Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Resource Assessments”

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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Security assessment and impact analysis of cyberattacks in integrated T&D power systems

In this paper, we examine the impact of cyberattacks in an integrated transmission and distribution (T&D) power grid model with distributed energy resource (DER) integration. We adopt the OCTAVE Allegro methodology to identify critical system assets, enumerate potential threats, analyze and prioritize risks for threat scenarios. Based on the analysis, attack strategies and exploitation scenarios are identified which could lead to system compromise. Specifically, we investigate the impact of data integrity attacks in inverted-based solar PV controllers, control signal blocking attacks in protective switches and breakers, and coordinated monitoring and switching time-delay attacks. Index Terms—Cyberattacks, security assessment, impact analysis, case studies, integrated power systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Central Hanford Ecological Integrity Assessments: Final Report

The Hanford Site is comprised of an expanse of shrub-steppe habitats that provides exceptional ecological value to plants and animals located on the site and in the surrounding greater Columbia Basin. The U.S. Department of Energy, Hanford Field Office (HFO)-managed portion of the Hanford Site, referred to herein as Central Hanford, has been the focus of various ecological monitoring efforts, such as vegetation monitoring. The scope and goals of vegetation surveys have varied greatly since the Hanford Site was established, but studies have documented a rapidly changing landscape, making it clear that routine vegetation monitoring is integral to understanding ecological changes and preserving the ecological value of the Hanford Site. A new vegetation monitoring effort was initiated in calendar year (CY) 2023 and continued through CY 2025 using methods based on ecological integrity assessments (EIA) (NHR-2024-04, Field Manual for Applying Rapid Ecological Integrity Assessments in Upland Plant Communities of Washington State ) developed by the Washington Natural Heritage Program (WNHP), a division of the Department of Natural Resources (DNR), and NatureServe.® The methods were modified and supplemented to meet monitoring goals at the Hanford Site. The EIA monitoring effort consisted of field surveys to evaluate vegetation and soil conditions for upland habitats throughout Central Hanford. Vegetation cover estimates were used to score a variety of metrics for vegetation condition. This report summarizes monitoring methods, monitoring results, and provides management recommendations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Essential Role of Integrated Nuclear-Renewable Energy Systems in Achieving Economy-wide Net Zero Solutions

Background/Objectives. The Biden administration has committed to full decarbonization of the U.S. electricity grid by 2035 and economy-wide net zero emissions by 2050. These aggressive goals demand immediate action if we are to be successful, and they require us to think more holistically about our clean energy options. Focused laboratory initiatives, such as the INL Integrated Energy Systems (IES) Initiative, and multiple programs within the Department of Energy are working together to address these holistic solutions. Approach/Activities. Traditionally, electricity generation and management and meeting energy demands for industry and transportation are considered independently. As we seek to achieve net zero, we need to reassess our energy demands. When we consider overall energy use, only one-third is in the form of electricity. Additional energy demands are in the form of heat or steam for industrial processes, as well as transportation. Emissions across these sectors are much harder to abate, and electrification may not be the best option. Reducing environmental emissions at an affordable cost, while maintaining grid reliability and resilience, will require us to use all of the clean energy resources that we have available. That means coordinating the use of nuclear, renewables, and fossil fuels with carbon capture to meet growing demands for electricity, industrial applications, and mobility. The primary focus of IES research is to assess the technical and economic potential of various IES solutions to enhance the flexibility and utilization of nuclear energy generators working alongside renewable generators to meet an array of energy demands—thereby maximizing the utilization of clean energy resources across all energy sectors. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. Results/Lessons Learned. This presentation will highlight the wide array of RD&D being conducted to develop and deploy nuclear-based IES that will be key to achieving our net zero goals. By working with key collaborators in the nuclear industry, analytical studies are now becoming a reality in multiple demonstration projects.

08 HYDROGEN↗
DOE OSTI2021

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗
DOE OSTI2025

TPCpp-10M: Simulated proton-proton collisions in a time projection chamber for AI foundation models

