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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Diffusion velocity correlation for nuclear graphite gasification at high temperature and low Reynolds numbers

The safety analysis of High-Temperature and Very High Temperature gas-cooled Reactors requires reliable estimates of nuclear graphite gasification as a function of temperature, among other parameters, in the unlikely event of an air ingress accident. Although the rates of the prevailing chemical reactions increase exponentially with temperature, graphite gasification at high temperatures is limited by the oxygen diffusion through the boundary layer. The effective diffusion velocity depends on the total flow rate and pressure of the bulk air-gas mixture. This paper develops a semi-empirical Sherwood number correlation for calculating the oxygen diffusion velocity. The correlation is based on a compiled database of the results of convective heat transfer experiments with wires and cylinders of different diameters in air, water and paraffin oil at 0.006 {<=} Re {<=} 1,604 and 0.068 {<=} Sc {<=} 35.2, and of mass transfer experiments at 4.8 {<=} Re {<=} 77 and 1,300 {<=} Sc {<=} 2,000. The developed correlation is within {+-} 8% of the compiled database of 567 data points and consistent with reported gasification rate measurements at higher temperatures in experiments using different size specimens of nuclear graphite grades of NBG-18 and NB-25, IG-11, IG-110 and IG-430 in atmospheric air at 0.08 {<=} Re {<=} 30. Unlike the Graetz solution that gives a constant Sh of 3.66 at Re {<=} 1.0, the present correlation shows Sh decreases monotonically to much lower values with decreasing Re. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

High-resolution time-of-flight mass spectrometry fingerprinting of metabolites from cecum and distal colon contents of rats fed resistant starch

Time-of-flight mass spectrometry along with statistical analysis was utilized to study metabolic profiles among rats fed resistant starch (RS) diets. Fischer 344 rats were fed four starch diets consisting of 55 % (w/w, dbs) starch. A control starch diet consisting of corn starch was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. A subgroup received antibiotic treatment to determine if perturbations in the gut microbiome were long lasting. A second subgroup was treated with azoxymethane (AOM), a carcinogen. At the end of the 8-week study, cecal and distal colon content samples were collected from the sacrificed rats. Metabolites were extracted from cecal and distal colon samples into acetonitrile. The extracts were then analyzed on an accurate-mass time-of-flight mass spectrometer to obtain their metabolic profile. The data were analyzed using partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis utilized a training set and verification set to classify samples within diet and treatment groups. PLS-DA could reliably differentiate the diet treatments for both cecal and distal colon samples. The PLS-DA analyses of the antibiotic and no antibiotic-treated subgroups were well classified for cecal samples and modestly separated for distal colon samples. PLS-DA analysis had limited success separating distal colon samples for rats given AOM from those not treated; the cecal samples from AOM had very poor classification. Mass spectrometry profiling coupled with PLS-DA can readily classify metabolite differences among rats given RS diets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-count-rate effects in event processing for the XRISM/Resolve X-ray microcalorimeter. II. Energy scale and resolution in orbit

The Resolve instrument on the X-ray Imaging and Spectroscopy Mission (XRISM) uses a 36 pixel microcalorimeter designed to deliver high-resolution, non-dispersive X-ray spectroscopy. Although it is optimized for extended sources with low count rates, Resolve observations of bright point sources are still able to provide unique insights into the physics of these objects, as long as high-count-rate effects are addressed in the analysis. These effects include the loss of exposure time for each pixel, changes in the energy scale, and changes in the energy resolution. To investigate these effects under realistic observational conditions, we observed the bright X-ray source, the Crab Nebula, with XRISM at several offset positions with respect to the Resolve field of view and with continuous illumination from 55 Fe sources on the filter wheel. For the spectral analysis, we excluded data where exposure-time loss was too significant to ensure reliable spectral statistics. The energy scale at 6 keV shows a slight negative shift in the high-count-rate regime. The energy resolution at 6 keV worsens as the count rate in electrically neighboring pixels increases, but can be restored by applying a nearest-neighbor coincidence cut (“cross-talk cut”). We examined how these effects influence the observation of bright point sources, using GX 13+1 as a test case, and identified an eV-scale energy offset at 6 keV between the inner (brighter) and outer (fainter) pixels. Users who seek to analyze velocity structures on the order of tens of km s–1 should account for such high-count-rate effects. These findings will aid in the interpretation of Resolve data from bright sources and provide valuable considerations for designing and planning for future microcalorimeter missions.

