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At least 271 records · Page 15

Three-Dimensional In Situ Observations of Polycrystalline Microstructure Evolution During Directional Solidification of Transparent Alloys Aboard the ISS and Quantitative Comparison with Numerical Modeling

Cellular/dendritic microstructures formed during solidification have a crucial influence on the mechanical properties of a wide range of structural alloys. By minimizing the amount of gravity-induced convection in the liquid, directional solidification experiments using transparent organic alloys conducted in the DECLIC-DSI onboard the International Space Station have provided unique 3D in situ observations of the spatiotemporal evolution of the solid-liquid interface during the formation of cellular and dendritic microstructures under purely diffusive growth conditions. Those observations have made it possible to perform benchmark quantitative comparisons with the predictions of state-of-the-art phase-field simulations of microstructure formation in 3D on experimentally relevant length and time scales. This talk will report quantitative comparisons between microgravity experiments and phase-field simulations in succinonitrile-camphor alloys of two different compositions, which shed new light on the selection of dendritic array structures, and on roles of macroscopic curvatures and subgrain boundaries between grains with a small misorientation with respect to the temperature gradient in the spatiotemporal evolution of the primary cellular spacing.

Kaihua Ji↗

Developing Mass Spectrometry for Water Quantitation and Volatiles Analysis from In-Situ Regolith

With a revived focus to create a sustainable hu-man presence on the moon, and in preparation for future Mars exploration, it is imperative that all resources are utilized to their fullest potential [1]. In-Situ Resource Utilization (ISRU) will be critical for future mission success as it would enable in-dependent operation of missions while reducing the dependence on the complex supply chain created between the Earth, the moon and Mars. One of the most critical resources that has been identified for ISRU on the lunar surface is water [2]. Water is a versatile resource that can be used in various space operations, such as ra-diation shielding and conversion to oxygen (O2) for propellant [3,4]. One of the most water rich resources is thought to be within the regolith lo-cated in the permanently shadowed regions (PSR) of the Moon; several upcoming missions, such as PRIME-1 and VIPER, are already sched-uled to confirm this hypothesis [5,6]. However, there are currently no missions planned to quanti-fy the abudance of water at these regions. The quantity of water contained in the ice will inform and help the development of future ISRU plants and operation. Water and other volatile gases can be detect-ed upon controlled heating of icy lunar regolith for an accurate quantification of water. This method is similar to thermogravimetric analysis, which was used to analyze Apollo lunar regolith sam-ples. However, losses via sublimation/evaporation or contamination may have occurred with the samples due to the transit and exposure to the terrestrial environment. Furthermore, water would not be expected for these samples since they were not collected from a PSR. Thus, for more accurate results, icy lunar regolith should be ana-lyzed in situ to provide the most representative composition of both water and other volatile gas-es. The Light Water Analysis and Volatile Extract (LightWAVE) project aims to address this knowledge gap. A system has been developed to collect, heat and analyze evolved gases from lu-nar regolith on the lunar surface. The gases will be analyzed by a modified commercial off the shelf (COTS) residual gas analyzer (RGA) quad-rupole mass spectrometer. Evolved gases from heated regolith samples can be identified by the observed mass-to-charge (m/z) ratios, and the peak intensities correlate to the abundances of the observed gases for quantitation. Therefore, our group is developing a calibration methodology utilizing a COTS RGA to quantitate water from in-situ regolith samples on the lunar surface. The partial pressure of water and ideal gas law will be used to quantify the total water evolved from a regolith sample. Here we present our methodol-ogy for the design and calibration for water quan-titation using a COTS RGA.

Nilab Azim↗

An Approach to Quantitative Risk Assessment for Combined Spaceflight Hazards: Evaluating the Impact of Short Sleep Durations on Space Crew Cardiovascular Health

Astronauts embarking on long-duration missions will be exposed to multiple spaceflight hazards including radiation, isolation and confinement, distance from Earth, hostile closed environments, and altered gravity. These hazards pose health risks to the crew in-mission and postflight, including risks to cardiovascular health. For radiation, quantitative risk models have been developed that are based on large-scale epidemiological evidence from exposed terrestrial populations, which are extrapolated to account for the difference in radiological effectiveness between ground-based and in-flight exposures. •Cardiovascular diseases (CVD) are multifactorial, therefore multiple risk factors can influence disease risk estimates. •Astronauts with spaceflight experience is a very small population. •To overcome limitations of cohort, population data from presumed equivalent stressors on Earth can be used to quantitatively assess possible risks. •Sleep disruption and short sleep duration are known consequences of spaceflight and are also established risk factors for cardiovascular disease on earth (Pateletal.,2020). •Coronary Heart Disease (CHD), Myocardial Infarction (MI), and stroke are negative health effects due to short sleep durations and sleep disruptions (Yinetal.,2017); (Cappuccio et al., 2010). •A combined CVD risk model including spaceflight stressor such as sleep, stress, radiation, etc.) will provide more precise estimate of risks.