Scientific foundation models hold great promise for advancing nuclear and particle physics by improving analysis precision and accelerating discovery. Yet, progress in this field is often limited by the lack of openly available large scale datasets, as well as standardized evaluation tasks and metrics. Furthermore, the specialized knowledge and software typically required to process particle physics data pose significant barriers to interdisciplinary collaboration with the broader machine learning community. This work introduces a large, openly accessible dataset of 10 million simulated proton-proton collisions, designed to support self-supervised training of foundation models. To facilitate ease of use, the dataset is provided in a common NumPy format. In addition, it includes 70,000 labeled examples spanning three well defined downstream tasks: track finding, particle identification, and noise tagging, to enable systematic evaluation of the foundation model's adaptability. The simulated data are generated using the Pythia Monte Carlo event generator at a center of mass energy of $\sqrt{s}$ = 200 GeV and processed with Geant4 to include realistic detector conditions and signal emulation in the sPHENIX Time Projection Chamber at the Relativistic Heavy Ion Collider, located at Brookhaven National Laboratory. This dataset resource establishes a common ground for interdisciplinary research, enabling machine learning scientists and physicists alike to explore scaling behaviors, assess transferability, and accelerate progress toward foundation models in nuclear and high energy physics. The complete simulation and reconstruction chain is reproducible with the sPHENIX software stack. All data and code locations are provided under Data Accessibility.

Data Analysis, Statistics and Probability (physics↗
DOE OSTI2026

Quantitative DNA Stable Isotope Probing Identifies Active Microorganisms Assimilating Volatile Fatty Acids in Full-Scale Enhanced Biological Phosphorus Removal Processes

Enhanced biological phosphorus removal (EBPR) systems often rely on exogenous carbon sources, such as volatile fatty acids (VFAs), to achieve higher P removal. Here, we employed DNA quantitative stable isotope probing (qSIP) using two VFAs, acetate and propionate, in cyclic anaerobic/aerobic incubations to assess their effects on P cycling and microbial activity with biomass from two full-scale EBPR water resource-recovery facilities that utilize VFA addition. We found that anaerobic VFA uptake preferences differed within known groups of PAOs, such as Candidatus Accumulibacter and Tetrasphaera-affiliated members (e.g., Ca. Phosphoribacter), between the two biomasses. The combination of qSIP with metagenomics identified isotopically labeled phages that were linked to active PAOs, highlighting their potential roles in modulating EBPR community composition and activity. The highest levels of anaerobic labeling from acetate were in genomes belonging to Saccharimonadales and Rickettsiales, which are generally host-associated with bacteria and eukaryotes, respectively. Furthermore, this finding highlights the possibility of cross-feeding between PAO hosts and their parasites or predators, as well as the role of so-far uncharacterized organisms participating in carbon cycling under EBPR conditions. Collectively, these results expand our understanding of the ecological interactions involved in communities anaerobically uptaking VFAs and cycling P that are central to EBPR.

Polyphosphate accumulating organisms↗
DOE OSTI2024

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world’s deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen’s antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Comparative Study of Data-Driven Area Inertia Estimation Approaches on WECC Power Systems

With the increasing integration of inverter-based resources into the power grid, there has been a notable reduction in system inertia, potentially compromising frequency stability. To assess the suitability of existing area inertia estimation techniques for real-world power systems, this paper presents a rigorous comparative analysis of system identification, measurement reconstruction, and electromechanical oscillation-based area inertia estimation methodologies, specifically applied to the large-scale and multi-area WECC 240-bus power system. Comprehensive results show that the system identification-based approach exhibits superior robustness and accuracy relative to its counterparts.

area inertia estimation↗
DOE OSTI2023

Study of Storage Requirements and Costs for Shaping Renewables and Nuclear Energy (FY23 Summary Report)

To decarbonize electricity generation primarily by using wind and solar resources, it is likely that additional low (or zero) carbon dioxide (CO 2 ) alternatives will be required for ensuring a reliable electricity supply. This study extends the work and modeling framework that we consolidated in FY 2022, by assessing the zero-CO 2 pathways of a Texas power system in which the availability of variable renewable energy (VRE), nuclear energy, and energy storage types (i.e., battery and thermal energy storage [TES]) are considered the sole resources available for expansion. Using the Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON) frameworks, this study investigates the market of two nuclear energy technologies (i.e., large light-water reactors [LWRs] and LWR-type small modular reactors [SMRs]) under two plausible storage coupling scenarios (i.e., electric coupling and direct thermal coupling). We also explore optimal environments for nuclear energy deployment, and identify key performance characteristics that make nuclear energy economically viable in areas with significant intermittent energy sources. Our analysis encompasses 24 cases. We model the least-cost grid systems, highlight the potential for a coupled LWR-TES approach, and utilize SMRs to achieve deep decarbonization in an affordable, technically feasible manner. We also examine seasonal variations in balancing electricity supply and demand, and account for varying performance, costs, and grid constraints. Overall, the findings of our modeling afford valuable insights for supporting future technology investment decisions in the energy sector.

