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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Different feeding patterns affect meat quality of Tibetan pigs associated with intestinal microbiota alterations

This study aimed to investigate the effects of different feeding patterns on meat quality, gut microbiota and its metabolites of Tibetan pigs. Tibetan pigs with similar body weight were fed the high energy diets ( HEP , 20 pigs) and the regular diets ( RFP , 20 pigs), and free-ranging Tibetan pigs ( FRP , 20 pigs) were selected as the reference. After 6 weeks of experiment, meat quality indexes of semitendinosus muscle ( SM ) and cecal microbiota were measured. The results of meat quality demonstrated that the shear force of pig SM in FRP group was higher than that in HEP and RFP groups ( p < 0.001); the pH-value of SM in HEP pigs was higher at 45 min ( p < 0.05) and lower at 24 h ( p < 0.01) after slaughter than that in FRP and RFP groups; the SM lightness ( L* value) of FRP pigs increased compared with RFP and HEP groups ( p < 0.001), while the SM redness ( a* value) of FRP pigs was higher than that of RFP group ( p < 0.05). The free fatty acid ( FA ) profile exhibited that the total FAs and unsaturated FAs of pig SM in HEP and RFP groups were higher than those in FRP group ( p < 0.05); the RFP pigs had more reasonable FA composition with higher n-3 polyunsaturated FAs ( PUFAs ) and lower n-6/n-3 PUFA ratio than HEP pigs ( p < 0.05). Based on that, we observed that Tibetan pigs fed high energy diets (HEP) had lower microbial α-diversity in cecum ( p < 0.05), and distinct feeding patterns exhibited a different microbial cluster. Simultaneously, the short-chain FA levels in cecum of FRP and RFP pigs were higher compared with HEP pigs ( p < 0.05). A total of 11 genera related to muscle lipid metabolism or meat quality, including Alistipes , Anaerovibrio , Acetitomaculun , etc., were identified under different feeding patterns ( p < 0.05). Spearman correlation analysis demonstrated that alterations of free FAs in SM were affected by the genera Prevotellaceae_NK3B31_group , Prevotellaceae UCG-003 and Christensenellaceae_R-7_group ( p < 0.05). Taken together, distinct feeding patterns affected meat quality of Tibetan pigs related to gut microbiota alterations.

Zhu, Yanbin↗
DOE OSTI2022

The Genetic Architecture of Nitrogen Use Efficiency in Switchgrass ( Panicum virgatum L.)

Switchgrass (Panicum virgatum L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity. Hence, it is imperative to develop nitrogen use-efficient switchgrass accessions by exploring the genetic basis of NUE in switchgrass. For that, we used 331 diverse field-grown switchgrass accessions planted under low and moderate N fertility treatments. We performed a genome wide association study (GWAS) in a holistic manner where we not only considered NUE as a single trait but also used its related phenotypic traits, such as total dry biomass at low N and moderate N, and nitrogen use index, such as NRE. We have evaluated the phenotypic characterization of the NUE and the related traits, highlighted their relationship using correlation analysis, and identified the top ten nitrogen use-efficient switchgrass accessions. Our GWAS analysis identified 19 unique single nucleotide polymorphisms (SNPs) and 32 candidate genes. Two promising GWAS candidate genes, caffeoyl-CoA O-methyltransferase (CCoAOMT) and <alfin-like 6(AL6), were further supported by linkage disequilibrium (LD) analysis. Finally, we discussed the potential role of nitrogen in modulating the expression of these two genes. Our findings have opened avenues for the development of improved nitrogen use-efficient switchgrass lines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Comparative Study of High-Resolution LysB29(Nε-myristoyl) des(B30) Insulin Structures Display Novel Dynamic Causal Interrelations in Monomeric-Dimeric Motions