Spaceflight Hazards↗

Quantitative Highlights of 20 years Aqua Data Archive and Data Usage

NASA’s Aqua satellite carries six Earth-observing instruments Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Advanced Microwave Sounding Unit (AMSU), Clouds and the Earth’s Radiant Energy System (CERES), Humidity Sounder for Brazil (HSB) and Moderate Resolution Imaging Spectroradiometer (MODIS). Currently only four of six instruments are collecting data, two instruments that stopped transmitting data are AMSR-E that suffered a major anomaly in October 2011 and was powered off in March 2016 while as HSB failed in February 2003. NASA’s Earth Science Data and Information System (ESDIS) Project makes these data, along with derived products, available to worldwide data users. Since the launch of Aqua on May 4, 2002, more than 10,000 data products have been archived and distributed by NASA-funded Distributed Active Archive Centers (DAACs) that are part of NASA’s Earth Observing System Data and Information System (EOSDIS). At the end of the 2021 Fiscal Year with over 100,000 orbits data, about 1,000 Aqua data products constituted almost 16.5 % of the entire EOSDIS data archive volume (8.6 PB out of approximately 55.2 PB), and 7.5 PB of Aqua data were distributed to over half-a-million public users worldwide. By categorizing the Aqua data products and their distribution, we can get a quantitative assessment of Aqua data usage. NASA’s ESDIS Project has collected archive, distribution, and user information from EOSDIS data users since February 2000. These metrics are available through the ESDIS Metrics System (EMS). EMS information is stored in a relational database from which quantitative metrics of Aqua data use can be retrieved and analyzed. The purposes of this study are to: 1) perform a comprehensive investigation of the 20-year trend in the archive and distribution of Aqua data products; 2) identify and characterize data product usage over the last 20 years; and 3) identify and characterize the global user community for these data. In addition to revealing how Aqua data use has evolved over time, the results of this study provide insights on identifying the various user communities for different kinds of Earth science data products. Also, because of the enormous quantity of data handled by EOSDIS DAACs, the study provides guidance of the requirements for future data systems that will be needed to effectively and efficiently handle the ever-increasing amounts of Earth science data produced by future (and ongoing) Earth science missions.

Lalit Wanchoo↗

Quantitative 3D Textural and Petrofabric Analysis of the Northwest Africa 10645 Nakhlite Using X-Ray Computed Tomography

Martian meteorites are currently the only samples available from Mars to study and are critical for elucidating variability in martian igneous processes over time [e.g., 1]. Quantifying igneous textures and fabrics can help us understand how rocks are formed and emplaced [e.g., 2]. These features are innately three dimensional (3D) and are often strongly heterogeneous in cumulate rocks, like the nakhlites and poikilitic shergottites [2–3], where there can be substantial textural variations between and within individual samples. However, most quantitative textural and fabric analyses on these samples have been limited to two dimensions through measurements made on polished petrographic thin sections. Thus, 3D petrographic measurements are imperative for both representative sample characterization and accurately interpreting magmatic processes. The emplacement of martian meteorites at or near the surface of Mars (i.e., extrusive or intrusive, respectively) remains enigmatic due to the innate lack of geologic context [e.g., 1], but conducting 3D quantitative textural and fabric analyses can help elucidate emplacement mechanisms and settings on Mars.

S. Ramsey↗

Quantitative Holdup Determinations Using Coded-Aperture Gamma-Ray Imaging

Passive gamma-ray imaging can be used to create images of distributed nuclear materials. Inherently quantitative, the images provide a means to directly determine the amount of nuclear material in the imager’s field of view. However, to take advantage of quantitative imaging, one must correct for changes to the imager’s efficiency across the image. This paper presents work on detailed calibration of a coded-aperture imager based on a portable, mechanically cooled, high-purity germanium detector. This enables the use of gamma-ray imaging as a tool to determine nuclear holdup. By applying the calibrations to images of small amounts of distributed 235U, quantity estimates within a few percent of the actual amounts present were obtained, validating the approach.

