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At least 91 records · Page 5

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was designed for a cruise Mach of 1.7 and 40 passengers. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, was generated using computational fluid dynamics (CFD) based sonic boom analysis at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) and modeled as a flow-through nacelle for CFD analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned using an aeropropulsive CFD simulation. A process for approximation of the NPSS engine at SOC by a CFD engine is developed. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the configuration with the CFD engines is optimized to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept. Finally, the CFD simulation data for the optimized concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of low-boom supersonic transports.

Low-boom supersonic transport↗

Multiobjective Multidisciplinary Optimization of Low-Boom Supersonic Transports Using Multifidelity Models

A multidisciplinary optimization (MDO) method has been developed to design a computational fluid dynamics (CFD) based low-boom configuration that can be obtained from a Pareto solution of a low-fidelity multiobjective MDO problem with mission constraints. This paper refines the developed MDO method by using multifidelity models for CFD-based multiobjective MDO and a better method for the system-level trade between the target low boom ground noise level and the overland range. The refined MDO method can generate a low-boom configuration that satisfies the mission requirements, has the lowest takeoff gross weight and the longest range for the low-boom mission, trims the low-boom cruise flight with fuel redistributions, and has a reversed equivalent area distribution closely matching a low-boom target with ground noise level below 70 PLdB. The validity of the refined MDO method is demonstrated by a design study of a low-boom supersonic transport that carries 40 passengers, flies a low-boom mission with cruise Mach of 1.7 and range of 3500 nm, and cruises overwater at Mach 1.8 with range of 3882 nm. Moreover, the refined MDO method eliminates the difference between the assumed cruise weight for CFD-based low-boom inverse design optimization and the estimated cruise weight of the optimal inverse design solution with respect to the mission requirements.

MDO↗

Clustering Approach To Identifying Low Lunar Frozen Orbits In A High-Fidelity Model

Low lunar frozen orbits are of continued interest in the astrodynamics community for trajectory design and space domain awareness. This paper presents a data-driven approach to analyzing a wide variety of numerically-generated lunar trajectories in a 100 × 100 lunar gravity model with the point mass gravity of the Earth and Sun. First, clustering is used to extract a summary of these trajectories: within each cluster, trajectories possess a geometrically similar evolution of perilune but varying drift and lifetimes. Within some clusters, trajectories with a bounded perilune evolution are also identified to produce candidates for lunar frozen orbits of distinct geometries.

lunar frozen orbit gravity model data clustering↗

Perceptual Fidelity Versus Engineering Compromises in Virtual Acoustic Displays

Immersive, three-dimensional displays are increasingly becoming a goal of advanced human-machine interfaces. While the technology for achieving truly useful multisensory environments is still being developed, techniques for generating three-dimensional sound are now both sophisticated and practical enough to be applied to acoustic displays. The ultimate goal of virtual acoustics is to simulate the complex acoustic field experienced by a listener freely moving around within an environment. Of course, such complexity, freedom of movement and interactivity is not always possible in a 'true' virtual environment, much less in lower-fidelity multimedia systems. However, many of the perceptual and engineering constraints (and frustrations) that researchers, engineers and listeners have experienced in virtual audio are relevant to multimedia. In fact, some of the problems that have been studied will be even more of an issue for lower fidelity systems that are attempting to address the requirements of a huge, diverse and ultimately unknown audience. Examples include individual differences in head-related transfer functions, A lack of real interactively (head-tracking) in many multimedia displays, and perceptual degradation due to low sampling rates and/or low-bit compression. This paper discusses some of the engineering constraints faced during implementation of virtual acoustic environments and the perceptual consequences of these constraints. Specific examples are given for NASA applications such as telerobotic control, aeronautical displays, and shuttle launch communications. An attempt will also be made to relate these issues to low-fidelity implementations such as the internet.