The treatment of insulin-dependent diabetes mellitus is characterized by artificial supplementation of pancreatic β-cell ability to regulate sugar levels in the blood. Even though various insulin analogs are crucial for reasonable glycemic control, understanding the dynamic mechanism of the insulin analogs may help to improve the best-protracted insulin analog to assist people with type 1 diabetes (T1D) to live comfortably while maintaining tight glycemic control. Here, we present the high-resolution crystal structure of NN304, known as insulin detemir, to 1.7 Å resolution at cryogenic temperature. We computationally further investigated our crystal structure’s monomeric-dimeric conformation and dynamic profile by comparing it with a previously available detemir structure (PDB ID: 1XDA). Our structure (PDB ID: 8HGZ), obtained at elevated pH, provides electrostatically triggered minor movements in the equilibrium between alternate conformational substates compared to the previous structure, suggesting it might induce an intermediate state in the dissociation pathway of the insulin detemir’s hexamer:dihexamer equilibrium. Supplemented with orientational cross-correlation analysis by a Gaussian network model (GNM), this alternate oligomeric conformation offers the distinct cooperative motions originated by loose coupling of distant conformational substates of a protracted insulin analog that has not been previously observed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Significant Increase in Detection of High-resolution Emission Spectra Using a Three-dimensional Atmospheric Model of a Hot Jupiter

High-resolution spectroscopy has opened the way for new, detailed study of exoplanet atmospheres. There is evidence that this technique can be sensitive to the complex, three-dimensional (3D) atmospheric structure of these planets. In this work, we perform cross-correlation analysis of high-resolution (R ∼ 100,000) CRIRES/VLT emission spectra of the hot Jupiter HD 209458b. We generate template emission spectra from a 3D atmospheric circulation model of the planet, accounting for temperature structure and atmospheric motions—winds and planetary rotation—missed by spectra calculated from one-dimensional models. In this first-of-its-kind analysis, we find that using template spectra generated from a 3D model produces a more significant detection (6.9σ) of the planet’s signal than any of the hundreds of one-dimensional models we tested (maximum of 5.1σ). We recover the planet’s thermal emission, its orbital motion, and the presence of CO in its atmosphere at high significance. Additionally, we analyzed the relative influences of 3D temperature and chemical structures in this improved detection, including the contributions from CO and H{sub 2}O, as well as the role of atmospheric Doppler signatures from winds and rotation. This work shows that the hot Jupiter’s 3D atmospheric structure has a first-order influence on its emission spectra at high resolution and motivates the use of multidimensional atmospheric models in high-resolution spectral analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

SDSS-IV MaNGA: Exploring the Local Scaling Relations for N/O

We present, for the first time, the relationship between local stellar mass surface density, Σ * , and N/O derived from SDSS-IV MaNGA data, using a sample of 792,765 high signal-to-noise ratio star-forming spaxels. Using a combination of phenomenological modeling and partial correlation analysis, we find that Σ * alone is insufficient to predict the N/O in MaNGA spaxels and that there is an additional dependence on the local star formation rate surface density, Σ SFR . This effect is a factor of 3 stronger than the dependence of 12+log(O/H) on Σ SFR . Surprisingly, we find that the local N/O scaling relations also depend on the total galaxy stellar mass at fixed Σ * and the galaxy size at fixed stellar mass. We find that more compact galaxies are more nitrogen rich, even when Σ * and Σ SFR are controlled for. We show that ~50% of the variance of N/O is explained by the total stellar mass and size. Thus, the evolution of nitrogen in galaxies is set by more than just local effects and does not simply track the buildup of oxygen in galaxies. The precise form of the N/O–O/H relation is therefore sensitive to the sample of galaxies from which it is derived. This result casts doubt on the universal applicability of nitrogen-based strong-line metallicity indicators derived in the local universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

The correlation between Arctic sea ice, cloud phase and radiation using A-Train satellites

