Simulating the SLS Sound Suppression Water System

NASA’s next-generation Space Launch System (SLS) for deep space exploration consists of four RS-25 liquid rocket engines and two five-segment solid rocket boosters (SRBs). At ignition, the SRBs create a significant over-pressure event, known as the Ignition Over-Pressure (IOP) event. The IOP event experienced in the first space shuttle flight (STS-1) in 1981 damaged the space shuttle orbiter and motivated significant design changes to the launch pad at NASA’s Kennedy Space Center. The RS-25 liquid rocket engines aboard the SLS, along with the SRBs, also create a very significant acoustic environment that, if not mitigated, can harm the SLS launch vehicle. An Ignition Over-Pressure/Sound Suppression (IOP/SS) water system was developed to reduce the amplitude of both the IOP event and the acoustic environment caused by the firing of the RS-25 engines and the SRBs.

Simulation of the IOP/SS system projecting water during ignition, depicted by a light blue isosurface under the Space Launch System’s RS-25 liquid engines. Note the undesirable water splash upward between the two north and south engine banks. (Jeff West, NASA Marshall)

Mitigation of the IOP and acoustic environment relies on proper design of the IOP/SS system. One of several important aspects of the design is the placement of the water spray so that it reduces pressure and sound within the launch environment while not interfering with the nominal operation of other subsystems in the vicinity of the water system, such as the RS-25 engines, the SRBs, and Hydrogen Burn-off Igniter (HBOI) systems. The volume of fluid (VOF) model developed using the Loci-STREAM computational fluid dynamics (CFD) software program provides the ability to simulate the placement of water within the IOP/SS system. The Loci-STREAM-VOF program was developed at NASA’s Marshall Space Flight Center to enable the use of high-performance computing for the VOF algorithm.

A detailed CFD model of the launch pad was developed, including the IOP/SS water system and the lower portions of the SLS launch vehicle, consisting of 82 million volume cells. The Loci-STREAM-VOF CFD program was then used to perform an unsteady simulation of the IOP/SS water system. This CFD simulation — the first of its kind — was used to determine the optimal placement of the water for reducing IOP and acoustic amplitudes, and maintaining operation of the other subsystems.

The CFD simulations of the initial designs identified water projection patterns that adversely interacted with both the SRBs and the HBOI subsystems. Based on the simulation results, the design of the IOP/SS system was significantly altered to avoid these problems while still performing its intended mitigation function. The CFD simulations also determined that the IOP/SS system was creating an air entrainment effect, or waterfall effect, which interfered with the intended operation of the HBOI subsystem. In this case, an HBOI system design change was devised that accommodated the waterfall effect. As a result, the IOP/SS and HBOI systems are expected to operate as intended during an SLS launch — avoiding expensive redesigns and schedule delays that would have occurred if these problems had been detected much later during full-scale testing activities.

The elevation of Greenland’s ice bed is a major factor in accurately projecting the evolution of the ice sheet. Fortunately, the Ice Sheet System Model (ISSM) can be used to approximate the bed topography. This image gives the elevation of the bed in meters.

Projecting Sea Level Rise

The ability to accurately project sea level rise (SLR) in a changing climate is of paramount importance to mitigate its socio-economic impacts. One of the most significant contributions to SLR comes from freshwater fluxes (evaporation and precipitation) originating in the melting polar ice sheets of Greenland and Antarctica. Understanding and projecting the evolution of these ice caps is a priority for the global science community.

A team at NASA’s Jet Propulsion Laboratory (JPL) and the University of California at Irvine (UCI) has developed open-source Ice Sheet System Model (ISSM) software to assimilate remote sensing data into projections of the water mass for both Greenland and Antarctica. The ISSM team aims to accurately assess the future contribution of freshwater fluxes to the ocean, and understand how this contribution will impact SLR in the coming decades.

