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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Turbine Engine Clearance Control Systems: Current Practices and Future Directions

Improved blade tip sealing in the high pressure compressor (HPC) and high pressure turbine (HPT) can provide dramatic reductions in specific fuel consumption (SFC), time-on-wing, compressor stall margin, and engine efficiency as well as increased payload and mission range capabilities. Maintenance costs to overhaul large commercial gas turbine engines can easily exceed $1M. Engine removal from service is primarily due to spent exhaust gas temperature (EGT) margin caused mainly by the deterioration of HPT components. Increased blade tip clearance is a major factor in hot section component degradation. As engine designs continue to push the performance envelope with fewer parts and the market drives manufacturers to increase service life, the need for advanced sealing continues to grow. A review of aero gas turbine engine HPT performance degradation and the mechanisms that promote these losses are discussed. Benefits to the HPT due to improved clearance management are identified. Past and present sealing technologies are presented along with specifications for next generation engine clearance control systems.

Lattime, Scott B.↗
NASA NTRS2015

A Methodology to Assess the Capability of Engine Designs to Meet Closed-loop Performance and Operability Requirements

Designing a closed-loop controller for an engine requires balancing trade-offs between performance and operability of the system. One such trade-off is the relationship between the 95% response time and minimum high-pressure compressor (HPC) surge margin (SM) attained during acceleration from idle to takeoff power. Assuming a controller has been designed to meet some specification on response time and minimum HPC SM for a mid-life (nominal) engine, there is no guarantee that these limits will not be violated as the engine ages, particularly as it reaches the end of its life. A characterization for the uncertainty in this closed-loop system due to aging is proposed that defines elliptical boundaries to estimate worst-case performance levels for a given control design point. The results of this characterization can be used to identify limiting design points that bound the possible con- troller designs yielding transient results that do not exceed specified limits in response time or minimum HPC SM. This characterization involves performing Monte Carlo simulation of the closed-loop system with controller constructed for a set of trial design points and developing curve fits to describe the size and orientation of each ellipse; a binary search procedure is then employed that uses these fits to identify the limiting design point. The method is demonstrated through application to a generic turbofan engine model in closed- loop with a simplified controller; it is found that the limit for which each controller was designed was exceeded by less than 4.76%. Extension of the characterization to another trade-off, that between the maximum high-pressure turbine (HPT) entrance temperature and minimum HPC SM, showed even better results: the maximum HPT temperature was estimated within 0.76%. Because of the accuracy in this estimation, this suggests another limit that may be taken into consideration during design and analysis. It also demonstrates the extension of the characterization to other attributes that contribute to the performance or operability of the engine. Metrics are proposed that, together, provide information on the shape of the trade-off between response time and minimum HPC SM, and how much each varies throughout the life cycle, at the limiting design points. These metrics also facilitate comparison of the expected transient behavior for multiple engine models.

engine control↗
NASA NTRS2015

A Methodology to Assess the Capability of Engine Designs to Meet Closed-Loop Performance and Operability Requirements

Designing a closed-loop controller for an engine requires balancing trade-offs between performance and operability of the system. One such trade-off is the relationship between the 95 percent response time and minimum high-pressure compressor (HPC) surge margin (SM) attained during acceleration from idle to takeoff power. Assuming a controller has been designed to meet some specification on response time and minimum HPC SM for a mid-life (nominal) engine, there is no guarantee that these limits will not be violated as the engine ages, particularly as it reaches the end of its life. A characterization for the uncertainty in this closed-loop system due to aging is proposed that defines elliptical boundaries to estimate worst-case performance levels for a given control design point. The results of this characterization can be used to identify limiting design points that bound the possible controller designs yielding transient results that do not exceed specified limits in response time or minimum HPC SM. This characterization involves performing Monte Carlo simulation of the closed-loop system with controller constructed for a set of trial design points and developing curve fits to describe the size and orientation of each ellipse; a binary search procedure is then employed that uses these fits to identify the limiting design point. The method is demonstrated through application to a generic turbofan engine model in closed-loop with a simplified controller; it is found that the limit for which each controller was designed was exceeded by less than 4.76 percent. Extension of the characterization to another trade-off, that between the maximum high-pressure turbine (HPT) entrance temperature and minimum HPC SM, showed even better results: the maximum HPT temperature was estimated within 0.76 percent. Because of the accuracy in this estimation, this suggests another limit that may be taken into consideration during design and analysis. It also demonstrates the extension of the characterization to other attributes that contribute to the performance or operability of the engine. Metrics are proposed that, together, provide information on the shape of the trade-off between response time and minimum HPC SM, and how much each varies throughout the life cycle, at the limiting design points. These metrics also facilitate comparison of the expected transient behavior for multiple engine models.