Abstract. Climate warming has a stronger impact on Arctic climate and sea ice cover (SIC) decline than previously thought. Better understanding and characterization of the relationship between sea ice and clouds and the implications for surface radiation is key to improving our confidence in Arctic climate projections. Here we analyze the relationship between sea ice, cloud phase and surface radiation over the Arctic, defined as north of 60° N, using active- and passive-sensor satellite observations from three different datasets. We find that all datasets agree on the climatology of and seasonal variability in total and liquid-bearing (liquid and mixed-phase) cloud covers. Similarly, our results show a robust relationship between decreased SIC and increased liquid-bearing clouds in the lowest levels (below 3 km) for all seasons (strongest in winter) but summer, while increased SIC and ice clouds are positively correlated in two of the three datasets. A refined map correlation analysis indicates that the relationship between SIC and liquid-bearing clouds can change sign over the Bering, Barents and Laptev seas, likely because of intrusions of warm air from low latitudes during winter and spring. Finally, the increase in liquid clouds resulting from decreasing SIC is associated with enhanced radiative cooling at the surface. Our findings indicate that the newly formed liquid clouds reflect more shortwave (SW) radiation back to space compared to the surface, generating a cooling effect of the surface, while their downward longwave (LW) radiation is similar to the upward LW surface emission, which has a negligible radiative impact on the surface. This overall cooling effect should contribute to dampening future Arctic surface warming as SIC continues to decline.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Measurement report: Role of organic coating and chemical composition on ice nucleation potential of atmospheric particles in European Arctic

Understanding the ice nucleation (IN) potential of Arctic aerosols is critical for predicting their influence on cloud formation and water cycles in this vulnerable region. This study investigates the role of particle composition, organic coatings, and aerosol sources in modulating ice nucleating particle (INPs) abundance across five aerosol samples collected at the Gruvebadet Observatory Station in Ny-Ålesund, Svalbard. The IN potential of Arctic aerosol particles was studied by investigating chemical, morphological, and INP abundance measurements. Single-particle analyses revealed distinct differences in mixing state, organic volume fraction (OVF), and organic coating morphology across samples. OVF distributions were linked to particle origin, with marine-influenced Na-rich particles often exhibiting thin organic coatings, while long-range transported particles showed thicker organic coatings. Biogenic contributions, though variable, were linked to heat-sensitive INPs, suggesting a role for labile biological macromolecules under certain meteorological conditions. Spearman rank correlation analysis between particle composition and immersion-mode INP concentrations at two freezing temperatures indicated that organic-rich and Na-rich particles were positively associated with enhanced INP abundance. However, discrepancies in INP abundance were observed for particles with thicker organic coatings, where the morphological configuration of the organic material may play a role. The results highlight that Arctic INP variability is governed not only by chemical composition but also by the morphological configuration of organic material, which can either enhance or inhibit ice nucleation depending on its abundance, distribution, thickness, and mixing state. These findings underscore the combined influence of source regions, atmospheric processing, and organic–inorganic interactions in shaping Arctic aerosol freezing behavior.

Lata, Nurun Nahar [Pacific Northwest National Labo↗
DOE OSTI2025

Causal relationships of vegetation productivity with root zone water availability and atmospheric dryness at the catchment scale

Abstract. This study explores the causal relationships between catchment water availability, vapor pressure deficit, and gross primary productivity (GPP) across 341 catchments in the contiguous US. Seasonal climatic, hydrological, and vegetation characteristics were represented using the Horton index, ecological aridity index, evaporative fraction index, and carbon uptake efficiency. Statistical methods, including circularity statistics, correlation analysis, and causality tests, were employed to determine the complex interactions between catchment wetness, atmospheric dryness, and vegetation carbon uptake. The results revealed a maximum lag of 2 months in the intra-annual variability of catchment water supply–productivity and atmospheric water demand–productivity relationships, with hysteresis patterns varying with the catchment's hydrological characteristics. In catchments not permanently under water-limited or energy-limited conditions, vegetation experiences hydrological stress during the peak growing period, coinciding with the highest gross primary productivity and carbon uptake efficiency being out of phase with the Horton index and in phase with the evaporative fraction index. Causality analysis highlights strong temporal continuity in GPP seasonal characteristics, with a cause–effect relationship between catchment water supply, atmospheric demand, and vegetation productivity spanning a maximum of 2 months. These findings underscore the need for a comprehensive functional framework that integrates catchment water supply, atmospheric demand, and vegetation productivity to enhance our understanding and predictive capabilities with regard to ecosystem responses to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

