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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Numerical Propulsion System Simulation (NPSS): An Award Winning Propulsion System Simulation Tool

The Numerical Propulsion System Simulation (NPSS) is a full propulsion system simulation tool used by aerospace engineers to predict and analyze the aerothermodynamic behavior of commercial jet aircraft, military applications, and space transportation. The NPSS framework was developed to support aerospace, but other applications are already leveraging the initial capabilities, such as aviation safety, ground-based power, and alternative energy conversion devices such as fuel cells. By using the framework and developing the necessary components, future applications that NPSS could support include nuclear power, water treatment, biomedicine, chemical processing, and marine propulsion. NPSS will dramatically reduce the time, effort, and expense necessary to design and test jet engines. It accomplishes that by generating sophisticated computer simulations of an aerospace object or system, thus enabling engineers to "test" various design options without having to conduct costly, time-consuming real-life tests. The ultimate goal of NPSS is to create a numerical "test cell" that enables engineers to create complete engine simulations overnight on cost-effective computing platforms. Using NPSS, engine designers will be able to analyze different parts of the engine simultaneously, perform different types of analysis simultaneously (e.g., aerodynamic and structural), and perform analysis in a more efficient and less costly manner. NPSS will cut the development time of a new engine in half, from 10 years to 5 years. And NPSS will have a similar effect on the cost of development: new jet engines will cost about a billion dollars to develop rather than two billion. NPSS is also being applied to the development of space transportation technologies, and it is expected that similar efficiencies and cost savings will result. Advancements of NPSS in fiscal year 2001 included enhancing the NPSS Developer's Kit to easily integrate external components of varying fidelities, providing the initial Visual-Based Syntax (VBS) capability, and developing additional capabilities to support space transportation. NPSS was supported under NASA's High Performance Computing and Communications Program. Through the NASA/Industry Cooperative Effort agreement, NASA Glenn and its industry and Government partners are developing NPSS. The NPSS team consists of propulsion experts and software engineers from GE Aircraft Engines, Pratt & Whitney, The Boeing Company, Honeywell, Rolls-Royce Corporation, Williams International, Teledyne Continental Motors, Arnold Engineering Development Center, Wright Patterson Air Force Base, and the NASA Glenn Research Center. Glenn is leading the way in developing NPSS--a method for solving complex design problems that's faster, better, and cheaper.

Stauber, Laurel J.↗
NASA NTRS2007

Development of a Prototype Automation Simulation Scenario Generator for Air Traffic Management Software Simulations

A technique for automated development of scenarios for use in the Multi-Center Traffic Management Advisor (McTMA) software simulations is described. The resulting software is designed and implemented to automate the generation of simulation scenarios with the intent of reducing the time it currently takes using an observational approach. The software program is effective in achieving this goal. The scenarios created for use in the McTMA simulations are based on data taken from data files from the McTMA system, and were manually edited before incorporation into the simulations to ensure accuracy. Despite the software s overall favorable performance, several key software issues are identified. Proposed solutions to these issues are discussed. Future enhancements to the scenario generator software may address the limitations identified in this paper.

Khambatta, Cyrus F.↗
NASA NTRS2007

Integrated Clinical Training for Space Flight Using a High-Fidelity Patient Simulator in a Simulated Microgravity Environment

This viewgraph presentation reviews the use of telemedicine in a simulated microgravity environment using a patient simulator. For decades, telemedicine techniques have been used in terrestrial environments by many cohorts with varied clinical experience. The success of these techniques has been recently expanded to include microgravity environments aboard the International Space Station (ISS). In order to investigate how an astronaut crew medical officer will execute medical tasks in a microgravity environment, while being remotely guided by a flight surgeon, the Medical Operation Support Team (MOST) used the simulated microgravity environment provided aboard DC-9 aircraft teams of crew medical officers, and remote flight surgeons performed several tasks on a patient simulator.

