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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Multi-Dimensional Damage Detection for Surfaces and Structures

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or sensory system, which may include a time domain reflectometer, resistivity monitoring hardware, or other resistance-based systems. To begin, a layered composite consisting of thin-film damage detection layers separated by non-damage detection layers is fabricated. The damage detection layers are attached to a detector that provides details regarding the physical health of each detection layer individually. If damage occurs to any of the detection layers, a change in the electrical properties of the detection layers damaged occurs, and a response is generated. Real-time analysis of these responses will provide details regarding the depth, location, and size estimation of the damage. Multiple damages can be detected, and the extent (depth) of the damage can be used to generate prognostic information related to the expected lifetime of the layered composite system. The detection system can be fabricated very easily using off-the-shelf equipment, and the detection algorithms can be written and updated (as needed) to provide the level of detail needed based on the system being monitored. Connecting to the thin film detection layers is very easy as well. The truly unique feature of the system is its flexibility; the system can be designed to gather as much (or as little) information as the end user feels necessary. Individual detection layers can be turned on or off as necessary, and algorithms can be used to optimize performance. The system can be used to generate both diagnostic and prognostic information related to the health of layer composite structures, which will be essential if such systems are utilized for space exploration. The technology is also applicable to other in-situ health monitoring systems for structure integrity.

Williams, Martha↗
NASA NTRS2011

Component-Level Electronic-Assembly Repair (CLEAR) Analysis of the Problem Reporting and Corrective Action (PRACA) Database of the International Space Station On-Orbit Electrical Systems

The NASA Constellation Program is investigating and developing technologies to support human exploration of the Moon and Mars. The Component-Level Electronic-Assembly Repair (CLEAR) task is part of the Supportability Project managed by the Exploration Technology Development Program. CLEAR is aimed at enabling a flight crew to diagnose and repair electronic circuits in space yet minimize logistics spares, equipment, and crew time and training. For insight into actual space repair needs, in early 2008 the project examined the operational experience of the International Space Station (ISS) program. CLEAR examined the ISS on-orbit Problem Reporting and Corrective Action database for electrical and electronic system problems. The ISS has higher than predicted reliability yet, as expected, it has persistent problems. A goal was to identify which on-orbit electrical problems could be resolved by a component-level replacement. A further goal was to identify problems that could benefit from the additional diagnostic and test capability that a component-level repair capability could provide. The study indicated that many problems stem from a small set of root causes that also represent distinct component problems. The study also determined that there are certain recurring problems where the current telemetry instrumentation and built-in tests are unable to completely resolve the problem. As a result, the root cause is listed as unknown. Overall, roughly 42 percent of on-orbit electrical problems on ISS could be addressed with a component-level repair. Furthermore, 63 percent of on-orbit electrical problems on ISS could benefit from additional external diagnostic and test capability. These results indicate that in situ component-level repair in combination with diagnostic and test capability can be expected to increase system availability and reduce logistics. The CLEAR approach can increase the flight crew s ability to act decisively to resolve problems while reducing dependency on Earth-supplied logistics for future Constellation Program missions.

Oeftering, Richard C.↗
NASA NTRS1992

Linear Spectral Analysis of Plume Emissions Using an Optical Matrix Processor

Plume spectrometry provides a means to monitor the health of a burning rocket engine, and optical matrix processors provide a means to analyze the plume spectra in real time. By observing the spectrum of the exhaust plume of a rocket engine, researchers have detected anomalous behavior of the engine and have even determined the failure of some equipment before it would normally have been noticed. The spectrum of the plume is analyzed by isolating information in the spectrum about the various materials present to estimate what materials are being burned in the engine. Scientists at the Marshall Space Flight Center (MSFC) have implemented a high resolution spectrometer to discriminate the spectral peaks of the many species present in the plume. Researchers at the Stennis Space Center Demonstration Testbed Facility (DTF) have implemented a high resolution spectrometer observing a 1200-lb. thrust engine. At this facility, known concentrations of contaminants can be introduced into the burn, allowing for the confirmation of diagnostic algorithms. While the high resolution of the measured spectra has allowed greatly increased insight into the functioning of the engine, the large data flows generated limit the ability to perform real-time processing. The use of an optical matrix processor and the linear analysis technique described below may allow for the detailed real-time analysis of the engine's health. A small optical matrix processor can perform the required mathematical analysis both quicker and with less energy than a large electronic computer dedicated to the same spectral analysis routine.

