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At least 199 records · Page 11

Using full-mission simulation for human factors research in air transport operations

This study examined state-of-the-art mission oriented simulation and its use in human factors research. Guidelines were developed for doing full-mission human factors research on crew member behavior during simulated air transport operations. The existing literature was reviewed. However, interviews with experienced investigators provided the most useful information. The fundamental scientific and practical issues of behavioral research in a simulation environment are discussed. Guidelines are presented for planning, scenario development, and the execution of behavioral research using full-mission simulation in the context of air transport flight operations . Research is recommended to enhance the validity and productivity of full-mission research by: (1) validating the need for high-fidelity simulation of all major elements in the operational environment, (2) improving methods for conducting full-mission research, and (3) examining part-task research on specific problems through the use of vehicles which contain higher levels of abstraction (and lower fidelity) of the operational environment.

Orlady, Harry W.↗

A Conservative, Scalable, Space-Time Blade Element Rotor Model for Multi-Rotor Vehicles

The development of a parallel blade-element rotor model and its implementation into an adaptive Cartesian method is described. The unsteady version of the rotor model applies a body force to all cells contained in the swept space-time volume at each timestep and special care is taken to maintain axisymmetry on the Cartesian grid. Mesh convergence of rotor thrust and torque is obtained with around 10000 cells in the disk for the steady model. Parallelization is accomplished using OpenMP and the rotor force computation is distributed across all available nodes. Simulations of an isolated XV-15 rotor in hover show good correlation with experimental data and predictions of multi-rotor thrust variation closely match previous high fidelity simulations. The final paper will also include results from the unsteady rotor model and parallel scaling tests.

Conservative↗

Aeroacoustic Study of a Subscale Large Civil Transport (STAR) Model – Part 2: Validation of Simulated Results

Aeroacoustic measurements of the 26%-scale, semispan Boeing 777-200 Subsonic Transport Aeroacoustic Research (STAR) model tested in the NASA Ames Research Center 40- by 80-foot wind tunnel were used to ascertain the efficacy of high-fidelity simulations to accurately predict noise from the landing gear of large commercial transports. The simulations, conducted with the lattice Boltzmann solver PowerFLOW®, used a digital replica of the STAR model with or without main landing gear deployed and slats and flaps set to their highest deflection angles to represent aircraft during landing. The computations were performed at a Mach number of 0.21, Reynolds number of 8.2 million based on the model mean aerodynamic chord, and other conditions prevalent during the STAR model test. Measured and computed surface pressures were in very good agreement at most port locations on the model, as were global force coefficients, indicating that the simulations captured the impact of main gear deployment on inboard flap loading. Noise sources produced by the main landing gear and high-lift devices were determined via source localization maps generated with CLEAN from synthetic and experimental data. In general, very good agreement between predicted and measured acoustic source location and relative strength was observed in the maps. Comparisons of far-field noise spectra obtained from the CLEAN deconvolution maps showed remarkable agreement between synthetic and experimental broadband noise at low and medium frequencies. Main landing gear sources for model-scale frequencies above 7,000 Hz could not be resolved with the spatial resolution used during the simulations.

airframe noise↗

Numerical Propulsion System Simulation for Space Transportation

Current system simulations are mature, difficult to modify, and poorly documented. Probabilistic life prediction techniques for space applications are in their early application stage. Many parts of the full system, variable fidelity simulation, have been demonstrated individually or technology is available from aeronautical applications. A 20% reduction in time to design with improvements in performance and risk reduction is anticipated. GRC software development will proceed with similar development efforts in aeronautical simulations. Where appropriate, parallel efforts will be encouraged/tracked in high risk areas until success is assured.

