptance and trust, but it does not have to be onerous. Neptune and Company, Inc. (Neptune) has developed a strong QA program that improves transparency, traceability, reproducibility, and therefore, defensibility and trust. Neptune's QA program has evolved over the past 27 years, transitioning from an ad hoc QA program, to a program that is currently Nuclear Quality Assurance-1 (NQA-1) compliant, and will soon be NQA-1/DOE approved for DOE EM modeling work. In addition, Neptune is a qualified laboratory assessor and qualified auditor for reference materials, a proficiency testing provider, and fully complies with the Environmental Protection Agency (EPA) QA program. Neptune's President and CEO, Kelly Black, was recently named the Chairperson of the International Organization for Standardization (ISO) Technical Committee 69, Application of Statistical Methods. A strong QA program has been developed for Neptune's radiological performance assessment (PA) program. Although pieces of their QA program are currently in development, their current program includes document control using Subversion, issue tracking and work flow tracking using JIRA, and transparency and traceability via a system of 'calc sheets' for documentation of all data analysis and modeling combined with 'check print' documentation of QA checking, and rigorous model testing and configuration control. All work is reviewed by an independent subject matter expert who is not associated with the collection and assembly of information, for an internal peer review. The program is enforced with a handful of Standard Operation Procedures (SOPs), Work Instructions, QA Project Plans (QAPPs), and Quality Management Plans (QMPs) that are updated frequently, with required annual training and acknowledgment. In addition, effective communication of modeling approaches and results to clients and stakeholders are integral to their QA program. Many of their models are built using the GoldSim modeling platform, for which their models are well-known for their level of transparency, documentation, and QA traceability. This level of QA is also applied to their process-level models. Neptune has taken some lessons learned from the extremely rigorous QA program required for the Yucca Mountain Project (YMP), and imposed the YMP requirements of complete traceability, transparency, and reproducibility, but avoided the inflexibility of a QA program that likely contributed to the suspect e-mails in 2005 that resulted in loss of trust in the YMP, and in nuclear waste disposal (and nuclear power) in general. There are far too many examples of loss of public trust due to poor QA that could have been easily avoided with a simple and straight-forward QA program combined with stakeholder engagement. The purpose of this paper is to share features of Neptune's Radiological Performance Assessment program QA program, and some of their QA related lessons learned over the past 27 years of QA for complex environmental modeling. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches

Abstract Wind power production is driven by, and varies with, the stochastic yet uncontrollable wind and environmental inputs. To compare a wind turbine's performance, a direct comparison on power outputs is always confounded by the stochastic effect of weather inputs. It is therefore crucial to control for the weather and environmental influence. Toward that objective, our study proposes an energy decomposition approach. We start with comparing the change in the total energy production and refer to the change in total energy as delta energy. On this delta energy, we apply our decomposition method, which is to separate the portion of energy change due to weather effects from that due to the turbine itself. We derive a set of mathematical relationships allowing us to perform this decomposition and examine the credibility and robustness of the proposed decomposition approach through extensive cross‐validation and case studies. We then apply the decomposition approach to Supervisory Control and Data Acquisition data associated with several wind turbines to which leading‐edge protection was carried out. Our study shows that the leading‐edge protection applied on blades may cause a small decline to the power production efficiency in the short term, although we expect the leading‐edge protection to benefit the blade's reliability in the long term.

17 WIND ENERGY↗
DOE OSTI2024

Identification and characterization of a skin microbiome on Caenorhabditis elegans suggests environmental microbes confer cuticle protection

