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At least 469 records · Page 26

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: B. A reduced model based on reversed-direction two point modeling

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter–erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding (Pitts et al 2019). Part A of the present study reports new results for largely the same ITER cases, confirming the strong correlation reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not as yet been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne (Ne s –1 ), and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In this part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction two point modeling, Rev2PM. The input to the reduced model is a value of the variable pair (T e,t @q ⊥,pk , Inj Ne )for a chosen case and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , the electron density at the X-point, n e,Xpt , etc. The reduced model was quantitatively characterized using one half of the code cases; it was then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus

Summary Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans ‐eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem‐born roots and base‐born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38‐mediated adventitious root formation. Protein–protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38‐regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.

54 ENVIRONMENTAL SCIENCES↗

STS-74/MIR Photogrammetric Appendage Structural Dynamics Experiment Preliminary Data Analysis

The Photogrammetric Appendage Structural Dynamics Experiment was designed, developed, and flown to demonstrate and prove measurement of the structural vibration response of a Russian Space Station Mir solar array using photogrammetric methods. The experiment flew on the STS-74 Space Shuttle mission to Mir in November 1995 and obtained video imagery of solar array structural response to various excitation events. The video imagery has been digitized and triangulated to obtain response time history data at discrete points on the solar array. This data has been further processed using the Eigensystem Realization Algorithm modal identification technique to determine the natural vibration frequencies, damping, and mode shapes of the solar array. The results demonstrate that photogrammetric measurement of articulating, nonoptically targeted, flexible solar arrays and appendages is a viable, low-cost measurement option for the International Space Station.

Gilbert, Michael G.↗

Robotic Subsurface Analyzer and Sample Handler for Resource Reconnaissance and Preliminary Site Assessment for ISRU Activities at the Lunar Cold Traps

Since the 1960s, claims have been made that water ice deposits should exist in permanently shadowed craters near both lunar poles. Recent interpretations of data from the Lunar Prospector-Neutron Spectrometer (LP- NS) confirm that significant concentrations of hydrogen exist, probably in the form of water ice, in the permanently shadowed polar cold traps. Yet, due to the large spatial resolution (45-60 Ian) of the LP-NS measurements relative to these shadowed craters (approx.5-25 km), these data offer little certainty regarding the precise location, form or distribution of these deposits. Even less is known about how such deposits of water ice might effect lunar regolith physical properties relevant to mining, excavation, water extraction and construction. These uncertainties will need to be addressed in order to validate fundamental lunar In Situ Resource Utilization (ISRU) precepts by 2011. Given the importance of the in situ utilization of water and other resources to the future of space exploration a need arises for the advanced deployment of a robotic and reconfigurable system for physical properties and resource reconnaissance. Based on a collection of high-TRL. designs, the Subsurface Analyzer and Sample Handler (SASH) addresses these needs, particularly determining the location and form of water ice and the physical properties of regolith. SASH would be capable of: (1) subsurface access via drilling, on the order of 3-10 meters into both competent targets (ice, rock) and regolith, (2) down-hole analysis through drill string embedded instrumentation and sensors (Neutron Spectrometer and Microscopic Imager), enabling water ice identification and physical properties measurements; (3) core and unconsolidated sample acquisition from rock and regolith; (4) sample handling and processing, with minimized contamination, sample containerization and delivery to a modular instrument payload. This system would be designed with three mission enabling goals, including: (1) a self-contained, low power, low mass, "black box'' configuration for operations from a lander, various classes of rovers or a surface-based platform with human assistance or robotic anchoring mechanisms; (2) reconfigurable and scalable sample handling for delivery to various types of instrumentation, depending on mission requirements; and (3) the use of advanced automation control and diagnostic techniques that will afford local human deployed, remote teleoperation and fully autonomous intelligent operations. Though a great deal of technology has been advanced toward these objectives, the SASH system faces significant design challenges, including the low gravity environment, various levels of autonomy in operations, radiation exposure, dust contamination, and temperature extremes and deltas. Significant input from the scientific and engineering communities, as well as a significant environmental testing program, will be required to guide the design process.