Owen, Karl↗

Pre-Test CFD for the Design and Execution of the Enhanced Injection and Mixing Project at NASA Langley Research Center

With the increasing costs of physics experiments and simultaneous increase in availability and maturity of computational tools it is not surprising that computational fluid dynamics (CFD) is playing an increasingly important role, not only in post-test investigations, but also in the early stages of experimental planning. This paper describes a CFD-based effort executed in close collaboration between computational fluid dynamicists and experimentalists to develop a virtual experiment during the early planning stages of the Enhanced Injection and Mixing project at NASA Langley Research Center. This projects aims to investigate supersonic combustion ramjet (scramjet) fuel injection and mixing physics, improve the understanding of underlying physical processes, and develop enhancement strategies and functional relationships relevant to flight Mach numbers greater than 8. The purpose of the virtual experiment was to provide flow field data to aid in the design of the experimental apparatus and the in-stream rake probes, to verify the nonintrusive measurements based on NO-PLIF, and to perform pre-test analysis of quantities obtainable from the experiment and CFD. The approach also allowed for the joint team to develop common data processing and analysis tools, and to test research ideas. The virtual experiment consisted of a series of Reynolds-averaged simulations (RAS). These simulations included the facility nozzle, the experimental apparatus with a baseline strut injector, and the test cabin. Pure helium and helium-air mixtures were used to determine the efficacy of different inert gases to model hydrogen injection. The results of the simulations were analyzed by computing mixing efficiency, total pressure recovery, and stream thrust potential. As the experimental effort progresses, the simulation results will be compared with the experimental data to calibrate the modeling constants present in the CFD and validate simulation fidelity. CFD will also be used to investigate different injector concepts, improve understanding of the flow structure and flow physics, and develop functional relationships. Both RAS and large eddy simulations (LES) are planned for post-test analysis of the experimental data.

Drozda, Tomasz G.↗

Aerodynamic Optimization of Rocket Control Surface Geometry Using Cartesian Methods and CAD Geometry

Aerodynamic design is an iterative process involving geometry manipulation and complex computational analysis subject to physical constraints and aerodynamic objectives. A design cycle consists of first establishing the performance of a baseline design, which is usually created with low-fidelity engineering tools, and then progressively optimizing the design to maximize its performance. Optimization techniques have evolved from relying exclusively on designer intuition and insight in traditional trial and error methods, to sophisticated local and global search methods. Recent attempts at automating the search through a large design space with formal optimization methods include both database driven and direct evaluation schemes. Databases are being used in conjunction with surrogate and neural network models as a basis on which to run optimization algorithms. Optimization algorithms are also being driven by the direct evaluation of objectives and constraints using high-fidelity simulations. Surrogate methods use data points obtained from simulations, and possibly gradients evaluated at the data points, to create mathematical approximations of a database. Neural network models work in a similar fashion, using a number of high-fidelity database calculations as training iterations to create a database model. Optimal designs are obtained by coupling an optimization algorithm to the database model. Evaluation of the current best design then gives either a new local optima and/or increases the fidelity of the approximation model for the next iteration. Surrogate methods have also been developed that iterate on the selection of data points to decrease the uncertainty of the approximation model prior to searching for an optimal design. The database approximation models for each of these cases, however, become computationally expensive with increase in dimensionality. Thus the method of using optimization algorithms to search a database model becomes problematic as the number of design variables is increased.

Nelson, Andrea↗

Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft

This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.

Nguyen, Nhan↗

A Component-Level Model of Automatic Dependent Surveillance - Broadcast (ADS-B)

Automatic Dependent Surveillance – Broadcast (ADS-B) is being employed in numerous peer-to-peer initiatives attempting to expand the capacity of the National Airspace System (NAS) or enable mixed operations of manned and unmanned vehicles. Safety assessments of these initiatives rely, in part, on modeling the accuracy of ADS-B in reporting the position and direction of an ownship and surrounding traffic. Frequently, these initiatives utilize a position uncertainty model that applies a reported ADS-B estimation position uncertainty (EPU) value to a Rayleigh distribution and uses a Gauss-Markov random walk to add error to the ADS-B output of a vehicle. This model of ADS-B state error is easy to implement and apply to numerous problems. However, it has a couple of draw-backs. First, the ADS-B state errors are equally probable in all directions. This is a good assumption in situations where aircraft maneuvering is not constrained. However, in situations where the aircraft maneuvering is constrained such as landing, the error distribution is likely to exhibit directionality and the non-directional model may skew results especially when assessing very low probabilities (e.g., 10(exp -9)) of catastrophic encounters. Second, the model does not account for processing latency in the receiving aircraft. NASA Langley Research Center (LaRC) recently examined the feasibility of decreasing the spacing of aircraft on parallel approaches to runways separated by as little as 700 feet. For Monte-Carlo analysis using a high-fidelity simulation of a large transport, LaRC started with a Gauss-Markov model of ADS-B error but then developed a component level model of ADS-B error to increase the fidelity of results.

