ALBERT

Description: To provide affordable space transportation we must be capable of using common fixed assets and the infrastructure for multiple purposes simultaneously. The Space Shuttle was operated for thirty years, but was not able to establish an effective continuous improvement program because of the high risk to the crew on every mission. An unmanned capability is needed to provide an acceptable risk to the primary mission. This paper is intended to present a case where a commercial space venture could share the large fixed cost of operating the infrastructure with the government while the government provides new advanced technology that is focused on reduced operating cost to the common launch transportation system. A conceivable commercial space venture could provide educational entertainment for the country's youth that would stimulate their interest in the science, technology, engineering, and mathematics (STEM) through access at entertainment parks or the existing Space Visitor Centers. The paper uses this example to demonstrate how growing public-private space market demand will re-orient space transportation industry priorities in flight and ground system design and technology development, and how the infrastructure is used and shared.

Description: NASA is committed to finding innovative solutions that improve the operational performance of ground support equipment while providing environment and cost benefits, as well. Through the Hydrogen Fuel Cell Mobile Lighting Tower (HFCML) project, NASA gained operational exposure to a novel application of high efficiency technologies. Traditionally, outdoor lighting and auxiliary power at security gates, launch viewing sites, fallback areas, outage support, and special events is provided by diesel generators with metal halide lights. Diesel generators inherently contribute to C02, NOx, particulate emissions, and are very noisy. In 2010, engineers from NASA's Technology Evaluation for Environmental Risk Mitigation Principal Center (TEERM) introduced KSC operations to a novel technology for outdoor lighting needs. Developed by a team led by Sandia National Laboratory (SNL), the technology pairs a 5kW hydrogen fuel cell with robust high efficiency plasma lights in a towable trailer. Increased efficiency, in both the fuel cell power source and lighting load, yields longer run times between fueling operations while providing greater auxiliary power. Because of the unit's quiet operation and no exhaust fumes, it is capable of being used indoors and in emergency situations, and meets the needs of all other operational roles for metal halide/diesel generators. The only discharge is some water and warm air. Environmental benefits include elimination of diesel particulate emissions and estimated 73% greenhouse gas emissions savings when the hydrogen source is natural gas (per GREET model). As the technology matures the costs could become competitive for the fuel cell units which are approximately 5 times diesel units. Initial operational . concerns included the hydrogen storage tanks and valves, lightning safety/grounding, and required operating and refueling procedures. TEERM facilitated technical information exchange (design drawings, technical standards, and operations manuals) necessary for KSC hydrogen system experts to approve use of the HFCML unit, including initiating the environmental checklist (i.e. exterior lighting waiver due to sea turtles), and development of operations and maintenance instructions. TEERM worked with SNL to establish a bailment agreement for KSC to utilize a Beta unit as part of normal Center Operations for a period of twelve months.

Description: This software translates MAPGEN (Europa and APGEN) domains to ASPEN, and the resulting domain can be used to perform planning for the Mars Exploration Rover (MER). In other words, this is a conversion of two distinct planning languages (both declarative and procedural) to a third (declarative) planning language in order to solve the problem of faithful translation from mixed-domain representations into the ASPEN Modeling Language. The MAPGEN planning system is an example of a hybrid procedural/declarative system where the advantages of each are leveraged to produce an effective planner/scheduler for MER tactical planning. The adaptation of the planning system (ASPEN) was investigated, and, with some translation, much of the procedural knowledge encoding is amenable to declarative knowledge encoding. The approach was to compose translators from the core languages used for adapting MAGPEN, which consists of Europa and APGEN. Europa is a constraint- based planner/scheduler where domains are encoded using a declarative model. APGEN is also constraint-based, in that it tracks constraints on resources and states and other variables. Domains are encoded in both constraints and code snippets that execute according to a forward sweep through the plan. Europa and APGEN communicate to each other using proxy activities in APGEN that represent constraints and/or tokens in Europa. The composition of a translator from Europa to ASPEN was fairly straightforward, as ASPEN is also a declarative planning system, and the specific uses of Europa for the MER domain matched ASPEN s native encoding fairly closely. On the other hand, translating from APGEN to ASPEN was considerably more involved. On the surface, the types of activities and resources one encodes in APGEN appear to match oneto- one to the activities, state variables, and resources in ASPEN. But, when looking into the definitions of how resources are profiled and activities are expanded, one sees code snippets that access various information available during planning for the moment in time being planned to decide at the time what the appropriate profile or expansion is. APGEN is actually a forward (in time) sweeping discrete event simulator, where the model is composed of code snippets that are artfully interleaved by the engine to produce a plan/schedule. To solve this problem, representative code is simulated as a declarative series of task expansions. Predominantly, three types of procedural models were translated: loops, if statements, and code blocks. Loops and if statements were handled using controlled task expansion, and code blocks were handled using constraint networks that maintained the generation of results based on what the order of execution would be for a procedural representation. One advantage with respect to performance for MAPGEN is the use of APGEN s GUI. This GUI is written in C++ and Motif, and performs very well for large plans.