Gorevan, S. P.↗

Bragg curve spectroscopy for improved fission fragment identification

We report on the development of Bragg curve spectroscopy techniques to improve fission fragment identification in the measurement of independent fission product yields. The NIFFTE collaboration’s fissionTPC detector provides ionization energy and particle tracking information from neutroninduced fission targets. A joint effort between PNNL, LLNL, LANL, and the Colorado School of Mines is investigating the ionization profiles deposited by U-235, U-238, and Pu-239 fission products in this detector, with the goal of including additional stopping power information beyond a standard 2E analysis. The aim is to improve the determination of fragment atomic and mass numbers with this information, via methods such as parametric fits and machine learning techniques.

Fulsom, Bryan G.↗

The Zwicky Transient Facility Bright Transient Survey. III. BTSbot: Automated Identification and Follow-up of Bright Transients with Deep Learning

Abstract The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright ( m peak ≤ 18.5 mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection (“scanning”) to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5 yr of ZTF operations. We present BTSbot , a multimodal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼1 hr quicker than scanners). We also find that BTSbot is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. BTSbot has been integrated into Fritz and Kowalski , ZTF’s first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. Between 2023 December and 2024 May, BTSbot selected 609 sources in real time, 96% of which were real extragalactic transients. With BTSbot and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human time needed to scan.

Rehemtulla, Nabeel (ORCID:0000000256832389)↗

Identification of Risks to Eva Created By Ambient Lighting Conditions at the Lunar South Pole

In the coming years, NASA’s Artemis Campaign intends to return humans to the Moon, both to explore and to establish a permanent human presence. The targeted landing and habitation sites are near the Lunar South Pole (LSP). Compared to the middle latitudes where the Apollo landings occurred, the sun at the LSP is consistently low in the sky, creating a much more challenging visual experience. The NASA Engineering & Safety Center (NESC) is working to characterize the extremes in ambient illumination that astronauts will encounter at the LSP, and to help programs characterize the lighting systems and glare protection that will be required to conduct safe surface operations. This paper will describe the LSP natural environments, and efforts to simulate that visual experience. It will also explain the risks derived from the lighting environment for the mission goals currently planned, and the kinds of new capabilities both in simulation techniques and in surface equipment that will be required to support those mission goals.

Identification of Risks↗

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗

Los Alamos National Laboratory Nuclear Material Management and Storage Program: Storage Health Metrics

The Strategic Materials Sustainment Program (SMSP) supports activities needed to manage the National Nuclear Security Administration’s (NNSA) inventory of strategic materials. As part of the SMSP, the Nuclear Material Management and Storage (NMM&S) program at the Los Alamos National Laboratory (LANL) is responsible for: (1) safe and secure storage of the SMSP strategic materials and others, (2) analysis, forecasting, and management of accountable nuclear materials; and (3) disposition of nuclear material through the Office of Nuclear Materials Integration (ONMI). The nuclear material management (NMM) mission is to ensure efficient nuclear material management lifecycle activities at LANL. The storage program function includes the management of storage capabilities across the site, supply chain management of nuclear materials, storage requirements integration, and nuclear container management (i.e., procurement, compliance, and safety). This report identifies key performance indicators (KPI) and describes the criteria and metrics used to assess the health of the storage component of the NMM&S program. “Health” is the ability of a process, system, facility, or program to safely and reliably accomplish its required mission. A health assessment provides timely identification of significant risks to enable mission performance. Significant risks identified are most effectively mitigated, avoided, or eliminated by evaluating and coordinating with stakeholders to specifically target, document, and often proceduralize strategies directed towards risk reduction. An effective health assessment involves status measurements of specific metrics that are tied directly to representative KPIs for a program. This document will baseline the KPI, criteria, and specific metrics that will be used to measure the “health” of the LANL Storage Program (i.e., NMM is not included).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Feedstock-Conversion Interface Consortium: Failure Mode and Effects Analysis Summary Report (FY2022)