ABSTRACT In the wild, C. elegans are emersed in environments teeming with a veritable menagerie of microorganisms. The C. elegans cuticular surface serves as a barrier and first point of contact with their microbial environments. In this study, we identify microbes from C. elegans natural habitats that associate with its cuticle, constituting a simple “skin microbiome.” We rear our animals on a modified CeMbio, mCeMbio, a consortium of ecologically relevant microbes. We first combine standard microbiological methods with an adapted micro skin-swabbing tool to describe the skin-resident bacteria on the C. elegans surface. Furthermore, we conduct 16S rRNA gene sequencing studies to identify relative shifts in the proportion of mCeMbio bacteria upon surface-sterilization, implying distinct skin- and gut-microbiomes. We find that some strains of bacteria, including Enterobacter sp. JUb101 , are primarily found on the nematode skin, while others like Stenotrophomonas indicatrix JUb19 and Ochrobactrum vermis MYb71 are predominantly found in the animal’s gut. Finally, we show that this skin microbiome promotes host cuticle integrity in harsh environments. Together, we identify a skin microbiome for the well-studied nematode model and propose its value in conferring host fitness advantages in naturalized contexts. IMPORTANCE The genetic model organism C. elegans has recently emerged as a tool for understanding host–microbiome interactions. Nearly all of these studies either focus on pathogenic or gut-resident microbes. Little is known about the existence of native, nonpathogenic skin microbes or their function. We demonstrate that members of a modified C. elegans model microbiome, mCeMbio, can adhere to the animal's cuticle and confer protection from noxious environments. We combine a novel micro-swab tool, the first 16S microbial sequencing data from relatively unperturbed C. elegans , and physiological assays to demonstrate microbially mediated protection of the skin. This work serves as a foundation to explore wild C. elegans skin microbiomes and use C. elegans as a model for skin research.

16S RNA↗
DOE OSTI2022

Differentially Private Synthesis and Sharing of Network Data Via Bayesian Exponential Random Graph Models

Abstract Network data often contain sensitive relational information. One approach to protecting sensitive information while offering flexibility for network analysis is to share synthesized networks based on the information in originally observed networks. We employ differential privacy (DP) and exponential random graph models (ERGMs) and propose the DP-ERGM method to synthesize network data. We apply DP-ERGM to two real-world networks. We then compare the utility of synthesized networks generated by DP-ERGM, the DyadWise Randomized Response (DWRR) approach, and the Synthesis through Conditional distribution of Edge given nodal Attribute (SCEA) approach. In general, the results suggest that DP-ERGM preserves the original information significantly better than two other approaches in network structural statistics and inference for ERGMs and latent space models. Furthermore, DP-ERGM satisfies node DP through modeling the global network structure with ERGM, a stronger notion of privacy than the edge DP under which DWRR and SCEA operate.

graph synthesis↗
DOE OSTI2020

Online Data-Enabled Predictive Control

We develop an online data-enabled predictive (ODeePC) control method for trajectory tracking of unknown systems, building upon the recently proposed DeePC. Our proposed ODeePC method leverages a primal-dual algorithm with real-time measurement feedback to iteratively compute the corresponding real-time optimal control policy as system conditions change. Specifically, our developed ODeePC: a) records data from the unknown system and updates the underlying primal-dual algorithm dynamically, b) can track changes in the system's operating point and adjust the control inputs, and c) is computationally efficient as it deploys a Fast Fourier Transform-based algorithm enabling the fast computation of the product of a non-square Hankel matrix with a vector. We provide theoretical guarantees regarding the asymptotic behavior of ODeePC and demonstrate its performance through a power system application.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Quantitative Validation of Control Bands Using Bayesian Statistical Analyses

Abstract This study presents a quantitative validation of 15 Similar Exposure Groups (SEGs) that were derived via control bands inherent to the Risk Level Based Management System currently being used at the Lawrence Livermore National Laboratory. For 93% of the SEGs that were evaluated, statistical analyses of personal exposure monitoring data, through Bayesian Decision Analysis (BDA), demonstrated that the controls implemented from the initial control bands assigned to these SEGs were at least as protective as the controls from the control band outcomes derived from the quantitative data. The BDA also demonstrated that for 40% of the SEGs, the controls from the initial control bands were overly protective, thus allowing controls to be downgraded, which resulted in a significant saving of environmental safety and health (ES&H) resources. Therefore, as a means to both confirm existing controls and to identify candidate SEGs for downgrading controls, efforts to continuously improve the accuracy of Control Banding (CB) strategies through the routine quantitative validation of SEGs are strongly encouraged. Targeted collaborative efforts across institutions and even countries for both the development of CB strategies and the validation of discreetly defined SEGs of commonly performed tasks will not only optimize limited ES&H resources but will also assist in providing a simplified process for essential risk communication at the worker level to the benefit of billions of workers around the world.

