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NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗

NASA NTRS2013

Formal Validation of Fault Management Design Solutions

The work presented in this paper describes an approach used to develop SysML modeling patterns to express the behavior of fault protection, test the model's logic by performing fault injection simulations, and verify the fault protection system's logical design via model checking. A representative example, using a subset of the fault protection design for the Soil Moisture Active-Passive (SMAP) system, was modeled with SysML State Machines and JavaScript as Action Language. The SysML model captures interactions between relevant system components and system behavior abstractions (mode managers, error monitors, fault protection engine, and devices/switches). Development of a method to implement verifiable and lightweight executable fault protection models enables future missions to have access to larger fault test domains and verifiable design patterns. A tool-chain to transform the SysML model to jpf-Statechart compliant Java code and then verify the generated code via model checking was established. Conclusions and lessons learned from this work are also described, as well as potential avenues for further research and development.

Statechart↗

NASA NTRS2010

Reactive Sequencing for Autonomous Navigation Evolving from Phoenix Entry, Descent, and Landing

Virtual Machine Language (VML) is an award-winning advanced procedural sequencing language in use on NASA deep-space missions since 1997, and was used for the successful entry, descent, and landing (EDL) of the Phoenix spacecraft onto the surface of Mars. Phoenix EDL utilized a state-oriented operations architecture which executed within the constraints of the existing VML 2.0 flight capability, compatible with the linear "land or die" nature of the mission. The intricacies of Phoenix EDL included the planned discarding of portions of the vehicle, the complex communications management for relay through on-orbit assets, the presence of temporally indeterminate physical events, and the need to rapidly catch up four days of sequencing should a reboot of the spacecraft flight computer occur shortly before atmospheric entry. These formidable operational challenges led to new techniques for packaging and coordinating reusable sequences called blocks using one-way synchronization via VML sequencing global variable events. The coordinated blocks acted as an ensemble to land the spacecraft, while individually managing various elements in as simple a fashion as possible. This paper outlines prototype VML 2.1 flight capabilities that have evolved from the one-way synchronization techniques in order to implement even more ambitious autonomous mission capabilities. Target missions for these new capabilities include autonomous touch-and-go sampling of cometary and asteroidal bodies, lunar landing of robotic missions, and ultimately landing of crewed lunar vehicles. Close proximity guidance, navigation, and control operations, on-orbit rendezvous, and descent and landing events featured in these missions require elaborate abort capability, manifesting highly non-linear scenarios that are so complex as to overtax traditional sequencing, or even the sort of one-way coordinated sequencing used during EDL. Foreseeing advanced command and control needs for small body and lunar landing guidance, navigation and control scenarios, work began three years ago on substantial upgrades to VML that are now being exercised in scenarios for lunar landing and comet/asteroid rendezvous. The advanced state-based approach includes coordinated state transition machines with distributed decision-making logic. These state machines are not merely sequences - they are reactive logic constructs capable of autonomous decision making within a well-defined domain. Combined with the JPL's AutoNav software used on Deep Space 1 and Deep Impact, the system allows spacecraft to autonomously navigate to an unmapped surface, soft-contact, and either land or ascend. The state machine architecture enabled by VML 2.1 has successfully performed sampling missions and lunar descent missions in a simulated environment, and is progressing toward flight capability. The authors are also investigating using the VML 2.1 flight director architecture to perform autonomous activities like rendezvous with a passive hypothetical Mars sample return capsule. The approach being pursued is similar to the touch-and-go sampling state machines, with the added complications associated with the search for, physical capture of, and securing of a separate spacecraft. Complications include optically finding and tracking the Orbiting Sample Capsule (OSC), keeping the OSC illuminated, making orbital adjustments, and physically capturing the OSC. Other applications could include autonomous science collection and fault compensation.

asteroid↗

NASA NTRS2015

Spacecube: A Family of Reconfigurable Hybrid On-Board Science Data Processors

SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.