AGC-4 Experiment Irradiation Monitoring Data Qualification Final Report

The Graphite Technology Development Program ran a series of six experiments to quantify the effects of irradiation on nuclear grade graphite. This report focuses on the fourth experiment, Advanced Graphite Creep 4 (AGC 4). The Advanced Reactor Development (ARD) Technology Development Office (TDO) Program for research and development activities require documentation of qualified monitoring data to design and license the first high-temperature reactor nuclear plant. Qualified data meets the requirements for use as described in the experiment planning and quality assurance documents. Failed data do not meet the requirements and provide no useable information. Trend data may not meet all requirements but still provide some useable information. Use of Trend data requires assessment of how any deficiencies affect a particular use of the data. AGC-4 began with Advanced Test Reactor (ATR) Cycle 157D on May 30, 2015. After irradiating the graphite for two cycles, the capsule was removed from the reactor after ATR Cycle 158A, which ended on January 2, 2016, due to interference with another experiment. Irradiation was resumed with Cycle 162A on October 7, 2017 after the interfering experiment was removed from the reactor. AGC-4 irradiation completed by the end of Cycle 166B on January 10, 2020. Between Cycles 162A and 166B, AGC-4 capsule was removed from the reactor core during two Powered Axial Locator Mechanism (PALM) Cycles 163A and 165A to avoid overheating. All thermocouples (TCs) have functioned throughout the AGC-4 experiment. A total of 9,256,184 out of all 11,167,213 temperature records (or 82.9%) are Qualified for use by the ARD Program and 1,911,029 missing values are Failed. Argon, helium, and total gas flow data were within expected ranges, except only eight out-of-range values occurred during outages. A total of 21,240,627 out of all 22,288,5103 gas flow rates (or 92.8%) are Qualified for use by the ARD Program and 1,644,476 are Failed records mostly due to missing values. Discharge gas line moisture values were consistently low during full ATR power, except for 162B, when moisture content was increasing to more than 200 ppmv by the end of this cycle. During outages, moisture content reached as high as 700 ppmv. 1,089,941 out of a total of 1,107,331 moisture values (or 98.4%) are within the measurement range of the instrument and are Qualified for use by the ARD Program and 17,390 missing moisture values are Failed. Graphite creep specimens were subjected to one of three loads: 393, 491, or 589 lbf. For a brief period during Cycle 157D between 12:19 on June 2, 2015, and 08:23 on June 11, 2015, the load cells were wired incorrectly, resulting in missing stack load data. Missing stack loads were estimated from measured ram pressures using regression equations developed from the existing data from Cycle 157D. Estimated stack loads during this period are considered to be an accurate representation of actual load applied to the stacks. These loads deviate slightly from the planned loads. This deviation does not prevent the data from being Qualified for use but must be taken into account when analyzing the effect of load on creep. 6,095,728 out of a total of 6,403,985 moisture values (or 95.2%) are within the measurement range of the instrument and are Qualified for use by the ARD Program and 308,257 missing load values are Failed. Stack displacement increased consistently throughout the eight cycles, with total displacement reached highest value of 2.4 in by the end of irradiation. During ATR outages, a set of pneumatic rams raised the stacks of graphite creep specimens to ensure the specimens were not stuck within the test train. This stack raising was performed seven times throughout irradiation. All stacks were raised successfully each time. 4,744,974 out of a total of 6,094,513 displacement values (or 77.9%) are within the measurement range of the instrument and are Qualified for use by the ARD Program and 1,349,539 displacement values are Failed mostly due to missing values. Analyses were conducted on correlations between TCs to look for trends and step changes that might indicate instrument degradation or failure. Correlation analysis was used to identify instances when TCs form short circuits, referred to as virtual junctions, which result in TCs reporting temperatures from some location in the capsule other than the location where they were intended to read. No evidence of virtual junctions was found. Analyses were also conducted on control charts of temperature differences of between two TCs, which are expected to behave consistently throughout the entire irradiation period. Upward or downward trend over time indicates at least one TC in the pair was drifted. Examining control charts for all 66 possible pairs out of twelve TCs installed in the AGC-4 capsules reveal no clear drift failures occurred, except unstable behavior of two TCs in Zone 3, TC-7 and TC-8, over irradiation time. In conclus

