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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2017

Implementation of (O-)CGR in The ONE

Routing in Delay-/Disruption-Tolerant Networking (DTN) requires specific solutions as link impairments prevent the use of ordinary Internet algorithms, based on a timely dissemination of network topology information. Among DTN routing algorithms there is a dichotomy between opportunistic and deterministic (scheduled) solutions. The former are numerous and apply to terrestrial environments; CGR is the most widely supported algorithm designed for scheduled connectivity, and it is usually applied to space networks. However, in an attempt to provide a unified approach, an opportunistic variant of CGR, Opportunistic CGR (OCGR) has been recently proposed by some of the authors. Performance evaluations are normally carried out for opportunistic solutions by means of simulators, such as The ONE considered in this paper. CGR by contrast is more often studied by means of small testbeds. As the simulation approach could be complementary for CGR, and essential for OCGR, the authors have recently ported both of them into The ONE, by developing and releasing as free software a specific additional package. The aim of this paper is to show the rationale of this choice and discuss the many challenges that needed to be tackled to achieve this primary goal.

Tempesta, G.↗

NASA NTRSDate not supplied

Propulsive trajectory optimization to minimize surface contamination

MOTIVATION: We present an optimization technique for propulsive vehicles that autonomously minimizes contamination during surface approach and landing. In addition to short-range hoppers, the optimization technique is also fully applicable to traditional orbit-to-surface landers. This study addresses scenarios where surface alterations from propulsion events are counterproductive or hazardous to the mission objectives. This is of immediate interest for landers (whether human or robotic), that may rely on pristine soils collected in the immediate vicinity of landing sites to accomplish science investigations, mining, or ISRU surface operations. Such missions are averse to various surface-plume interactions such as thermal scoring, physical agitation, and contamination. The capability can be applied with minimal impact to the baseline mission concept. METHODS: Optimization algorithms have been developed to calculate descent trajectories and maneuvers, thrust magnitude, and attitude for various mission cases. These parameters are determined as an optimal solution when minimizing either fuel consumption, contamination deposited at the landing site, or some weighted combination of both. Among constraints imposed on the solution, we examined pitch rate, vertical takeoff and vertical landing (VTVL) requirements, size of the contamination zone, and minimum ground clearance during flight. This tool provides unique, non-intuitive solutions and can be a valuable resource for mission planners. RESULTS: A variety of agile trajectory solutions were obtained, each yielding different reductions in landing site contamination and corresponding to only modest increases in fuel consumption. Several optimal trajectories were obtained by varying the contamination weight in the fitness function. As expected, when the contamination weight is zero, the trajectory appears close to parabolic since the optimization scheme only attempts to minimize for fuel utilization, yielding essentially, the expected ballistic trajectory. Notably for contamination weights greater than zero, trajectory inflections are observed in the descent phase, which manifests as hovering or additional, mini “pseudo hops” before the final touchdown. A trajectory inflection is characterized by arresting the majority of the spacecraft vertical velocity component at a coordinate outside of the landing target, and without violating ground clearance constraints. FUTURE WORK: Our optimization technique is ready for laboratory or field demonstrations to validate the sophisticated maneuvering solutions obtained for fuel optimization and surface preservation. An appropriate testbed would validate the optimal guidance algorithms, the navigation system, and sensor suite by emulating vehicle flight in closed loop robotic tests. Critically, these algorithms could then be ported to flight software for implementation.

surface contamination↗

NASA NTRS1996

Integrated Modeling Methodology Validation Using the Micro-Precision Interferometer Testbed

This paper validates the integrated modeling methodology used for design and performance evaluation of complex opto-mechanical systems, particularly spaceborne interferometers. The methodology integrates structural modeling, optical modeling, and control system design into a common environment, the Integrated Modeling of Optical Systems (IMOS) software package.