reconfigurable computing↗

NASA NTRS2015

Radiation-Hardened Electronics for Advanced Communications Systems

Novel approach enables high-speed special-purpose processors Advanced reconfigurable and reprogrammable communication systems will require sub-130-nanometer electronics. Legacy single event upset (SEU) radiation-tolerant circuits are ineffective at speeds greater than 125 megahertz. In Phase I of this project, ICs, LLC, demonstrated new base-level logic circuits that provide SEU immunity for sub-130-nanometer high-speed circuits. In Phase II, the company developed an innovative self-restoring logic (SRL) circuit and a system approach that provides high-speed, SEU-tolerant solutions that are effective for sub-130-nanometer electronics scalable to at least 22-nanometer processes. The SRL system can be used in the design of NASA's next-generation special-purpose processors, especially reconfigurable communication processors.

Whitaker, Sterling↗

NASA NTRS2015

Characterizing the Effects of a Vertical Time Threshold for a Class of Well-Clear Definitions

A fundamental requirement for the integration of unmanned aircraft into civil airspace is the capability of aircraft to remain well clear of each other and avoid collisions. This requirement has led to a broad recognition of the need for an unambiguous, formal definition of well clear. It is further recognized that any such definition must be interoperable with existing airborne collision avoidance systems (ACAS). A particular class of well-clear definitions uses logic checks of independent distance thresholds as well as independent time thresholds in the vertical and horizontal dimensions to determine if a well-clear violation is predicted to occur within a given time interval. Existing ACAS systems also use independent distance thresholds, however a common time threshold is used for the vertical and horizontal logic checks. The main contribution of this paper is the characterization of the effects of the decoupled vertical time threshold on a well-clear definition in terms of (1) time to well-clear violation, and (2) interoperability with existing ACAS. The paper provides governing equations for both metrics and includes simulation results to illustrate the relationships. In this paper, interoperability implies that the time of well-clear violation is strictly less than the time a resolution advisory is issued by ACAS. The encounter geometries under consideration in this paper are initially well clear and consist of constant-velocity trajectories resulting in near-mid-air collisions.

Upchurch, Jason M.↗

NASA NTRS2016

Simulation Development and Analysis of Crew Vehicle Ascent Abort

NASA's Commercial Crew Program is an integral step in its journey to Mars as it would expedite development of space technologies and open up partnership with U.S. commercial companies. NASA reviews and independent assessment of Commercial Crew Program is fundamental to its success, and being able to model a commercial crew vehicle in a simulation rather than conduct a live test would be a safer, faster, and less expensive way to assess and certify the capabilities of the vehicle. To this end, my project was to determine the feasibility of using a simulation tool named SOMBAT version 2.0 to model a multiple parachute system for Commercial Crew Program simulation. The main tasks assigned to me were to debug and test the main parachute system model, (capable of simulating one to four main parachute bodies), and to utilize a graphical program to animate the simulation results. To begin tackling the first task, I learned how to use SOMBAT by familiarizing myself with its mechanics and by understanding the methods used to tweak its various parameters and outputs. I then used this new knowledge to set up, run, and analyze many different situations within SOMBAT in order to explore the limitations of the parachute model. Some examples of parameters that I varied include the initial velocity and orientation of the falling capsule, the number of main parachutes, and the location where the parachutes were attached to the capsule. Each parameter changed would give a different output, and in some cases, would expose a bug or limitation in the model. A major bug that I discovered was the inability of the model to handle any number of parachutes other than three. I spent quite some time trying to debug the code logically, but was unable to figure it out until my mentor taught me that digital simulation limitations can occur when some approximations are mistakenly assumed for certain in a physical system. This led me to the realization that unlike in all of the programming classes I have taken thus far that focus on pure logic, simulation code focuses on mimicking the physical world with some approximation and can have inaccuracies or numerical instabilities. Learning from my mistake, I adopted new methods to analyze these different simulations. One method the student used was to numerically plot various physical parameters using MATLAB to confirm the mechanical behavior of the system in addition to comparing the data to the output from a separate simulation tool called FAST. By having full control over what was being outputted from the simulation, I could choose which parameters to change and to plot as well as how to plot them, allowing for an in depth analysis of the data. Another method of analysis was to convert the output data into a graphical animation. Unlike the numerical plots, where all of the physical components were displayed separately, this graphical display allows for a combined look at the simulation output that makes it much easier for one to see the physical behavior of the model. The process for converting SOMBAT output for EDGE graphical display had to be developed. With some guidance from other EDGE users, I developed a process and created a script that would easily allow one to display simulations graphically. Another limitation with the SOMBAT model was the inability for the capsule to have the main parachutes instantly deployed with a large angle between the air speed vector and the chutes drag vector. To explore this problem, I had to learn about different coordinate frames used in Guidance, Navigation & Control (J2000, ECEF, ENU, etc.) to describe the motion of a vehicle and about Euler angles (e.g. Roll, Pitch, Yaw) to describe the orientation of the vehicle. With a thorough explanation from my mentor about the description of each coordinate frame, as well as how to use a directional cosine matrix to transform one frame to another, I investigated the problem by simulating different capsule orientations. In the end, I was able to show that this limitation could be avoided if the capsule is initially oriented antiparallel to its velocity vector.

