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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Overview of the TriBITS Lifecycle Model: Lean/Agile Software Lifecycle Model for Research-based Computational Science and Engineering Software

Software lifecycles are becoming an increasingly important issue for computational science & engineering (CSE) software. The process by which a piece of CSE software begins life as a set of research requirements and then matures into a trusted high-quality capability is both commonplace and extremely challenging. Although an implicit lifecycle is obviously being used in any effort, the challenges of this process--respecting the competing needs of research vs. production--cannot be overstated. Here we describe a proposal for a well-defined software lifecycle process based on modern Lean/Agile software engineering principles. What we propose is appropriate for many CSE software projects that are initially heavily focused on research but also are expected to eventually produce usable high-quality capabilities. The model is related to TriBITS, a build, integration and testing system, which serves as a strong foundation for this lifecycle model, and aspects of this lifecycle model are ingrained in the TriBITS system. Indeed this lifecycle process, if followed, will enable large-scale sustainable integration of many complex CSE software efforts across several institutions.

Agile↗
DOE OSTI2012

TriBITS Lifecycle Model: A Lean/Agile Software Lifecycle Model for Research-based Computational Science and Engineering and Applied Mathematical Software (V.1.0)

Software lifecycles are becoming an increasingly important issue for computational science and engineering (CSE) software. The process by which a piece of CSE software begins life as a set of research requirements and then matures into a trusted high-quality capability is both commonplace and extremely challenging. Although an implicit lifecycle is obviously being used in any effort, the challenges of this process - respecting the competing needs of research vs. production - cannot be overstated. Here we describe a proposal for a well-defined software lifecycle process based on modern Lean/Agile software engineering principles. What we propose is appropriate for many CSE software projects that are initially heavily focused on research but also are expected to eventually produce usable high-quality capabilities. The model is related to TriBITS, a build, integration and testing system, which serves as a strong foundation for this lifecycle model, and aspects of this lifecycle model are ingrained in the TriBITS system. Here, we advocate three to four phases or maturity levels that address the appropriate handling of many issues associated with the transition from research to production software. The goals of this lifecycle model are to better communicate maturity levels with customers and to help to identify and promote Software Engineering (SE) practices that will help to improve productivity and produce better software. An important collection of software in this domain is Trilinos, which is used as the motivation and the initial target for this lifecycle model. However, many other related and similar CSE (and non-CSE) software projects can also make good use of this lifecycle model, especially those that use the TriBITS system. Indeed this lifecycle process, if followed, will enable large-scale sustainable integration of many complex CSE software efforts across several institutions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Model-Data Fusion Approaches for Retrospective and Predictive Assessment of the Pan-Arctic Scale Permafrost Carbon Feedback to Global Climate

Policy decisions regarding climate change mitigation and adaptation rely on having reliable projections of future climate change. Coupled climate-carbon models predict that the northern high latitudes will serve as a substantial land carbon sink during the 21stcentury, but these models lack many of the key processes governing high-latitude ecosystem processes. Arctic tundra and boreal forests are unique from other biomes particularly because of the presence of snow, ice and frozen ground, and it is important to understand the mechanisms that drive interconnected processes in these landscapes. Increasing our confidence in climate projections requires an integrated approach where existing, on-going and planned observational and experimental studies of high-latitude ecosystem processes are organized and analyzed in a framework designed to target improvements in understanding key ecosystem-climate feedbacks. For this project we designed an approach to improve our scientific understanding of the permafrost carbon feedback through broad-scale assessment of the drivers and responses of the Arctic system carbon cycle using data-driven models of simple-to-intermediate complexity. The made a valuable contribution to the first of its kind, data-driven quantitative assessment of the impact of permafrost thaw on pan-Arctic scale carbon cycle feedbacks to the global climate system. The approach drew on a conceptual framework for integrating the key system components and their underlying data within a “book-keeping” framework for assessment of the key processes driving the permafrost carbon feedback. The results provided quantitative model-data benchmarking to constrain future projections of carbon cycle responses to a warming Arctic. The framework used environmental proxy data sets examining recent-era geomorphologic land-form transitions and vegetation dynamics, through remotely-sensed data, to guide the extrapolation of site-based data on the key system components to larger regions. These products contribute to the development of finer-scale, more complex representation of permafrost carbon processes in terrestrial biogeochemistry models, to operate within coupled Earth system modeling frameworks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Microstructure Aware Plasticity Model: Formulation and Usage Guide

Herein, the formulation, parameter sensitivities, and usage methods for the Microstructure-Aware Plasticity (MAP) model are presented. This document is intend to serve as a reference for the underlying theory that constitutes the MAP model and as a practical guide for analysts and future developers on how aspects of this material model influence generalized mechanical behavior.

