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At least 343 records · Page 19

Programming methodology for a general purpose automation controller

The General Purpose Automation Controller is a multi-processor architecture for automation programming. A methodology has been developed whose aim is to simplify the task of programming distributed real-time systems for users in research or manufacturing. Programs are built by configuring function blocks (low-level computations) into processes using data flow principles. These processes are activated through the verb mechanism. Verbs are divided into two classes: those which support devices, such as robot joint servos, and those which perform actions on devices, such as motion control. This programming methodology was developed in order to achieve the following goals: (1) specifications for real-time programs which are to a high degree independent of hardware considerations such as processor, bus, and interconnect technology; (2) a component approach to software, so that software required to support new devices and technologies can be integrated by reconfiguring existing building blocks; (3) resistance to error and ease of debugging; and (4) a powerful command language interface.

Sturzenbecker, M. C.↗

YADA: Yet Another Distributed Architecture for Real-Time Robotic Control Systems

This paper presents YADA, a new software architecture for real-time robotic control systems that is minimal, modular, and fully transparent. YADA divides control software into decoupled behavior, user-interface, and hardware-level bus modules. This decoupling at the module level is accomplished by auto-generating human-readable message types that are tailored to the hardware topology oft he current system. These message types provide modules with a common framework for exchanging state information and relaying commands to devices while being agnostic to the communication protocol itself. We also detail how to structure behavior and bus modules to facilitate modularity and flexibility with third party software. YADA has been used with success on several technology development testbeds at JPL, an example of which is given in this paper, and has proven to provide developers a light-weight and highly reconfigurable system for efficient debugging and practical code sharing

Godart, Peter↗

Virtual Sensor Test Instrumentation

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Wang, Roy↗

OOD/OOP experience in the Science Operations Center part of the ground system for X ray Timing Explorer mission

The Science Operations Center (SOC) for the X-ray Timing Explorer (XTE) mission is an important component of the XTE ground system. Its mandate includes: (1) command and telemetry for the three XTE instruments, using CCSDS standards; (2) monitoring of the real-time science operations, reconfiguration of the experiment and the instruments, and real-time commanding to address the targets of opportunity (TOO) and alternate observations; and (3) analysis, processing, and archival of the XTE telemetry, and the timely delivery of the data products to the principal investigator (PI) teams and the guest observers (GO). The SOC has two major components: the science operations facility (SOF) that addresses the first two objectives stated above and the guest observer facility (GOF) that addresses the third. The SOF has subscribed to the object oriented design and implementation; while the GOF uses the traditional approach in order to take advantage of the existing software developed in support of previous missions. This paper details the SOF development using the object oriented design (OOD), and its implementation using the object oriented programming (OOP) in C++ under Unix environment on client-server architecture using Sun workstations. It also illustrates how the object oriented (OO) and the traditional approaches coexist in SOF and GOF, the lessons learned, and how the OOD facilitated the distributed software development collaboratively by four different teams. Details are presented for the SOF system, its major subsystems, its interfaces with the rest of the XTE ground data system, and its design and implementation approaches.

Choudhary, Abdur Rahim↗

Software Testbed for Developing and Evaluating Integrated Autonomous Subsystems

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently under development and not yet sufficiently capable, the ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA's EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to select and sequence actions based on the state of the ADAPT system. Real-time sensor data, commands, and plans are displayed in information-dense arrays of timelines and graphs that zoom and scroll in unison. A dynamic schematic display uses color to show the real-time fault state and utilization of the system components and resources. An execution manager coordinates the activities of the other subsystems. The subsystems are integrated using the Internet Communications Engine (ICE). an object-oriented toolkit for building distributed applications.