25 ENERGY STORAGE↗
DOE OSTI2024

A Collaborative Industrial Assessment Center (IAC) for Expanded Outreach within the Southeast

This GA-FL IAC had impacts on workforce development and economic impact for regional small- and medium-sized enterprises. Qualified faculty and campus staff educated and trained cohorts of students regarding state-of-the-art industrial assessments. Students gained hands-on experiences in learning about manufacturing processes, energy systems, developing assessment recommendations/calculations, and client interaction. These skills were complemented by the incorporation of IAC themes into some course curricula. As far as economic impact, the center conducted 66 assessments over 5 years primarily in Georgia and Florida. These represented hundreds of thousands of dollars in potential annual resource savings to the clients and region.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Energy Storage Participation Algorithm Competition Overview: Market simulation, divisions, stages, storage attributes, and scoring

The Energy Storage Participation Algorithm Competition (ESPA-Comp) aims to assess the performance of participants’ battery storage offer algorithms on their ability to maximize the value of battery storage resources under three different market designs: two-settlement, multi-settlement, and rolling horizon forward markets. This document describes the overall design of the competition at a high level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Bridging the Gap on Data and Analysis for Distribution System Planning: Information That Utilities Can Provide Regulators, State Energy Offices and Other Stakeholders

Electric utilities conduct planning annually to ensure their distribution system meets technical standards, policies, and regulations; addresses forecasted grid conditions; satisfies customer needs; and advances utility priorities. The plan identifies grid deficiencies, analyzes potential solutions, and prioritizes capital investments and other expenditures. About 20 U.S. states and jurisdictions require regulated utilities to file some type of distribution system plan with the public utility commission for review. Requirements for sharing distribution system data and analyses vary widely, from few specific requirements to a detailed list of information that must be provided. While utilities conduct extensive analysis to develop distribution system plans, in most jurisdictions regulators and stakeholders do not know what data are available and how the utility uses the data in planning and investing. This report aims to bridge the gap by increasing understanding of the types of data and analyses utilities employ to develop distribution system plans and how the information affects their decision-making. The report describes information that states and stakeholders can ask for related to 11 data categories: -Forecasting loads and distributed energy resources (DERs) -Scenario analysis -Worst-performing circuits -Asset management strategy -Hosting capacity analysis -Value of DERs -Grid needs assessment -Cost-effectiveness framework for investments -Distribution system investment strategy and implementation -Geotargeted programs -Non-wires alternatives procurements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Photovoltaic and Cost Analysis for Winston-Salem, North Carolina

This study assesses the feasibility of solar installations at various sites in Winston-Salem, focusing on factors such as solar resource availability, electricity costs, and rooftop area for photovoltaic systems. The analysis begins by estimating daily energy requirements based on annual electricity use, followed by adjusting for seasonal and operational fluctuations. Using regional solar data from the National Solar Radiation Database (NSRDB), we calculate average peak sun hours to determine effective system sizing. A parametric approach using the System Advisor Model (SAM) refines this sizing process, incorporating a safety margin of 1.2 to address demand peaks. Each PV system is designed to fit available rooftop space, and a coverage threshold of 70% is identified as optimal for maximizing cost savings and sustainability. This threshold allows installations to meet substantial energy demands, supporting energy resilience and enhancing economic returns.

14 SOLAR ENERGY↗
DOE OSTI2025

Data for "Implications of Zoning Ordinances for Rural Utility-Scale Solar Deployment and Power System Decarbonization in the Great Lakes Region".

This dataset includes the Energy Zoning Database and geographic shapefiles used to identify suitable rural areas for utility-scale solar development. Additionally, it contains the input data required for the capacity expansion model, including information on existing electric generators and their associated costs, solar resource potential, and transmission infrastructure data. These datasets collectively support the analysis presented in the paper, ensuring a comprehensive assessment of zoning regulations, land suitability, and the economic and technical feasibility of solar deployment in rural areas.