Hurst, Victor↗
NASA NTRS2011

Systems Engineering Simulator (SES) Simulator Planning Guide

The simulation process, milestones and inputs are unknowns to first-time users of the SES. The Simulator Planning Guide aids in establishing expectations for both NASA and non-NASA facility customers. The potential audience for this guide includes both internal and commercial spaceflight hardware/software developers. It is intended to assist their engineering personnel in simulation planning and execution. Material covered includes a roadmap of the simulation process, roles and responsibilities of facility and user, major milestones, facility capabilities, and inputs required by the facility. Samples of deliverables, facility interfaces, and inputs necessary to define scope, cost, and schedule are included as an appendix to the guide.

McFarlane, Michael↗
NASA NTRS2012

Communication Systems Simulation Laboratory (CSSL): Simulation Planning Guide

The simulation process, milestones and inputs are unknowns to first-time users of the CSSL. The Simulation Planning Guide aids in establishing expectations for both NASA and non-NASA facility customers. The potential audience for this guide includes both internal and commercial spaceflight hardware/software developers. It is intended to assist their engineering personnel in simulation planning and execution. Material covered includes a roadmap of the simulation process, roles and responsibilities of facility and user, major milestones, facility capabilities, and inputs required by the facility. Samples of deliverables, facility interfaces, and inputs necessary to define scope, cost, and schedule are included as an appendix to the guide.

Schlesinger, Adam↗
NASA NTRS2012

Integrating Existing Simulation Components into a Cohesive Simulation System

A tradition of leveraging the re-use of components to help manage costs has evolved in the development of complex system. This tradition continues on in the Joint Polar Satellite System (JPSS) Program with the cloning of the Suomi National Polar-orbiting Partnership (NPP) satellite for the JPSS-1 mission, including the instrument complement. One benefit of re-use on a mission is the availability of existing simulation assets from the systems that were previously built. An issue arises in the continual shift of technology over a long mission, or multi-mission, lifecycle. As the missions mature, the requirements for the observatory simulations evolve. The challenge in this environment becomes re-using the existing components in that ever-changing landscape. To meet this challenge, the system must: establish an operational architecture that minimizes impacts on the implementation of individual components, consolidate the satisfaction of new high-impact requirements into system-level infrastructure, and build in a long-term view of system adaptation that spans the full lifecycle of the simulation system. The Flight Vehicle Test Suite (FVTS) within the JPSS Program is defining and executing this approach to ensure a robust simulation capability for the JPSS multi-mission environment

McLaughlin, Brian J.↗
NASA NTRS2019

JSC-Rocknest: a Large-Scale Mojave Mars Simulant (MMS) Based Soil Simulant for In-Situ Resource Utilization Water-Extraction Studies

The Johnson Space Center Rocknest (JSC-RN) simulant was developed in response to a need by NASA's Advanced Exploration Systems (AES) In Situ Resource Utilization (ISRU) project for a simulant to be used in component and system testing for water extraction from Mars regolith. JSC-RN was de-signed to be chemically and mineralogically similar to material from the aeolian sand shadow named Rocknest in Gale Crater, particularly the 1-3 weight percentage water release as measured by the Sample Analysis at Mars (SAM) instrument. Rocknest material is a proxy for average martian soils, which are unconsolidated and could be easily scooped by rovers or landers in order to extract water. One way in which water can be extracted from aeolian material is through heating, where adsorbed and structural water is thermally removed from minerals. The water can then be condensed and used as drinking water or split and used as propellant for spacecraft or as a source of breathable O2. As such, it was essential that JSC-RN contained evolved gas profiles, especially low temperature water (less than 400 degrees Centigrade), that mimicked what is observed in martian soils. Because many of these ISRU tests require hundreds of kilograms of Mars soil simulant, it was essential that JSC-RN be cost-effective and based on com-ponents that could be purchased commercially (i.e., not synthesized in the lab). Here, we describe the JSC-RN martian soil simulant, which is ideal for large-scale production and use in ISRU water extraction studies.