Testbed↗

Apollo Lightcraft Project

This second year of the NASA/USRA-sponsored Advanced Aeronautical Design effort focused on systems integration and analysis of the Apollo Lightcraft. This beam-powered, single-stage-to-orbit vehicle is envisioned as the shuttlecraft of the 21st century. The five person vehicle was inspired largely by the Apollo Command Module, then reconfigured to include a new front seat with dual cockpit controls for the pilot and co-pilot, while still retaining the 3-abreast crew accommodations in the rear seat. The gross liftoff mass is 5550 kg, of which 500 kg is the payload and 300 kg is the LH2 propellant. The round trip cost to orbit is projected to be three orders of magnitude lower than the current space shuttle orbiter. The advanced laser-driven 5-speed combined-cycle engine has shiftpoints at Mach 1, 5, 11 and 25+. The Apollo Lightcraft can climb into low Earth orbit in three minutes, or fly to any spot on the globe in less than 45 minutes. Detailed investigations of the Apollo Lightcraft Project this second year further evolved the propulsion system design, while focusing on the following areas: (1) man/machine interface; (2) flight control systems; (3) power beaming system architecture; (4) re-entry aerodynamics; (5) shroud structural dynamics; and (6) optimal trajectory analysis. The principal new findings are documented. Advanced design efforts for the next academic year (1988/1989) will center on a one meter+ diameter spacecraft: the Lightcraft Technology Demonstrator (LTD). Detailed engineering design and analyses, as well as critical proof-of-concept experiments, will be carried out on this small, near-term machine. As presently conceived, the LTD could be constructed using state of the art components derived from existing liquid chemical rocket engine technology, advanced composite materials, and high power laser optics.

Myrabo, Leik N.↗

Low Impact Docking System (LIDS)

Since 1996, NASA has been developing a docking system that will simplify operations and reduce risks associated with mating spacecraft. This effort has focused on developing and testing an original, reconfigurable, active, closed-loop, force-feedback controlled docking system using modern technologies. The primary objective of this effort has been to design a docking interface that is tunable to the unique performance requirements for all types of mating operations (i.e. docking and berthing, autonomous and piloted rendezvous, and in-space assembly of vehicles, modules and structures). The docking system must also support the transfer of crew, cargo, power, fluid, and data. As a result of the past 10 years of docking system advancement, the Low Impact Docking System or LIDS was developed. The current LIDS design incorporates the lessons learned and development experiences from both previous and existing docking systems. LIDS feasibility was established through multiple iterations of prototype hardware development and testing. Benefits of LIDS include safe, low impact mating operations, more effective and flexible mission implementation with an anytime/anywhere mating capability, system level redundancy, and a more affordable and sustainable mission architecture with reduced mission and life cycle costs. In 1996 the LIDS project, then known as the Advanced Docking Berthing System (ADBS) project, launched a four year developmental period. At the end of the four years, the team had built a prototype of the soft-capture hardware and verified the control system that will be used to control the soft-capture system. In 2001, the LIDS team was tasked to work with the X- 38 Crew Return Vehicle (CRV) project and build its first Engineering Development Unit (EDU).

LaBauve, Tobie E.↗

Marsbee - Swarm of Flapping Wing Flyers for Enhanced Mars Exploration: NASA Innovative Advanced Concepts (NIAC) - Phase I: Final Report

