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Ryan, Harry M.

Publications and source records attributed to Ryan, Harry M..

Spring 2014 Internship Diffuser Data Analysis

J-2X engine testing on the A-2 test stand at the NASA John C. Stennis Space Center (SSC) has recently concluded. As part of that test campaign, the engine was operated at lower power levels in support of expanding the use of J-2X to other missions. However, the A-2 diffuser was not designed for engine testing at the proposed low power levels. To evaluate the risk of damage to the diffuser, computer simulations were created of the rocket engine exhaust plume inside the 50ft long, water-cooled, altitude-simulating diffuser. The simulations predicted that low power level testing would cause the plume to oscillate in the lower sections of the diffuser. This can possibly cause excessive vibrations, stress, and heat transfer from the plume to the diffuser walls. To understand and assess the performance of the diffuser during low power level engine testing, nine accelerometers and four strain gages were installed around the outer surface of the diffuser. The added instrumentation also allowed for the verification of the rocket exhaust plume computational model. Prior to engine hot-fire testing, a diffuser water-flow test was conducted to verify the proper operation of the newly installed instrumentation. Subsequently, two J-2X engine hot-fire tests were completed. Hot-Fire Test 1 was 11.5 seconds in duration, and accelerometer and strain data verified that the rocket engine plume oscillated in the lower sections of the diffuser. The accelerometers showed very different results dependent upon location. The diffuser consists of four sections, with Section 1 being closest to the engine nozzle and Section 4 being farthest from the engine nozzle. Section 1 accelerometers showed increased amplitudes at startup and shutdown, but low amplitudes while the diffuser was started. Section 3 accelerometers showed the opposite results with near zero G amplitudes prior to and after diffuser start and peak amplitudes to +/- 100G while the diffuser was started. Hot-Fire Test 1 strain gages showed different data dependent on section. Section 1 strains were small, and were in the range of 50 to 150 microstrain, which would result in stresses from 1.45 to 4.35 ksi. The yield stress of the material, A-285 Grade C Steel, is 29.7 ksi. Section 4 strain gages showed much higher values with strains peaking at 1600 microstrain. This strain corresponds to a stress of 46.41 ksi, which is in excess of the yield stress, but below the ultimate stress of 55 to 75 ksi. The decreased accelerations and strain in Section 1, and the increased accelerations and strain in Sections 3 and 4 verified the computer simulation prediction of increased plume oscillations in the lower sections of the diffuser. Hot-Fire Test 2 ran for a duration of 125 seconds. The engine operated at a slightly higher power level than Hot-Fire Test 1 for the initial 35 seconds of the test. After 35 seconds the power level was lowered to Hot-Fire Test 1 levels. The acceleration and strain data for Hot-Fire Test 2 was similar during the initial part of the test. However, just prior to the engine being lowered to the Hot-Fire Test 1 power level, the strain gage data in Section 4 showed a large decrease to strains near zero microstrain from their peak at 1500 microstrain. Future work includes further strain and acceleration data analysis and evaluation.

Laigaie, Robert T.