Madden, Michael M.↗

From Simulation to Reality With Random Noise

The challenging environment of autonomous vehicle (AV) navigation necessitates certain functions be performed by deep neural networks. Optimizing these models involves collecting vast quantities of domain-specific training data and ensuring that the dataset is representative of expected conditions. High-fidelity simulation plays a vital role in making this process feasible, allowing a wide range of scenarios to be explored at low cost. However, learning from simulation introduces subtle biases into models, which can degrade real-world performance in unpredictable ways. This effect can be mitigated with learning schemes specialized to bridge distributional shifts (transfer learning). Given the complex nature of these methods, the underlying models, and their environments, meaningfully evaluating performance is notstraight forward. Many unrelated factors can effect an improvement in generalization accuracy, but a full ablation analysis is often difficult. To tease out signal from noise, it is necessary to understand how transfer learning performance is affected by noise itself. The goals of this paper are (i) to establish a domain randomization baseline for a simple classification transfer learning task and (ii) to validate the RRAV testbed as a platform for further research in sim-to-real learning. We generate imagery from a simulation of NASA Ames Research Center and train a small convolutional neural network (ConvNet) to classify position relative to a centerline. Further models are trained with different types of noise progressively added to the data. The models are deployed aboard the on-site test vehicle to test real-world performance. In our experiments, we find that such naive domain randomization raises sim-to-real accuracy from 64% to 79%, while training directly on real data yields an 89% accuracy ceiling. These results suggest that the isolated mechanism of domain randomization can significantly improve generalization.

simulation↗

Quiet mode for nonlinear rotor models

High frequency harmonics are generated by helicopter rotor systems, and nonlinear blade-element models of these systems create the same harmonics. In discrete real-time rotorcraft simulation, however, especially for handling qualities research, they are more of a nuisance than a benefit. The cycle times required to adequately represent them are rarely obtainable. The result is that distinct frequencies alias into the pilot and simulator bandwidths, thereby decreasing simulation fidelity. However, use of an interpolation procedure permits the observation of harmonics at their proper frequency locations, and an accompanying notch filter may then be used to attenuate the harmonics prior to decimation. Rotorcraft simulations using these techniques are not contaminated with the spurious frequencies that create variable trim points, produce erroneous stability and control derivative data, and obscure time histories.

Mcfarland, R. E.↗

An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer

The Terrestrial Planet Finder formation flying Interferometer (TPF-I) will be a five-spacecraft, precision formation operating near the second Sun-Earth Lagrange point. As part of technology development for TPF-I, a formation and attitude control system (FACS) is being developed that achieves the precision and functionality needed for the TPF-I formation and that will be demonstrated in a distributed, real-time simulation environment. In this paper we present an overview of FACS and discuss in detail its formation estimation, guidance and control architectures and algorithms. Since FACS is currently being integrated into a high-fidelity simulation environment, component simulations demonstrating algorithm performance are presented.

Scharf, Daniel P.↗

An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer

The Terrestrial Planet Finder formation flying Interferometer (TPF-I) will be a five-spacecraft, precision formation operating near a Sun-Earth Lagrange point. As part of technology development for TPF-I, a formation and attitude control system (FACS) is being developed that achieves the precision and functionality associated with the TPF-I formation. This FACS will be demonstrated in a distributed, real-time simulation environment. In this paper we present an overview of the FACS and discuss in detail its constituent formation estimation, guidance and control architectures and algorithms. Since the FACS is currently being integrated into a high-fidelity simulation environment, component simulations demonstrating algorithm performance are presented.

