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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 OSTI2020

PhycoCosm, a comparative algal genomics resource

Abstract Algae are a diverse, polyphyletic group of photosynthetic eukaryotes spanning nearly all eukaryotic lineages of life and collectively responsible for ∼50% of photosynthesis on Earth. Sequenced algal genomes, critical to understanding their complex biology, are growing in number and require efficient tools for analysis. PhycoCosm (https://phycocosm.jgi.doe.gov) is an algal multi-omics portal, developed by the US Department of Energy Joint Genome Institute to support analysis and distribution of algal genome sequences and other ‘omics’ data. PhycoCosm provides integration of genome sequence and annotation for >100 algal genomes with available multi-omics data and interactive web-based tools to enable algal research in bioenergy and the environment, encouraging community engagement and data exchange, and fostering new sequencing projects that will further these research goals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Application of quantitative risk assessment to address stakeholder questions in geologic carbon storage

Ambitious international greenhouse gas emissions reduction targets demand a rapid transformation to a low-carbon economy. This transformation includes the accelerated adoption of carbon dioxide (CO2) capture and storage (CCS) technology. However, as with any large-scale engineering enterprise, the widespread commercial-scale deployment of geologic carbon storage (GCS) raises important questions about technology and cost-effectiveness, safety, environmental risk, and long-term liability. Effectively assessing and managing risks and liability associated with GCS projects is a key technical need throughout the project life cycle-from site selection and permitting to monitoring design, operational risk management, and post-operational site closure. This presentation highlights recent advancements in tools for quantitative risk assessment, being developed by the National Risk Assessment Partnership (NRAP). NRAP is a multi-year, multinational laboratory research collaboration sponsored by the U.S. Department of Energy's Office of Fossil Energy and Carbon Management. Our focus will be on these tools' applications in addressing critical stakeholder questions related to supporting permitting to ensure secure and environmentally protective storage; designing effective and efficient monitoring plans; evaluating the effectiveness of remedial actions and risk management alternatives; and informing liability assessment and investment decisions. This paper will detail the key functionality of NRAP’s Open-Source Integrated Assessment Model (NRAP-Open-IAM), a computational framework for assessing leakage risk and containment assurance. This model features streamlined workflows for calculating leakage risk profiles, delineating risk-based area of review, and assessing contingency plans and post-injection site care requirements. ORION is an open-source, observation-based ensemble forecasting toolkit to help operators assess the seismic hazard at a carbon storage site. The State of Stress Analysis Tool (SOSAT), designed to assess subsurface stress conditions and evaluate geomechanical risk resulting from CO2 injection in an area of interest will also be presented. We will also introduce a prototype model to evaluate storage project costs and liability associated with risk management. The Technoeconomic and Liability Evaluation for Storage (TALES) model uses results from forecasts of leakage and induced seismicity risk to estimate the lifecycle cost of managing risk. Finally, a preliminary example of how the NRAP Risk-based Adaptive Monitoring Plan (RAMP) tool can be used to design efficient and effective site monitoring plans and estimate the detectability of fluid leakage will be provided. The relevance of these tools for addressing key stakeholder questions amidst uncertainty will be emphasized.

decision support↗
DOE OSTI2023

Wind Turbine Generator Reliability Analysis to Reduce Operations and Maintenance (O&M) Costs

Wind turbine major systems (blades, pitch, main bearing, gearbox, and generator) are integrated into a composite system. Specifications for these systems and components are developed to achieve symmetry of operation, avoiding negative interaction. For instance, the main bearing, gearbox, and generator (drivetrain) components are interdependent, functioning in unison for efficient energy production. Hence, wind resource and grid interactions affecting the drivetrain impact the performance and reliability of the turbine generator. This paper discusses generator reliability covering the technology evolution over the last 20 years. EPRI's Wind Network for Enhanced Reliability (WinNER) web-based tool and Shermco Industries databases are presented, and conclusions are drawn regarding failures specific to generator design, manufacturing, and operating conditions. Additionally, this paper compares the life expectancy of stator-fed configurations and doubly fed generator systems.

