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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

QA/QC-ed Groundwater Level Time Series in PLM-1 and PLM-6 Monitoring Wells, East River, Colorado (2016-2022)

This data set contains QA/QC-ed (Quality Assurance and Quality Control) water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location at the East River Watershed, Colorado, USA. These wells are used to monitor subsurface water and carbon inventories and fluxes, and to determine the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry (see related references) can be used to estimate rates of solute export from the hillslope to the floodplain and river. QA/QC analysis of measured groundwater levels in monitoring wells PLM-1 and PLM-6 included identification and flagging of duplicated values of timestamps, gap filling of missing timestamps and water levels, removal of abnormal/bad and outliers of measured water levels. The QA/QC analysis also tested the application of different QA/QC methods and the development of regular (5-minute, 1-hour, and 1-day) time series datasets, which can serve as a benchmark for testing other QA/QC techniques, and will be applicable for ecohydrological modeling. The package includes a Readme file, one R code file used to perform QA/QC, a series of 8 data csv files (six QA/QC-ed regular time series datasets of varying intervals (5-min, 1-hr, 1-day) and two files with QA/QC flagging of original data), and three files for the reporting format adoption of this dataset (InstallationMethods, file level metadata (flmd), and data dictionary (dd) files).QA/QC-ed data herein were derived from the original/raw data publication available at Williams et al., 2020 (DOI: 10.15485/1818367). For more information about running R code file (10.15485_1866836_QAQC_PLM1_PLM6.R) to reproduce QA/QC output files, see README (QAQC_PLM_readme.docx). This dataset replaces the previously published raw data time series, and is the final groundwater data product for the PLM wells in the East River. Complete metadata information on the PLM1 and PLM6 wells are available in a related dataset on ESS-DIVE: Varadharajan C, et al (2022). https://doi.org/10.15485/1660962. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. 2022/09/09 Update: Converted data files using ESS-DIVE’s Hydrological Monitoring Reporting Format. With the adoption of this reporting format, the addition of three new files (v1_20220909_flmd.csv, V1_20220909_dd.csv, and InstallationMethods.csv) were added. The file-level metadata file (v1_20220909_flmd.csv) contains information specific to the files contained within the dataset. The data dictionary file (v1_20220909_dd.csv) contains definitions of column headers and other terms across the dataset. The installation methods file (InstallationMethods.csv) contains a description of methods associated with installation and deployment at PLM1 and PLM6 wells. Additionally, eight data files were re-formatted to follow the reporting format guidance (er_plm1_waterlevel_2016-2020.csv, er_plm1_waterlevel_1-hour_2016-2020.csv, er_plm1_waterlevel_daily_2016-2020.csv, QA_PLM1_Flagging.csv, er_plm6_waterlevel_2016-2020.csv, er_plm6_waterlevel_1-hour_2016-2020.csv, er_plm6_waterlevel_daily_2016-2020.csv, QA_PLM6_Flagging.csv). The major changes to the data files include the addition of header_rows above the data containing metadata about the particular well, units, and sensor description. 2023/01/18 Update: Dataset updated to include additional QA/QC-ed water level data up until 2022-10-12 for ER-PLM1 and 2022-10-13 for ER-PLM6. Reporting format specific files (v2_20230118_flmd.csv, v2_20230118_dd.csv, v2_20230118_InstallationMethods.csv) were updated to reflect the additional data. R code file (QAQC_PLM1_PLM6.R) was added to replace the previously uploaded HTML files to enable execution of the associated code. R code file (QAQC_PLM1_PLM6.R) and ReadMe file (QAQC_PLM_readme.docx) were revised to clarify where original data was retrieved from and to remove local file paths.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

A Co-Investigator Proposal for the Cornell University CAPER Rocket: Cleft Accelerated Plasma Experiment Rocket

