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NASA NTRS2008

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗

NASA NTRS2016

A Model for Jet-Surface Interaction Noise Using Physically Realizable Upstream Turbulence Conditions

This paper is a continuation of previous work in which a generalized Rapid Distortion Theory (RDT) formulation was used to model low-frequency trailing-edge noise. The research was motivated by proposed next-generation aircraft configurations where the exhaust system is tightly integrated with the airframe. Data from recent experiments at NASA on the interaction between high-Reynolds-number subsonic jet flows and an external flat plate showed that the power spectral density (PSD) of the far-field pressure underwent considerable amplification at low frequencies. For example, at the 90deg observation angle, the low-frequency noise could be as much as 10 dB greater than the jet noise itself. In this paper, we present predictions of the noise generated by the interaction of a rectangular jet with the trailing edge of a semi-infinite flat plate. The calculations are based on a formula for the acoustic spectrum of this noise source derived from an exact formal solution of the linearized Euler equations involving (in this case) one arbitrary convected scalar quantity and a Rayleigh equation Green's function. A low-frequency asymptotic approximation for the Green's function based on a two-dimensional mean flow is used in the calculations along with a physically realizable upstream turbulence spectrum, which includes a finite decorrelation region. Numerical predictions of the sound field, based on three-dimensional RANS solutions to determine the mean flow, turbulent kinetic energy and turbulence length and time scales, for a range of subsonic acoustic Mach number jets and nozzle aspect ratios are compared with experimental data. Comparisons of the RANS results with flow data are also presented for selected cases. We find that a finite decorrelation region in the turbulence spectrum increases the low-frequency algebraic decay (the low frequency "roll-off") of the acoustic spectrum with angular frequency thereby producing much closer agreement with noise data for Strouhal numbers less than 0.1. Secondly, the large-aspect-ratio theory is able to predict the low-frequency amplification due to the jet-edge interaction reasonably well, even for moderate aspect ratio nozzles. We show also that the noise predictions for smaller aspect ratio jets can be fine-tuned using the appropriate RANS-based mean flow and turbulence properties.

Jet↗

NASA NTRS2004

The Role of Ontologies in Schema-based Program Synthesis

Program synthesis is the process of automatically deriving executable code from (non-executable) high-level specifications. It is more flexible and powerful than conventional code generation techniques that simply translate algorithmic specifications into lower-level code or only create code skeletons from structural specifications (such as UML class diagrams). Key to building a successful synthesis system is specializing to an appropriate application domain. The AUTOBAYES and AUTOFILTER systems, under development at NASA Ames, operate in the two domains of data analysis and state estimation, respectively. The central concept of both systems is the schema, a representation of reusable computational knowledge. This can take various forms, including high-level algorithm templates, code optimizations, datatype refinements, or architectural information. A schema also contains applicability conditions that are used to determine when it can be applied safely. These conditions can refer to the initial specification, to intermediate results, or to elements of the partially-instantiated code. Schema-based synthesis uses AI technology to recursively apply schemas to gradually refine a specification into executable code. This process proceeds in two main phases. A front-end gradually transforms the problem specification into a program represented in an abstract intermediate code. A backend then compiles this further down into a concrete target programming language of choice. A core engine applies schemas on the initial problem specification, then uses the output of those schemas as the input for other schemas, until the full implementation is generated. Since there might be different schemas that implement different solutions to the same problem this process can generate an entire solution tree. AUTOBAYES and AUTOFILTER have reached the level of maturity where they enable users to solve interesting application problems, e.g., the analysis of Hubble Space Telescope images. They are large (in total around 100kLoC Prolog), knowledge intensive systems that employ complex symbolic reasoning to generate a wide range of non-trivial programs for complex application do- mains. Their schemas can have complex interactions, which make it hard to change them in isolation or even understand what an existing schema actually does. Adding more capabilities by increasing the number of schemas will only worsen this situation, ultimately leading to the entropy death of the synthesis system. The root came of this problem is that the domain knowledge is scattered throughout the entire system and only represented implicitly in the schema implementations. In our current work, we are addressing this problem by making explicit the knowledge from Merent parts of the synthesis system. Here; we discuss how Gruber's definition of an ontology as an explicit specification of a conceptualization matches our efforts in identifying and explicating the domain-specific concepts. We outline the dual role ontologies play in schema-based synthesis and argue that they address different audiences and serve different purposes. Their first role is descriptive: they serve as explicit documentation, and help to understand the internal structure of the system. Their second role is prescriptive: they provide the formal basis against which the other parts of the system (e.g., schemas) can be checked. Their final role is referential: ontologies also provide semantically meaningful "hooks" which allow schemas and tools to access the internal state of the program derivation process (e.g., fragments of the generated code) in domain-specific rather than language-specific terms, and thus to modify it in a controlled fashion. For discussion purposes we use AUTOLINEAR, a small synthesis system we are currently experimenting with, which can generate code for solving a system of linear equations, Az = b.