Terrestrial Planet Finder (TPF)↗

Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test

The spacecraft system that plays the greatest role throughout the program lifecycle is the Command and Data Handling System (C&DH), along with the associated algorithms and software. The C&DH takes on this role as cost driver because it is the brains of the spacecraft and is the element of the system that is primarily responsible for the integration and interoperability of all spacecraft subsystems. During design and development, many activities associated with mission design, system engineering, and subsystem development result in products that are directly supported by the C&DH, such as interfaces, algorithms, flight software (FSW), and parameter sets. A modular system architecture has been developed that provides a means for rapid spacecraft assembly, test, and integration. This modular C&DH software architecture, which can be targeted and adapted to a wide variety of spacecraft architectures, payloads, and mission requirements, eliminates the current practice of rewriting the spacecraft software and test environment for every mission. This software allows missionspecific software and algorithms to be rapidly integrated and tested, significantly decreasing time involved in the software development cycle. Additionally, the FSW includes an Onboard Dynamic Simulation System (ODySSy) that allows the C&DH software to support rapid integration and test. With this solution, the C&DH software capabilities will encompass all phases of the spacecraft lifecycle. ODySSy is an on-board simulation capability built directly into the FSW that provides dynamic built-in test capabilities as soon as the FSW image is loaded onto the processor. It includes a six-degrees- of-freedom, high-fidelity simulation that allows complete closed-loop and hardware-in-the-loop testing of a spacecraft in a ground processing environment without any additional external stimuli. ODySSy can intercept and modify sensor inputs using mathematical sensor models, and can intercept and respond to actuator commands. ODySSy integration is unique in that it allows testing of actual mission sequences on the flight vehicle while the spacecraft is in various stages of assembly, test, and launch operations all without any external support equipment or simulators. The ODySSy component of the FSW significantly decreases the time required for integration and test by providing an automated, standardized, and modular approach to integrated avionics and component interface and functional verification. ODySSy further provides the capability for on-orbit support in the form of autonomous mission planning and fault protection.

Cuseo, John↗

Optimal generalized multistep integration formulae for real-time digital simulation

The problem of discretizing a dynamical system for real-time digital simulation is considered. Treating the system and its simulation as stochastic processes leads to a statistical characterization of simulator fidelity. A plant discretization procedure based on an efficient matrix generalization of explicit linear multistep discrete integration formulae is introduced, which minimizes a weighted sum of the mean squared steady-state and transient error between the system and simulator outputs.

Moerder, D. D.↗

Simulation Modeling Requirements for Loss-of-Control Accident Prevention of Turboprop Transport Aircraft

In-flight loss of control remains the leading contributor to aviation accident fatalities, with stall upsets being the leading causal factor. The February 12, 2009. Colgan Air, Inc., Continental Express flight 3407 accident outside Buffalo, New York, brought this issue to the forefront of public consciousness and resulted in recommendations from the National Transportation Safety Board to conduct training that incorporates stalls that are fully developed and develop simulator standards to support such training. In 2010, Congress responded to this accident with Public Law 11-216 (Section 208), which mandates full stall training for Part 121 flight operations. Efforts are currently in progress to develop recommendations on implementation of stall training for airline pilots. The International Committee on Aviation Training in Extended Envelopes (ICATEE) is currently defining simulator fidelity standards that will be necessary for effective stall training. These recommendations will apply to all civil transport aircraft including straight-wing turboprop aircraft. Government-funded research over the previous decade provides a strong foundation for stall/post-stall simulation for swept-wing, conventional tail jets to respond to this mandate, but turboprops present additional and unique modeling challenges. First among these challenges is the effect of power, which can provide enhanced flow attachment behind the propellers. Furthermore, turboprops tend to operate for longer periods in an environment more susceptible to ice. As a result, there have been a significant number of turboprop accidents as a result of the early (lower angle of attack) stalls in icing. The vulnerability of turboprop configurations to icing has led to studies on ice accumulation and the resulting effects on flight behavior. Piloted simulations of these effects have highlighted the important training needs for recognition and mitigation of icing effects, including the reduction of stall margins. This paper addresses simulation modeling requirements that are unique to turboprop transport aircraft and highlights the growing need for aerodynamic models suitable for stall training for these configurations. A review of prominent accidents that involved aerodynamic stall is used to illustrate various modeling features unique to turboprop configurations and the impact of stall behavior on susceptibility to loss of control that has led to new training requirements. This is followed by an overview of stability and control behavior of straight-wing turboprops, the related aerodynamic characteristics, and a summary of recent experimental studies on icing effects. In addition, differences in flight dynamics behavior between swept-wing jets and straight-wing turboprop configurations are discussed to compare and contrast modeling requirements. Specific recommendations for aerodynamic models along with further research needs and data measurements are also provided. 1