Accurately modeling the evolution of ice sheets involves complex physical processes that are still not fully understood, and requires a significant amount of computing power. Furthermore, large amounts of input data (coming from various sources such as regional climate models) need to be processed. To address these issues, ISSM is used. The state-of-the-art finite element model takes full advantage of a wide range of high-performance computing (HPC) environments. The HPC element is essential for dealing with the degrees of freedom that arise as a result of the huge problem domain and complex equations that govern ice flow.

Cart3D automates the grid layouts for aircraft and spacecraft design analysis.

The results have had a widespread impact on the cryosphere scientific community. Among the team’s most significant contributions are the new capabilities to automatically differentiate the ISSM code base in order to assimilate NASA’s remote sensing data, and to perform uncertainty quantification. Moreover, optimization procedures utilizing NASA’s Operation IceBridge data have produced an accurate and physically consistent bedrock topography of the Greenland ice sheet.

Modeling of Complex Flow

Developed at NASA’s Ames Research Center and named NASA Software of the Year in 2002, Cart3D is a high-fidelity inviscid analysis package for conceptual and preliminary aerodynamic design. It allows users to perform automated CFD analysis on complex geometry, and supports steady and time-dependent simulations. The package features fully integrated adjoint-driven mesh adaptation, and includes utilities for geometry import, surface modeling and intersection, mesh generation, and post-processing of results. The main flow solvers run in parallel using either shared memory (OpenMP) or distributed memory (MPI) with excellent scalability.

Cubes is an automated mesh generation tool in Cart3D that produces Cartesian meshes around arbitrarily complex, watertight geometry. The mesh is adaptively refined based on the local curvature of the geometry. The time to generate a mesh is insensitive to the complexity of the geometry. The highly optimized code generates meshes at more than four million cells per minute on typical desktop computers, and memory requirements are below one gigabyte per million cells.

Passive particle visualization of a contra-rotating, open-rotor simulation created using LAVA. Red particles are seeded on the upstream blades; blue on the aft blades. Solid colors are seeded on the tips, while faded colors are on the blade trailing edges. (Michael Barad, Cetin Kiris, NASA Ames)

FlowCart is a scalable, multilevel, linearly exact upwind solver in Cart3D that uses on-the-fly domain-decomposition to achieve excellent scalability on modern multicore computers. It is among the most scalable, accurate, and robust codes in the industry. On most modern desktop machines, it can converge well over 2 million cells per hour, per core, and is targeted directly at multicore CPUs. FlowCart is tightly integrated into Cart3D with a suite of automation tools built around it. Since it is a multilevel code, it converges very quickly and includes the latest technical developments on low-dissipation numerics, solid wall boundaries, mesh interfaces, and limiters.

Another software package that enables CFD was developed at Langley Research Center. The software’s fast user run-time, robustness, and efficiency have enabled its extensive use in space shuttle modeling. The Adaptive Refinement Tool (ART) permits the computational modeling of flow, including jet or rocket plumes, wakes, and shocks via unstructured tetrahedral grids. The ART package was developed in response to an internal need to model complicated flow models. Commercially available software did not allow NASA the flexibility to model the complexities associated with spacecraft reentry, or to model unusual and unforeseen scenarios.

The major source of broadband noise generation from aircraft slats comes from the wake (generated from the leading edge) and its impingement on the lower surface of the slat. In this figure, an iso-contour of Q-criteria, colored by streamwise velocity, illustrates the wake in the slat cove region (blue denotes low velocity; red is high velocity). Note that a 2D Kelvin-Helmholtz instability generated just downstream of the leading edge quickly develops small, three-dimensional structures. (Jeffrey Housman, NASA Ames)

ART executes commands via colloquial English, and has built-in internal statistical programming that increases its ease of use. ART allows the user the choice of alternate variables such as temperature or pressure at will, which facilitates modeling unusual or unlikely occurrences. ART also allows cells to be divided into two, four, or eight cells as compared to traditional software, which allows cell division only in units of eight. This is advantageous as it allows the user to control cell division more succinctly. With the end goal being flexibility, NASA based ART on standard Fortran-90 language and used tetrahedrals as opposed to rectangles in the grid design.

