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Artificial fog serves as volume-projection medium for display of three-dimensional image. Projection technique enables display of images for variety of purposes, possibly including entertainment, indoor and outdoor advertising, medical diagnostics and image representations for surgical procedures, and education.
Concepts of an autonomous and automated space-compliant diagnostic system were developed for conditioned-based maintenance (CBM) of rocket motors for space exploration vehicles. The diagnostic system will provide real-time information on the integrity of critical structures on launch vehicles, improve their performance, and greatly increase crew safety while decreasing inspection costs. Using the SMART Layer technology as a basis, detailed procedures and calibration techniques for implementation of the diagnostic system were developed. The diagnostic system is a distributed system, which consists of a sensor network, local data loggers, and a host central processor. The system detects external impact to the structure. The major functions of the system include an estimate of impact location, estimate of impact force at impacted location, and estimate of the structure damage at impacted location. This system consists of a large-area sensor network, dedicated multiple local data loggers with signal processing and data analysis software to allow for real-time, in situ monitoring, and longterm tracking of structural integrity of solid rocket motors. Specifically, the system could provide easy installation of large sensor networks, onboard operation under harsh environments and loading, inspection of inaccessible areas without disassembly, detection of impact events and impact damage in real-time, and monitoring of a large area with local data processing to reduce wiring.
Real-time identification of tissue would improve procedures such as stereotactic brain biopsy (SBX), functional and implantation neurosurgery, and brain tumor excision. To standard SBX equipment has been added: (1) computer-controlled stepper motors to drive the biopsy needle/probe precisely; (2) multiple microprobes to track tissue density, detect blood vessels and changes in blood flow, and distinguish the various tissues being penetrated; (3) neural net learning programs to allow real-time comparisons of current data with a normative data bank; (4) three-dimensional graphic displays to follow the probe as it traverses brain tissue. The probe can differentiate substances such as pig brain, differing consistencies of the 'brain-like' foodstuff tofu, and gels made to simulate brain, as well as detect blood vessels imbedded in these substances. Multimodality probes should improve the safety, efficacy, and diagnostic accuracy of SBX and other neurosurgical procedures.
CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.
BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.
The radiated power distribution is a crucial aspect of heat transport, heat load mitigation, and plasma exhaust performance. An imaging video bolometer camera has been installed to measure the plasma radiated power in the divertor region of the Wendelstein 7-X (W7-X) stellarator. This diagnostic offers a wide-angle (40° × 68°) sampling of the plasma volume in both the poloidal and toroidal directions. The field-of-view is covered with a large number (> 500) of bolometer channels, providing imaging capability. The diagnostic design is introduced here together with its data analysis procedure. A set of laboratory experiments is performed to assess the thermal properties of the gold absorber foil and their spatial uniformity. Following installation, a heat source originating from the inertially cooled front of the diagnostic is identified and filtered out. The discharge data indicate a satisfactory signal-to-noise ratio as well as spatiotemporal resolution. These represent the first toroidally resolved images of the line-integrated radiated power in the W7-X island divertor. The diagnostic was then upgraded with a thinner platinum absorber and adjusted mirrors. Early data from the most recent experimental campaign employing the upgraded design show a considerable improvement in the diagnostic performance with more bolometer channels (> 1400), extended coverage, and increased spatial resolution.
A solar pumped liquid laser that can be scaled up to high power (10Mw CW) for space applications was developed. Liquid lasers have the inherent advantage over gases in that they provide much higher lasant densities and thus high power densities. Liquids also have inherent advantages over solids in that they have much higher damage thresholds and are much cheaper to produce for large scale applications. Among the liquid laser media that are potential candidates for solar pumping, the POC13:Nd(3+):ZrC14 liquid was chosen for its high intrinsic efficiency as well as its relatively good stability against decomposition due to protic contamination. The development and testing of the laser liquid and the development of a large solar concentrator to pump the laser was emphasized. The procedure to manufacture the laser liquid must include diagnostic tests of the solvent purity (from protic contamination) at various stages in the production process.
