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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Update: structural uncertainty of used nuclear fuel in dry storage canisters

The Structural Uncertainty research task uses numerical modeling to help close knowledge gaps associated with extended dry storage of used nuclear fuel. Modeling helps to predict the expected range of mechanical loading on used nuclear fuel and dry storage system components, which is needed to help guide materials research. Knowledge of expected loads helps the materials researchers prioritize their research and focus only on the relevant material degradation phenomena that can have an effect on the ability of dry storage systems to function. The loads considered in this task are DSC tip-over, handling drops of the multipurpose fuel canister, and seismic loading of DSC systems while situated on the concrete pad of a storage facility. This document is a progress report that describes the work that was performed in fiscal year 2015. The work is a broad task that considers a number of physical phenomena and uses sophisticated LS-DYNA finite element models to predict used fuel and DSC system response to dynamic loads. Due to the broad list of topics and limited budgets, the topics of this task are prioritized at the beginning of the year and the priorities are subject to revision throughout the year as the Pacific Northwest National Laboratory team collaborates with other members of the Used Fuel Disposition Campaign. This year, three topics were investigated: options for modeling cladding in LS-DYNA, the effect of cladding thinning in the tip-over load case, and stress corrosion cracking in multipurpose canister welds. In each of these cases, significant progress was made. This report details the work that was done and identifies areas where more work is needed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Uncovering universal rules governing the selectivity of the archetypal DNA glycosylase TDG

Thymine DNA glycosylase (TDG) is a pivotal enzyme with dual roles in both genome maintenance and epigenetic regulation. TDG is involved in cytosine demethylation at CpG sites in DNA. Here we have used molecular modeling to delineate the lesion search and DNA base interrogation mechanisms of TDG. First, we examined the capacity of TDG to interrogate not only DNA substrates with 5-carboxyl cytosine modifications but also G:T mismatches and nonmismatched (A:T) base pairs using classical and accelerated molecular dynamics. To determine the kinetics, we constructed Markov state models. Base interrogation was found to be highly stochastic and proceeded through insertion of an arginine-containing loop into the DNA minor groove to transiently disrupt Watson–Crick pairing. Next, we employed chain-of-replicas path-sampling methodologies to compute minimum free energy paths for TDG base extrusion. We identified the key intermediates imparting selectivity and determined effective free energy profiles for the lesion search and base extrusion into the TDG active site. Here, our results show that DNA sculpting, dynamic glycosylase interactions, and stabilizing contacts collectively provide a powerful mechanism for the detection and discrimination of modified bases and epigenetic marks in DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Structure and Dynamics of Domains in Ferroelectric Nanostructures – Phase-Field Modeling (Final Technical Report)

Domain pattern formation is one of the most common phenomena in nature and is a topic of immense interest in many fields ranging from materials science and physics to chemistry and biology. This DOE sponsored research project explored the basic science concerning the thermodynamic stability of mesoscale polarization domain patterns and their temporal evolution mechanisms during formation and subsequent switching in ferroelectric nanostructures and heterostructures. The project employed the computational phase-field method in combination of microelasticity and electrostatic theories. The research was carried out in close collaboration with a number of experimental groups who used High Resolution Transmission Electron Microscopy (HRTEM), in situ TEM with Scanning Probe Microscopy (SPM), or Piezoresponse Force Microscopy (PFM) to characterize the domain structures and dynamics of ferroelectric thin films and heterostructures and who grow high-quality ferroelectric and multiferroic thin films using advanced growth techniques such as Molecular Beam Epitaxy (MBE), Pulsed Laser Deposition (PLLD), and sputtering. The research efforts of the project help establish the phase-field method as the most powerful method for understanding and predicting domain structures in ferroelectric thin films and nanostructures. The findings of the project led to the basic understanding of stability and switching mechanisms of ferroelectric domains under different mechanical boundary conditions and under either homogeneous capacitor configurations or local fields using metallic probes as electrodes and the emergence of charged domain walls during domain switching. The project predicted the spatial length scales, temperature ranges, and electromechanical conditions for different polar states in heterostructures and guided the discovery of both transient and stable novel polarization states containing vortex lattices in oxide superlattices. The project resulted in 134 journal publications and 6 PhD theses with all the PhD graduates currently working in either academia or industry within the United States. The basic understanding on the stability of mesoscale polar states and pattern evolution achieved by the project improved our ability to control and engineer properties of ferroelectric thin films and heterostructures for potential applications in nanoscale electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns, emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1983

NASA/USAF research in structural dynamics

Research in the structural dynamics of large space structures is discussed. The problems of structural response are emphasized. Dynamic modeling, structural members, finite element techniques, axial loads, and vibration tests are among the topics discussed.

