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Relatively-simple transformer circuit boosts 0-to-5 volt pulses from TTL circuitry to plus or minus 10-volt pulses for transmission over data bus. Also reduces bus voltages to lower voltages required by TTL circuitry. Circuit consists of transformer, two voltage-reference networks, quad differential line receiver, and line driver.
The extensions and enhancements of the fiber optic data bus technology supported by the Space Station Focused Technology Program are discussed. This includes the operating software for the network called the Network Operating System (NOS); gateways and bridges for multiple network topologies; and very large scale topology implimentations to shrink the size and power of the Bus Interface Unit (BIU) down to more manageable dimensions. CMOS is being investigated for the lower speed (parallel) logic. Gallium arsendide is being studied for the high speed (serial) logic.
A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.
Naturally occurring space radiation particles can produce transient and permanent changes in the electrical properties of electronic devices and systems. In this work, the transient radiation effects on DRAM and CMOS SRAM were considered. In addition, the effect of total ionizing dose radiation of the switching times of CMOS logic gates were investigated. Effects of transient radiation on the column and cell of MOS dynamic memory cell was simulated using SPICE. It was found that the critical charge of the bitline was higher than that of the cell. In addition, the critical charge of the combined cell-bitline was found to be dependent on the gate voltage of the access transistor. In addition, the effect of total ionizing dose radiation on the switching times of CMOS logic gate was obtained. The results of this work indicate that, the rise time of CMOS logic gates increases, while the fall time decreases with an increase in total ionizing dose radiation. Also, by increasing the size of the P-channel transistor with respect to that of the N-channel transistor, the propagation delay of CMOS logic gate can be made to decrease with, or be independent of an increase in total ionizing dose radiation. Furthermore, a method was developed for replacing polysilicon feedback resistance of SRAMs with a switched capacitor network. A switched capacitor SRAM was implemented using MOS Technology. The critical change of the switched capacitor SRAM has a very large critical charge. The results of this work indicate that switched capacitor SRAM is a viable alternative to SRAM with polysilicon feedback resistance.
This project was motivated by State-of-the-Art (SOTA) technology that incorporates Network on Chips (NOC) for efficient data communication across the various computer kernels. For example, on the AMD Versal Field Programmable Gate Arrays (FPGA), an NoC has been incorporated for fast data communication from the programmable logic and other computer kernels (processing system, adaptable intelligence engines, etc.). The radiation effects on the legacy technology of this FPGA, such as the programmable logic, are well understood, and established methods exist to measure cross-sections when new families/generations are released; however, newly incorporated technologies, such as the NoC, are not fully understood and could introduce new failure points into the mission space.
The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.
A scenario of relational, hierarchial, and network data bases is presented and a distributed access view integrated data base system (DAVID) is described for uniformly accessing data bases which are heterogeneous and physically distributed. The DAVID system is based on data base logic so that the relational approach is generalized to the heterogeneous approach. The global data manager is explained as are global data manipulation languages which can operate on all the data bases and can query the data dictionary and the data directory.
Application of PLCs to the rocket engine component testing at a new Stennis Space Center Component Test Facility is suggested as an alternative to dedicated specialized computers. The PLC systems are characterized by rugged design, intuitive software, fault tolerance, flexibility, multiple end device options, networking capability, and built-in diagnostics. A distributed PLC-based system is projected to be used for testing LH2/LOx turbopumps required for the ALS/NLS rocket engines.
The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.
The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.
Intelligent systems have been applied to today's problems and could also be applied to space operations integrity. One of these systems is the XMAN tool designed for 'troubleshooting' jet engines. XMAN is the eXpert MAiNtenance tool developed to be an expert information analysis tool which stores trending and diagnostic data on Air Force engines. XMAN operates with a 'network topology' which follows a flow chart containing engine management information reports required by the governments technical order procedures. With XMAN technology, the user is able to identify engine problems by presenting the assertions of the fault isolation logic and attempting to satisfy individual assertions by referring to the databases created by an engine monitoring system. The troubleshooting process requires interaction between the technician and the computer to acquire new evidence form auxiliary maintenance tests corroboration of analytical results to accurately diagnose equipment malfunctions. This same technology will be required for systems which are functioning in space either with an onboard crew, or with an unmanned system. The technology and lessons learned developing this technology while suggesting definite applications for its use with developing space systems are addressed.
Abstract This study introduces the low‐volume core (LVC) fabrication method, which enables the monolithic molding of compact, complex, versatile, and intelligent soft robotic systems. This method uses thin and flexible thermoplastic sheets to mold internal chambers in soft fluidic actuators, valves, and circuits. The LVC fabrication method creates low‐volume networks in soft actuators (LV‐net actuators) that can be made with compact and complex geometries, enabling both low actuation volume input and multi‐degree‐of‐freedom actuators. LVC fabrication can also be used for compact, completely soft, and monolithic logic components (valves with low‐volume core, also called as LV valves) to provide directional resistance as well as a switching mechanism that enables fluidic logic in soft systems. The compatibility of the fabrication methods for both soft actuators and valves facilitates the creation of compact, integrated, and versatile soft robotic systems with embodied intelligence. This study introduces two examples of such intelligent soft robotic systems that integrate both LV‐net actuators and LV valves to demonstrate capability for complex system fabrication.