This report provides an overview of the development of failure modes and effects analysis (FMEA) and its implementation as a systematic criticality and risk assessment tool supporting a quality by design (QbD) approach for FCIC research. This report also provides a high-level overview of the results for the FMEA evaluation of two feedstock preprocessing system configurations: (1) generation of pine residue materials for high-temperature pyrolysis conversion and (2) generation of corn stover materials for low-temperature conversion using deacetylation and disc mechanical refining pretreatment for fermentation to hydrocarbons. For the results presented in this report, our FMEA interviews included two approaches. The first approach was to perform FMEA interviews for the entire system of unit operations giving a wholistic system level view. The second approach consisted of detailed interviews for each individual unit operation within the system allowing for a “deep dive” into the specific failures for the individual components within the configuration. These two approaches provide different resolutions of information. The FMEA results of this report were focused on failures associated with meeting critical quality attributes (CQAs) identified for the target conversion processes for each processed feedstock type. The information gathered through the FMEA interviews include estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score. The complete results of all FMEA interviews are provided in the Appendices of this report.

09 BIOMASS FUELS↗

Quantitative Analysis of Radar Returns from Insects

When a number of flying insects is low enough to permit their resolution as individual radar targets, quantitative estimates of their aerial density are developed. Accurate measurements of heading distribution using a rotating polarization radar to enhance the wingbeat frequency method of identification are presented.

Riley, J. R.↗

Acoustic target detection and classification using neural networks

A neural network approach to the classification of acoustic emissions of ground vehicles and helicopters is demonstrated. Data collected during the Joint Acoustic Propagation Experiment conducted in July of l991 at White Sands Missile Range, New Mexico was used to train a classifier to distinguish between the spectrums of a UH-1, M60, M1 and M114. An output node was also included that would recognize background (i.e. no target) data. Analysis revealed specific hidden nodes responding to the features input into the classifier. Initial results using the neural network were encouraging with high correct identification rates accompanied by high levels of confidence.

Robertson, James A.↗

Pancam Imaging of the Mars Exploration Rover Landing Sites in Gusev Crater and Meridiani Planum

The Mars Exploration Rovers carry four Panoramic Camera (Pancam) instruments (two per rover) that have obtained high resolution multispectral and stereoscopic images for studies of the geology, mineralogy, and surface and atmospheric physical properties at both rover landing sites. The Pancams are also providing significant mission support measurements for the rovers, including Sun-finding for rover navigation, hazard identification and digital terrain modeling to help guide long-term rover traverse decisions, high resolution imaging to help guide the selection of in situ sampling targets, and acquisition of education and public outreach imaging products.

Bell, J. F., III↗

Multi-Organization Multi-Discipline Effort Developing a Mitigation Concept for Planetary Defense

There have been significant recent efforts in addressing mitigation approaches to neutralize Potentially Hazardous Asteroids (PHA). One such research effort was performed in 2015 by an integrated, inter-disciplinary team of asteroid scientists, energy deposition modeling scientists, payload engineers, orbital dynamist engineers, spacecraft discipline engineers, and systems architecture engineer from NASAs Goddard Space Flight Center (GSFC) and the Department of Energy (DoE) National Nuclear Security Administration (NNSA) laboratories (Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratories (LLNL) and Sandia National Laboratories). The study team collaborated with GSFCs Integrated Design Centers Mission Design Lab (MDL) which engaged a team of GSFC flight hardware discipline engineers to work with GSFC, LANL, and LLNL NEA-related subject matter experts during a one-week intensive concept formulation study in an integrated concurrent engineering environment. This team has analyzed the first of several distinct study cases for a multi-year NASA research grant. This Case 1 study references the Near-Earth Asteroid (NEA) named Bennu as the notional target due to the availability of a very detailed Design Reference Asteroid (DRA) model for its orbit and physical characteristics (courtesy of the Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) mission team). The research involved the formulation and optimization of spacecraft trajectories to intercept Bennu, overall mission and architecture concepts, and high-fidelity modeling of both kinetic impact (spacecraft collision to change a NEAs momentum and orbit) and nuclear detonation effects on Bennu, for purposes of deflecting Bennu.