McCord, Tyler A.↗
DOE OSTI2025

Evaluation of Cross-Protection of African Swine Fever Vaccine ASFV-G-ΔI177L Between ASFV Biotypes

Background/Objectives: Vaccine development for the prevention of ASF has been very challenging due to the extensive genetic and largely unknown antigenic diversity. Inactivated vaccines, using different inactivation methods and a variety of adjuvants, have been consistently inefficacious. Historically, animals recovering from an infection with an attenuated virus became protected from the development of a clinical disease caused by an antigenically related strain. Therefore, immunization of susceptible animals with attenuathe ted virus strains has become a common method of vaccination with the first two commercially available vaccines based on recombinant live-attenuated viruses (LAVs). An important limitation is that the efficacy of the LAV is restricted to those strains that are antigenically related and, in most cases, only provide protection against homologous strains. Due to the unknown antigenic heterogeneity among all ASFV field isolates, the development of broad-spectrum vaccines is a challenge. Besides the anecdotal data, there is not a large amount of information describing patterns of cross-protection between different ASFV strains. Methods: We evaluated the cross-protection induced by the ASFV live-attenuated vaccine ASFV-G-ΔI177L against different biotypes of ASFV and compared their genomic sequences to determine potential genetic mutations that could cause the lack of cross-protection. Results: Results presented here demonstrate different patterns of protection when ASFV-G-ΔI177L vaccinated pigs were challenged with six different ASFV field isolates belonging to different biotypes. Conclusions: The presence of cross-protection cannot be predicted solely by the classical methodology for genotyping-based B646L ORF only. Biotyping, considering the entire virus proteome, appears to be a more promising prediction tool, although additional gathering of experimental data will be necessary to fully validate it; until then, the presence of cross-protection needs to be confirmed in efficacy trials challenging vaccinated animals.

Immunology↗
DOE OSTI2023

Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report)

Secure Data Logging and Processing with Blockchain and Machine Learning (ML) research is focused on the development of a platform to securely log and process sensor data in fossil power plants. The platform integrates two emerging technologies, blockchain and ML, and incorporates several innovative mechanisms to ensure the integrity, reliability, and resiliency of power systems. The goal is to protect the power plant from various cyberattacks such as false data injection and denial of service attacks using these technologies. The research goal was enabled by the following Research Project Objectives: 1) Secure authentication and identity verification of sensor nodes, actuators, and other equipment within a network. 2) Development of mechanisms that ensure only data sent by legitimate sensors are accepted and stored in the data repository. 3) Development of data aggregation methodologies using ML / Deep Learning (DL) algorithms to minimize noise / faulty data. 4) Implementation of the blockchain technologies to provide data security using secured IOTA framework & nodes.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Making a Water Data System Responsive to Information Needs of Decision Makers

Evidence-based environmental management requires data that are sufficient, accessible, useful and used. A mismatch between data, data systems, and data needs for decision making can result in inefficient and inequitable capital investments, resource allocations, environmental protection, hazard mitigation, and quality of life. In this paper, we examine the relationship between data and decision making in environmental management, with a focus on water management. We focus on the concept of decision-driven data systems —data systems that incorporate an assessment of decision-makers' data needs into their design. The aim of the research was to examine the process of translating data into effective decision making by engaging stakeholders in the development of a water data system. Using California's legislative mandate for state agencies to integrate existing water and other environmental data as a case study, we developed and applied a participatory approach to inform data-system design and identify unmet data needs. Using workshops and focused stakeholder meetings, we developed 20 diverse use cases to assess data sources, availability, characteristics, gaps, and other attributes of data used for representative decisions. Federal and state agencies made up about 90% of the data sources, and could readily adapt to a federated data system, our recommended model for the state. The remaining 10% of more-specialized data, central to important decisions across multiple use cases, would require additional investment or incentives to achieve data consistency, interoperability, and compatibility with a federated system. Based on this assessment, we propose a typology of different types of data limitations and gaps described by stakeholders. We also propose technical, governance, and stakeholder engagement evaluation criteria to guide planning and building environmental data systems. Data-system governance involving both producers and users of data was seen as essential to achieving workable standards, stable funding, convenient data availability, resilience to institutional change, and long-term buy-in by stakeholders. Our work provides a replicable lesson for using decision-maker and stakeholder engagement to shape the design of an environmental data system, and inform a technical design that addresses both user and producer needs.

