Spot-size Enlargement due to Pulsed-Power Fault Modes: II. Injector Faults [Slides]
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A fault injector system, called an in-circuit injector, was designed and developed to facilitate fault injection experiments performed at NASA-Langley's Avionics Integration Research Lab (AIRLAB). The in-circuit fault injector (ICFI) allows fault injections to be performed on electronic systems without special test features, e.g., sockets. The system supports stuck-at-zero, stuck-at-one, and transient fault models. The ICFI system is interfaced to a VAX-11/750 minicomputer. An interface program has been developed in the VAX. The computer code required to access the interface program is presented. Also presented is the connection procedure to be followed to connect the ICFI system to a circuit under test and the ICFI front panel controls which allow manual control of fault injections.
We have investigated injector faults with numerical experiments. For this investigation we used the nominal tune that is also being used to assess beam stability. Beam spill in the DST due to a serious injector fault was evaluated using the LSP slice algorithm. Only the most serious fault investigated (-350 keV) caused beam spill in the DST. DST transport focusing solenoids limit the beam spill. Beam spill in the DST is the result of large halo caused by betatron oscillations of the mismatched beam. Bremsstrahlung radiation from the DST beam spill was estimated from Tom Martin scaling normalized to DARHT-I. In conclusion, Scorpius is reasonably safe from beam spill radiation in the DST due to injector faults.
To enable effective management, planning, and operations for future missions that involve a crewed space habitat, operational support must be migrated from Earth to the habitat. Intelligent System Health Management technologies (ISHM) promise to enable the future space habitats to increase the safety and mission success while minimizing operational risks. In this paper, Water Recycling System (WRS) deployed at NASA Ames Research Center's Sustainability Base is used for verification and validation of the proposed solution. Our work includes the development of the WRS simulation model based on its dynamic physical characteristics and the design of Automatic Contingency Management (ACM) framework that integrates fault diagnosis and optimization. In WRS modeling, a nominal model with fault injectors is developed. Fault detection and isolation techniques are then developed for isolating causes and identifying the severity of the faults. Dynamic Programming (DP) based fault mitigation strategies are designed to accommodate the faults in the system. A series of simulations are presented with different fault modes and the results indicate that the proposed ACM system can alleviate the fault in the WRS optimally regarding energy consumption and effects of the fault.
The objective of the AIPS program is to achieve a validated fault tolerant distributed computer system. The goals of the AIPS fault injection study were: (1) to present the fault injection study components addressing the AIPS validation objective; (2) to obtain feedback for fault removal from the design implementation; (3) to obtain statistical data regarding fault detection, isolation, and reconfiguration responses; and (4) to obtain data regarding the effects of faults on system performance. The parameters are described that must be varied to create a comprehensive set of fault injection tests, the subset of test cases selected, the test case measurements, and the test case execution. Both pin level hardware faults using a hardware fault injector and software injected memory mutations were used to test the system. An overview is provided of the hardware fault injector and the associated software used to carry out the experiments. Detailed specifications are given of fault and test results for the I/O Network and the AIPS Fault Tolerant Processor, respectively. The results are summarized and conclusions are given.
Automated test capability for extensive low-level hardware fault insertion testing is developed. The test capability is used to calibrate fault detection coverage and associated latency times as relevant to projecting overall system reliability. Described are modifications made to the NASA Ames Reconfigurable Flight Control System (RDFCS) Facility to fully automate the total test loop involving the Draper Laboratories' Fault Injector Unit. The automated capability provided included the application of sequences of simulated low-level hardware faults, the precise measurement of fault latency times, the identification of fault symptoms, and bulk storage of test case results. A PDP-11/60 served as a test coordinator, and a PDP-11/04 as an instrumentation device. The fault injector was controlled by applications test software in the PDP-11/60, rather than by manual commands from a terminal keyboard. The time base was especially developed for this application to use a variety of signal sources in the system simulator.
This paper describes FTAPE (Fault Tolerance And Performance Evaluator), a tool that can be used to compare fault-tolerant computers. The major parts of the tool include a system-wide fault-injector, a workload generator, and a workload activity measurement tool. The workload creates high stress conditions on the machine. Using stress-based injection, the fault injector is able to utilize knowledge of the workload activity to ensure a high level of fault propagation. The errors/fault ratio, performance degradation, and number of system crashes are presented as measures of fault tolerance.
The authors demonstrate the need to address fault latency in highly reliable real-time control computer systems. It is noted that the effectiveness of all known recovery mechanisms is greatly reduced in the presence of multiple latent faults. The presence of multiple latent faults increases the possibility of multiple errors, which could result in coverage failure. The authors present experimental evidence indicating that the duration of fault latency is dependent on workload. A synthetic workload generator is used to vary the workload, and a hardware fault injector is applied to inject transient faults of varying durations. This method makes it possible to derive the distribution of fault latency duration. Experimental results obtained from the fault-tolerant multiprocessor at the NASA Airlab are presented and discussed.