opto-mechanical↗

NASA NTRS2019

The NASA Urban Air Mobility Testbed Flight Research Aircraft

The National Aeronautics and Space Administration (NASA) is leading government, industry and academic research effort known as Urban Air Mobility (UAM). The UAM activity goal is to develop the technology needed to make possible an urban air transportation system that makes use of human-crewed and crewless vehicles using automation, artificial intelligence and other technologies to safely and efficiently air transport people and goods within an urban environment. The NASA Langley Research Center (LaRC) created a UAM Flight Research Testbed Aircraft from a Cessna LC40 general aviation aircraft. The testbed has updated digital avionics and research systems needed to conduct flight research. The aircraft has two separate autopilots; a standard Federal Aviation Ad-ministration (FAA) certified system, and a modified research autopilot. The research autopilot has modifications that allow increased authority and enhancements to allow more automation and artificial intelligence controls. A network of three research computers hosts software to research several activities including automated air traffic sense and avoid, ground collision avoidance and obstacle avoidance. These UAM research activities involve automation and artificial intelligence technologies developed at three NASA centers. The NASA Langley, NASA Armstrong, and NASA Ames Research Centers are working together to develop and test these UAM technologies. This paper provides details of the systems, capabilities and research projects of the UAM Testbed Research Aircraft.

Howell, Charles T.↗

NASA NTRS1994

Space Station Module Power Management and Distribution System (SSM/PMAD)

This report provides an overview of the Space Station Module Power Management and Distribution (SSM/PMAD) testbed system and describes recent enhancements to that system. Four tasks made up the original contract: (1) common module power management and distribution system automation plan definition; (2) definition of hardware and software elements of automation; (3) design, implementation and delivery of the hardware and software making up the SSM/PMAD system; and (4) definition and development of the host breadboard computer environment. Additions and/or enhancements to the SSM/PMAD test bed that have occurred since July 1990 are reported. These include: (1) rehosting the MAESTRO scheduler; (2) reorganization of the automation software internals; (3) a more robust communications package; (4) the activity editor to the MAESTRO scheduler; (5) rehosting the LPLMS to execute under KNOMAD; implementation of intermediate levels of autonomy; (6) completion of the KNOMAD knowledge management facility; (7) significant improvement of the user interface; (8) soft and incipient fault handling design; (9) intermediate levels of autonomy, and (10) switch maintenance.

Miller, William↗

NASA NTRS2009

Systematic Benchmarking of Diagnostic Technologies for an Electrical Power System

Automated health management is a critical functionality for complex aerospace systems. A wide variety of diagnostic algorithms have been developed to address this technical challenge. Unfortunately, the lack of support to perform large-scale V&V (verification and validation) of diagnostic technologies continues to create barriers to effective development and deployment of such algorithms for aerospace vehicles. In this paper, we describe a formal framework developed for benchmarking of diagnostic technologies. The diagnosed system is the Advanced Diagnostics and Prognostics Testbed (ADAPT), a real-world electrical power system (EPS), developed and maintained at the NASA Ames Research Center. The benchmarking approach provides a systematic, empirical basis to the testing of diagnostic software and is used to provide performance assessment for different diagnostic algorithms.

Kurtoglu, Tolga↗

NASA NTRS2003

Developments at the Advanced Design Technologies Testbed

A report presents background and historical information, as of August 1998, on the Advanced Design Technologies Testbed (ADTT) at Ames Research Center. The ADTT is characterized as an activity initiated to facilitate improvements in aerospace design processes; provide a proving ground for product-development methods and computational software and hardware; develop bridging methods, software, and hardware that can facilitate integrated solutions to design problems; and disseminate lessons learned to the aerospace and information technology communities.