Wong, Chi S.↗

NASA NTRS2017

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Advanced Collision Avoidance System for UAS (ACAS Xu) Interoperability White Paper Presentation

The Phase 1 DAA Minimum Operational Performance Standards (MOPS) provided requirements for two classes of DAA equipment: equipment Class 1 contains the basic DAA equipment required to assist a pilot in remaining well clear, while equipment Class 2 integrates the Traffic Alert and Collision Avoidance (TCAS) II system. Thus, the Class 1 system provides RWC functionality only, while the Class 2 system is intended to provide both RWC and Collision Avoidance (CA) functionality, in compliance with the Minimum Aviation System Performance (MASPS) for the Interoperability of Airborne Collision Avoidance Systems. The FAAs TCAS Program Office is currently developing Airborne Collision Avoidance System X (ACAS X) to support the objectives of the Federal Aviation Administrations (FAA) Next Generation Air Transportation System Program (NextGen). ACAS X has a suite of variants with a common underlying design that are intended to be optimized for their intended airframes and operations. ACAS Xu being is designed for UAS and allows for new surveillance technologies and tailored logic for platforms with different performance characteristics. In addition to Collision Avoidance (CA) alerting and guidance, ACAS Xu is being tuned to provide RWC alerting and guidance in compliance with the SC 228 DAA MOPS. With a single logic performing both RWC and CA functions, ACAS Xu will provide industry with an integrated DAA solution that addresses many of the interoperability shortcomings of Phase I systems. While the MOPS for ACAS Xu will specify an integrated DAA system, it will need to show compliance with the RWC alerting thresholds and alerting requirements defined in the DAA Phase 2 MOPS. Further, some functional components of the ACAS Xu system such as the remote pilots displayed guidance might be mostly references to the corresponding requirements in the DAA MOPS. To provide a seamless, integrated, RWC-CA system to assist the pilot in remaining well clear and avoiding collisions, several issues need to be addressed within the Phase 2 SC-228 DAA efforts. Interoperability of the RWC and CA alerting and guidance, and ensuring pilot comprehension, compliance and performance, will be a primary research area.

detect and avoid↗

NASA NTRS2017

Digital Device Architecture and the Safe Use of Flash Devices in Munitions

Flash technology is being utilized in fuzed munition applications and, based on the development of digital logic devices in the commercial world, usage of flash technology will increase. Digital devices of interest to designers include flash-based microcontrollers and field programmable gate arrays (FPGAs). Almost a decade ago, a study was undertaken to determine if flash-based microcontrollers could be safely used in fuzes and, if so, how should such devices be applied. The results were documented in the Technical Manual for the Use of Logic Devices in Safety Features. This paper will first review the Technical Manual and discuss the rationale behind the suggested architectures for microcontrollers and a brief review of the concern about data retention in flash cells. An architectural feature in the microcontroller under study will be discussed and its use will show how to screen for weak or failed cells during manufacture, storage, or immediately prior to use. As was done for microcontrollers a decade ago, architectures for a flash-based FPGA will be discussed, showing how it can be safely used in fuzes. Additionally, architectures for using non-volatile (including flash-based) storage will be discussed for SRAM-based FPGAs.