systems analysis↗
NASA NTRS2019

Dynamic Analysis of the STARC-ABL Propulsion System

In the pursuit of Electrified Aircraft Propulsion (EAP), much of the attention is on the development of hybrid electric concept vehicles and their propulsion systems from a steady state performance perspective. While it is steady-state performance that largely determines the efficiency of civil air transports, engine operability and transient performance define constraints for the steady state design that impact efficiency and system viability. Neglecting dynamics and control technologies can result in an over-designed, sub optimal propulsion system or a concept that is not feasible. Thus, dynamic system studies were conducted on the propulsion system of the conceptual aircraft design known as the Single-aisle Turboelectric AiRCraft with Aft Boundary Layer propulsor (STARC-ABL). This paper describes the development of a controller to verify the baseline concept's feasibility from an operability perspective. Further, studies were conducted to identify excessive stability margin in the baseline design that could be traded for potential benefits in efficiency through an engine re design. This study revealed the potential to reduce the high pressure compressor (HPC) stall margin by 3%. Finally, a study was conducted to investigate the potential benefit of adding energy storage to the STARC-ABL concept that further improves operability and enables more gains in engine efficiency and performance. The energy storage provided an additional 0.5% stall margin can be removed from the HPC.

dynamic systems analysis↗
NASA NTRS2019

Dynamic Analysis of the STARC-ABL Propulsion System

In the pursuit of Electrified Aircraft Propulsion (EAP), much of the attention is on the development of hybrid electric concept vehicles and their propulsion systems from a steady state performance perspective. While it is steady-state performance that largely determines the efficiency of civil air transports, engine operability and transient performance define constraints for the steady state design that impact efficiency and system viability. Neglecting dynamics and control technologies can result in an over-designed, sub optimal propulsion system or a concept that is not feasible. Thus, dynamic system studies were conducted on the propulsion system of the conceptual aircraft design known as the Single-aisle Turboelectric AiRCraft with Aft Boundary Layer propulsor (STARC-ABL). This paper describes the development of a controller to verify the baseline concept's feasibility from an operability perspective. Further, studies were conducted to identify excessive stability margin in the baseline design that could be traded for potential benefits in efficiency through an engine re design. This study revealed the potential to reduce the high pressure compressor (HPC) stall margin by 3%. Finally, a study was conducted to investigate the potential benefit of adding energy storage to the STARC-ABL concept that further improves operability and enables more gains in engine efficiency and performance. The energy storage provided an additional 0.5% stall margin can be removed from the HPC.

STARC-ABL↗
NASA NTRS2013

NASA Center for Climate Simulation (NCCS) Advanced Technology AT5 Virtualized Infiniband Report

The NCCS is part of the Computational and Information Sciences and Technology Office (CISTO) of Goddard Space Flight Center's (GSFC) Sciences and Exploration Directorate. The NCCS's mission is to enable scientists to increase their understanding of the Earth, the solar system, and the universe by supplying state-of-the-art high performance computing (HPC) solutions. To accomplish this mission, the NCCS (https://www.nccs.nasa.gov) provides high performance compute engines, mass storage, and network solutions to meet the specialized needs of the Earth and space science user communities

cloud↗
NASA NTRS2013

Virtualized Infiniband: Enabling HPC in the Cloud

Presentation describes virtualized infiniband and how it enables doing high performance computing level processing and file systems in a cloud environment. Generic benchmarks are included.

