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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System

Lithium-ion (Li-ion) batteries are being deployed on the electrical grid for a variety of purposes, such as to smooth fluctuations in solar renewable power generation. The lifetime of these batteries will vary depending on their thermal environment and how they are charged and discharged. To optimal utilization of a battery over its lifetime requires characterization of its performance degradation under different storage and cycling conditions. Aging tests were conducted on commercial graphite/nickel-manganese-cobalt (NMC) Li-ion cells. A general lifetime prognostic model framework is applied to model changes in capacity and resistance as the battery degrades. Across 9 aging test conditions from 0oC to 55oC, the model predicts capacity fade with 1.4% RMS error and resistance growth with 15% RMS error. The model, recast in state variable form with 8 states representing separate fade mechanisms, is used to extrapolate lifetime for example applications of the energy storage system integrated with renewable photovoltaic (PV) power generation.

25 ENERGY STORAGE↗
NASA NTRS2012

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗
DOE OSTI2025

IBPSA Project 2 BOPTEST: An update on the test cases available in the framework for testing advanced control strategies in buildings

Project 2 develops software infrastructure, test cases, and extensions for the Building Optimization Testing Framework (BOPTEST) to address the expanding needs of building and urban energy system controls through open international collaboration. This paper provides an overview of the new test cases available as of BOPTEST version 0.7.1. Each test case is developed using open-source Modelica libraries and Spawn of EnergyPlus, enabling the creation of high-fidelity building models that incorporate envelope dynamics, Heating Ventilation and Air Conditioning (HVAC) systems, and explicit control representations. Currently, eight test cases are available, with five additional cases under development. These test cases cover a wide range of climates, building types, and HVAC systems. This paper compiles and summarizes test case descriptions, cites original manuscripts that developed them for a more detailed description, and reports baseline control performance metrics. Furthermore, two example applications are presented: one illustrating different levels of control, from supervisory to low-level, and another demonstrating how Model Predictive Control (MPC) solutions must be adapted from continuous to integer to control some building actuators.

Zanetti, Ettore↗
DOE OSTI2016

Kinetic corrections from analytic non-Maxwellian distribution functions in magnetized plasmas

In magnetized plasma physics, almost all developed analytic theories assume a Maxwellian distribution function (MDF) and in some cases small deviations are described using the perturbation theory. The deviations with respect to the Maxwellian equilibrium, called kinetic effects, are required to be taken into account especially for fusion reactor plasmas. Generally, because the perturbation theory is not consistent with observed steady-state non-Maxwellians, these kinetic effects are numerically evaluated by very central processing unit (CPU)-expensive codes, avoiding the analytic complexity of velocity phase space integrals. We develop here a new method based on analytic non-Maxwellian distribution functions constructed from non-orthogonal basis sets in order to (i) use as few parameters as possible, (ii) increase the efficiency to model numerical and experimental non-Maxwellians, (iii) help to understand unsolved problems such as diagnostics discrepancies from the physical interpretation of the parameters, and (iv) obtain analytic corrections due to kinetic effects given by a small number of terms and removing the numerical error of the evaluation of velocity phase space integrals. This work does not attempt to derive new physical effects even if it could be possible to discover one from the better understandings of some unsolved problems, but here we focus on the analytic prediction of kinetic corrections from analytic non-Maxwellians. As applications, examples of analytic kinetic corrections are shown for the secondary electron emission, the Langmuir probe characteristic curve, and the entropy. This is done by using three analytic representations of the distribution function: the Kappa distribution function, the bi-modal or a new interpreted non-Maxwellian distribution function (INMDF). The existence of INMDFs is proved by new understandings of the experimental discrepancy of the measured electron temperature between two diagnostics in JET. As main results, it is shown that (i) the empirical formula for the secondary electron emission is not consistent with a MDF due to the presence of super-thermal particles, (ii) the super-thermal particles can replace a diffusion parameter in the Langmuir probe current formula, and (iii) the entropy can explicitly decrease in presence of sources only for the introduced INMDF without violating the second law of thermodynamics. Moreover, the first order entropy of an infinite number of super-thermal tails stays the same as the entropy of a MDF. The latter demystifies the Maxwell's demon by statistically describing non-isolated systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1970

Two examples of applications of Kalman filtering to integrated systems of navigation

Two applications of optimal stochastic filters to navigation systems are described. The first is an air navigation system consisting of an inertial device (INS) and a Loran, plus an altimeter. The second is an application to a system of submarine navigation consisting of an inertial device (SINS) and an Omega plus a depth sensor.