17 WIND ENERGY↗
DOE OSTI2020

Double-Shell Tank Primary Bottom Visual Inspection Results - 20025

A pressing need for the Double-Shell Tank Integrity Program at Hanford is of the ability to inspect the bottom of the tanks. Though the DSTs' annulus spaces (the space between the internal and external tank walls) have been inspected visually since 1992 and with Ultrasonic Testing (UT) since 1996, inspections of the tank bottoms have been able to be conducted due to limitations of available technology, omitting about 40 percent of the tank surface below the maximum fill level from routine inspection. Visual inspections of the tank annulus have been conducted up to five times in some DSTs and portions of the annulus space for all of the DSTs has been inspected twice with UT. This region includes the walls of the primary tank and secondary liner along with accessible portions of the secondary liner bottom. Due to this lack of technology, the degradation of the primary tank bottom in Tank AY-102 was undetected until the tank leaked into its annulus space, confirmed in 2012. Since that time, WRPS has been working with the nondestructive examination community and the Pacific Northwest National Laboratory, to evaluate potential technologies to conduct these challenging remote inspections. Recent work has included the development, testing, and deployment of several remote visual inspection technologies to observe the condition of the primary tank bottom of the DSTs by leveraging air distribution slots in the refractory pad on which it rests. Robotic solutions to conduct this inspection were developed with a detailed understanding of the physical configuration and operational logistics. Understanding and subsequent communication of these details to vendors within the robotics and nondestructive examination community was a critical component to the successful production of these new tools. Throughout the FY16-FY18 years, vendors from nondestructive examination community were solicited for ideas to meet the tank bottom inspection challenge. Two tank bottom visual inspection solutions were then pursued to meet that challenge. Both tools were successfully deployed at Tank AP-107, and provided valuable visuals, never before obtained from the under tank environment of a double-shell tank. While there are minor opportunities for improvement identified with each system, general outcomes were overwhelmingly positive. Both systems were successfully able to navigate the refractory air slot pattern from the outer edge to the tank center and record video footage. The micro-crawler provided high quality and very stable footage through the air slot pattern, but took longer to deploy into the slots and traverse through them than the alternative system. The push-pull tethered camera was able to navigate all seven of its target air slots in a matter of a few hours, which included deployment, movement between slot entrances, and complete removal of the system from the annulus environment. Through these air slots, new information was gained about the tank bottom and refractory pad condition of tank AP-107, AP-106, AP-108, and AN-102. While some debris was noted in the air slots, including sand, chipped refractory, and construction materials, the refractory was found to be structurally stable and adequately supporting the primary tank bottom through the full diameter of the tank. Primary tank bottom steel exterior was found to be in good condition, free of ongoing or aggressive corrosion conditions. Looking toward the future, robotic access to and visual inspection of refractory air slots and the primary tank bottom steel has now proven viable. Incorporating periodic air slot inspections as a regular practice within the Double-Shell Tank Integrity Program is the next step, allowing trending of any changes in condition. As ultrasonic testing infrastructure was leveraged to complete the initial system deployments described in this report, it makes sense to adopt that same strategy for ongoing periodic examinations and deploy these primary tank bottom inspection tools alongside ultrasonic testing operations. Development of visual inspection tools to evaluate the primary tank bottom region of the double-shell tanks was planned as the first stage of inspection. Continued development of volumetric sensors and incorporation of these inspection tools into Hanford's ongoing Double-Shell Tank Integrity Program are the next steps, seeking to continuously expand understanding of asset integrity and remaining useful life. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Pathways to a Sustainable Aviation Ecosystem: Aviation Energy Research and Operation Simulator (AEROSim)

The National Renewable Energy Laboratory (NREL) has developed highly accessible tools for ground vehicle modeling, making it easy to quickly compare powertrains and estimate the impact of technology improvements on fuel/energy consumption, performance, cost, and battery life. With AEROSim, NREL advanced aircraft, enabling the same level of ease and versatility in comparing aircraft designs across a range of scenarios and conditions.

advanced air mobility↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Investigating the impact of environmental factors on West Nile virus human case prediction in Ontario, Canada

West Nile virus is the most common mosquito borne disease in North America and the leading cause of viral encephalitis. West Nile virus is primarily transmitted between birds and mosquitoes while humans are incidental, dead-end hosts. Climate change may increase the risk of human infections as climatic variables have been shown to affect the mosquito life cycle, biting rate, incubation period of the disease in mosquitoes, and bird migration patterns. We develop a zero-inflated Poisson model to investigate how human West Nile virus case counts vary with respect to mosquito abundance and infection rates, bird abundance, and other environmental covariates. We use a Bayesian paradigm to fit our model to data from 2010–2019 in Ontario, Canada. Our results show mosquito infection rate, temperature, precipitation, and crow abundance are positively correlated with human cases while NDVI and robin abundance are negatively correlated with human cases. We find the inclusion of spatial random effects allows for more accurate predictions, particularly in years where cases are higher. Our model is able to accurately predict the magnitude and timing of yearly West Nile virus outbreaks and could be a valuable tool for public health officials to implement prevention strategies to mitigate these outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Microalgal lipids: biochemistry and biotechnology

