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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

High Sensitivity of Mobile Phone Microscopy Screening for Schistosoma haematobium in Azaguié, Côte d’Ivoire

Schistosomiasis infections continue to impact African settings disproportionately, and there is an urgent need for novel tools to evaluate infection control and elimination strategies at the community level. Mobile phone microscopes are portable and semiautomated devices with multiple applications for screening neglected tropical diseases. In a community-based schistosomiasis screening program in Azaguié, Côte d’Ivoire, mobile phone microscopy demonstrated a sensitivity of 85.7% (95% CI: 69.7–95.2%) and specificity of 93.3% (95% CI: 87.7–96.9%) for Schistosoma haematobium identification compared with conventional light microscopy, and 95% sensitivity (95% CI: 74.1–99.8%) with egg concentrations of five or more per 10 mL of urine. Mobile phone microscopy is a promising tool for schistosomiasis control and elimination efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

INTERFUEL: FAST - FY 2020 Federal Fleet Dataset [Slides]

This presentation provides an overview of the fiscal year (FY) 2020 federal motor vehicle fleet dataset collected through the Federal Automotive Statistical Tool (FAST). FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles. The presentation discusses the size of the dataset; a high-level look at what the information collected shows about the makeup and operation of the federal motor vehicle fleet during FY 2020 and how that compares with recent years; the process used to review the agency submissions comprising the dataset and the impact of some of the agency-provided corrections to identified issues; activities following the finalization of the dataset.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Deployment and Overview of RAVEN Capabilities for a Probabilistic Risk Assessment Demo for a PWR Station Blackout

Starting in 2012, Idaho National Laboratory (INL) has been engaged to provide tools and methodologies to support a new approach to safety assessment and management of safety related issues for Nuclear Power Plants (NPPs). This activity is placed under the Risk Informed Safety Margin Characterization (RISMC) [2] umbrella that is one of the technical paths of the Department Of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. RISMC takes a broader approach to risk evaluation by generating more comprehensive information. This information is used to gain a more accurate estimation of risk margins and to highlight feasible improvements that seek the optimal point between risk mitigation and economical viability of the nuclear energy option. This is, of course, done without taking any judgmental approach with respect to risk, which is a regulatory body task, and the economical viability, which is up to the single states and the open electricity market. RISMC is therefore composed of methodologies and tools. The augmented information that RISMC seeks to generate, as enabling decision tool, is not holistic with respect all possible metrics and operational aspects of a power plant; it is rather channeled toward the improvement of safety and the associated economical impact. While these are indeed two very broad metrics, they still allow a focus within the development of the underlying tools that, in a resource constrained environment (DOE founding, computational, mathematical) maximize the benefit of the program to the nuclear industry.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Rules and Tools Crosswalk: A Compendium of Computational Tools to Support Geologic Carbon Storage Environmentally Protective UIC Class VI Permitting

This report identifies computational tools useful for addressing aspects of the dedicated carbon storage (Class VI) well permit application under the U. S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) Program. The survey was conducted by researchers of the National Energy Technology Laboratory’s (NETL) Research and Innovation Center in collaboration with representatives of the U.S. EPA, Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL), and the four Regional Initiatives to Accelerate Carbon Capture, Utilization, and Storage: Carbon Utilization and Storage Partnership of the Western United States (CUSP), Plains CO 2 Reduction Partnership Initiative to Accelerate Carbon Capture, Utilization, and Storage Deployment (PCOR Partnership), Midwest Regional Carbon Initiative (MRCI), and the Southeast Regional Carbon Utilization and Storage Partnership (SECARB-USA). A total of 59 tools were identified through the elicitation for this report. It is intended to serve as a reference that can be used by geologic carbon storage stakeholders to identify computational tools that may be used to develop Class VI permit applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Household Energy Burden in Beacon Hill, Seattle, WA [Slides]

This technical assistance is part of the Communities Local Energy Action Program (CLEAP) for the Beacon Hill, Seattle, Washington community coalition consisting of El Centro de la Raza, Beacon Hill Council and Bethany United Church of Christ with supportive partners, Seattle City Light and the Seattle Office of Sustainability and Environment. This report uses the Low-Income Energy Affordability Data (LEAD) Tool to identify the most energy burdened households by income group, building type, building age and fuel type.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

COnTORT: COmprehensive Transcriptomic ORganizational Tool for Simultaneously Retrieving and Organizing Numerous Gene Expression Data Sets from the NCBI Gene Expression Omnibus Database

We introduce COnTORT ( CO mprehensive T ranscriptomic OR ganizational T ool), a publicly available program that retrieves all available gene expression data and associated metadata for an organism from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. The data are compiled into text files that can be used for downstream bioinformatic applications.

