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Automated self-contained portable device can be used by technicians with minimal training. Data acquired from patient at remote site are transmitted to centralized interpretation center using conventional telephone equipment. There, diagnostic information is analyzed, and results are relayed back to remote site.
Basic requirements for a ground test facility simulating low density hypersonic flows are discussed. Such facilities should be able to produce shock velocities in the range of 10-17 km/sec in an initial pressure of 0.010 to 0.050 Torr. The facility should be equipped with diagnostics systems to be able to measure the emitted radiation, characteristic temperatures and populations in various energy levels. In the light of these requirements, NASA Ames's electric arc-driven low density shock tube facility is described and available experimental diagnostics systems and computational tools are discussed.
Maintenance practices have long focused on time based "preventive maintenance" techniques. Components were changed out and parts replaced based on how long they had been in place instead of what condition they were in. A reliability centered maintenance (RCM) program seeks to offer equal or greater reliability at decreased cost by insuring only applicable, effective maintenance is performed and by in large part replacing time based maintenance with condition based maintenance. A significant portion of this program involved introducing non-intrusive technologies, such as vibration analysis, oil analysis and I/R cameras, to an existing labor force and management team.
Space Life Sciences Directorate (SLSD) specializes in transitioning technology and knowledge to medical operations. This activity encompasses funding a spectrum of research and technology efforts, such as understanding fundamental biological mechanisms altered by microgravity and executing technology watches for state of the art diagnostic imaging equipment. This broad spectrum approach to fulfilling the need to protect crewmember health and performance during long and short duration missions to the International Space Station, moon and Mars is made possible by having a line of site between research and operations. Currently, SLSD's line of site is articulated in a transition to medical practice (TMP) process. This process is designed to shepherd information and knowledge gained through fundamental and mechanistic research toward the development of an operational solution such as a pre-flight selection criteria; an in-flight countermeasure, monitoring capability or treatment; or a post-flight reconditioning program. The TMP process is also designed to assist with the customization of mature hardware or technology for NASA specific use. The benefits of this process are that the concept of operational usability is interjected early in the research, design, or acquisition phase, and stakeholders are involved early to identify requirements and also periodically asked to assess requirements compliance of research or technology development project. Currently a device known as the actiwatch is being assessed for the final transition to operational use. Specific examples of research to operations transition success help to illustrate the process and bolster communication between the research and medical operations communities.
Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.
To fulfill the increasing needs of diagnostic support for researchers in plasma technology, a portable diagnostic package (PDP) equipped for both laser Thomson scattering (TS) and optical emission spectroscopy has been designed and constructed at Oak Ridge National Laboratory (ORNL), aiming to measure the temperature and number density of electrons and temperatures of ions in plasma devices. The PDP has been initially implemented on a high density and low temperature electrothermal arc source (ET-arc) at ORNL to test its TS capability. TS from the plasmas in the ET-arc has been obtained using the PDP. The electron temperature and number density were determined from TS spectra. These results were then compared to measurements from previous studies on the ET-arc. The TS diagnostic measured 0.8 ± 0.1, 1.3 ± 0.2, and 0.7 ± 0.1 eV and (4.4 ± 0.5) × 1021, (5.9 ± 0.7) × 1021, and (4.3 ± 0.5) x 1021 m-3, respectively, from three lines of sight that transect the plasma column.
An objective method and apparatus for noise control and acoustic diagnostics of motorcar engines are reported. The method and apparatus let us know whether the noisiness of the vehicle under test exceeds the admissible threshold levels given by appropriate standards and if so what is the main source of the excessive noise. The method consists in measuring both the overall noise level and the sound pressure levels in definite frequency bands while the engine speed is controlled as well and may be fixed at prescribed values. Whenever the individually adjusted threshold level has been exceeded in any frequency band, a self-sustaining control signal is sent.