VanDalsem, William R.↗

NASA NTRS1986

Data Management System (DMS) testbed user's manual development, volumes 1 and 2

A critical review of the network communication services contained in the Tinman User's Manual for Data Management System Test Bed (Tinman DMS User's Manual) is presented. The review is from the perspective of applying modern software engineering principles and using the Ada language effectively to ensure the test bed network communication services provide a robust capability. Overall the material on network communication services reflects a reasonably good grasp of the Ada language. Language features are appropriately used for most services. Design alternatives are offered to provide improved system performance and a basis for better application software development. Section two contains a review and suggests clarifications of the Statement of Policies and Services contained in Appendix B of the Tinman DMS User's Manual. Section three contains a review of the Network Communication Services and section four contains concluding comments.

Mcbride, John G.↗

NASA NTRS2021

Combined Cycle Engine Large-Scale Inlet for Mode Transition Studies: System Identification Rack Software Design

This report describes the development of the system identification (SysID) rack custom application code. This code is used to automate the system identification experimental processes for the National Aeronautics and Space Administration (NASA) Combined Cycle Engine Large-Scale Inlet for Mode Transition Experiments testbed. This series of experiments took place in the NASA Glenn Research Center (GRC) 10 foot by 10 foot (10x10) Supersonic Wind Tunnel (SWT) test facility. The SysID code was developed to apply command signals to testbed actuators, receive actuator feedback signals, and acquire sensor data which is used to identify the dynamics of the experimental processes. This code development and the process identification experiments were conducted during Phase-2 testing at various operating points. These points were predefined from data collected during the Phase-1 testbed characterization experiments. The developed SysID code was executed on a NASA designed and built real-time data acquisition (DAQ) and controls (SysID) rack. This report focuses on the development of the SysID rack real-time DAQ and control hardware and the custom application code used to automate the system identification process. The implementation of this reliable and efficient data acquisition and controls development tool is demonstrated by presenting an example of experimental data collected to be used for system identification.

R Thomas↗

NASA NTRS2021

Integration of an Arm Kinematics Hot Patch onboard the Curiosity Rover

NASA's Mars Science Laboratory (MSL) mission has updated the Curiosity rover's flight software multiple times since landing on Mars on August 6, 2012. The most common patching method has been a hot patch, in which running flight software is modified after being copied into RAM from its persistent storage. The latest hot patch to be installed on Curiosity fixed an issue in the robotic arm software that computes generalized inverse kinematics. Additional unit testing performed since the start of the surface mission revealed that this software can sometimes produce erroneous solutions.The cause was identified as numerical instability in a quartic root finder. When the inputs to that solver are not well conditioned, floating-point numerical issuescan cause erroneous roots to be reported. In theory, this could result in the robotic arm turret instruments being commanded to unintended positions, for example, below the terrain surface. Out of approximately 3.7 million unit test cases, 97.2\% of the position errors were below 5 mm. However, there were 16 test cases where theposition error was greater than 20 cm, and the maximum position error was 1.2 meters.The patch was uploaded to Curiosity on sol 2642 (January 11, 2020) after the solution was developed, re-implemented as a hot patch, and validated and verified using Earth-based Curiosity testbeds. A checkout test of the patch was performed on Curiosity on sol 2657, and nominal use of the patch began on sol 2658. In this paper, we describe the steps that led to integrating the arm kinematic hot patch into Curiosity's flight software, from the discovery of the bug to the nominal use of the patch in flight.

Maimone, Mark↗

NASA NTRS1991

ECLSS predictive monitoring

On Space Station Freedom (SSF), design iterations have made clear the need to keep the sensor complement small. Along with the unprecendented duration of the mission, it is imperative that decisions regarding placement of sensors be carefully examined and justified during the design phase. In the ECLSS Predictive Monitoring task, we are developing AI-based software to enable design engineers to evaluate alternate sensor configurations. Based on techniques from model-based reasoning and information theory, the software tool makes explicit the quantitative tradeoffs among competing sensor placements, and helps designers explore and justify placement decisions. This work is being applied to the Environmental Control and Life Support System (ECLSS) testbed at MSFC to assist design personnel in placing sensors for test purposes to evaluate baseline configurations and ultimately to select advanced life support system technologies for evolutionary SSF.