Myers, Kevin S.↗
DOE OSTI2018

Verification and Validation of Optimization of Replacement Portal Monitoring Replay Tools

The Los Alamos National Laboratory and the Johns Hopkins Applied Physics Laboratory (APL) are both developing optimization software to fulfill the objective of Phase III of the Replacement Portal Monitoring (RPM) Program for the Department of Homeland Security. The objective of the Phase III of the RPM Program is to conduct an evaluation of three RPM systems designed to enhance mission effectiveness, gain operational efficiencies, and to address emerging mission needs against the Countering Weapons of Mass Destruction (CWMD ) nuclear threat basis and special nuclear material (SNM) used in performance testing. As such this task involves the use of global optimization algorithms.

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

DCA_Tools

HPC software for ab-initio, condensed-matter physics, quantum mechanics calculations needs to be built on top of well tested libraries some of which address requirements unique to the programming domain. During the development of the DCA++ code, that we use in our research, we have developed a collection of libraries that may be of use to other computational scientists working in the same or similar domains. The libraries include: a) a pythonic input-language system, b) tensors whose shape is constructed from generalized dimension objects such at time domains. frequency domains, momentum domains, vertex domains et. al. and c) linear algebra operations that resolve to BLA/LAPACK operations when possible. This supports the implementation of Greens functions and operations on them such as are used in condensed matter physics.

Summers, Michael S↗
DOE OSTI2024

NSUF FY24 Program Overview and Updates

The Nuclear Science User Facilities (NSUF) is one of a diverse number of U.S. Department of Energy (DOE) user facilities established to provide researchers with the most advanced tools of modern science. The NSUF was established to provide access to unique capabilities to a broad range of researchers to address the important issues relevant to irradiation effects in nuclear fuels and materials. The NSUF represents a consortium of capabilities distributed across the U.S. at twenty institutions. The NSUF is centered at the Idaho National Laboratory, but it coordinates activities at nineteen “partner” institutions. These institutions have capabilities that include neutron, ion, and gamma irradiation, hot cells, advanced material characterization, and high-performance computing. The NSUF goal is to provide access these capabilities at no cost to nuclear energy researchers to produce the highest quality research results to increase understanding of advanced nuclear energy technologies important to DOE-NE.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Institute for Sustained Performance, Energy, and Resilience (SuPER)

The University of Tennessee (UTK) and University of Texas at El Paso (UTEP) partnership supported the three main thrusts of the SUPER project---performance, energy, and resilience. The UTK-UTEP effort thus helped advance the main goal of SUPER, which was to ensure that DOE's computational scientists can successfully exploit the emerging generation of high performance computing (HPC) systems. This goal is being met by providing application scientists with strategies and tools to productively maximize performance, conserve energy, and attain resilience. The primary vehicle through which UTK provided performance measurement support to SUPER and the larger HPC community is the Performance Application Programming Interface (PAPI). PAPI is an ongoing project that provides a consistent interface and methodology for collecting hardware performance information from various hardware and software components, including most major CPUs, GPUs and accelerators, interconnects, I/O systems, and power interfaces, as well as virtual cloud environments. The PAPI software is widely used for performance modeling of scientific and engineering applications---for example, the HOMME (High Order Methods Modeling Environment) climate code, and the GAMESS and NWChem computational chemistry codes---on DOE supercomputers. PAPI is widely deployed as middleware for use by higher-level profiling, tracing, and sampling tools (e.g., CrayPat, HPCToolkit, Scalasca, Score-P, TAU, Vampir, PerfExpert), making it the de facto standard for hardware counter analysis. PAPI has established itself as fundamental software infrastructure in every application domain (spanning academia, government, and industry), where improving performance can be mission critical. Ultimately, as more application scientists migrate their applications to HPC platforms, they will benefit from the extended capabilities this grant brought to PAPI to analyze and optimize performance in these environments, whether they use PAPI directly, or via third-party performance tools. Capabilities added to PAPI through this grant include support for new architectures such as the lastest GPU and Xeon Phi accelerators, and advanced power measurement and management features. Another important topic for the UTK team was providing support for a rich ecosystem of different fault management strategies in the context of parallel computing. Our long term efforts have been oriented toward proposing flexible strategies and providing building boxes that application developers can use to build the most efficient fault management technique for their application. These efforts span across the entire software spectrum, from theoretical models of existing strategies to easily assess their performance, to algorithmic modifications to take advantage of specific mathematical properties for data redundancy and to extensions to widely used programming paradigms to empower the application developers to deal with all types of faults. We have also continued our tight collaborations with users to help them adopt these technologies to ensure their application always deliver meaningful scientific data. Large supercomputer systems are becoming more and more power and energy constrained, and future systems and applications running on them will need to be optimized to run under power caps and/or minimize energy consumption. The UTEP team contributed to the SUPER energy thrust by developing power modeling methodologies and investigating power management strategies. Scalability modeling results showed that some applications can scale better with respect to an increasing power budget than with respect to only the number of processors. Power management, in particular shifting power to processors on the critical path of an application execution, can reduce perturbation due to system noise and other sources of runtime variability, which are growing problems on large-scale power-constrained computer systems.