Gary, C. K.↗
DOE OSTI2026

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Monitoring Based Commissioning: Step-by-Step Approach to Implementation in Chiller Plants

Chilled water systems consume a significant portion of the energy in manufacturing, and inefficient operation could significantly influence utility bills and the environmental footprint of a facility. One way to ensure long-term energy-efficient plant operation is to ensure that chilled water system equipment, such as chillers, cooling towers, and pumps, are running at their best. Periodic operational assessments help to meet efficiency objectives for cooling plants. However, occasional set point and operational changes resulting from short-term fluctuations cause the plant operation to deviate from optimal. These changes accumulate over time, and operational efficiency deteriorates. Significant energy efficiency improvement potential in chilled water systems can be achieved by operational changes alone. Recent developments in information technology and the industrial internet of things data processing ability have overcome traditional problems and given rise to a new paradigm: monitoring-based commissioning (MBCx). Commissioning platforms and fault detection and diagnostics capabilities have evolved over time and presented more sophisticated abilities to efficiently control process cooling plants. The typical architectures of the MBCx process and a detailed approach to implement the process for chilled water systems are presented. A case study highlighting the energy-and cost-savings potential of MBCx systems is also presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Bayesian inference of electron density and ion temperature profiles from neutral beam and halo Balmer- α emission at Wendelstein 7-X

By employing Bayesian inference techniques, the full electron density profile from the plasma core to the edge of Wendelstein 7-X (W7-X) is inferred solely from neutral hydrogen beam and halo Balmer- α (H α ) emission data. The halo is a cloud of neutrals forming in the vicinity of the injected neutral beam due to multiple charge exchange reactions. W7-X is equipped with several neutral hydrogen beam heating sources and an H α spectroscopy system that views these sources from different angles and penetration depths in the plasma. As the beam and halo emission form complex spectra for each spatial point that are non-linearly dependent on the plasma density profile and other parameters, a complete model from the neutral beam injection and halo formation through to the spectroscopic measurements is required. The model is used here to infer electron density profiles for a range of common W7-X plasma scenarios. The inferred profiles show good agreement with profiles determined by the Thomson scattering and interferometry diagnostics across a broad range of absolute densities without any changes to the input or fitting parameters. The time evolution of the density profile in a discharge with continuous core density peaking is successfully reconstructed, demonstrating sufficient spatial resolution to infer strongly shaped profiles. Furthermore, it is shown as a proof of concept that the model is also able to infer the main ion temperature profile using the same data set.

forward modeling↗
DOE OSTI2025

Combined TDLAS and chemiluminescence imaging in a flat flame burner operated with NH3/H2 blends

Ammonia is viewed as a viable hydrogen carrier due to favorable storage and transport characteristics. While it can be re-converted to hydrogen at point-of-use via thermal catalytic cracking, direct utilization in combustion systems can result in reduced costs and improved efficiency. A major barrier to this approach is the low flammability and potential for high nitrogen oxide emissions, driven by fuel-bound nitrogen and complex kinetic pathways. While a number of kinetic mechanisms currently exist for simulating ammonia combustion, a major need continues to be direct information about species profiles in easy-to-model systems capable of isolating chemical kinetics from multi-dimensional fluid dynamic effects. This paper reports on recent species measurements made in a flat flame burner using a combined tunable-diode-laser-absorption-spectroscopy (TDLAS) and chemiluminescence imaging approach. Three flame conditions were included representative of NH3/H2 blends, partially cracked NH3 (inc. N2), and 100% NH3 with enhanced air (30% oxygen). Two NIR distributed feedback (DFB) laser diodes were used to determine H2O concentration and temperature (via ratio thermometry) at various radial and axial positions, after which an inverse Abel transform was used to infer centerline values. Companion images were collected using a Princeton Instrument PI-MAX intensified camera equipped with a 105mm UV lens and multiple filter sets targeting OH*, NH*, and NH2* emission. Results were compared to companion Cantera burner-stabilized flame simulations using various kinetic mechanisms. A recent mechanism including excited species chemistry was also included, to investigate whether excited and ground state profiles exhibit significant differences.

