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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Prevalence of human papillomavirus genotypes in high-grade cervical precancer and invasive cervical cancer from cancer registries before and after vaccine introduction in the United States

Background. US population-based cancer registries can be used for surveillance of human papillomavirus (HPV) types found in HPV-associated cancers. Using this framework, HPV prevalence among high-grade cervical precancers and invasive cervical cancers were compared before and after HPV vaccine availability. Methods. Archived tissue from 2 studies of cervical precancers and invasive cervical cancers diagnosed from 1993-2005 (prevaccine) were identified from 7 central cancer registries in Florida; Hawaii; Iowa; Kentucky; Louisiana; Los Angeles County, California; and Michigan; from 2014 through 2015 (postvaccine) cases were identified from 3 registries in Iowa, Kentucky, and Louisiana. HPV testing was performed using L1 consensus polymerase chain reaction analysis. HPV-type–specific prevalence was examined grouped by hierarchical attribution to vaccine types: HPV 16, 18, HPV 31, 33, 45, 52, 58, other oncogenic HPV types, and other types/HPV negative. Generalized logit models were used to compare HPV prevalence in the prevaccine study to the postvaccine study by patient age, adjusting for sampling factors. Results. A total of 676 precancers (328 prevaccine and 348 postvaccine) and 1140 invasive cervical cancers (777 prevaccine and 363 postvaccine) were typed. No differences were observed in HPV-type prevalence by patient age between the 2 studies among precancers or invasive cancers. Conclusions. The lack of reduction in vaccine-type prevalence between the 2 studies is likely explained by the low number of cases and low HPV vaccination coverage among women in the postvaccine study. Monitoring HPV-type prevalence through population-based strategies will continue to be important in evaluating the impact of the HPV vaccine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Longitudinal SARS-CoV-2 seroprevalence in Portugal and antibody maintenance 12 months after infection

During the COVID-19 pandemic, Portugal has experienced three distinct SARS-CoV-2 infection waves. We previously documented the prevalence of SARS-CoV-2 immunity, measured by specific antibodies, in September 2020, 6 months after the initial moderate wave. Here, we show the seroprevalence changes 6 months later, up to the second week of March 2021, shortly following the third wave, which was one of the most severe in the world, and 2 months following the start of the vaccination campaign. A longitudinal epidemiological study was conducted, with a stratified quota sample of the Portuguese population. Serological testing was performed, including ELISA determination of antibody class and titers. The proportion of seropositives, which was 2.2% in September 2020, rose sharply to 17.3% (95% CI: 15.8–18.8%) in March 2021. Importantly, circulating IgG and IgA antibody levels were very stable 6 months after the initial determination and up to a year after initial infection, indicating long-lasting infection immunity against SARS-CoV-2. Moreover, vaccinated people had higher IgG levels from 3 weeks post-vaccination when compared with previously infected people at the same time post-infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Massively parallel quantum chemical density matrix renormalization group method

Here, we present, to the best of our knowledge, the first attempt to exploit the supercomputer platform for quantum chemical density matrix renormalization group (QCDMRG) calculations. We have developed the parallel scheme based on the in-house MPI global memory library, which combines operator and symmetry sector parallelisms, and tested its performance on three different molecules, all typical candidates for QC-DMRG calculations. In case of the largest calculation, which is the nitrogenase FeMo cofactor cluster with the active space comprising 113 electrons in 76 orbitals and bond dimension equal to 6000, our parallel approach scales up to approximately 2000 CPU cores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. In this work, to respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics. G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Estimating posterior quantity of interest expectations in a multilevel scalable framework

Scalable approaches for uncertainty quantification are necessary for characterizing prediction confidence in large-scale subsurface flow simulations with uncertain permeability. To this end we explore a multilevel Monte Carlo approach for estimating posterior moments of a particular quantity of interest, where we employ an element-agglomerated algebraic multigrid (AMG) technique to generate the hierarchy of coarse spaces with guaranteed approximation properties for both the generation of spatially correlated random fields and the forward simulation of Darcy's law to model subsurface flow. In both these components (sampling and forward solves), we exploit solvers that rely on state-of-the-art scalable AMG. To illustrate the applicability of this approach, numerical tests are performed on two 3D examples-a unit cube and an egg-shaped domain with an irregular boundary-where the scalability of each simulation as well as the scalability of the overall algorithm are demonstrated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Material property characterization of 3D printed polypropylene wood plastic composites

