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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Light Improves Alertness and Mood during the Sleep Inertial Period following Slow Wave Sleep

Introduction: Waking from sleep, especially slow wave sleep (SWS), is associated with reduced alertness known as sleep inertia. Light improves alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of light to improve alertness and mood immediately after waking from SWS. Methods: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched bright light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. Results: Compared to the control condition, participants exposed to bright blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). Discussion: Exposure to blue-enriched bright light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance.

alertness↗
NASA NTRSDate not supplied

Blue-enriched Light Improves Alertness and Mood Following Abrupt Awakening from Slow Wave Sleep

INTRODUCTION: All crew on the International Space Station (ISS) have a sleep opportunity at the same time. Emergencies arising during this time require all crew members to be abruptly awoken from sleep and to be alert, ready to work as a team, and to perform safety-critical tasks soon after waking. However, crew may experience sleep inertia after waking, which is associated with reduced alertness, poor mood, and impaired performance, especially if woken from deep sleep (slow wave sleep, SWS). Light has been shown to improve alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of blue-enriched light to improve alertness and mood immediately after waking from SWS, i.e., during the sleep inertia period. METHODS: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. RESULTS: Compared to the control condition, participants exposed to blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). DISCUSSION: Exposure to blue-enriched light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance. This countermeasure to sleep inertia may be suitable for implementation to alert crew members during mid-sleep emergencies but requires further testing in field settings.

alertness↗
NASA NTRSDate not supplied

Rise and Shine: Using Light as a Countermeasure to Sleep Inertia

INTRODUCTION: Sleep inertia describes the phenomenon of sleepiness and poor performance experienced after waking from sleep. This period of impaired alertness and performance is of significant concern to workers who nap on shift, or work on-call and are required to perform safety-critical tasks soon after waking (e.g., emergency services, healthcare, military). Light has been shown to acutely improve alertness during sleep deprivation and circadian misalignment. In this study, we assessed the efficacy of blue-enriched light to improve alertness and mood immediately after waking from SWS, i.e., during the sleep inertia period. METHODS: Twelve participants kept a sleep schedule of 8.5 h for 5 nights and 5 h for one night prior to the overnight laboratory visit (confirmed by actigraphy). Participants went to bed at their scheduled habitual bedtime in the laboratory and were monitored by standard polysomnography. After at least 5 min of SWS, participants were awoken and exposed to either red ambient light (control) or blue-enriched light (light) for 1 h. During this time, participants completed a subjective scale of alertness (Karolinska Sleepiness Scale, KSS) and visual analogue scales (VAS) of mood at 2 min, 17 min, 32 min, and 47 min after waking. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the opposite condition (control or light). A linear mixed-effects model with fixed effects of condition, time, and condition*time and a random effect of participant was used to determine the impact of light across the testing period. An average of baseline responses (pre-sleep) was included as a covariate. RESULTS: Compared to the control condition, participants exposed to blue-enriched light reported feeling more alert (KSS: F1,77=4.955, p=.029; VASalert: F1,77=8.226, p=.005), more cheerful (VAScheerful: F1,77=8.615, p=.004), less depressed (VASdepressed: F1,77=4.649, p=.034), and less lethargic (VASlethargic: F1,77=5.652, p=.020). DISCUSSION: Exposure to blue-enriched light immediately after waking from SWS may help to improve subjective alertness and mood. Future analyses will explore whether these findings extend to effects on cognitive performance. This countermeasure to sleep inertia may be suitable for implementation to alert crew members during mid-sleep emergencies but requires further testing in field settings.

