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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A high-speed linear algebra library with automatic parallelism

Parallel or distributed processing is key to getting highest performance workstations. However, designing and implementing efficient parallel algorithms is difficult and error-prone. It is even more difficult to write code that is both portable to and efficient on many different computers. Finally, it is harder still to satisfy the above requirements and include the reliability and ease of use required of commercial software intended for use in a production environment. As a result, the application of parallel processing technology to commercial software has been extremely small even though there are numerous computationally demanding programs that would significantly benefit from application of parallel processing. This paper describes DSSLIB, which is a library of subroutines that perform many of the time-consuming computations in engineering and scientific software. DSSLIB combines the high efficiency and speed of parallel computation with a serial programming model that eliminates many undesirable side-effects of typical parallel code. The result is a simple way to incorporate the power of parallel processing into commercial software without compromising maintainability, reliability, or ease of use. This gives significant advantages over less powerful non-parallel entries in the market.

Boucher, Michael L.↗
NASA NTRS1995

Scientific Visualization and Computational Science: Natural Partners

Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization research because the results vary so widely and include things that have no known appearance. The amount of data creates additional challenges for both hardware and software systems. Evaluations of visualization should ultimately reflect the insight gained into the scientific phenomena. So making good visualizations requires consideration of characteristics of the user and the purpose of the visualization. Knowledge about human perception and graphic design is also relevant. It is this breadth of knowledge that stimulates proposals for multidisciplinary visualization teams and intelligent visualization assistant software. Visualization is an immature field, but computational science is stimulating research on a broad front.

Uselton, Samuel P.↗
NASA NTRS2007

Simulating Flights of Future Launch Vehicles and Spacecraft

Marshall Aerospace Vehicle Representation in C (MAVERIC) is a computer program for generic, low-to-high-fidelity simulation of the flight(s) of one or more launch vehicle(s) or spacecraft. MAVERIC is designed to accommodate multi-staged vehicles, powered serially or in parallel, with multiple engines, tanks, and cargo elements. Engines can be of jet or conventional rocket types, using either liquid or solid propellants. MAVERIC includes generic subsystem software models for propulsion systems, mass properties, reaction control systems, aerodynamic properties, guidance systems, and navigation systems. Simulations can be started at points other than liftoff. Also included are guidance-system software models that accommodate the ascent, orbit, coasting, deorbiting, entry, terminal-area-energy-management, approach, and landing phases of flight. Options to use different wind profiles and atmospheres are included. A Monte Carlo capability is provided for modeling dispersions associated with atmospheric effects (including winds), propulsion, navigation, aerodynamics, and mass properties. Failures of engines and other subsystems can be modeled. The program is written in the C programming language, which makes it possible for the program to have high degrees of modularity, reusability, and maintainability, thereby also facilitating modification for modeling new vehicles.

McCarter, James W.↗
NASA NTRSDate not supplied

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials↗
NASA NTRS2001

End-to-End Demonstrator of the Safe Affordable Fission Engine (SAFE) 30: Power Conversion and Ion Engine Operation

The Safe Affordable Fission Engine (SAFE) test series addresses Phase 1 Space Fission Systems issues in particular non-nuclear testing and system integration issues leading to the testing and non-nuclear demonstration of a 400-kW fully integrated flight unit. The first part of the SAFE 30 test series demonstrated operation of the simulated nuclear core and heat pipe system. Experimental data acquired in a number of different test scenarios will validate existing computational models, demonstrated system flexibility (fast start-ups, multiple start-ups/shut downs), simulate predictable failure modes and operating environments. The objective of the second part is to demonstrate an integrated propulsion system consisting of a core, conversion system and a thruster where the system converts thermal heat into jet power. This end-to-end system demonstration sets a precedent for ground testing of nuclear electric propulsion systems. The paper describes the SAFE 30 end-to-end system demonstration and its subsystems.