NASA's Constellation Program for Exploration of the Moon and Mars places human crews in extreme isolation in resource scarce environments. Near Earth, the discontinuation of Space Shuttle flights after 2010 will alter the up- and down-mass capacity for the International Space Station (ISS). NASA is considering new options for logistics support strategies for future missions. Aerospace systems are often composed of replaceable modular blocks that minimize the need for complex service operations in the field. Such a strategy however, implies a robust and responsive logistics infrastructure with relatively low transportation costs. The modular Orbital Replacement Units (ORU) used for ISS requires relatively large blocks of replacement hardware even though the actual failed component may really be three orders of magnitude smaller. The ability to perform in-situ repair of electronics circuits at the component level can dramatically reduce the scale of spares and related logistics cost. This ability also reduces mission risk, increases crew independence and improves the overall supportability of the program. The Component-Level Electronics Assembly Repair (CLEAR) task under the NASA Supportability program was established to demonstrate the practicality of repair by first investigating widely used soldering materials and processes (M&P) performed by modest manual means. The work will result in program guidelines for performing manual repairs along with design guidance for circuit reparability. The next phase of CLEAR recognizes that manual repair has its limitations and some highly integrated devices are extremely difficult to handle and demand semi-automated equipment. Further, electronics repairs require a broad range of diagnostic capability to isolate the faulty components. Finally repairs must pass functional tests to determine that the repairs are successful and the circuit can be returned to service. To prevent equipment demands from exceeding spacecraft volume capacity and skill demands from exceeding crew time and training limits, the CLEAR project is examining options provided by non-real time tele-operations, robotics, and a new generation of diagnostic equipment. This paper outlines a strategy to create an effective repair environment where, with the support of ground based engineers, crewmembers can diagnose, repair and test flight electronics in-situ. This paper also discusses the implications of successful tele-robotic repairs when expanded to rework and reconfiguration of used flight assets for building Constellation infrastructure elements.
Heating, ventilation, and air-conditioning (HVAC) systems can develop faults due to poor installation practices or gradual wear and tear, leading to decreased HVAC system’s efficiency, compromised thermal comfort, and shortened equipment lifespan (EERE, 2018). Automated fault detection and diagnosis (AFDD) technologies offer a solution by identifying energy-wasting HVAC faults, such as inadequate indoor airflow and incorrect refrigerant charge, and guiding technicians to enhance system efficiency. In the realm of residential HVAC, AFDD can be implemented through various fault detection and diagnosis capabilities, sensor configurations, and target applications. These technologies typically fall into three categories: smart diagnostic tools, original equipment manufacturer (OEM)-embedded tools, and add-on tools. Smart diagnostic tools employ temporarily installed sensors to directly measure HVAC system characteristics, while OEM-embedded tools utilize factory-installed sensors to identify faults or assess system performance. However, both these types of AFDD technologies are often only accessible for high-end HVAC equipment or require additional sensor installation by qualified technicians, resulting in high investment costs and limited applicability for low-income residential buildings. On the other hand, add-on tools rely solely on data from smart thermostats and meters to detect faults by continuously analyzing equipment runtime or energy usage. As smart thermostat and meter costs decrease and their prevalence increases, these tools can be readily deployed in low-income residential buildings. However, they possess limited capabilities as they rely solely on basic trend analysis. Enhancing such tools with advanced machine learning algorithms can significantly improve their effectiveness.
Diagnostician(TM)-on-Chip (DOC) technology identifies faults and commands systems reconfiguration. Smart microcontrollers operating in conjunction with other system-control circuits, command self-correcting system/equipment actions in real time. DOC microcontroller generates commands for associated built-in test equipment to stimulate unit of equipment diagnosed, collects and processes response data obtained by built-in test equipment, and performs diagnostic reasoning on response data, using diagnostic knowledge base derived from design data.
A fielded expert system automates equipment fault isolation and recommends corrective maintenance action for Air Force jet engines. The knowledge based diagnostics tool was developed as an expert system interface to the Comprehensive Engine Management System, Increment IV (CEMS IV), the standard Air Force base level maintenance decision support system. XMAM (trademark), the Expert Maintenance Tool, automates procedures for troubleshooting equipment faults, provides a facility for interactive user training, and fits within a diagnostics information feedback loop to improve the troubleshooting and equipment maintenance processes. The application of expert diagnostics to the Air Force A-10A aircraft TF-34 engine equipped with the Turbine Engine Monitoring System (TEMS) is presented.