Mars exploration has received significant interest from academia, industry, government, and the general public. Despite continued interest, flying on Mars remains challenging, mainly due to the ultra-thin Martian atmospheric density. Although the gravitational acceleration on Mars is 38 percent of Earth's 9.8 meters per second squared, the Martian atmospheric density is only 1.3 percent of the air density on Earth. The aerodynamic forces are proportional to the ambient fluid density. Therefore, flying near the surface of Mars has been considered nearly impossible. The proposed mission architecture (Fig. 1) consists of a Mars rover (already existing) that serves as a mobile base for Marsbees - a deployable swarm of small bio-inspired flapping wing vehicles. In one ConOps scenario, each Marsbee would carry an integrated stereographic video camera and the swarm could construct a 3D topographic map of the local surface for rover path planning. These flying scouts would provide a "third-dimension" to the rover capabilities. In other scenarios, each part of the swarm of Marsbees could carry pressure and temperature sensors for atmospheric sampling, or small spectral analyzers for identification of mineral outcroppings. In each scenario, the rover acts as a recharging and deployment/return station and data and communication hub. Human exploration of Mars is one of the major objectives of NASA and commercial entities such as SpaceX and Boeing. The identified innovations unique to the bio-inspired flapping Marsbee provide viable multi-mode flying mobility for Martian atmospheric and terrain exploration. A swarm of Marsbees provides an enhanced reconfigurable Mars exploration system that is resilient to individual component failures. These Marsbees can carry sensors and wireless communication devices in combination with a Mars rover and helicopters. These enhanced sensing and information gathering abilities can contribute to the following NASA Mars mission objectives: i) "Determine the habitability of an environment", ii) "Obtain surface weather measurements to validate global atmospheric models", and iii) "Prepare for human exploration on Mars." Various commercial entities, e.g. SpaceX and Boeing, are investing in technologies to transport humans to Mars.

Kang, Chang-kwon↗

A Model-based Approach to Reactive Self-Configuring Systems

This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

Williams, Brian C.↗

Integrated System Modeling for Nuclear Thermal Propulsion (NTP)

Nuclear thermal propulsion (NTP) has long been identified as a key enabling technology for space exploration beyond LEO. From Wernher Von Braun's early concepts for crewed missions to the Moon and Mars to the current Mars Design Reference Architecture (DRA) 5.0 and recent lunar and asteroid mission studies, the high thrust and specific impulse of NTP opens up possibilities such as reusability that are just not feasible with competing approaches. Although NTP technology was proven in the Rover / NERVA projects in the early days of the space program, an integrated spacecraft using NTP has never been developed. Such a spacecraft presents a challenging multidisciplinary systems integration problem. The disciplines that must come together include not only nuclear propulsion and power, but also thermal management, power, structures, orbital dynamics, etc. Some of this integration logic was incorporated into a vehicle sizing code developed at NASA's Glenn Research Center (GRC) in the early 1990s called MOMMA, and later into an Excel-based tool called SIZER. Recently, a team at GRC has developed an open source framework for solving Multidisciplinary Design, Analysis and Optimization (MDAO) problems called OpenMDAO. A modeling approach is presented that builds on previous work in NTP vehicle sizing and mission analysis by making use of the OpenMDAO framework to enable modular and reconfigurable representations of various NTP vehicle configurations and mission scenarios. This approach is currently applied to vehicle sizing, but is extensible to optimization of vehicle and mission designs. The key features of the code will be discussed and examples of NTP transfer vehicles and candidate missions will be presented.

Systems Engineering↗

Protocol for Communication Networking for Formation Flying

An application-layer protocol and a network architecture have been proposed for data communications among multiple autonomous spacecraft that are required to fly in a precise formation in order to perform scientific observations. The protocol could also be applied to other autonomous vehicles operating in formation, including robotic aircraft, robotic land vehicles, and robotic underwater vehicles. A group of spacecraft or other vehicles to which the protocol applies could be characterized as a precision-formation- flying (PFF) network, and each vehicle could be characterized as a node in the PFF network. In order to support precise formation flying, it would be necessary to establish a corresponding communication network, through which the vehicles could exchange position and orientation data and formation-control commands. The communication network must enable communication during early phases of a mission, when little positional knowledge is available. Particularly during early mission phases, the distances among vehicles may be so large that communication could be achieved only by relaying across multiple links. The large distances and need for omnidirectional coverage would limit communication links to operation at low bandwidth during these mission phases. Once the vehicles were in formation and distances were shorter, the communication network would be required to provide high-bandwidth, low-jitter service to support tight formation-control loops. The proposed protocol and architecture, intended to satisfy the aforementioned and other requirements, are based on a standard layered-reference-model concept. The proposed application protocol would be used in conjunction with conventional network, data-link, and physical-layer protocols. The proposed protocol includes the ubiquitous Institute of Electrical and Electronics Engineers (IEEE) 802.11 medium access control (MAC) protocol to be used in the datalink layer. In addition to its widespread and proven use in diverse local-area networks, this protocol offers both (1) a random- access mode needed for the early PFF deployment phase and (2) a time-bounded-services mode needed during PFF-maintenance operations. Switching between these two modes could be controlled by upper-layer entities using standard link-management mechanisms. Because the early deployment phase of a PFF mission can be expected to involve multihop relaying to achieve network connectivity (see figure), the proposed protocol includes the open shortest path first (OSPF) network protocol that is commonly used in the Internet. Each spacecraft in a PFF network would be in one of seven distinct states as the mission evolved from initial deployment, through coarse formation, and into precise formation. Reconfiguration of the formation to perform different scientific observations would also cause state changes among the network nodes. The application protocol provides for recognition and tracking of the seven states for each node and for protocol changes under specified conditions to adapt the network and satisfy communication requirements associated with the current PFF mission phase. Except during early deployment, when peer-to-peer random access discovery methods would be used, the application protocol provides for operation in a centralized manner.

