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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Advancing the practice of systems engineering at JPL

In FY 2004, JPL launched an initiative to improve the way it practices systems engineering. The Lab's senior management formed the Systems Engineering Advancement (SEA) Project in order to "significantly advance the practice and organizational capabilities of systems engineering at JPL on flight projects and ground support tasks." The scope of the SEA Project includes the systems engineering work performed in all three dimensions of a program, project, or task: 1. the full life-cycle, i.e., concept through end of operations 2. the full depth, i.e., Program, Project, System, Subsystem, Element (SE Levels 1 to 5) 3. the full technical scope, e.g., the flight, ground and launch systems, avionics, power, propulsion, telecommunications, thermal, etc. The initial focus of their efforts defined the following basic systems engineering functions at JPL: systems architecture, requirements management, interface definition, technical resource management, system design and analysis, system verification and validation, risk management, technical peer reviews, design process management and systems engineering task management, They also developed a list of highly valued personal behaviors of systems engineers, and are working to inculcate those behaviors into members of their systems engineering community. The SEA Project is developing products, services, and training to support managers and practitioners throughout the entire system lifecycle. As these are developed, each one needs to be systematically deployed. Hence, the SEA Project developed a deployment process that includes four aspects: infrastructure and operations, communication and outreach, education and training, and consulting support. In addition, the SEA Project has taken a proactive approach to organizational change management and customer relationship management - both concepts and approaches not usually invoked in an engineering environment. This paper'3 describes JPL's approach to advancing the practice of systems engineering at the Lab. It describes the general approach used and how they addressed the three key aspects of change: people, process and technology. It highlights a list of highly valued personal behaviors of systems engineers, discusses the various products, services and training that were developed, describes the deployment approach used, and concludes with several lessons learned.

process improvement↗
NASA NTRSDate not supplied

The Transition of Satellite Observations Assimilated in GEOS to JEDI

In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) in the Goddard Earth Observing System (GEOS), which is used for weather, climate, and air quality forecasts and producing reanalysis datasets, it is necessary to validate the observing system in JEDI. NASA’s Global Modeling and Assimilation Office (GMAO), with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) and adding all the necessary features to replicate existing capability. Various satellite and conventional observations are assimilated by the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures including the GEOS all-sky microwave radiance assimilation framework to assimilate those observation in UFO. Robust tests are conducted to ensure correct configurations of observational data bias correction (BC), quality control (QC), and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations is reported in this presentation.

Jianjun Jin↗
NASA NTRS2022

Reliability-Aware Requirements Development for Autonomy Software

Autonomy is the ability of a system to make decisions and take actions in the presence of uncertainty. Validating autonomy, therefore, is a matter of validating that the system makes intelligent decisions even when there might be discrepancies between the observed and the expected state of the world as well as when the possible outcome of each of the possible courses of action is uncertain. During the requirements engineering phase, the functions, including those that are required to be autonomous and their expected behavior are specified. However, in the case of autonomous software system, it is challenging to specify all possible scenarios that the software may encounter. Additionally, since autonomous behaviors cannot always be fully predetermined, it is difficult to reason about their completeness and correctness. While these challenges are also faced with non-autonomous system, they are more prevalent for autonomous system due to their complexity and emergent behavior. Our efforts have been three-fold. On one hand, we have developed a goal-based method for requirements decomposition. We have embedded this approach into a higher-level systems engineering framework and then developed methods for decision and reliability analysis within this framework. And finally, we use simulation analysis to validate the more theoretical methods and provide a feedback mechanism. The decision analysis approach (DA) helps in identifying and mitigating the run-time risks, by bringing to the forefront the uncertainties, decisions, interactions, and other factors that may cause autonomous software to make erroneous decisions. The DA framework is used to quantify, for each decision that the software can make, failure risk due to uncertainties. The information about the key decisions and circumstances that can cause autonomous system to make incorrect decisions are used to generate test scenarios to be run in a simulator to ensure that the system can handle error-prone circumstances. The results or outcomes from decisions, based on the simulated scenarios, can then be leveraged to further gain insight of the assured system. We combine a goal-based approach with simulation analysis to facilitate requirements development for autonomous systems and further provide a method for run-time systems level reliability considerations during the autonomous software development process. The DA and the reliability analysis methods provide a formalism for the consideration of uncertainty in the run time decision-making process for autonomous software. This formalism considers the uncertainty involved in the outcome of different courses of action, in terms of performance and cost, as well as a method to consider the system level reliability implications. System level reliability considerations for autonomous software decision making contribute to the satisfaction of the system level goals over the lifecycle of a given mission. We demonstrate our approach using a hypothetical rover path planning example. The requirements for our rover simulator are based on existing literature about Mars rovers and lessons learned from real world observations at JPL. The specifics of the autonomy design for the Mars rovers, that have not been previously cleared for external release, are not used for our demonstrations.