This document captures the system architecture for a Component-Level Electronic-Assembly Repair (CLEAR) capability needed for electronics maintenance and repair of the Constellation Program (CxP). CLEAR is intended to improve flight system supportability and reduce the mass of spares required to maintain the electronics of human rated spacecraft on long duration missions. By necessity it allows the crew to make repairs that would otherwise be performed by Earth based repair depots. Because of practical knowledge and skill limitations of small spaceflight crews they must be augmented by Earth based support crews and automated repair equipment. This system architecture covers the complete system from ground-user to flight hardware and flight crew and defines an Earth segment and a Space segment. The Earth Segment involves database management, operational planning, and remote equipment programming and validation processes. The Space Segment involves the automated diagnostic, test and repair equipment required for a complete repair process. This document defines three major subsystems including, tele-operations that links the flight hardware to ground support, highly reconfigurable diagnostics and test instruments, and a CLEAR Repair Apparatus that automates the physical repair process.
Neutral gas analysis, the measurement and evaluation of total and partial pressures, is a key technique to study the impact of neutral gas dynamics on retention, recycling and release processes of fuel or impurity species in fusion devices. At JET, the experiment closest to ITER in terms of operating parameters and size, various detectors and techniques for partial pressure and total pressure measurements are deployed together to characterise neutral gas dynamics during and after plasma operation on various toroidal and poloidal locations. An extensive modification of JET's sub-divertor neutral gas diagnostic system aims at retaining and extending established measurement capabilities in the forthcoming Deuterium-Tritium (DT) experiments (DTE2). To achieve DT compatibility, a separation of radiation-sensitive electronics from the sensor and adequate radiation shielding is required, as well as utilisation of a DT compatible differential pumping system with adjustable throughput to account for the strong pressure variation in the sub-divertor region. Finally, the sub-divertor neutral gas diagnostic will be equipped with multiple Residual Gas Analysers (RGAs), utilising quadrupole mass spectrometry and electrostatic ion-trap-principles, all operating with remote electronics located behind the biological radiation shield. These RGAs will record data in a fast selected discrete mass mode during plasma pulses (cycle ~2 s) and will automatically switch back to continuous data recording (cycle ~100 s) afterwards. They will be complemented by a newly improved Penning gauge spectroscopy configuration in particular supporting the He and D 2 separation relevant for DT operation. The distance between these devices and their associated control unit is typically 15m . A newly developed RGA with a cable length of 80 m, compatible with the ITER environment, will also be employed for the first time. Finally, this set-up and its operation in DTE2 will provide vital input to the development of the ITER divertor RGA in the most relevant environment currently available.
The prototypical α → ω phase transition in zirconium is an ideal test bed for our understanding of polymorphism under extreme loading conditions. After half a century of study, a consensus had emerged that the transition is realized via one of two distinct displacive mechanisms, depending on the nature of the compression path. However, recent dynamic-compression experiments equipped with diffraction diagnostics performed in the past few years have revealed new transition mechanisms, demonstrating that our understanding of the underlying atomistic dynamics and transition kinetics is in fact far from complete. We present classical molecular dynamics simulations of the α → ω phase transition in single-crystal zirconium shock compressed along the [0001] axis using a machine-learning-class potential. The transition is predicted to proceed primarily via a modified version of the two-stage Usikov-Zilberstein mechanism, whereby the high-pressure ω phase heterogeneously nucleates at boundaries between grains of an intermediate β phase. We further observe the fomentation of atomistic disorder at the junctions between β grains, leading to the formation of highly defective interstitial material between the ω grains. We directly compare synthetic x-ray diffraction patterns generated from our simulations with those obtained using femtosecond diffraction in recent dynamic-compression experiments, and show that the simulations produce the same unique, anisotropic diffuse scattering signal unlike any previously seen from an elemental metal. Our simulations suggest that the diffuse signal arises from a combination of thermal diffuse scattering, nanoparticlelike scattering from residual kinetically stabilized α and β grains, and scattering from interstitial defective structures. Published by the American Physical Society 2024