Abstract Wood flour (WF) at 10 wt.% and 20 wt.% loadings was used as a reinforcing filler to enhance the applicability of polypropylene (PP) for 3D printing. After performing printability tests of PP wood plastic composites (WPCs), the mechanical properties of both injection‐molded and 3D‐printed PP WPC specimens were explored. Test specimens were prepared from 3D printed hexagons for analyzing the mechanical properties. Adding WF to neat PP increased the storage modulus and the glass transition temperature while decreasing the degree of crystallinity and the coefficient of thermal expansion, while enhancing the printability of neat PP. The tensile strength, tensile modulus of elasticity, flexural strength, and flexural modulus of elasticity of injection‐molded neat PP improved by up to 21%, 59%, 30%, and 56%, respectively, with 20 wt.% WF. However, the impact strength of injection‐molded neat PP decreased by 85%, with 20 wt.% WF. After 3D printing, the tensile strength and tensile modulus of elasticity of printed neat PP increased by up to 84% and 60%, respectively, with 20 wt.% WF. The flexural strength and flexural modulus of elasticity of neat printed PP remained unchanged compared to those of PP filled with 20 wt.% WF, while the impact strength decreased by 87%. Highlights WF was used as a reinforcement in polypropylene designed for 3D printing A pilot‐scale, pellet‐fed 3D printer was used to print hollow hexagons, and then test specimens were fabricated from these hexagons for mechanical properties The tensile and flexural properties of 3D printed neat polypropylene improved, while the impact strength decreased after adding 20 wt.% WF to the neat PP.

Hwang, Sungjun↗
DOE OSTI2024

Additive manufacturing of sandwich panels with continuous fiber reinforced high modulus composite facings

Abstract An improved approach consisting of a combination of fiber placement and fused filament fabrication is introduced for the additive manufacture (AM) of structural grade sandwich beams. Here, sandwich beams are additively manufactured using in‐situ deposition and consolidation of continuous fiber unidirectional facings made from a commingled yarn system of e‐glass fiber (~50% vol.) and amorphous PET, and a hexagonal honeycomb core structure made from PETG. Both facings and the sandwich core are manufactured on a single machine, in one sequence (skin‐core‐skin), employing the benefit of matrix compatibility to create autohesion at the interfaces. Flexural and transverse shear rigidity are determined experimentally and compared with analytical predictions and show correlation to within 3%. Flexural strength and core shear strength are also measured. Post‐mortem examinations show that core fracture and core facing debond were the dominant failure mode in flexure. Single cantilever beam tests were performed to evaluate core facing debond toughness. Subsequently, surface preheat using infrared heaters was utilized to increase autohesion between core and facing. The results show debond toughness was increased 4 times using infrared heating. This research effort presents a manufacturing approach that has the potential for the AM of stiff, well bonded, structural grade sandwich beams, in an integrated sequence, employing in‐situ consolidation to the facings, without the need for the use of intermediate adhesives for skin‐to‐core bonding. Highlights An improved additive manufacturing technique for making sandwich panels is developed. Sandwich panel facings have fiber volume fractions of approximately 50%. Surface preheat improves core‐to‐facing debond toughness by a factor of 4. Top and bottom facings are consolidated during manufacture leading to better properties. Experimental results are compared to analytical predictions and show good correlation.

17 WIND ENERGY↗
DOE OSTI2021

The Sensitivity of PBX 9502 to Drilling Operations

Polymer-bonded explosive (PBX) 9502 (95% TATB, 5% Kel-F 800 by weight) is dry-drilled on a CNC milling machine and its thermomechanical response to varying feed rates, drilling speeds, and peck depths with 4 mm and 5 mm diameter drill bits is investigated. The tested samples are affixed to a force sensor that enables recording temporally resolved cutting forces and torques, and a drill-embedded thermocouple yields local temperature data. From the data, an empirical relationship between temperature changes and feed per revolution is developed, which reveals reduced temperatures in higher feed per revolution regimes for PBX 9502. The observed relationship allows extrapolating to temperatures for other hole diameters, indicating increased temperature for smaller diameter drilling across the board. Additional testing was performed with PBX 9501 (95% HMX, 2.5% Estane®, 2.5% BDNPA/BDNPF by weight), albeit over a reduced parameter space, which revealed the opposite behavior for the feed per revolution temperature dependence. It is concluded that both PBX 9502 and PBX 9501 can be dry-drilled efficiently beyond the limits of presently applicable US-DOE standards, where cutting interface temperatures remain far below material critical temperatures. Finally, data reveals that coolant usage in the drilling process for these materials provides a wide safety margin.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗
DOE OSTI2023