Runtime and Pressurization Analyses of Propellant Tanks

Multi-element unstructured CFD has been utilized at NASA SSC to carry out analyses of propellant tank systems in different modes of operation. The three regimes of interest at SSC include (a) tank chill down (b) tank pressurization and (c) runtime propellant draw-down and purge. While tank chill down is an important event that is best addressed with long time-scale heat transfer calculations, CFD can play a critical role in the tank pressurization and runtime modes of operation. In these situations, problems with contamination of the propellant by inclusion of the pressurant gas from the ullage causes a deterioration of the quality of the propellant delivered to the test article. CFD can be used to help quantify the mixing and propellant degradation. During tank pressurization under some circumstances, rapid mixing of relatively warm pressurant gas with cryogenic propellant can lead to rapid densification of the gas and loss of pressure in the tank. This phenomenon can cause serious problems during testing because of the resulting decrease in propellant flow rate. With proper physical models implemented, CFD can model the coupling between the propellant and pressurant including heat transfer and phase change effects and accurately capture the complex physics in the evolving flowfields. This holds the promise of allowing the specification of operational conditions and procedures that could minimize the undesirable mixing and heat transfer inherent in propellant tank operation. It should be noted that traditional CFD modeling is inadequate for such simulations because the fluids in the tank are in a range of different sub-critical and supercritical states and elaborate phase change and mixing rules have to be developed to accurately model the interaction between the ullage gas and the propellant. We show a typical run-time simulation of a spherical propellant tank, containing RP-1 in this case, being pressurized with room-temperature nitrogen at 540 R. Nitrogen, shown in blue on the right-hand side of the figures, enters the tank from the diffuser at the top of the figures and impinges on the RP-1, shown in red, while the propellant is being continuously drained at the rate of 1050 lbs/sec through a pipe at the bottom of the tank. The sequence of frames in Figure 1 shows the resultant velocity fields and mixing between nitrogen and RP-1 in a cross-section of the tank at different times. A vortex is seen to form in the incoming nitrogen stream that tends to entrain propellant, mixing it with the pressurant gas. The RP-1 mass fraction contours in Figure 1 are also indicative of the level of mixing and contamination of the propellant. The simulation is used to track the propagation of the pure propellant front as it is drawn toward the exit with the evolution of the mixing processes in the tank. The CFD simulation modeled a total of 10 seconds of run time. As is seen from Figure 1d, after 5.65 seconds the propellant front is nearing the drain pipe, especially near the center of the tank. Behind this pure propellant front is a mixed fluid of compromised quality that would require the test to end when it reaches the exit pipe. Such unsteady simulations provide an estimate of the time that a high-quality propellant supply to the test article can be guaranteed at the modeled mass flow rate. In the final paper, we will discuss simulations of the LOX and propellant tanks at NASA SSC being pressurized by an inert ullage. Detailed comparisons will be made between the CFD simulations and lower order models as well as with test data. Conditions leading to cryo collapse in the tank will also be identified.

Field, Robert E.

Characterization and Analyses of Valves, Feed Lines and Tanks used in Propellant Delivery Systems at NASA SSC

Accurate modeling of liquid rocket engine test processes involves assessing critical fluid mechanic and heat and mass transfer mechanisms within a cryogenic environment, and accurately modeling fluid properties such as vapor pressure and liquid and gas densities as a function of pressure and temperature. The Engineering and Science Directorate at the NASA John C. Stennis Space Center has developed and implemented such analytic models and analysis processes that have been used over a broad range of thermodynamic systems and resulted in substantial improvements in rocket propulsion testing services. In this paper, we offer an overview of the analyses techniques used to simulate pressurization and propellant fluid systems associated with the test stands at the NASA John C. Stennis Space Center. More specifically, examples of the global performance (one-dimensional) of a propellant system are provided as predicted using the Rocket Propulsion Test Analysis (RPTA) model. Computational fluid dynamic (CFD) analyses utilizing multi-element, unstructured, moving grid capability of complex cryogenic feed ducts, transient valve operation, and pressurization and mixing in propellant tanks are provided as well.

Ryan, Harry M.

Overview of Propellant Delivery Systems at the NASA John C. Stennis Space Center

A wide range of rocket propulsion test work occurs at he NASA John C. Stennis Space Center (SSC) including full-scale engine test activities at test facilities A-1, A-2, B-1 and B-2 as well as combustion device research and development activities at the E-Complex (E-1, E-2. E-3 and E-4) test facilities. One of the greatest challenges associated with operating a test facility is maintaining the health of the primary propellant system and test-critical support systems. The challenge emerges due to the fact that the operating conditions of the various system components are extreme (e.g., low temperatures, high pressures) and due to the fact that many of the components and systems are unique. The purpose of this paper is to briefly describe the experience and modeling techniques that are used to operate the unique test facilities at NASA SSC that continue to support successful propulsion testing.

Haselmaier, L. Haynes

Testing Facility Uncertainty Analyses for RBCC Systems Testing

The Rocket Based Combined Cycle (RBCC) engine is expected to evolve based upon past combined-cycle propulsion test experience/data and new extensive test data. Currently, it is envisioned that a portion of the component and system testing will be pursued at NASA Stennis Space Center (SSC). To realize the greatest benefit of the test data, uncertainty analyses are being performed on the relevant RBCC components and systems to be tested at NASA SSC to ascertain the needed measurement requirements. These studies pertain to the existing E-Complex test stands as well as a new facility, E-4. This paper describes the approach used in the studies and gives examples to demonstrate the approach and the usefulness of the results. Future work will greatly increase the reliability of the test data while minimizing costs by focusing expenditures in the proper areas that are critical to program success and not allowing resources to be wasted in areas that are not significant relative to overall program goals.

Hudson, Susan T.