X-rays: general↗
DOE OSTI2014

Mass Spectrometry and Fourier Transform Infrared Spectroscopy for Analysis of Biological Materials

Time-of-flight mass spectrometry along with statistical analysis was utilized to study metabolic profiles among rats fed resistant starch (RS) diets. Fischer 344 rats were fed four starch diets consisting of 55% (w/w, dbs) starch. A control starch diet consisting of corn starch was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. A subgroup received antibiotic treatment to determine if perturbations in the gut microbiome were long lasting. A second subgroup was treated with azoxymethane (AOM), a carcinogen. At the end of the eight week study, cecal and distal-colon contents samples were collected from the sacrificed rats. Metabolites were extracted from cecal and distal colon samples into acetonitrile. The extracts were then analyzed on an accurate-mass time-of-flight mass spectrometer to obtain their metabolic profile. The data were analyzed using partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis utilized a training set and verification set to classify samples within diet and treatment groups. PLS-DA could reliably differentiate the diet treatments for both cecal and distal colon samples. The PLS-DA analyses of the antibiotic and no antibiotic treated subgroups were well classified for cecal samples and modestly separated for distal-colon samples. PLS-DA analysis had limited success separating distal colon samples for rats given AOM from those not treated; the cecal samples from AOM had very poor classification. Mass spectrometry profiling coupled with PLS-DA can readily classify metabolite differences among rats given RS diets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Recent trends in power system reliability and implications for evaluating future investments in resiliency

Here, this study examines the relationship between annual changes in electricity reliability reported by a large cross-section of U.S. electricity distribution utilities over a period of 13 years and a broad set of potential explanatory variables, including weather and utility characteristics. We find statistically significant correlations between the average number of power interruptions experienced annually and above average wind speeds, precipitation, lightning strikes, and a measure of population density: customers per line mile. We also find significant relationships between the average number of minutes of power interruptions experienced and above average wind speeds, precipitation, cooling degree-days, and one strategy used to mitigate the impacts of severe weather: the amount of underground transmission and distribution line miles. Perhaps most importantly, we find a significant time trend of increasing annual average number of minutes of power interruptions over time—especially when interruptions associated with extreme weather are included. Lastly, the research method described in this analysis can provide a basis for future efforts to project long-term trends in reliability and the associated benefits of strategies to improve grid resiliency to severe weather—both in the U.S. and abroad.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

In the face of increasing frequency of extreme events, enhancing resilience and reliability of energy infrastructure demands innovative solutions. Hydropower, with its inherent generation flexibility and grid-forming capability, offers significant potential for enhancing power grid resilience through the establishment of microgrids. To enable informed decision-making and strategic planning, we present the Hydropower Resilience Database (HRD) that integrates data from various sources such as Oakridge National Laboratory (ORNL) HydroSource, National Inventory of Dams, and US Western Grid database. By integrating relevant information on hydropower plant characteristics, including dams, reservoirs, and connected electrical grid, this resource enables hydropower plant owners, utilities, and community stakeholders to identify and evaluate the feasibility of using hydropower resources in microgrids to support nearby communities and critical infrastructure in various challenging scenarios. Using HRD, a set of metrics are evaluated to quantify the capability of hydropower plants to support essential microgrid functions. An interactive tool is developed using ArcGIS, enabling the visualization and analysis using HRD. Our research contributes to strategic planning efforts for fortifying energy infrastructure, ensuring reliable power supply during disruptions, and advancing the development of robust and resilient energy systems in regions susceptible to grid vulnerabilities.