Cantor, Alida↗
DOE OSTI2021

A Transformational Natural Gas Fueled Dynamic SOFC for Data Center in-Rack Power (Final Technical Report)

Data centers consume 250TWh or 1% of global electricity use in 2019. This electricity demand is expected to grow exponentially in the future. The current data center power supply relies on electric grids with diesel engines and batteries as backup; the latter is critically important because a sudden loss of power could erase crucial data, causing catastrophic economic loss. However, such a double protection architecture is costly, inefficient and polluting. In search for better in-rack power system, fuel-cell based generators have recently emerged as a promising alternative to diesel engines and batteries because of its potential to be more cost-effective, more efficient and less polluting. Among many types of fuel cells, solid oxide fuel cells stand out to be a front runner because of their ability to directly operate on natural gas that has an existing infrastructure. However, there are several critical challenges facing SOFC generators to meet the rigorous power requirements of data centers: high cost, poor reliability and more importantly, slow response to the datacenters’ dynamic load change. The unexpected overload conditions in data centers can cause fuel starvation; the latter can initiate microcracks in the anode structure, thus jeopardizing the lifetime of the SOFC generator. The current efforts to increase transient power capabilities of traditional SOFCs and therefore protect SOFC stacks from internal damage during transient loading, rely primarily upon mathematical algorithms. One of the challenges to these control methodologies is the physical limitations of the fuel delivery system such as slow response of mass flow controllers to fast power demand.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

MARSAME Radiological Release Report for Diamond Drive Widening and Roundabout Construction Projects, Revision 1

Environmental Protection and Compliance, Environmental Stewardship (EPC-ES) has determined that the soil, concrete and asphalt associated with the Diamond Drive Widening/Roundabout Projects (Figure 1) meets the criteria for unrestricted release to the public under Department of Energy (DOE) Order 458.1, Radiation Protection for the Public and the Environment (DOE, 2020). These conclusions are based on the known history of the area combined with soil sample data collected in 2022; the findings are consistent with DOE Order 458.1 and Los Alamos National Laboratory (LANL) Functional Series Document EPC-ES-FSD-004, Environmental Radiation Protection (LANL, 2021). Sampling and data analysis, as described in this report, were sufficient to meet measurement quality objectives (MQOs) under the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) manual (NUREG, 2009) and LANL procedures (LANL, 2020). Final approvals for waste disposition will come from LANL’s Waste Management Program.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Adjoint sensitivity analysis and data assimilation for verification of dry storage cask contents

Dry cask storage is a method for interim storage of spent fuel assemblies which contain fissile isotopes of uranium and plutonium. These can present a proliferation concern and consequently there is a need for non-destructive testing methods to verify a dry cask's contents for proliferation protection. We present an application of adjoint sensitivity analysis and data assimilation to a multigroup diffusion model of dry cask storage. Adjoint sensitivity analysis allows the efficient calculation of sensitivities for use in data assimilation to calibrate imprecisely known parameter values and data consistency tests to detect diversion scenarios. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Platinum/Tantalum Carbide Core–Shell Nanoparticles with Sub‐Monolayer Shells for Methanol and Oxygen Electrocatalysis

Abstract Core–shell architectures provide great opportunities to improve catalytic activity, but achieving nanoparticle stability under electrochemical cycling remains challenging. Herein, core–shell nanoparticles comprising atomically thin Pt shells over earth‐abundant TaC cores are synthesized and used as highly durable electrocatalysts for the methanol oxidation reaction (MOR) and the oxygen reduction reaction (ORR) needed to drive direct methanol fuel cells (DMFCs). Characterization data show that a thin oxidic passivation layer protects the TaC core from undergoing dissolution in the fuel cell‐relevant potential range, enabling the use of partially covered Pt/TaC core–shell nanoparticles for MOR and ORR with high stability and enhanced catalytic performance. Specifically, at the anode the surface‐oxidized TaC further enhances MOR activity compared to conventional Pt nanoparticles. At the cathode, the Pt/TaC catalyst feature increases tolerance to methanol crossover. These results show unique synergistic advantages of the core–shell particles and open opportunities to tailor catalytic properties for electrocatalytic reactions.

