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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Smart and Intelligent Sensors

John C. Stennis Space Center (SSC) provides rocket engine propulsion testing for NASA's space programs. Since the development of the Space Shuttle, every Space Shuttle Main Engine (SSME) has undergone acceptance testing at SSC before going to Kennedy Space Center (KSC) for integration into the Space Shuttle. The SSME is a large cryogenic rocket engine that uses Liquid Hydrogen (LH2) as the fuel. As NASA moves to the new ARES V launch system, the main engines on the new vehicle, as well as the upper stage engine, are currently base lined to be cryogenic rocket engines that will also use LH2. The main rocket engines for the ARES V will be larger than the SSME, while the upper stage engine will be approximately half that size. As a result, significant quantities of hydrogen will be required during the development, testing, and operation of these rocket engines.Better approaches are needed to simplify sensor integration and help reduce life-cycle costs. 1.Smarter sensors. Sensor integration should be a matter of "plug-and-play" making sensors easier to add to a system. Sensors that implement new standards can help address this problem; for example, IEEE STD 1451.4 defines transducer electronic data sheet (TEDS) templates for commonly used sensors such as bridge elements and thermocouples. When a 1451.4 compliant smart sensor is connected to a system that can read the TEDS memory, all information needed to configure the data acquisition system can be uploaded. This reduces the amount of labor required and helps minimize configuration errors. 2.Intelligent sensors. Data received from a sensor be scaled, linearized; and converted to engineering units. Methods to reduce sensor processing overhead at the application node are needed. Smart sensors using low-cost microprocessors with integral data acquisition and communication support offer the means to add these capabilities. Once a processor is embedded, other features can be added; for example, intelligent sensors can make a health assessment to inform the data acquisition client when sensor performance is suspect. 3.Distributed sample synchronization. Networks of sensors require new ways for synchronizing samples. Standards that address the distributed timing problem (for example, IEEE STD 1588) provide the means to aggregate samples from many distributed smart sensors with sub-microsecond accuracy. 4. Reduction in interconnect. Alternative means are needed to reduce the frequent problems associated with cabling and connectors. Wireless technologies offer the promise of reducing interconnects and simultaneously making it easy to quickly add a sensor to a system.

Lansaw, John↗

Expert system decision support for low-cost launch vehicle operations

Progress in assessing the feasibility, benefits, and risks associated with AI expert systems applied to low cost expendable launch vehicle systems is described. Part one identified potential application areas in vehicle operations and on-board functions, assessed measures of cost benefit, and identified key technologies to aid in the implementation of decision support systems in this environment. Part two of the program began the development of prototypes to demonstrate real-time vehicle checkout with controller and diagnostic/analysis intelligent systems and to gather true measures of cost savings vs. conventional software, verification and validation requirements, and maintainability improvement. The main objective of the expert advanced development projects was to provide a robust intelligent system for control/analysis that must be performed within a specified real-time window in order to meet the demands of the given application. The efforts to develop the two prototypes are described. Prime emphasis was on a controller expert system to show real-time performance in a cryogenic propellant loading application and safety validation implementation of this system experimentally, using commercial-off-the-shelf software tools and object oriented programming techniques. This smart ground support equipment prototype is based in C with imbedded expert system rules written in the CLIPS protocol. The relational database, ORACLE, provides non-real-time data support. The second demonstration develops the vehicle/ground intelligent automation concept, from phase one, to show cooperation between multiple expert systems. This automated test conductor (ATC) prototype utilizes a knowledge-bus approach for intelligent information processing by use of virtual sensors and blackboards to solve complex problems. It incorporates distributed processing of real-time data and object-oriented techniques for command, configuration control, and auto-code generation.