Microalgae, including cyanobacteria, are a genetically diverse and biochemically diverse group of mostly photosynthetic organisms that can be found in nearly every ecosystem. They produce a broad range of compounds, including structural and bioactive lipids with various roles in the metabolism of the cell and potential applications in biotechnology. Here, the majority of lipids are synthesized in the chloroplast using acetate to produce fatty acids and terpenoids via the acetate pathway and methylerythritol phosphate deoxy-xylulose phosphate pathway, respectively. This review will highlight the major groups of microalgal lipids as well as their applications in food, fuels, and specialty chemicals. Future directions include the development of microalgal chassis organisms and molecular tools to manipulate lipid synthesis for the enhanced production of target metabolites.

cyanobacteria↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗
DOE OSTI2022

Chromosome‐level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates

Summary Thlaspi arvense (field pennycress) is being domesticated as a winter annual oilseed crop capable of improving ecosystems and intensifying agricultural productivity without increasing land use. It is a selfing diploid with a short life cycle and is amenable to genetic manipulations, making it an accessible field‐based model species for genetics and epigenetics. The availability of a high‐quality reference genome is vital for understanding pennycress physiology and for clarifying its evolutionary history within the Brassicaceae. Here, we present a chromosome‐level genome assembly of var. MN106‐Ref with improved gene annotation and use it to investigate gene structure differences between two accessions (MN108 and Spring32‐10) that are highly amenable to genetic transformation. We describe non‐coding RNAs, pseudogenes and transposable elements, and highlight tissue‐specific expression and methylation patterns. Resequencing of forty wild accessions provided insights into genome‐wide genetic variation, and QTL regions were identified for a seedling colour phenotype. Altogether, these data will serve as a tool for pennycress improvement in general and for translational research across the Brassicaceae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The secondary metabolism collaboratory: a database and web discussion portal for secondary metabolite biosynthetic gene clusters

Secondary metabolites are small molecules produced by all corners of life, often with specialized bioactive functions with clinical and environmental relevance. Secondary metabolite biosynthetic gene clusters (BGCs) can often be identified within DNA sequences by various sequence similarity tools, but determining the exact functions of genes in the pathway and predicting their chemical products can often only be done by careful, manual comparative analysis. To facilitate this, we report the first release of the secondary metabolism collaboratory (SMC), which aims to provide a comprehensive, tool-agnostic repository of BGC sequence data drawn from all publicly available and user-submitted bacterial and archaeal genome and contig sources. On the website, users are provided a searchable catalog of putative BGCs identified from each source, along with visualizations of gene and domain annotations derived from multiple sequence analysis tools. SMC’s data is also available through publicly-accessible application programming interface (API) endpoints to facilitate programmatic access. Users are encouraged to share their findings (and search for others’) through comment posts on BGC and source pages. At the time of writing, SMC is the largest repository of BGC information, holding 13.1M BGC regions from 1.3M source sequences and growing, and can be found at https://smc.jgi.doe.gov.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stochastic Techno Economic Model

The Stochastic Techno-Economic Model or STEM is an analytical tool that estimates the logistics cost of different biomass feedstocks by incorporating uncertainty into the modeling framework. The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.

Burli, PralhadH↗
DOE OSTI2022

Economic and embodied energy analysis of integrated circuit manufacturing processes

Integrated circuits (ICs) are the fundamental microelectronic building blocks of typical information and communication technology (ICT) devices such as laptops and smartphone. With the emergence of faster and cheaper low-power ICs for the growing ICT market, there is a limited information on their manufacturing energy and economic impacts owing to the lack of recurrent upgradation of proprietary IC manufacturing process data. In this work, economic and life cycle energy assessments (LCAs) of IC manufacturing and assembly processes were conducted using the latest bill of materials (BOM) manufacturing data in a state-of-the-art IC manufacturing cost software tool developed by IC Knowledge, LLC. IC manufacturing cost was estimated to be $\$$1.00-$\$$5.00/cm 2 ; the high-end cost represents the most advanced 3D NAND IC technology with the Wafer Level Chip Scale Package cost of $4/cm 2 . Total cumulative energy demand (CED) estimates of IC manufacturing using the OpenLCA software ranged from 9 to 38 MJ/cm 2 or 56–235 BJ/month with the largest share (~ 75%) from on-site energy. The IC manufacturing CED is projected to increase with the progress in IC technology node, which has increased by more than two times for technology node evolution from 110 to 14 nm. Furthermore, the representative detailed BOM data were considered to reduce the CED uncertainties of the estimated standard deviation of 35%- 42%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multicriteria-Based Selection of Microalgae Biorefineries: Biomass Composition Defines the Most Suitable Product Portfolios