ammonia combustion↗
NASA NTRSDate not supplied

Multi-Objective Optimization of a Diodic Profile

The present paper investigates the flow physics of Tesla valves and studies how various geometric parameters affect their performance. The performance of the valve is measured by its diodicity, evaluated by comparing pressure drops and discharge coefficients in the forward and reverse flow directions. First, only the flow return angle of a baseline geometry was varied to understand the impact of return angle on valve performance. These baseline geometries are first analyzed with CFD, and then fabricated and installed in a steady-state experimental test rig equipped with pressure transducers, to measure forward and reverse discharge coefficients. Seven additional geometries are also tested in cold flow to identify the impact of diode count, diode volume, and orifice size on valve performance. Next, a multi-objective optimizer is allowed to vary 12 geometric parameters to produce an optimum geometry.

Propulsion↗
NASA NTRS1982

Civil helicopter propulsion system reliability and engine monitoring technology assessments

A study to reduce operating costs of helicopters, particularly directed at the maintenance of the propulsion subsystem, is presented. The tasks of the study consisted of problem definition refinement, technology solutions, diagnostic system concepts, and emergency power augmentation. Quantifiable benefits (reduced fuel consumption, on-condition engine maintenance, extended drive system overhaul periods, and longer oil change intervals) would increase the initial cost by $43,000, but the benefit of $24.46 per hour would result in breakeven at 1758 hours. Other benefits not capable of being quantified but perhaps more important include improved aircraft avilability due to reduced maintenance time, potential for increased operating limits due to continuous automatic monitoring of gages, and less time and fuel required to make engine power checks. The most important improvement is the on-condition maintenance program, which will require the development of algorithms, equipment, and procedures compatible with all operating environments.

Murphy, J. A.↗
NASA NTRS2008

LETS: Lunar Environments Test System

The Environmental Effects Branch (EM50) at the Marshall Space Flight Center has developed a unique capability within the agency, namely the Lunar Environment Test System (LETS). LETS is a cryo-pumped vacuum chamber facility capable of high vacuum (10-7 Torr). LETS is a cylindrical chamber, 30 in. (0.8 m) diameter by 48 in. (1.2 m) long thermally controlled vacuum system. The chamber is equipped with a full array of radiation sources including vacuum ultraviolet, electron, and proton radiation. The unique feature of LETS is that it contains a large lunar simulant bed (18 in. x 40 in. x 6 in.) holding 75 kg of JSC-1a simulant while operating at a vacuum of 10-7 Torr. This facility allows three applications: 1) to study the charging, levitation and migration of dust particles, 2) to simulate the radiation environment on the lunar surface, and 3) to electrically charge the lunar simulant enhancing the attraction and adhesion of dust particles to test articles more closely simulating the lunar surface dust environment. LETS has numerous diagnostic instruments including TREK electrostatic probes, residual gas analyzer (RGA), temperature controlled quartz crystal microbalance (TQCM), and particle imaging velocimeter (PIV). Finally, LETS uses continuous Labview data acquisition for computer monitoring and system control.