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Challenges and Lessons Learned from fabrication, testing and analysis of eight MQXFA Low Beta Quadrupole magnets for HL-LHC

By the end of October 2022, the US HL-LHC Accelerator Upgrade Project (AUP) had completed fabrication of ten MQXFA magnets and tested eight of them. The MQXFA magnets are the low beta quadrupole magnets to be used in the Q1 and Q3 Inner Triplet elements of the High Luminosity LHC. This AUP effort is shared by BNL, Fermilab, and LBNL, with strand verification tests at NHMFL. An important step of the AUP QA plan is the testing of MQXFA magnets in a vertical cryostat at BNL. The acceptance criteria that could be tested at BNL were all met by the first four production magnets (MQXFA03-MQXFA06). Subsequently, two magnets (MQXFA07 and MQXFA08) did not meet some criteria and were disassembled. Lessons learned during the disassembly of MQXFA07 caused a revision to the assembly specifications that were used for MQXFA10 and subsequent magnets. In this paper, we present a summary of: 1) the fabrication and test data of all the MQXFA magnets; 2) the analysis of MQXFA07/A08 test results with characterization of the limiting mechanism; 3) the outcome of the investigation, including the lessons learned during MQXFA07 disassembly; and 4) the finite element analysis correlating observations with test performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