Ziock, Klaus-Peter↗

Workshop Report: 2021 International Symposium of Quantitative Codesign of Supercomputers

This report provides general information about the First International Symposium on the Quantitative Design of Supercomputers (SQCS). This new workshop was held in conjunction with Supercomputing ’21 on November 19, 2021, in St Louis Missouri. The symposium aims at combining two methodologies—collaborative codesign and data-driven analysis—to realize the potential of supercomputing more fully. We refer to the design solutions that rely on intelligence from data-driven insights across applications, systems, system software, workflows, and facilities as quantitative codesign of supercomputers.

Jones, Terry↗

Workshop Report: 2022 International Symposium of Quantitative Codesign of Supercomputers

This report provides general information about the Second International Symposium on the Quantitative Design of Supercomputers (SQCS). This new workshop was held in conjunction with Supercomputing ’22 on November 13, 2022, in Dallas Texas. The symposium aims at combining two methodologies—collaborative codesign and data-driven analysis—to realize the potential of supercomputing more fully. We refer to the design solutions that rely on intelligence from data-driven insights across applications, systems, system software, workflows, and facilities as quantitative codesign of supercomputers.

Jones, Terry↗

Data Collection and Analysis Challenges and Mitigation Strategies for Quantitative Human Factors Research Studies in Nuclear Power Plant Modernization

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program Plant Modernization Pathway is conducting targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. LWR fleet. In this effort, the application of human factors engineering (HFE) provides an important role in ensuring new digital plant technologies enable broad innovation and business improvement with continued operational safety. Evaluation is a key activity in HFE, which often occurs iteratively through the system design lifecycle. While qualitative methods are important in collecting information of how users perform tasks through observations, quantitative methods are equally important in assessing system design based on performance. In collecting and analyzing this quantitative data, there are notable challenges in the nuclear HFE domain that may threaten the validity and reliability of the inferences made in these studies. Notable challenges include small sample size and limited resources, large error variance and small effect size, an “adding test features to losing degrees of freedom” dilemma, non-normal distribution, and heterogeneity of variance. The results in control room usability studies are often statistically non-significant, which makes it hard to interpret. This work discusses these challenges across different scientific viewpoints and provides real-world examples of these challenges in practice. Collectively, the objective of this work is to position these challenges to the larger data science community as a means of identifying future opportunities to address these issues.

99 GENERAL AND MISCELLANEOUS↗

Quantitative phase microscopy monitors subcellular dynamics in single cells exposed to nanosecond pulsed electric fields

A substantial body of literature exists to study the dynamics of single cells exposed to short duration (<1 μs), high peak power (~1 MV/m) transient electric fields. Much of this research is limited to traditional fluorescence-based microscopy techniques, which introduce exogenous agents to the culture and are only sensitive to a single molecular target. Quantitative phase imaging (QPI) is a coherent imaging modality which uses optical path length as a label-free contrast mechanism, and has proven highly effective for the study of single-cell dynamics. In this work, we introduce QPI as a useful imaging tool for the study of cells undergoing cytoskeletal remodeling after nanosecond pulsed electric field (nsPEF) exposure. In particular, we use cell swelling, dry mass and disorder strength measurements derived from QPI phase images to monitor the cellular response to nsPEFs. We hope this demonstration of QPI's utility will lead to a further adoption of the technique for the study

59 BASIC BIOLOGICAL SCIENCES↗

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↗

From cytoplasm to lumen—mapping the free pools of protein subunits of three photosynthetic complexes using quantitative mass spectrometry

The phycobilisome (PBS) captures light energy and transfers it to photosystem I (PSI) and photosystem II (PSII). Which and how many copies of protein subunits in PBSs, PSI, and PSII remain unbound in thylakoids are unknown. Here, quantitative mass spectrometry (QMS) was used to quantify substantial pools of free extrinsic subunits of PSII and PSI. Interestingly, the membrane intrinsic PsaL is 3-fold higher than PsaA/B. This scenario complements the static structures of these complexes as revealed by X-ray crystallography and cryo-EM. Furthermore, the ratios of ApcG and photoprotective OCP over PBS indicate a pool of extra ApcG. The 2.5 ratio of CpcG-PBS over CpcL-PBS improves our understanding of these light-harvesting complexes involved in energy capture and photoprotection in cyanobacteria.

cyanobacteria↗

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. Here, the lack of reliability data for bulk liquid hydrogen (LH 2 ) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH 2 storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH 2 storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH 2 . Based on this analysis, scenario and reliability data needs to add LH 2 -related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.

