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At least 559 records · Page 31

Health Monitoring of a Rotating Disk Using a Combined Analytical-Experimental Approach

Rotating disks undergo rigorous mechanical loading conditions that make them subject to a variety of failure mechanisms leading to structural deformities and cracking. During operation, periodic loading fluctuations and other related factors cause fractures and hidden internal cracks that can only be detected via noninvasive types of health monitoring and/or nondestructive evaluation. These evaluations go further to inspect material discontinuities and other irregularities that have grown to become critical defects that can lead to failure. Hence, the objectives of this work is to conduct a collective analytical and experimental study to present a well-rounded structural assessment of a rotating disk by means of a health monitoring approach and to appraise the capabilities of an in-house rotor spin system. The analyses utilized the finite element method to analyze the disk with and without an induced crack at different loading levels, such as rotational speeds starting at 3000 up to 10 000 rpm. A parallel experiment was conducted to spin the disk at the desired speeds in an attempt to correlate the experimental findings with the analytical results. The testing involved conducting spin experiments which, covered the rotor in both damaged and undamaged (i.e., notched and unnotched) states. Damaged disks had artificially induced through-thickness flaws represented in the web region ranging from 2.54 to 5.08 cm (1 to 2 in.) in length. This study aims to identify defects that are greater than 1.27 cm (0.5 in.), applying available means of structural health monitoring and nondestructive evaluation, and documenting failure mechanisms experienced by the rotor system under typical turbine engine operating conditions.

Abdul-Aziz, Ali↗

BioSentinel: Optimizing Growth Conditions for Improved Yeast Cell Viability After Long-Term Desiccation

NASA's BioSentinel mission is one of thirteen secondary payloads to be deployed on the Space Launch System Exploration Mission-1 (SLS EM-1). The BioSentinel nanosatellite will be sent into a heliocentric orbit beyond Low Earth Orbit (LEO), to study the effects of deep space radiation on the budding yeast, Saccharomyces cerevisiae. Ionizing radiation encountered in deep space can create damaging lesions in DNA, including double strand breaks (DSBs). Budding yeast is suitable as a biological model to study these effects, as it is eukaryotic, and can be desiccated for prolonged periods while retaining viability, thus serving as a robust analog for human cells. On the ground, yeast cells are grown in liquid medium, then loaded into the wells of microfluidic cards and air dried prior to integration into the payload. Once the spacecraft reaches its target heliocentric orbit, a mixture of growth medium and metabolic indicator dye will be pumped into the microwells at specific time points to rehydrate the cells and allow them to grow. A 3-color LED detection system will measure changes in growth and metabolism resulting from ionizing radiation exposure. BioSentinel contains a wild type control strain and a rad51 mutant that is defective for DNA damage repair. In this study, we will determine the optimal amount of time to grow diploid yeast cells in liquid culture before they are desiccated for space flight. After an extended time in stationary phase, they become more tolerant to desiccation due to stress caused by nitrogen starvation. However, excessive exposure can lead to loss of viability and to a heterogeneous cell population due to sporulation. Since viability loss during desiccation poses a risk to mission success, a stress preconditioning process during initial growth may increase long-term cell viability. To determine the growth period that improves desiccation tolerance but allows for retention of uniform radiation sensitivity, we will grow both strains in liquid medium for a varying number of days (4 to 7), desiccate the cells, and then observe changes to cell viability and ionizing radiation sensitivity over time. Supported by the Space Life Sciences Training Program at NASA Ames Research Center.

Cui, Kaixin↗

Origin of proton irradiation-induced deep acceptors in Al 0.70 Ga 0.30 N

Deep level defect introduction and carrier removal were characterized using steady-state photocapacitance (SSPC), deep level transient spectroscopy (DLTS) and lighted capacitance–voltage for proton irradiated n-type Al 0.70 Ga 0.30 N Schottky diodes grown by metal-organic vapor phase epitaxy on AlN-on-sapphire templates. SSPC observed deep levels in the as-grown diode with zero-phonon transition energies of 2.20, 2.65, 3.10, 3.40, and 4.65 eV relative to the conduction band minimum (E c ), and an additional deep level emerged at 1.20 eV with irradiation. Lighted capacitance–voltage measurements quantified the deep level concentration (N t ) of states detected by SSPC, and it was observed that N t increased with proton fluence only for the 1.2 and 4.65 eV levels. Carrier removal was much larger than the increase in N t of the 1.2 and 4.65 eV deep levels, suggesting that radiation-induced deep level compensators existed beyond what was detected with SSPC. DLTS detected additional, proton-induced deep acceptors at E c —0.55, 0.82, and 1.16 eV, the latter of which is likely the same 1.20 eV deep state observed by SSPC. The concentration of the E c —0.82 eV defect state was large enough to reconcile carrier removal with total deep level introduction. Comparing the E c —0.82 and 1.16 eV deep acceptor levels to previous experimental and theoretical reports suggests that their atomistic origins could be the nitrogen vacancy (V N ) and oxygen substituting on the nitrogen sub-lattice (O N ), respectively. This defect behavior contrasts starkly with GaN, where V N and O N are shallow donors, and demonstrates that the electronic properties of defects can evolve drastically within the AlGaN alloy system ranging from wide bandgap GaN to ultra-wide bandgap AlN.

