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: No abstract available

Description: Flight data from an entry, descent, and landing (EDL) sequence can be used to reconstruct the vehicle's trajectory, aerodynamic coefficients and the atmospheric profile experienced by the vehicle. Past Mars missions have contained instruments that do not provide direct measurement of the freestream atmospheric conditions. Thus, the uncertainties in the atmospheric reconstruction and the aerodynamic database knowledge could not be separated. The upcoming Mars Science Laboratory (MSL) will take measurements of the pressure distribution on the aeroshell forebody during entry and will allow freestream atmospheric conditions to be partially observable. This data provides a mean to separate atmospheric and aerodynamic uncertainties and is part of the MSL EDL Instrumentation (MEDLI) project. Methods to estimate the flight performance statistically using on-board measurements are demonstrated here through the use of simulated Mars data. Different statistical estimators are used to demonstrate which estimator best quantifies the uncertainties in the flight parameters. The techniques demonstrated herein are planned for application to the MSL flight dataset after the spacecraft lands on Mars in August 2012.

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: We propose a filter bank consisting of an ordinary current-state extended Kalman filter, and two similar but constrained filters: one is constrained by a null hypothesis that the miss distance between two conjuncting spacecraft is inside their combined hard body radius at the predicted time of closest approach, and one is constrained by an alternative complementary hypothesis. The unconstrained filter is the basis of an initial screening for close approaches of interest. Once the initial screening detects a possibly risky conjunction, the unconstrained filter also governs measurement editing for all three filters, and predicts the time of closest approach. The constrained filters operate only when conjunctions of interest occur. The computed likelihoods of the innovations of the two constrained filters form a ratio for a Wald sequential probability ratio test. The Wald test guides risk mitigation maneuver decisions based on explicit false alarm and missed detection criteria. Since only current-state Kalman filtering is required to compute the innovations for the likelihood ratio, the present approach does not require the mapping of probability density forward to the time of closest approach. Instead, the hard-body constraint manifold is mapped to the filter update time by applying a sigma-point transformation to a projection function. Although many projectors are available, we choose one based on Lambert-style differential correction of the current-state velocity. We have tested our method using a scenario based on the Magnetospheric Multi-Scale mission, scheduled for launch in late 2014. This mission involves formation flight in highly elliptical orbits of four spinning spacecraft equipped with antennas extending 120 meters tip-to-tip. Eccentricities range from 0.82 to 0.91, and close approaches generally occur in the vicinity of perigee, where rapid changes in geometry may occur. Testing the method using two 12,000-case Monte Carlo simulations, we found the method achieved a missed detection rate of 0.1%, and a false alarm rate of 2%.

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: The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) will provide orbit determination and prediction support for the Magnetospheric Multiscale (MMS) mission during the mission's commissioning period. The spacecraft will launch into a highly elliptical Earth orbit in 2015. Starting approximately four days after launch, a series of five large perigee-raising maneuvers will be executed near apogee on a nearly every-other-orbit cadence. This perigee-raise operations concept requires a high-accuracy estimate of the orbital state within one orbit following the maneuver for performance evaluation and a high-accuracy orbit prediction to correctly plan and execute the next maneuver in the sequence. During early mission design, a linear covariance analysis method was used to study orbit determination and prediction accuracy for this perigee-raising campaign. This paper provides a higher fidelity Monte Carlo analysis using the operational COTS extended Kalman filter implementation that was performed to validate the linear covariance analysis estimates and to better characterize orbit determination performance for actively maneuvering spacecraft in a highly elliptical orbit. The study finds that the COTS extended Kalman filter tool converges on accurate definitive orbit solutions quickly, but prediction accuracy through orbits with very low altitude perigees is degraded by the unpredictability of atmospheric density variation.