Hrbud, Ivana↗
NASA NTRS2019

Preliminary Computational Assessment of Disk Rotating Detonation Engine Configurations

The pressure gain combustion (PGC) community is currently investigating rotating detonation engine (RDE) configurations where the flow direction is predominantly radial while the detonation travels circumferentially. These configurations are sometimes referred to as disk rotating detonation engines (DRDE) due to their nominal appearance as two disks in parallel with a gap between them. Having radial flow between disks, as opposed to the conventional RDE with axial flow in an annulus, may have profound effects on both the flow field and the performance. It may also yield extraordinarily compact devices which are well suited to particular propulsion and power applications. This presentation describes a preliminary effort to model the DRDE using a modified computational fluid dynamics (CFD) code originally written for analyzing ordinary RDE's. The quasi-two-dimensional code modifications are described, and some simple test flows are analyzed to insure that the modifications are functioning as envisioned. The code is then used to examine several DRDE scenarios such as radially inward and radially outward devices to see if stable operation is possible and if so, to assess the performance in terms of pressure gain. It is found that several flow scenarios are not only stable, but show superior performance to the ordinary RDE.

Paxson, Daniel E.↗
DOE OSTI2021

Outcomes and Insights From Simplified Analytic Trajectory Optimization for a Tethered Underwater Kite

This letter formulates and solves a periodic trajectory optimization problem for a tethered underwater kite. The goal is to maximize the average mechanical power harvested by the kite. The type of kite considered in this letter extracts electricity from ocean currents by moving cross-current as its reel away from its base station, and consumes electricity to reel back. The problem of optimizing this kite’s trajectory is challenging due to the high dimensionality and nonlinearity of its dynamics. To tackle this challenge, the literature often separates the problem into two subproblems focusing on optimizing the cross-current and the reel-in/reel-out components of the trajectory, respectively, which may be sub-optimal. In contrast, this letter solves for the combined cross-current and reel-in/reel-out trajectory by linearizing the dynamics of the kite around a zero-power reference equilibrium trajectory in spherical coordinates. This allows the trajectory optimization problem to be solved analytically for simple sinusoidal input perturbations from equilibrium. Here we use linear quadratic regulation to enable the nonlinear kite model to track the optimized trajectory. The result is a computationally efficient approach that achieves an attractive Loyd factor of 19.9%, while providing important insights into the nature of the optimal trajectory.

42 ENGINEERING↗
NASA NTRS2006

Large Engine Technology (LET) Short Haul Civil Tiltrotor Contingency Power Materials Knowledge and Lifing Methodologies

This report documents the results of an experimental program conducted on two advanced metallic alloy systems (Rene' 142 directionally solidified alloy (DS) and Rene' N6 single crystal alloy) and the characterization of two distinct internal state variable inelastic constitutive models. The long term objective of the study was to develop a computational life prediction methodology that can integrate the obtained material data. A specialized test matrix for characterizing advanced unified viscoplastic models was specified and conducted. This matrix included strain controlled tensile tests with intermittent relaxtion test with 2 hr hold times, constant stress creep tests, stepped creep tests, mixed creep and plasticity tests, cyclic temperature creep tests and tests in which temperature overloads were present to simulate actual operation conditions for validation of the models. The selected internal state variable models where shown to be capable of representing the material behavior exhibited by the experimental results; however the program ended prior to final validation of the models.

Spring, Samuel D.↗
DOE OSTI2020

Modeling Flexible Generator Operating Regions via Chance- constrained Stochastic Unit Commitment

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

42 ENGINEERING↗
DOE OSTI2022

Toward a machine-guided approach to energetic material discovery

In this article, we trained a machine learning (ML) model to connect microstructural details of an energetic material formulation to its performance for the purpose of guiding the discovery of new explosive formulations. Our hypothesis was that the algorithm would robustly learn the training data and produce an accurate surrogate model. Specifically, the algorithm learned the relationship between details of the void size distribution (VSD), initiating shock pressure, and the energetic material performance. We used realistic constraints on the VSD and a range of cases were ingested by a physically informed reactive flow model working within a hydrodynamic solver running on high-performance computing resources. The ML algorithm produced a surrogate model that accurately predicted known test points around the parameter space. In addition to the utility of the model and the process used for its development, we noted interesting comparisons between what we, the authors—subject matter experts, would heuristically conclude from the training data and the surrogate model predictions. We detected nuanced details that were missed by the surrogate model; however, these details are not important to an energetic material formulator. We concluded that the algorithm did indeed robustly learn the training data and produce an accurate surrogate model. We further concluded that the surrogate model is a powerful tool to guide the formulator in the absence of subject matter experts and limited-access computing resources.

