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NASA NTRS2018

Examination of Wave Speed in Rotating Detonation Engines Using Simplified Computational Fluid Dynamics

A simplified, two-dimensional, computational fluid dynamic (CFD) simulation, with a reactive Euler solver is used to examine possible causes for the low detonation wave propagation speeds that are consistently observed in air breathing rotating detonation engine (RDE) experiments. Intense, small-scale turbulence is proposed as the primary mechanism. While the solver cannot model this turbulence, it can be used to examine the most likely, and profound effect of turbulence. That is a substantial enlargement of the reaction zone, or equivalently, an effective reduction in the chemical reaction rate. It is demonstrated that in the unique flowfield of the RDE, a reduction in reaction rate leads to a reduction in the detonation speed. A subsequent test of reduced reaction rate in a purely one-dimensional pulsed detonation engine (PDE) flowfield yields no reduction in wave speed. The reasons for this are explained. The impact of reduced wave speed on RDE performance is then examined, and found to be minimal. Two other potential mechanisms are briefly examined. These are heat transfer, and reactive mixture non-uniformity. In the context of the simulation used for this study, both mechanisms are shown to have negligible effect on either wave speed or performance.

combustion↗

NASA NTRS2018

Convergence Analysis of Turbulent Flow Solutions

Data from the "Turbulence Modeling Resource" website for turbulent flow over an NACA-0012 airfoil is analyzed to determine the convergence behavior of three second-order CFD (Computational Fluid Dynamics) codes: CFL3D (Computational Fluids Lab 3 Dimensional flow solver), FUN3D (Fully Unstructured Navier-stokes flow solver), and TAU (German Aerospace Center (DLR) 2 dimensional code for unstructured hybrid grids solving the Reynolds-Averaged Navier-Stokes equations or the Euler equations). The convergence of both integrated properties and pointwise data are examined. Several different methods for estimating errors and computing convergence rates are compared. A high-order extension to the Richardson extrapolation is developed that improves the accuracy of the mesh limit values and provides a quantitative estimate of the threshold of the asymptotic regime. The coefficient of total drag exhibits second-order convergence for all three codes, and convergence is monotone over a sequence of 7 grids. Other force coefficients are not so well behaved. The convergence rates of the viscous component of drag on the three nest grids ranges from 3:0 for CFL3D to 1:0 for FUN3D. The three codes are converging to similar but not identical solutions. The largest differences between the codes are in the coefficient of lift for which the difference between CFL3D and FUN3D is greater than 10 (sup minus 4). The best agreement occurs in the viscous component of drag, which is the only force component for which all three codes are converging towards each other at a rate of second-order. The agreement between the two unstructured grid codes is good with all properties except lift converging towards common values at a rate of second-order. No one code was universally better than the other. The TAU code has the lowest error in total drag, FUN3D has the lowest error in lift, and CFL3D has the lowest error in the viscous component of drag.

Atkins, Harold L.↗

NASA NTRS2019

Free-Flight CFD Simulations of Ballistic Range and Flight Tests

Free-Flight CFD capability has been implemented into the finite-volume solver US3D under the Entry Systems Modeling project. Several simulations of ballistic range experiments have been performed in order to validate the simulation software and methodology. Extension of the software to flight scale trajectories with varying freestream conditions has been carried out. Results show promising ability to predict vehicle behavior as compared to flight. Finally, a multi-body free-flight capability has been developed to generalize the single-body free-flight solver to study multiple bodies in proximal flight.

Brock, Joseph M.↗

NASA NTRS2019

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

NASA NTRS2019

Fully-Coupled Fluid-Structure Interaction Simulations of a Supersonic Parachute

A validated computational fluid-structure interaction method for simulating the complex interaction between the large deformation of very thin, highly deformable structures and compressible flows is extended to consider large-scale problems in supersonic flows using parallel computing. The coupled fluid-structure interaction system is solved in a partitioned, or weakly-coupled, manner. The foundations of the applied fluid-structure interaction method are a higher-order, block-structured Cartesian, sharp immersed boundary method for the compressible Navier-Stokes equations and a computational structural dynamics solver employing a geometrically nonlinear 3-node shell element based on the mixed interpolation of tensorial components formulation. The method is applied to large deformation fluid-structure interaction validation cases before being applied to the inflation of a supersonic parachute in the upper Martian atmosphere where the goal is to demonstrate the capabilities of the solver when considering large-scale problems in supersonic flows.