08 HYDROGEN↗

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗

Unveiling decaying mechanism through quantitative structure-activity relationship in electrolytes for lithium-ion batteries

Understanding the decaying mechanism in lithium-ion batteries (LIBs) is critical to establishing a stable electrolyte system. Despite the advent of various novel electrolyte solvents designated for high-voltage LIBs, their working principles are not fully understood. Currently, oxidative decomposition of electrolytes is believed to be the major cause of capacity fade, and tremendous effort has been devoted to discovering a new electrolyte with enhanced anodic stability. However, the oxidative decomposition process cannot solely explain the rapid decay of some electrolyte systems with intrinsic high anodic stability when used with a high-nickel layered oxide cathode such as LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622). In this report, a study of the quantitative structure-activity relationship was conducted to deepen the mechanistic understanding of the decay in high-voltage LIBs. Here, the results obtained from the newly introduced molecular pair analysis and linear free-energy relationship (LFER) studies were highly consistent with the solvation-involved decaying mechanism in a high-nickel layered oxide cathode cycling at high voltage (> 4.5 V vs. Li/Li + ). There was no evidence correlating the solvation ability of electrolyte solvents with the decay of a high-nickel layered oxide cathode cycling at a relatively low voltage (< 4.3 V vs. Li/Li + ), nor with the high-voltage spinel cathode LiNi 0.5 Mn 1.5 O 4 (LNMO). Undoubtedly, the unveiled mechanistic insight provides a critical guideline for the development of an appropriate electrolyte system targeting different high-voltage cathode materials.

25 ENERGY STORAGE↗

Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants

Digital instrumentation and control (DI&C) systems at nuclear power plants (NPPs) have many advantages over analog systems. They are proven to be more reliable, cheaper, and easier to maintain given obsolescence of analog components. However, they also pose new engineering and technical challenges, such as possibility of common cause failures (CCFs) unique to digital systems. Here this paper proposes a Platform for Risk Assessment of DI&C (PRADIC) that is developed by Idaho National Laboratory (INL). A methodology for evaluation of software CCFs in high safety-significant safety-related DI&C systems of NPPs was developed as part of the framework. The framework integrates three stages of a typical risk assessment—qualitative hazard analysis and quantitative reliability and consequence analyses. The quantified risks compared with respective acceptance criteria provide valuable insights for system architecture alternatives allowing design optimization in terms of risk reduction and cost savings. A comprehensive case study performed to demonstrate the framework's capabilities is documented here in this paper. Results show that the PRADIC is a powerful tool capable to identify potential digital-based CCFs, estimate their probabilities, and evaluate their impacts on system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Rapid Targeted Quantitation of Protein Overexpression with Direct Infusion Shotgun Proteome Analysis (DISPA-PRM)

While much effort has been placed on comprehensive quantitative proteome analysis, certain applications demand measurement of only a few target proteins from complex systems. Traditional approaches to targeted proteomics rely on nano-liquid chromatography (nLC) and targeted mass spectrometry (MS) methods, e.g., parallel reaction monitoring (PRM). However, the time requirement for nLC can limit throughput of targeted proteomics. To achieve rapid and high-throughput targeted methods, here we show that nLC separations can be eliminated and replaced with direct infusion shotgun proteome analysis (DISPA) using high-field asymmetric waveform ion mobility spectrometry (FAIMS) with PRM. We demonstrate application of DISPA-PRM for rapid targeted quantification of bacterial enzymes utilized in the production of biofuels by monitoring temporal expression in 72 metabolically engineered bacterial cultures in under 2.5 hours, with a measured dynamic range >1200-fold. Here, we conclude that DISPA-PRM presents a valuable innovative tool with results comparable to nLC-MS/MS, enabling fast and rapid detection of targeted proteins in complex mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major weakness is the potential performance drift of the LC-MS platform over time, which in turn limits its utility for analyzing large-scale sample sets. To address this, in this work we introduce an experimental and data analysis scheme based on a block-design with common controls within each block for enabling LC-MS-based large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller, and more manageable blocks, minimizing instrument drift and variability within a block. Furthermore, each designated block also contains common controls (or reference) samples for normalization within and across blocks. We demonstrated the effectiveness of this method by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials (ENMs) at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. The data revealed consistent quantification of proteins across all six blocks, as shown by highly stable quantification of house-keeping proteins in all samples and high levels of quantification correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes without potential ratio compression as often encountered with isobaric labeling. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

59 BASIC BIOLOGICAL SCIENCES↗