Jennings, Esther↗

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

A Comparison Between Orion Automated and Space Shuttle Rendezvous Techniques

The Orion spacecraft will replace the space shuttle and will be the first human spacecraft since the Apollo program to leave low earth orbit. This vehicle will serve as the cornerstone of a complete space transportation system with a myriad of mission requirements necessitating rendezvous to multiple vehicles in earth orbit, around the moon and eventually beyond . These goals will require a complex and robust vehicle that is, significantly different from both the space shuttle and the command module of the Apollo program. Historically, orbit operations have been accomplished with heavy reliance on ground support and manual crew reconfiguration and monitoring. One major difference with Orion is that automation will be incorporated as a key element of the man-vehicle system. The automated system will consist of software devoted to transitioning between events based on a master timeline. This effectively adds a layer of high level sequencing that moves control of the vehicle from one phase to the next. This type of automated control is not entirely new to spacecraft since the shuttle uses a version of this during ascent and entry operations. During shuttle orbit operations however many of the software modes and hardware switches must be manually configured through the use of printed procedures and instructions voiced from the ground. The goal of the automation scheme on Orion is to extend high level automation to all flight phases. The move towards automation represents a large shift from current space shuttle operations, and so these new systems will be adopted gradually via various safeguards. These include features such as authority-to-proceed, manual down modes, and functional inhibits. This paper describes the contrast between the manual and ground approach of the space shuttle and the proposed automation of the Orion vehicle. I will introduce typical orbit operations that are common to all rendezvous missions and go on to describe the current Orion automation architecture and contrast it with shuttle rendezvous techniques and circumstances. The shuttle rendezvous profile is timed to take approximately 3 days from orbit insertion to docking at the International Space Station (ISS). This process can be divided into 3 phases: far-field, mid-field and proximity operations. The far-field stage is characterized as the most quiescent phase. The spacecraft is usually too far to navigate using relative sensors and uses the Inertial Measurement Units (IMU s) to numerically solve for its position. The maneuvers are infrequent, roughly twice per day, and are larger than other burns in the profile. The shuttle uses this opportunity to take extensive ground based radar updates and keep high fidelity orbit states on the ground. This state is then periodically uplinked to the shuttle computers. The targeting solutions for burn maneuvers are also computed on the ground and uplinked. During the burn the crew is responsible for setting the shuttle attitude and configuring the propulsion system for ignition. Again this entire process is manually driven by both crew and ground activity. The only automatic processes that occur are associated with the real-time execution of the burn. The Orion automated functionality will seek to relieve the workload of both the crew and ground during this phase

Ruiz, Jose O,↗

NASA Tech Briefs, December 2009

Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design.