The objectives are: 1) To support the Cornell wave instruments in a study of dayside ion outflow. 2) In conjunction with the U. of Alaska ground optical data, a prime objective was to measure the topside Cusp ion spectra responsible for dayside proton aurora. If such a correlative measurement could be made, then monitoring of this cusp precipitation from the ground could be routinely achieved. The nature of Cusp ions has and will continue to provide information about dayside magnetic reconnection. 3) A third objective was to study the dayside microburst electron precipitation from the BPS/CPS population. The Scifer rocket flight showed a bursty electron population at 1000 km altitude correlated closely with pulsation ground aurora on closed field lines. The frequency of this pulsating aurora is about 1 Hz. Ground pulsation measurements have recorded dayside bursts of Pc1 waves which could very well be the source of the electrons responsible for the pulsating aurora. In support of the Caper flight, UNH provided ground induction antennas to measure the equatorial Pc1 waves that might be dumping trapped electrons from the Central Plasma Sheet population. The Caper flight was launched on the last day of the window and all the Cornell and UNH instrumentation worked perfectly. Unfortunately the rocket trajectory flew very far to the west of the ground site at Longyearbyen missing conjugacy by several hundred kilometers. This meant the intended aurora was not crossed and all the ground experiments were far from being near the foot print of the rocket ruling out correlative science. The "miss" was primarily due to a decision during the countdown by the Andoya Rocket Range to move the azimuth of the rocket to the west to avoid Norwegian fishing boats at the splash point of the first two stages, and to make matters worse, the dispersion of the fourth stage of the rocket added entirely in this direction. Although no publications have resulted from the UNH data up to this point, a joint publication with the U. of Alaska group using both the Scifer and Caper data is in preparation. The data will continue to be worked on. There is interest in the Caper data as evidence by two recent papers presented at the "Low Latitude Boundary Layer Chapman Conference" held in New Orleans, Louisiana in April 2001.

Arnoldy, Roger L.↗
DOE OSTI2016

Magnetic field disorder and faraday effects on the polarization of extragalactic radio sources

We present a polarization catalog of 533 extragalactic radio sources that have a 2.3 GHz total intensity above 420 mJy from the S-band Polarization All Sky Survey, S-PASS, with corresponding 1.4 GHz polarization information from the NRAO VLA Sky Survey, NVSS. We studied the selection effects and found that fractional polarization, π, of radio objects at both wavelengths depends on the spectral index, the source magnetic field disorder, the source size, and depolarization. The relationship between depolarization, spectrum, and size shows that depolarization occurs primarily in the source vicinity. The median π{sub 2.3} of resolved objects in NVSS is approximately two times larger than that of unresolved sources. Sources with little depolarization are ∼2 times more polarized than both highly depolarized and re-polarized sources. This indicates that intrinsic magnetic field disorder is the dominant mechanism responsible for the observed low fractional polarization of radio sources at high frequencies. We predict that number counts from polarization surveys will be similar at 1.4 GHz and at 2.3 GHz, for fixed sensitivity, although ∼10% of all sources may currently be missing because of strong depolarization. Objects with π{sub 1.4}≈π{sub 2.3}⩾4% typically have simple Faraday structures, so they are most useful for background samples. Almost half of flat-spectrum (α⩾−0.5) and ∼25% of steep-spectrum objects are re-polarized. Steep-spectrum, depolarized sources show a weak negative correlation of depolarization with redshift in the range 0 < z < 2.3. Previous non-detections of redshift evolution are likely due the inclusion of re-polarized sources as well.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The cross-section measurement for the 3 H($e, e'K^+)nnΛ$ reaction

The small binding energy of the hypertriton leads to predictions of the non-existence of bound hypernuclei for isotriplet three-body systems such as nnΛ. However, invariant mass spectroscopy at GSI has reported events that may be interpreted as the bound nnΛ state. The nnΛ state was sought by missing-mass spectroscopy via the (e, e'K + ) reaction at Jefferson Lab’s experimental Hall A. The present experiment has higher sensitivity to the nnΛ-state investigation in terms of better precision by a factor of about three. The analysis shown in this article focuses on the derivation of the reaction cross-section for the 3 H(γ*, K + )X reaction. Events that were detected in an acceptance, where a Monte Carlo simulation could reproduce the data well (|δp/p| < 4%), were analyzed to minimize the systematic uncertainty. No significant structures were observed with the acceptance cuts, and the upper limits of the production cross-section of the nnΛ state were obtained to be 21 and $31 nbsr -1 at the 90% confidence level when theoretical predictions of (-B Λ , Γ) = (0.25, 0.8) MeV and (0.55, 4.7) MeV, respectively, were assumed. The cross-section result provides valuable information for examining the existence of nnΛ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