virtualization↗
NASA NTRS2019

Dynamic Analysis of the STARC-ABL Propulsion System

In the pursuit of Electrified Aircraft Propulsion (EAP), much of the attention is on the development of hybrid electric concept vehicles and their propulsion systems from a steady state performance perspective. While it is steady-state performance that largely determines the efficiency of civil air transports, engine operability and transient performance define constraints for the steady state design that impact efficiency and system viability. Neglecting dynamics and control technologies can result in an over-designed, sub optimal propulsion system or a concept that is not feasible. Thus, dynamic system studies were conducted on the propulsion system of the conceptual aircraft design known as the Single-aisle Turboelectric AiRCraft with Aft Boundary Layer propulsor (STARC-ABL). This paper describes the development of a controller to verify the baseline concept's feasibility from an operability perspective. Further, studies were conducted to identify excessive stability margin in the baseline design that could be traded for potential benefits in efficiency through an engine re design. This study revealed the potential to reduce the high pressure compressor (HPC) stall margin by 3%. Finally, a study was conducted to investigate the potential benefit of adding energy storage to the STARC-ABL concept that further improves operability and enables more gains in engine efficiency and performance. The energy storage provided an additional 0.5% stall margin can be removed from the HPC.

STARC-ABL↗
NASA NTRSDate not supplied

Earth System Digital Twins (ESDT)

"First Webinar for a digital twin webinar series titled ""Digital Twin Webinar Series 1: Concept, Practices, and Vision"". This kick-off webinar will focus on concepts, architecture and high level discussion on digital twins for Earth science and other domain sciences. The agenda will be the following: - Dr. Jacqueline Le Moigne is NASA AIST program manager, and the first federal program manager to programmatically fund 14 digital twin research projects. - Mr. Stan Posey is the HPC Program Manager, ESM and CFD Domains at NVIDIA. - Dr. Goodchild is a emeritus professor at UCSB, member of the national academy, and a founder of digital earth international society."

Information Systems↗
NASA NTRS2019

Electra: A Modular-Based Expansion of NASA's Supercomputing Capability

NASA has increasingly relied on high-performance computing (HPC) re- sources for computational modeling, simulation, and data analysis to meet the science and engineering goals of its missions in space exploration, aeronautics, and Earth and space science. The NASA Advanced Supercomputing (NAS) Division at Ames Research Center in Silicon Valley, Calif., hosts NASA’s premier supercomputing resources, integral to achieving and enhancing the success of the agency’s missions. NAS provides a balanced environment, funded under the High-End Computing Capability (HECC) project, comprised of world-class supercomputers, including its flagship distributed-memory cluster, Pleiades; high-speed networking; and massive data storage facilities, along with multi-disciplinary support teams for user support, code porting and optimization, and large-scale data analysis and scientific visualization. However, as scientists have increased the fidelity of their simulations and engineers are conducting larger parameter-space studies, the requirements for supercomputing resources have been growing by leaps and bounds. With the facility housing the HECC systems reaching its power and cooling capacity, NAS undertook a prototype project to investigate an alternative approach for housing supercomputers. Modular supercomputing, or container-based computing, is an innovative concept for expanding NASA’s HPC capabilities. With modular supercomputing, additional containers—similar to portable storage pods—can be connected together as needed to accommodate the agency’s ever-increasing demand for computing resources. In addition, taking advantage of the local weather permits the use of cooling technologies that would additionally save energy and reduce annual water usage. The first stage of NASA’s Modular Supercomputing Facility (MSF) prototype, which resulted in a 1,000 square-foot module on a concrete pad with room for 16 compute racks, was completed in Fall 2016 and an SGI (now HPE) computer system, named Electra, was deployed there in early 2017. Cooling is performed via an evaporative system built into the module, and preliminary experience shows a Power Usage Effectiveness (PUE) measurement of 1.03. Electra achieved over a petaflop on the LINPACK benchmark, sufficient to rank number 96 on the November 2016 TOP500 list [14]. The system consists of 1,152 InfiniBand-connected Intel Xeon Broadwell-based nodes. Its users access their files on a facility-wide file system shared by all HECC compute assets via Mellanox MetroX InfiniBand extenders, which connect the Electra fabric to Lustre routers in the primary facility over fiber-optic links about 900 feet long. The MSF prototype has exceeded expectations and is serving as a blueprint for future expansions. In the remainder of this chapter, we detail how modular data center technology can be used to expand an existing compute resource. We begin by describing NASA’s requirements for supercomputing and how resources were provided prior to the integration of the Electra module-based system.