Bures, Tomas↗

NASA NTRS2013

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

mathematical models↗

NASA NTRS1994

A dynamic localization model with stochastic backscatter

The modeling of subgrid scales in large-eddy simulation (LES) has been rationalized by the introduction of the dynamic localization procedure. This method allows one to compute rather than prescribe the unknown coefficients in the subgrid-scale model. Formally, the LES equations are supposed to be obtained by applying to the Navier-Stokes equations a 'grid filter' operation. Though the subgrid stress itself is unknown, an identity between subgrid stresses generated by different filters has been derived. Although preliminary tests of the Dynamic Localization Model (DLM) with k-equation have been satisfactory, the use of a negative eddy viscosity to describe backscatter is probably a crude representation of the physics of reverse transfer of energy. Indeed, the model is fully deterministic. Knowing the filtered velocity field and the subgrid-scale energy, the subgrid stress is automatically determined. We know that the LES equations cannot be fully deterministic since the small scales are not resolved. This stems from an important distinction between equilibrium hydrodynamics and turbulence. In equilibrium hydrodynamics, the molecular motions are also not resolved. However, there is a clear separation of scale between these unresolved motions and the relevant hydrodynamic scales. The result of molecular motions can then be separated into an average effect (the molecular viscosity) and some fluctuations. Due to the large number of molecules present in a box with size of the order of the hydrodynamic scale, the ratio between fluctuations and the average effect should be very small (as a result of the 'law of large numbers'). For that reason, the hydrodynamic balance equations are usually purely deterministic. In turbulence, however, there is no clear separation of scale between small and large eddies. In that case, the fluctuations around a deterministic eddy viscosity term could be significant. An eddy noise would then appear through a stochastic term in the subgrid-scale model and could be the source of backscatter.

Carati, Daniele↗

NASA NTRS2004

EVA Performance Prediction

Astronaut physical performance capabilities in micro gravity EV A or on planetary surfaces when encumbered by a life support suit and debilitated by a long exposure to micro gravity will be less than unencumbered pre flight capabilities. The big question addressed by human factors engineers is: what can the astronaut be expected to do on EVA or when we arrive at a planetary surface? A second question is: what aids to performance will be needed to enhance the human physical capability? These questions are important for a number of reasons. First it is necessary to carry out accurate planning of human physical demands to ensure that time and energy critical tasks can be carried out with confidence. Second it is important that the crew members (and their ground or planetary base monitors) have a realistic picture of their own capabilities, as excessive fatigue can lead to catastrophic failure. Third it is important to design appropriate equipment to enhance human sensory capabilities, locomotion, materials handling and manipulation. The evidence from physiological research points to musculoskeletal, cardiovascular and neurovestibular degradation during long duration exposure to micro gravity . The evidence from the biomechanics laboratory (and the Neutral Buoyancy Laboratory) points to a reduction in range of motion, strength and stamina when encumbered by a pressurized suit. The evidence from a long history of EVAs is that crewmembers are indeed restricted in their physical capabilities. There is a wealth of evidence in the literature on the causes and effects of degraded human performance in the laboratory, in sports and athletics, in industry and in other physically demanding jobs. One approach to this challenge is through biomechanical and performance modeling. Such models must be based on thorough task analysis, reliable human performance data from controlled studies, and functional extrapolations validated in analog contexts. The task analyses currently carried out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

Peacock, Brian↗

NASA NTRS1992

Approximation methods for stochastic petri nets

Stochastic Marked Graphs are a concurrent decision free formalism provided with a powerful synchronization mechanism generalizing conventional Fork Join Queueing Networks. In some particular cases the analysis of the throughput can be done analytically. Otherwise the analysis suffers from the classical state explosion problem. Embedded in the divide and conquer paradigm, approximation techniques are introduced for the analysis of stochastic marked graphs and Macroplace/Macrotransition-nets (MPMT-nets), a new subclass introduced herein. MPMT-nets are a subclass of Petri nets that allow limited choice, concurrency and sharing of resources. The modeling power of MPMT is much larger than that of marked graphs, e.g., MPMT-nets can model manufacturing flow lines with unreliable machines and dataflow graphs where choice and synchronization occur. The basic idea leads to the notion of a cut to split the original net system into two subnets. The cuts lead to two aggregated net systems where one of the subnets is reduced to a single transition. A further reduction leads to a basic skeleton. The generalization of the idea leads to multiple cuts, where single cuts can be applied recursively leading to a hierarchical decomposition. Based on the decomposition, a response time approximation technique for the performance analysis is introduced. Also, delay equivalence, which has previously been introduced in the context of marked graphs by Woodside et al., Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's is slower, but the accuracy is generally better. Delay equivalence often fails to converge, while flow equivalent aggregation can lead to potentially bad results if a strong dependence of the mean completion time on the interarrival process exists.