Armstrong, Andrew Michael [Sandia National Laborat↗

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nondestructive testing of Scout rocket motors

The nondestructive tests applied to Scout rocket motors were reviewed and appraised. Analytical techniques were developed to evaluate the capabilities of the radiographic and ultrasonic procedures used. Major problem areas found were the inadequacy of high voltage radiography for detecting unbonds and propellant cracks having narrow widths, the inability to relate the ultrasonic signals received from flat-bottomed holes in standards to those received from real defects and in the general area of the specification of acceptance criteria and how these were to be met. To counter the deficiencies noted, analyses were conducted to the potential utility of radiometric, acoustic, holographic and thermographic techniques for motor and nozzle bond inspection, a new approach to qualifying magnetic particle inspection and the application of acoustic emission analysis to the evaluation of proof and leak test data.

Oaks, A. E.↗

Laser Based Remote and Rapid Inspection for Composite Plates

Composites have been extensively used in aero structure and become the predominate components in the new airframes. Thus, rapid and effective inspection for composite structures is highly desired in aerospace engineering in order to shorten the certificate cycle for new structures or provide safety guarantee for existing ones. In this paper, a laser based remote Lamb wave inspection system is presented and implemented on composite plates for simulated damage detection. The system employs pulsed laser (PL) and scanning laser Doppler vibrometer (SLDV) for noncontact and remote Lamb wave actuation and wavefield sensing. A composite plate with simulated defect (surface bonded quartz rod) is inspected with the PL-SLDV laser system. Wave scattering are observed in the SLDV acquired wavefield and the damage is further evaluated with wavefield imaging and frequency wavenumber analysis. Potential application towards automatic PL Lamb wave excitation is also explored through employing an industry robotic arm towards rapid inspection.

Lamb waves↗

Screening and Qualification of BME Feedthrough Capacitors for a Space Project

Surface mount technology feedthrough ceramic capacitors are gaining popularity in Hi-Rel systems due to small size and great filtering characteristics. In this work, BME feedthrough capacitors compliant with AEC-Q200 requirements have been evaluated, screened and qualified for a space project. Evaluation included analysis of the effect of post-soldering thermal shocks, temperature dependencies of leakage currents, distribution of breakdown voltages, assessments of high-current capability, and thermal resistance of the parts. The parts have been screened and qualified at conditions close to the military requirements for ceramic capacitors. No failures were detected during screening including burning-in, but two samples failed during monitored 2000 hour life testing at 125C and two times rated voltage. Failure analysis revealed manufacturing defects that required additional analysis of screening and qualification test conditions. Highly accelerated life testing (HALT) has been carried out to assess reliability acceleration factors and the probability of failure at the use conditions. An approach to selection of adequate burning-in and life test conditions is discussed.

Alexander Teverovsky↗

Screening and Qualification of BME Feedthrough Capacitors for a Space Project

Surface mount technology feedthrough ceramic capacitors are gaining popularity in Hi-Rel systems due to small size and great filtering characteristics. In this work, BME feedthrough capacitors compliant with AEC-Q200 requirements have been evaluated, screened and qualified for a space project. Evaluation included analysis of the effect of post-soldering thermal shocks, temperature dependencies of leakage currents, distribution of breakdown voltages, assessments of high-current capability, and thermal resistance of the parts. The parts have been screened and qualified at conditions close to the military requirements for ceramic capacitors. No failures were detected during screening including burning-in, but two samples failed during monitored 2000 hour life testing at 125C and two times rated voltage. Failure analysis revealed manufacturing defects that required additional analysis of screening and qualification test conditions. Highly accelerated life testing (HALT) has been carried out to assess reliability acceleration factors and the probability of failure at the use conditions. An approach to selection of adequate burning-in and life test conditions is discussed.