Abstract Background Numerous medical resource demand models have been created as tools for governments or hospitals, aiming to predict the need for crucial resources like ventilators, hospital beds, personal protective equipment (PPE), and diagnostic kits during crises such as the COVID-19 pandemic. However, the reliability of these demand models remains uncertain. Methods Demand models typically consist of two main components: hospital use epidemiological models that predict hospitalizations or daily admissions, and a demand calculator that translates the outputs of the epidemiological model into predictions for resource usage. We conducted separate analyses to evaluate each of these components. In the first analysis, we validated various hospital use epidemiological models using a recent validation framework designed for epidemiological models. This allowed us to quantify the accuracy of the models in predicting critical aspects such as the date and magnitude of local COVID-19 peaks, among other factors. In the second analysis, we evaluated a range of demand calculators for ventilators, medical gowns, and COVID-19 test kits. To achieve this, we decoupled these demand calculators from the underlying epidemiological models and provided ground truth data for their inputs. This approach enabled a direct comparison of the demand calculators, comparing them against each other and actual usage data when available. The code is available athttps://doi.org/10.5281/zenodo.13712387. Results Performance varied greatly across the epidemiological models, with greater variability in COVID-19 hospital use predictions than for COVID-19 deaths as analyzed previously. Some models did not have any peaks. Among those that did, the models under-estimated date of peak approximately as often as they over-estimated, but were more likely to under-estimate magnitude of peak, with typical relative errors around 50%. Regarding demand calculator predictions, there was significant variability, including five-fold differences in predictions for gown models. Validation against actual or surrogate usage data illustrated the potential value of demand models while demonstrating their limitations. Conclusions The emerging field of demand modeling holds promise in averting medical resource shortages during future public health emergencies. However, achieving this potential necessitates focused efforts on standardization, transparency, and rigorous model validation before placing reliance on demand models in critical public health decision-making.
NASA's Zero-g aircraft, operated by the Johnson Space Center, provides the unique weightless or zero-g environment of space flight for hardware development and test and astronaut training purposes. The program, which began in 1959, uses a slightly modified Boeing KC-135A aircraft, flying a parabolic trajectory, to produce weightless periods of 20 to 25 seconds. The program has supported the Mercury, Gemini, Apollo, Skylab, Apollo-Soyuz and Shuttle programs as well as a number of unmanned space operations. Typical experiments for flight in the aircraft have included materials processing experiments, welding, fluid manipulation, cryogenics, propellant tankage, satellite deployment dynamics, planetary sciences research, crew training with weightless indoctrination, space suits, tethers, etc., and medical studies including vestibular research. The facility is available to microgravity research organizations on a cost-reimbursable basis, providing a large, hands-on test area for diagnostic and support equipment for the Principal Investigators and providing an iterative-type design approach to microgravity experiment development. The facility allows concepts to be proven and baseline experimentation to be accomplished relatively inexpensively prior to committing to the large expense of a space flight.
This article describes the need and the strategy for CFD model development, validation, and verification for Cryogenic Fluid Management (CFM) of Propellant Tanks in Space. It describes the type of CFD models that must be developed to address the future needs of Space CFM. It also discusses the two classes of experiments currently used to validate the fidelity of the CFD models. These two experiment classes are: (a) the small-scale simulant fluid science experiments that are equipped with scientific diagnostics to elucidate the underlying two-phase fluid physics of the CFM processes; and (b) the large-scale cryogenic experiments that assess the engineering performance of the propellant tank for storage and transfer. The current status of the CFD model development and validation is briefly assessed by presenting examples of segregated two-phase flow problems that have been successfully modeled. The future model development directions for CFM situations involving more complex interpenetrating phases are also defined.
Increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircrafts are being addressed through the concept of Intelligent Propulsion Systems. These systems are potentially enabled through increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control, and distributed control with smart sensors and actuators. The focus of this report is on "On-Board Intelligence", and the discussions are limited to the overall engine gas-path performance perspective. The emphasis throughout the report is on identifying the sensor and actuator needs to realize these intelligent engine concepts and identifying the current sensor and actuator technologies and roadmaps for emerging technologies. The report is of interest both to the "Customers" to understand the investment needs and the "Researchers" and "Technology Developers" to understand the technology needs for closing the gap from current sensor and actuator capabilities to future performance and universal requirements and targets.