alertness↗
NASA NTRS1993

Symmetry in polarimetric remote sensing

Relationships among polarimetric backscattering coefficients are derived from the viewpoint of symmetry groups. For both reciprocal and non-reciprocal media, symmetry encountered in remote sensing due to reflection, rotation, azimuthal, and centrical symmetry groups is considered. The derived properties are general and valid to all scattering mechanisms, including volume and surface scatterings and their interactions, in a given symmetrical configuration. The scattering coefficients calculated from theoretical models for layer random media and rough surfaces are shown to obey the symmetry relations. Use of symmetry properties in remote sensing of structural and environmental responses of scattering media is also discussed. Orientations of spheroidal scatterers described by spherical, uniform, planophile, plagiothile, erectophile, and extremophile distributions are considered to derive their polarimetric backscattering characteristics. These distributions can be identified from the observed scattering coefficients by comparison with theoretical symmetry calculations. A new parameter is then defined to study scattering structures in geophysical media. Observations from polarimetric data acquired by the Jet Propulsion Laboratory airborne synthetic aperture radar over forests, sea ice, and sea surface are presented. Experimental evidences of the symmetry relationships are shown and their use in polarimetric remote sensing is illustrated. For forests, the coniferous forest in Mt. Shasta area (California) and mixed forest near Presque Isle (Maine) exhibit characteristics of the centrical symmetry at C-band. For sea ice in the Beaufort Sea, multi-year sea ice has a cross-polarized ratio e close to e(sub 0), calculated from symmetry, due to the randomness in the scattering structure. First-year sea ice has e much smaller than e(sub 0) due to the preferential alignment of the columnar structure of the ice. From polarimetric data of a sea surface in the Bering Sea, it is observed that e and e(sub 0) are increasing with incident angle and e is greater than e(sub 0) at L-band because of the directional feature of sea surface waves. Symmetry properties of geophysical media can also be used to calibrate polarimetric radars.

Nghiem, S. V.↗
DOE OSTI2019

Perennial Bioenergy Crop Yield and Quality Response to Nitrogen Fertilization

At two sites in the North Central USA (Michigan (KBS) and Wisconsin (ARL)), we evaluated the effect of N fertilization on the yield and quality of five perennial bioenergy feedstock cropping systems: (1) switchgrass (Panicum virgatum L.), (2) giant miscanthus (Miscanthus × giganteus), (3) a native grass mixture (5 species), (4) an early successional field (volunteer herbaceous species), and (5) a restored prairie (18 species). In a randomized complete block design with 5 replicates and 2 split plots, N was applied at 0 and 56 kg ha –1 to split plots for each cropping system from 2010 to 2016. No yield response to N was detected in switchgrass at either location in any year. Giant miscanthus exhibited a positive yield response to N at both sites (11% at KBS and 83% at ARL). Nitrogen fertilizer addition significantly reduced glucose (KBS 12.9 and 13.8 g kg –1 year –1 , ARL 11.2 and 9.7 g kg –1 year –1 ) in the native grass mix and restored prairie systems respectively. Here, nitrogen fertilizer also reduced xylose at KBS in the switchgrasss, native grass mix, and restored prairie (4.9, 7.5, and 5.0 g kg –1 year –1 ). At ARL, N fertilization reduced xylose levels in switchgrass, giant miscanthus, and restored prairie (7.4, 6.8, and 6.2 g kg –1 year –1 ) and increased xylose levels in the early successional system (5.0 g kg –1 year –1 ).

09 BIOMASS FUELS↗
NASA NTRS1988

Predicting the velocity and azimuth of fragments generated by the range destruction or random failure of rocket casings and tankage

A calculational method is described which provides a powerful tool for predicting solid rocket motor (SRM) casing and liquid rocket tankage fragmentation response. The approach properly partitions the available impulse to each major system-mass component. It uses the Pisces code developed by Physics International to couple the forces generated by an Eulerian-modeled gas flow field to a Lagrangian-modeled fuel and casing system. The details of the predictive analytical modeling process and the development of normalized relations for momentum partition as a function of SRM burn time and initial geometry are discussed. Methods for applying similar modeling techniques to liquid-tankage-overpressure failures are also discussed. Good agreement between predictions and observations are obtained for five specific events.

Eck, Marshall↗
NASA NTRS1992

Responses Of A DRAM To Energetic Heavy Ions

Report presents results of experiments where multiple-bit errors were induced in 256-kbit commercial integrated-circuit dynamic random-access memory (DRAM) by variety of normally incident heavy ions. Idea demonstrates utility of DRAM and methods used to analyze experimental data, with view towards applying methods and data to other digital integrated circuits.