Ferraro, A.↗
NASA NTRS2003

Carbon-Based Wear Coatings: Properties and Applications

The technical function of numerous engineering systems - such as vehicles, machines, and instruments - depends on the processes of motion and on the surface systems. Many processes in nature and technology depend on the motion and dynamic behavior of solids, liquids, and gases. Smart surface systems are essential because of the recent technological push toward higher speeds, loads, and operating temperatures; longer life; lighter weight and smaller size (including nanotechnology); and harsh environments in mechanical, mechatronic, and biomechanical systems. If proper attention is not given to surface systems, then vehicles, machines, instruments, and other technical systems could have short lives, consume excessive energy, experience breakdowns, result in liabilities, and fail to accomplish their missions. Surface systems strongly affect our national economy and our lifestyles. At the NASA Glenn Research Center, we believe that proper attention to surface systems, especially in education, research, and application, could lead to economic savings of between 1.3 and 1.6 percent of the gross domestic product. Wear coatings and surface systems continue to experience rapid growth as new coating and surface engineering technologies are discovered, more cost-effective coating and surface engineering solutions are developed, and marketers aggressively pursue, uncover, and exploit new applications for engineered surface systems in cutting tools and wear components. Wear coatings and smart surface systems have been used widely in industrial, consumer, automotive, aerospace, and biomedical applications. This presentation expresses the author's views of and insights into smart surface systems in wear coatings. A revolution is taking place in carbon science and technology. Diamond, an allotrope of carbon, joins graphite, fullerenes, and nanotubes as its major pure carbon structures. It has a unique combination of extreme properties: hardness and abrasion resistance; adhesion and friction; thermal conductivity; chemical and thermal inertness; corrosion and wear resistance; radiation resistance and biocompatibility; electronic, acoustic, and electrochemical characteristics; and environmental compatibility. These properties make diamond attractive for a wide range of diverse applications. In particular, chemical-vapor-deposited (CVD) diamond coatings offer a broad potential, since size and cost are not as limiting. The production of large, superhard diamond films or sheets at low cost make designer materials possible. This presentation is divided into two sections: properties and applications of hard coatings. The first section is concerned with the fundamental properties of the surfaces of CVD diamonds and related materials. The surface properties of hard coatings with favorable coefficients of friction (less than or equal to 0.1) and dimensional wear coefficients (less than or equal to 10(exp -6) cubic millimeters/N.m) in specific environments are discussed. The second section is devoted to applications. Examples of actual, successful applications and of potential challenging applications of the coatings.such as CVD diamond, diamondlike carbon, and cubic boron nitride-are described. Cutting tools coated with CVD diamond are of immediate commercial interest. Other applications, such as microelectromechanical systems (MEMS), valves, and bearings of CVD diamond, are being developed, but at a slow pace. There is a continually growing interest in commercializing diamondlike carbon for wear parts applications, such as biomedical parts and implants, forming dies, transport guides, magnetic tapes and disks, valves, and gears. Cubic boron nitride films are receiving attention because they can be used on tools to machine ferrous materials or on wear parts in sliding contact with ferrous materials.

Miyoshi, Kazuhisa↗
NASA NTRS2005

Modern Radar Techniques for Geophysical Applications: Two Examples

The last decade of the evolution of radar was heavily influenced by the rapid increase in the information processing capabilities. Advances in solid state radio HF devices, digital technology, computing architectures and software offered the designers to develop very efficient radars. In designing modern radars the emphasis goes towards the simplification of the system hardware, reduction of overall power, which is compensated by coding and real time signal processing techniques. Radars are commonly employed in geophysical radio soundings like probing the ionosphere; stratosphere-mesosphere measurement, weather forecast, GPR and radio-glaciology etc. In the laboratorio di Geofisica Ambientale of the Istituto Nazionale di Geofisica e Vulcanologia (INGV), Rome, Italy, we developed two pulse compression radars. The first is a HF radar called AIS-INGV; Advanced Ionospheric Sounder designed both for the purpose of research and for routine service of the HF radio wave propagation forecast. The second is a VHF radar called GLACIORADAR, which will be substituting the high power envelope radar used by the Italian Glaciological group. This will be employed in studying the sub glacial structures of Antarctica, giving information about layering, the bed rock and sub glacial lakes if present. These are low power radars, which heavily rely on advanced hardware and powerful real time signal processing. Additional information is included in the original extended abstract.

