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Crawler Transporter (CT) #2 has been undergoing refurbishment to carry the Space Launch System (SLS). After returning to normal operation, multiple filters of the gear box lubrication system failed/clogged and went on bypass during a test run to the launch pad. Analysis of the filters was done in large part with polarized light microscopy (PLM) to identify the filter contaminates and the source of origin.
A new way of employing hardware redundancy to reduce the number of tests for fault detection in both combinational and synchronous sequential circuits is investigated. An approach is presented for utilizing systematic redundancy to simplify design work. Models for PLM (programmable logic module) and CMM (controllable memory module) are depicted. Systematic design and detection procedures are described. Using these procedures, an easily testable circuit (for stuck faults) can be designed. In contrast to the earlier results on fault detection in logic circuit, two tests are needed to detect any stuck faults of combinational logic circuit. Four tests are necessary and sufficient to detect any stuck faults of elementary logic gates and the malfunction of flip-flops of synchronous sequential circuit using Delay flip-flops or trigger flip-flops.
Included is a set of viewgraphs that present the results of a study conducted at the LaRC Space Station Freedom Office at the request of the Space Station Freedom Level 1 Program Office and the JSC ACRV Project Office to determine the implications of accommodating two Soyuz TM spacecraft as Assured Crew Return Vehicles (ACRV) on the Space Station Freedom (SSF) at the Permanently Crewed Capability (PCC) stage. The study examined operational as well as system issues associated with the accommodation of the Soyuz for several potential configuration options. Operational issues considered include physical hardware clearances, worst case Soyuz departure paths, and impacts to baseline operations such as Pressurized Logistics Module (PLM) exchange, Space Station Remote Manipulator System (SSRMS) attachment, Extravehicular Activity (EVA), and automatic rendezvous and docking (AR&D). Systems impact analysis included determining differences between Soyuz interface requirements and SSF capabilities for the Electrical Power System (EPS), Thermal Control System (TCS), Communications and Tracking (C&T), Audio-Video Subsystem (A/V), Data Management System (DMS), and Environmental Control and Life Support System (ECLSS). Significant findings of this study have indicated that the current AV capability of the Soyuz will need to be increased to provide adequate departure clearances for a worst case escape from an uncontrolled SSF and that an interface element will be required to mate the Soyuz vehicles to station, provide for AR&D structural loads, and to house Soyuz-to-SSF system interfaces.
NASA currently projects ending the ISS mission in approximately 2016, due primarily to the expense of re-boost and re-supply. Lunar outposts are expected to be in place in the same timeframe. In support of these mission goals, a scheme to reuse ISS modules on the moon has been identified. These modules could function as pressurized volumes for human habitation in a lunar vacuum as they have done in low-earth orbit. The ISS hull is structurally capable of withstanding a lunar landing because there is no atmospheric turbulence or friction. A compelling reason to send ISS modules to the moon is their large mass; a large portion of the ISS would survive re-entry if allowed to de-orbit to Earth. ISS debris could pose a serious risk to people or structures on Earth unless a controlled re-entry is performed. If a propulsive unit is devised to be attached to the ISS and control re-entry, a propulsion system could be used to propel the modules to the moon and land them there. ISS modules on the lunar surface would not require re-boost. Radiation protection can be attained by burying the module in lunar regolith. Power and a heat removal system would be required for the lunar modules which would need little support structure other than the lunar surface. With planetary mass surrounding the module, heat flux may be controlled by conductance. The remaining requirement is the re-supply of life-support expendables. There are raw materials on the moon to supplement these vital resources. The lunar maria is known to contain approximately 40% oxygen by mass in inorganic mineral compounds. Chemical conversion of moon rocks to release gaseous oxygen is known science. Recycling and cleaning of air and water are currently planned to be accomplished with ISS Environmental Control & Life Support Systems (ECLSS). By developing a Propulsion and Landing Module (PLM) to dock to the Common Berthing Mechanism (CBM), several identical PLMs could be produced to rescue and transfer the ISS modules to the lunar surface, one by one. The propulsion does not need to be as swift as Apollo, nor would the modules need to be manned during transportation to the moon. The trajectory from low-Earth to lunar orbit would avoid or quickly pass through the Van Allen belts to minimize radiation exposure to electronics onboard. A landing technology similar to Apollo's could be utilized to land an ISS module on the moon. Since the mission will be unmanned, system redundancy could be minimized to keep the cost down. If the mission failed and a module crashed landed on the moon, the risk of debris landing on Earth would be avoided and the raw materials could be used in future lunar missions.
This paper will describe an overview of the Constellation Architecture Team Lunar Scenario 12.0 (LS-12) surface habitation approach and concept performed during the study definition. The Lunar Scenario 12 architecture study focused on two primary habitation approaches: a horizontally-oriented habitation module (LS-12.0) and a vertically-oriented habitation module (LS-12.1). This paper will provide an overview of the 12.0 lunar surface campaign, the associated outpost architecture, habitation functionality, concept description, system integration strategy, mass and power resource estimates. The Scenario 12 architecture resulted from combining three previous scenario attributes from Scenario 4 "Optimized Exploration", Scenario 5 "Fission Surface Power System" and Scenario 8 "Initial Extensive Mobility" into Scenario 12 along with an added emphasis on defining the excursion ConOps while the crew is away from the outpost location. This paper will describe an overview of the CxAT-Lunar Scenario 12.0 habitation concepts and their functionality. The Crew Operations area includes basic crew accommodations such as sleeping, eating, hygiene and stowage. The EVA Operations area includes additional EVA capability beyond the suitlock function such as suit maintenance, spares stowage, and suit stowage. The Logistics Operations area includes the enhanced accommodations for 180 days such as enhanced life support systems hardware, consumable stowage, spares stowage, interconnection to the other habitation elements, a common interface mechanism for future growth, and mating to a pressurized rover or Pressurized Logistics Module (PLM). The Mission & Science Operations area includes enhanced outpost autonomy such as an IVA glove box, life support, medical operations, and exercise equipment.
