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At least 1,117 records · Page 62

An Aerodynamic Simulation Process for Iced Lifting Surfaces and Associated Issues

This paper discusses technologies and software tools that are being implemented in a software toolkit currently under development at NASA Glenn Research Center. Its purpose is to help study the effects of icing on airfoil performance and assist with the aerodynamic simulation process which consists of characterization and modeling of ice geometry, application of block topology and grid generation, and flow simulation. Tools and technologies for each task have been carefully chosen based on their contribution to the overall process. For the geometry characterization and modeling, we have chosen an interactive rather than automatic process in order to handle numerous ice shapes. An Appendix presents features of a software toolkit developed to support the interactive process. Approaches taken for the generation of block topology and grids, and flow simulation, though not yet implemented in the software, are discussed with reasons for why particular methods are chosen. Some of the issues that need to be addressed and discussed by the icing community are also included.

Choo, Yung K.↗

Strain System for the Motion Base Shuttle Mission Simulator

The Motion Base Shuttle Mission Simulator (MBSMS) Strain System is an innovative engineering tool used to monitor the stresses applied to the MBSMS motion platform tilt pivot frames during motion simulations in real time. The Strain System comprises hardware and software produced by several different companies. The system utilizes a series of strain gages, accelerometers, orientation sensor, rotational meter, scanners, computer, and software packages working in unison. By monitoring and recording the inputs applied to the simulator, data can be analyzed if weld cracks or other problems are found during routine simulator inspections. This will help engineers diagnose problems as well as aid in repair solutions for both current as well as potential problems.

Huber, David C.↗

Parachute Models Used in the Mars Science Laboratory Entry, Descent, and Landing Simulation

An end-to-end simulation of the Mars Science Laboratory (MSL) entry, descent, and landing (EDL) sequence was created at the NASA Langley Research Center using the Program to Optimize Simulated Trajectories II (POST2). This simulation is capable of providing numerous MSL system and flight software responses, including Monte Carlo-derived statistics of these responses. The MSL POST2 simulation includes models of EDL system elements, including those related to the parachute system. Among these there are models for the parachute geometry, mass properties, deployment, inflation, opening force, area oscillations, aerodynamic coefficients, apparent mass, interaction with the main landing engines, and off-loading. These models were kept as simple as possible, considering the overall objectives of the simulation. The main purpose of this paper is to describe these parachute system models to the extent necessary to understand how they work and some of their limitations. A list of lessons learned during the development of the models and simulation is provided. Future improvements to the parachute system models are proposed.

Cruz, Juan R.↗

Design and performance/measurement simulation studies for a ER-2 sunphotometer

Work and results, including developed software, obtained under this grant (NAG 2-620) have been reported in various progress reports, an M.S. Thesis, and software programs. The purpose of this final report is simply to provide a documented listing of what has already been reported. This includes the following: (1) Conceptual Design and Simulation of a Spectral Sunphotometer for the ER-2 Aircraft; (2) Continued Simulation and Design Studies for an ER-2 Sunphotometer; and (3) Simulation and Performance Studies of a Spectra Sunphotometer for the ER-2 Aircraft. Also, software and computational results for modeling airmass and diffuse light effects due to aerosols were provided in support of NASA ARC research on the effects of aerosols resulting from the Pinatubo volcanic eruptions. The references for these articles are as follows: (1) Post Pinatubo Optical Depth Spectra vs. Latitude and Vortex Structure; and (2) Pinatubo and Pre-Pinatubo Optical-Depth Spectra -- Mauna Loa Measurements, Comparisons, Inferred Particle Size Distributions, Radiative Effects, and Relationships to Lidar Data.

Reagan, J. A.↗

Integrated Bosch Process System Models for In-Situ Oxygen and Carbon Production

In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).

In situ Resource Utilization↗

Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations: Translational controller results

The reinforcement learning techniques developed at Ames Research Center are being applied to proximity and docking operations using the Shuttle and Solar Maximum Mission (SMM) satellite simulation. In utilizing these fuzzy learning techniques, we also use the Approximate Reasoning based Intelligent Control (ARIC) architecture, and so we use two terms interchangeable to imply the same. This activity is carried out in the Software Technology Laboratory utilizing the Orbital Operations Simulator (OOS). This report is the deliverable D3 in our project activity and provides the test results of the fuzzy learning translational controller. This report is organized in six sections. Based on our experience and analysis with the attitude controller, we have modified the basic configuration of the reinforcement learning algorithm in ARIC as described in section 2. The shuttle translational controller and its implementation in fuzzy learning architecture is described in section 3. Two test cases that we have performed are described in section 4. Our results and conclusions are discussed in section 5, and section 6 provides future plans and summary for the project.

