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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

3D Multistage Simulation of Each Component of the GE90 Turbofan Engine

A 3D multistage simulation of each component of the GE90 Turbofan engine has been made. This includes 49 blade rows. A coupled simulation of all blade rows will be made very soon. The simulation is running using two levels of parallelism. The first level is on a blade row basis with information shared using files. The second level is using a grid domain decomposition with information shared using MPI. Timings will be shown for running on the SP2, an SGI Origin and a distributed system of HP workstations. On the HP workstations, the CHIMP version of MPI is used, with queuing supplied by LSF (Load Sharing Facility). A script-based control system is used to ensure reliability. An MPEG movie illustrating the flow simulation of the engine has been created using PV3, a parallel visualization library created by Bob Haimes of MIT. PVM is used to create a virtual machine from 10 HP workstations and display on an SGI workstation. A representative component simulation will be compared to rig data to demonstrate its usefulness in turbomachinery design and analysis.

Turner, Mark↗
DOE OSTI2021

Transforming Energy through Computational Excellence. Exascale Computing: Combustion; Simulating Effects of Fuel Injection Location in Supersonic Jet Engines

Computational tractable simulations using an adaptive-mesh-refinement solverfor compressible reacting flows help researchers understand how variations in fuel injection location within the supersonic flow cavity impacts combustion efficiency. By identifying the important physical determinants of the combustion processes, this study shows a promising pathway to improving flame stability and combustion efficiency, as well as reducing emissions.

adaptive mesh refinement↗
DOE OSTI2015

KIVA Software

KIVA is a family of Fortran-based Computational Fluid Dynamics (CFD) software that predicts complex multi-species multi-phase turbulent fuel and air flows. KIVA models all engine combustion processes with models for spray, soot formation, spark ignition, and reactive chemistry (including pollutantformation processes). Employing KIVA software helps to optimize internal combustion engine processes, including diesel engines, for higher efficiency and lower emissions. KIVA engine modeling routines such as spray and core CFD Arbitrary Lagrangian-Eulerian (ALE) algorithms are now ubiquitous in the industry of engine code simulators. In addition, many engineers and researchers have made modifications to or enhanced our routines to address specific problems in engine designs.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2012

A Systems-Level Perspective on Engine Ice Accretion

Talk covers: (1) Problem of Engine Power Loss;(2) Modeling Engine Icing Effects; (3) Simulation of Engine Rollback; (4) Icing/Engine Control System Interaction; (5) Detection of Ice Accretion; (6) Potential Mitigation Strategies.

May, Ryan David↗
NASA NTRS2014

Aviation Trends Related to Atmospheric Environment Safety Technologies Project Technical Challenges

Current and future aviation safety trends related to the National Aeronautics and Space Administration's Atmospheric Environment Safety Technologies Project's three technical challenges (engine icing characterization and simulation capability; airframe icing simulation and engineering tool capability; and atmospheric hazard sensing and mitigation technology capability) were assessed by examining the National Transportation Safety Board (NTSB) accident database (1989 to 2008), incidents from the Federal Aviation Administration (FAA) accident/incident database (1989 to 2006), and literature from various industry and government sources. The accident and incident data were examined for events involving fixed-wing airplanes operating under Federal Aviation Regulation (FAR) Parts 121, 135, and 91 for atmospheric conditions related to airframe icing, ice-crystal engine icing, turbulence, clear air turbulence, wake vortex, lightning, and low visibility (fog, low ceiling, clouds, precipitation, and low lighting). Five future aviation safety risk areas associated with the three AEST technical challenges were identified after an exhaustive survey of a variety of sources and include: approach and landing accident reduction, icing/ice detection, loss of control in flight, super density operations, and runway safety.

Reveley, Mary S.↗
DOE OSTI2015

Development of Kinetic Mechanisms for Next-Generation Fuels and CFD Simulation of Advanced Combustion Engines

Predictive chemical kinetic models are needed to represent next-generation fuel components and their mixtures with conventional gasoline and diesel fuels. These kinetic models will allow the prediction of the effect of alternative fuel blends in CFD simulations of advanced spark-ignition and compression-ignition engines. Enabled by kinetic models, CFD simulations can be used to optimize fuel formulations for advanced combustion engines so that maximum engine efficiency, fossil fuel displacement goals, and low pollutant emission goals can be achieved.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Engineering Dynamically Decoupled Quantum Simulations with Trapped Ions

An external drive can improve the coherence of a quantum many-body system by averaging out noise sources. It can also be used to realize models that are inaccessible in the static limit, through Floquet Hamiltonian engineering. The full possibilities for combining these tools remain unexplored. We develop the requirements needed for a pulse sequence to decouple a quantum many-body system from an external field without altering the intended dynamics. Demonstrating this technique experimentally in an ion-trap platform, we show that it can provide a large improvement to coherence in real-world applications. Finally, we engineer an approximate quantum simulation of the Haldane-Shastry model, an exactly solvable paradigm for long-range interacting spins. Our results expand and unify the quantum simulation toolbox.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1957