Zoutendyk, John A.↗
DOE OSTI2022

Is Mini Beam Ready for Human Trials? Results of Randomized Study of Treating De-Novo Brain Tumors in Canines Using Linear Accelerator Generated Mini Beams

The main challenge in treating malignant brain neoplasms lies in eradicating the tumor while minimizing treatmentrelated damage. Conventional radiation treatments are associated with considerable side effects. Synchrotron generated micro-beam radiation (SMBRT) has shown to preserve brain architecture while killing tumor cells, however physical characteristics and limited facility access restrict its use. We have created a new clinical device which produces mini beams on a linear accelerator, to provide a new type of treatment called mini-beam radiation therapy (MBRT). The objective of this study is to compare the treatment outcomes of linear accelerator based MBRT versus standard radiation treatment (SRT), to evaluate the tumor response and the treatment-related changes in the normal brain with respect to each treatment type. Pet dogs with de-novo brain tumors were accrued for treatment. Dogs were randomized between standard fractionated stereotactic (9 Gy in 3 fractions) radiation treatment vs. a single fraction of MBRT (26 Gy mean dose). Dogs were monitored after treatment for clinical assessment and imaging. When the dogs were euthanized, a veterinary pathologist assessed the radiation changes and tumor response. We accrued 16 dogs, 8 dogs in each treatment arm. In the MBRT arm, 71% dogs achieved complete pathological remission. The radiation-related changes were all confined to the target region. Structural damage was not observed in the beam path outside of the target region. In contrast, none of the dogs in control group achieved remission and the treatment related damage was more extensive. Therapeutic superiority was observed with MBRT, including both tumor control and the normal structural preservation. The MBRT findings are suggestive of an immune related mechanism which is absent in standard treatment. These findings together with the widespread availability of clinical linear accelerators make MBRT a promising research topic to explore further treatment and clinical trial opportunities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2018

Investigation of Multi-Input, Multi-Output (MIMO) Random Control Applied to Direct Field Acoustic Testing

Direct Field Acoustic Testing (DFAT) offers potential cost and time savings over reverberant chamber acoustic testing of spacecraft. The NASA Multi-Purpose Crew Vehicle (MPCV) Program recently directed a series of acoustic tests on Orion structural test articles comparing DFAT and reverberant testing of the same test article with a view to qualifying DFAT for manned space flight vehicles. The verification process compared four parameters noise level compliance with the one third octave test specification, spatial uniformity of the acoustic field, spatial correlation of the acoustic field and vibration response of vehicle structure, including representative solar array panels. While the results of the verification were encouraging, MPCV Loads and Dynamics engaged Quartus Engineering to investigate whether alternative MIMO random control strategies might improve the spatial uniformity and/or the spatial correlation of the DFAT acoustic field. This paper presents the results of acoustic field simulations of the DFAT test and provides a better understanding of how MIMO random control systems originally developed for vibration and structural durability testing can be expected to perform in DFAT testing.

Direct Field↗
DOE OSTI2019

Spillover as a cause of bias in baseline evaluation methods for demand response programs

Prior research has shown load reduction estimates from residential event-driven demand response programs (e.g., Critical Peak Pricing)using X of the highest Y days with a weather adjustment method are the best performing within the class of currently used baseline methods. However, they are still biased relative to estimates produced from randomized control trials (RCTs), the unbiased “gold standard” evaluation method. In this paper we identify underlying factors that cause some of the bias found in one commonly used baseline method. Rather than simply quantifying bias, our research provides a deeper understanding of what causes the bias and thus can be used to develop more accurate methods that are not subject to these underlying factors. Previous studies have compared various baseline methods relative to each other; however, because all baseline methods are biased, it is impossible to determine the true bias that exists in them. We have access to a unique RCT dataset: the Sacramento Municipal Utility District's study of critical peak pricing. Our analysis of 23 event days over two summers allows us to identify the true bias on load reduction estimates by using the RCT estimates as the unbiased gold standard against which we compare the estimates from the baseline methods. We found that spillover of energy reductions, from hours targeted by a program onto other hours, is one underlying factor that is a major cause of bias in baseline methods. We discuss alternative baseline methods that may not be subject to this same bias.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A novel FPCL model producing directional contraction through induction of fibroblast alignment by biphasic pulse direct current electric field