AGC-4 Experiment Irradiation Monitoring Data Qualification Interim Report

The Graphite Technology Development Program is running a series of six experiments to quantify the effects of irradiation on nuclear grade graphite. The fourth experiment, Advanced Graphite Creep 4 (AGC 4), began with Advanced Test Reactor (ATR) cycle 157D on May 30, 2015, and has been irradiated 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 will resume when the interfering experiment is removed from the reactor. This report documents qualification of AGC 4 experiment irradiation monitoring data for use by the Advanced Reactor Technologies (ART) Technology Development Office (TDO) Program for research and development activities required to design and license the first HTR nuclear plant. Qualified data meet 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. All thermocouples (TCs) have functioned throughout the AGC-4 experiment. All temperature data are Qualified for use by the ART TDO Program. Argon, helium, and total gas flow data were within expected ranges and are Qualified for use by the ART TDO Program. Discharge gas line moisture values were consistently low during cycle 157D. At the start of cycle 158A, gas moisture briefly spiked to over 600 ppmv and then declined throughout the cycle. Moisture values are within the measurement range of the instrument and are Qualified for use by the ART TDO Program. 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. Stack displacement increased consistently throughout the first two cycles with total displacement ranging from 0.4 to 0.8 in. 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 twice. All stacks were raised successfully each time. The load and displacement data are Qualified for use by the ART TDO Program.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Towards AI Based Data Classification for Decision Making During Testing

During the development of high-consequence items, test systems should be capable of differentiating between test failures resulting from narrowly missing requirements versus those indicating potentially catastrophic faults. In many instances, classifying the data corresponds to simply identifying whether measured waveforms have approximately the anticipated shape. Cast in this light, the problem reduces to converting raw data into a form optimal for use with neural network classifiers. This manuscript investigates different means of representing raw data for image classification. Raw data plots and Short Time Fourier Transform (STFT) spectrograms are classified by both custom built, small-scale, Convolution Neural Networks (CNN) and open-source, multi-million parameter, pre-trained deep CNNs. In the case of time varying frequency content, the STFTs provide images with greater detail and can be accurately classified with simpler networks. This requires less memory and runs faster than classifying the raw data using the more sophisticated options—making STFTs optimal for applications with memory constraints. STFTs are not a panacea. In some cases the time-domain signal contains useful information that should not be discarded. Rather than using raw data or STFTs, the images can be constructed from both by using red and green channels of an RGB image to visualize the real and imaginary components of the transform, with the raw data occupying the blue channel.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

False positive PSMA PET for tumor remnants in the irradiated prostate and other interpretation pitfalls in a prospective multi-center trial

Readers need to be informed about potential pitfalls of [ 68 Ga]Ga-PSMA-11 PET interpretation. Here we report [ 68 Ga]Ga-PSMA-11 PET findings discordant with the histopathology/composite reference standard in a recently published prospective trial on 635 patients with biochemically recurrent prostate cancer. Consensus reads were false positive in 20 regions of 17/217 (8%) patients with lesion validation. Majority of the false positive interpretations (13 of 20, 65%) occurred in the context of suspected prostate (bed) relapse (T) after radiotherapy ( n = 11); other false positive findings were noted for prostate bed post prostatectomy (T, n = 2), pelvic nodes (N, n = 2), or extra pelvic lesions (M, n = 5). Major sources of false positive findings were PSMA-expressing residual adenocarcinoma with marked post-radiotherapy treatment effect. False negative interpretation occurred in 8 regions of 6/79 (8%) patients with histopathology validation, including prostate (bed) ( n = 5), pelvic nodes ( n = 1), and extra pelvic lesions ( n = 2). Lesions were missed mostly due to small metastases or adjacent bladder/urine uptake.[ 68 Ga]Ga-PSMA-11 PET at biochemical recurrence resulted in less than 10% false positive interpretations. Post-radiotherapy prostate uptake was a major source of [ 68 Ga]Ga-PSMA-11 PET false positivity. In few cases, PET correctly detects residual PSMA expression post-radiotherapy, originating however from treated, benign tissue or potentially indolent tumor remnants.