HDG-1 Experiment Irradiation Monitoring Data Qualification Final Report

SUMMARY The U.S. Department of Energy (DOE) Advanced Reactor Technologies (ART) Graphite Research and Development (GRD) Program is conducting a series of six experiments to quantify the effects of irradiation on nuclear-grade graphite. This report documents the qualification of irradiation monitoring data for the fifth experiment, High Dose Graphite-1 (HDG-1). Qualified monitoring data are required by the ART program to support the design and licensing of the first high-temperature reactor (HTR) nuclear plant. Data are classified as Qualified if they meet the usage requirements described in the experiment planning and quality assurance (QA) documents, Failed if they do not meet those requirements and provide no usable information, or Trend if they do not fully meet all requirements but still provide useful information subject to an assessment of how any deficiencies may affect a particular use of the data. HDG-1 irradiation began with Advanced Test Reactor (ATR) Cycle 168B on August 24, 2020, and concluded after Cycle 173C on January 27, 2025. The HDG-1 capsule was removed from the reactor core twice—during core internal change (CIC) Cycle 170A and powered axial locator mechanism (PALM) Cycle 172A—to prevent overheating of the graphite specimens during high-power PALM cycles. The capsule was therefore irradiated during a total of seven normal ATR cycles: 168B, 169A, 171A, 171B, 173A, 173B, and 173C. Irradiation monitoring data evaluated in this report include thermocouple (TC) temperature, gas flow rate, gas moisture, gas pressure, specimen load, and graphite stack displacement. Temperature. A total of 14,508,065 TC temperature records were captured. Of these, 13,901,785 (95.8%) are Qualified and 606,280 (4.2%) are Failed. The principal source of failed temperature data was the instrument failure of TC-9 (Zone 2) on June 24, 2024, and TC-10 (Zone 1) on July 5, 2024, near the end of Cycle 173A, which resulted in 595,554 Failed readings. An additional 379 missing values and 10,347 slightly negative values from TC-13 during ATR outages are also Failed. Neither TC-9 nor TC-10 was used as a temperature-control TC, and their failures did not compromise capsule condition monitoring. Correlation analysis of all 13 TCs found no evidence of virtual junction formation. Control chart analysis revealed clear downward drift of approximately 80°C for TC-6 (Zone 3) relative to other stable TCs, and possible downward drift of approximately 60°C for TC-13 relative to the Zone 5 control TC (TC-1), though TC-13 remained consistent with the Zone 2 control TC (TC-12). Gas flow. A total of 20,088,090 gas flow rate records were captured. Of these, 19,941,463 (99.3%) are Qualified and 146,627 (0.7%) are Failed due to missing values. All argon, helium, and total gas flow data were within expected ranges throughout the irradiation. Gas moisture. A total of 1,116,005 outlet gas moisture values were captured. Of these, 1,101,421 (98.7%) are Qualified and 14,584 (1.3%) are Failed, comprising 14,556 out-of-range values and 28 missing values. The out-of-range moisture values exceeded 22,000 ppmv for approximately 1 week at the beginning of Cycle 173A, when accumulated moisture evaporated after the capsule was retrieved from water storage during PALM Cycle 172A and reinserted into the east flux trap. Moisture levels returned to below 25 ppmv for the remaining three cycles, and the transient high-moisture event did not affect the integrity of specimen irradiation. Gas pressure. A total of 7,812,035 gas pressure values were captured. Of these, 6,642,048 (85.0%) are Qualified and 1,169,987 (15.0%) outlet pressure values are Failed, comprising 718,537 zero outlet pressure values due to sensor failure from Cycle 168B through Cycle 171B, 54,550 missing values, and 396,900 too-low outlet pressure values, ranging from 1.1 to 1.6 psia after sensor replacement during Cycle 173A. Load. A total of 6,696,030 load values were captured. Of these, 6,694,580 (99.98%) are Qualified and 1,450 (0.02%) are Failed due to missing values. Applied loads to the six specimen stacks were stable throughout the irradiation. Stack displacement. A total of 6,696,030 displacement values were captured. Of these, 5,713,297 (85.32%) are Qualified and 3,781 (0.06%) are Failed due to missing values. Stack displacement increased consistently throughout the irradiation, reaching approximately 3.08 in. for Channels 5 and 6 by the end of irradiation. 978,952 (14.62%) substantially elevated displacements observed for Channel 6 beginning in Cycle 171A and for Channel 5 beginning in Cycle 173A are assigned Trend status. Raising pressure. A total of 1,115,999 raising pressure values were captured. Of these, 1,115,430 (99.95%) are Qualified and 569 (0.05%) are Failed due to missing values. Ram pressure. A total of 6,696,030 ram pressure values were captured. Of these, 6,692,249 (99.95%) are Qualified and 3,484 (0.05%) are Failed due to missing values. Stack raising was perf

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Digital Image Correlation as an Experimental Modal Analysis Capability

Digital image correlation (DIC) is an established test technique in several fields including quasi-static displacement measurements. Recently there has been growing interest in using DIC to measure structural dynamic response and even extract modal parameters from that information. Although high-speed cameras have become more ubiquitous, there are no commercial end-to-end packages for modal analysis based on image data, particularly when combined with traditional data acquisition systems. As such, the practitioner is left to develop several key data processing capabilities, hardware interface equipment, and testing practices themselves. This work highlights several practical aspects that have been encountered while establishing DIC as a viable modal testing capability in a laboratory environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Correlations between Texture Profile Analysis and Sensory Evaluation of Cured Largemouth Bass Meat (Micropterus salmoides)