Szatkowski, G. P.↗

Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

Mehr, Ali Farhang↗

SpaceCube Version 1.5

SpaceCube 1.5 is a high-performance and low-power system in a compact form factor. It is a hybrid processing system consisting of CPU (central processing unit), FPGA (field-programmable gate array), and DSP (digital signal processor) processing elements. The primary processing engine is the Virtex- 5 FX100T FPGA, which has two embedded processors. The SpaceCube 1.5 System was a bridge to the SpaceCube 2.0 and SpaceCube 2.0 Mini processing systems. The SpaceCube 1.5 system was the primary avionics in the successful SMART (Small Rocket/Spacecraft Technology) Sounding Rocket mission that was launched in the summer of 2011. For SMART and similar missions, an avionics processor is required that is reconfigurable, has high processing capability, has multi-gigabit interfaces, is low power, and comes in a rugged/compact form factor. The original SpaceCube 1.0 met a number of the criteria, but did not possess the multi-gigabit interfaces that were required and is a higher-cost system. The SpaceCube 1.5 was designed with those mission requirements in mind. The SpaceCube 1.5 features one Xilinx Virtex-5 FX100T FPGA and has excellent size, weight, and power characteristics [4×4×3 in. (approx. = 10×10×8 cm), 3 lb (approx. = 1.4 kg), and 5 to 15 W depending on the application]. The estimated computing power of the two PowerPC 440s in the Virtex-5 FPGA is 1100 DMIPS each. The SpaceCube 1.5 includes two Gigabit Ethernet (1 Gbps) interfaces as well as two SATA-I/II interfaces (1.5 to 3.0 Gbps) for recording to data drives. The SpaceCube 1.5 also features DDR2 SDRAM (double data rate synchronous dynamic random access memory); 4- Gbit Flash for storing application code for the CPU, FPGA, and DSP processing elements; and a Xilinx Platform Flash XL to store FPGA configuration files or application code. The system also incorporates a 12 bit analog to digital converter with the ability to read 32 discrete analog sensor inputs. The SpaceCube 1.5 design also has a built-in accelerometer. In addition, the system has 12 receive and transmit RS- 422 interfaces for legacy support. The SpaceCube 1.5 processor card represents the first NASA Goddard design in a compact form factor featuring the Xilinx Virtex- 5. The SpaceCube 1.5 incorporates backward compatibility with the Space- Cube 1.0 form factor and stackable architecture. It also makes use of low-cost commercial parts, but is designed for operation in harsh environments.

Geist, Alessandro↗

Intelligent Wireless Sensor Networks for System Health Monitoring

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of PAN configuration, providing the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the WSN is reconfigured. The session will present the architecture and technical feasibility of creating fault-tolerant WSNs for aerospace applications based on our application of the technology to a Structural Health Monitoring testbed. The interim results of WSN development and testing including our software architecture for intelligent sensor management will be discussed in the context of the specific tradeoffs required for effective use. Initial certification measurement techniques and test results gauging WSN susceptibility to Radio Frequency interference are introduced as key challenges for technology adoption. A candidate Developmental and Flight Instrumentation implementation using intelligent sensor networks for wind tunnel and flight tests is developed as a guide to understanding key aspects of the aerospace vehicle design, test and operations life cycle.

networks↗

Printable Spacecraft: Flexible Electronic Platforms for NASA Missions

Atmospheric confetti. Inchworm crawlers. Blankets of ground penetrating radar. These are some of the unique mission concepts which could be enabled by a printable spacecraft. Printed electronics technology offers enormous potential to transform the way NASA builds spacecraft. A printed spacecraft's low mass, volume and cost offer dramatic potential impacts to many missions. Network missions could increase from a few discrete measurements to tens of thousands of platforms improving areal density and system reliability. Printed platforms could be added to any prime mission as a low-cost, minimum resource secondary payload to augment the science return. For a small fraction of the mass and cost of a traditional lander, a Europa flagship mission might carry experimental printed surface platforms. An Enceladus Explorer could carry feather-light printed platforms to release into volcanic plumes to measure composition and impact energies. The ability to print circuits directly onto a variety of surfaces, opens the possibility of multi-functional structures and membranes such as "smart" solar sails and balloons. The inherent flexibility of a printed platform allows for in-situ re-configurability for aerodynamic control or mobility. Engineering telemetry of wheel/soil interactions are possible with a conformal printed sensor tape fit around a rover wheel. Environmental time history within a sample return canister could be recorded with a printed sensor array that fits flush to the interior of the canister. Phase One of the NIAC task entitled "Printable Spacecraft" investigated the viability of printed electronics technologies for creating multi-functional spacecraft platforms. Mission concepts and architectures that could be enhanced or enabled with this technology were explored. This final report captures the results and conclusions of the Phase One study. First, the report presents the approach taken in conducting the study and a mapping of results against the proposed Phase One objectives. Then an overview of the general field of printed electronics is provided, including manufacturing approaches, commercial drivers, and the current state of integrated systems. The bulk of the report contains the results and findings of Phase One organized into four sections: a survey of components required for a printable spacecraft, technology roadmaps considerations, science mission and engineering applications, and potential risks and challenges of the technology.

Spacecraft↗