Radiology, Nuclear Medicine & Medical Imaging↗
DOE OSTI2020

The CYBER security – Competency Health and Maturity Progression (CYBER-CHAMP) model: Extending the National Initiative for Cybersecurity Education (NICE) Framework Across Organizational Security

Problem Statement: There is a pervasive talent deficit in the cybersecurity industry that prevents employers from being able to fill their open positions efficiently. A holistic approach to security is required to ensure organizations have adequate prevention and response capabilities in case of a cyberattack. Specifically, industrial control systems (ICS’s) and their operational technology (OT) components have become a constant target for cyberattacks. Research Questions: It is proposed that the NICE Framework should be extended in the following areas: 1) Include guidance regarding the job roles and competencies for both IT and OT professionals. 2) Offer step-by-step solutions, based on the work role mappings from the NICE Framework, to increase cybersecurity through employee training and education. 3) Provide a streamlined, lifecycle approach to building a cybersecurity program. Contribution: The CYBER security – Competency Health and Maturity Progression (CYBER-CHAMP©) model provides a customized solution for businesses to understand their education gaps in organizational security and target areas for improvement. Rationale: The Framework for Improving Critical Infrastructure Cybersecurity v1.1 addresses ICS but does not offer a measurement of cybersecurity maturity or clear methods to ascertain an organization’s current risk profile. In Phases 1 and 5 of the model, measurements are provided to help an organization build their current and target risk profiles. The NICE framework provides a structure for planning an IT cybersecurity workforce, but the OT aspects of cybersecurity are only briefly discussed. The model uses Phases 2-3 to examine the competencies of an organization’s workforce, which includes both IT and OT roles. Current frameworks do not offer next steps to increase an organization’s cybersecurity. During Phase 4, employees’ roles are mapped to training, education, and/or certifications from common vendors. Investigative Approach: The model provides measurements and metrics for both an organization’s status and continual improvement. This improvement methodology includes guidance for creating an overall strategic plan for security improvement via products designed to increase an organization’s operational readiness through workforce competency health. Lessons Learned: Depending on who was participating, there were contradicting answers given in Phase 1 due to different security cultures in the organization. This revelation has influenced the steps listed in the User’s Guide, where Phase 1’s first recommended step is to assemble a team that champions the facilitation and implementation of the model in the organization. During Phase 2, the discovery was made that organizations may be missing roles that are necessary to perform critical cybersecurity functions. By understanding the functional roles and competencies needed, they can contract or hire cybersecurity help to fill these gaps. Implications: Using the model, organizations can discuss quantitative measures for improvement as a business case for advancing their security program. Future research can validate and extend the present theory and model to a variety of environments. It is of interest to investigate additional security roles and knowledge domains that are used to build standardized cybersecurity curriculum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Hygrothermal Material Properties for Soils in Building Science

Hygrothermal performance of soils coupled to buildings is complicated because of the dearth of information on soil properties. However they are important when numerical simulation of coupled heat and moisture transport for below-grade building components are performed as their temperature and moisture content has an influence on the durability of the below-grade building component. Soils can be classified by soil texture. According to the Unified Soil Classification System (USCA), 12 different soils can be defined on the basis of three soil components: clay, sand, and silt. This study shows how existing material properties for typical American soils can be transferred and used for the calculation of the coupled heat and moisture transport of building components in contact with soil. Furthermore a thermal validation with field measurements under known boundary conditions is part of this study, too. Field measurements for soil temperature and moisture content for two specified soils are carried out right now under known boundary conditions. As these field measurements are not finished yet, the full hygrothermal validation is still missing