Lindvall, Mikael↗
NASA NTRS1992

Code inspection instructional validation

The Shuttle Data Systems Branch (SDSB) of the Flight Data Systems Division (FDSD) at Johnson Space Center contracted with Southwest Research Institute (SwRI) to validate the effectiveness of an interactive video course on the code inspection process. The purpose of this project was to determine if this course could be effective for teaching NASA analysts the process of code inspection. In addition, NASA was interested in the effectiveness of this unique type of instruction (Digital Video Interactive), for providing training on software processes. This study found the Carnegie Mellon course, 'A Cure for the Common Code', effective for teaching the process of code inspection. In addition, analysts prefer learning with this method of instruction, or this method in combination with other methods. As is, the course is definitely better than no course at all; however, findings indicate changes are needed. Following are conclusions of this study. (1) The course is instructionally effective. (2) The simulation has a positive effect on student's confidence in his ability to apply new knowledge. (3) Analysts like the course and prefer this method of training, or this method in combination with current methods of training in code inspection, over the way training is currently being conducted. (4) Analysts responded favorably to information presented through scenarios incorporating full motion video. (5) Some course content needs to be changed. (6) Some content needs to be added to the course. SwRI believes this study indicates interactive video instruction combined with simulation is effective for teaching software processes. Based on the conclusions of this study, SwRI has outlined seven options for NASA to consider. SwRI recommends the option which involves creation of new source code and data files, but uses much of the existing content and design from the current course. Although this option involves a significant software development effort, SwRI believes this option will produce the most effective results.

Orr, Kay↗
NASA NTRS2018

Electrically Heated Testing of the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Experiment Using a Depleted Uranium Core

The Kilopower project aims to develop and demonstrate scalable fission-based power technology for systems capable of delivering 1 to 10 kW of electric power with a specific power ranging from 2.5 to 6.5 W/kg. This technology could enable high-power science missions or could be used to provide surface power for manned missions to the Moon or Mars. NASA has partnered with the U.S. Department of Energy's National Nuclear Security Administration, Los Alamos National Laboratory, Nevada National Security Site (NNSS), and Y−12 National Security Complex to develop and test a prototypic reactor and power system using existing facilities and infrastructure. This technology demonstration, referred to as the "Kilowatt Reactor Using Stirling TechnologY (KRUSTY)," will undergo nuclear ground testing by the end of calendar year (CY) 2017 at the NNSS. The 1-kWe variation of the Kilopower system was chosen for the KRUSTY demonstration. The concept for the 1-kWe flight system consists of a 4 kWt highly enriched uranium-molybdenum reactor operating at 800 degC coupled to sodium heat pipes. The heat pipes deliver heat to the hot ends of eight 125-W Stirling convertors producing a net electrical output of 1 kW. Waste heat is rejected using titanium-water heat pipes coupled to carbon composite radiator panels. The KRUSTY test, based on this design, uses a prototypic highly enriched uranium-molybdenum core coupled to prototypic sodium heat pipes. The heat pipes transfer heat to two Advanced Stirling Convertors (ASC−E2s) and six thermal simulators, which simulate the thermal draw of full-scale power conversion units. Thermal simulators and Stirling engines are gas cooled. The most recent project milestone was the completion of nonnuclear system-level testing using an electrically heated depleted uranium (DU) (nonfissioning) reactor core simulator at the NASA Glenn Research Center. System-level testing has validated performance predictions and has demonstrated system-level operation and control in a test configuration that replicates the one to be used at the Device Assembly Facility (DAF) at the NNSS. Fabrication, assembly, and testing of the DU core has allowed for higher fidelity system-level testing at Glenn, and has validated the fabrication methods to be used on the highly enriched uranium core that will supply heat for the DAF KRUSTY demonstration.