Doyle, Richard J.↗

NASA NTRS2016

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Trevino, Luis↗

NASA NTRS1996

Intercomparison, Visualization, and Analysis Testbed System for EOS Global Assimilated Datasets and Satellite Data

The Space Science and Engineering Center (SSEC) of the University of Wisconsin - Madison had two primary goals for NASA grant NAG5-2906. (1) Collaborate with scientists at NASA Goddard Space Flight Center (GSFC) to integrate SSEC's Vis5D software into NASA's Interactive Image Spread Sheet (IISS). Vis5D provides environmental modelers with interactive three-dimensional visualization of their model output. Integration of Vis5D with the IISS would give 3-D graphics capability to the iiss. (2) Make improvements in Vis5D as required by scientists at the NASA Data Assimilation Office (DAO). We were successful in both of these goals. Furthermore, the generic approach taken to achieving the first goal has enabled Vis5D to be integrated into many other software systems.

Source record↗

NASA NTRS2018

Fast Linearized Coronagraph Optimizer (FALCO) II: Optical Model Validation and Time Savings over Other Methods

We have developed the Fast Linearized Coronagraph Optimizer (FALCO), a new software toolbox for high-contrast, coronagraphic wavefront sensing and control. FALCO rapidly calculates the linearized deformable mirror (DM) response matrices, also called control Jacobians, and can be used for the design, simulation, or testbed operation of several types of coronagraphs. In this paper, we demonstrate that the optical propagation used in FALCO is accurate and matches PROPER. In addition, we demonstrate the drastic reduction in runtime when using FALCO for DM Jacobian calculations instead of the conventional method used, for example with a model of the Wide-Field Infrared Survey Telescope (WFIRST) Coronagraph Instrument (CGI). We then compare the relative accuracy between optical models in FALCO and PROPER.

Coker, Carl↗

NASA NTRS2021

Terminal Descent Radar System Testbed for Future Planetary Landers

Terminal Descent Radars (TDR), or landing radars, have been an integral element of Guidance, Navigation and Control (GN\&C) sensor suites of robotic exploration missions to the Moon and Mars. As plans for new, exciting exploration missions to the Moon, Mars and other planetary bodies are being developed, there is a need for a new generation of TDRs that are smaller, consume less power and are less expensive than previous sensors. The challenge of designing such a landing sensor is twofold: the first is to have well-vetted software tools that allow us to explore the design space for a particular mission scenario and analyze performance of relevant radar architectures. The second challenge is to reduce mass and power requirements of a landing radar without compromising reliability and performance. New design approaches that address these challenges need to be tested and demonstrated in realistic Entry-Descent-Landing (EDL)/Deorbit-Descent-Landing (DDL) scenarios. In this paper, we describe a TDR testbed developed at the Jet Propulsion Laboratory. The testbed is a closed-loop design, analysis and verification capability used to design and evaluate the next generation of landing radars for a variety of EDL/DDL scenarios.

Tope, Michael↗

NASA NTRS2021

Terminal Descent Radar System Testbed for Future Planetary Landers

Tope, Michael↗

NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes.

Trevino, Luis↗

NASA NTRS1992

Mini-mast CSI testbed user's guide

The Mini-Mast testbed is a 20 m generic truss highly representative of future deployable trusses for space applications. It is fully instrumented for system identification and active vibrations control experiments and is used as a ground testbed at NASA-Langley. The facility has actuators and feedback sensors linked via fiber optic cables to the Advanced Real Time Simulation (ARTS) system, where user defined control laws are incorporated into generic controls software. The object of the facility is to conduct comprehensive active vibration control experiments on a dynamically realistic large space structure. A primary goal is to understand the practical effects of simplifying theoretical assumptions. This User's Guide describes the hardware and its primary components, the dynamic characteristics of the test article, the control law implementation process, and the necessary safeguards employed to protect the test article. Suggestions for a strawman controls experiment are also included.

Tanner, Sharon E.↗