Pinson, L. D.↗
NASA NTRS1987

CFD validation experiments at McDonnell Aircraft Company

Information is given in viewgraph form on computational fluid dynamics (CFD) validation experiments at McDonnell Aircraft Company. Topics covered include a high speed research model, a supersonic persistence fighter model, a generic fighter wing model, surface grids, force and moment predictions, surface pressure predictions, forebody models with 65 degree clipped delta wings, and the low aspect ratio wing/body experiment.

Verhoff, August↗
DOE OSTI2018

Summer Workshops on Climate Change Impacts and Integrated Assessment of Climate Change (Final Technical Report)

This grant supported a long sequence of summer workshops in Snowmass, Colorado that began in 1996. The last workshop in this sequence was held in the summer of 2016. This annual event was a centerpiece in the Department of Energy’s support for the creation and maintenance of a community of practice in integrated multi-sector dynamics research and modeling. These workshops brought together key members of the multi-sector dynamics modeling community with other researchers engaged in relevant research on multi-sector (energy, water, land, etc., dynamics) research to participate in discussions of cutting-edge research topics and develop collaborative approaches for addressing open research challenges. This grant provided funds to leverage BER and other federal research investments in the development of appropriate multi-sector dynamics modeling methods by expanding interactions and promoting collaborations between the community of researchers engaged in this research and those involved in other energy and environmental systems research programs. This process is augmented through various outreach activities including periodic presentations and web-based and other internet-based methods for disseminating key scientific findings and to otherwise engage broader participation in pre- and post-workshop discussions and information exchange. The main goals of the summer workshop series were to: Build and support an integrated multi-sector dynamics (iMSD)research community of practice; Infuse best-in-class science into iMSD research activities; Exchange international iMSD research perspectives and information; Accelerate research integration among the iMSD, the sectoral impacts, and earth and environmental systems modeling communities; Develop collaborative scientific perspectives on significant iMSD research challenges; Build collaborations in addressing the challenges; and Develop processes to share information more broadly within the iMSD and the associated family of research communities. The funding provided for this workshop series has helped the energy and environmental systems modeling research community in general - and the multi-sector dynamics research community in particular - make progress on addressing these and other significant research and community building challenges.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Passive dynamic controllers for non-linear mechanical systems

The objective is to develop active model-independent controllers for slewing and vibration control of nonlinear multibody flexible systems, including flexible robots. The topics are presented in viewgraph form and include: passive stabilization; work-energy rate principle; Liapunov theory; displacement feedback; dynamic controller; displacement and acceleration feedback; velocity feedback; displacement feedback; physical interaction; a 6-DOF robot; and simulation results.

Jer-Nan Juang↗
DOE OSTI2017

Development and Assessment of CTFFuel

This milestone report documents an approach that seeks to develop a standalone fuel solver to simulate steady-state and transient thermo-mechanical responses of light-water reactor fuel rods and assess its temperature predictions against analytical solutions, and a well-known and validated fuel performance code. This manuscript focuses on five major topics: (1) development of the CTFFuel, (2) discussion of the newly implemented fuel deformation models in dynamic gap conductance model of CTFFuel, (3) enabling the dynamic gap conductance model in VERA-CS, (4) verification of the solid conduction solution and comparison of the CTFFuel with respect to the workhorse code, CTF, and (5) benchmark of the thermal conductivity degradation using the burnup dependent fuel thermal conductivity models and benchmark of the fuel centerline temperature using the dynamic gap conductance model with Halden measurements and FRAPCON-4.0 simulation results. CTFFuel temperature predictions are compared to predictions from FRAPCON-4.0 for UO 2 , UO 2 +Gd 2 O 3 and MOX fuels through reactor’s life. The main motivation is to understand discrepancies between CTFFuel and FRAPCON-4.0’s temperature predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1990

Active damping in a flexible manipulator

Viewgraphs on active damping in a flexible manipulator are presented. Topics covered include: Shuttle Remote Manipulator System (SRMS); flexible structures; vibration; modeling of a flexible manipulator dynamical structure; designing control law criterion that minimizes vibration; and candidate application of fuzzy logic control law to the problem.

Pham, Trung T.↗
NASA NTRS1984

Pilot modeling, modal analysis, and control of large flexible aircraft

The issues to be addressed are threefold. The first deals with the question of whether dynamic aeroelastic effects can significantly impact piloted flight dynamics. For example, if one were to explore this problem experimentally, what mathematical model would be appropriate to use in the simulation? What modes, for example, should be included in the simulation, or what linear model should be used in the control synthesis? The second question deals with the appropriate design criteria or design objectives. In the case of active control, for example, what would be the design objectives for the control synthesis if aeroelastic effects are a problem? The outline of the topics includes a description of a model analysis methodology aimed at answering the question of the significance of higher order dynamics. Secondly, a pilot vehicle analysis of some experimental data addresses the question of ""What's important in the task?'' The experimental data will be presented briefly, followed by the results of an open-loop modal analysis of the generic vehicle configurations in question. Finally, one of the vehicles will be augmented via active control and the results presented.