Arokiasamy, B. J.↗
DOE OSTI2017

Newmark local time stepping on high-performance computing architectures

In multi-scale complex media, finite element meshes often require areas of local refinement, creating small elements that can dramatically reduce the global time-step for wave-propagation problems due to the CFL condition. Local time stepping (LTS) algorithms allow an explicit time-stepping scheme to adapt the time-step to the element size, allowing near-optimal time-steps everywhere in the mesh. We develop an efficient multilevel LTS-Newmark scheme and implement it in a widely used continuous finite element seismic wave-propagation package. In particular, we extend the standard LTS formulation with adaptations to continuous finite element methods that can be implemented very efficiently with very strong element-size contrasts (more than 100x). Capable of running on large CPU and GPU clusters, we present both synthetic validation examples and large scale, realistic application examples to demonstrate the performance and applicability of the method and implementation on thousands of CPU cores and hundreds of GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Advanced IGCC/Hydrogen Gas Turbine Development

The objective of this program was to develop the technologies required for a fuel flexible (coal derived hydrogen or syngas) gas turbine for IGCC that met DOE turbine performance goals. The overall DOE Advanced Power System goal was to conduct the research and development (R&D) necessary to produce coal-based IGCC power systems with high efficiency, near-zero emissions, and competitive capital cost. To meet this goal, the DOE Fossil Energy Turbine Program had as an interim objective of 2 to 3 percentage points improvement in combined cycle (CC) efficiency. The final goal is 3 to 5 percentage points improvement in CC efficiency above the state of the art for CC turbines in IGCC applications at the time the program started. The efficiency goals were for NOx emissions of less than 2 ppm NOx (@15 % O2). As a result of the technologies developed under this program, the DOE goals were exceeded with a projected 8 point efficiency improvement. In addition, a new combustion technology was conceived of and developed to overcome the challenges of burning hydrogen and achieving the DOE’s NOx goal. This report also covers the developments under the ARRA-funded portion of the program that include gas turbine technology advancements for improvement in the efficiency, emissions, and cost performance of gas turbines for industrial applications with carbon capture and sequestration. Example applications could be cement plants, chemical plants, refineries, steel and aluminum plants, manufacturing facilities, etc. The DOE’s goal for more than 5 percentage point improvement in efficiency was met with cycle analyses performed for representative IGCC Steel Mill and IGCC Refinery applications. Technologies were developed in this program under the following areas: combustion, larger latter stage buckets, CMC and EBC, advanced materials and coatings, advanced configurations to reduce cooling, sealing and rotor purge flows, turbine aerodynamics, advanced sensors, advancements in first stage hot gas path components, and systems analyses to determine benefits of all previously mentioned technologies to a gas turbine system in an IGCC configuration. This project built on existing gas turbine technology and product developments, and developed and validated the necessary turbine related technologies and sub-systems needed to meet the DOE turbine program goals. The scope of the program did not cover the design and validation of a full-scale prototype machine with the technology advances from this program incorporated. In summary, the DOE goals were met with this program. While the commercial landscape has not resulted in a demand for IGCC gas turbines many of the technologies that were developed over the course of the program are benefiting the US by being applied to new higher efficiency natural gas fueled gas turbines.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

GLOBAL REFERENCE ATMOSPHERIC MODELS FOR AEROASSIST APPLICATIONS

Aeroassist is a broad category of advanced transportation technology encompassing aerocapture, aerobraking, aeroentry, precision landing, hazard detection and avoidance, and aerogravity assist. The eight destinations in the Solar System with sufficient atmosphere to enable aeroassist technology are Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Saturn's moon Titan. Engineering-level atmospheric models for five of these targets - Earth, Mars, Titan, Neptune, and Venus - have been developed at NASA's Marshall Space Flight Center. These models are useful as tools in mission planning and systems analysis studies associated with aeroassist applications. The series of models is collectively named the Global Reference Atmospheric Model or GRAM series. An important capability of all the models in the GRAM series is their ability to simulate quasi-random perturbations for Monte Carlo analysis in developing guidance, navigation and control algorithms, for aerothermal design, and for other applications sensitive to atmospheric variability. Recent example applications are discussed.

Duvall, Aleta↗
NASA NTRS1993

Formal Functional Test Designs: Bridging the Gap Between Test Requirements and Test Specifications

This presentation describes the testing life cycle, the purpose of the test design phase, and test design methods and gives an example application. Also included is a description of Test Representation Language (TRL), a summary of the language, and an example of an application of TRL. A sample test requirement and sample test design are included.