42 ENGINEERING↗
DOE OSTI2018

Crashworthiness Models for Automotive Batteries

Safety is a key element of any device designed to store energy, particularly of electrochemical batteries, which convert energy of chemical reactions to electrical energy. Safety considerations are especially important when applied to large automotive batteries designed for propulsion of electric vehicles (EV). The high amount of energy stored in EV battery packs translates to higher probability of fire in case of severe deformation of battery compartment due to automotive crash or impact caused by road debris. While such demand for safety has resulted in heavier protection of battery enclosure, the mechanisms leading to internal short circuit due to deformation of the battery are not well understood even on the level of a single electrochemical cell. Moreover, not all internal shorts result in thermal runaway, and thus a criterion for catastrophic failure needs to be developed. This report summarizes the effort to pinpoint the critical deformation necessary to trigger a short via experimental study on large format automotive Li-ion cells subjected to large deformations as those occurring in deformation of battery module or pack. Mechanical properties of cell components were determined via experimental testing and served as input for constitutive models of Finite Element (FE) analysis. It has been rationalized that long-range stress fields occurring in spherical indentation of battery modules would trigger different deformation and failure scenarios compared to indentation of a single cell supported by a rigid flat surface. In order to investigate large deformations characteristic of battery module, a custom experimental set up has been built where the pouch cell was deformed against a compliant backing, which was represented by a ballistic clay. Experiments were also conducted on deformation of stacks of 10 pouch cells, - configuration representing half-module in Ford Focus EV battery pack without cooling plates and structural components. Comparison of the results shows promise for the compliant backing setup for safety evaluation of battery cells under more realistic conditions compared to indentation of single cell against undeformable backing where compression and electrode particle penetration through separator could be the major mechanism for short circuit.

25 ENERGY STORAGE↗
DOE OSTI2021

Network Based Estimation of Wind Farm Power and Velocity Data Under Changing Wind Direction

This paper describes an estimation algorithm for velocity and power output signals in a wind farm under changing wind direction. A graph-theoretic definition describes the wind farm as a collection of nodes (turbines) and time-varying weighted edges (inter-turbine wake propagation) that change as a function of incoming wind direction. The velocity at each turbine is determined through a discrete input-output model. Changes in wind direction serve as the input and the output is defined in terms of a time-varying weighted adjacency matrix that depends on the time-delay of information propagation between turbines. These delays, which are defined in terms of the advection speed of the wind and the distance between the turbines, capture the delayed effect of wind direction changes on the inter-connectivity of the graph as the wind conditions at the farm inlet propagate through the turbine array. An event-based update framework is employed to capture time-dependent topology changes due to shifts in wind direction. Simulation results for dynamically changing wind inlet directions to a circular wind farm are compared to predictions from both the static and dynamic versions of the FLOw Redirection and Induction in Steady State (FLORIS) model. The approach is shown to enable real-time tracking of dynamic changes to wind farm power output within a framework that can be easily integrated into real-time, horizon-based, control strategies that typically do not account for wind direction changes.

distributed↗
DOE OSTI2016

Crashworthiness Models for Automotive Batteries - Report on Project 2088-A031-15 for DOT/NHTSA

Safety is a key element of any device designed to store energy, in particular electrochemical batteries, which convert energy of chemical reactions to electrical energy. Safety considerations are especially important when applied to large automotive batteries designed for propulsion of electric vehicles (EV). The high amount of energy stored in EV battery packs translates to higher probability of fire in case of severe deformation of battery compartment due to automotive crash or impact caused by road debris. While such demand for safety has resulted in heavier protection of battery enclosure, the mechanisms leading to internal short circuit due to deformation of the battery are not well understood even on the level of a single electrochemical cell. Moreover, not all internal shorts result in thermal runaway, and thus a criterion for catastrophic failure needs to be developed. This report summarizes the effort to pinpoint the critical deformation necessary to trigger a short via experimental study on large format automotive Li-ion cells in a rigid spherical indentation configuration. Cases of single cells and cell stacks undergoing indentation were investigated. Mechanical properties of cell components were determined via experimental testing and served as input for constitutive models of Finite Element (FE) analysis. The ability of the model to predict the behavior of cell(s) under spherical indentation and to predict failure leading to internal short circuit was validated against experiments. The necessity of resolving pairs of negative and positive electrodes in the FE formulation is clearly demonstrated by comparing layer-resolved simulations with simulations involving batteries with homogenized material properties. Finally, a coupled solution of electrochemical-electrical-thermal (EET) problem on a Nissan Leaf battery module was demonstrated towards the goal of extending the simulations to module level.