Chemistry↗
DOE OSTI2024

Setups for eliminating static charge of the ATLAS18 strip sensors

Abstract Construction of the new all-silicon Inner Tracker (ITk), developed by the ATLAS collaboration to beable to track charged particles produced at the High-Luminosity LHC, started in 2020 and is expected tocontinue till 2028. The ITk detector will include 18,000 highly segmented and radiation hard n+-in-psilicon strip sensors (ATLAS18), which are being manufactured by Hamamatsu Photonics. Mechanical and electrical characteristics of produced sensors are measured upon their delivery at several institutes participating in a complex Quality Control (QC) program. The QC tests performed on each individual sensor check the overall integrity and quality of the sensor.During the QC testing of ATLAS18 strip sensors, an increased number of sensors thatfailed the electrical tests was observed. In particular, IV measurements indicated an early breakdown,while large areas containing several tens or hundreds of neighbouring strips with low interstrip isolationwere identified by the Full strip tests, and leakage current instabilities were measured in a long-term leakage current stability setup. Moreover, a high surface electrostatic charge reaching a level of several hundreds of volts per inch was measured on a large number of sensors and on the plastic sheets, whichmechanically protect these sensors in their paper envelopes. Accumulated data indicates a clearcorrelation between observed electrical failures and the sensor charge-up.To mitigate the above-described issues, the QC testing sites significantly modified the sensor handlingprocedures and introduced sensor recovery techniques based on irradiation of the sensor surface with UVlight or application of intensive flows of ionized gas. In this presentation, we will describe the setupsimplemented by the QC testing sites to treat silicon strip sensors affected by static charge andevaluate the effectiveness of these setups in terms of improvement of the sensor performance.

Instruments & Instrumentation↗
DOE OSTI2025

Digital Filter Design for Point-on-Wave Sensors: Highlighting Frequency Response Limitations and Enhancing Grid Simulation Accuracy

Data is proving to be the backbone of today's and, more importantly, tomorrow's grid. As the system changes and introduces fast-acting devices like power electronics, overall observability tends to decrease from the utility point-of-view. This can be mitigated by adding more high-fidelity sensors onto the grid, although this incurs a cost. These sensors are never ideal, and each have unique frequency responses that may influence the data produced. This may, in turn, impact the protection and control of the power grid. This paper presents a methodology of representing these point-on-wave sensors digitally by estimating digital-filter representations of them, thereby introducing means of improving the sensor models used in electromagnetic-transient (EMT) simulations. This may help with identifying potential high-frequency, sensor-induced distortions, and system resonance compensation. Three commercial-grade medium-voltage point-on-wave sensors are utilized in a lab environment to obtain experimental frequency responses with a frequency sweep, and it is shown that both Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filter representations may approximate these responses with varying degrees of accuracy, though each has their own strengths and weaknesses. It is found that, in general, FIR estimation better approximates these sensors than IIR estimation does.

Wilson, Aaron [ORNL] (ORCID:0000000327331697)↗
DOE OSTI2025

Geographic, sectoral, and constituent characteristics of US off‐site manufacturing wastewater disposal

This study employs recent US Environmental Protection Agency off-site manufacturing wastewater disposal data and a socioenvironmental assessment tool for the United States to understand the characteristics of such disposal in terms of geography, major contributing sectors and pollutants, and environmental impacts. Environmental impact analyses of manufacturing are insufficient without encompassing the extended physical boundary of waste management. Our analysis reveals that off-site manufacturing wastewater disposal occurs disproportionately in populations residing in census tracts already negatively impacted by environmental hazards (impacted populations, or IPs) with 44% of transfers and 55% of Risk Screening Environmental Indicators (RSEI) Hazard going to these areas, compared to their national share of 37%. Disposal hazard is concentrated in a small number of populations, with a Gini coefficient of 0.99 for RSEI Hazard. Four manufacturing sub-sectors are significant generators: Chemicals, Fabricated Metals, Primary Metals, and Transportation Equipment, with Chemicals off-site wastewater disposal largely occurring in IPs. For individual contaminants, chromium compounds and chromium represent more than 85% of the hazard but less than 10% of transfers. We explore transfer distances and waste generation and disposal hotspots, finding that the Midwest hosts a disproportionate share of off-site wastewater disposal. Further, RSEI Hazard steeply rises at shorter distances and plateaus over distances >500 miles, revealing opportunities to reduce hazard by reducing 20–500-mile transfers. Our findings strongly support targeted mitigation strategies like process substitutions, control technologies, on-site recycling and treatment, and minimizing transfer distances. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

Fuchs, Heidi [Lawrence Berkeley National Laborator↗