13 HYDRO ENERGY↗
DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

In the face of increasing frequency of extreme events, enhancing resilience and reliability of energy infrastructure demands innovative solutions. Hydropower, with its inherent generation flexibility and grid-forming capability, offers significant potential for enhancing power grid resilience through the establishment of microgrids. To enable informed decision-making and strategic planning, we present the Hydropower Resilience Database (HRD) that integrates data from various sources such as Oakridge National Laboratory (ORNL) HydroSource, National Inventory of Dams, and US Western Grid database. By integrating relevant information on hydropower plant characteristics, including dams, reservoirs, and connected electrical grid, this resource enables hydropower plant owners, utilities, and community stakeholders to identify and evaluate the feasibility of using hydropower resources in microgrids to support nearby communities and critical infrastructure in various challenging scenarios. Using HRD, a set of metrics are evaluated to quantify the capability of hydropower plants to support essential microgrid functions. An interactive tool is developed using ArcGIS, enabling the visualization and analysis using HRD. Our research contributes to strategic planning efforts for fortifying energy infrastructure, ensuring reliable power supply during disruptions, and advancing the development of robust and resilient energy systems in regions susceptible to grid vulnerabilities.

13 HYDRO ENERGY↗
DOE OSTI2025

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies

Because natural gas emits less carbon than other fossil fuels, it holds promise as a green energy transition fuel. However, the overall carbon footprint of natural gas is significantly elevated by methane emissions that occur during its production and transmission (Cusworth et al. 2022). Methane “super-emitters,” while comprising only about 1% of sites, are responsible for the majority of oil- and gas-sourced methane emissions, making their detection and mitigation critical in reducing the climate impact of natural gas and in meeting national and global sustainability goals (Sherwin et al. 2024). Yet, despite advancements in detection, significant uncertainties remain regarding the size, frequency, and duration distributions of methane emissions (e.g., Frankenberg et al. 2016, Cusworth et al. 2022, Chen, Sherwin et al. 2022, Conrad et al. 2023, Johnson et al. 2023, Sherwin et al. 2024) underscoring the need for comprehensive emissions inventories segmented by basin across the US. Airborne surveys are well-suited for collecting data to build these comprehensive, basin-level inventories because they allow for extensive spatial coverage, and have the spatial resolution, and the sensitivity to pinpoint individual methane sources. As remote sensing technologies enable rapid basin-scale surveys, it is imperative to establish scientifically and statistically robust standards to generate reliable and actionable emissions inventories. Recent work has shown that differences in airborne sampling strategies, detection technologies, and analysis can lead to large differences between survey conclusions if not correctly accounted for (Chen et al. 2024). This elevates the importance of incorporating proper sampling and analysis techniques when designing a methane emissions monitoring campaign to produce accurate results and facilitate cross-study comparisons. In this paper, we describe a survey strategy designed using the latest conclusions from the literature to align results from different aerial surveys. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions. We present results from a Department of Energy-funded project that deployed this survey strategy in two understudied oil and gas- producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma.

03 NATURAL GAS↗
DOE OSTI2018

Steam Reforming Process for Treating Radioactive Waste - 18172

In 2005 the THOR steam reforming fluidized-bed reactor (FBR) technology was selected by the DOE for treatment of sodium-bearing waste (SBW) at the INL. During commissioning a number of equipment reliability and process control challenges were encountered preventing the start of radiological operations. To address these challenges the team adopted a phased systematic mechanistic approach, underpinned by scientific principles and supported by some of the world's leading experts in FBR technology. The Phase 1 effort broadly addressed the entire plant and associated modifications. Phase 2 focused on the most critical issues associated with the denitration and mineralization reformer (DMR) vessel: specifically, mitigation of wall scale (mineral deposits) that formed on the inside of the DMR; mitigation of friable agglomerates (sand-castles) that caused operational instabilities; repair of damaged lower fluidizing gas distributor (ring header), and resolution of auger-grinder (A/G) reliability issues. Basic chemistry and fluidization, as well as operational issues were evaluated using engineering analysis, modeling, bench-scale, pilot scale, and full-scale runs to validate the resolutions. The bench scale testing revealed the need to ensure at least a 5 vol% concentration of CO{sub 2} in the fluidizing gas to minimize undesirable reaction intermediates that could form in less fluidized regions of the bed. Engineering analysis and modeling results pointed to the need to redesign the fluidizing gas distributor to overcome fluidization problems. Chemistry evaluations guided efforts to minimize the deposition of wall-scale. The process modifications were confirmed on the pilot level and are being validated in the full-scale unit (Phase 3). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Backup power or bill savings? How electricity tariffs impact residential solar-plus-storage usage in the United States