Jungnitz, Hauke Joerg↗

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 NTRS2016

Enabling Affordable Communications for the Burgeoning Deep Space Cubesat Fleet

The low costs of development and launch, coupled with new propulsive technologies, have made CubeSats increasingly popular for use in science investigations beyond geosynchronous orbit. As this deep space CubeSat fleet grows in size, the challenge of trying to provide affordable communications for it grows commensurately. The mass, power, and volume constraints inherent to CubeSats limit the antenna size and transmit power that they can use to close the deep space link. As a consequence, CubeSats need to rely more heavily on ground antennas that are characterized by large aperture, low noise temperatures, and relatively high-power transmitters. Such antennas are not in great abundance, nor are they inexpensive to build. For this reason, NASA’s Deep Space Network has been advocating a three-pronged approach to meeting anticipated CubeSat demand: development of simultaneous, shared-beam multi-spacecraft communications capabilities, development of large-antenna cross-support arrangements with other agencies and universities, and development of less uplink-intensive navigation techniques. This paper focuses on the pursuit of simultaneous, shared-beam multi-spacecraft communications capabilities. While the Multiple Spacecraft per Antenna (MSPA) technique has existed for over a decade, it has generally been limited to supporting downlink for just two in-beam spacecraft at a time. This limitation has largely been a function of the number and cost of available receivers. A relatively new technique that potentially overcomes this limitation is Opportunistic MSPA (OMSPA). Instead of relying on additional receivers, OMSPA makes use of a digital recorder at each ground station that is capable of capturing the intermediate frequency (IF) signals from every spacecraft in the antenna beam within the frequency bands of interest. When CubeSat projects see one or more opportunities for their CubeSat(s) to intercept the traditionally scheduled antenna beam of a “host” spacecraft, they can arrange for the CubeSat(s) to transmit open loop during those opportunities. Via a secure Internet site, the CubeSat mission operators can then retrieve the time- and frequency-relevant portions of the digital recording for subsequent demodulation and decoding, or subscribe to a service that does it for them. This “opportunistic” use of a host spacecraft’s ground antenna beam potentially enables CubeSat projects to make use of large ground antennas for downlink without having to compete with bigger, better-funded missions for antenna time in the formal scheduling process. In so doing, it also potentially enables CubeSat projects to avoid the aperture fees associated with formally scheduled downlink time - fees that factor into the “bottom-line” of competitively-bid NASA missions and that actually get charged to non-NASA missions. Taking advantage of these potential OMSPA benefits, however, will require CubeSat projects to pursue mission designs that ensure at least periodic in-beam operations relative to a “host” spacecraft. In the case of a constellation of CubeSats with inter-spacecraft distances that do not extend outside of the beam-width of the desired ground antenna at the given range, one CubeSat can serve as the “host” and have a formally scheduled downlink while the rest of the CubeSats can downlink essentially for “free” via OMSPA. Deep space CubeSats, of course, will need uplink in addition to downlink. Beyond commanding, this need is driven by the use of two-way ranging and Doppler for navigation. While OMSPA may not directly facilitate uplink, it does have the potential to free up antennas for those spacecraft that periodically require formally scheduled links for commanding and two-way radio metrics. NASA is also exploring the physical feasibility of an in-beam, simultaneous multi-spacecraft uplink technique. As with OMSPA, if successful, it will require little new equipment, further enabling affordable deep space CubeSat communications.