42 ENGINEERING↗
DOE OSTI2023

Machine Learning in Power System Operations: Training Data

Reliability and stability of the electric grid today has depended upon operations of the grid which include the protective relay. Today, the electricity sector faces new challenges with the shift of generation resource characteristics away from the traditional “big iron” generation to inverter-based resources (IBR) which shift the physics and assumption used in grid operation and protection. These changing conditions represent new challenges for protective relays (identification of faults) and increased challenges for protection engineers (correct settings and configuration, reduction of mis-operations), both issues recognized in research and industry. Finding new approaches to reduce mis-operations in relaying and new approaches to fault identification is critical to grid operations. Using today’s modern technology of embedded systems, edge computing, machine learning (ML), and communications we can help address challenges and augment and improve on existing power system operations methodologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1991

A parallel-pipelined architecture for a multi carrier demodulator

Analog devices have been used for processing the information on board the satellites. Presently, digital devices are being used because they are economical and flexible as compared to their analog counterparts. Several schemes of digital transmission can be used depending on the data rate requirement of the user. An economical scheme of transmission for small earth stations uses single channel per carrier/frequency division multiple access (SCPC/FDMA) on the uplink and time division multiplexing (TDM) on the downlink. This is a typical communication service offered to low data rate users in commercial mass market. These channels usually pertain to either voice or data transmission. An efficient digital demodulator architecture is provided for a large number of law data rate users. A demodulator primarily consists of carrier, clock, and data recovery modules. This design uses principles of parallel processing, pipelining, and time sharing schemes to process large numbers of voice or data channels. It maintains the optimum throughput which is derived from the designed architecture and from the use of high speed components. The design is optimized for reduced power and area requirements. This is essential for satellite applications. The design is also flexible in processing a group of a varying number of channels. The algorithms that are used are verified by the use of a computer aided software engineering (CASE) tool called the Block Oriented System Simulator. The data flow, control circuitry, and interface of the hardware design is simulated in C language. Also, a multiprocessor approach is provided to map, model, and simulate the demodulation algorithms mainly from a speed view point. A hypercude based architecture implementation is provided for such a scheme of operation. The hypercube structure and the demodulation models on hypercubes are simulated in Ada.

Kwatra, S. C.↗
NASA NTRS1986

Engineering the Voyager Uranus mission

Several factors that affected the continuing expedition of Voyager 2 to Uranus are discussed. The hydrazine propellant and electrical power supplies on the spacecraft, and the radio signal strength and sun sensor and star tracker sensitivities are examined. The use of the on-board computer to steady the spacecraft and reduce image smear is described. The Voyager employs radiometric and optical data to navigate. The changes required to improve the transmission capabilities of the spacecraft and to eliminate the on-board hardware failures are analyzed.

Laeser, R. P.↗
NASA NTRS1994

Engineering Analysis Subsystem Environment for Spacecraft Engineering Subsystem Mission Operations

The Engineering Analysis Subsystem Environment (EASE) prototype is a collection of computer programs on networked workstations providing a multimission, multisubsystem environment that enables the operation of several spacecraft simultaneously with fewer analysts. Through the use of automated tools, graphical data visualization and information management, EASE has achieved an increase in mission operations productivity. Recently, a database, a trending tool, and a power sequence expansion tool have been added to EASE. This paper discusses these enhancements and provides an update of the operation experience with the realtime Galileo telemetry data.

EASE↗
DOE OSTI2021

Pulse Detonation Engine for Advanced Oxy-Combustion of Coal-Based Fuel for Direct Power Extraction Applications