Vaughn, Jason A.↗
DOE OSTI2021

Absolute calibration of the Lyman-α measurement apparatus at DIII-D

The LLAMA (Lyman-Alpha Measurement Apparatus) diagnostic was recently installed on the DIII-D tokamak [Rosenthal et al., Rev. Sci. Instrum. (submitted) (2020)]. LLAMA is a pinhole camera system with a narrow band Bragg mirror, a bandpass interference filter, and an absolute extreme ultraviolet photodiode detector array, which measures the Ly-α brightness in the toroidal direction on the inboard, high field side (HFS) and outboard, low field side (LFS). This contribution presents a setup and a procedure for an absolute calibration near the Ly-α line at 121.6 nm. The LLAMA in-vacuum components are designed as a compact, transferable setup that can be mounted in an ex situ vacuum enclosure that is equipped with an absolutely calibrated Ly-α source. The spectral purity and stability of the Ly-α source are characterized using a vacuum ultraviolet spectrometer, while the Ly-α source brightness is measured by a NIST-calibrated photodiode. The non-uniform nature of the Ly-α source emission was overcome by performing a calibration procedure that scans the Ly-α source position and employs a numerical optimization to determine the emission pattern. Nominal and measured calibration factors are determined and compared, showing agreement within their uncertainties. A first conversion of the measured signal obtained from DIII-D indicates that the Ly-α brightness on the HFS and LFS is on the order of 1020 Ph sr-1 m-2 s-1. The established calibration setup and procedure will be regularly used to re-calibrate the LLAMA during DIII-D vents to monitor possible degradation of optical components and detectors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

CAN-D: A Modular Four-Step Pipeline for Comprehensively Decoding Controller Area Network Data

Controller area networks (CANs) are a broadcast protocol for real-time communication of critical vehicle subsystems. Original equipment manufacturers of passenger vehicles hold secret their mappings of CAN data to vehicle signals, and these definitions vary according to make, model, and year. Without these mappings, the wealth of real-time vehicle information hidden in the CAN packets is uninterpretable, severely impeding vehicle-related research, including CAN cybersecurity and privacy studies, aftermarket tuning, efficiency and performance monitoring, and fault diagnosis to name a few. Guided by the four-part CAN signal definition, we present CAN-D (CAN-Decoder), a modular, four-step pipeline for identifying each signal's boundaries (start bit and length), endianness (byte ordering), signedness (bit-to-integer encoding), and by leveraging diagnostic standards, augmenting a subset of the extracted signals with meaningful, physical interpretation. En route to CAN-D, we provide a comprehensive review of the CAN signal reverse engineering research. All previous methods ignore endianness and signedness, rendering them incapable of decoding many standard CAN signal definitions. Incorporating endianness grows the search space from 128 to 4.72E21 signal tokenizations and introduces a web of changing dependencies. In response, we formulate, formally analyze, and provide an efficient solution to an optimization problem, allowing identification of the optimal set of signal boundaries and byte orderings. In addition, we provide two novel, state-of-the-art signal boundary classifiers—both of which are superior to previous approaches in precision and recall in three different test scenarios—and the first signedness classification algorithm, which exhibits a $>$ 97% F-score. Altogether, CAN-D is the only solution with the potential to extract any CAN signal that is also the state of the art. In evaluation on 10 vehicles of different makes, CAN-D's average $\ell ^1$ error is five times better (81% less) than all previous methods and exhibits lower average error, even when considering only signals that meet prior methods’ assumptions. Finally, CAN-D is implemented in lightweight hardware, allowing for an on-board diagnostic (OBD-II) plugin for real-time in-vehicle CAN decoding.

42 ENGINEERING↗
DOE OSTI2024

New Insertion Device Control System for the APS Upgrade

New Hybrid Permanent Magnet Undulators (HPMUs) have been designed and manufactured using servo motors for precise and reliable gap motion control for the Advanced Photon Source Upgrade (APS-U) project. Meanwhile, existing HPMUs equipped with legacy stepper motors are systematically replaced with servo motors. In parallel with mechanical modifications of the undulators, a comprehensive upgrade has been implemented for the control of the devices. This upgrade includes integration of standardized industrial components for replacement of motor controllers and motor drives using the Kollmorgen Programmable Controller Multi-axis Master (PCMM) controllers and the AKD2G series servo drives. Soft Input Output Controllers (IOCs) are developed and deployed to replace the legacy VME-based IOCs for both single-period undulators and Revolver undulators. In this paper, we will present the architecture of the new insertion device control system, including control mechanisms, interlock protocols, and tools for diagnostics and troubleshooting.