25 ENERGY STORAGE↗
DOE OSTI2021

Modeling Framework for Bulk Electric Grid Impacts from HEMP E1 and E3 Effects (Tasks 3.1 Final Report)

This report presents a framework to evaluate the impact of a high-altitude electromagnetic pulse (HEMP) event on a bulk electric power grid. This report limits itself to modeling the impact of EMP E1 and E3 components. The co-simulation of E1 and E3 is presented in detail, and the focus of the paper is on the framework rather than actual results. This approach is highly conservative as E1 and E3 are not maximized with the same event characteristics and may only slightly overlap. The actual results shown in this report are based on a synthetic grid with synthetic data and a limited exemplary EMP model. The framework presented can be leveraged and used to analyze the impact of other threat scenarios, both manmade and natural disasters. This report d escribes a Monte-Carlo based methodology to probabilistically quantify the transient response of the power grid to a HEMP event. The approach uses multiple fundamental steps to characterize the system response to HEMP events, focused on the E1 and E3 components of the event. 1) Obtain component failure data related to HEMP events testing of components and creating component failure models. Use the component failure model to create component failure conditional probability density function (PDF) that is a function of the HEMP induced terminal voltage. 2) Model HEMP scenarios and calculate the E1 coupled voltage profiles seen by all system components. Model the same HEMP scenarios and calculate the transformer reactive power consumption profiles due to E3. 3) Sample each component failure PDF to determine which grid components will fail, due to the E1 voltage spike, for each scenario. 4) Perform dynamic simulations that incorporate the predicted component failures from E1 and reactive power consumption at each transformer affected by E3. These simulations allow for secondary transients to affect the relays/protection remaining in service which can lead to cascading outages. 5) Identify the locations and amount of load lost for each scenario through grid dynamic simulation. This can be an indication of the immediate grid impacts from a HEMP event. In addition, perform more detailed analysis to determine critical nodes and system trends. 6) To help realize the longer-term impacts, a security constrained alternating current optimal power flow (ACOPF) is run to maximize critical load served. This report describes a modeling framework to assess the systemic grid impacts due to a HEMP event. This stochastic simulation framework generates a large amount of data for each Monte Carlo replication, including HEMP location and characteristics, relay and component failures, E3 GIC profiles, cascading dynamics including voltage and frequency over time, and final system state. This data can then be analyzed to identify trends, e.g., unique system behavior modes or critical components whose failure is more likely to cause serious systemic effects. The proposed analysis process is demonstrated on a representative system. In order to draw realistic conclusions of the impact of a HEMP event on the grid, a significant amount of work remains with respect to modeling the impact on various grid components.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

The Second Skin: A Wearable Sensor Suite that Enables Real-Time Human Biomechanics Tracking Through Deep Learning

Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.

Casey, Ryan T. F. [Georgia Institute of Technology↗
DOE OSTI2012

The Impact of Intrinsic Heavy Quark Distributions in the Proton on New Physics Searches at the High Intensity Frontier

The possibility of an intense proton facility, at 'Project X' or elsewhere, will provide many new opportunities for searches for physics beyond the Standard Model. A Project X can serve a yet broader role in the search for new physics, and in this note we highlight the manner in which thus-enabled studies of the flavor structure of the proton, particularly of its intrinsic heavy quark content, facilitate other direct and indirect searches for new physics. Intrinsic heavy quarks in both light and heavy hadrons play a key role in searches for physics BSM with hadrons - and their study at the Intensity Frontier may prove crucial to establishing its existence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Measuring the seeds of ion outflow: auroral sounding rocket observations of low-altitude ion heating and circulation

Here, we present an analysis of in situ measurements from the MICA (Magnetosphere-Ionosphere Coupling in the Alfvén Resonator) nightside auroral sounding rocket with comparisons to a multifluid ionospheric model. MICA made observations at altitudes below 325 km of the thermal ion kinetic particle distributions that are the origins of ion outflow. Late flight, in the vicinity of an auroral arc, we observe frictional processes controlling the ion temperature. Upflow of these cold ions is attributed to either the ambipolar field resulting from the heated electrons or possibly to ion-neutral collisions. We measure E → xB → convection away from the arc (poleward) and downflows of hundreds of m s -1 poleward of this arc, indicating small-scale low-altitude plasma circulation. In the early flight we observe DC electromagnetic Poynting flux and associated ELF wave activity influencing the thermal ion temperature in regions of Alfvénic aurora. We observe enhanced, anisotropic ion temperatures which we conjecture are caused by transverse heating by wave-particle interactions (WPI) even at these low altitudes. Throughout this region we observe several hundred m s -1 upflow of the bulk thermal ions colocated with WPI; however, the mirror force is negligible at these low energies; thus, the upflow is attributed to ambipolar fields (or possibly neutral upwelling drivers). Moreover, the low-altitude MICA observations serve to inform future ionospheric modeling and simulations of (a) the need to consider the effects of heating by WPI at altitudes lower than previously considered viable and (b) the occurrence of structured and localized upflows/downflows below where higher-altitude heating rocesses are expected.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Rainier Mesa/Shoshone Mountain Hydrostratigraphic Framework Model-Prime Model Model Development Process and Model Description, Revision 0

