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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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This report focuses specifically on the development of a methodology to generate predictive kinematics in the absence of measured test data or the ability to test in the microgravity environment. The customer for this deliverable is the AEC project.
Advanced, near-net shape manufacturing methods have the potential to enable production of structures with fewer welds and reduced machining requirements. Two such methods that are suitable for the manufacturing of single-piece, stiffened barrel-shaped structures are presented. The first solution deployed existing manufacturing technology to produce a thick-walled barrel with integrally machined stiffeners. In this study, an 8-ft. diameter barrel was produced and subjected to a buckling test. Data on the manufacturing and testing of this barrel are provided and compared against the traditional multi-piece weld construction approach. The single-piece barrel resulted in a 28% greater load carrying capacity than the welded barrel. A second solution utilized a novel flow-forming technique to produce the barrel and stiffeners in one process without the need for welding or machining. This is an emerging manufacturing method known as the Integrally Stiffened Cylinder (ISC) process. This innovative process is being evaluated for launch vehicle and commercial aircraft manufacturing. The one-piece, stiffened ISC barrels, which have been successfully fabricated at 10 ft. in diameter, offer a direct replacement for conventional multi-piece, welded or riveted structures. A cost-benefit analysis for launch vehicle cryogenic propellant tanks estimated that the ISC process offers up to a 50% reduction in manufacturing costs and a 10% reduction in mass.
Two second-order Kalman filtering methods are added to the New Statistical Trajec-tory Estimation Program (NewSTEP). The two filters are of the class of Sigma-Point Kalman Filters, namely the Unscented Kalman Filter and the Divided Difference Filter. Both filters are implemented with an iterative measurement update step. Results from simulation test case and a flight data test case are provided to show the filter performance. The results indicate that the new second-order filters pro-duce trajectory estimates with reduced uncertainties when compared to the existing first-order filtering method.
In this study a method of determining the coefficients in a Prony series representation of a viscoelastic modulus from rate dependent data is presented. Load versus time test data for a sequence of different rate loading segments is least-squares fitted to a Prony series hereditary integral model of the material tested. A nonlinear least squares regression algorithm is employed. The measured data includes ramp loading, relaxation, and unloading stress-strain data. The resulting Prony series which captures strain rate loading and unloading effects, produces an excellent fit to the complex loading sequence.
Two RL10A-3-3A rocket engines comprise the main propulsion system for the Centaur upper stage vehicle. Centaur is used with bod Titan and Atlas launch vehicles, carrying military and civilian payloads from high altitudes into orbit and beyond. The RL10 has delivered highly reliable service for the past 30 years. Recently, however, there have been two in-flight failures which have refocused attention on the RL10. This heightened interest has sparked a desire for an independent RL10 modeling capability within NASA and th Air Force. Pratt & Whitney, which presently has the most detailed model of the RL10, also sees merit in having an independent model which could be used as a cross-check with their own simulations. The Space Propulsion Technology Division (SPTD) at the NASA Lewis Research Center has developed a computer model of the RL10A-3-3A. A project team was formed, consisting of experts in the areas of turbomachinery, combustion, and heat transfer. The overall goal of the project was to provide a model of the entire RL10 rocket engine for government use. In the course of the project, the major engine components have been modeled using a combination of simple correlations and detailed component analysis tools (computer codes). The results of these component analyses were verified with data provided by Pratt & Whitney. Select modeling results and test data curves were then integrated to form the RL10 engine system model The purpose of this report is to introduce the reader to the RL10 rocket engine and to describe the engine system model. The RL10 engine and its application to U.S. launch vehicles are described first, followed by a summary of the SPTD project organization, goals, and accomplishments. Simulated output from the system model are shown in comparison with test and flight data for start transient, steady state, and shut-down transient operations. Detailed descriptions of all component analyses, including those not selected for integration with the system model, are included as appendices.
Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.
Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.