Adoption of paired solar-plus-storage systems has accelerated in recent years, driven by both the demand for backup power and a desire to manage utility bills. Tradeoffs between those two uses can arise through the reserve setting on the battery storage system, which serves to maintain a minimum state of charge in case of a power interruption. Our paper applies an economic framework to evaluate this tradeoff in terms of changes in bill savings and customer reliability value across reserve levels, considering how those tradeoffs depend on the underlying electricity rate structure and levels. The analysis is based on a representative set of load profiles, solar profiles, tariff designs, and stochastic power interruption events across ten different regions in the United States. We find that the opportunity cost of holding storage capacity in reserve, in terms of foregone bill reductions, outweighs any gains in reliability value from mitigated power interruptions in the majority of customer situations. Higher storage reserve levels increase total customer value only in specific circumstances, such as for customers with inferior reliability (10x average interruptions), with a very high value of lost load ($50/kWh), and with tariff or interconnection rules that disallow grid charging. However, even this result is dampened when considering tariff designs with higher price differentials that increase the opportunity cost of holding storage in reserve (e.g. import/export or time-of-use rates). Allowing grid charging in tariffs essentially eliminates the necessity to hold any storage in reserve in all sensitivity cases explored.

Electric resilience↗
DOE OSTI2012

Planetary Candidates Observed by Kepler, III: Analysis of the First 16 Months of Data

New transiting planet candidates are identified in sixteen months (May 2009 - September 2010) of data from the Kepler spacecraft. Nearly five thousand periodic transit-like signals are vetted against astrophysical and instrumental false positives yielding 1091 viable new planet candidates, bringing the total count up to over 2,300. Improved vetting metrics are employed, contributing to higher catalog reliability. Most notable is the noise-weighted robust averaging of multiquarter photo-center offsets derived from difference image analysis which identifies likely background eclipsing binaries. Twenty-two months of photometry are used for the purpose of characterizing each of the new candidates. Ephemerides (transit epoch, T{sub 0}, and orbital period, P) are tabulated as well as the products of light curve modeling: reduced radius (R{sub P}/R{sub {star}}), reduced semi-major axis (d/R{sub {star}}), and impact parameter (b). The largest fractional increases are seen for the smallest planet candidates (197% for candidates smaller than 2R{sub {circle_plus}} compared to 52% for candidates larger than 2R{sub {circle_plus}}) and those at longer orbital periods (123% for candidates outside of 50 day orbits versus 85% for candidates inside of 50 day orbits). The gains are larger than expected from increasing the observing window from thirteen months (Quarter 1 - Quarter 5) to sixteen months (Quarter 1 - Quarter 6). This demonstrates the benefit of continued development of pipeline analysis software. The fraction of all host stars with multiple candidates has grown from 17% to 20%, and the paucity of short-period giant planets in multiple systems is still evident. The progression toward smaller planets at longer orbital periods with each new catalog release suggests that Earth-size planets in the Habitable Zone are forthcoming if, indeed, such planets are abundant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Research Needs and New Capabilities for Retail Electricity Rate Analysis

Retail electricity rates are at the center of supply- and demand-side changes in future power systems and influence system costs and DER adoption decisions, all with important implications for system reliability, resiliency, and energy affordability. Building on decades of research experience and analytical insights at Lawrence Berkeley National Laboratory (LBNL) and the National Renewable Energy Laboratory (NREL), the report identifies key near-term analysis questions, enhancements to existing capabilities, and longer-term new capabilities to provide actionable insights for electricity system decision-makers, including state utility regulators, electric and gas utilities, ratepayer advocates, and DER solution providers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Analysis shear wave velocity structure obtained from surface wave methods in Bornova, Izmir