Source record↗

Modular, Adaptive, Reconfigurable Systems: Technology for Sustainable, Reliable, Effective, and Affordable Space Exploration

In order to execute the Vision for Space Exploration, we must find ways to reduce cost, system complexity, design, build, and test times, and at the same time increase flexibility to satisfy multiple functions. Modular, Adaptive, Reconfigurable System (MARS) technologies promise to set the stage for the delivery of system elements that form the building blocks of increasingly ambitious missions involving humans and robots. Today, space systems are largely specialized and built on a case-by-case basis. The notion of modularity however, is nothing new to NASA. The 1970's saw the development of the Multi-Mission Modular spacecraft (MMS). From 1980 to 1992 at least six satellites were built under this paradigm, and included such Goddard Space Flight Center missions as SSM, EUVE, UARS, and Landsat 4 and 5. Earlier versions consisted of standard subsystem "module" or "box" components that could be replaced within a structure based on predefined form factors. Although the primary motivation for MMS was faster/cheaper integration and test, standardization of interfaces, and ease of incorporating new subsystem technology, it lacked the technology maturity and programmatic "upgrade infrastructure" needed to satisfy varied mission requirements, and ultimately it lacked user buy-in. Consequently, it never evolved and was phased out. Such concepts as the Rapid Spacecraft Development Office (RSDO) with its regularly updated catalogue of prequalified busses became the preferred method for acquiring satellites. Notwithstanding, over the past 30 years since MMS inception, technology has advanced considerably and now modularity can be extended beyond the traditional MMS module or box to cover levels of integration, from the chip, card, box, subsystem, to the space system and to the system-of-systems. This paper will present the MARS architecture, cast within the historical context of MMS. Its application will be highlighted by comparing a state-of-the-art point design vs. a MARS-enabled lunar mission, as a representative robotic case design.

Esper, Jaime↗

Science Capabilities of the Common Habitat

The Common Habitat is the primary habitable element in a conceptual architecture feasibility study for long-duration space exploration with an eight-person crew size. On lunar or planetary surfaces, the Common Habitat forms the core of a Surface Base Camp. In microgravity, the Common Habitat is the core of the Deep Space Exploration Vehicle (DSEV), an in-space transportation spacecraft. The Common Habitat employs a horizontal orientation that is divided internally into a lower deck, mid deck, and upper deck, roughly separating outfitting into individual, work, and group functions. On a planetary surface, the habitat is incorporated into a base camp, located near the south pole in the case of the Moon. The Mars base camp is currently location agnostic. Each base camp is divided into habitation, landing, resource production, and power zones. In microgravity, the habitat is incorporated into the Deep Space Exploration Vehicle, a vessel capable of transporting the crew within the inner solar system. In addition to crew and teleoperated control of external science assets, the Common Habitat employs a suite of life and physical science laboratory systems to enable it to support science investigations across a variety of destination environments, primarily featuring the Moon and Mars, along with the intervening interplanetary space. Other potential destinations include Near Earth Asteroids and Venus and Earth orbits. Located in the aft starboard section of the Common Habitat mid deck, the life science laboratory supports primarily biology and human research. In its baseline configuration, the laboratory includes horizontal work surfaces, freezers, multiple gloveboxes, sample transfer/exposure capability, large instruments, and reconfigurable ISPR-compatible payload bays. The Medical Care Facility and exercise facility can also support life science research. In the aft port section of the mid deck, the physical science laboratory supports physics, chemistry, materials science, geology, and remote sensing (including astrophysics, heliophysics, Earth science, planetary science, and meteorology). It provides a baseline of similar ISPR-compatible payload bays and adds additional freezers, including those for cryogenic sample storage, a remote sensing workstation, more gloveboxes, also with sample transfer/exposure, combustion chambers, fluid mechanics chambers, and a gas chromatograph. It leverages the Command & Control Center for teleoperations of mobile science assets. Both laboratories are highly modular, with the ability to swap out both payloads and instruments on an as-needed basis. The integrated science outfitting of the Common Habitat positions its crew to contribute to all of NASA’s Moon to Mars science objectives and extend human understanding into the inner solar system.

Lunar Suface↗