Planetary Defense↗

Failure Mode and Effects Analysis Summary Report

This report provides an overview of the development of failure modes and effects analysis (FMEA) and its implementation as a systematic criticality and risk assessment tool supporting a quality by design (QbD) approach for FCIC research. This report also provides a high-level overview of the results for the FMEA evaluation of two feedstock preprocessing system configurations: (1) generation of pine residue materials for high-temperature pyrolysis conversion and (2) generation of corn stover materials for low-temperature conversion using deacetylation and disc mechanical refining pretreatment for fermentation to hydrocarbons. For the results presented in this report, our FMEA interviews included two approaches. The first approach was to perform FMEA interviews for the entire system of unit operations giving a wholistic system level view. The second approach consisted of detailed interviews for each individual unit operation within the system allowing for a “deep dive” into the specific failures for the individual components within the configuration. These two approaches provide different resolutions of information. The FMEA results of this report were focused on failures associated with meeting critical quality attributes (CQAs) identified for the target conversion processes for each processed feedstock type. The information gathered through the FMEA interviews include estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score. The complete results of all FMEA interviews are provided in the Appendices of this report.

conversion↗

Spectroscopic study of a possible $Λnn$ resonance and a pair of $ΣNN$ states using the $(e,e'K^+)$ reaction with a tritium target

Here, a mass spectroscopy experiment with a pair of nearly identical high resolution spectrometers and a tritium target was performed in Hall A at Jefferson Lab. Utilizing the (e,e'K + ) reaction, enhancements, which may correspond to a possible $\Lambda$nn resonance and a pair of ΣNN states, were observed with an energy resolution of about 1.21 MeV (σ), although greater statistics are needed to make definitive identifications. An experimentally measured Λnn state may provide a unique constraint in determining the Λn interaction, for which no scattering data exist. In addition, although bound A = 3 and 4 Σ hypernuclei have been predicted, only an A = 4 Σ hypernucleus ($^4_Σ$He) was found, utilizing the (K - ,π - ) reaction on a 4 He target. The possible bound ΣNN state is likely a Σ 0 nn state, although this has to be confirmed by future experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Discovery and Identification of Dimethylsilanediol as a Contaminant in ISS Potable Water

In September 2010, analysis of ISS potable water samples was undertaken to determine the contaminant(s) responsible for a rise of total organic carbon (TOC) in the Water Processor Assembly (WPA) product water. As analysis of the routine target list of organic compounds did not reveal the contaminant, efforts to look for unknown compounds were initiated, resulting in discovery of an unknown peak in the gas chromatography/mass spectrometry (GC/MS) analysis for glycols. A mass spectrum of the contaminant was then generated by concentrating one of the samples and analyzing it by GC/MS in full-scan mode. Although a computer match of the compound identity could not be obtained with the instrument database, a search with a more up-to-date mass spectral library yielded a good match with dimethylsilanediol (DMSD). Inductively coupled plasma/mass spectrometry (ICP/MS) analyses showed abnormally high silicon levels in the samples, confirming that the unknown compound(s) contained silicon. DMSD was then synthesized to confirm the identification and provide a standard to develop a calibration curve. Further confirmation was provided by external direct analysis in real time time of flight (DART TOF) mass spectrometry. To routinely test for DMSD in the future, a quantitative method was needed. A preliminary GC/MS method was developed and archived samples from various locations on ISS were analyzed to determine the extent of the contamination and provide data for troubleshooting. This paper describes these events in more detail as well as problems encountered in routine GC/MS analyses and the subsequent development of high performance liquid chromatography and LC/MS/MS methods for measuring DMSD.

Rutz, Jeffrey A.↗

Does the identification of simple features require serial processing?

Several recent studies have shown performance decrements with increasing display size when background texture elements are present in a same-different feature discrimination task--a result that challenges the traditional notion that the identities of simple visual features are processed in parallel, preattentively. Four experiments are reported that explore the implications of these results. Experiment 1 replicates the recent studies but limits the generalizability of the results to small target numbers. Experiments 2 and 3 show that the observed performance decrements are not due to a serial or even limited-capacity, parallel process. Experiment 4 suggests that decision factors idiosyncratic to the use of texture elements in a same-different task are responsible for the effect. It is concluded that the identification of simple visual features proceeds in parallel, with unlimited capacity (i.e., preattentively).

Pattern Recognition, Visual↗