Li, W.↗
DOE OSTI2022

DARHT : Enduring Lessons from a Technical Project in a National Laboratory Context [Slides]

The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory (LANL) is the world’s first flash x-ray facility able to take multiple high-resolution radiographs of the interior features of fast-moving dense objects during a single experiment. DARHT’s radiography and complimentary diagnostics makes it an important diagnostic tool in support of the US Department of Energy’s (DOE)/National Nuclear Security Administration (NNSA)’s stewardship of the US nuclear deterrent. The project to construct DARHT ran from 1988 through 2003. Initial Operating Capability along a single axis began in 1999. A technical issue delayed Critical Decision 4 for the full dual-axis capability until 2008. DARHT was characterized by several directed changes resulting from an environmental impact study, changes to the global security context resulting from the end of underground nuclear testing, and rapid evolution of applicable technology. Conventional building and lab-space construction were part of the project, but the project was dominated by Special Facility Equipment that, together with the mission to support the nuclear weapons program, required the project to be completed by national laboratories. Although the project pre-dated implementation of DOE Order 413.3, several important lessons for national laboratory projects remain applicable today and will be discussed here, including projects appropriate for the national laboratory environment, scope stability, risk acceptance and mitigation, communication, and collaboration. Finally, considerations for DOE contractor project managers are offered based upon the DARHT experience.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗
NASA NTRS2000

Advanced imaging of the macrostructure and microstructure of bone

Noninvasive and/or nondestructive techniques are capable of providing more macro- or microstructural information about bone than standard bone densitometry. Although the latter provides important information about osteoporotic fracture risk, numerous studies indicate that bone strength is only partially explained by bone mineral density. Quantitative assessment of macro- and microstructural features may improve our ability to estimate bone strength. The methods available for quantitatively assessing macrostructure include (besides conventional radiographs) quantitative computed tomography (QCT) and volumetric quantitative computed tomography (vQCT). Methods for assessing microstructure of trabecular bone noninvasively and/or nondestructively include high-resolution computed tomography (hrCT), micro-computed tomography (muCT), high-resolution magnetic resonance (hrMR), and micromagnetic resonance (muMR). vQCT, hrCT and hrMR are generally applicable in vivo; muCT and muMR are principally applicable in vitro. Although considerable progress has been made in the noninvasive and/or nondestructive imaging of the macro- and microstructure of bone, considerable challenges and dilemmas remain. From a technical perspective, the balance between spatial resolution versus sampling size, or between signal-to-noise versus radiation dose or acquisition time, needs further consideration, as do the trade-offs between the complexity and expense of equipment and the availability and accessibility of the methods. The relative merits of in vitro imaging and its ultrahigh resolution but invasiveness versus those of in vivo imaging and its modest resolution but noninvasiveness also deserve careful attention. From a clinical perspective, the challenges for bone imaging include balancing the relative advantages of simple bone densitometry against the more complex architectural features of bone or, similarly, the deeper research requirements against the broader clinical needs. The considerable potential biological differences between the peripheral appendicular skeleton and the central axial skeleton have to be addressed further. Finally, the relative merits of these sophisticated imaging techniques have to be weighed with respect to their applications as diagnostic procedures requiring high accuracy or reliability on one hand and their monitoring applications requiring high precision or reproducibility on the other. Copyright 2000 S. Karger AG, Basel.

NASA Discipline Musculoskeletal↗
NASA NTRS1997

Robotic multimodality stereotactic brain tissue identification: work in progress

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.

Brain/anatomy & histology/surgery↗
NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