Biswas, Rupak↗
NASA NTRSDate not supplied

Advanced Information Systems Technology for NASA Earth System Digital Twins (ESDT)

ESA and NASA have both started programs to design and develop Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. Earth System Digital Twins integrate diverse Earth and human activity models, continuous observations, and information system capabilities to provide unified, comprehensive representations and predictions that can be utilized for monitoring the health of the Planet, as well as for developing actionable information to support decision making. More generally, Digital Twins will help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change. This Townhall will first provide a short description of ESA’s, NASA’s and CNES’s current efforts in Digital Twins: • Destination Earth (DestinE) is the first initiative of the European Union to create a Digital Twin of the Earth, particularly focused on weather and climate, and as a coordinated effort between the European Centre for Medium-Range Weather Forecasts (ECMWF), ESA and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). • Additionally, ESA is developing several Digital Twin Earth Precursor Activities to study some of the key scientific and technical challenges associated with building a “Digital Twin Earth”. These include forests, hydrology, Antarctica, food systems, oceans, and climate hot spots Digital Twin prototypes. • NASA Earth Science Technology Office (ESTO)’s Advanced Information Systems Technology (AIST) Program has started an initiative in Earth System Digital Twins (ESDT), with 14 current projects in this area, developing various information systems technologies and prototypes that will help prepare the development of future NASA Digital Twins. • CNES is currently developing the concept of a Digital Twin Factory (DTF), which relies on a data lake, a high computing capability using clouds and/or HPC and has thematic algorithms and methodologies able to generate registered and coherent layers of information in order to enrich a datacube from which physical indicators can be computed spatially. NASA, ESA and CNES are also currently defining science use cases that will be presented during the townhall; those and a few short discussions of current projects will serve as a starting point to engage a dialogue about Digital Twins of the Earth with the IGARSS community.

earth science remote sensing; Information systems↗
NASA NTRSDate not supplied

Verification and Validation of Elastodynamic Simulation Software for Aerospace Research

Physics-based simulation of nondestructive evaluation (NDE) inspection can help to advance the inspectability and reliability of mechanical systems. However, NDE simulations applicable to non-idealized mechanical components often require large compute domains and long run times. This has prompted development of custom NDE simulation software tailored to high performance computing (HPC) hardware. Verification and validation (V&V) is an integral part of developing this software to ensure implementations are robust and applicable to inspection problems, producing tools and simulations suitable for computational NDE research. This presentation addresses factors common to V&V of several elastodynamic simulation codes applicable to ultrasonic NDE. Examples are drawn from in-house simulation software at NASA Langley Research Center, ranging from ensuring reliability in a 1D heterogeneous media wave equation solver to the V&V needs of 3D cluster-parallel elastodynamic software. Factors specific to a research environment are addressed, where individual simulation results can be as relevant as the software product itself. Distinct facets of V&V are discussed including testing to establish software reliability, employing systematic approaches for consistency with fundamental conservation laws, establishing the numerical stability of algorithms, and demonstrating concurrence with empirical data. This talk also addresses V&V practices for small groups of researchers. This includes establishing resources (e.g. time and personnel) for V&V during project planning to mitigate and control the risk of setbacks. Similarly, we identify ways for individual researchers to use V&V during simulation software development itself to both speed up the development process and reduce incurred technical debt.