42 ENGINEERING↗
DOE OSTI2025

Pressure Gain, Stability, and Operability of Methane/Syngas Based RDEs Under Steady and Transient Conditions (Final Project Report)

The scope of this work addresses key issues associated with losses associated with the detonation wave and other processes internal to the RDE operation, as well as it develops modeling tools for the evaluation of these losses and exhaust emissions in RDEs. The main challenge in studying RDEs is that RDE performance is highly reliant on the specifics of the design so much so that simple/canonical systems alone cannot provide useful engineering information, but practical RDE designs are sufficiently complex and involve extreme operational environments that detailed access either experimentally (laser diagnostics, for instance) or computationally (direct numerical simulations) are as yet to become practical. To overcome this challenge, we have conducted a combined experimental/simulation/analytical study investigating key phenomena that control the characteristics of operation of RDEs. As a result, the study has developed tools and methods that can be used to evaluate performance and design approaches using reduced-physics models, with the assumptions validated using detailed simulations, and the model prediction tested using experimental observations. The specific objectives of the research were: (1) Develop and demonstrate a low-loss fully axial injection concept, taking advantage of stratification effects to alter the detonation structure and position the wave favorably within the combustor; (2) Obtain stability and operability characteristics of an RDE across operating conditions to aid in the development of operability and performance rules for the operations of other systems; and (3) Develop quantitative metrics for performance gain as well as quantitative description of the loss mechanisms through a combination of diagnostics development, reduced-order modeling, and detailed simulations. The work conducted here has made contribution on design of low-loss inlets that has broad application within the power generation industry for use with pressure gain combustion. The operability and stability of different designs, while focusing on axial air inlet designs, has been analyzed. The effect of nozzle and injection conditions was studied. Models and simulations of exhaust emissions, focusing on NOx emission has been developed and used to investigate how operation of the RDE affect NOx production using Lagrangian analysis of RDE simulations. This work has built on previous programs, with the goal of further understanding operation of RDEs and elevate the readiness of design consideration. In addition, a suite of diagnostic and modeling tools have been developed to obtain quantitative metrics on performance based on measurements, which can be readily transferred to other experimental configurations.

08 HYDROGEN↗
DOE OSTI2022

A combined experimental and numerical approach that eliminates the non-uniqueness associated with the Johnson-Cook parameters obtained using inverse methods