Alexander Teverovsky↗

Slow-Light Mid-IR Silicon Photonic Chips for NO 2 and CH 4 Gas Detection

A compact, chip-scale mid-infrared gas sensor is demonstrated, leveraging a two-dimensional photonic crystal waveguide (PCW) fabricated on a silicon-on-insulator (SOI) platform. The PCW comprises a hexagonal lattice with lattice constant a = 860 nm and hole radius r = 0.22a, incorporating a central line defect of reduced-radius holes (r s = 0.7r) to induce slow-light propagation near the photonic band edge with a group index of approximately 73, thereby enhancing light-matter interaction. The sensor operates at fundamental absorption wavelengths of 3.42 μm for nitrogen dioxide (NO 2 ) and 3.40 μm for methane (CH 4 ), utilizing the strongest molecular vibrational transitions for maximum sensitivity. Experimental validation was conducted using dynamically diluted gas mixtures generated by mass flow controllers, with signal acquisition performed by a liquid nitrogen-cooled InSb detector. For NO 2 , the sensor exhibited excellent linear response over 5–25 ppm (part per million) with coefficient of determination R 2 = 0.9934, achieving a detection limit of 210 ppb (part per billion)─representing the first reported silicon photonic-based NO 2 detection. For CH 4 , exposure to 25 ppm resulted in a 6.4% decrease in transmitted intensity, demonstrating multigas sensing capability. The CMOS-compatible fabrication process and compact 3 mm device footprint establish this SOI-PCW platform as a scalable, low-power solution for integrated mid-infrared gas sensing, with significant potential for environmental monitoring and industrial safety applications.

Crystals↗

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing↗

Nondestructive tests of regenerative chambers

The capabilities and limitations of nondestructive evaluation methods were studied to detect and locate bond deficiencies in regeneratively cooled thrust chambers for rocket engines. Flat test panels and a cylinder were produced to simulate regeneratively cooled thrust chamber walls. Planned defects with various bond integrities were produced in the panels to evaluate the sensitivity, accuracy, and limitations of nondestructive methods to define and locate bond anomalies. Holography, acoustic emission, and ultrasonic scan were found to yield sufficient data to discern bond quality when used in combination and in selected sequences. Bonding techniques included electroforming and brazing. Materials of construction included electroformed nickel bonded to Nickel 200 and OFHC copper, electroformed copper bonded to OFHC copper, and 300 series stainless steel brazed to OFHC copper. Variations in outer wall strength, wall thickness, and defect size were evaluated for nondestructive test response.

Malone, G. A.↗

Diagnostic accuracy of an ultrasonic multiple transducer cardiac imaging system

An ultrasonic multiple-transducer imaging system for intracardiac structure visualization is developed in order to simplify visualization of the human heart in vivo without radiation hazard or invasion of the body. Results of the evaluation of the diagnostic accuracy of the devised system in a clinical setting for adult patients are presented and discussed. Criteria are presented for recognition of mitral valva prolapse, mitral stenosis, pericardial effusion, atrial septal defect, and left ventricular dyssynergy. The probable cause for false-positive and false-negative diagnoses is discussed. However, hypertrophic myopathy and congestive myopathy were unable to be detected. Since only qualitative criteria were used, it was not possible to differentiate patients with left ventricular volume overload from patients without cardiac pathology.

Popp, R. L.↗

Harnessing the Quantum Zeno Effect in superconducting qubits for particle detection

Superconducting qubits, originally developed for quantum computing, are emerging as a potentially powerful tool for detecting low-energy particle interactions, such as dark matter and neutrinos. These devices can register energy deposits as small as a few meV, dramatically lowering the detection threshold compared to conventional sensors. However, their deployment in rare-event searches is hampered by a critical and unresolved background: Two-Level Systems (TLSes). TLSes are material defects that can scramble qubit frequencies and coherence times in a way that resembles particle energy deposits. Such false signals can critically limit the sensitivity and extend experimental runtimes for qubit-based sensors by years. This talk introduces a novel method to eliminate TLSes as a background source in superconducting qubit-based detectors. By harnessing the Quantum Zeno Effect (QZE), a well-established quantum phenomenon where frequent observation inhibits system evolution, I will discuss the possibility of “freezing” these TLS defects in place. This effectively suppresses their interference, stabilizes qubit behavior, and opens the door to using TLSes themselves as auxiliary sensors. I have already identified target TLSes and observed early signs of QZE-like dynamics in Fermilab-fabricated devices. The method builds on my existing collaborations at Fermilab’s Quantum Information Testbed (QUIET), with access to low muon flux cryogenic facilities 100 meters underground, control electronics, and expert mentors across multiple institutions. By removing a key bottleneck to superconducting sensor deployment, this research targets advancing the development of a general-purpose technique to enhance sensitivity, reduce false positives, and accelerate discovery in searches for dark matter, neutrinos, and other rare phenomena.