An infrared imaging system is used to quantify the imposed surface temperature distribution along a liquid/gas free surface in support of the Surface Tension Driven Convection Experiment, a planned Space Transportation System flight experiment. For ground-based work a commercially available instrument was used to determine the feasibility of using the type of imaging system for this experiment. The ground-based work was used as a baseline for compiling specifications for a flight qualified imager to be designed, fabricated, tested and qualified for flight. The requirements and specifications for the flight model are given along with the reasons for departures from the ground-based equipment. The flight qualification requirements discussed are a representative sample of the necessary procedures which must be followed to flight qualify diagnostic equipment for use aboard the STS. The potential problems and concerns associated with operating an imaging system in orbit are also discussed.
An infrared imaging system is used to quantify the imposed surface temperature distribution along a liquid/gas free surface in support of the Surface Tension Driven Convection Experiment, a planned Space Transportation System flight experiment. For ground-based work a commercially available instrument was used to determine the feasibility of using this type of imaging system for this experiment. The ground-based work was used as a baseline for compiling specifications for a flight qualified imager to be designed, fabricated, tested and qualified for flight. The requirements and the specifications for the flight model are given along with the reasons for departures from the ground-based equipment. The flight qualification requirements discussed are a representative sample of the necessary procedures which must be followed to flight qualify diagnostic equipment for use aboard the STS. The potential problems and concerns associated with operating an imaging system on orbit are also discussed.
The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.
The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.
The improvements which have been incorporated in the Streamtube Curvature Program to enhance both its computational and diagnostic capabilities are described. Detailed descriptions are given of the revisions incorporated to more reliably handle the jet stream-external flow interaction at trailing edges. Also presented are the augmented boundary layer procedures and a variety of other program changes relating to program diagnostics and extended solution capabilities. An updated User's Manual, that includes information on the computer program operation, usage, and logical structure, is presented. User documentation includes an outline of the general logical flow of the program and detailed instructions for program usage and operation. From the standpoint of the programmer, the overlay structure is described. The input data, output formats, and diagnostic printouts are covered in detail and illustrated with three typical test cases.
BACKGROUND: Medical operations on the International Space Station will emphasize the stabilization and transport of critically injured personnel and so will need to be capable of advanced trauma life support (ATLS). METHODS: We evaluated the ATLS invasive procedures in the microgravity environment of parabolic flight using a porcine animal model. Included in the procedures evaluated were artificial ventilation, intravenous infusion, laceration closure, tracheostomy, Foley catheter drainage, chest tube insertion, peritoneal lavage, and the use of telemedicine methods for procedural direction. RESULTS: Artificial ventilation was performed and appeared to be unaltered from the 1-G environment. Intravenous infusion, laceration closure, percutaneous dilational tracheostomy, and Foley catheter drainage were achieved without difficulty. Chest tube insertion and drainage were performed with no more difficulty than in the 1-G environment due to the ability to restrain patient, operator and supplies. A Heimlich valve and Sorenson drainage system were both used to provide for chest tube drainage collection with minimal equipment, without the risk of atmospheric contamination, and with the capability to auto-transfuse blood drained from a hemothorax. The use of telemedicine in chest tube insertion was demonstrated to be useful and feasible. Peritoneal lavage using a percutaneous technique, although requiring less training to perform, was found to be dangerous in weightlessness due to the additional pressure of the bowel on the anterior abdominal wall creating a high risk of bowel perforation. CONCLUSIONS: The performance of ATLS procedures in microgravity appears to be feasible with the exception of diagnostic peritoneal lavage. Minor modifications to equipment and techniques are required in microgravity to effect surgical drainage in the presence of altered fluid dynamics, to prevent atmospheric contamination, and to provide for the restraint requirements. A parabolic simulation system was developed for equipment and procedure verification, physiological research, and possible crew medical officer training in the future.
