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Redundant command lines use two different "true" signals to avoid common failure modes. When function is required to operate, computer generates command and transmits it to demultiplexer, where it is split along two paths, producing outputs from separate electronic cards. Outputs combine to drive AND gate high and begin function.
The Space Shuttle Program (SSP) has a zero-fault-tolerant design related to an inadvertent firing of the primary reaction control jets on the Orbiter during mated operations with the International Space Station (ISS). Failure modes identified by the program as a wire-to-wire "smart" short or a Darlington transistor short resulting in a failed-on primary thruster during mated operations with ISS can drive forces that exceed the structural capabilities of the docked Shuttle/ISS structure. The assessment team delivered 17 observations, 6 findings and 15 recommendations to the Space Shuttle Program.
In support of future deep space manned missions, an autonomous/automated vehicle, providing crew autonomy and an autonomous response planning system, will be required due to the light time delays in communication. Vehicle capabilities as a whole must provide for tactical response to vehicle system failures and space environmental effects induced failures, for risk mitigation of permanent loss of communication with Earth, and for assured crew return capabilities. The complexity of human rated space systems and the limited crew sizes and crew skills mix drive the need for a robust autonomous capability on-board the vehicle. The HAL 9000 Space Operating System[2] designed for such missions and space craft includes the first distributed real-time planning / re-planning system. This paper will detail the software architecture of the multiple planning engine system, and the interface design for plan changes, approval and implementation that is performed autonomously. Operations scenarios will be defined for analysis of the planning engines operations and its requirements for nominal / off nominal activities. An assessment of the distributed realtime re-planning system, in the defined operations environment, will be provided as well as findings as it pertains to the vehicle, crew, and mission control requirements needed for implementation.
Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.
Vibration tests were performed on the tile/strain-isolator-pad system used as thermal protection for the space shuttle orbiter. Experimental data on normal and in-plane vibration response and damping properties are presented. Three test specimens exhibited shear type motion during failures that occurred in the tile near the tile/strain-isolator-pad bond-line. A dynamic instability is described which has large in-plane motion at a frequency one-half that of the nominal driving frequency. Analysis shows that this phenomenon is a parametric response.
Studies of neuronal dysfunction in the central nervous system (CNS) are frequently limited by the failure of primary neurons to propagate in vitro. Neuronal cell lines can be substituted for primary cells but they often misrepresent normal conditions. We hypothesized that a dimensional (3-D) cell culture system would drive the phenotype of transformed neurons closer to that of untransformed cells. In our studies comparing 3-D versus 2-dimensional (2-D) culture, neuronal SH-SY5Y (SY) cells underwent distinct morphological changes combined with a significant drop in their rate of cell division. Expression of the proto-oncogene N-myc and the RNA binding protein HuD was decreased in 3-D culture as compared to standard 2-D conditions. We observed a decline in the anti-apoptotic protein Bcl-2 in 3-D culture, coupled with increased expression of the pro-apoptotic proteins Bax and Bak. Moreover, thapsigargin (TG)-induced apoptosis was enhanced in the 3-D cells. Microarray analysis demonstrated significantly differing mRNA levels for over 700 genes in the cells of each culture type. These results indicate that a 3-D culture approach narrows the phenotypic gap between neuronal cell lines and primary neurons. The resulting cells may readily be used for in vitro research of neuronal pathogenesis.
A Weibull analysis was performed of the strength distribution and size effects for 2000 specimens of H-451 nuclear-grade graphite. The data, generated elsewhere, measured the tensile and four-point-flexure room-temperature rupture strength of specimens excised from a single extruded graphite log. Strength variation was compared with specimen location, size, and orientation relative to the parent body. In our study, data were progressively and extensively pooled into larger data sets to discriminate overall trends from local variations and to investigate the strength distribution. The CARES/Life and WeibPar codes were used to investigate issues regarding the size effect, Weibull parameter consistency, and nonlinear stress-strain response. Overall, the Weibull distribution described the behavior of the pooled data very well. However, the issue regarding the smaller-than-expected size effect remained. This exercise illustrated that a conservative approach using a two-parameter Weibull distribution is best for designing graphite components with low probability of failure for the in-core structures in the proposed Generation IV (Gen IV) high-temperature gas-cooled nuclear reactors. This exercise also demonstrated the continuing need to better understand the mechanisms driving stochastic strength response. Extensive appendixes are provided with this report to show all aspects of the rupture data and analytical results.