This document presents the results of revisions to the Rainier Mesa/Shoshone Mountain (RM/SM) hydrostratigraphic framework model (HFM) that was constructed for Corrective Action Unit (CAU) 99: Rainier Mesa/Shoshone Mountain. The revised HFM is described as the “RM/SM HFM-Prime” and serves as the base HFM. The modeling efforts and the revisions described in this report have been performed as part of the Underground Test Area (UGTA) Activity that was initiated by the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) to assess and evaluate the effects of the underground nuclear tests on groundwater at the Nevada National Security Site (NNSS) and vicinity. This document builds on the content of the internal Hydrostratigraphic Framework Model of the Rainier Mesa Area Phase I' - Base Model: Model Development Process & Data Package Description (N-I, 2014a) and specific document review comments from the UGTA RM/SM CAU Preemptive Review members (Zavarin, 2015). This document provides, where necessary, the justifications and rationale for interpretations and revisions to the hydrostratigraphic framework of the RM/SM CAU. The fundamental objective of the effort described in this report was to revise the RM/SM HFM, particularly in the areas and vicinity of the sub-CAU models, in order to incorporate some of the higher-resolution hydrogeologic interpretations used to construct several of the sub-CAU scale flow and transport models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Fast Uncovering of Graph Communities on a Chip: Toward Scalable Community Detection on Multicore and Manycore Platforms

Graph representations are pervasive in scientific and social computing. They serve as vital tools to model the interplay among different interacting entities. In this paper, we visit the problem of community detection, which is one of the most widely used graph operations toward scientific discovery. Community detection refers to the process of identifying tightly-knit subgroups of vertices in a large graph. These sub-groups (or communities) represent vertices that are tied together through common structure or function. Identification of communities could help in understanding the modular organization of complex networks. However, owing to large data sizes and high computational costs, performing community detection at scale has become increasingly challenging. Here, we present a detailed review and analysis of some of the leading computational methods and implementations developed for executing community detection on modern day multicore and manycore architectures. Our goals are to: a) define the problem of community detection and highlight its scientific significance; b) relate to challenges in parallelizing the operation on modern day architectures; c) provide a detailed report and taxonomical classification of the approaches that have been designed for various architectures; and d) finally, provide insights into the strengths and suitability of different architectures for community detection, and a preview into the future trends of the area. It is our hope that this detailed treatment of community detection on parallel architectures can serve as an exemplar study for extending the application of modern day multicore and manycore architectures to other complex graph applications.

community detection, multithreaded platforms↗
DOE OSTI2012

Towards automated crystallographic structure refinement with phenix.refine

phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods. phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. It has several automation features and is also highly flexible. Several hundred parameters enable extensive customizations for complex use cases. Multiple user-defined refinement strategies can be applied to specific parts of the model in a single refinement run. An intuitive graphical user interface is available to guide novice users and to assist advanced users in managing refinement projects. X-ray or neutron diffraction data can be used separately or jointly in refinement. phenix.refine is tightly integrated into the PHENIX suite, where it serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Simplified predictive models for CO 2 sequestration performance assessment

CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessment modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical “proxy models” are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measurement of nuclear interaction cross sections towards neutron-skin thickness determination

The accuracy of reaction theories used to extract properties of exotic nuclei from scattering experiments is often unknown or not quantified, but of utmost importance when, e.g., constraining the equation of state of asymmetric nuclear matter from observables as the neutron-skin thickness. In order to test the Glauber multiple-scattering model, the total interaction cross section of 12 C on carbon targets was measured at initial beam energies of 400, 550, 650, 800, and 1000 MeV/nucleon. The measurements were performed during the first experiment of the newly constructed R 3 B (Reaction with Relativistic Radioactive Beams) experiment after the start of FAIR Phase-0 at the GSI/FAIR facility with beam energies of 400, 550, 650, 800, and 1000 MeV/nucleon. The combination of the large-acceptance dipole magnet GLAD and a newly designed and highly efficient Time-of-Flight detector enabled a precise transmission measurement with several target thicknesses for each initial beam energy with an experimental uncertainty of ±0.4%. A comparison with the Glauber model revealed a discrepancy of around 3.1% at higher beam energies, which will serve as a crucial baseline for the model-dependent uncertainty in future fragmentation experiments.

Astronomy & Astrophysics↗