Boustani, Jonathan↗

NASA NTRS2019

Aeroelastic Indicial Response Reduced-Order Modeling for Flexible Flight Vehicles

A reduced-order modeling method capable of providing computationally efficient predictions of the nonlinear, unsteady aerodynamics encountered by flexible flight vehicles under- going forced oscillations is presented. Models are developed using indicial response theory, which characterizes a vehicle’s dynamics through identification of time-accurate aerodynamic responses due to step changes in the vehicle-state parameters, e.g., angle-of-attack, pitch rate. A coupled computational fluid dynamics aeroelastic analysis is proposed for identifying step (indicial) responses of flexible vehicles. In this approach, aeroelastic indicial responses are simulated via prescribed rigid body motions, while fluid-structure interactions are captured at the subiterative level through coupling to a linear modal structural solver. A nonlinear extension of indicial response theory is applied through time-dependent linear interpolation of a database of locally linear aeroelastic step responses. Reduced-order models are then created using the mathematical principle of convolution applied to the interpolated aeroelastic indicial responses to predict the time-dependent aerodynamic response of a flexible vehicle to any arbitrary prescribed flight maneuver. The NASA FUN3D computational fluid dynamics solver is utilized for simulating full-order trajectories and indicial response functions. Aerodynamic predictions were generated for the X-56A aircraft undergoing a series of harmonic forced oscillations. The s are shown to provide a practical option for evaluating the unsteady aerodynamics of flexible vehicles using high-fidelity simulations.

Hiller, Brett↗

NASA NTRS2020

Face- and Cell-Averaged Nodal-Gradient Approach to Cell-Centered Finite-Volume Method on Mixed Grids

In this paper, the averaged nodal-gradient approach previously developed for triangular grids is extended to mixed triangular-quadrilateral grids. It is shown that the face- averaged approach leads to deteriorated iterative convergence on quadrilateral grids. To develop a convergent solver, we consider cell-averaging instead of face-averaging for quadri- lateral cells. We show that the cell-averaged approach leads to a convergent solver and can be efficiently combined with the face-averaged approach on mixed grids. The method is demonstrated for various inviscid and viscous problems from low to high Mach numbers on two-dimensional mixed grids.

Nishikawa, Hiroaki↗

NASA NTRS2020

Unstructured Grid Development for the Space Launch System Liftoff and Transition Lineloads Computational Analysis

Production of aerodynamic lineloads databases for the Space Launch System (SLS) vehicle at Liftoff and Transition (LOT) conditions has required the development of a Computational Fluid Dynamics (CFD) workflow capable of producing high-quality solutions for this unique phase of flight. Aerodynamic considerations included a wide range of flow angles (from 0°up to 90°total angle of attack), resulting leeside separation, and interaction effects between the three bodies of the integrated SLS vehicle, as well as the nearby launch tower. Computational mesh development for similar problems at the NASA Langley Research Center (such as for the Constellation/Ares launch vehicles) has primarily relied on in-house tools such as VGRID/POSTGRID, with grids designed for NASA-developed and maintained flow solvers such as USM3D and FUN3D. The workflow for such problems has evolved over the development of the various SLS configurations to incorporate new tools such as the Heldenpatch/Heldenmesh grid generator (Helden Aerospace) and CREATE-AV Kestrel (US Department of Defense) flow solver. This paper describes efforts to benchmark a grid generation approach for LOT problems using Heldenpatch/Heldenmesh and Kestrel, verified against prior best practices from VGRID/POSTGRID. Parameters studied include surface grid density, first-layer viscous cell height, and volume grid growth rate parameters. Resulting solutions are compared based on total force and moment values, sectional line loads, and surface pressures, all validated against existing wind tunnel aerodynamic databases where available for the SLS Block 1B Cargo configuration.