A method for determining atmospheric absorption coefficients from acoustic flight test data is presented. Measurements from five series of acoustic flight tests were included in the study. The number of individual flights totaled 24: six Boeing 707 flights performed in May 1969 in connection with the turbofan nacelle modification program, eight flights from Boeing tests conducted during the same period, and 10 flights of the Boeing 747 airplane. The effects of errors in acoustic, meteorological, and aircraft performance and position measurements are discussed. Tabular data of the estimated sample variance of the data for each test are given for source directivity angles from 75 deg to 120 deg and each 1/3-octave frequency band. Graphic comparisons are made of absorption coefficients derived from ARP 866, using atmospheric profile data, with absorption coefficients determined by the experimental method described in the report.
Of the six chilldown tests, data from only one could be used for evaluation. During the rest of the chilldown tests, there was leakage hydrogen flow into the pump cavity prior to the initiation of the chilldown test. In all of the tests the hydrogen condition into the pump was probably 100% vapor. The data from this one test, therefore, can be used to compare only the single phase fluid correlation in the analytical pump chilldown model. In general, the actual pump chilled down much faster than predicted by the analytical pump model. There were insufficient data from the test to measure the pump flow rate and pump inlet fluid condition; therefore, these parameters were extrapolated based on related data which were available. However, even with the highest probable flow rate, the pump chilled faster than predicted.
The Compact Muon Solenoid (CMS) experiment will undergo changes as part of the Large Hadron Collider upgrade. The CMS tracker will be upgraded to cope with the new radiation environment and to provide tracking at the first level trigger. This upgrade features a new type of silicon module called PS Module, which combines a Pixel sensor and a Strip sensor in the same module. The pixel portion of the PS module has a sensor bump bonded to 16 Macro Pixel ASICs (MPA) to form a Macro Pixel Sub Assembly (MaPSA). At Fermilab, MaPSAs are tested for quality control before being assembled with the strip sensors, readout and service electronics to form a PS Module. All of this test data is stored in a centralized database, and is used to grade the final module to determine if it will be installed in the detector. The Phase II Outer Tracker Analyzer of Test Outputs (POTATO) is the software that processes this data and determines the module grades. Using recent technologies, an AI agent is being im plemented into POTATO in order to allow users to more efficiently sort through the large amounts of analysis data and ensure that only the user specified data is being considered. This poster will display the process of testing a MaPSA, how that test data is relevant to module assembly and grading, and how the POTATO grading tool is being improved with the use of an embedded AI agent.
HTTF Facility Selected test RELAP5-3D model Paul Bayless' model Recent model changes Ongoing work status Few preliminary results Outlook What is the plan going forward?
In June 2019, a full-scale crash test of a Fokker F28 Fellowship aircraft will be conducted at NASA Langley Research Center?s Landing and Impact Research (LandIR) Facility. The F28 is a high-performance twin-turbo fan narrow-body aircraft with seating in a 3+2 configuration. The MK4000 variant, used in this test, is capable of carrying up to 85 passengers on medium range routes. The F28 was first type certified by the Federal Aviation Administration (FAA) in 1969 and now the majority of the F28 fleet has retired from service in the United States. In 2016, the FAA and NASA Langley Research Center (LaRC) signed an interagency agreement for conducting a research program to obtain test data that will support the development of airframe level crash requirements for transport category airplanes [1]. The objectives of the full-scale crash test can be divided into six categories: (1) To compare and contrast responses in identical aircraft undergoing vertical only to combined vertical and horizontal loading conditions, (2) To examine the effects of horizontal loading on aircraft structure during a crash event, (3) To generate data for the use in calibration of computer modelling efforts, (4) To generate data from onboard Anthropomorphic Test Devices (ATDs) for the evaluation of injury, (5) To obtain data from experimental seats, and (6) To obtain data from new and novel ATD designs including Warrior Injury Assessment MANikin (WIAMan) [2], Test device for Human Occupant Response (THOR), and other newly developed child ATDs. The focus of this presentation will be to document finite element model development of the full-scale F28 aircraft and to present preliminary test-analysis predictions. NASA obtained the full-scale F28 aircraft, plus three fuselage sections and two sets of wings with funding through the NASA Aviation Safety Program in 1998. In addition to the hardware, NASA purchased a full NASTRAN model of the airframe that had been developed by the Dutch manufacturer, Fokker. Beginning in 2016, the NASTRAN model was converted to LS-DYNA? [4, 5] format and modified by combining parts, adding missing parts of internal structure, and including ballast for loading weights, etc. It contains: 89,223 nodes; 24,065 beam elements; 55,404 shell elements; 29,044 solid elements; 740 parts; 80 material definitions; and, 46 Constrained Nodal Rigid Bodies (CNRBs). The aircraft model will be executed in LSDYNA to simulate the test article impact onto a 2-ft.-high bed of soil under combined velocity conditions of 70-ft/s forward and 30-ft/s vertical velocity. Pre-test simulation predictions will be generated and correlated with test data.