Katz, Richard B.↗

NASA NTRS2017

Software Defined Radios - Architectures, Systems and Functions

Software Defined Radio (SDR) technology has been proven in the commercial sector since the early 90's. Today's rapid advancement in mobile telephone reliability and power management capabilities exemplifies the effectiveness of the SDR technology for the modern communications market. SDR technology offers potential to revolutionize satellite transponder technology by increasing science data through-put capability by at least an order of magnitude. While the SDR is adaptive in nature and is "One-size-fits-all" by design, conventional transponders are built to a specific platform and must be redesigned for every new bus. The SDR uses a minimum amount of analog/Radio Frequency (RF) components to up/down-convert the RF signal to/from a digital format. Once analog data is digitized, all processing is performed using hardware logic. Typical SDR processes include; filtering, modulation, up/down converting and demodulation. These innovations have reduced the cost of transceivers, a decrease in power requirements and a commensurate reduction in volume. An additional pay-off is the increased flexibility of the SDR: allowing the same hardware to implement multiple transponder types by altering hardware logic -no change of analog hardware is required -all of which can be ultimately accomplished in orbit.

Sims, Herb↗

NASA NTRS2017

Software Defined Radios - Architectures, Systems and Functions

Software Defined Radio is an industry term describing a method of utilizing a minimum amount of Radio Frequency (RF)/analog electronics before digitization takes place. Upon digitization all other functions are performed in software/firmware. There are as many different types of SDRs as there are data systems. Software Defined Radio (SDR) technology has been proven in the commercial sector since the early 90's. Today's rapid advancement in mobile telephone reliability and power management capabilities exemplifies the effectiveness of the SDR technology for the modern communications market. In contrast the foundations of transponder technology presently qualified for satellite applications were developed during the early space program of the 1960's. SDR technology offers potential to revolutionize satellite transponder technology by increasing science data through-put capability by at least an order of magnitude. While the SDR is adaptive in nature and is "One-size-fits-all" by design, conventional transponders are built to a specific platform and must be redesigned for every new bus. The SDR uses a minimum amount of analog/Radio Frequency components to up/down-convert the RF signal to/from a digital format. Once analog data is digitized, all processing is performed using hardware logic. Typical SDR processes include; filtering, modulation, up/down converting and demodulation. This presentation will show how the emerging SDR market has leveraged the existing commercial sector to provide a path to a radiation tolerant SDR transponder. These innovations will reduce the cost of transceivers, a decrease in power requirements and a commensurate reduction in volume. A second pay-off is the increased flexibility of the SDR by allowing the same hardware to implement multiple transponder types by altering hardware logic - no change of analog hardware is required - all of which can be ultimately accomplished in orbit. This in turn would provide high capability and low cost transponder to programs of all sizes.

Sims, William H.↗

NASA NTRS2017

A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.

engine control↗

NASA NTRS2017

Unexpected Control Structure Interaction on International Space Station

On June 23, 2011, the International Space Station (ISS) was performing a routine 180 degree yaw maneuver in support of a Russian vehicle docking when the on board Russian Segment (RS) software unexpectedly declared two attitude thrusters failed and switched thruster configurations in response to unanticipated ISS dynamic motion. Flight data analysis after the maneuver indicated that higher than predicted structural loads had been induced at various locations on the United States (U.S.) segment of the ISS. Further analysis revealed that the attitude control system was firing thrusters in response to both structural flex and rigid body rates, which resonated the structure and caused high loads and fatigue cycles. It was later determined that the thruster themselves were healthy. The RS software logic, which was intended to react to thruster failures, had instead been heavily influenced by interaction between the control system and structural flex. This paper will discuss the technical aspects of the control structure interaction problem that led to the RS control system firing thrusters in response to structural flex, the factors that led to insufficient preflight analysis of the thruster firings, and the ramifications the event had on the ISS. An immediate consequence included limiting which thrusters could be used for attitude control. This complicated the planning of on-orbit thruster events and necessitated the use of suboptimal thruster configurations that increased propellant usage and caused thruster lifetime usage concerns. In addition to the technical aspects of the problem, the team dynamics and communication shortcomings that led to such an event happening in an environment where extensive analysis is performed in support of human space flight will also be examined. Finally, the technical solution will be presented, which required a multidisciplinary effort between the U.S. and Russian control system engineers and loads and dynamics structural engineers to develop and implement an extensive modification in the RS software logic for ISS attitude control thruster firings.