Briggs, Maxwell H.↗
NASA NTRS1995

Flight test validation of a frequency-based system identification method on an F-15 aircraft

A frequency-based performance identification approach was evaluated using flight data from the NASA F-15 Highly Integrated Digital Electronic Control aircraft. The approach used frequency separation to identify the effectiveness of multiple controls simultaneously as an alternative to independent control identification methods. Fourier transformations converted measured control and response data into frequency domain representations. Performance gradients were formed using multiterm frequency matching of control and response frequency domain models. An objective function was generated using these performance gradients. This function was formally optimized to produce a coordinated control trim set. This algorithm was applied to longitudinal acceleration and evaluated using two control effectors: nozzle throat area and inlet first ramp. Three criteria were investigated to validate the approach: simultaneous gradient identification, gradient frequency dependency, and repeatability. This report describes the flight test results. These data demonstrate that the approach can accurately identify performance gradients during simultaneous control excitation independent of excitation frequency.

Schkolnik, Gerard S.↗
NASA NTRS2015

Methods for LEO Testing of CubeSat Propulsion Systems

Low Earth Orbit is becoming an inexpensive and readily available technology demonstration environment. Many new CubeSat technologies are taking advantage of this as an economical mechanism to advance beyond TRL 5. A wave of CubeSat propulsion systems favoring both reaction control and primary thrust will approach TRL 5 over the coming years, with some already there. These propulsion systems cover a wide range of capabilities including taking CubeSats to interplanetary destinations. In order to determine the feasibility of using LEO to validate the propulsion system performance and in doing so raising the TRL, a variety of factors need to be addressed. These factors include: method of measurement, environmental disturbances, spacecraft control states, and spacecraft mass properties. Propulsion Pathfinder is a NASA Ames Research Center lead project focused on raising the TRL of multiple propulsion systems over a series of flights in the coming years. This paper will highlight a few of the methods of measurement considered by this project to validate the performance of a propulsion system. The measurement methods range from tracking acceleration andor wheel spin-up to monitoring Two Line Elements between thrusting and non thrusting states. Focus will then be placed on the uncertainty of the measurement method and subsequently its feasibility through an analysis of LEO disturbance environment models and common CubeSat mass properties. In addition, the primary spacecraft control states and their imposition from the propulsion system are assessed.

Feasibility↗
NASA NTRS1993

CSI Flight Computer System and experimental test results

This paper describes the CSI Computer System (CCS) and the experimental tests performed to validate its functionality. This system is comprised of two major components: the space flight qualified Excitation and Damping Subsystem (EDS) which performs controls calculations; and the Remote Interface Unit (RIU) which is used for data acquisition, transmission, and filtering. The flight-like RIU is the interface between the EDS and the sensors and actuators positioned on the particular structure under control. The EDS and RIU communicate over the MIL-STD-1553B, a space flight qualified bus. To test the CCS under realistic conditions, it was connected to the Phase-0 CSI Evolutionary Model (CEM) at NASA Langley Research Center. The following schematic shows how the CCS is connected to the CEM. Various tests were performed which validated the ability of the system to perform control/structures experiments.

Sparks, Dean W., Jr.↗
NASA NTRS2000

Remote Diagnosis of the International Space Station Utilizing Telemetry Data

Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.

Deb, Somnath↗
NASA NTRSDate not supplied

Resilience Modeling in Complex Engineered Systems with Human-Machine Interactions

In recent times, there has been a growing interest in resilience-based design. Resilience-based design operates on the concept that failures and unexpected events will happen, and when they occur, complex engineered systems should be able to operate within acceptable bounds and recover reasonably. Humans can contribute to the resilience of a system by quickly detecting unforeseen events and taking corrective measures. To this effect, researchers have proposed guidelines and design approaches that can help promote human-system resilience. However, there is no early design stage tool to validate if a system is indeed resilient after applying these guidelines and design methods. In this research, we integrate the Human Error and Functional Failure Reasoning (HEFFR) framework into the fmdtools toolkit to enable designers to model the combined (machine, human, and joint) failures, including their propagation and dynamic effects, during early design stages. This integrated tool also allows designers to model the effects of performance shaping factors, team dynamics, and human-machine interactions in systems of systems. A demonstrative example of a remotely operated rover is explored to demonstrate how this approach can be applied to understand resilience in complex engineered systems with human interactions.

Lukman Irshad↗
NASA NTRS2023

Seasonal Forecasting Skill for the High Mountain Asia Region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorological relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks-to-months is an area of active research and development. NASA’s 15 Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1-3 month lead times in the HMA region, including a portion of the Indian Subcontinent, during the retrospective forecast period, 1981-2016. To assess forecast skill, we evaluate 2-m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and 20 Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are 25 evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system’s ability to forecast HMA hydrometeorology.