Wenzel, Elizabeth M.↗

Perceptual Fidelity vs. Engineering Compromises In Virtual Acoustic Displays

Immersive, three-dimensional displays are increasingly becoming a goal of advanced human-machine interfaces. While the technology for achieving truly useful multisensory environments is still being developed, techniques for generating three-dimensional sound are now both sophisticated and practical enough to be applied to acoustic displays. The ultimate goal of virtual acoustics is to simulate the complex acoustic field experienced by a listener freely moving around within an environment. Of course, such complexity, freedom of movement and interactively is not always possible in a "true" virtual environment, much less in lower-fidelity multimedia systems. However, many of the perceptual and engineering constraints (and frustrations) that researchers, engineers and listeners have experienced in virtual audio are relevant to multimedia. In fact, some of the problems that have been studied will be even more of an issue for lower fidelity systems that are attempting to address the requirements of a huge, diverse and ultimately unknown audience. Examples include individual differences in head-related transfer functions, a lack of real interactively (head-tracking) in many multimedia displays, and perceptual degradation due to low sampling rates and/or low-bit compression. This paper discusses some of the engineering Constraints faced during implementation of virtual acoustic environments and the perceptual consequences of these constraints. Specific examples are given for NASA applications such as telerobotic control, aeronautical displays, and shuttle launch communications. An attempt will also be made to relate these issues to low-fidelity implementations such as the internet.

Wenzel, Elizabeth M.↗

Robust Design Under Uncertainty of Hypersonic Inlets

The objective of this work is to optimize scramjet inlet designs under uncertainty at multiple fidelity levels. Optimizations are performed for both deterministic and stochastic conditions. For stochastic conditions, robust design is used to minimize the variance in system performance in addition to optimizing mean system performance. Uncertainty quantification is performed using non-intrusive polynomial chaos. Comparisons are made between low-fidelity analysis and high-fidelity analysis, as well as deterministic optimization and robust optimization. Results indicate that the general design trend of previous inlet optimization techniques is recovered for the external compression portion of an inlet. For the internal compression portion of an inlet, when viscous effects become more significant and boundary layer separation becomes more likely, the optimal trend departs from previous results. Multifidelity uncertainty quantification methods are found to substantially reduce the computation time of robust design while obtaining results that nearly match those of high-fidelity analysis. Robust optimization is found to decrease the standard deviation of throat Mach number by up to 40% compared to deterministic optimization. Changes in the design variables and total turning that lead to robust scramjet inlets are identified and linked back to fundamental physical principles through the theta-beta-Mach function.

Hypersonic↗

Advancing the State-of-the-Practice for Liquid Rocket Engine Injector Design

Current shortcomings in both the overall injector design process and its underlying combustion stability assessment methodology are rooted in the use of empirically based or low fidelity representations of complex physical phenomena and geometry details that have first order effects on performance, thermal environments and combustion stability. The result is a design and analysis capability that is often inadequate to reliably arrive at a suitable injector design in an efficient manner. Specifically, combustion instability has been particularly difficult to predict and mitigate. Large hydrocarbon-fueled booster engines have been especially problematic in this regard. Where combustion instability has been a problem, costly and time-consuming redesign efforts have often been an unfortunate consequence. This paper presents an overview of a recently completed effort at NASA Marshall Space Flight Center to advance the state-of-the-practice for liquid rocket engine injector design. Multiple perturbations of a gas-centered swirl coaxial (GCSC) element that burned gaseous oxygen and RP-1 were designed, assessed for combustion stability, and tested. Three designs, one stable, one marginally unstable and one unstable, were used to demonstrate both an enhanced overall injector design process and an improved combustion stability assessment process. High-fidelity results from state-of-the-art computational fluid dynamics CFD simulations were used to substantially augment and improve the injector design methodology. The CFD results were used to inform and guide the overall injector design process. They were also used to upgrade selected empirical or low-dimensional quantities in the ROCket Combustor Interactive Design (ROCCID) stability assessment tool. Hot fire single element injector testing was used to verify both the overall injector designs and the stability assessments. Testing was conducted at the Air Force Research Laboratory and at Purdue University. Companion papers provide details of the overall injector design process, full- and sub-scale testing, ROCCID-based stability assessments and the CFD simulations.