Pressure gain combustion and magnetohydrodynamic (MHD) systems have the potential to provide a step increase in the efficiency of combined-cycle power plants. Specific advantages include a net pressure increase to the system instead of a pressure drop, the high temperature of the detonation waves can increase the efficiency of power extraction compared to other processes, significant thermal energy can be released in a compact region, and the high velocities of the flow increase extraction of electrical power. In summary, a pressure gain combustor coupled with a MHD has the potential to be transformative. Despite the potential advantages, relatively little research has been conducted considering coupled pressure gain combustion systems with MHD systems. With this background and motivation, the overall goal of this effort was to advance the knowledge, technology, and computational tools associated with coupled detonation and MHD systems. A joint experimental and computational approach was used while seeking to accomplish the goals of this work. Specifically, two pulse detonation engines were developed and used for the experiments to produce detonations. Detonation speeds were measured for a variety of flow and fuel conditions (e.g., methane, propane, with coal particles). Preliminary electrical conductivity measurements were collected. An extensive amount of research was performed to identify sensitivities of detonation behaviors to the presence of combustion products. Computationally, a twofold approach was used in this work. First, a solver was developed for solving the governing equations for a reactive flow with coupled detonation and ionization chemistry. The solver was applied to study the impacts of seed material ionization on detonation. Second, a conservation element-solution element (CE-SE) based numerical solver for detonation studies with a reduced reaction mechanism for oxy-methane combustion was developed and verified on standard test cases. Key findings and contributions from this work are as follows. A system was developed for injecting powderized coal, or other seeding material, into a pulse-detonation system. The influence of a combustion product (i.e., CO 2 ) on detonation behavior was identified. Knowledge gained from this work is applicable to devices such as rotating detonation engines, where combustion products mix with fresh reactants. A system for measuring the electrical conductivity of the exhaust from a pulse-detonation engine was developed. The open-source solver, Clawpack, was extended to solve the reactive Euler equations for simulating detonations. A coupled combustion and ionization chemistry was developed in a single chemical kinetic model for methane oxidation. This model can be used to solve coupled MHD and detonation simulations. It was found that parasitic interactions from ionization chemistry with the magnetic field can reduce the detonation velocity by up to 8%, with a potential impact on power extraction of 15%. It is recommended that interactions between the detonation front and MHD field be considered. Higher gas temperatures and velocities were achieved owing to oxy-fuel detonations. Use of radical dissociation reactions in the reduced reaction mechanism, was found to be critical in predicting detonation temperature and velocity accurately.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Numerical modeling of hydrogen mixing in a direct-injection engine fueled with gaseous hydrogen

Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Positive-Sequence Modeling of Droop-Controlled Grid-Forming Inverters for Transient Stability Simulation of Transmission Systems

Here, this paper describes a positive-sequence model to represent two widely reported droop-controlled grid-forming inverters for bulk power systems simulation study. Methods of how to develop the equivalent voltage source behind impedance to represent inverters with and without inner control loops, modeling of P-f and Q-V droop controls, active and reactive power limiting modeling, and modeling of fault current limiting controls are described in detail. The model is implemented in commercially available positive-sequence simulation tools and compared with detailed electromagnetic transient models in both a single-grid-forming-inverter infinite-bus system and a modified IEEE 39-bus system. Finally, the model is tested on the full US Western Electricity Coordinating Council (WECC) system. Study results show that the model has a good level of accuracy compared to the detailed EMT models, and at the same time also achieves a high computational efficiency, which is suitable for the bulk power system simulation study.

42 ENGINEERING↗
DOE OSTI2021

Cybersecurity Certification Recommendations for Interconnected Grid Edge Devices and Inverter Based Resources

Escalating deployment of PV and grid-edge devices on the distribution grid has increased the sustainability and efficiency of the electric grid. However, the increasing number of distributed energy resources (DERs) deployed creates a heightened cyber-physical interdependency on the distribution grid and thus creates more vectors for cyber-attacks to exploit through information and communication technology (ICT) systems and networks. For example, control signal packets can be modified, intercepted, or corrupted due to vulnerabilities in communication protocols used by microgrid controllers and grid edge devices for power control. Therefore, to mitigate and prevent cyber-attacks on grid edge devices and the inverter-based resources connected to the distribution grid, the U.S. Department of Solar Energy Technologies Office (SETO) awarded funding to the National Renewable Energy Laboratory and Sandia National Laboratory (SNL) to research, develop, and harmonize cybersecurity standards for Photovoltaic (PV) systems and for other kinds of DERs. To help develop a standard for DER cybersecurity, NREL established certification recommendations and test cases, in consensus with the solar industry and UL, for ensuring intrinsic design security for DERs. These recommendations were developed to bolster the cybersecure functionalities such as TLS, MAC, CRL, session resumption/renegotiation, and password, system, and service security management within the DER devices. The proposed test cases verify authentication, authorization, confidentiality, and data integrity for data and communications of DERs that use Transmission Control Protocol/Internet Protocol (TCP/IP). They were also developed to protect DER communications from eavesdropping, replay, man-in-the-middle, denial of service (DoS), spoofing through security certificates, least-privilege violation, and brute-force credentials. This report, which has been validated and reviewed by UL, expands upon those test cases to provide DER cybersecurity certification recommendations which increase DER resiliency and help to mitigate cyber-attacks. UL's collaboration with NREL and approval of this document will accelerate the adoption of a UL standard for DER cybersecurity.

24 POWER TRANSMISSION AND DISTRIBUTION↗