Properties of the soil from the bedrock is necessary to describe accurately and reliably for the reduction of earthquake damage. Because seismic waves change their amplitude and frequency content owing to acoustic impedance difference between soil and bedrock. Firstly, shear wave velocity and depth information of layers on bedrock is needed to detect this changing. Shear wave velocity can be obtained using inversion of Rayleigh wave dispersion curves obtained from surface wave methods (MASW- the Multichannel Analysis of Surface Waves, ReMi-Refraction Microtremor, SPAC-Spatial Autocorrelation). While research depth is limeted in active source study, a passive source methods are utilized for deep depth which is not reached using active source methods. ReMi method is used to determine layer thickness and velocity up to 100 m using seismic refraction measurement systems.The research carried out up to desired depth depending on radius using SPAC which is utilized easily in conditions that district using of seismic studies in the city. Vs profiles which are required to calculate deformations in under static and dynamic loads can be obtained with high resolution using combining rayleigh wave dispersion curve obtained from active and passive source methods. In the this study, Surface waves data were collected using the measurements of MASW, ReMi and SPAC at the İzmir Bornova region. Dispersion curves obtained from surface wave methods were combined in wide frequency band and Vs-depth profiles were obtained using inversion. Reliability of the resulting soil profiles were provided by comparison with theoretical transfer function obtained from soil paremeters and observed soil transfer function from Nakamura technique and by examination of fitting between these functions. Vs values are changed between 200-830 m/s and engineering bedrock (Vs>760 m/s) depth is approximately 150 m.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

High-Performance Computing for Advanced Smart Grid Applications

The power grid is becoming far more complex as a result of the grid evolution meeting an information revolution. Due to the penetration of smart grid technologies, the grid is evolving as an unprecedented speed and the information infrastructure is fundamentally improved with a large number of smart meters and sensors that produce several orders of magnitude larger amounts of data. How to pull data in, perform analysis, and put information out in a real-time manner is a fundamental challenge in smart grid operation and planning. The future power grid requires high performance computing to be one of the foundational technologies in developing the algorithms and tools for the significantly increased complexity. New techniques and computational capabilities are required to meet the demands for higher reliability and better asset utilization, including advanced algorithms and computing hardware for large-scale modeling, simulation, and analysis. This chapter summarizes the computational challenges in smart grid and the need for high performance computing, and present examples of how high performance computing might be used for future smart grid operation and planning.

computational challenges↗
DOE OSTI2020

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Monitoring of microbial communities in anaerobic digestion sludge for biogas optimisation

Highlights: • Characterisation of microbial communities by cloning, pyrosequencing and T-RFLP. • T-RFLP is most suitable as monitoring method but lacks taxonomic information. • Existing in silico tools unable to identify T-RFs in T-RFLP analysis of AD sludge. • This study developed a combined approach to assign taxonomy to database of T-RFs. • Combined approach is a reliable and economical way to monitor microbial consortia. - Abstract: This study characterised and compared the microbial communities of anaerobic digestion (AD) sludge using three different methods – (1) Clone library; (2) Pyrosequencing; and (3) Terminal restriction fragment length polymorphism (T-RFLP). Although high-throughput sequencing techniques are becoming increasingly popular and affordable, the reliance of such techniques for frequent monitoring of microbial communities may be a financial burden for some. Furthermore, the depth of microbial analysis revealed by high-throughput sequencing may not be required for monitoring purposes. This study aims to develop a rapid, reliable and economical approach for the monitoring of microbial communities in AD sludge. A combined approach where genetic information of sequences from clone library was used to assign phylogeny to T-RFs determined experimentally was developed in this study. In order to assess the effectiveness of the combined approach, microbial communities determined by the combined approach was compared to that characterised by pyrosequencing. Results showed that both pyrosequencing and clone library methods determined the dominant bacteria phyla to be Proteobacteria, Firmicutes, Bacteroidetes, and Thermotogae. Both methods also found that sludge A and B were predominantly dominated by acetogenic methanogens followed by hydrogenotrophic methanogens. The number of OTUs detected by T-RFLP was significantly lesser than that detected by the clone library. In this study, T-RFLP analysis identified majority of the dominant species of the archaeal consortia. However, many of the more highly diverse bacteria consortia were missed. Nevertheless, the combined approach developed in this study where clone sequences from the clone library were used to assign phylogeny to T-RFs determined experimentally managed to accurately predict the same dominant microbial groups for both sludge A and sludge B, as compared to the pyrosequencing results. Results showed that the combined approach of clone library and T-RFLP accurately predicted the dominant microbial groups and thus is a reliable and more economical way to monitor the evolution of microbial systems in AD sludge.