Space launch systems↗

NASA NTRSDate not supplied

TPSAS-NF1676L-18428-DND

The Challenges of Unsteady Adjoint-Based Design: - The adjoint approach still provides all of the sensitivities at the same cost as analysis, and the 20x estimate still applies for the expense of an optimization - But every simulation is now an unsteady problem - Where the steady adjoint solver linearized about a single solution (the steady-state), the unsteady adjoint solver must essentially do this at every physical time step

Eric Nielsen↗

NASA NTRSDate not supplied

Simulations of a Turbulent Flow Subjected to Favorable and Adverse Pressure Gradients

This paper reports the results from a direct numerical simulation of an initially turbulent boundary layer passing over a wall-mounted “speed bump” geometry. The speed bump, represented in the form of a Gaussian distribution profile, generates a favorable pressure gradient region over the upstream half of the geometry, followed by an adverse pressure gradient over the downstream half. The boundary layer approaching the bump undergoes strong acceleration in the favorable pressure gradient region before experiencing incipient or very weak separation within the adverse pressure gradient region. These types of flows have proven to be particularly challenging to predict using lower-fidelity simulation tools based on various turbulence modeling approaches and warrant the use of the highest-fidelity simulation techniques. Simulation results are utilized to examine the key phenomena present in the flowfield, such as relaminarization/stabilization in the strong acceleration region succeeded by retransition to turbulence near the onset of adverse pressure gradient, incipient/weak separation, and development of internal layers where the sense of streamwise pressure gradient changes at the foot, apex and tail of the bump. The present direct numerical simulation is performed using a flow solver developed exclusively for graphics processing units, which is found to provide a significant speedup compared to an earlier solver optimized for central processing unit architectures.

Ali Uzun↗

NASA NTRSDate not supplied

Comparing Unstructured Adaptive Mesh Solutions for the High Lift Common Research Model Airfoil

Discretization error is a common source of uncertainty in Computational Fluid Dynamics (CFD) analyses. Traditional means of controlling discretization error through fixed-mesh refinement studies has proven to be difficult particularly when modeling complex geometries and flow fields. One reason for this is that mesh generation in today’s production CFD workflow is often a labor intensive process that is heavily dependent on user judgment. Unstructured mesh adaptation is known to be an efficient way to control discretization errors in CFD. Adaptive methods replace user based decision making with automated processes that optimize a mesh to reduce discretization error. This paper compares the application of multiple solution adaptive techniques in combination with multiple flow solvers to solve for the flow field about a 2D airfoil section of the NASA High-Lift Common Research Model (HL-CRM). By driving the adaptive mesh processes to a similar level of mesh convergence, the ability to achieve consistent results between multiple adaptive techniques and flow solvers is demonstrated. Mesh convergence for the various adaptive mesh approaches is compared identifying potential areas for improvement and providing mesh generation guidance for future workshops.

mesh adaptation high-lift 2D airfoil↗

NASA NTRSDate not supplied

Comparing Unstructured Adaptive Mesh Solutions for the High Lift Common Research Model Airfoil

mesh adaptation↗

NASA NTRSDate not supplied

Improvements in Iterative Convergence of FUN3D Solutions

This paper presents a hierarchical adaptive nonlinear iteration method (HANIM) implemented in NASA computational fluid dynamics code, FUN3D, to improve robustness and computational efficiency of FUN3Dsolutions. In contrast to the baseline iterative solver that relies on an approximate Jacobian, a simple multicolor Gauss-Seidel point-implicit iteration scheme, and linear CFL ramping, HANIM is based upon a hierarchy of modules including pre conditioner, generalized conjugate residual, realizability check, nonlinear control,and CFL adaption modules. HANIM performance is systematically compared with the performance of the baseline solver. The iterative solutions are compared for three aerodynamic benchmark cases: a subsonic separated flow around a hemisphere cylinder, a supersonic flow through a long duct, and a subsonic flow over the NASA wing-body juncture model. Two Reynolds-averaged Navier-Stokes turbulence models are used in these computations, namely, the negative variant of the linear one-equation Spalart-Allmar as model and its nonlinear extension based on quadratic constitutive relations.