36 MATERIALS SCIENCE↗
NASA NTRS1999

Loss tolerant speech decoder for telecommunications

A method and device for extrapolating past signal-history data for insertion into missing data segments in order to conceal digital speech frame errors. The extrapolation method uses past-signal history that is stored in a buffer. The method is implemented with a device that utilizes a finite-impulse response (FIR) multi-layer feed-forward artificial neural network that is trained by back-propagation for one-step extrapolation of speech compression algorithm (SCA) parameters. Once a speech connection has been established, the speech compression algorithm device begins sending encoded speech frames. As the speech frames are received, they are decoded and converted back into speech signal voltages. During the normal decoding process, pre-processing of the required SCA parameters will occur and the results stored in the past-history buffer. If a speech frame is detected to be lost or in error, then extrapolation modules are executed and replacement SCA parameters are generated and sent as the parameters required by the SCA. In this way, the information transfer to the SCA is transparent, and the SCA processing continues as usual. The listener will not normally notice that a speech frame has been lost because of the smooth transition between the last-received, lost, and next-received speech frames.

Prieto, Jr., Jaime L.↗
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 OSTI2024

The hypernuclear physics program at Jefferson Lab

Missing mass spectroscopy of Λ hypernuclei using the (e, e' K⁺) re action has been performed in the past at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) by several experiments in Halls A and C. A new experimen tal campaign is expected to start running in 2026 in Hall C and to provide the first study of the isospin dependence in medium-mass hyperisotopes by populating $^{40}_Λ{K}$ and $^{48}_Λ{K}$ using isotopically enriched calcium targets [E12-15-008]. During this cam paign, it will be possible to study Λ interactions in nuclear matter using a lead target [E12-20-013]. Solid-state targets made of lithium, beryllium, boron [LOI12-23-013], and aluminum [LOI12-23-016] are considered to be included in the campaign. The use of the HKS and HES spectrometers together with thin target foils and high beam currents leads to a sub-MeV energy resolution, significantly better than in hadron beam experiments. Valuable information on few-body hyperon systems would be gained if helium targets were used [E12-19-002]. Using an additional spectrometer for measuring the decay-pion spectra could give access to the binding energies of light hyperfragments [LOI12-23-011]. The measurement of precise and accurate en ergy spectra of different hyperisotopes probes the Λ-N interaction in nuclei including the Λ-N-N interaction. The latter is assumed to play a key role for the stiffness of the nuclear equation of state relevant for the stability of neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2015

2014 Space Radiation Standing Review Panel

The 2014 Space Radiation Standing Review Panel (from here on referred to as the SRP) participated in a WebEx/teleconference with members of the Space Radiation Program Element, representatives from the Human Research Program (HRP), the National Space Biomedical Research Institute (NSBRI), and NASA Headquarters on November 21, 2014 (list of participants is in Section XI of this report). The SRP reviewed the updated Research Plan for the Risk of Cardiovascular Disease and Other Degenerative Tissue Effects from Radiation Exposure (Degen Risk). The SRP also received a status update on the Risk of Acute and Late Central Nervous System Effects from Radiation Exposure (CNS Risk), the Risk of Acute Radiation Syndromes Due to Solar Particle Events (ARS Risk), and the Risk of Radiation Carcinogenesis (Cancer Risk). The SRP thought the teleconference was very informative and that the Space Radiation Program Element did a great job of outlining where the Element is with respect to our state of knowledge on the risks of carcinogenesis, central nervous system effects, and the risk of cardiovascular disease and other degenerative tissue effects from exposure to space radiation. The SRP was impressed with the quality of research that is being conducted and the progress the Space Radiation Program Element has made in the past year. While much work has been done, the SRP had a few remaining questions regarding the broad applicability of these findings to a manned deep space mission (in terms of cognitive function, the paradigms were still hippocampal based and also using Alzheimer disease models). The SRP believes that NASA should consider developing an approach to follow astronauts long-term (beyond retirement) for potential side-effects/risks of space exposure that may be unknown. Radiation toxicities often occur decades after exposure, and potential consequences would be missed if intensified exams stop after retirement of the astronauts. In addition, while cancer is one consequence of radiation exposure that is monitored, potential other side effects (CNS, Alzheimer Disease, loss of cognitive function, etc.) are not included in long-term studies and would be missed. Inclusion of long-term data would be of benefit to the astronauts themselves who have given their service to the corps but also to future astronauts and the future of space exploration.