Description: The Mission Data System provides a framework for modeling complex systems in terms of system behaviors and goals that express intent. Complex activity plans can be represented as goal networks that express the coordination of goals on different state variables of the system. Real-time projection extends the ability of this system to verify plan achievability (all goals can be satisfied over the entire plan) into the execution domain so that the system is able to continuously re-verify a plan as it is executed, and as the states of the system change in response to goals and the environment. Previous versions were able to detect and respond to goal violations when they actually occur during execution. This new capability enables the prediction of future goal failures; specifically, goals that were previously found to be achievable but are no longer achievable due to unanticipated faults or environmental conditions. Early detection of such situations enables operators or an autonomous fault response capability to deal with the problem at a point that maximizes the available options. For example, this system has been applied to the problem of managing battery energy on a lunar rover as it is used to explore the Moon. Astronauts drive the rover to waypoints and conduct science observations according to a plan that is scheduled and verified to be achievable with the energy resources available. As the astronauts execute this plan, the system uses this new capability to continuously re-verify the plan as energy is consumed to ensure that the battery will never be depleted below safe levels across the entire plan.

Description: An important aspect of mission planning for NASA s operation of the International Space Station is the allocation and management of space for supplies and equipment. The Stowage, Configuration Analysis, and Operations Planning teams collaborate to perform the bulk of that planning. A Geometric Reasoning Engine is developed in a way that can be shared by the teams to optimize item placement in the context of crew planning. The ISS crew spends (at the time of this writing) a third or more of their time moving supplies and equipment around. Better logistical support and optimized packing could make a significant impact on operational efficiency of the ISS. Currently, computational geometry and motion planning do not focus specifically on the optimized orientation and placement of 3D objects based on multiple distance and containment preferences and constraints. The software performs reasoning about the manipulation of 3D solid models in order to maximize an objective function based on distance. It optimizes for 3D orientation and placement. Spatial placement optimization is a general problem and can be applied to object packing or asset relocation.

Description: In the polar regions of the Moon, some areas within craters are permanently shadowed from solar illumination and can drop to temperatures of 100 K or lower. These sites may serve as cold traps, capturing ice and other volatile compounds, possibly for eons. Interestingly, ice stored in these locations could potentially alter how lunar exploration is conducted. Within craters inside craters (double-shaded craters) that are shaded from thermal re-radiation and from solar illuminated regions, even colder regions should exist and, in many cases, temperatures in these regions never exceed 50 K. Working in these harsh environments with existing conventional systems, exploration or mining activities could be quite daunting and challenging. However, if the unique characteristics of these environments were exploited, the power, weight, and total mass that is required to be carried from the Earth to the Moon for lunar exploration and research would be substantially reduced. In theory, by minimizing the heat transfer between an object and the lunar surface, temperatures near absolute zero can be produced. In a single or double-shaded crater, if the object was isolated from the variety of thermal sources and was allowed to radiatively cool to space, the achievable temperature would be limited by the 3 K cosmic background and the anomalous solar wind that can strike the object being cooled. Our analysis shows that under many circumstances, with some simple thermal radiation shielding, it is possible to establish environments with temperatures of several degrees Kelvin.

Description: Carbon nanotube (CNT)-based sensors for structural health monitoring (SHM) can be embedded in structures of all geometries to monitor conditions both inside and at the surface of the structure to continuously sense changes. These CNTs can be manipulated into specific orientations to create small, powerful, and flexible sensors. One of the sensors is a highly flexible sensor for crack growth detection and strain field mapping that features a very dense and highly ordered array of single-walled CNTs. CNT structural health sensors can be mass-produced, are inexpensive, can be packaged in small sizes (0.5 micron(sup 2)), require less power than electronic or piezoelectric transducers, and produce less waste heat per square centimeter than electronic or piezoelectric transducers. Chemically functionalized lithographic patterns are used to deposit and align the CNTs onto metallic electrodes. This method consistently produces aligned CNTs in the defined locations. Using photo- and electron-beam lithography, simple Cr/Au thin-film circuits are patterned onto oxidized silicon substrates. The samples are then re-patterned with a CNT-attracting, self-assembled monolayer of 3-aminopropyltriethoxysilane (APTES) to delineate the desired CNT locations between electrodes. During the deposition of the solution-suspended single- wall CNTs, the application of an electric field to the metallic contacts causes alignment of the CNTs along the field direction. This innovation is a prime candidate for smart skin technologies with applications ranging from military, to aerospace, to private industry.