Abraham, Douglas S.↗

NASA NTRS2003

Self-Supervised Dynamical Systems

Some progress has been made in a continuing effort to develop mathematical models of the behaviors of multi-agent systems known in biology, economics, and sociology (e.g., systems ranging from single or a few biomolecules to many interacting higher organisms). Living systems can be characterized by nonlinear evolution of probability distributions over different possible choices of the next steps in their motions. One of the main challenges in mathematical modeling of living systems is to distinguish between random walks of purely physical origin (for instance, Brownian motions) and those of biological origin. Following a line of reasoning from prior research, it has been assumed, in the present development, that a biological random walk can be represented by a nonlinear mathematical model that represents coupled mental and motor dynamics incorporating the psychological concept of reflection or self-image. The nonlinear dynamics impart the lifelike ability to behave in ways and to exhibit patterns that depart from thermodynamic equilibrium. Reflection or self-image has traditionally been recognized as a basic element of intelligence. The nonlinear mathematical models of the present development are denoted self-supervised dynamical systems. They include (1) equations of classical dynamics, including random components caused by uncertainties in initial conditions and by Langevin forces, coupled with (2) the corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces, denoted supervising forces, composed of probability densities and functionals thereof. The equations of classical mechanics represent motor dynamics that is, dynamics in the traditional sense, signifying Newton s equations of motion. The evolution of the probability densities represents mental dynamics or self-image. Then the interaction between the physical and metal aspects of a monad is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. This feedback is what makes the evolution of probability densities nonlinear. The deviation from linear evolution can be characterized, in a sense, as an expression of free will. It has been demonstrated that probability densities can approach prescribed attractors while exhibiting such patterns as shock waves, solitons, and chaos in probability space. The concept of self-supervised dynamical systems has been considered for application to diverse phenomena, including information-based neural networks, cooperation, competition, deception, games, and control of chaos. In addition, a formal similarity between the mathematical structures of self-supervised dynamical systems and of quantum-mechanical systems has been investigated.

Zak, Michail↗

NASA NTRS2011

An Interim Report on NASA's Draft Space Technology Roadmaps

NASA has developed a set of 14 draft roadmaps to guide the development of space technologies under the leadership of the NASA Office of the Chief Technologist (OCT). Each of these roadmaps focuses on a particular technology area (TA). The roadmaps are intended to foster the development of advanced technologies and concepts that address NASA's needs and contribute to other aerospace and national needs. OCT requested that the National Research Council conduct a study to review the draft roadmaps, gather and assess relevant community input, and make recommendations and suggest priorities to inform NASA's decisions as it finalizes its roadmaps. The statement of task states that "based on the results of the community input and its own deliberations, the steering committee will prepare a brief interim report that addresses high-level issues associated with the roadmaps, such as the advisability of modifying the number or technical focus of the draft NASA roadmaps." This interim report, which does not include formal recommendations, addresses that one element of the study charge. NASA requested this interim report so that it would have the opportunity to make an early start in modifying the draft roadmaps based on feedback from the panels and steering committee. The final report will address all other tasks in the statement of task. In particular, the final report will include a prioritization of technologies, will describe in detail the prioritization process and criteria, and will include specific recommendations on a variety of topics, including many of the topics mentioned in this interim report. In developing both this interim report and the final report to come, the steering committee draws on the work of six study panels organized by technical area, loosely following the organization of the 14 roadmaps, as follows: A Panel 1: Propulsion and Power TA01 Launch Propulsion Systems TA02 In-Space Propulsion Technologies TA03 Space Power and Energy Storage Systems TA13 Ground and Launch Systems Processing B Panel 2: Robotics, Communications, and Navigation TA04 Robotics, TeleRobotics, and Autonomous Systems TA05 Communication and Navigation Systems C Panel 3: Instruments and Computing TA08 Science Instruments, Observatories, and Sensor Systems TA11 Modeling, Simulation, Information Technology, and Data Processing D Panel 4: Human Health and Surface Exploration TA06 Human Health, Life Support, and Habitation Systems TA07 Human Exploration Destination Systems E Panel 5: Materials Panel TA10 Nanotechnology TA12 Materials, Structures, Mechanical Systems, and Manufacturing TA14 Thermal Management Systems F Panel 6: Entry, Descent, and Landing Panel TA09 Entry, Descent, and Landing Systems In addition to drawing on the expertise represented on the steering committee and panels, the committee obtained input from each of 14 public workshops held on each of the 14 roadmaps. At these 1-day workshops, invited speakers, guests, and members of the public engaged in discussions on the different technology areas and their value to NASA. Broad community input was also solicited from a public website, where more than 240 public comments were received on the draft roadmaps in response to application of criteria (such as benefit, risk and reasonableness, and alignment with NASA and national goals) that the steering committee established. This interim report reflects the results of deliberations by the steering committee in light of these public inputs as well as additional inputs from the six panels. The steering committee's final report will be completed early in 2012. That report will prioritize the technologies that span the entire scope of the 14 roadmaps and provide additional guidance on crosscutting themes and other relevant topics.