It is important that engineering and management accept the need for an availability requirement that is derived with its influencing attributes. It is the intent of this paper to provide the visibility of relationships of these major attribute drivers (variables) to each other and the resultant system inherent availability. Also important to provide bounds of the variables providing engineering the insight required to control the system's engineering solution, e.g., these influencing attributes become design requirements also. These variables will drive the need to provide integration of similar discipline functions or technology selection to allow control of the total parts count. The relationship of selecting a reliability requirement will place a constraint on parts count to achieve a given availability requirement or if allowed to increase the parts count will drive the system reliability requirement higher. They also provide the understanding for the relationship of mean repair time (or mean down time) to maintainability, e.g., accessibility for repair, and both the mean time between failure, e.g., reliability of hardware and availability. The concerns and importance of achieving a strong availability requirement is driven by the need for affordability, the choice of using the two launch solution for the single space application, or the need to control the spare parts count needed to support the long stay in either orbit or on the surface of the moon. Understanding the requirements before starting the architectural design concept will avoid considerable time and money required to iterate the design to meet the redesign and assessment process required to achieve the results required of the customer's space transportation system. In fact the impact to the schedule to being able to deliver the system that meets the customer's needs, goals, and objectives may cause the customer to compromise his desired operational goal and objectives resulting in considerable increased life cycle cost of the fielded space transportation system.
It is important that engineering and management accept the need for an availability requirement that is derived with its influencing attributes. It is the intent of this paper to provide the visibility of relationships of these major attribute drivers (variables) to each other and the resultant system inherent availability. Also important to provide bounds of the variables providing engineering the insight required to control the system's engineering solution, e.g., these influencing attributes become design requirements also. These variables will drive the need to provide integration of similar discipline functions or technology selection to allow control of the total parts count. The relationship of selecting a reliability requirement will place a constraint on parts count to achieve a given availability requirement or if allowed to increase the parts count will drive the system reliability requirement higher. They also provide the understanding for the relationship of mean repair time (or mean down time) to maintainability, e.g., accessibility for repair, and both the mean time between failure, e.g., reliability of hardware and availability. The concerns and importance of achieving a strong availability requirement is driven by the need for affordability, the choice of using the two launch solution for the single space application, or the need to control the spare parts count needed to support the long stay in either orbit or on the surface of the moon. Understanding the requirements before starting the architectural design concept will avoid considerable time and money required to iterate the design to meet the redesign and assessment process required to achieve the results required of the customer's space transportation system. In fact the impact to the schedule to being able to deliver the system that meets the customer's needs, goals, and objectives may cause the customer to compromise his desired operational goal and objectives resulting in considerable increased life cycle cost of the fielded space transportation system.
It is important that engineering and management accept the need for an availability requirement that is derived with its influencing attributes. It is the intent of this paper to provide the visibility of relationships of these major attribute drivers (variables) to each other and the resultant system inherent availability. Also important to provide bounds of the variables providing engineering the insight required to control the system's engineering solution, e.g., these influencing attributes become design requirements also. These variables will drive the need to provide integration of similar discipline functions or technology selection to allow control of the total parts count. The relationship of selecting a reliability requirement will place a constraint on parts count to achieve a given availability requirement or if allowed to increase the parts count will drive the system reliability requirement higher. They also provide the understanding for the relationship of mean repair time (or mean down time) to maintainability, e.g., accessibility for repair, and both the mean time between failure, e.g., reliability of hardware and availability. The concerns and importance of achieving a strong availability requirement is driven by the need for affordability, the choice of using the two launch solution for the single space application, or the need to control the spare parts count needed to support the long stay in either orbit or on the surface of the moon. Understanding the requirements before starting the architectural design concept will avoid considerable time and money required to iterate the design to meet the redesign and assessment process required to achieve the results required of the customer's space transportation system. In fact the impact to the schedule to being able to deliver the system that meets the customer's needs, goals, and objectives may cause the customer to compromise his desired operational goal and objectives resulting in considerable increased life cycle cost of the fielded space transportation system.
High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by -64% but overestimates nitrate by +36%. The largest underestimate in sulfate occurs during the pollution event, where models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 25% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.
Future space transportation architectures and designs must be affordable. Consequently, their Life Cycle Cost (LCC) must be controlled. For the LCC to be controlled, it is necessary to identify all the requirements and elements of the architecture at the beginning of the concept phase. Controlling LCC requires the establishment of the major operational cost drivers. Two of these major cost drivers are reliability and maintainability, in other words, the system's availability (responsiveness). Potential reasons that may drive the inherent availability requirement are the need to control the number of unique parts and the spare parts required to support the transportation system's operation. For more typical space transportation systems used to place satellites in space, the productivity of the system will drive the launch cost. This system productivity is the resultant output of the system availability. Availability is equal to the mean uptime divided by the sum of the mean uptime plus the mean downtime. Since many operational factors cannot be projected early in the definition phase, the focus will be on inherent availability which is equal to the mean time between a failure (MTBF) divided by the MTBF plus the mean time to repair (MTTR) the system. The MTBF is a function of reliability or the expected frequency of failures. When the system experiences failures the result is added operational flow time, parts consumption, and increased labor with an impact to responsiveness resulting in increased LCC. The other function of availability is the MTTR, or maintainability. In other words, how accessible is the failed hardware that requires replacement and what operational functions are required before and after change-out to make the system operable. This paper will describe how the MTTR can be equated to additional labor, additional operational flow time, and additional structural access capability, all of which drive up the LCC. A methodology will be presented that provides the decision makers with the understanding necessary to place constraints on the design definition. This methodology for the major drivers will determine the inherent availability, safety, reliability, maintainability, and the life cycle cost of the fielded system. This methodology will focus on the achievement of an affordable, responsive space transportation system. It is the intent of this paper to not only provide the visibility of the relationships of these major attribute drivers (variables) to each other and the resultant system inherent availability, but also to provide the capability to bound the variables, thus providing the insight required to control the system's engineering solution. An example of this visibility is the need to provide integration of similar discipline functions to allow control of the total parts count of the space transportation system. Also, selecting a reliability requirement will place a constraint on parts count to achieve a given inherent availability requirement, or require accepting a larger parts count with the resulting higher individual part reliability requirements. This paper will provide an understanding of the relationship of mean repair time (mean downtime) to maintainability (accessibility for repair), and both mean time between failure (reliability of hardware) and the system inherent availability.