Deep Reinforcement Learning Based Smart Water Heater Control for Reducing Electricity Consumption and Carbon Emission

Water heating is the third largest electricity consumer in U.S. households, after space heating and cooling. Thus, water heaters represent a significant potential for reducing electricity consumption and associated CO2 emissions of residential buildings. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity consumption and the CO2 emissions of a heat pump water heater without affecting user comfort. In this approach, a set of RL agents focusing on either electricity saving or emission reduction, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on different hot water usage and Marginal Operating Emissions Rate (MOER) profiles. The testing results showed that the RL agents that focus on electricity saving can save electricity in the range of 12–22% by operating the water heater with maximum heat pump efficiency and minimum electric element utilization. On the other hand, the RL agents that focus on emission reduction reduced emissions in the range of 18–37% by making use of the variable MOER values. These RL agents used the heat pump and/or an element when the MOER values are low due to the availability of renewable energy sources (e.g., solar and wind) and mostly avoided the periods of carbon-intensive periods. Overall, these results showed that the proposed RL approach can help minimize the electricity consumption and the CO2 emissions of a heat pump water heater without having any prior knowledge about the device.

Amasyali, Kadir↗
DOE OSTI2025

The three-point form factor of Tr ϕ 3 to six loops

We study the three-point form factor of the length-three half-BPS operator (Tr ϕ 3 ) in planar $\mathcal{N}$ = 4 Super-Yang-Mills theory, using analyticity and integrability methods. We find that the functions describing the form factor in perturbation theory live in the same restrictive space of multiple polylogarithms as the one describing the form factor of the stress-tensor operator (Tr ϕ 2 ). Furthermore, we find that the leading-order data in the collinear limit provided by the form factor operator product expansion (FFOPE) is enough to fix the form factor uniquely, at least through six loops. We perform various tests of our results using the subleading FFOPE corrections. We also analyze the form factor in the Regge limit where two Mandelstam invariants are large; we obtain a compact representation for the form factor in this limit which is valid to all orders in the coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Evaluating the Lightning Strike Damage Tolerance for CFRP Composite Laminates Containing Conductive Nanofillers

Conductive nanofillers, such as carbon nanotube, graphene nanoplatelets, and carbon black particles (with diameters in nanometers) have been shown to enhance the electrical conductivity of fiber reinforced polymer matrix composites in many existing studies. The motivation is primarily for lightning strike protection, electromagnetic interference shielding, de-icing, and the manufacturing of lightweight electronic components. Here, we evaluate the lightning strike damage tolerance of carbon fiber reinforced polymer (CFRP) matrix composite laminates containing conductive nanofillers with varying weight fractions, including carbon black (CB), carbon nanotubes (CNT), and a mix of CB and CNT, through simulated lightning strike tests, followed by both non-destructive ultrasonic inspection and destructive sectioning to characterize the damage inflicted by the simulated lightning strike. Three-point flexural tests are performed to evaluate the residual strength retained by all CFRP specimens. Results show that lightning strike damage experienced varying levels of reduction for CFRP composite specimens containing conductive fillers in comparison to the baseline specimen without fillers. Notably, the delamination only penetrated to the interface between the 1st and 2nd layer for the specimen with 0.25 wt.% CNT in comparison to the baseline CFRP specimen for which the delamination penetrated to the interface between the 5th and 6th layer. Moreover, the retention of the flexural modulus increased from 26.5% to a maximum of 95.0% for the specimen with 0.25 wt.% hybrid CB and CNT. Yet, we show that using our chosen conductive fillers cannot fully eliminate lightning strike damage. Additionally, adding conductive fillers could compromise the flexural properties. We provide discussions on future recommendations on using conductive fillers for the lightning strike protection of CFRP composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Approaching air buoyancy in aero/cryogel vacuum vessels