Crider, Dennis↗

On-orbit/On-surface Servicing, Assembly, and Manufacturing (OSAM) Architecture Simulation System (OASiS)

On-orbit/on-surface servicing, assembly, and manufacturing (OSAM) –recently renamed“in-space servicing, assembly, and manufacturing”(ISAM) –will aid in the development of vital research-enabling structuresin space, such as the In-space Assembled Telescope, the Lunar Gateway, and the Lunar Safe Haven. As these structures become larger and more complex, developers will need new methods for verifying and validating their OSAM mission architectures at full-scale prior to launch, without paying for extensive facility upgrades or additional hardware prototypes. Under the OSAM Architecture Simulation System (OASiS) project, modular OSAM modeling and simulation capabilities were developed to help rapidly prototype and evaluate OSAM technologies and operational concepts.Theywerethenusedto demonstrate and evaluate data from the simulation of a simpleOSAM operation against ananaloghardware setup. Using collected test data, the teamevaluatedthe accuracy of the simulation environment against the behavior of real hardwareandgainedinsight on how to further improve OSAM modeling and simulation. With thesenewcapabilities and many more to come, developers will be able to test complex OSAM operations on multiple scales, iterate on technology designs faster, achieve higher operational accuracy, and ultimately reduce mission development costs. A comprehensive, high-fidelity simulation environment will ensure the successful servicing, assembly, and manufacturing of structures that help us study and explore our universe.

isam↗

Multi-Platform Avionics Simulator

Multi-Platform Avionics Simulator (MPAvSim) is a software library for development of simulations of avionic hardware. MPAvSim facilitates simulation of interactions between flight software and such avionic peripheral equipment as telecommunication devices, thrusters, pyrotechnic devices, motor controllers, and scientific instruments. MPAvSim focuses on the behavior of avionics as seen by flight software, rather than on performing high-fidelity simulations of dynamics. However, MPAvSim is easily integrable with other programs that do perform such simulations. MPAvSim makes it possible to do real-time partial hardware- in-the-loop simulations. An MPAvSim simulation consists of execution chains (see figure) represented by flow graphs of models, defined here as stateless procedures that do some work. During a simulation, MPAvSim walks the execution chain, running each model in turn. Using MPAvSim, flight software can be run against a spacecraft that is all simulation, all hardware, or part hardware and part simulation. With respect to a specific piece of hardware, either the hardware itself or its simulation can be plugged in without affecting the rest of the system. Thus, flight software can be tested before hardware is available, and as items of hardware become available, they can be substituted for their simulations, with minimal disruption.

Clark, Micah↗

Fast Simulation of the NICER Instrument

The NICER mission uses a complicated physical system to collect information from objects that are, by x-ray timing science standards, rather faint. To get the most out of the data we will need a rigorous understanding of all instrumental effects. We are in the process of constructing a very fast, high fidelity simulator that will help us to assess instrument performance, support simulation-based data reduction, and improve our estimates of measurement error. We will combine and extend existing optics, detector, and electronics simulations. We will employ the Compute Unied Device Architecture (CUDA2) to parallelize these calculations. The price of suitable CUDA-compatible multi-gigaflop cores is about $0.20/core, so this approach will be very cost-effective.

gEDA↗