This thesis studies the relationship by creating a tool (FTAPE) that integrates a high stress workload generator with fault injection and by using the tool to evaluate system performance under error conditions. The workloads are comprised of processes which are formed from atomic components that represent CPU, memory, and I/O activity. The fault injector is software-implemented and is capable of injecting any memory addressable location, including special registers and caches. This tool has been used to study a Tandem Integrity S2 Computer. Workloads with varying numbers of processes and varying compositions of CPU, memory, and I/O activity are first characterized in terms of performance. Then faults are injected into these workloads. The results show that as the number of concurrent processes increases, the mean fault latency initially increases due to increased contention for the CPU. However, for even higher numbers of processes (less than 3 processes), the mean latency decreases because long latency faults are paged out before they can be activated.
Fault tolerance is an efficient approach adopted to avoid or reduce the damage of a system failure. In this work we present the results of a fault injection campaign we conducted on the Duplex Framework (DF). The DF is a software developed by the UCLA group [1, 2] that uses a fault tolerant approach and allows to run two replicas of the same process on two different nodes of a commercial off-the-shelf (COTS) computer cluster. A third process running on a different node, constantly monitors the results computed by the two replicas, and eventually restarts the two replica processes if an inconsistency in their computation is detected. This approach is very cost efficient and can be adopted to control processes on spacecrafts where the fault rate produced by cosmic rays is not very high.
We use machine-learning and cross-correlation techniques to enhance earthquake detectability by two magnitude units for the earthquake sequence near Musreau Lake, Alberta, which is induced by wastewater disposal. This deep catalogue reveals a series of en echelon ~N–S oriented strike-slip faults that are favourably oriented for reactivation. These faults require only ~0.6 MPa overpressure for triggering to occur. Earthquake activity occurs in bursts, or episodes; episodes restricted to the largest fault tend to have earthquakes starting near the southern end (distant from injectors) and progressing northwards (towards the injectors). While most events are concentrated along these ~N–S oriented faults, we also delineate smaller faults. Together, these findings suggest pore pressure as the triggering mechanism, where a time-dependent increase in pore pressure likely caused these faults to progressively reawaken. Analysis of the ‘next record-breaking event’, a statistical model that forecasts the sequencing of earthquake magnitudes, suggests that the next largest event would be M L ~4.3. The seismically illuminated length of the largest fault indicates potential magnitudes as large as M w 5.3.
In June 2018 the team embarked on an ambitious project to address the slow development pace of Alaska’s 20+ billion barrels heavy oil resource via the first ever polymer flood pilot. Following the successful commencement of the pilot in August 2018, the field demonstration, supporting laboratory experiments and numerical simulation have steadily progressed. A significant amount of valuable data and lessons learned have been collected, and are reported in this paper. The ongoing pilot and the research activities is making headway toward the primary objective of validating the use of polymer flooding for extracting heavy oil in Alaska’s challenging environment. The pilot is conducted in two pre-existing pairs of horizontal injectors and producers in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field. A customized polymer blending and pumping unit injects HPAM polymer at a concentration of 1,750 ppm to achieve a target viscosity of 45 cP. Supporting coreflood laboratory experiments have focused on quantification of polymer retention in the rock, and effect of injection water salinity, polymer, and their combinations on oil recovery. The injection and production response of the pilot flood pattern is utilized to develop a history matched reservoir simulation model for forecasting oil recovery beyond the pilot. Finally, specially designed laboratory experiments address anticipated operating concerns regarding post-polymer breakthrough such as oil-water separation efficiency and polymer induced fouling of heater tubes. Polymer has been injected continuously since startup except for two short equipment modification shutdowns, and more recently a prolonged disruption due to polymer hydration issues at the J-pad field site. Cumulatively, over 600,000 lbs. of polymer has been injected, corresponding to ~7%PV. The two producers show significant decrease in the water cut, gradually increasing oil rate, and no polymer breakthrough. Two main observations from the coreflood are a significant uncertainty in polymer retention values, and positive oil recovery response to low salinity water (2,600 mg/liter TDS). The heterogeneity in the flood pattern presents some challenges in obtaining a robust history matched simulation model. Experimental results on produced fluids treatment indicate the formation of a dense polymer deposit, at certain conditions, on heating tubes that can negatively impact the heat transfer efficiency. The scientific knowledge, including the lessons learned during unanticipated shutdowns, quality control, logistics and field data that is being acquired from this effort has referential value for other planned EOR projects. Finally, by all indications, the polymer field pilot is steadily progressing toward achieving the ultimate goal of unlocking the massive heavy oil resources on Alaska North Slope (ANS).