Tucker, P. K.↗

The Effect of Boundary Layer Character on Stochastic Rotor Blade Vortex Shedding Noise

This work illustrates the effect of a rotor blade’s boundary layer on the broadband LBL-VS self-noise emitted from an optimum hovering rotor through experimental and multi-fidelity computational studies. Blade surface roughness effects associated with different manufacturing techniques and the effect of adding a boundary layer trip were shown to decrease LBL-VS noise by upwards of 30 dB at the frequency of maximum emission with a slight penalty in aerodynamic performance when compared with smooth rotor blades. Low-fidelity 2-D viscous flow analysis verified the presence of laminar separation bubbles on the rotor blades which are responsible for LBL-VS noise. Three high-fidelity lattice-Boltzmann simulations were conducted with different wall-functions to predict the boundary layer character correspondent to their experimental counterpart and the resultant presence or absence of LBL-VS noise. Excellent aerodynamic and aeroacoustic agreement was seen between the lattice-Boltzmann simulations and the experimental data for the cases with surface roughness and the boundary layer trip, with the broadband noise results from the simulation with fully turbulent wall-functions diverging from the experimental results above 5 kHz. The transitional wall-function simulation which emulated the smooth experimental blades underpredicted thrust by 14% and broadband noise by a minimum of 10 dB with an accurately predicted broadband noise trend.

Christopher S Thurman↗

Immersive Simulations and Engineering Environment (iSEE): Improving Fidelity of Virtual Reality Simulations

The Immersive Simulation and Engineering Environment (iSEE) provides Kennedy Space Center (KSC) with accurate Human Systems Integration (HSI) analysis of the stresses on a human body incurred from physical work, along with accessibility and reach factors. Human Factors engineers can observe the simulations conducted by iSEE and work with the gathered data to help make the working environment at KSC safer. The software that runs the HSI analysis, however, provides users with a low fidelity virtual environment. Previously, this led to the addition and implementation of other iSEE programs that were capable of higher-fidelity simulations. The difficulties of streamlining the workflow in the lab with these new programs is currently being addressed.

Sein, Alexandr↗

Holographic Weapons Sight as Crew Optical Alignment Sight

Crew Optical Alignment Sights (COAS) are used by spacecraft pilots to provide a visual reference to a target spacecraft for lateral relative position during rendezvous and docking operations. NASA s Orion vehicle, which is currently under development, has not included a COAS in favor of automated sensors, but the crew office has requested such a device be added for situational awareness and contingency support. The current Space Shuttle COAS was adopted from Apollo heritage, weighs several pounds, and is no longer available for procurement which would make re-use difficult. In response, a study was conducted to examine the possibility of converting a commercially available weapons sight to a COAS for the Orion spacecraft. The device used in this study was the XPS series Holographic Weapon Sight (HWS) procured from L-3 EOTech. This device was selected because the targeting reticule can subtend several degrees, and display a graphic pattern tailored to rendezvous and docking operations. Evaluations of the COAS were performed in both the Orion low-fidelity mockup and rendezvous simulations in the Reconfigurable Operational Cockpit (ROC) by crewmembers, rendezvous engineering experts, and flight controllers at Johnson Space Center. These evaluations determined that this unit s size and mounting options can support proper operation and that the reticule visual qualities are as good as or better than the current Space Shuttle COAS. The results positively indicate that the device could be used as a functional COAS and supports a low-cost technology conversion solution.