Altitude-Wind-Tunnel Investigation of the 19B-2, 19B-8, and 19XB-1 Jet Propulsion Engines: Performance and Windmilling Drag Characteristics - 3

The performance characteristics of the 19B-8 and 19XB-1 turbojet engines and the windmilling-drag characteristics of the 19B-6 engine were determined in the Cleveland altitude wind tunnel. The investigations were conducted on the 19B-8 engine at simulated altitudes from 5000 to 25,000 feet with various free-stream ram-pressure ratios and on the 19XB--1 engine at simulated altitudes from 5000 to 30,000 feet with approximately static free-stream conditions. Data for these two engines are presented to show the effect of altitude, free-stream ram-pressure ratio, and tail-pipe-nozzle area on engine performance. A 21-percent reduction in tail-pipe-nozzle area of the 19B-8 engine increased the let thrust 43 percent the net thrust 72 percent, and the fuel consumption 64 percent. An increase in free-stream ram-pressure ratio raised the jet thrust and the air flow and lowered the net thrust throughout the entire range of engine speeds for the 19B-8 engine. At similar operating conditions, the corrected jet thrust and corrected air flow were approximately the same for both engines, and the corrected specific fuel consumption based on jet thrust was lower for the 19XB-1 engine than for the 19B-8 engine. The thrust and air-flow data obtained with both engines at various altitudes for a given free-stream rampressure ratio were generalized to standard sea-level atmospheric conditions. The performance parameters involving fuel consumption generalized only at high engine speeds at simulated altitudes as high as 15,000 feet. The windmilling drag of the 19B-8 engine increased rapidly as the airspeed was increased.

Fleming, WIlliam A.↗
DOE OSTI2022

Support Vector Machines for Estimating Decision Boundaries with Numerical Simulations

Many engineering design problems can be formulated as decisions between two possible options. This is the case, for example, when a quantity of interest must be maintained below or above some threshold. The threshold thereby determines which input parameters lead to which option, and creates a boundary between the two options known as the decision boundary. This report details a machine learning approach for estimating decision boundaries, based on support vector machines (SVMs), that is amenable to large scale computational simulations. Because it is computationally expensive to evaluate each training sample, the approach iteratively estimates the decision boundary in a manner that requires relatively few training samples to glean useful estimates. The approach is then demonstrated on three example problems from structural mechanics and heat transport.

25 ENERGY STORAGE↗
DOE OSTI2025

Quantum simulation of charge and exciton transfer in multi-mode models using engineered reservoirs

Quantum simulation enables studies of open-system dynamics in non-perturbative regimes by programming electronic, vibrational, and environmental interactions on comparable energy scales. Trapped ions offer this capability, combining spins, phonons, and tunable dissipation on one platform. We demonstrate an open-system quantum simulation of charge and exciton transfer in a multi-mode linear vibronic coupling model. Using tailored spin-phonon interactions with reservoir engineering, we emulate a system with two dissipative vibrational modes coupled to donor and acceptor sites and track its non-equilibrium dynamics. We continuously tune the system from the charge transfer regime to the vibrationally assisted exciton transfer regime and find that degenerate modes enhance transfer rates at large energy gaps, while non-degenerate modes activate pathways that reduce the energy-gap dependence. Thus, the presence of one additional vibration introduces interfering pathways and reshapes non-perturbative excitation transfer. Our results establish a scalable, hardware-efficient route to simulate vibronic processes with engineered environments.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1991

Simulation of a combined-cycle engine

A FORTRAN computer program was developed to simulate the performance of combined-cycle engines. These engines combine features of both gas turbines and reciprocating engines. The computer program can simulate both design point and off-design operation. Widely varying engine configurations can be evaluated for their power, performance, and efficiency as well as the influence of altitude and air speed. Although the program was developed to simulate aircraft engines, it can be used with equal success for stationary and automative applications.