Jani, Yashvant↗

Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations: Special approach/docking testcase results

As part of the RICIS project, the reinforcement learning techniques developed at Ames Research Center are being applied to proximity and docking operations using the Shuttle and Solar Maximum Mission (SMM) satellite simulation. In utilizing these fuzzy learning techniques, we use the Approximate Reasoning based Intelligent Control (ARIC) architecture, and so we use these two terms interchangeably to imply the same. This activity is carried out in the Software Technology Laboratory utilizing the Orbital Operations Simulator (OOS) and programming/testing support from other contractor personnel. This report is the final deliverable D4 in our milestones and project activity. It provides the test results for the special testcase of approach/docking scenario for the shuttle and SMM satellite. Based on our experience and analysis with the attitude and translational controllers, we have modified the basic configuration of the reinforcement learning algorithm in ARIC. The shuttle translational controller and its implementation in ARIC is described in our deliverable D3. In order to simulate the final approach and docking operations, we have set-up this special testcase as described in section 2. The ARIC performance results for these operations are discussed in section 3 and conclusions are provided in section 4 along with the summary for the project.

Jani, Yashvant↗

Mars Science Laboratory Entry Descent and Landing Simulation Using DSENDS

The most recent planetary science mission to Mars is Mars Science Laboratory (MSL) with the Curiosity rover, launched November 26, 2011 and landed at Gale Crater on August 6, 2012. This spacecraft was the first use at Mars of a complete closed-loop Guidance Navigation and Control (GN&C) system, including guided entry with a lifting body that greatly reduces dispersions during the Entry, Descent and Landing (EDL) phase to achieve a 25 km x 20 km landing error relative to the selected Gale Crater landing target. In order to confirm meeting the above landing criteria, high-fidelity simulation of the EDL phase is required. The tool used for 6DOF EDL trajectory verification analysis is Dynamics Simulator for Entry, Descent and Surface landing (DSENDS), which is a high-fidelity simulation tool from JPLs Dynamics and Real-Time Simulation Laboratory for the development, test and operations of aero-flight vehicles. DSENDS inherent capability is augmented for MSL with project-specific models of atmosphere, aerodynamics, sensors and thrusters along with GN&C flight software to enable high-fidelity trajectory simulation. This paper will present the model integration and independent verification experience of the JPL EDL trajectory analysis team.

Mars↗

Mars Science Laboratory Entry Descent and Landing Simulation Using DSENDS

The most recent planetary science mission to Mars was Mars Science Laboratory (MSL) with the Curiosity rover, launched November 26, 2011 and landed at Gale Crater on August 6, 2012. This spacecraft was the first use at Mars of a complete closed-loop Guidance Navigation and Control (GN&C) system, including guided entry with a lifting body that greatly reduces dispersions during the Entry, Descent and Landing (EDL) phase to achieve a 25 km X 20 km landing error relative to the selected Gale Crater landing target. In order to confirm meeting the above landing criteria, high-fidelity simulation of the EDL phase is required. The tool used for 6DOF EDL trajectory verification analysis is Dynamics Simulator for Entry, Descent and Surface landing (DSENDS), which is a high-fidelity simulation tool from JPLs Dynamics and Real-Time Simulation Laboratory for the development, test and operations of aero-flight vehicles. DSENDS inherent capability is augmented for MSL with project-specific models of atmosphere, aerodynamics, sensors and thrusters along with GN&C flight software to enable high-fidelity trajectory simulation. This paper will present the model integration and independent verification experience of the JPL EDL trajectory analysis team.

Burkhart, P. Daniel↗

ESSAA: Embedded system safety analysis assistant

The Embedded System Safety Analysis Assistant (ESSAA) is a knowledge-based tool that can assist in identifying disaster scenarios. Imbedded software issues hazardous control commands to the surrounding hardware. ESSAA is intended to work from outputs to inputs, as a complement to simulation and verification methods. Rather than treating the software in isolation, it examines the context in which the software is to be deployed. Given a specified disasterous outcome, ESSAA works from a qualitative, abstract model of the complete system to infer sets of environmental conditions and/or failures that could cause a disasterous outcome. The scenarios can then be examined in depth for plausibility using existing techniques.

Wallace, Peter↗

Fault Detection, Isolation and Recovery (FDIR) Portable Liquid Oxygen Hardware Demonstrator

The Fault Detection, Isolation and Recovery (FDIR) hardware demonstration will highlight the effort being conducted by Constellation's Ground Operations (GO) to provide the Launch Control System (LCS) with system-level health management during vehicle processing and countdown activities. A proof-of-concept demonstration of the FDIR prototype established the capability of the software to provide real-time fault detection and isolation using generated Liquid Hydrogen data. The FDIR portable testbed unit (presented here) aims to enhance FDIR by providing a dynamic simulation of Constellation subsystems that feed the FDIR software live data based on Liquid Oxygen system properties. The LO2 cryogenic ground system has key properties that are analogous to the properties of an electronic circuit. The LO2 system is modeled using electrical components and an equivalent circuit is designed on a printed circuit board to simulate the live data. The portable testbed is also be equipped with data acquisition and communication hardware to relay the measurements to the FDIR application running on a PC. This portable testbed is an ideal capability to perform FDIR software testing, troubleshooting, training among others.