Two piloted simulations were conducted at NASA's Johnson Space Center using the Cooper-Harper scale to study the handling qualities of the Orion Command Module capsule during atmospheric entry flight. The simulations were conducted using high fidelity 6-DOF simulators for Lunar Return Skip Entry and International Space Station Return Direct Entry flight using bank angle steering commands generated by either the Primary (PredGuid) or Backup (PLM) guidance algorithms. For both evaluations, manual control of bank angle began after descending through Entry Interface into the atmosphere until drogue chutes deployment. Pilots were able to use defined bank management and reversal criteria to accurately track the bank angle commands, and stay within flight performance metrics of landing accuracy, g-loads, and propellant consumption, suggesting that the pilotability of Orion under manual control is both achievable and provides adequate trajectory performance with acceptable levels of pilot effort. Another significant result of these analyses is the applicability of flying a complex entry task under high speed entry flight conditions relevant to the next generation Multi Purpose Crew Vehicle return from Mars and Near Earth Objects.
This report provides results of a Micrometeoroid and Orbital Debris (MMOD) risk assessment of the Mars Sample Return Earth Entry Vehicle (MSR EEV). The assessment was performed using standard risk assessment methodology illustrated in Figure 1-1. Central to the process is the Bumper risk assessment code (Figure 1-2), which calculates the critical penetration risk based on geometry, shielding configurations and flight parameters. The assessment process begins by building a finite element model (FEM) of the spacecraft, which defines the size and shape of the spacecraft as well as the locations of the various shielding configurations. This model is built using the NX I-deas software package from Siemens PLM Software. The FEM is constructed using triangular and quadrilateral elements that define the outer shell of the spacecraft. Bumper-II uses the model file to determine the geometry of the spacecraft for the analysis. The next step of the process is to identify the ballistic limit characteristics for the various shield types. These ballistic limits define the critical size particle that will penetrate a shield at a given impact angle and impact velocity. When the finite element model is built, each individual element is assigned a property identifier (PID) to act as an index for its shielding properties. Using the ballistic limit equations (BLEs) built into the Bumper-II code, the shield characteristics are defined for each and every PID in the model. The final stage of the analysis is to determine the probability of no penetration (PNP) on the spacecraft. This is done using the micrometeoroid and orbital debris environment definitions that are built into the Bumper-II code. These engineering models take into account orbit inclination, altitude, attitude and analysis date in order to predict an impacting particle flux on the spacecraft. Using the geometry and shielding characteristics previously defined for the spacecraft and combining that information with the environment model calculations, the Bumper-II code calculates a probability of no penetration for the spacecraft.
Why tag components differently? - Various methods are in place to tag different components, but not every component is tracked; - Variance in method can make it difficult to obtain component information and identify discrepancies; -Time and resources are spent on component localization and verification. Previous work of RA10 interns: - Researching more efficient asset tracking methods; - Investigating cost effective ways to localize components; - Past interns identified using QR (Quick Response) codes as a potential solution. Link QR codes to Windchill (PLM - Product Lifecycle Management system) DDMS (Design and Data Management System) after QR code is printed/etched and physically tagging it as quickly as possible
Extensive testing with plants for bioregenerative life support systems has been conducted by NASA for nearly 40 years, both through university grants and work at NASA field centers. During this time, numerous meetings were held to develop strategies and roadmaps for implementing bioregenerative life support systems. Findings from several of these meetings are summarized in this report. In nearly all cases, the recommendations included an active ground-based research program and integration tests with other life support subsystems, followed by eventual spaceflight testing. The most recent roadmap of NASA’s Exploration Life Support Crop Element suggests a sequence of first developing a modular vegetable production unit (VPU) to provide perishable foods to supplement the crew’s diet. A similar system could then be used on the lunar surface, with additional modules added as the lunar outpost expands. Eventually, these modules could be transferred to a dedicated pressurized logistics module (PLM) for crop production. Experience from the lunar tests could then be used to conduct a similar buildup for Mars missions, where in situ food production and bioregeneration would be important for achieving outpost autonomy. To date, most trade studies of bioregenerative life support systems indicate that reducing the costs associated with crop lighting systems are key, and use of light-emitting diodes (LEDs) or direct solar lighting offers promising options. Likewise, sustaining high yields and high harvest index (% edible biomass) will be important for minimizing costs, and this can be achieved by optimizing growth environments and through selecting, breeding, and genetically engineering crops suitable for space environments. Collectively, these strategies and roadmaps suggest that a combined approach of fundamental research, hardware (plant chamber) development, and operational testing is required to achieve reliable bioregenerative life support systems.
Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.
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