Description: By studying the Orbital Express mission, modeling the spacecraft and scenarios, and testing the system, a technique has been developed that uses recursive decomposition to represent procedural actions declaratively, schema-level uncertainty reasoning to make uncertainty reasoning tractable, and lightweight, natural language processing to automatically parse procedures to produce declarative models. Schema-level uncertainty reasoning has, at its core, the basic assumption that certain variables are uncertain, but not independent. Once any are known, then the others become known. This is important where a variable is uncertain for an action and many actions of the same type exist in the plan. For example, if the number of retries to purge pump lines was unknown (but bounded), and each attempt required a sub-plan, then, once the correct number of attempts required for a purge was known, it would likely be the same for all subsequent purges. This greatly reduces the space of plans that needs to be searched to ensure that all executions are feasible. To accommodate changing scenario procedures, each is ingested into a tabular format in temporal order, and a simple natural-language parser is used to read each step and to derive the impact of that step on memory, power, and communications. Then an ASPEN (Activity Scheduling and Planning Environment) model is produced based on this analysis. The model is tested and further changed by hand, if necessary, to reflect the actual procedure. This results in a great savings of time used for modeling procedures. Many processes that need to be modeled in ASPEN (a declarative system) are, in fact, procedural. ASPEN includes the ability to model activities in a hierarchical fashion, but this representation breaks down if there is a practically unbounded number of sub-activities and decomposition topologies. However, if recursive decomposition is allowed, HTN-like encodings are enabled to represent most procedural phenomena. For example, if a switch requires a variable (but known at the time of the attempt) number of attempts to switch on, one can recurse on the number of remaining switch attempts and decompose into either the same switching activity with one less required attempt, or not decompose at all (or decompose into a dummy task), resulting in the end of the decomposition. In fact, any bounded procedural behavior can be modeled using recursive decompositions assuming that the variables impinging the disjunctive decomposition decision are computable at the time that the decision is made. This enables one to represent tasks that are controlled outside of the scheduler, but that the scheduler must accommodate, without requiring one to give a declarative model of the procedural behavior.

Description: The Long Life (Lithium Ion) Battery (LLB/LIB) is designed to replace the current Extravehicular Mobility Unit (EMU) Silver/Zinc (Ag/Zn) Increased Capacity Battery (ICB), which is used to provide power to the Primary Life Support Subsystem (PLSS) during Extravehicular Activities (EVAs). The LLB (a battery based on commercial lithium ion cell technology) is designed to have the same electrical and mechanical interfaces as the current ICB. The EMU LIB Charger is designed to charge, discharge, and condition the LLB either in a charger-strapped configuration or in an EMU-mounted configuration. This paper will retroactively apply the principles of Systems Maturity Assessment to the LLB project through use of the Integration Readiness Level and Earned Readiness Management. The viability of this methodology will be considered for application to new and existing technology development projects.

Description: This paper describes technology to support a new paradigm of space science campaigns. These campaigns enable opportunistic science observations to be autonomously coordinated between multiple spacecraft. Coordinated spacecraft can consist of multiple orbiters, landers, rovers, or other in-situ vehicles (such as an aerobot). In this paradigm, opportunistic science detections can be cued by any of these assets where additional spacecraft are requested to take further observations characterizing the identified event or surface feature. Such coordination will enable a number of science campaigns not possible with present spacecraft technology. Examples from Mars include enabling rapid data collection from multiple craft on dynamic events such as new Mars dark slope streaks, dust-devils or trace gases. Technology to support the identification of opportunistic science events and/or the re-tasking of a spacecraft to take new measurements of the event is already in place on several individual missions such as the Mars Exploration Rover (MER) Mission and the Earth Observing One (EO1) Mission. This technology includes onboard data analysis techniques as well as capabilities for planning and scheduling. This paper describes how these techniques can be cue and coordinate multiple spacecraft in observing the same science event from their different vantage points.