The design of a Self-Diagnostic (SD) accelerometer system for the Space Shuttle Main Engine is presented. This retrofit system connects diagnostic electronic hardware and software to the current M6 accelerometer system. This paper discusses the general operation of the M6 accelerometer SD system and procedures for developing and evaluating the SD system. Signal processing techniques using M6 accelerometer diagnostic data are explained. Test results include diagnostic data responding to changing ambient temperature, mounting torque and base mounting impedance.
The effects of atmospheric haze on Thematic Mapper data, transformed to TM Tasseled Cap features, are illustrated by means of simulation. A spectral feature by which the amount of atmospheric haze may be inferred is derived and described for both simulated and actual TM data. Results presented for two actual TM scenes illustrate the diagnostic feature's sensitivity to changes in haze level as well as its insensitivity to scene-class-related variability. The method by which such a diagnostic feature might be incorporated into a haze normalization procedure is also discussed.
A detailed operating manual is presented for a grid generating program that produces 3-D meshes for advanced turboprops. The code uses both algebraic and elliptic partial differential equation methods to generate single rotation and counterrotation, H or C type meshes for the z - r planes and H type for the z - theta planes. The code allows easy specification of geometrical constraints (such as blade angle, location of bounding surfaces, etc.), mesh control parameters (point distribution near blades and nacelle, number of grid points desired, etc.), and it has good runtime diagnostics. An overview is provided of the mesh generation procedure, sample input dataset with detailed explanation of all input, and example meshes.
The International Space Station (ISS) uses Orbital Replacement Units (ORU’s) to repair failures on orbit. Using ORU’s reduces the crew time required to repair failures, but several copies of each ORU must be stored on ISS to ensure system availability. A typical ORU contains many components and has significant mass, but each ORU can repair only a single component failure. A full set of the ORU internal components could repair many different failures. Lower level assembly or component repair should reduce total spares mass. Successful electronics repair experiments were conducted on ISS. However, implementing component level repair would require a significant effort. The systems must be designed so they can be repaired during a mission, considering component layout and accessibility. The repair procedures must be developed and repair facilities, tools, and diagnostic and test instruments provided. Tracing a fault to a component is much more difficult than isolating it to an ORU. Replacing a component is much more difficult than replacing an ORU. Some problems with lower level repair are discussed. The mass savings of lower level repair will not save as much launch cost as before since launch cost has recently been reduced by an order of magnitude. Most system failures are not component failures that can be fixed by replacing a component but are due to system level problems. Repair and maintenance should be planned as part of an overall maintainability design. The risk that a lower level repair will fail is considerably greater than when using ORUs. With modern high reliability packaged systems, failure diagnosis and repair has become a lost art. However, diagnosis and repair data from the 1960’s show that increasing complexity often causes much longer diagnosis and repair times and may prevent successful repair. Increasing complexity by using lower level repair directly increases system cost, failure rate, crew time for repair, and the risk of an unrepairable system failure.
Non-invasive methods of detecting radiation exposure show promise to improve upon current approaches to biological dosimetry in ease, speed, and accuracy. Here we developed a pipeline that employs Fourier transform infrared (FTIR) spectroscopy in the mid-infrared spectrum to identify a signature of low dose ionizing radiation exposure in mouse ear pinnae over time. Mice exposed to 0.1 to 2 Gy total body irradiation were repeatedly measured by FTIR at the stratum corneum of the ear pinnae. We found significant discriminative power for all doses and time-points out to 90 days after exposure. Classification accuracy was maximized when testing 14 days after exposure (specificity > 0.9 with a sensitivity threshold of 0.9) and dropped by roughly 30% sensitivity at 90 days. Infrared frequencies point towards biological changes in DNA conformation, lipid oxidation and accumulation and shifts in protein secondary structure. Since only hundreds of samples were used to learn the highly discriminative signature, developing human-relevant diagnostic capabilities is likely feasible and this non-invasive procedure points toward rapid, non-invasive, and reagent-free biodosimetry applications at population scales.