Simulating Cleaner Skies and Quieter Aircraft

There are many studies proving that exposure to airplane noise leads to increased stress, possible hearing loss, and other negative health effects. Noise generated by high-lift devices on aircraft, such as the slats located at the front of the wings, causes large-amplitude broadband sound waves. These waves propagate down to communities near airports, causing disruption and annoyance. To create cleaner, quieter aircraft, NASA is working with aviation industry partners to develop green aviation tools and technologies that will improve fuel efficiency, reduce harmful carbon emissions, and meet noise restriction standards for people living around airports and for passengers in airplane cabins.

One concept being studied under NASA’s Environmentally Responsible Aviation (ERA) and Advanced Air Transport Technology (AATT) projects is the contra-rotating open rotor propulsion system, which has two ultra-thin blades spinning in opposite directions on the same shaft — picture two rows of blades on a giant kitchen blender. These contra-rotating blades rotate around the outside of a turbofan jet engine. Some advantages of this design include more efficient airflow through the turbofan blades to improve flight performance and reduce carbon emissions. But like blenders, the blade rotations are noisy.

To support the AATT project’s goal to develop feasible hybrid gas-electric propulsion systems for commercial aircraft, aeronautics researchers at Ames Research Center’s NASA Advanced Supercomputing (NAS) facility have produced unique aeroacoustic simulations using their in-house Launch Ascent and Vehicle Aerodynamics (LAVA) software framework to reliably predict noise sources for contra-rotating open rotors.

The simulations and results generated by LAVA are helping the AATT project assess the agency’s modeling and simulation tools to support the design and development of new propulsion systems. “We took on the challenge of simulating the complex aerodynamic flows in the open rotor design with LAVA to see if we could help the aeronautics community better understand the noise-generation process,” said Cetin Kiris, chief of the NAS Division’s Computational Aerosciences Branch and leader of the LAVA development team.

Kiris explained that one of LAVA’s key features is a Cartesian immersed boundary flow solver that takes advantage of traditional computer-aided design (CAD) files, giving NASA scientists the ability to bypass the tedious grid-generation process and start their number crunching right away on their open-rotor (and similar) computational problems. “One of our most important findings is that acoustic tones predicted by the Cartesian immersed boundary and traditional body-fitted methods compared well with wind tunnel experiments,” Kiris said.

To verify the accuracy of the LAVA CFD methods, the NAS team compared their simulated sound pressure level ranges with extensive wind tunnel test data from Glenn Research Center in Cleveland and from GE. The LAVA results from two different computational grid models matched closely with the test results for individual tones produced when the rotor blades rotate up to 6,848 RPM — humans can hear frequencies up to 20,000 RPM.

Another concept being studied under the ERA project is analyzing aircraft slat noise. Again, LAVA was used for high-fidelity, time-accurate, near-field CFD analysis of the slat noise, which was then propagated to the far-field using the LAVA Ffowcs Williams-Hawkings (FWH) acoustic module. An experimental test was also performed in the Quiet Flow Facility (QFF) at NASA’s Langley Research Center to validate the computed results of the acoustic simulation. Time-averaged surface pressure coefficient (Cp) and both near- and far-field power spectral density (PSD) spectra were used for the validation.

Prior to the experimental test, LAVA CFD analysis was used exclusively to help design the experiment at the QFF. Both steady and time-accurate Reynolds-averaged Navier-Stokes (RANS) calculations were performed in both free-air and installed configurations for several angles of attack.

To simulate the slat noise, a higher-order, accurate, finite-difference scheme was developed for general non-orthogonal curvilinear coordinates within LAVA, along with advanced hybrid RANS/Large Eddy Simulation (LES) models. The increased accuracy in both the numerical discretization and the turbulence model allows fine-scale structures to be modeled on relatively coarser meshes, reducing the computation resource requirements.

The high-fidelity, time-accurate, near-field CFD analysis was performed on the Pleiades supercomputer at the NAS facility using 500 cores and 62,000 core-hours.




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