Although parallel alignment of fibroblasts to the tension lines of scar has been evidenced in vivo, how scar contracture generates directional contraction remains largely unclear due to the lack of effective in vitro model. Fibroblast populated collagen lattice (FPCL), a widely used in vitro model, fails to mimic scar contracture since it produces concentric contraction with the random orientation of fibroblast. We hypothesized that a novel FPCL model with fibroblast alignment might produce directional contraction and then simulate scar contracture better. Here, we showed that although direct current electric fields (DCEFs) enabled fibroblasts aligned perpendicularly to the field vector, it also promoted electrotactic migration of fibroblast in FPCL. By contrast, biphasic pulse direct current electric fields (BPDCEFs), featured by reversal of the EF direction periodically, abolished the electrotactic migration, but induced fibroblast alignment in a pulse frequency dependent manner. Specifically, BPDCEF at a pulse frequency of 0.0002 Hz induced fibroblast alignment comparable to that induced by DCEF under the same field strength (300 mV/mm), leading to an enhanced contraction of FPCL along the direction of cell alignment. FPCL pretreated by BPDCEF showed an elliptical contraction whereas it was concentric in control FPCL. Further study revealed that F-actin redistributions acted as a key mechanism for the induction of fibroblasts alignment by BPDCEF. Cytochalasin D, an inhibitor of actin dynamics, abolished F-actins redistribution, and significantly suppressed the fibroblasts alignment and the directional contraction of FPCL. Importantly, BPDCEF significantly increased RhoA activity in fibroblasts, while this response was attenuated by C3 transferase pre-treatment, a potent inhibitor of RhoA, caused F-actin depolymerization and actin filament bundle randomly distributed. Taken together, our study suggests a crucial role for fibroblast orientation in scar contracture, and provides a novel FPCL model that may be feasible and effective for investigating scar contracture in vitro.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Randomly Layered Superstructure of In 2 O 3 Truncated Nano-Octahedra and Its High-Pressure Behavior

This study outlines the synthesis and characterization of a unique superlattice composed of vertex-truncated indium oxide (In 2 O 3 ) nano-octahedra, along with an exploration of its response to high-pressure conditions. Here, using a bright-field transmission electron microscope (BF-TEM), we determined an average circumradius of 15.2 nm for these octahedral building blocks. The resilience and response of the superlattice to pressure variations, peaking at 18.01 GPa, were examined by employing synchrotron-based Wide-Angle X-ray Scattering (WAXS) and Small-Angle X-ray Scattering (SAXS) techniques. The WAXS data revealed no phase transitions, reinforcing the stability of the 2D superlattice comprised of random layers in alignment with a 2D p31m symmetry. Notably, the SAXS data unveiled a pressure-induced, irreversible octahedron translation and ligand interaction occurring within the random layer. Through our examination of these pressure-sensitive behaviors, we identified a distinctive translation model inherent to octahedra and observed modulation in the superlattice cell parameter induced by pressure. This research signifies a noteworthy progression in deciphering the intricate behaviors of 2D superlattices under high-pressure conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An application of survival analysis to disruption prediction via Random Forests</strong

We report one of the most pressing challenges facing the fusion community is adequately mitigating or, even better, avoiding disruptions of tokamak plasmas. However, before this can be done, disruptions must first be predicted with sufficient warning time to actuate a response. The established field of survival analysis provides a convenient statistical framework for time-to-event (i.e. time-to-disruption) studies. This paper demonstrates the integration of an existing disruption prediction machine learning algorithm with the Kaplan–Meier estimator of survival probability. Specifically discussed are the implied warning times from binary classification of disruption databases and the interpretation of output signals from Random Forest algorithms trained and tested on these databases. This survival analysis approach is applied to both smooth and noisy test data to highlight important features of the survival and hazard functions. In addition, this method is applied to three Alcator C-Mod plasma discharges and compared to a threshold-based scheme for triggering alarms. In one case, both techniques successfully predict the disruption; although, in another, neither warns of the impending disruption with enough time to mitigate. For the final discharge, the survival analysis approach could avoid the false alarm triggered by the threshold method. Limitations of this analysis and opportunities for future work are also presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Uncertainty quantification in multiscale simulation of woven fiber composites