The microstructural characteristics and morphology of interfaces in metals can be crucial in governing the initiation of plasticity and early deformation mechanisms under extreme conditions. During high-strain-rate deformation, these interfaces significantly affect dislocation nucleation, twinning, and other mechanisms that directly impact material strength and failure. Despite their importance, a substantial knowledge gap remains between the observed macroscopic material behavior and the underlying role of bimetal interfaces in plasticity initiation. Here, to address this gap, large-scale molecular dynamics simulations are performed on Al/Ti bimetal structures to examine the effect of interface characteristics on the onset of plasticity under uniaxial compression. Specifically, this study investigates how interface roughness (flat vs waveform interfaces) modifies the initiation of plastic events in the microstructure. Atomistic simulations indicate that interface roughness (a microscopic behavior) reduces the stress required for dislocation nucleation, thereby reducing the peak stress relative to a flat interface. For the square interface, the step height strongly influences plasticity initiation by setting the separation of locally flat regions. Varying the interface rotation relative to the loading direction (macroscopic behavior) reveals that the peak stress for both flat and waveform interfaces initially decreases and then increases with rotation, accompanied by a shift in dominant mechanisms—from Al twinning (flat) to interface sliding and Ti-dominated phase transformation and twinning at lower angles. The change in the stress-strain slope during initial compression reflects how rotation alters the resolved shear stress and activates different slip systems. Overall, the study provides valuable insights into the role of bimetal interfaces in controlling plasticity initiation and early deformation pathways for Al/Ti under extreme loading conditions.
Comparative lubrication tests were run with OH-58A helicopter tail rotor drive shaft bearings. The tests were run in an outdoor environment with ambient temperatures ranging from 10 to 75 F. Dust was periodically applied to the bearings to simulate field conditions. The cause of bearing failure was associated with dust penetration. Rotor shaft failure was found to be caused by the shaft rotating in the standard rubber collar due to seizure of the bearings. Bearings with a positive rubbing seal having a MIL-G-81322 grease produced lives greater than with bearings having labyrinth seals and a mineral oil paste lubricant. An elongated collar prevented failure of the rotor shaft during bearing seizure. In a limited test, installation of tail boom shrouds over the bearings which excluded dust and water resulted in bearing lives in excess of 1800 hours or 1200 hours greater than the current 600 hours TBO, regardless of the lubricant-bearing combination used.
Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models–specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.
Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models--specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.
Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose some critical challenges. While AVs may help reduce crashes caused by human error, they still may experience failures of technologies and sensing, as well as decision-making errors in a mixed traffic environment. A disengagement refers to an AV transitioning control from autonomous systems to the trained test driver. The safety critical nature of disengagements makes it imperative to analyze disengagements and crashes together. In this study, we analyze both crashes and disengagements from real-world AV driving in California to fill the knowledge gap regarding the relationship between disengagements and crashes in a mixed traffic environment. A nested logit model was calibrated using three different outcomes: (1) disengagement with a crash, (2) disengagement with no crash, and (3) no disengagement with a crash. Furthermore, endogenous switching regime models were also calibrated to draw distinctions between the relation of disengagements and crashes while accounting for endogeneity effects. The results show that factors related to AV systems (such as software failures) and other roadway participants increase the propensity of a disengagement without a crash. Furthermore, AVs were observed to disengage less often as the technology matured over time. Marginal effects revealed an 8% decrease. The results thus suggest that disengagements are a part of AVs' safe performance and disengagement alerts may need to be triggered in order to avoid certain failures with current technology.
Depleted uranium (DU) hohlraums are utilized for indirect drive fusion experiments at Lawrence Livermore National Laboratory. The production process for DU hohlraums is intricate, involving complex sputtering, machining, and leaching techniques. Achieving low-stress and defect-free hohlraums presents significant challenges. Recent failures have revealed that some uranium flakes, known as slivers, detach from the diagnostic windows and fall onto the capsule. These catastrophic failures were observed only after target assembly, leading to the hypothesis that oxidation of the DU by glue vapor might be the cause. A study investigating the impact of glue vapor on DU hohlraums found that spallation occurred in three out of seven sample hohlraums after three weeks. The slivers observed in these samples were consistent with those seen in assembled targets. This marks the first experimental reproduction of such catastrophic slivering failures. Consequently, future studies can now focus on sliver mitigation and the precise diagnosis of the failure mode.