NDE↗
NASA NTRS2013

Scheduling Operations for Massive Heterogeneous Clusters

High-performance computing (HPC) programming has become increasingly difficult with the advent of hybrid supercomputers consisting of multicore CPUs and accelerator boards such as the GPU. Manual tuning of software to achieve high performance on this type of machine has been performed by programmers. This is needlessly difficult and prone to being invalidated by new hardware, new software, or changes in the underlying code. A system was developed for task-based representation of programs, which when coupled with a scheduler and runtime system, allows for many benefits, including higher performance and utilization of computational resources, easier programming and porting, and adaptations of code during runtime. The system consists of a method of representing computer algorithms as a series of data-dependent tasks. The series forms a graph, which can be scheduled for execution on many nodes of a supercomputer efficiently by a computer algorithm. The schedule is executed by a dispatch component, which is tailored to understand all of the hardware types that may be available within the system. The scheduler is informed by a cluster mapping tool, which generates a topology of available resources and their strengths and communication costs. Software is decoupled from its hardware, which aids in porting to future architectures. A computer algorithm schedules all operations, which for systems of high complexity (i.e., most NASA codes), cannot be performed optimally by a human. The system aids in reducing repetitive code, such as communication code, and aids in the reduction of redundant code across projects. It adds new features to code automatically, such as recovering from a lost node or the ability to modify the code while running. In this project, the innovators at the time of this reporting intend to develop two distinct technologies that build upon each other and both of which serve as building blocks for more efficient HPC usage. First is the scheduling and dynamic execution framework, and the second is scalable linear algebra libraries that are built directly on the former.

Humphrey, John↗
NASA NTRSDate not supplied

Implicit Thermochemical Nonequilibrium Compressible Flow Simulations on Unstructured Grids Using GPUs

As next-generation exascale-class systems arrive, existing software must be updated accordingly to effectively utilize these systems. For high concurrency and energy efficiency, many of these systems utilize GPU architectures. In this work, we present a CUDA C++ implementation of FUN3D's thermochemical nonequilibrium capability for turbulent flows. Efficiency is demonstrated at scale using the Summit system at the Oak Ridge Leadership Computing Facility which is representative of future exascale systems. This work enables faster, higher fidelity, and scale-resolving simulations of thermochemical nonequilibrium flows including reentry, hypersonics, and combustion.

CFD, GPU, HPC, Hypersonics, Chemistry↗
NASA NTRS2006

Performance Evaluation of Supercomputers using HPCC and IMB Benchmarks

The HPC Challenge (HPCC) benchmark suite and the Intel MPI Benchmark (IMB) are used to compare and evaluate the combined performance of processor, memory subsystem and interconnect fabric of five leading supercomputers - SGI Altix BX2, Cray XI, Cray Opteron Cluster, Dell Xeon cluster, and NEC SX-8. These five systems use five different networks (SGI NUMALINK4, Cray network, Myrinet, InfiniBand, and NEC IXS). The complete set of HPCC benchmarks are run on each of these systems. Additionally, we present Intel MPI Benchmarks (IMB) results to study the performance of 11 MPI communication functions on these systems.

Saini, Subhash↗
NASA NTRS2016

NASA Phase2 Unlimited Rights Final Report Research and Technology for Aerospace Propulsion Systems (RTAPS) Task Order: ERA Advanced Core Compressor Technology Program

As part of the NASA Integrated Systems Research Program (ISRP), Environmentally Responsible Aviation (ERA) Project, NASA GRC and GE Aviation have partnered to investigate the technology barriers associated with improved fuel economy of large gas turbine engines. Crucial to improving fuel economy is the increase in pressure ratio (PR) of the core high pressure compressor (HPC). A key enabler to increasing HPC pressure ratios are new technology front stage airfoil designs that have higher efficiency, higher pressure ratios and improvements in front stage part-power operability. The purpose of this work is to design and test two high pressure ratio, high efficiency front block designs. The baseline design, hereafter referred to as Build 1, is similar to what would be found in a high efficiency 30:1 PR class HPC. A redesigned front block with improved blading will also be tested and hereafter be referred to as Build 2. The goal of Build 2 is to increase stage aero loading (increase stage pressure ratio) beyond Build 1 while maintaining equivalent efficiency and stall margin. The detailed inter-stage and traverse data from the two builds will be used to improve understanding of the complex flow physics at high-speed and part-speed conditions that impact performance and operability. By addressing, understanding and solving the challenges associated with aerodynamic losses and stage matching better design strategies can be incorporated in future core compressors with higher efficiency, thereby enabling improvement in mission fuel burn while still meeting operability requirements.