A fault insertion device (FID) comprises a transceiver and an FPGA. The transceiver receives signals from a MIL-STD-1553/1760 communications bus. The FPGA evaluates the signals received from the communications bus against a set of rules stored by the FPGA. Based upon the set of rules, the FPGA can selectively modify messages received from the communications bus prior to transmission to a remote terminal or a bus controller that is configured to communicate on the communications bus.
This paper focuses on the application of expert systems technology to the automatic detection, verification and correction of anomalous rocket engine operations through interfacing with an intelligent adaptive control system. The design of a reliable and intelligent propulsion control and monitoring system is outlined which includes the architecture of an Integrated Expert System (IES) serving as the core component. The IES functions include automatic knowledge acquisition, integrated knowledge base, and fault diagnosis and prediction methodology. The results of fault analysis and diagnostic techniques are presented for an example fault in the SSME main combustion chamber injectors.
RadiaSoft and Jefferson Laboratory are working together to develop a machine-learning-based smart alarm system for the CEBAF injector. Because of the injector’s large number of parameters and possible fault scenarios, it is highly desirable to have an autonomous alarm system that can quickly identify and diagnose unusual machine states. We present our work on artificial neural networks designed to identify such undesirable machine states. In particular, we test both auto-encoders and inverse models as possible tools for differentiating between normal and abnormal states. These models are being developed using both supervised and unsupervised learning techniques, and are being trained using CEBAF injector data collected during dedicated machine studies as well as during regular operations. Lastly, we discuss tradeoffs between the two types of models.
We present initial results from a proof-of-concept ?smart alarm? for the CEBAF injector. Because of the injector's large number of parameters and possible fault scenarios, it is highly desirable to have an autonomous alarm system that can quickly identify and diagnose unusual machine states. Our approach leverages a trained neural network to not only identify an anomalous machine state, but also to identify the root-cause by pinpointing the specific element or region responsible. We developed an inverse model trained on data collected during normal operations. Using the inverse model, measurements from the machine are used to compute machine settings, which are then compared to EPICS setpoints. Instances when predictions differ from EPICS setpoints by a user-defined threshold are flagged as anomalies, and the user is alerted to the issue. We present the results of our data collection efforts, model training and performance, and initial performance metrics.
This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Cognac oil field J Sand, in the field’s Northeast fault block, using a line drive pattern design (one CO 2 injector and two production wells), for 10-year and 20-year injection scenarios. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.
Historically, cryogenic rocket engines have not been used for in-space applications due to their additional complexity, the mission need for high reliability, and the challenges of propellant boil-off. While the mission and vehicle architectures are not yet defined for the lunar and Martian robotic and human exploration objectives, cryogenic rocket engines offer the potential for higher performance and greater architecture/mission flexibility. In-situ cryogenic propellant production could enable a more robust exploration program by significantly reducing the propellant mass delivered to low earth orbit, thus warranting the evaluation of cryogenic rocket engines versus the hypergolic bi-propellant engines used in the Apollo program. A multi-use engine. one which can provide the functionality that separate engines provided in the Apollo mission architecture, is desirable for lunar and Mars exploration missions because it increases overall architecture effectiveness through commonality and modularity. The engine requirement derivation process must address each unique mission application and each unique phase within each mission. The resulting requirements, such as thrust level, performance, packaging, bum duration, number of operations; required impulses for each trajectory phase; operation after extended space or surface exposure; availability for inspection and maintenance; throttle range for planetary descent, ascent, acceleration limits and many more must be addressed. Within engine system studies, the system and component technology, capability, and risks must be evaluated and a balance between the appropriate amount of technology-push and technology-pull must be addressed. This paper will summarize many of the key technology challenges associated with using high-performance cryogenic liquid propellant rocket engine systems and components in the exploration program architectures. The paper is divided into two areas. The first area describes how the mission requirements affect the engine system requirements and create system level technology challenges. An engine system architecture for multiple applications or a family of engines based upon a set of core technologies, design, and fabrication approaches may reduce overall programmatic cost and risk. The engine system discussion will also address the characterization of engine cycle figures of merit, configurations, and design approaches for some in-space vehicle alternatives under consideration. The second area evaluates the component-level technology challenges induced from the system requirements. Component technology issues are discussed addressing injector, thrust chamber, ignition system, turbopump assembly, and valve design for the challenging requirements of high reliability, robustness, fault tolerance, deep throttling, reasonable performance (with respect to weight and specific impulse).