09 BIOMASS FUELS↗
DOE OSTI2017

Relation between quantitative coronary CTA and myocardial ischemia by adenosine stress myocardial CT perfusion

Background: Coronary-computed tomography angiography (CTA) has limited accuracy to predict myocardial ischemia. Besides luminal area stenosis, other coronary plaque morphology and composition parameters may help to assess ischemia. With the integration of coronary CTA and adenosine stress CT myocardial perfusion (CTP), reliable information regarding coronary anatomy and function can be derived in one procedure. This analysis aimed to investigate the association between coronary stenosis severity, plaque composition and morphology and the presence of ischemia measured with adenosine stress myocardial CTP. Methods and Results: 84 patients (age, 62 ± 10 years; 48% men) who underwent sequential coronary CTA and adenosine stress myocardial CT perfusion were analyzed. Automated quantification was performed in all coronary lesions (quantitative CTA). Downstream myocardial ischemia was assessed by visual analysis of the rest and stress CTP images and defined as a summed difference score of ≥1. One or more coronary plaques were present in 146 coronary arteries of which 31 (21%) were ischemia-related. Of the lesions with a stenosis percentage <50%, 50%-70%, and >70%, respectively, 9% (6/67), 18% (9/51), and 57% (16/28) demonstrated downstream ischemia. Furthermore, mean plaque burden, plaque volume, lesion length, maximal plaque thickness, and dense calcium volume were significantly higher in ischemia-related lesions, but only stenosis severity (%) (OR 1.06; 95% CI 1.02-1.10; P = .006) and lesion length (mm) (OR 1.26; 95% CI 1.02-1.55; P = .029) were independent correlates. Conclusions: Increasing stenosis percentage by quantitative CTA is positively correlated to myocardial ischemia measured with adenosine stress myocardial CTP. However, stenosis percentage remains a moderate determinant. Lumen area stenosis and lesion length were independently associated with ischemia, adjusted for coronary plaque volume, mean plaque burden, maximal lesion thickness, and dense calcium volume.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Physicochemical properties of digital light processing 3D-Printed alumina and mullite ceramics

Alumina ceramics fabricated using conventional techniques such as uniaxial pressing or injection molding are popular due to their low density, excellent insulation, and mechanical properties. However, these methods often limit the fabrication of complex geometries with high dimensional accuracy due to tooling constraints and limited design freedom. To overcome these limitations, this study employed Digital Light Processing (DLP) additive manufacturing (AM), which enables the production of precise structures. In addition, the optimization of sintering parameters to enhance the densification and performance of alumina and mullite ceramics was investigated, with a specific focus on how varying sintering temperatures and hold times affect part shrinkage, geometric accuracy, and material integrity. Flexural strength of both alumina and mullite specimens was clearly influenced by the way the layers was stacked. When layers were arranged across the direction of the applied load (Z = 4; XZ), the strength was higher than when they were stacked along the same direction as the load (Z = 3; XY). Weibull analysis based on these results showed high modulus values across all samples, indicating good reliability in the flexural strength measurements. This reliability, combined with the clear influence of sintering parameters, highlights how processing conditions effect the material properties and mechanical performance of parts produced through DLP additive manufacturing. In conclusion, these findings open new avenues for ceramic AM across various applications, enhancing the potential for innovation in fields such as aerospace, biomedical engineering, and energy.

36 MATERIALS SCIENCE↗