Lithium-ion battery (LiB) technology is playing a crucial role in transforming the predominantly fossil fuel-based transportation and stationary storage sectors to achieve a low-carbon economy. Rapid innovation in the LiB materials to electrode to cell design is happening to satisfy the performance, life, and safety metrics required by those myriads of applications. Lately, advanced analytics, such as machine-learning or artificial intelligence (ML/AI) techniques, are being used more frequently to aid in expedited LiB technology development, performance validation, and life prediction. The success of these techniques often relies on a large volume of well-defined and high-quality battery test data. On the other hand, most battery developers and research and development (R&D) communities are still following a classical approach to develop batteries, which is running calendar- and/or cycle-aging tests, performing reference performance tests (RPTs), and conducting post-mortem analyses periodically without paying attention to the wealth of data often not collected during the calendar or cycle life aging tests. This sparse data collection approach is time- and resource-intensive, requiring data capture and evaluation of months to years of RPT data to diagnose accurate battery state of performance, health, and safety. Even so, the underlying aging modes and mechanisms can be missed. If collected properly, battery test data during cycling or calendaring can be efficiently combined with ML/AI techniques to create powerful tools in the rapid diagnosis of battery state of performance, health, and safety along with insights into underlying aging modes and mechanisms. In this report, we discuss the importance of effective cycle-by-cycle (CBC) data collection with example case studies. Within a reasonable timeframe, RPT data are often inadequate in capturing many of the crucial battery aging dynamics, which often predominantly show up in CBC test data. Finally, we also show examples of ML/AI techniques that use CBC data in rapid diagnosis and projection of LiB state of health (SOH) to motivate the scientific community in collecting and using CBC data to facilitate expeditious technology development and validation.
Application of the free-suspension residual flexibility modal test method to the International Space Station Pathfinder structure is described. The Pathfinder, a large structure of the general size and weight of Space Station module elements, was also tested in a large fixed-base fixture to simulate Shuttle Orbiter payload constraints. After correlation of the Pathfinder finite element model to residual flexibility test data, the model was coupled to a fixture model, and constrained modes and frequencies were compared to fixed-base test. modes. The residual flexibility model compared very favorably to results of the fixed-base test. This is the first known direct comparison of free-suspension residual flexibility and fixed-base test results for a large structure. The model correlation approach used by the author for residual flexibility data is presented. Frequency response functions (FRF) for the regions of the structure that interface with the environment (a test fixture or another structure) are shown to be the primary tools for model correlation that distinguish or characterize the residual flexibility approach. A number of critical issues related to use of the structure interface FRF for correlating the model are then identified and discussed, including (1) the requirement of prominent stiffness lines, (2) overcoming problems with measurement noise which makes the antiresonances or minima in the functions difficult to identify, and (3) the use of interface stiffness and lumped mass perturbations to bring the analytical responses into agreement with test data. It is shown that good comparison of analytical-to-experimental FRF is the key to obtaining good agreement of the residual flexibility values.