GEOS↗
NASA NTRS2018

Optical Measurement System for Strain Field Ahead of a Crack Tip for Lattice Structures

The aim of the ARAMADAS project is to automate the construction of cuboctahedral lattice structures. Lattice materials are appealing for aerospace applications due to their strength and stiffness at ultra-light densities. However, in order for any material to be realistically considered for such environments, it must also be damage tolerant. The ability of a material to absorb damage is characterized by its fracture toughness, which remains poorly characterized for lattice materials. Consequently, the objective of this research is to develop an optical measurement system to experimentally validate the strain field ahead of a crack tip in architecture lattice materials. Although the ability to predict the strain field ahead of a crack tip has been investigated for continuum materials, such behaviour of three-dimensional architectures is under-investigated. As such, we will use a custom optical measurement system to track deformation of the voxels in a side-cracked plate fracture specimen. The system shall use 3D pose estimation, stereo imaging, and possibly color tracking, in combination with optical flow algorithms, to compute information regarding the three-dimensional movement movement of the lattice nodes during mechanical testing. Bench top experiments will validate the optical measurement system and characterize precision. Additionally, the effect of multiple cameras on precision, as well as system scalability will be investigated. Final results will compare measured lattice deformation with finite element predictions.

Lennig, Miriam↗
NASA NTRS1997

Verifying Stability of Dynamic Soft-Computing Systems

Soft computing is a general term for algorithms that learn from human knowledge and mimic human skills. Example of such algorithms are fuzzy inference systems and neural networks. Many applications, especially in control engineering, have demonstrated their appropriateness in building intelligent systems that are flexible and robust. Although recent research have shown that certain class of neuro-fuzzy controllers can be proven bounded and stable, they are implementation dependent and difficult to apply to the design and validation process. Many practitioners adopt the trial and error approach for system validation or resort to exhaustive testing using prototypes. In this paper, we describe our on-going research towards establishing necessary theoretic foundation as well as building practical tools for the verification and validation of soft-computing systems. A unified model for general neuro-fuzzy system is adopted. Classic non-linear system control theory and recent results of its applications to neuro-fuzzy systems are incorporated and applied to the unified model. It is hoped that general tools can be developed to help the designer to visualize and manipulate the regions of stability and boundedness, much the same way Bode plots and Root locus plots have helped conventional control design and validation.

Wen, Wu↗
NASA NTRS1983

A large antenna system flight experiment

The design and development of large antenna systems are discussed. The validation objectives and techniques of the structural behavior of the system are outlined along with studies of the dynamics, deployment, and unpacking. The validation of flexible control and system performance are also considered.

Soosaar, K.↗
NASA NTRS1988

A rule-based systems approach to spacecraft communications configuration optimization

An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimization method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

Rash, James L.↗
NASA NTRS1988

A rule-based systems approach to spacecraft communications configuration optimization

An experimental rule-based system for optimizing user spacecraft communications configurations was developed at NASA to support mission planning for spacecraft that obtain telecommunications services through NASA's Tracking and Data Relay Satellite System. Designated Expert for Communications Configuration Optimization (ECCO), and implemented in the OPS5 production system language, the system has shown the validity of a rule-based systems approach to this optimization problem. The development of ECCO and the incremental optimizatin method on which it is based are discussed. A test case using hypothetical mission data is included to demonstrate the optimization concept.

Rash, James L.↗
NASA NTRS1990

Fault injection experiments using FIAT

The results of several experiments conducted using the fault-injection-based automated testing (FIAT) system are presented. FIAT is capable of emulating a variety of distributed system architectures, and it provides the capabilities to monitor system behavior and inject faults for the purpose of experimental characterization and validation of a system's dependability. The experiments consist of exhaustively injecting three separate fault types into various locations, encompassing both the code and data portions of memory images, of two distinct applications executed with several different data values and sizes. Fault types are variations of memory bit faults. The results show that there are a limited number of system-level fault manifestations. These manifestations follow a normal distribution for each fault type. Error detection latencies are found to be normally distributed. The methodology can be used to predict the system-level fault responses during the system design stage.

Barton, James H.↗
NASA NTRS2002

Verification and Validation of Neural Networks for Aerospace Systems

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: Overview of Adaptive Systems and V&V Processes/Methods.

Mackall, Dale↗