The supply of microalgae-derived biofuels and bioproducts will be vital in a global-scale bioeconomy. As the diversity of microalgae strains and their compositional plasticity may yield a wide array of products of market interest, the design of effective biorefineries is a central aspect in the path to making microalgae-based products available in the market. In this way, the conversion of microalgae biomass should be planned to employ mature technologies, while maximizing economic and environmental benefits obtained from a diverse product portfolio. This study applied sequential, hybrid Multicriteria Decision Analyses (MCDA) to aid the decision-making process of outlining the most suitable biorefining pathways for specific compositional profiles. For this, the methodology simultaneously considered multiple technical, economic, and environmental criteria, such as market aspects for the main algae-derived products, potential reduction in greenhouse gas (GHG) emissions provided by the biobased alternatives, and technology readiness level of conversion routes, among others. The framework was tested using productivity and compositional data for 13 high-productivity summer strains cultivated under varying nutrient availability. The analysis pointed to compositional profile being a key driver in defining the core biorefining strategy of algae biomass, with lipid-to-carbohydrate ratios higher than roughly 1 warranting the preferential processing of lipids into hydrocarbon fuels with the remainder of the algae biomass compounds being sent to higher-value applications, such as carboxylic acids and renewable thermoplastic substitutes. An in-depth process simulation, techno-economic assessment (TEA), and life-cycle analysis (LCA) effort was carried out as a closing step to corroborate the results stemming from the proposed framework. This study validates the use of MCDAs as a screening method prior to implementing more time-consuming analysis techniques and makes a compelling case for this approach as a product selection tool on a wide range of algae species, thus helping establish species-agnostic (but composition-driven) biorefineries.

biofuels↗
DOE OSTI2021

Efficient facemask decontamination via forced ozone convection

The COVID-19 crisis has taken a significant toll on human life and the global economy since its start in early 2020. Healthcare professionals have been particularly vulnerable because of the unprecedented shortage of Facepiece Respirators (FPRs), which act as fundamental tools to protect the medical staff treating the coronavirus patients. In addition, many FPRs are designed to be disposable single-use devices, creating an issue related to the generation of large quantities of non-biodegradable waste. In this contribution, we describe a plasma-based decontamination technique designed to circumvent the shortages of FPRs and alleviate the environmental problems posed by waste generation. The system utilizes a Dielectric Barrier Discharge (DBD) to generate ozone and feed it through the fibers of the FPRs. The flow-through configuration is different than canonical ozone-based sterilization methods, in which the equipment is placed in a sealed ozone-containing enclosure without any flow through the mask polymer fibers. We demonstrate the rapid decontamination of surgical masks using Escherichia coli ( E. coli ) and Vesicular Stomatitis Virus (VSV) as model pathogens, with the flow-through configuration providing a drastic reduction in sterilization time compared to the canonical approach. We also demonstrate that there is no deterioration in mask structure or filtration efficiency resulting from sterilization. Finally, we show that this decontamination approach can be implemented using readily available tools, such as a plastic box, a glass tube, few 3D printed components, and the high-voltage power supply from a plasma globe toy. The prototype assembled for this study is portable and affordable, with effectiveness comparable to that of larger and more expensive equipment.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quantitative far-infrared band strengths of iodine monochloride (ICl), a molten salt off-gas product

The gaseous (by)products generated from molten salt reactors need to be monitored to prevent the release of potentially toxic gases to the environment. In particular, 129I has a long half-life and its toxicity and persistence in the environment make iodine and iodine-containing compounds (such as ICl from chloride containing molten salt systems) of great concern. Optical spectroscopy tools, including Raman and Fourier-transform infrared (FTIR) spectroscopies, are ideal for monitoring and quantifying such off-gas products. Iodine (I2) has a strong and distinct Raman signature and the change in signal with a change in concentration can be used for quantification of these byproducts. Iodine monochloride (ICl) has distinct signatures in both the Raman and the infrared, and its spectrum can also potentially be used for quantitative measurement of this species. In this paper we discuss our recent results on the quantification of iodine monochloride using infrared spectroscopy, in particular first reports of the absolute infrared band strength of ICl.

infrared (IR) spectroscopy, Molten Salt Reactors, ↗