Oostdyk, Rebecca L.↗

Flight Test of an Adaptive Controller and Simulated Failure/Damage on the NASA NF-15B

The method of flight-testing the Intelligent Flight Control System (IFCS) Second Generation (Gen-2) project on the NASA NF-15B is herein described. The Gen-2 project objective includes flight-testing a dynamic inversion controller augmented by a direct adaptive neural network to demonstrate performance improvements in the presence of simulated failure/damage. The Gen-2 objectives as implemented on the NASA NF-15B created challenges for software design, structural loading limitations, and flight test operations. Simulated failure/damage is introduced by modifying control surface commands, therefore requiring structural loads measurements. Flight-testing began with the validation of a structural loads model. Flight-testing of the Gen-2 controller continued, using test maneuvers designed in a sequenced approach. Success would clear the new controller with respect to dynamic response, simulated failure/damage, and with adaptation on and off. A handling qualities evaluation was conducted on the capability of the Gen-2 controller to restore aircraft response in the presence of a simulated failure/damage. Control room monitoring of loads sensors, flight dynamics, and controller adaptation, in addition to postflight data comparison to the simulation, ensured a safe methodology of buildup testing. Flight-testing continued without major incident to accomplish the project objectives, successfully uncovering strengths and weaknesses of the Gen-2 control approach in flight.

Buschbacher, Mark↗

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a streamlined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to pro-ceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule, development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor downselection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measurements for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jacob↗

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a stream-lined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to proceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule. Development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor down-selection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measure-ments for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jake↗

Structural mechanics simulations

Sandia National Laboratory has a very broad structural capability. Work has been performed in support of reentry vehicles, nuclear reactor safety, weapons systems and components, nuclear waste transport, strategic petroleum reserve, nuclear waste storage, wind and solar energy, drilling technology, and submarine programs. The analysis environment contains both commercial and internally developed software. Included are mesh generation capabilities, structural simulation codes, and visual codes for examining simulation results. To effectively simulate a wide variety of physical phenomena, a large number of constitutive models have been developed.

Biffle, Johnny H.↗

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.

Integrated Demand Management↗

LADEE Multi-Domain Simulation

The Lunar Atmosphere Dust Environment Explorer (LADEE) was a small explorer class spacecraft that was launched on Sept 7, 2013 and that was de-orbited and successfully impacted the Moons surface on April 17, 2014 after completing all of the mission objectives. The low-cost rapidly prototyped hardware design used for the spacecraft was extend to the development of the software base. To achieve this goal, a Model Based Design approach was utilized to develop the onboard flight software, and out of this development a model based multipurpose simulator was created of the LADEE spacecraft and its mission environment. This simulator extended the traditional function of propagating the vehicle's kinematic and rotational states and included the electrical and thermal states propagation. Traditionally, these domains are handled by domain specific high fidelity simulations that use the states histories from other domains as input. By reducing the fidelity and abstracting the relevant features being monitored and controlled by the flight software, it was possible to model the coupling across these domains resulting in more accurate overall system behavior. A faster than real-time workstation (WSIM) version of the LADEE simulator was used to develop and test the software control algorithms in the Simulink environment. To maximize the performance of the simulation, modeling knobs were introduced to reduce the resolution of the some of the domains models when the effects of that domain were not significant for the scope of that simulation. The automatic code generation feature in Simulink was used to port the simulation to several real-time environments to support Processor-in-the-Loop (PIL) and Hardware-in-the-Loop (HIL) testing, verification and validation. The real-time environment required that the design of each of the domain models be deterministic as possible in the time required to perform all of the calculations to update its states. The simulation interface was designed to be compatible with the command interface employed by the LADEE mission operation team. The WSIM, PIL, and HIL simulators thus used a common interface and thus were used for flight software testing, for mission operations personnel training (nominal and off-nominal operations) prior to the mission and to perform command sequence verification during the mission. This presentation will look at the modeling strategies used to create a common interface to the simulator and to model and couple multiple domains within the simulation, the results of those strategies, and the lessons learned.

Multi-Domain↗

Virtual Environment User Interfaces to Support RLV and Space Station Simulations in the ANVIL Virtual Reality Lab

Several virtual reality I/O peripherals were successfully configured and integrated as part of the author's 1997 Summer Faculty Fellowship work. These devices, which were not supported by the developers of VR software packages, use new software drivers and configuration files developed by the author to allow them to be used with simulations developed using those software packages. The successful integration of these devices has added significant capability to the ANVIL lab at MSFC. In addition, the author was able to complete the integration of a networked virtual reality simulation of the Space Shuttle Remote Manipulator System docking Space Station modules which was begun as part of his 1996 Fellowship. The successful integration of this simulation demonstrates the feasibility of using VR technology for ground-based training as well as on-orbit operations.

Dumas, Joseph D., II↗