Texture is an important factor in evaluating the quality of aquatic products. To evaluate the texture properties of cured large mouth bass, edible sodium chloride (0, 1.0, 2.0, and 3.0%) was smeared to the bass meat. Texture profile analysis (TPA) and sensory evaluation were performed to evaluate the quality of the cured samples, and the correlations of the indexes in the two methods were analyzed. Two principal components were obtained from the TPA indexes and sensory evaluation indexes, and the cumulative variance contribution rates were 73.87% and 72.99%, respectively. Results from the principal component analysis showed that the main indicators that affected the TPA were gumminess and springiness, while those that affected sensory evaluation were chewiness and adhesiveness. The TPA index and sensory evaluation could be effectively improved when the sodium chloride added to the bass meat was 1%. In the correlation analysis, sensory springiness was negatively correlated with TPA hardness ( P < 0.05 , r = −0.553) but positively correlated with TPA chewiness ( P < 0.05 , r = 0.596). After stepwise regression analysis, the prediction equation between the sensory springiness and TPA hardness was obtained as SSp=5.770−0.002Ha. These results provide a basis for predicting the quality of large mouth bass cured products.

Li, Meijin↗
DOE OSTI2022

Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates, with application to analysis of biomarker correlates in vaccine trials

Herein, this article presents generalized semiparametric regression models for conditional cumulative incidence functions with competing risks data when covariates are missing by sampling design or happenstance. A doubly robust augmented inverse probability weighted (AIPW) complete-case approach to estimation and inference is investigated. This approach modifies IPW complete-case estimating equations by exploiting the key features in the relationship between the missing covariates and the phase-one data to improve efficiency. An iterative numerical procedure is derived to solve the nonlinear estimating equations. The asymptotic properties of the proposed estimators are established. A simulation study examining the finite-sample performances of the proposed estimators shows that the AIPW estimators are more efficient than the IPW estimators. The developed method is applied to the RV144 HIV-1 vaccine efficacy trial to investigate vaccine-induced IgG binding antibodies to HIV-1 as correlates of acquisition of HIV-1 infection while taking account of whether the HIV-1 sequences are near or far from the HIV-1 sequences represented in the vaccine construct.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Correlation-based network analysis combined with machine learning techniques highlight the role of the GABA shunt in Brachypodium sylvaticum freezing tolerance

Perennial grasses will account for approximately 16 billion gallons of renewable fuels by the year 2022, contributing significantly to carbon and nitrogen sequestration. However, perennial grasses productivity can be limited by severe freezing conditions in some geographical areas, although these risks could decrease with the advance of climate warming, the possibility of unpredictable early cold events cannot be discarded. We conducted a study on the model perennial grass Brachypodium sylvaticum to investigate the molecular mechanisms that contribute to cold and freezing adaption. The study was performed on two different B. sylvaticum accessions, Ain1 and Osl1, typical to warm and cold climates, respectively. Both accessions were grown under controlled conditions with subsequent cold acclimation followed by freezing stress. For each treatment a set of morphological parameters, transcription, metabolite, and lipid profiles were measured. State-of-the-art algorithms were employed to analyze cross-component relationships. Phenotypic analysis revealed higher adaption of Osl1 to freezing stress. Our analysis highlighted the differential regulation of the TCA cycle and the GABA shunt between Ain1 and Osl1. Osl1 adapted to freezing stress by repressing the GABA shunt activity, avoiding the detrimental reduction in fatty acid biosynthesis and the concomitant detrimental effects on membrane integrity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Digital Image Correlation Strain Field Analysis of Materials for Target Systems

Many accelerator facilities are currently being limited in beam power by their target facilities. When exposed to high-energy proton beams, target systems experience radiation damage, mechanical stress, and extreme temperatures, altering their physical properties.For example, due to defects induced in materials by high-energy protons, the physical properties of materials will change during irradiation. Conducting PIEs (Post Irradiation Examinations) can help us understand how the materials can change.Analyzing the strain field across an irradiated sample can help identify where defects have been created, how the hardness of materials have changed, and where they will experience failure.

Ayyildiz, Onat↗