Source record↗

NASA NTRS2018

NASA Additive Manufacturing Initiatives for Deep Space Human Exploration

Additive Manufacturing (AM) is being infused into aerospace industries at an accelerated pace. Reasons for this rapid adoption include: (1) Innovation Capability e.g. design features such as topology optimization, integrated fluid passages, and mesh structures; (2) Rapid Development and Optimization - ability to quickly iterate the design, development, and test cycle; (3) Affordability - reductions in part counts, cost, and schedule. NASA's Marshall Space Flight Center (MSFC) has taken a leadership role in application of AM technologies for deep space human exploration, leading the Agency's In Space Manufacturing (ISM) initiative and the application of AM for a broad variety of space propulsion systems. MSFC has championed the development of ISM capabilities since our first reduced-gravity aircraft experiment flew in 1999. Partnering with Made In Space, MSFC placed the first 3D Printer on ISS in 2014 and the second generation printer, the Additive Manufacturing Facility, in 2016. The next ISS technology demonstration will be the Refabricator, a recycler/basic printer scheduled to launch in late Fall 2018. Ground-based development is progressing in common use materials, metals 3D printing, printed electronics, and the new cornerstone of ISM, the FabLab. The latest developments in each area will be described. An overview of NASA's In Space Robotic Manufacturing and Assembly (IRMA) ground-based risk reduction projects will also be presented. MSFC has aggressively incorporated AM capabilities for design and development of space propulsion components. The capabilities have been rapidly matured and extensively exercised to produce and hot-fire test the Additive Manufacturing Demonstrator Engine, an in-space class prototype engine. This experience base has been extended to support Aerojet Rocketdyne in the application of AM to the RS-25, the Space Launch System Core Stage engine, and to small propulsion systems and thrusters for small satellites and cubesats. The latest developments will be described. In responding to a request from NASA's Commercial Crew Program for a consistent methodology for evaluation of AM processes and parts, MSFC began development of a draft standard for AM space flight hardware in late 2014. The draft was broadly disseminated for comments in mid-2015, and subsequently revised into two documents, a standard and a specification for AM space flight hardware, which were formally released by MSFC in October 2017. An overview of the key elements of these documents will be presented.

Clinton, Raymond↗

NASA NTRS2006

SpaceWire Protocol ID: What Does It Mean To You?

Spacewire is becoming a popular solution for satellite high-speed data buses because it is a simple standard that provides great flexibility for a wide range of system requirements. It is simple in packet format and protocol, allowing users to easily tailor their implementation for their specific application. Some of the attractive aspects of Spacewire that make it easy to implement also make it hard for future reuse. Protocol reuse is difficult because Spacewire does not have a defined mechanism to communicate with the higher layers of the protocol stack. This has forced users of Spacewire to define unique packet formats and define how these packets are to be processed. Each mission writes their own Interface Control Document (ICD) and tailors Spacewire for their specific requirements making reuse difficult. Part of the reason for this habit may be because engineers typically optimize designs for their own requirements in the absence of a standard. This is an inefficient use of project resources and costs more to develop missions. A new packet format for Spacewire has been defined as a solution for this problem. This new packet format is a compliment to the Spacewire standard that will support protocol development upon Spacewire. The new packet definition does not replace the current packet structure, i.e., does not make the standard obsolete, but merely extends the standard for those who want to develop protocols over Spacewire. The Spacewire packet is defined with the first part being the Destination Address, which may be one or more bytes. This is followed by the packet cargo, which is user defined. The cargo is truncated with an End-Of-Packet (EOP) marker. This packet structure offers low packet overhead and allows the user to define how the contents are to be formatted. It also provides for many different addressing schemes, which provide flexibility in the system. This packet flexibility is typically an attractive part of the Spacewire. The new extended packet format adds one new field to the packet that greatly enhances the capability of Spacewire. This new field called the Protocol Identifier (ID) is used to identify the packet contents and the associated processing for the packet. This feature along with the restriction in the packet format that uses the Protocol ID, allows a deterministic method of decoding packets that was not before possible. The first part of the packet is still the Destination Address, which still conforms to the original standard but with one restriction. The restriction is that the first byte seen at the destination by the user needs to be a logical address, independent of the addressing scheme used. The second field is defined as the Protocol ID, which is usually one byte in length. The packet cargo (user defined) follows the Protocol ID. After the packet cargo is the EOP, which defines the end of packet. The value of the Protocol ID is assigned by the Spacewire working group and the protocol description published for others to use. The development of Protocols for Spacewire is currently the area of greatest activity by the Spacewire working group. The first protocol definition by the working group has been completed and is now in the process of formal standardization. There are many other protocols in development for missions that have not yet received formal Protocol ID assignment, but even if the protocols are not formally assigned a value, this effort will provide synergism for future developments.

Rakow, Glenn↗