Vangerpen, Jon↗
NASA NTRS1994

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Litt, Jonathan↗
DOE OSTI2019

Innovative Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Numerical simulation of non-isothermal multiphase porous flow combined with reactive transport is used in a wide range of applications, which include nuclear waste repositories, enhanced recovery of petroleum reservoirs, contaminant remediation, geothermal engineering, and carbon sequestration. Understanding and predicting underground phenomena can have enormous impact on how to deal with world issues like climate change, clean water, and renewable energy. The main motivation for this proposal arises from safety assessment of future nuclear waste repositories using the U.S. Department of Energy (DOE) Geologic Disposal Safety Assessment (GDSA) Framework, and performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the nation's only active nuclear waste repository in Carlsbad, New Mexico. I am a technical staff member at Sandia National Laboratories involved in both projects.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles

Optimal engine operation during a transient driving cycle is the key to achieving greater fuel economy, engine efficiency, and reduced emissions. In order to achieve continuously optimal engine operation, engine calibration methods use a combination of static correlations obtained from dynamometer tests for steady-state operating points and road and/or track performance data. As the parameter space of control variables, design variable constraints, and objective functions increases, the cost and duration for optimal calibration become prohibitively large. In order to reduce the number of dynamometer tests required for calibrating modern engines, a large-scale simulation-driven machine learning approach is presented in this work. A parallel, fast, robust, physics-based reduced-order engine simulator is used to obtain performance and emission characteristics of engines over a wide range of control parameters under various transient driving conditions (drive cycles). We scale the simulation up to 3,906 nodes of the Theta supercomputer at the Argonne Leadership Computing Facility to generate data required to train a machine learning model. The trained model is then used to predict various engine parameters of interest, and the results are compared with those predicted by the engine simulator. Our results show that a deepneural-network-based surrogate model achieves high accuracy: Pearson product-moment correlation values larger than 0.99 and mean absolute percentage error within 1.07% for various engine parameters such as exhaust temperature, exhaust pressure, nitric oxide, and engine torque. Once trained, the deep-neural-network-based surrogate model is fast for inference: it requires about 16 mu s for predicting the engine performance and emissions for a single design configuration compared with about 0.5 s per configuration with the engine simulator. Moreover, we demonstrate that transfer learning and retraining can be leveraged to incrementally retrain the surrogate model to cope with new configurations that fall outside the training data space.

deep learning↗
DOE OSTI2015

Capturing Cyclic Variability in EGR Dilute SI Combustion using Multi-Cycle RANS

Dilute combustion is an effective approach to increase the thermal efficiency of spark-ignition (SI) internal combustion engines (ICEs). However, high dilution levels typically result in large cycle-to-cycle variations (CCV) and poor combustion stability, therefore limiting the efficiency improvement. In order to extend the dilution tolerance of SI engines, advanced ignition systems are the subject of extensive research. When simulating the effect of the ignition characteristics on CCV, providing a numerical result matching the measured average in-cylinder pressure trace does not deliver useful information regarding combustion stability. Typically Large Eddy Simulations (LES) are performed to simulate cyclic engine variations, since Reynold-Averaged Navier-Stokes (RANS) modeling is expected to deliver an ensemble-averaged result. In this paper it is shown that, when using RANS, the cyclic perturbations coming from different initial conditions at each cycle are not damped out even after many simulated cycles. As a result, multi-cycle RANS results feature cyclic variability. This allows evaluating the effect of advanced ignition sources on combustion stability but requires validation against the entire cycle-resolved experimental dataset. A single-cylinder GDI research engine is simulated using RANS and the numerical results for 20 consecutive engine cycles are evaluated for several operating conditions, including stoichiometric as well as EGR dilute operation. The effect of the ignition characteristics on CCV is also evaluated. Results show not only that multi-cycle RANS simulations can capture cyclic variability and deliver similar trends as the experimental data, but more importantly that RANS might be an effective, lower-cost alternative to LES for the evaluation of ignition strategies for combustion systems that operate close to the stability limit.

Scarcelli, Riccardo↗
NASA NTRS1991

A simulation study of turbofan engine deterioration estimation using Kalman filtering techniques

Deterioration of engine components may cause off-normal engine operation. The result is an unecessary loss of performance, because the fixed schedules are designed to accommodate a wide range of engine health. These fixed control schedules may not be optimal for a deteriorated engine. This problem may be solved by including a measure of deterioration in determining the control variables. These engine deterioration parameters usually cannot be measured directly but can be estimated. A Kalman filter design is presented for estimating two performance parameters that account for engine deterioration: high and low pressure turbine delta efficiencies. The delta efficiency parameters model variations of the high and low pressure turbine efficiencies from nominal values. The filter has a design condition of Mach 0.90, 30,000 ft altitude, and 47 deg power level angle (PLA). It was evaluated using a nonlinear simulation of the F100 engine model derivative (EMD) engine, at the design Mach number and altitude over a PLA range of 43 to 55 deg. It was found that known high pressure turbine delta efficiencies of -2.5 percent and low pressure turbine delta efficiencies of -1.0 percent can be estimated with an accuracy of + or - 0.25 percent efficiency with a Kalman filter. If both the high and low pressure turbine are deteriorated, the delta efficiencies of -2.5 percent to both turbines can be estimated with the same accuracy.

Lambert, Heather H.↗