Hogancamp, J. V.↗
DOE OSTI2015

Large eddy simulation of a reacting spray flame with multiple realizations under compression ignition engine conditions

An n-dodecane spray flame (Spray A from Engine Combustion Network) was simulated using a detailed combustion model along with a dynamic structure LES model to evaluate its performance at engine-relevant conditions and understand the transient behavior of this turbulent flame. The liquid spray was treated with a traditional Lagrangian method and the gas-phase reaction was modeled using a detailed combustion model. A 103-species skeletal mechanism was used for the n-dodecane chemical kinetic model. Significantly different flame structures and ignition processes are observed for the LES compared to those of RANS predictions. The LES data suggests that the first ignition initiates in lean mixture and propagates to rich mixture, and the main ignition happens in rich mixture, preferable less than 0.14 in mixture fraction space. LES was observed to have multiple ignition spots in the mixing layer simultaneously while the main ignition initiates in a clearly asymmetric fashion. The temporal flame development also indicates the flame stabilization mechanism is auto-ignition controlled and modulated by flame propagation. Soot predictions by LES present much better agreement with experiments compared to RANS both qualitatively and quantitatively. Multiple realizations for LES were performed to understand the realization to realization variation and to establish best practices for ensemble-averaging diesel spray flames. The relevance index analysis suggests that an average of 2 and 5 realizations can reach 99\% of similarity to the target average of 16 realizations on the temperature and mixture fraction fields, respectively. However, more realizations are necessary for OH and soot mass fraction due to their high fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Kinetic Plasma Simulation in the MOOSE Framework: Verification of Electrostatic Particle In Cell Capabilities

In magnetic confinement nuclear fusion reactors, the interaction between the plasma edge and plasma facing components is extremely important. At the plasma edge, a kinetic representation such as particle-in-cell (rather than a fluid representation) is required to accurately capture the plasma behavior. General purpose particle-in-cell plasma simulation capabilities have been developed in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. This new capability is a part of the development of a new MOOSE-based framework for modeling plasma facing components, the Fusion ENergy Integrated multiphys-X (FENIX) framework. In this work, the verification of foundational particle-in-cell capabilities in FENIX is presented. This new plasma simulation capability has three main components: moving particles in discrete steps on the finite element mesh, mapping charge density from the particle's location to the finite element mesh, and solving for the electrostatic potential based on the charge density mapped from particles to the mesh. In this paper, simple verification problems demonstrating each of these new capabilities are presented, and future work includes electromagnetic capabilities and Monte Carlo collisions with neutral gas particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Using the Beopt Automated Residential Simulation Test Suite to Enable Comparative Analysis Between Energy Simulation Engines (Preprint)

Verification and validation are crucial software quality control procedures to follow when developing and implementing models. This is particularly important because a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes building models that isolate the impacts of specific components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models. These discrepancies are caused by differences in the algorithms used by the engines or coding errors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1964

Solar simulation in the MSC Space Environment Simulation Laboratory

The MSC Solar Simulator history and requirements for the Space Environment Simulation Laboratory (SESL) are briefly reviewed. A description is presented of the SESL, and a discussion is included of the solar simulator development and present status. A Radiant Intensity Measuring System for the SESL is briefly described.

SPACE ENVIRONMENT↗
DOE OSTI2014

Using the BEopt Automated Residential Simulation Test Suite to Enable Comparative Analysis Between Energy Simulation Engines: Preprint

Verification and validation are crucial software quality control procedures when developing and implementing models. This is particularly important as a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes models that isolate the impacts of specific building components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models; these discrepancies are caused by differences in the models used by the engines or coding errors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Bridging particle and reactor scales in the simulation of biomass fast pyrolysis by coupling particle resolved simulation and coarse grained CFD-DEM