Schmidt, D. K.↗
DOE OSTI2021

cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1988

Domain decomposition algorithms and computation fluid dynamics

In the past several years, domain decomposition was a very popular topic, partly motivated by the potential of parallelization. While a large body of theory and algorithms were developed for model elliptic problems, they are only recently starting to be tested on realistic applications. The application of some of these methods to two model problems in computational fluid dynamics are investigated. Some examples are two dimensional convection-diffusion problems and the incompressible driven cavity flow problem. The construction and analysis of efficient preconditioners for the interface operator to be used in the iterative solution of the interface solution is described. For the convection-diffusion problems, the effect of the convection term and its discretization on the performance of some of the preconditioners is discussed. For the driven cavity problem, the effectiveness of a class of boundary probe preconditioners is discussed.

Chan, Tony F.↗
DOE OSTI2022

Learning Global Proliferation Expertise Evolution Using AI-Driven Analytics and Public Information

Detecting and anticipating global proliferation expertise and capability evolution from unstructured, noisy, and incomplete public data streams is a highly desired, but extremely challenging task. Here, in this article, we present our pioneering data-driven approach to support the non-proliferation mission to detect and explain the evolution of proliferation expertise and capability development globally from terabytes of publicly available information (PAI), focusing on our knowledge extraction pipeline and descriptive analytics. We first discuss how we fuse nine open-source data streams, including multilingual data, to convert 4 TB of unstructured data to structured knowledge and encode dynamically evolving proliferation expertise representations—content and context graphs. For this, we rely on natural language processing (NLP) and deep learning (DL) models to perform information extraction, topic modeling, and distributed text representation (aka embedding) learning. We then present interactive, usable, and explainable descriptive analytics to refine domain knowledge and present it in a human-understandable form. Finally, we introduce future work avenues that will leverage our dynamic knowledge representations and descriptive analytics to enable predictive and prescriptive inferences to achieve real-time domain understanding and contextual reasoning about global proliferation expertise and capability evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRSDate not supplied

Regional and Seasonal Trends in Tropical Ozone from SHADOZ Profiles: Reference for Models and Satellite Products

Understanding lowermost stratosphere (LMS) ozone variability is an important topic in the trends and climate assessment communities because of feedbacks among changing temperature, dynamics, water vapor and ozone. LMS evaluations are usually based on satellite observations. Free tropospheric (FT) ozone assessments typically rely on profiles from commercial aircraft. Ozonesonde measurements constitute an independent dataset encompassing both LMS and FT. We used Southern Hemisphere Additional Ozonesondes (SHADOZ) data from 1998-2019 in the GSFC Multiple Linear Regression (MLR) model to analyze monthly mean FT and LMS ozone across five well-distributed tropical sites, three based on combination of nearby individual stations (Figure 1). Our findings: (1) both FT (defined as 5-15 km) and LMS (15-20 km) ozone trends exhibit marked regional and seasonal variability. (2) Stations with the largest FT ozone increases, in the equatorial Americas and western Pacific/east Indian Ocean, show these trends most strongly in February-May when there is convectively-driven wave activity. (3) LMS ozone losses are greatest in the 2nd half of the year (solid lines in Figure 2) when the losses are correlated with an increase in tropopause height (TH) as derived from SHADOZ radiosonde data. ( 4) When the upper FT and LMS are defined by tropopause-relative coordinates, the LMS ozone trend calculated by MLR becomes insignificant, as shown in the dashed lines in Figure 2. Thus, the 20-year decline in tropical LMS ozone reported in recent satellite- and model-based studies does not point to a chemical loss but is rather a signature of a tropopause that has been perturbed by a changing climate. Output based on our regional and monthly averaged FT and LMS ozone trends will be available as a reference for satellite- and model-based analyses.

Free Tropospheric (FT) ozone assessments↗
DOE OSTI2024

Light Water Reactor Sustainability Program: Use of Time Distributions to Predict Operator Procedure Performance in Dynamic Human Reliability Analysis

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework affords software capable of conducting human reliability analysis (HRA) using a dynamic approach built around operating procedures (OPs) from nuclear power plants (NPPs). Previous HUNTER reports document the development of this software tool, the coupling of HUNTER to the simulator code, the collection of operator performance data by using simulators to calibrate HUNTER models, and linking HUNTER to probabilistic risk assessment (PRA) software. The present report largely addresses two topics. The first is a new function in HUNTER called the HUNTER Procedure Performance Predictor (P3). HUNTER P3 uses HUNTER’s built in Monte Carlo tools featuring human performance variability to identify potential error traps in procedures. The second topic is time distribution analysis to generate time inputs for dynamic HRA. The current analysis was performed to investigate time distributions for task primitives, which are the minimum task unit of analysis used in dynamic HRA modeling. Using the time distribution data, the elapsed time for human actions in an extended loss of AC power (ELAP) scenario is then investigated. Time data and prediction are essential for modeling procedure performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