Li Wang↗

NASA NTRSDate not supplied

CFD 2030 Grand Challenge: CFD-in-the-Loop Monte Carlo Flight Simulation for Space Vehicle Design

Flight qualification of space vehicles is markedly different from those typically employed for aircraft. The concept of an extensive flight test campaign for a space vehicle does not exist, and vehicle designers must look to alternative techniques for demonstrating robust and reliable performance of their vehicles prior to operational flight. A space vehicle may undergo only a handful of flight tests in its development cycle, with each flight representing a drastically different flight phase or flight configuration. For instance, NASA’s Space Launch System (SLS) launch vehicle and Orion spacecraft will only see a total of four flight demonstrations before flying a crew on its first operational mission, and each flight demonstrates a unique vehicle configuration and/or set of flight conditions. The SLS will be flown only one time before it becomes operational (Artemis 1). The Orion spacecraft Crew Module (CM) will have been tested twice, once on a Delta IV launch vehicle (Exploration Flight Test 1) and once as a fully integrated system with the SLS launch vehicle (Artemis 1). The Orion Launch abort system will have been tested twice, once in a pad abort scenario (Pad Abort 1) and once in an inflight abort scenario (Ascent Abort 2) on a modified Peacekeeper booster. Both of these latter tests involve only a boiler plate CM, not a functional Orion spacecraft. Thus, unlike aircraft, there is very little opportunity for engineers to assess and evaluate their preflight predictions. Instead, space vehicle designers rely on Monte Carlo flight simulations with detailed dispersions of predicted nominal flight behavior to determine how robust their design is to errors and uncertainties in the flight conditions their vehicle may encounter. These Monte Carlo analyses entail thousands of trajectory simulations to demonstrate that the vehicle can meet design requirements at a specified level of reliability. From an aerodynamics and aerothermodynamics perspective, these trajectory simulations are fueled by an extensive aerodynamic database that covers the complete range of expected flight conditions, vehicle configurations, and flight attitudes expected in a given mission. Today, these databases amount to a table of engineering parameters that can be quickly interrogated by the trajectory simulator. The aerodynamic and aerothermodynamic databases are assembled via a series of ground tests, empirical and analytical analysis, physics-based computational analysis, applicable past flight performance data, and in some cases, engineering judgment. These databases generally take years to assemble for a new space vehicle system and in the case of SLS/Orion, over a decade of test and analysis have been expended to develop the extensive databases required to cover the myriad of configurations and potential flight conditions required for the system. Recently, it has been proposed that Computational Fluid Dynamic (CFD) and computing capability may be reaching a point where it is foreseeable that CFD could be integrated directly into the production trajectory simulation tools used to design NASA’s space vehicles. To demonstrate this, NASA has embarked on two demonstrations of this type of capability, one where six degree of freedom flight trajectory simulation equations are embedded in an existing CFD solver and another where a production CFD solver is loosely coupled with a production trajectory simulation tool. These efforts represent an initial demonstration of a future approach to flight trajectory simulation, but they are a far cry from the capability required to perform a full-up CFD-in-the-loop Monte Carlo trajectory simulation. Therefore, this represents a viable grand challenge for computational methods addressing space vehicle design and development. The final paper/presentation will discuss the many hurdles, beyond simply raw computational power, to realizing this grand challenge and how they map directly to the CFD Vision 2030 ojectives. Among these are the wide range of flight conditions, including accelerating/decelerating flight, encountered by a space vehicle during launch and/or entry. The vehicle can also encounter numerous configuration changes, some of which can be quite drastic, during the course of its flight, so robust, automated geometry modeling, grid generation, and adaptation will play a huge role in reaching this goal. Multiply this by 1000’s of trajectory simulations occurring simultaneously in a given Monte Carlo analysis, and the problem readily scales to absorb virtually any size of supercomputer envisioned today. The concept of CFD-in-the-loop Monte Carlo trajectory simulation poses a formidable challenge for emerging and future computing systems, and it has the potential to shave years off the development cycle for aerodynamic and aerothermodynamic performance predictions as compared to today’s space vehicle design approach.