Abstract Johnson-Cook constitutive model is a commonly used material model for machining simulations. The model includes five parameters that capture the initial yield stress, strain-hardening, strain-rate hardening, and thermal softening behavior of the material. These parameters are difficult to determine using experiments since the conditions observed during machining (such as high strain-rates of the order of $$10^5$$ 10 5 /sec - $$10^6$$ 10 6 /sec) are challenging to recreate in the laboratory. To address this problem, several researchers have recently proposed inverse approaches where a combination of experiments and analytical models are used to predict the Johnson-Cook parameters. The errors between the measured cutting forces, chip thicknesses and temperatures and those predicted by analytical models are minimized and the parameters are determined. In this work, it is shown that only two of the five Johnson-Cook parameters can be determined uniquely using inverse approaches. Two different algorithms, namely, Adaptive Memory Programming for Global Optimization (AMPGO) and Particle Swarm Optimization (PSO), are used for this purpose. The extended Oxley’s model is used as the analytical tool for optimization. For determining a parameter’s value, a large range for each parameter is provided as an input to the algorithms. The algorithms converge to several different sets of values for the five Johnson-Cook parameters when all the five parameters are considered as unknown in the optimization algorithm. All of these sets, however, yield the same chip shape and cutting forces in FEM simulations. Further analyses show that only the strain-rate and thermal softening parameters can be determined uniquely and the three parameters present in the strain-hardening term of the Johnson-Cook model cannot be determined uniquely using the inverse method. A combined experimental and numerical approach is proposed to eliminate this determine all parameters uniquely.

42 ENGINEERING↗
DOE OSTI2019

Fluorine-programmed nanozipping to tailored nanographenes on rutile TiO 2 surfaces

The rational synthesis of nanographenes and carbon nanoribbons directly on nonmetallic surfaces has been an elusive goal for a long time. In this paper, we report that activation of the carbon (C)–fluorine (F) bond is a reliable and versatile tool enabling intramolecular aryl-aryl coupling directly on metal oxide surfaces. A challenging multistep transformation enabled by C–F bond activation led to a dominolike coupling that yielded tailored nanographenes directly on the rutile titania surface. Because of efficient regioselective zipping, we obtained the target nanographenes from flexible precursors. Fluorine positions in the precursor structure unambiguously dictated the running of the “zipping program,” resulting in the rolling up of oligophenylene chains. Finally, the high efficiency of the hydrogen fluoride zipping makes our approach attractive for the rational synthesis of nanographenes and nanoribbons directly on insulating and semiconducting surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A County-Level Program to Assess Farming System Ecosystem Services

The survival of Florida’s biodiversity and economy is dependent on finding ways to balance farm economics with proper management of water and other natural resources. Taking on this challenge of maximizing the delivery of ecosystems services from agricultural production systems is the mandate of the Hendry County Sustainable Biofuels Center. Given that sea level rise is the overarching, long-term threat to the south Florida and its ecosystems, the most valuable ecosystems services for the state of Florida are those that mitigate climate change. Biofuels are put forward as one approach to forestalling climate change, but its value as an industry in providing this and other ecosystem services is unproven. The Sustainable Biofuels Center has developed a set of programs to both document and enhance the ecosystems services values of the evolving Florida biofuels industry. The Center engages in agricultural systems evaluation, sustainability indexing and sustainability research. Methods employed for documenting ecosystems services and costs include Life Cycle Assessment, Emergy Analysis, and optimization of cost-benefit functions. Radically new farming and economic compensation systems must be created and implemented if we are to achieve a successful agricultural business model built upon balanced revenue streams from these varied services. Accordingly, the Center also supports field research and demonstration projects to document the capacity for innovative farming systems to deliver ecosystems services such as water storage. To help promote the inclusion of ecosystems services considerations in farm operations, the program includes curriculum development at both the K-12 and college level, as well as programs to bring diverse stakeholders in to collaborative visioning process. Lastly, since county governments are often the level where new industry seek entry to the landscape, the Center is also developing metrics and tools through which economic development officers can evaluate business developer requests for tax breaks, land use changes and various other permissions and incentives against the economic and ecological benefits as well as any natural resource costs. Solving the underlying problem requires that agricultural lands provide society with a more balanced set of values in the form of food, energy, and ecosystem services through proper water, nutrient, and soil management. County-level programs can help realize that vision.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assessment of Physical Security Modeling and Simulation in the Vulnerability Assessment Process