Merancy, Nujoud↗

Pseudo Linear Gyro Calibration

Previous high fidelity onboard attitude algorithms estimated only the spacecraft attitude and gyro bias. The desire to promote spacecraft and ground autonomy and improvements in onboard computing power has spurred development of more sophisticated calibration algorithms. Namely, there is a desire to provide for sensor calibration through calibration parameter estimation onboard the spacecraft as well as autonomous estimation on the ground. Gyro calibration is a particularly challenging area of research. There are a variety of gyro devices available for any prospective mission ranging from inexpensive low fidelity gyros with potentially unstable scale factors to much more expensive extremely stable high fidelity units. Much research has been devoted to designing dedicated estimators such as particular Extended Kalman Filter (EKF) algorithms or Square Root Information Filters. This paper builds upon previous attitude, rate, and specialized gyro parameter estimation work performed with Pseudo Linear Kalman Filter (PSELIKA). The PSELIKA advantage is the use of the standard linear Kalman Filter algorithm. A PSELIKA algorithm for an orthogonal gyro set which includes estimates of attitude, rate, gyro misalignments, gyro scale factors, and gyro bias is developed and tested using simulated and flight data. The measurements PSELIKA uses include gyro and quaternion tracker data.

Harman, Richard↗

An Overview of the Proprotor Performance Test in the 14-­ by 22­-Foot Subsonic Tunnel

This work experimentally investigates the aerodynamic behavior of proprotors across a wide range of angles of attack. These flight conditions are intended to be representative of Urban Air Mobility (UAM) vehicle platforms that utilize articulating propulsors to transition from a vertical takeoff and landing (VTOL) phase typical of a conventional rotor­craft, to an axial mode of forward flight typical of a fixed-­wing aircraft. These data are used to identify the potential limits of lower­ fidelity aerodynamic modeling tools, as well as to inform future acoustic phases of testing. Tests were conducted on two proprotor designs in the NASA Langley 14­- by 22­-Foot Subsonic Tunnel using an articulating propeller test stand. Hover results identified unique flow physics on one of the proprotors, including severe outboard flow separation and perpendicular blade vortex interactions on the outboard portions of the blades. Transition and forward flight conditions yielded very informative trends in terms of both on-­ and off­-axis forces and moments against which low-­fidelity prediction models were compared.

aerodynamics↗

An Overview of the Proprotor Performance Test in the 14- by 22-Foot Subsonic Tunnel

This work experimentally investigates the aerodynamic behavior of proprotors across a wide range of angles of attack. These flight conditions are intended to be representative of Urban Air Mobility (UAM) vehicle platforms that utilize articulating propulsors to transition from a vertical takeoff and landing (VTOL) phase typical of a conventional rotor­craft, to an axial mode of forward flight typical of a fixed-­wing aircraft. These data are used to identify the potential limits of lower­ fidelity aerodynamic modeling tools, as well as to inform future acoustic phases of testing. Tests were conducted on two proprotor designs in the NASA Langley 14­- by 22­-Foot Subsonic Tunnel using an articulating propeller test stand. Hover results identified unique flow physics on one of the proprotors, including severe outboard flow separation and perpendicular blade vortex interactions on the outboard portions of the blades. Transition and forward flight conditions yielded very informative trends in terms of both on-­ and off­-axis forces and moments against which low-­fidelity prediction models were compared.

Nikolas Zawodny↗

High-Fidelity Simulations of a Quadrotor Vehicle for Urban Air Mobility

High-fidelity computational fluid dynamics simulations have been carried out to analyze NASA’s quadrotor air taxi concept for urban air mobility. High-order accurate schemes, dual-time stepping, and the delayed detached-eddy simulation model have been employed. The flow solver has been loosely coupled with the rotorcraft comprehensive analysis code. The vehicle simulated is a six-passenger quadrotor for air taxi operations. The quadrotor has been simulated in hover and cruise, with flight conditions representative of an air taxi mission. Initially, the quadcopter vehicle is analyzed using low-fidelity tools. Then, a complete analysis using high-fidelity simulations of the quadcopter is performed in conjunction with collective pitch control. Airloads, wake geometry, and performance are studied and compared. A comparison between isolated rotors and complete vehicle simulations is presented. NASA’s quadrotor is one of NASA’s concept vehicles designed in support of aircraft development for vertical take-off and landing air taxi operations.