We report woven fiber composites have been increasingly employed as light-weight materials in aerospace, construction, and transportation industries due to their superior properties. These materials possess a hierarchical structure that necessitates the use of multiscale simulations in their modeling. To account for the inherent uncertainty in materials, such simulations must be integrated with statistical uncertainty quantification (UQ) and propagation (UP) methods. However, limited advancement has been made in this regard due to the significant computational costs and complexities in modeling spatially correlated structural variations coupled at different scales. In this work, a non-intrusive approach is proposed for multiscale UQ and UP to address these limitations. We introduce the top-down sampling method that allows to model non-stationary and continuous (but not differentiable) spatial variations of uncertainty sources by creating nested random fields (RFs) where the hyperparameters of an ensemble of RFs is characterized by yet another RF. We employ multi-response Gaussian RFs in top-down sampling and leverage statistical techniques (such as metamodeling and dimensionality reduction) to address the considerable computational costs of multiscale simulations. We apply our approach to quantify the uncertainty in a cured woven composite due to spatial variations of yarn angle, fiber volume fraction, and fiber misalignment angle. Finally, our results indicate that, even in linear analysis, the effect of uncertainty sources on the material’s response could be significant.

42 ENGINEERING↗
DOE OSTI2021

Peridynamic Model for Microballistic Perforation of Multilayer Graphene

The peridynamic theory of solid mechanics is applied to the continuum modeling of the impact of small, high-velocity silica spheres on multilayer graphene targets. The model treats the laminate as a brittle elastic membrane. The material model includes separate failure criteria for the initial rupture of the membrane and for propagating cracks. Material variability is incorporated by assigning random variations in elastic properties within Voronoi cells. Here, the computational model is shown to reproduce the primary aspects of the response observed in experiments, including the growth of a family of radial cracks from the point of impact.

42 ENGINEERING↗
DOE OSTI2024

Randomized control trial of moderate dose vitamin D alters microbiota stability and metabolite networks in healthy adults

ABSTRACT Evidence indicates that both vitamin D and the gut microbiome are involved in the process of colon carcinogenesis. However, it is unclear what effects supplemental vitamin D 3 has on the gut microbiome and its metabolites in healthy adults. We conducted a double-blind, randomized, placebo-controlled trial to identify the acute and long-term microbiota structural and metabolite changes that occur in response to a moderate dose (4,000 IU) of vitamin D 3 for 12 weeks in healthy adults. Our results demonstrated a significant increase in serum 25-hydroxy-vitamin D (25(OH)D) in the treatment group compared to placebo ( P < 0.0001). Vitamin D 3 significantly increased compositional similarity ( P < 0.0001) in the treatment group, and enriched members of the Bifidobacteriaceae family. We also identified a significant inverse relationship between the percent change in serum 25(OH)D and microbial stability in the treatment group ( R = −0.52, P < 0.019). Furthermore, vitamin D 3 supplementation resulted in notable metabolic shifts, in addition to resulting in a drastic rewiring of key gut microbial-metabolic associations. In conclusion, we show that a moderate dose of vitamin D 3 among healthy adults has unique acute and persistent effects on the fecal microbiota, and suggest novel mechanisms by which vitamin D may affect the host-microbiota relationship. IMPORTANCE Preventative measures to reduce the rise in early-onset colorectal cancer are of critical need. Both vitamin D, dietary and serum levels, and the gut microbiome are implicated in the etiology of colorectal cancer. By understanding the intimate relationship between vitamin D, the gut microbiome, and its metabolites, we may be able to identify key mechanisms that can be targeted for intervention, including inflammation and metabolic dysfunction. Furthermore, the similarity of vitamin D to cholesterol, which is metabolized by the gut microbiome, gives precedence to its ability to produce metabolites that can be further studied and leveraged for controlling colorectal cancer incidence and mortality.

Wyatt, Madhur↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Eigenvalue uncertainty in stressed structures.

A method is presented for calculating the statistics of the natural frequencies and mode shapes of vibration for a structure acted upon by an external static loading which results in the structure being stressed for eigenvalue analysis. The analytical tools presented apply to the probabilistic eigenvalue problem, and it is apparent that structural parameter uncertainty will significantly influence all aspects of the structure's response. The treatment of a sample problem serves the purpose of furthering understanding for the importance of considering structural parameters as random variables.

Hart, G. C.↗