This report provides a comprehensive assessment of physical security modeling and simulation tools available for use in the vulnerability assessment (VA) process for nuclear facilities. It outlines the historical evolution of VA methodologies, emphasizing the transition from traditional layer-based approaches to a more holistic framework that integrates detection probabilities directly into combat simulations. The document details the critical components of the VA process, including the characterization of targets, threats, and protective measures, as well as the development of adversary scenarios that reflect both insider and outsider threats. It highlights the importance of performance assurance programs, emphasizing the need for continuous evaluation and testing of security systems to ensure their effectiveness against evolving threats. Additionally, the report discusses the significance of utilizing accredited modeling and simulation tools in accredited areas to accurately represent adversary actions and the corresponding responses of protective forces. By establishing a systematic approach to VA, this document aims to enhance the overall security posture of nuclear facilities, ensuring compliance with regulatory standards while effectively mitigating risks associated with potential adversarial actions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2012

Radioactive Waste Characterization Strategies; Comparisons Between AK/PK, Dose to Curie Modeling, Gamma Spectroscopy, and Laboratory Analysis Methods- 12194

In the coming fiscal years of potentially declining budgets, Department of Energy facilities such as the Los Alamos National Laboratory (LANL) will be looking to reduce the cost of radioactive waste characterization, management, and disposal processes. At the core of this cost reduction process will be choosing the most cost effective, efficient, and accurate methods of radioactive waste characterization. Central to every radioactive waste management program is an effective and accurate waste characterization program. Choosing between methods can determine what is classified as low level radioactive waste (LLRW), transuranic waste (TRU), waste that can be disposed of under an Authorized Release Limit (ARL), industrial waste, and waste that can be disposed of in municipal landfills. The cost benefits of an accurate radioactive waste characterization program cannot be overstated. In addition, inaccurate radioactive waste characterization of radioactive waste can result in the incorrect classification of radioactive waste leading to higher disposal costs, Department of Transportation (DOT) violations, Notice of Violations (NOVs) from Federal and State regulatory agencies, waste rejection from disposal facilities, loss of operational capabilities, and loss of disposal options. Any one of these events could result in the program that mischaracterized the waste losing its ability to perform it primary operational mission. Generators that produce radioactive waste have four characterization strategies at their disposal: - Acceptable Knowledge/Process Knowledge (AK/PK); - Indirect characterization using a software application or other dose to curie methodologies; - Non-Destructive Analysis (NDA) tools such as gamma spectroscopy; - Direct sampling (e.g. grab samples or Surface Contaminated Object smears) and laboratory analytical; Each method has specific advantages and disadvantages. This paper will evaluate each method detailing those advantages and disadvantages including; - Cost benefit analysis (basic materials costs, overall program operations costs, man-hours per sample analyzed, etc.); - Radiation Exposure As Low As Reasonably Achievable (ALARA) program considerations; - Industrial Health and Safety risks; - Overall Analytical Confidence Level. The concepts in this paper apply to any organization with significant radioactive waste characterization and management activities working to within budget constraints and seeking to optimize their waste characterization strategies while reducing analytical costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Improving Ligand Geometry in Protein Data Bank Structures Computationally

Information about the three‐dimensional structures of complex biological molecules is an indispensable research tool for many fields of study, including biology, chemistry, pharmacology, and computer science. The Protein Data Bank (PDB) is an public digital archive providing access to structures of nucleic acids, proteins, and large macromolecular machines determined experimentally by X‐ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and 3‐dimensional electron microscopy (3DEM). PDB structures undergo validation for structural plausibility upon their deposition into the PDB using the program Mogul, which cross references each deposited structure against similar data in the Cambridge Structural Database (CSD). Ligands associated with PDB structures are a common source of structural inaccuracy. In this study, a programmatic pipeline was developed to determine if ligand geometric accuracy could be improved using known computational tools. Ligands with dubious geometry were identified through a Python mining code. A sample set of the identified structures was remodeled into minimum energy conformations using the molecular dynamics program AMBER and then fit to the original experimental density maps using the molecular modeling program Coot. The refined models were compared to the original models in the PDB as well as to similar structures in the CSD using the deposition statistical validation server. Preliminary results suggest that the pipeline effectively identifies and improves ligand structures that possess inaccurate geometry. This method can be used to evaluate and improve the accuracy of specific ligands in structures both archived and pending deposition. Support or Funding Information This work was supported by an NSF REU and the RCSB PDB [NSF (DBI‐1338415), NIH, and DOE.] This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Miller, Beck↗