Steinberg, Susan↗
NASA NTRS2019

TPSAS-NF1676L-34013-DND

Currently, many experiments pursuing comprehensive characterization of the atmosphere include coordinated observations by both lidar and polarimeters in order to obtain important complimentary information about aerosol properties. The most advanced passive observations by space-based multi-angle polarimeters are sensitive to the properties of aerosol in total atmospheric column, but have very limited sensitivity to vertical structure of the atmosphere. Polarimeter observations can be used not only for retrieval of aerosol optical thickness, but also for deriving microphysical information about aerosol particle shape, size distribution, complex refractive index, and the properties of underlying surface (Dubovik et al., 2019). In a contrast, the lidar observations of atmospheric responses from different altitudes to laser pulses are designed to provide vertical profiles of atmospheric characteristics. Here we present the recent advancement in GRASP algorithm (Generalized Aerosol Retrieval of Atmospheric and Surface Properties) (Dubovik et al., 2011, 2014) that allows simultaneous inversion of co-incident lidar and polarimeter spaceborne observations and derives a united set of vertically resolved aerosol and surface parameters. Such synergetic retrieval is an extension to satellite data of the approach for synergetic processing of active and passive measurements developed earlier by (Lopatin et al., 2013) for ground-based observations. Another addition to these developments is the inclusion of Raman-shifted and volume depolarization backscattering observations that improve sensitivity to the vertical properties of aerosol, while polarimetric observations provide sufficient constraints on aerosol type and loading that generally are missing in lidar signals. The potential and limitations of such synergetic processing is illustrated by application to co-incident PARASOL and CALIPSO data.

Anton Lopatin↗
DOE OSTI2021

43-0434 Bridge Inspection Report 2021

The documentation includes the following: 1. 2021 NMDOT Bridge Inspection Report including Element Level Data Collection (in digital formats prepared by NMSU)--conforms to the National Bridge Inspection Standards and AASHTO Manual for Bridge Element Inspection; 2. 2021 Supplemental Report (in digital formats prepared by NMSU)--provides detailed information related to current condition of major bridge components; 3. 2021 Inspection Pictures (in digital format prepared by NMSU); 4. 2021 Delamination Map (in digital format prepared by LANL). During the 2021 inspection, three critical findings were reported to our LANL contact, Mr. Jonathan Stein, by text and/or email on June 26, 2021. 1. The south joint of the bridge had a modular section of the joint that could potentially come loose during the passing of vehicles. This was reported as a critical finding for safety. If the modular section becomes dislodged or deformed it could pose a serious hazard that could result in a punctured tire to vehicles, motorcyclists and/or bicyclist causing drivers/riders to lose control; 2. The bracket plate located at the north end of the bridge on the pedestrian walkway was corroded through and provides little protection to pedestrians and bicyclists. This was reported as a critical finding for safety to prevent injuries to people; 3. The north approach rail has three missing posts. These posts help ensure that traffic is redirected and the energy is absorbed by the rail. This was reported as a critical finding for safety. Additionally, the approach rail is on a curve with a nearby drop off. Immediate repair is recommended. Based on the 2021 inspection, the bridge deck is rated in "fair" condition. The chain drag performed on the deck identified several areas with delamination that are concentrated near the expansion joints, in the closure joint of the deck near the bridge centerline, and at the south end of the northbound lanes. The chain drag performed during the 2021 inspection revealed 215,333 sq. in. (1495 sq. ft) of delaminations and patched areas (not including the sidewalk). This is approximately a 600% increase from 2019. It is recommended that the delaminations and spalls with exposed rebar be repaired. The "delaminated area" map for the 2021 inspection is provided in the supplemental report.

42 ENGINEERING↗
DOE OSTI2017

Order priors for Bayesian network discovery with an application to malware phylogeny

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges) in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.

97 MATHEMATICS AND COMPUTING↗