CFD 2030↗

NASA NTRSDate not supplied

CFD Modeling of Cryogenic Chilldown in a Complex Channel under Normal and Low Gravity Conditions

Future NASA architectures have baselined cryogenic propulsion systems as well as cryogenic fluid management to support lunar missions and ultimately to support future missions to Mars. These missions will require chilling hardware down prior to engine restart as well as chilling lines and tanks prior to transferring and refueling these propulsion elements in orbit. In lieu of expensive tests conducted on-orbit, accurate predictive computational models of these chilldown processes can be used to reduce system and propellant mass as well as mission risk. To gain confidence in these computational models, appropriate anchoring and validation to experimental data in a relevant environment needs to be performed. Recent ground and sub-orbital flight experiments conducted by the Japan Aerospace Exploration Agency (JAXA) investigated chilldown of a complex channel resembling a turbopump bearing cavity at low flow rates. This work presents Computational Fluid Dynamics (CFD) model development of the chilldown experiment employing two-phase flow boiling models available in commercial CFD software STAR-CCM+ using Volume of Fluid (VOF) and the traditional Euler-Euler multiphase flow solvers. Comparisons of the numerical and experimental results under normal and low-gravity conditions are presented. An assessment of solid wall temperatures and phase distribution yielded important insights into multiphase solver choice, dependence on gravity environment, and challenges associated with cryogenic flow boiling prediction and validation.

CFD↗

NASA NTRSDate not supplied

Enhancing Scalability for FUN3D Rotorcraft Simulations with Yoga: an Overset Grid Assembler

FUN3D, an unstructured grid Navier-Stokes CFD code is capable of overset grid simu- lations, but does not have an internal method for assembling an overset grid system from a group of component grids. FUN3D currently relies on the third party codes Suggar++ and DiRTlib to perform domain assembly and provide intergrid connectivity for overset simulations. Rotorcraft simulations with moving, deforming blades require domain assembly and mesh deformation at each time step. For these simulations, the three primary drivers of computational cost for each time step are: deforming the mesh, performing domain assembly, and performing subiterations of the flow solver. FUN3D exhibits strong and weak scalability for the flow solver subiterations and the mesh deformation. However, FUN3D is currently hardwired directly to the serial version of Suggar++, which has a fixed cost for a given mesh system. Therefore, domain assembly begins to dominate the total cost of each time step as grid systems become larger. An integrated method for parallel domain assembly is presented that addresses scalability for large grid systems. Restructuring within FUN3D to accommodate integrated domain assembly is also discussed, which could enable use of the parallel Suggar++ library.

Cameron T Druyor↗

NASA NTRSDate not supplied

A Framework for Mesh-Geometry Associativity during Mesh Adaptation

A framework has been developed for describing how a computational mesh is associated to the geometry model it discretizes. The target application of this framework is surface mesh adaptation in a CFD flow solver. The framework, called MeshLink, consists of two components. First, a schema has been defined for describing the one-to-many associativity of a surface mesh to the geometry model entities to which it is attached. Second, a high-level library provides a kernel-agnostic wrapper for providing the necessary geometry queries to an application (e.g., mesher, flow solver). Both the schema and library are provided freely and openly. MeshLink’s ability to support solution mesh adaptation on linear and curved meshes for a high-order flow solution is demonstrated on several test cases relevant to the aerospace and automotive industries.

mesh adaptation↗

NASA NTRSDate not supplied

Structured Overset and Unstructured Grid Simulations for the Third AIAA Sonic Boom Prediction Workshop

Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Description of the mesh generation techniques and numerical methods are provided along with a comparison of nearfield and far-field predictions with available experimental data as well as other workshop sub-missions. Strong consistency was observed between the Biconvex and C608 nearfield predictions across the two solvers used for this study, as well as validation and verification data. Additionally, near-field and farfield ground signature results using a combination of a truncated computational fluid dynamics (CFD) domain coupled to a mid-field space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM, but at less computational cost.

CST↗