Owusu-Obeng, Papa Yaw (ORCID:0000000334385183)↗
DOE OSTI2021

Multiple lineages of Streptomyces produce antimicrobials within passalid beetle galleries across eastern North America

Some insects form symbioses in which actinomycetes provide defense against pathogens by making antimicrobials. The range of chemical strategies employed across these associations, and how these strategies relate to insect lifestyle, remains underexplored. We assessed subsocial passalid beetles of the species Odontotaenius disjunctus , and their frass (fecal material), which is an important food resource within their galleries, as a model insect/actinomycete system. Through chemical and phylogenetic analyses, we found that O. disjunctus frass collected across eastern North America harbored multiple lineages of Streptomyces and diverse antimicrobials. Metabolites detected in frass displayed synergistic and antagonistic inhibition of a fungal entomopathogen, Metarhizium anisopliae , and multiple streptomycete isolates inhibited this pathogen when co-cultivated directly in frass. These findings support a model in which the lifestyle of O. disjunctus accommodates multiple Streptomyces lineages in their frass, resulting in a rich repertoire of antimicrobials that likely insulates their galleries against pathogenic invasion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Offshore Wind Workforce Safety Standards and Training Resource

The standardization of safety training requirements for people working at sea to build and operate offshore wind energy projects, adoption of those standards, and alignment with offshore safety training curriculum development was identified as a high-priority workforce gap in the U.S. Offshore Wind Workforce Assessment (Stefek, 2022). Safety is a top priority for the offshore wind industry; however, there has been uncertainty surrounding what unique safety standards and training will be needed and how various offshore wind safety stakeholders will be involved. The scope of safety training for this resource includes workers who build and operate offshore wind energy projects at sea and defines the stakeholders in the complex ecosystem. This fact sheet aims to help reduce these uncertainties by: 1) Delineating jurisdictional lines, while clarifying roles and responsibilities amongst stakeholders; 2) Identifying key actions or partnerships that can encourage further success with safety training and workforce development.

offshore wind↗
DOE OSTI2022

Assessing the Potential Impact of River Chemistry on Arctic Coastal Production

The Arctic coastal margin receives a disproportionately large fraction of the global river discharge. The bio-geochemistry of the river water as it empties into the marine environment reflects inputs and processes that occur as the water travels from its headwaters. Climate-induced changes to Arctic vegetation and permafrost melt may impact river chemistry. Understanding the impact of river nutrients on coastal marine production, and how this may change in the future, are important for resource managers and community members who monitor and rely on coastal food resources. Using the Energy Exascale Earth System Model we explore the impact of timing and river nutrient concentrations on primary production in each coastal Arctic region and then assess how this influences secondary production and particle fluxes supporting the benthic food web. Our results indicate that while the concentration of Arctic river nitrogen can have a significant impact on annual average nitrogen and primary production in the coastal Arctic, with production increases of up to 20% in the river influenced interior Seas, the timing of the river nutrient inputs into the marine environment appears less important. Bloom timing and partitioning between small and large phytoplankton were minimally impacted by both river nutrient concentration and timing, suggesting that in general, coastal Arctic ecosystem dynamics will continue to be primarily driven by light availability, rather than nutrients. Under a doubling river nutrient scenario, the percentage increase in the POC flux to the benthos on river influenced Arctic coastal shelves was 2-4 times the percentage increase in primary production, suggesting changes to the river nutrient concentration has the potential to modify the Arctic food web structure and dynamics. Generally, the nutrient-induced changes to primary production were smaller than changes previously simulated in response to ice reduction and temperature increase. However, in the Laptev Sea, the production increase resulting from a doubling of river nutrients exceeded the production increase simulated with an atmospheric warming scenario. Dissolved organic carbon is presently poorly represented in the model so its impact on production is hard to simulate. Applying established relationships between modeled DOC, total DOC, and light absorption we illustrate that DOC could play a very important role in modulating production. Our findings highlight the importance of developing more realistic river nutrient and discharge forcing for Earth System Models such that their impact on the critical Arctic coastal domain can be more adequately resolved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Utility Energy Service Contract Guide: A Resource for Contracting Officers Working on UESC Projects

A Utility Energy Service Contract (UESC) is a limited-source contract between a federal agency and serving utility for energy management services including energy and water efficiency improvements and demand-reduction services. In a UESC, the Contracting Officer (CO) will lead the acquisition effort, supported by technically knowledgeable staff working closely with the utility, to assess potential, investigate technical and economic feasibility, and ensure a fair and reasonable price for design and implementation of the project. The UESC Guide is a compilation of samples and templates developed as a resource to help COs implement Task Orders (TOs) for UESCs under existing U.S. General Services Administration (GSA) Areawide Contracts (AWC). All samples and templates provided in this guide were derived from actual UESC project contract documents and will be available for download on FEMP’s website at https://www.energy.gov/node/850656. Templates in Microsoft Word can be modified to address each agency’s unique acquisition process.

Federal Energy Management Program↗