Wind tunnel to Atmospheric Mapping (WAM) is a methodology for scaling and testing a static aeroelastic wind tunnel model. The WAM procedure employs scaling laws to define a wind tunnel model and wind tunnel test points such that the static aeroelastic flight test data and wind tunnel data will be correlated throughout the test envelopes. This methodology extends the notion that a single test condition - combination of Mach number and dynamic pressure - can be matched by wind tunnel data. The primary requirements for affecting this extension are matching flight Mach numbers, maintaining a constant dynamic pressure scale factor and setting the dynamic pressure scale factor in accordance with the stiffness scale factor. The scaling is enabled by capabilities of the NASA Langley Transonic Dynamics Tunnel (TDT) and by relaxation of scaling requirements present in the dynamic problem that are not critical to the static aeroelastic problem. The methodology is exercised in two example scaling problems: an arbitrarily scaled wing and a practical application to the scaling of the Active Aeroelastic Wing flight vehicle for testing in the TDT.
Steady-state and transient computer models of the RL10A-3-3A rocket engine have been created using the Rocket Engine Transient Simulation (ROCETS) code. These models were created for several purposes. The RL10 engine is a critical component of past, present, and future space missions; the model will give NASA an in-house capability to simulate the performance of the engine under various operating conditions and mission profiles. The RL10 simulation activity is also an opportunity to further validate the ROCETS program. The ROCETS code is an important tool for modeling rocket engine systems at NASA Lewis. ROCETS provides a modular and general framework for simulating the steady-state and transient behavior of any desired propulsion system. Although the ROCETS code is being used in a number of different analysis and design projects within NASA, it has not been extensively validated for any system using actual test data. The RL10A-3-3A has a ten year history of test and flight applications; it should provide sufficient data to validate the ROCETS program capability. The ROCETS models of the RL10 system were created using design information provided by Pratt & Whitney, the engine manufacturer. These models are in the process of being validated using test-stand and flight data. This paper includes a brief description of the models and comparison of preliminary simulation output against flight and test-stand data.
An experimental investigation of the Common Research Model with Natural Laminar Flow (CRM-NLF) took place in the National Transonic Facility (NTF) at the NASA Langley Research Center in 2018. The 5.2% scale semispan model was designed using a new natural laminar flow design method, Crossflow Attenuated NLF (CATNLF). CATNLF enables laminar flow on typical transport wings with high sweep and Reynolds number by reshaping the wing airfoils to obtain specific pressure distribution characteristics that control the crossflow growth near the leading edge. The CATNLF method also addresses Tollmien- Schlichting transition, attachment line transition, and Görtler vortices. During the wind tunnel test, data were acquired to address three primary test objectives: validate the CATNLF design method, characterize the NTF laminar flow testing capabilities, and establish best practices for laminar flow wind tunnel testing. The present paper provides both experimental and computational data to understand the CRM-NLF laminar flow characteristics, as well as address the three primary test objectives. The effects of angle of attack and Reynolds number on the CRM-NLF laminar flow extent are studied, and the dominant transition mechanism is evaluated at a variety of test conditions. Critical N-factors are calculated for the NTF environment, and a discussion on best practices for laminar flow wind tunnel testing is provided. The CRM-NLF in the NTF provided initial confirmation of the ability of the CATNLF method to suppress crossflow growth and enable significant extents of laminar flow on transport wings with high sweep and Reynolds numbers.
Total ionizing dose radiation test data on integrated circuits are analyzed. Tests were performed with the electron accelerator (Dynamitron) that provides a steady state 2.5 MeV electron beam. Some radiation exposures were made with a Cobalt-60 gamma ray source. The results obtained with the Cobalt-60 source are considered an approximate measure of the radiation damage that would be incurred by an equivalent dose of electrons.