Efficient utilization of biomass is challenging due to the complexity of the feedstock at molecular, particle, and reactor scales. Direct coupling of particle scale model and reactor scale simulation is computationally infeasible. In this work, the results from a particle resolved simulation were used to calibrate the heat transfer and reaction kinetics of particles. A hybrid drag model was used to consider the different fluidization properties of sands and biomass particles. The computation cost was reduced using a coarse-grained Discrete Element Method (DEM). The simulated conversion rate, char yield, tar yield, and pyrolysis gas yield compare well with experiment. The residence time and axial distributions of biomass were also analyzed. This novel multi-scale method provides an efficient and accurate tool for the modeling of biomass pyrolysis reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Computational simulation of a 100 kW dual circulating fluidized bed reactor processing coal by chemical looping with oxygen uncoupling

Chemical looping with oxygen uncoupling (CLOU) is a promising carbon capture technology that utilizes two interconnected fluidized-bed reactors to separate oxygen from air using a metal oxide, and then to use that oxygen to combust fuel in a nitrogen-free environment. CLOU is particularly well suited for solid fuels such as coal since released O 2 will readily combust with solid char. This study presents simulations of the University of Utah's dual fluidized bed chemical looping process development unit (PDU) operating as a CLOU system at 100 kW th , using CPFD Software's Barracuda-VR™ CFD modeling program. A full 3D model of the PDU was used including both reactors, as well as loop seals and cyclone separators. Hydrodynamic settings and the drag model are based on previous cold-flow validation experiments. Mechanisms describing CLOU reaction kinetics for cuprous oxide oxidation in the air reactor and cupric oxide reduction in the fuel reactor were adapted from previously completed experimental work. Coal char kinetics were based on the carbon-hydrogen-nitrogen-oxygen-sulfur, CHNOS, method. Submodels for devolatilization, gasification, and homogenous gas-phase reactions used relationships from the literature. Results predict volatile burnout almost immediately, though coal combustion continues into the upper portions of the fuel reactor and cyclone. Lastly, nitrogen gas leakage into the fuel reactor is shown to be mostly carryover from the air reactor

42 ENGINEERING↗
DOE OSTI2015

A practical discrete-adjoint method for high-fidelity compressible turbulence simulations

Methods and computing hardware advances have enabled accurate predictions of complex compressible turbulence phenomena, such as the generation of jet noise that motivates the present effort. However, limited understanding of underlying physical mechanisms restricts the utility of such predictions since they do not, by themselves, indicate a route to design improvements. Gradient-based optimization using adjoints can circumvent the flow complexity to guide designs, though this is predicated on the availability of a sufficiently accurate solution of the forward and adjoint systems. These are challenging to obtain, since both the chaotic character of the turbulence and the typical use of discretizations near their resolution limits in order to efficiently represent its smaller scales will amplify any approximation errors made in the adjoint formulation. Formulating a practical exact adjoint that avoids such errors is especially challenging if it is to be compatible with state-of-the-art simulation methods used for the turbulent flow itself. Automatic differentiation (AD) can provide code to calculate a nominally exact adjoint, but existing general-purpose AD codes are inefficient to the point of being prohibitive for large-scale turbulence simulations. Here, we analyze the compressible flow equations as discretized using the same high-order workhorse methods used for many high-fidelity compressible turbulence simulations, and formulate a practical space–time discrete-adjoint method without changing the basic discretization. A key step is the definition of a particular discrete analog of the continuous norm that defines our cost functional; our selection leads directly to an efficient Runge–Kutta-like scheme, though it would be just first-order accurate if used outside the adjoint formulation for time integration, with finite-difference spatial operators for the adjoint system. Its computational cost only modestly exceeds that of the flow equations. We confirm that its accuracy is limited by computing precision, and we demonstrate it on the aeroacoustic control of a mixing layer with a challengingly broad range of turbulence scales. For comparison, the error from a corresponding discretization of the continuous-adjoint equations is quantified to potentially explain its limited success in past efforts to control jet noise. The differences are illuminating: the continuous-adjoint is shown to suffer from exponential error growth in (reverse) time even for the best-resolved largest turbulence scales. Implications for jet noise reduction and turbulence control in general are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