Air impermeability has been observed in low-density aerogel and cryogel materials, which has led to a series of experiments to investigate the feasibility of an air buoyant vacuum vessel, as well as the fabrication and testing of sub-buoyant prototypes. Here, bulk samples of silica aerogel were shown to isolate vacuum from ambient air for several hours with optimal vacuum isolation occurring at a density of approximately 85 mg cm –3 . It was demonstrated using polyimide aerogel and cryogel materials that the ability of these foam materials to provide an air impermeable layer between vacuum and atmosphere, in spite of being comprised of mostly void space, is related to material stiffness. It is hypothesized that this behavior is due to local deformation of the random nanostructure of the material. Spherical shell vacuum vessels were produced using the polyimide cryogel, and less than 133 Pa vacuum containment was demonstrated under active pumping. In order to approach the non-buoyant to buoyant transition for these vacuum vessels, a polyimide composite was produced using helical fibers for which preliminary mechanical testing was performed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atomic Layer Deposition Niobium Nitride Films for High-Q Resonators

Niobium nitride (NbN) is a useful material for fabricating detectors because of its high critical temperature and relatively high kinetic inductance. In particular, NbN can be used to fabricate nanowire detectors and mm-wave transmission lines. When deposited, NbN is usually sputtered, leaving room for concern about uniformity at small thicknesses. In this work, we present atomic layer deposition niobium nitride (ALD NbN) as an alternative technique that allows for precision control of deposition parameters such as film thickness, stage temperature, and nitrogen composition. Atomic-scale control over film thickness admits a high degree of uniformity for films 4–30 nm thick; control over deposition temperature gives rise to growth rate changes, which can be used to optimize film thickness and critical temperature. In order to charac- terize ALD NbN in the radio-frequency regime, we construct single-layer micro- wave resonators and test their performance as a function of stage temperature and input power. ALD processes can admit high resonator quality factors, with ≥ 43% of resonators above Q i = 10 6 , which in turn increase detector multiplexing capabilities. i Furthermore, we find critical temperatures in the range of 7.5–10.9 K that vary as a function of cycle count and deposition temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A new method for predicting hurricane rapid intensification based on co-occurring environmental parameters

Abstract Tropical cyclones (TCs) that undergo Rapid Intensification (RI) can pose serious socioeconomic threats and can potentially result in major damaging impacts along coastal areas. Considering the complexity of various physical mechanisms that play a role in RI and its relatively low probability of occurrence, predicting RI remains a major operational challenge. In this study, we propose a simple deterministic binary classification model based on the co-occurrence of environmental parameters (MCE) to predict an RI event. More specifically, the model determines the possibility of RI based on a simple count of the number of environmental predictors deemed favorable and unfavorable. We compare our model results to logistic regression (LR) and decision tree (DT) models, well-trained using the same set of environmental predictors. Results reveal that at an RI threshold of 30 kt, the MCE exhibits a critical success index score of 0.233 which is 14% higher than DT and LR model performances. When tested at multiple RI thresholds, the MCE displays relatively higher skill scores across multiple metrics. By simultaneously evaluating the favorability of predictors, the MCE is able to comparatively reduce the number of false alarms predicted when certain predictors are unfavorable toward RI. Interpreting these model results to gain a physical understanding of how co-occurring environmental parameters can affect RI, we highlight future directions for using models based on the MCE approach to understand and predict TC RI as well as other meteorological extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Oxidation of the HiSiMo Cast Irons Alloyed with Cr/Al at 800 °C

To improve the oxidation resistance of cast iron containing Si and Mo (HiSiMo), 1wt.% Cr and 3wt.% Al were added into the base alloy to improve high temperature oxidation resistance for exhaust manifold applications. Oxidation tests were performed in both dry and wet air (air + 10% H 2 O) at 800 °C for 1, 10, 24, and 50 h. The mass change and oxide thickness were measured to evaluate the oxidation resistance. Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDS) and transmission electron microscopy (TEM) were employed to characterize the oxidized samples. Here, the results showed that the additions of Al or Cr selectively oxidized to form a more oxidation resistant surface oxide layer, which reduced the mass gain during these experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Super Resolution Digital Image Correlation (SR-DIC): an Alternative to Image Stitching at High Magnifications

Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.

Hansen, R. S.↗
DOE OSTI2020

Shear Punch Testing of Neutron-Irradiated HT-9 and 14YWT

Shear punch mechanical testing was performed on neutron-irradiated HT-9 and 14YWT alloys, comparing the traditional ferritic/martensitic steel with the advanced oxide dispersion strengthened nanostructured ferritic alloy. The samples were irradiated at various temperatures between 380°C and 520°C. In HT-9, on increasing the irradiation temperature, the 1% offset shear stress and maximum shear stress decreased. The advanced 14YWT alloy was less sensitive to irradiation temperature with respect to irradiation hardening. However, it still exhibited irradiation hardening at each temperature.

36 MATERIALS SCIENCE↗