ARMD↗

Additive Construction using Basalt Regolith Fines

Planetary surfaces are often covered in regolith (crushed rock), whose geologic origin is largely basalt. The lunar surface is made of small-particulate regolith and areas of boulders located in the vicinity of craters. Regolith composition also varies with location, reflecting the local bedrock geology and the nature and efficiency of the micrometeorite-impact processes. In the lowland mare areas (suitable for habitation), the regolith is composed of small granules (20 - 100 microns average size) of mare basalt and volcanic glass. Impacting micrometeorites may cause local melting, and the formation of larger glassy particles, and this regolith may contain 10-80% glass. Studies of lunar regolith are traditionally conducted with lunar regolith simulant (reconstructed soil with compositions patterned after the lunar samples returned by Apollo). The NASA Kennedy Space Center (KSC) Granular Mechanics & Regolith Operations (GMRO) lab has identified a low fidelity but economical geo-technical simulant designated as Black Point-1 (BP-1). It was found at the site of the Arizona Desert Research and Technology Studies (RATS) analog field test site at the Black Point lava flow in adjacent basalt quarry spoil mounds. This paper summarizes activities at KSC regarding the utilization of BP-1 basalt regolith and comparative work with lunar basalt simulant JSC-1A as a building material for robotic additive construction of large structures. In an effort to reduce the import or in-situ fabrication of binder additives, we focused this work on in-situ processing of regolith for construction in a single-step process after its excavation. High-temperature melting of regolith involves techniques used in glassmaking and casting (with melts of lower density and higher viscosity than those of metals), producing basaltic glass with high durability and low abrasive wear. Most Lunar simulants melt at temperatures above 1100 C, although melt processing of terrestrial regolith at 1500 C is not uncommon. These temperatures are achievable by laser heating or by using solar concentrators. Similar to volcanic magma, the cooling rate determines the crystallite size - slower cooling develops larger crystals, and rapid quenching can result in fully amorphous glass.

Additive↗

Aerodynamic Simulation of Runback Ice Accretion

This report presents the results of recent investigations into the aerodynamics of simulated runback ice accretion on airfoils. Aerodynamic tests were performed on a full-scale model using a high-fidelity, ice-casting simulation at near-flight Reynolds (Re) number. The ice-casting simulation was attached to the leading edge of a 72-in. (1828.8-mm ) chord NACA 23012 airfoil model. Aerodynamic performance tests were conducted at the ONERA F1 pressurized wind tunnel over a Reynolds number range of 4.7?10(exp 6) to 16.0?10(exp 6) and a Mach (M) number ran ge of 0.10 to 0.28. For Re = 16.0?10(exp 6) and M = 0.20, the simulated runback ice accretion on the airfoil decreased the maximum lift coe fficient from 1.82 to 1.51 and decreased the stalling angle of attack from 18.1deg to 15.0deg. The pitching-moment slope was also increased and the drag coefficient was increased by more than a factor of two. In general, the performance effects were insensitive to Reynolds numb er and Mach number changes over the range tested. Follow-on, subscale aerodynamic tests were conducted on a quarter-scale NACA 23012 model (18-in. (457.2-mm) chord) at Re = 1.8?10(exp 6) and M = 0.18, using low-fidelity, geometrically scaled simulations of the full-scale castin g. It was found that simple, two-dimensional simulations of the upper- and lower-surface runback ridges provided the best representation of the full-scale, high Reynolds number iced-airfoil aerodynamics, whereas higher-fidelity simulations resulted in larger performance degrada tions. The experimental results were used to define a new subclassification of spanwise ridge ice that distinguishes between short and tall ridges. This subclassification is based upon the flow field and resulting aerodynamic characteristics, regardless of the physical size of the ridge and the ice-accretion mechanism.

Broeren, Andy P.↗

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