Axial Compressors↗
NASA NTRS2019

Scaling Evaluation of Ice-Crystal Icing on a Modern Turbofan Engine in PSL Using the COMDES-MELT Code

This paper presents preliminary ice-crystal icing (ICI) altitude scaling evaluation results of a Honeywell Uncertified Research Engine (HURE) that was tested in the NASA Glenn Research Center Propulsion Systems Laboratory (PSL) during January of 2018. This engine geometry features a hidden core design to keep the core less exposed. The engine was fitted with internal video cameras to observe various ice buildup processes at multiple selected locations within the engine core flow path covering the fan stator, the splitter-lip/shroud/strut, and the high pressure compressor (HPC) variable inlet guide vane (IGV) regions. The potential ice accretion risk was pre-determined to occur by using NASA’s in-house 1D Engine Icing Risk assessment code, COMDES-MELT. The code was successful in predicting the risk of ice accretion in adiabatic regions like the fan-stator of the HURE at specific engine operating points. However at several operating points during the test, liquid water was observed running along the shroud toward the variable IGV of the HPC regions with an air temperature well below freezing, thus no particle melting could have occurred due to heating from the air alone. It was reasoned that other sources of heat were present in that region. To account for these heat sources the inlet total temperature was adjusted to give a wet bulb temperature of 24 F below the standard minimum wet bulb temperature of 492 R to allow ice to accrete in the splitter-lip/shroud/strut region, which was determined from a reference case where hard ice was observed in that region. With that adjustment the COMDES-MELT code was successful in providing operating points where there was a risk of ice accretion during the test campaign. In addition to calculating possible conditions at different selected lower altitudes, simulations were run to determine potential inlet conditions that could lead to ice-crystal accretion along the prescribed stations where the cameras were available. From there, scaled test conditions were determined by best matching the following three icing related parameters of the reference condition: (1) the local air total wet bulb temperature, (2) the local ice crystal cloud melt ratio and (3) the engine fan face ice/water to air mass flux ratio of the ice crystal cloud. Instantaneous images taken from the time-lapsed movies of ice buildup were used along with the relevant thermodynamic data of air, water vapor and local icing condition to help evaluate how closely the proposed altitude scaling method could be used in ground based test facility to duplicate selected reference ICI features observed at specific location inside this engine at different scale altitudes. Discussions on observed limitation for engine icing scaling application from this test campaign and needed improvement are provided. A scaling test procedure to help identify potential ICI risk conditions and possible ice accretion locations of a new turbofan engine is evaluated in PSL.

Engine Testing in PSL↗
NASA NTRSDate not supplied

The Influence of Computer Architecture on Performance and Scaling for Hypersonic Flow Simulations

It is critical to understand how hypersonic simulation tools perform on a range of computational platforms. This information will aid in the acquisition of appropriate hardware and the potential refactoring of hypersonic codes to run on different systems. In this paper, we consider two representative high-speed reacting flow cases: a model Mach 8 hypersonic waverider glide vehicle and a model hydrocarbon-fueled hypersonic ramjet propulsion system. In both scenarios, the flow fields are in chemical non-equilibrium and are modeled by the multi-species reacting Navier-Stokes equations. For these simulations we use several hypersonic simulation tools, including US3D, Kestrel, FUN3D, and the JENRER© flow solver. We explore several high performance computing systems containing IntelR© XeonR© Platinum processors, AMD EPYCTM7702 processors, and NVIDIAR© Tesla V100 devices. We compare performance and strong scaling between the different systems.

CPU↗