testing life cycle test design test requirements T↗
DOE OSTI2017

Computational Thermodynamics of Materials Zi-Kui Liu and Yi Wang

This authoritative volume introduces the reader to computational thermodynamics and the use of this approach to the design of material properties by tailoring the chemical composition. The text covers applications of this approach, introduces the relevant computational codes, and offers exercises at the end of each chapter. The book has nine chapters and two appendices that provide background material on computer codes. Chapter 1 covers the first and second laws of thermodynamics, introduces the spinodal as the limit of stability, and presents the Gibbs-Duhem equation. Chapter 2 focuses on the Gibbs energy function. Starting with a homogeneous system with a single phase, the authors proceed to phases with variable compositions, and polymer blends. The discussion includes the contributions of external electric and magnetic fields to the Gibbs energy. Chapter 3 deals with phase equilibria in heterogeneous systems, the Gibbs phase rule, and phase diagrams. Chapter 4 briefly covers experimental measurements of thermodynamic properties used as input for thermodynamic modeling by Calculation of Phase Diagrams (CALPHAD). Chapter 5 discusses the use of density functional theory to obtain thermochemical data and fill gaps where experimental data is missing. The reader is introduced to the Vienna Ab Initio Simulation Package (VASP) for density functional theory and the YPHON code for phonon calculations. Chapter 6 introduces the modeling of Gibbs energy of phases with the CALPHAD method. Chapter 7 deals with chemical reactions and the Ellingham diagram for metal-oxide systems and presents the calculation of the maximum reaction rate from equilibrium thermodynamics. Chapter 8 is devoted to electrochemical reactions and Pourbaix diagrams with application examples. Chapter 9 concludes this volume with the application of a model of multiple microstates to Ce and Fe3Pt. CALPHAD modeling is briefly discussed in the context of genomics of materials. The book introduces basic thermodynamic concepts clearly and directs readers to appropriate references for advanced concepts and details of software implementation. The list of references is quite comprehensive. The authors make liberal use of diagrams to illustrate key concepts. The two Appendices at the end discuss software requirements and the file structure, and present templates for special quasi-random structures. There is also a link to download pre-compiled binary files of the YPHON code for Linux or Microsoft Windows systems. The exercises at the end of the chapters assume that the reader has access to VASP, which is not freeware. Readers without access to this code can work on a limited number of exercises. However, results from other first principles codes can be organized in the YPHON format as explained in the Appendix. This book will serve as an excellent reference on computational thermodynamics and the exercises provided at the end of each chapter make it valuable as a graduate level textbook. Reviewer: Ram Devanathan is Acting Director of Earth Systems Science Division, Pacific Northwest National Laboratory, USA.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Development of Modeling Capabilities for Launch Pad Acoustics and Ignition Transient Environment Prediction

This paper presents development efforts to establish modeling capabilities for launch vehicle liftoff acoustics and ignition transient environment predictions. Peak acoustic loads experienced by the launch vehicle occur during liftoff with strong interaction between the vehicle and the launch facility. Acoustic prediction engineering tools based on empirical models are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. Modeling approaches are needed that capture the important details of the plume flow environment including the ignition transient, identify the noise generation sources, and allow assessment of the effects of launch pad geometric details and acoustic mitigation measures such as water injection. This paper presents a status of the CFD tools developed by the MSFC Fluid Dynamics Branch featuring advanced multi-physics modeling capabilities developed towards this goal. Validation and application examples are presented along with an overview of application in the prediction of liftoff environments and the design of targeted mitigation measures such as launch pad configuration and sound suppression water placement.

West, Jeff↗
DOE OSTI2021

AbacusHOD : a highly efficient extended multitracer HOD framework and its application to BOSS and eBOSS data

ABSTRACT We introduce the AbacusHOD model and present two applications of AbacusHOD and the AbacusSummit simulations to observations. AbacusHOD is a Halo Occupation Distribution (HOD) framework written in Python that is particle-based, multitracer, highly generalized, and highly efficient. It is designed specifically with multitracer/cosmology analyses for next-generation large-scale structure surveys in mind, and takes advantage of the volume and precision offered by the new state-of-the-art AbacusSummit cosmological simulations. The model is also highly customizable and should be broadly applicable to any upcoming surveys and a diverse range of cosmological analyses. In this paper, we demonstrate the capabilities of the AbacusHOD framework through two example applications. The first example demonstrates the high efficiency and the large HOD extension feature set through an analysis of full-shape redshift-space clustering of BOSS galaxies at intermediate to small scales ($\lt 30\, h^{-1}$ Mpc), assessing the necessity of introducing secondary galaxy biases (assembly bias). We find strong evidence for using halo environment instead of concentration to trace secondary galaxy bias, a result which also leads to a moderate reduction in the ‘lensing is low’ tension. The second example demonstrates the multitracer capabilities of the AbacusHOD package through an analysis of the extended Baryon Oscillation Spectroscopic Survey cross-correlation measurements between three different galaxy tracers: luminous red galaxies, emission-line galaxies, and quasi-stellar objects. We expect the AbacusHOD framework, in combination with the AbacusSummit simulation suite, to play an important role in a simulation-based analysis of the upcoming Dark Energy Spectroscopic Instrument data sets.

79 ASTRONOMY AND ASTROPHYSICS↗