Gomez, Susan F.↗

NASA NTRS2017

Software Defined Radios - Architectures, Systems and Functions

Sims, Herb↗

NASA NTRS2017

A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

engine control↗

NASA NTRS2018

Estimating Software Reliability for Space Launch Vehicles in Probabilistic Risk Assessment (PRA)

It is acutely recognized in the Probabilistic Risk assessment (PRA) field that software plays a defining role in overall system reliability for all modern systems across a wide variety of industries. Regardless if the software is embedded firmware for working components or elements, part of a Human-Machine-Interface, or automated command and control logic, the success of the software to fulfill its function under nominal and off-nominal environments will be a dominant contributor to system reliability. It is also recognized that software reliability prediction and estimation is one of the more challenging and questionable aspects of any PRA or system analyses due to the nature of software and its integration with physics based systems. Irrespective of this dichotomy, any incorporation of software reliability methods requires that the contributions are accountable, quantitative, and tractable. This paper provides a brief overview of software reliability methods, establishes some minimum requirements that the methods should incorporate for completeness, and provides a logic structure for applying software reliability. Model resolution will be discussed that supports current testing plans and trade studies. We will provide initial recommendations for use in the NASA PRA and present a future dynamic option for software and PRA. Space Launch Vehicle Software is recognized to be reliable in static conditions, yet relatively vulnerable to a set of failure modes in changing environments/flight phases. Two quantitative methods were chosen to incorporate software reliability into a Space Launch Vehicle PRA accounting for phase adjustments. One method predicts latent software failure using statistical methods, and the second provides estimates of coding errors and software operating system failures based on test and historical data, respectively. Software uncertainty will also be discussed. We determined that recommendations for PRA software reliability should be modeled at the software module level where multiple software components compose a module and combinations of the software architecture can lead to a functional failure.

Novack, Steven↗

NASA NTRS2018

Estimating Software Reliability for Space Launch Vehicles in Probabilistic Risk Assessment (PRA)

It is acutely recognized in the Probabilistic Risk Assessment (PRA) field that software plays a defining role in overall system reliability for all modern systems across a wide variety of industries. Regardless of whether the software is embedded firmware for working components or elements, part of a Human-Machine-Interface, or automated command and control logic, the success of the software to fulfill its function under nominal and off-nominal environments will be a dominant contributor to system reliability. It is also recognized that software reliability prediction and estimation is one of the more challenging and questionable aspects of any PRA or system analyses due to the nature of software and its integration with physics based systems. Irrespective of this dichotomy, any incorporation of software reliability methods requires that the contributions are accountable, quantitative, and tractable. This paper provides a brief overview of software reliability methods, establishes some minimum requirements that the methods should incorporate for completeness, and provides a logic structure for applying software reliability. Model resolution will be discussed that supports current testing plans and trade studies. We will provide initial recommendations for use in the National Aeronautics and Space Administration (NASA) PRA and present a future dynamic option for software and PRA. Space Launch Vehicle software is recognized to be reliable in static conditions, yet relatively vulnerable to a set of failure modes in changing environments/flight phases. Two quantitative methods were chosen to incorporate software reliability into a Space Launch Vehicle PRA accounting for phase adjustments. One method predicts latent software failure using statistical methods, and the second provides estimates of coding errors and software operating system failures based on test and historical data. Software uncertainty will also be discussed. It is determined that recommendations for PRA software reliability should be modeled at the software module level where multiple software components compose a module and combinations of the software architecture can lead to a functional failure.

Steven D. Novack↗

NASA NTRS2019

Method for Tracking and Communicating Aggregate Risk Through the Use of Model-Based Systems Engineering (MBSE) Tools

Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.

model based mission assurance↗