Seidel, Olivia [Texas U., Arlington]↗

Terahertz Imaging and Backscatter Radiography Probability of Detection Study for Space Shuttle Foam Inspections

This slide presentation reviews the use of terahertz imaging and Backscatter Radiography in a probability of detection study of the foam on the external tank (ET) shedding and damaging the shuttle orbiter. Non-destructive Examination (NDE) is performed as one method of preventing critical foam debris during the launch. Conventional NDE methods for inspection of the foam are assessed and the deficiencies are reviewed. Two methods for NDE inspection are reviewed: Backscatter Radiography (BSX) and Terahertz (THZ) Imaging. The purpose of the Probability of Detection (POD) study was to assess performance and reliability of the use of BSX and or THZ as an appropriate NDE method. The study used a test article with inserted defects, and a sample of blanks included to test for false positives. The results of the POD study are reported.

Ussery, Warren↗

First constraints on causal sources of primordial gravitational waves from BICEP/Keck, SPTpol, SPT-3G, Planck and WMAP $B$-mode data

Non-inflationary sources of gravitational waves in the early Universe generically predict causality-limited tensor power spectra at low frequencies. We report the first-ever constraints on such sources based on cosmic microwave background (CMB) $B$-mode polarization measurements. Using data from BICEP/Keck, SPTpol, SPT-3G, Planck, and WMAP, we constrain the amplitude of an early causal tensor (ECT) power spectrum parameterized by $r_{ect}$, the ratio of causal tensor power to total scalar power at $k~=~0.01$ Mpc$^{-1}$, and obtain a 95% CL upper limit of $r_{ect}<$ 0.0077. Since $r_{ect}$ can easily be related to the parameters of a given theory, our bound robustly constrains a broad class of well-motivated gravitational wave sources in the early universe, including first-order cosmological phase transitions, enhanced small-scale density perturbations, and various topological defects. Finally, we translate our limit into a bound on the present-day energy density in gravitational waves at ultra-low frequencies otherwise inaccessible to traditional gravitational wave detection strategies, including pulsar timing arrays, interferometers, and resonant cavities.

Zebrowski, Jessica A. [Fermilab; Chicago U., KICP]↗

Transient Studies of CO 2 Adsorption over CeO 2 Nanostructures with In Situ DRIFTS and Modulation Excitation

Experiments of in-situ DRIFTS combined with modulation excitation (ME) spectroscopy showed a rich surface chemistry associated with the adsorption of CO 2 on nanocubes and nanospheres of ceria. The nanocubes exposed faces with a (100) orientation, with the edges and corners displaying (110) and (111) orientations, respectively. Here, the nanospheres mainly contained ceria (111) and (110) planes. DFT calculations showed that CO 2 is a multidentate adsorbate on ceria that can undergo changes in its bonding configuration depending on the chemical environment. At 250 °C, a temperature typically used for the conversion of CO 2 into oxygenates, alkanes and olefins, CO 2 reacted with O centers or OH groups present on the nanocubes and nanospheres to yield bi- and tri-dentate carbonates, hydroxycarbonates, and formates. Both nanostructures were highly reactive and a dynamic equilibrium was established: carbonate species were rapidly generated upon the injection of CO 2 and they decomposed upon the removal of CO 2 from the gas phase. In the case of the ceria nanocubes, the adsorption/desorption processes were essentially reversible, opening the door to catalytic transformations. A larger concentration of defects in the ceria nanospheres led to strongly bound carbonates and formates that may be spectators, site blockers, or surface modifiers in catalytic processes. In the ME studies, additional intermediates were detected, and it was clear that the response of surface species to the presence/absence of CO 2 was highly dependent on the morphology of the ceria nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vision inspection system and method

An optical vision inspection system (4) and method for multiplexed illuminating, viewing, analyzing and recording a range of characteristically different kinds of defects, depressions, and ridges in a selected material surface (7) with first and second alternating optical subsystems (20, 21) illuminating and sensing successive frames of the same material surface patch. To detect the different kinds of surface features including abrupt as well as gradual surface variations, correspondingly different kinds of lighting are applied in time-multiplexed fashion to the common surface area patches under observation.

Huber, Edward D.↗

Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor

Online detection techniques to monitor the health of rotating engine components are becoming increasingly attractive to aircraft engine manufacturers in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenge to easily implement, especially in the presence of scattered loading conditions, crack size, component geometry, and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini-cracks before any catastrophic event occurs. These techniques go further to evaluate material discontinuities and other anomalies that have grown to the level of critical defects that can lead to failure. Generally, health monitoring is highly dependent on sensor systems capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system.

Abdul-Aziz, Ali↗