Numerous planning and scheduling systems employ underlying constraint reasoning systems. Debugging such systems involves the search for errors in model rules, constraint reasoning algorithms, search heuristics, and the problem instance (initial state and goals). In order to effectively find such problems, users must see why each state or action is in a plan by tracking causal chains back to part of the initial problem instance. They must be able to visualize complex relationships among many different entities and distinguish between those entities easily. For example, a variable can be in the scope of several constraints, as well as part of a state or activity in a plan; the activity can arise as a consequence of another activity and a model rule. Finally, they must be able to track each logical inference made during planning. We have developed PlanWorks, a comprehensive system for debugging constraint-based planning and scheduling systems. PlanWorks assumes a strong transaction model of the entire planning process, including adding and removing parts of the constraint network, variable assignment, and constraint propagation. A planner logs all transactions to a relational database that is tailored to support queries for of specialized views to display different forms of data (e.g. constraints, activities, resources, and causal links). PlanWorks was specifically developed for the Extensible Universal Remote Operations Planning Architecture (EUROPA(sub 2)) developed at NASA, but the underlying principles behind PlanWorks make it useful for many constraint-based planning systems. The paper is organized as follows. We first describe some fundamentals of EUROPA(sub 2). We then describe PlanWorks' principal components. We then discuss each component in detail, and then describe inter-component navigation features. We close with a discussion of how PlanWorks is used to find model flaws.
For the first time, a unipolar terminal-attractor based neural associative memory (TABAM)system with adaptive threshold and perfect convergence is presented. By adaptively setting thethreshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors and inner-product approach, we demonstrate via computer simulation the achievement ofperfect convergence and correct retrieval. The simulation is completed with a small number of storedstates (M) and a small number of neurons (N) but a large M/N ratio. An experiment with exclusive-or logic operation using LCTV SLMs is used to show feasibility of the optoelectronic implementationof the models.
Microgrids are now a common practice in distribution systems to increase resilience and reliability. However, microgrid protection remains a critical challenge, considering its requirement to operate in both grid connected and islanded, and the variability in fault characteristics under each mode of operation. This paper presents unbalanced power (S unb ) based fault detection algorithm, which considers local voltage and current unbalances to determine faults in the system. S unb is a computationally efficient fault detection algorithm that is suitable for implementation in the programmable logic of entry level protective relays. In addition, the difference in current and voltage unbalance (D n ) is used to determine the fault type. The proposed method demonstrates high sensitivity and selectivity for line-to-ground (LG), line-to-line (LL), and double line-to-ground (LLG) faults, representing the most common faults in distribution systems. It also allows relay coordination with upstream and downstream protection devices in both island and grid connected operation, while preserving grading margins. The same pickup and time multiplier settings of a particular relay for both modes of operation eliminates the need for adaptive settings, which rely on communication networks. Validation was performed with a hardware-in-the-loop (HIL) setup using Typhoon HIL real time simulator interfaced with three entry-level, SEL 751 relays. Results confirmed the algorithm’s ability to discriminate fault conditions, and determine the fault type under both operating modes, maintain fast detection times, and ensure proper protection coordination.
AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.
Theoretical analysis and some experiments have demonstrated that siliconon- insulator (SOI) 4-gate transistors the type known as G(exp 4)FETs could be efficiently used for in-plane crossing of signal paths. Much of the effort of designing very-large-scale integrated (VLSI) circuits is focused on area-efficient routing of signals. The main source of difficulty in VLSI signal routing is the requirement to prevent crossing, in the same plane, of wires that are meant to be kept electrically insulated from each other. Consequently, it often becomes necessary to design and build VLSI circuits in multiple layers with vias (connections between conductors in different layers at selected locations). Suitable devices that would prevent, or at least sufficiently suppress, undesired electrical coupling (cross-talk) between wires crossing in the same plane would enable compact, simpler implementation complex interconnection networks with in-plane crossings that, heretofore, have not been possible in VLSI circuitry. The use of G4FETs as in-plane signal-crossing devices or routers, in combination with the use of G(exp 4)FETs as universal programmable logic gates, would create opportunities for reducing complexity in VLSI design.
LOTIS is a gamma-ray burst optical counterpart search experiment located near Lawrence Livermore National Laboratory in California. Since operations began in 1996 October, LOTIS has responded to five triggers as of 1997 July 30, which occurred during good weather conditions. GR-B 970223 (BATSE trigger 6100) was an exceptionally strong burst, lasting approx. 30 s with a peak at approx. 8 s. LOTIS began imaging the error box approx. 11 s after the burst began and achieved simultaneous optical coverage of 100% of the region enclosed by the BATSE 3 sigma error circle and the interplanetary network annulus. No optical transients were observed brighter than the m{}_{V} approx.11 completeness limit of the resulting images, providing a new upper limit on the ratio of simultaneous optical to gamma-ray fluence of R-{L) less than 1.1 x 10 logical and {-4} and on the ratio of simultaneous optical (at 700 mn) to gamma-ray (at 100 keV) flux density of R-{F} less than 305 for a B-type spectrum and R-{F} less than 475 for an M-type spectrum.