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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Small tensor product distributed active space (STP-DAS) framework for relativistic and non-relativistic multiconfiguration calculations: Scaling from 10 9 on a laptop to 10 12 determinants on a supercomputer

Despite the power and flexibility of configuration interaction (CI) based methods in computational chemistry, their broader application is limited by an exponential increase in both computational and storage requirements, particularly due to the substantial memory needed for excitation lists that are crucial for scalable parallel computing. Here, the objective of this work is to develop a new CI framework, namely, the small tensor product distributed active space (STP-DAS) framework, aimed at drastically reducing memory demands for extensive CI calculations on individual workstations or laptops, while simultaneously enhancing scalability for extensive parallel computing. Moreover, the STP-DAS framework can support various CI-based techniques, such as complete active space (CAS), restricted active space, generalized active space, multireference CI, and multireference perturbation theory, applicable to both relativistic (two- and four-component) and non-relativistic theories, thus extending the utility of CI methods in computational research. We conducted benchmark studies on a supercomputer to evaluate the storage needs, parallel scalability, and communication downtime using a realistic exact-two-component CASCI (X2C-CASCI) approach, covering a range of determinants from 10 9 to 10 12 . Additionally, we performed large X2C-CASCI calculations on a single laptop and examined how the STP-DAS partitioning affects performance.

Complete-active space self-consistent field↗

The evolution of analytical techniques for multiplex analysis of protein biomarkers

Introduction: The landscape of biomarker development has evolved with advanced analytical technologies, particularly affinity- and mass spectrometry-based techniques. These advancements have deepened our understanding of disease mechanisms, enabling the development of precise diagnostic tools and personalized medicine. Protein biomarkers, which play pivotal roles in biological processes, have become invaluable in diagnosing and monitoring diseases, aided by their presence in various biological samples and the availability of established detection methods. Areas covered: This review covers the role of protein biomarkers in clinical practice, the development and dimensionality of protein biomarkers, advancements in detection technologies, a comparison of these technologies, and future directions in biomarker discovery and disease mechanism elucidation. Expert opinion: Advances in biomarker technologies have the potential to transform diagnostics and personalized treatment but face challenges such as high costs and technical complexity. Enhancing reproducibility and integrating multi-omics approaches may offer better insights. In conclusion, the field should evolve toward high-throughput, automated methods, continuously adapting research, and clinical practices.

59 BASIC BIOLOGICAL SCIENCES↗

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

54 ENVIRONMENTAL SCIENCES↗

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

Abstract Background and Objectives The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations’ heat exposure in the early (1995–2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. Research Design and Methods We estimate older adults’ heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. Results Population aging and rising temperatures are documented throughout the United States, with particular “hotspots” in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. Discussion and Implications Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

60 APPLIED LIFE SCIENCES↗

Inverse modeling of circular lattices via orbit response measurements in the presence of degeneracy

The number and location of beam position monitors (BPMs) and steerers with respect to the quadrupoles in a circular lattice can lead to degeneracy in the context of fitting linear optics and extracting lattice information from measured closed orbits. Furthermore, the measurement uncertainties due to the imperfection of BPMs and steerers can be propagated by the fitting process in ways that prohibit the successful extraction of discrepancies between lattice elements in the real machine and their description in the corresponding model. We systematically studied the influence of the placement of BPMs and steerers on the reconstruction of linear optics and corresponding lattice information. The derivative of orbit response coefficients with respect to the quadrupole strengths, the Jacobian, is derived as an analytical formula. This analytical version of the Jacobian is used to further derive the theoretical limitations of fitting linear optics from closed orbits in terms of the placement of BPMs and steerers. It is further demonstrated that when evaluating the Jacobian during the fitting procedure, the analytical version can be used in place of the conventional finite-difference computation. This allows for greatly improved efficiency when computing the Jacobian during each iteration of the fitting procedure. The approach is tested with large-scale simulations and the findings are verified by measurement data taken on SIS18 synchrotron at GSI Helmholtz Centre for Heavy Ion Research. The presented methods are of general nature and can be applied to other accelerator lattices as well. The fitting procedure by using the analytical Jacobian is tested in conjunction with various methods for mitigating quasidegeneracy and the results agree with those obtained by using the conventional Jacobian via finite-difference approximation.

47 OTHER INSTRUMENTATION↗

CAN-D: A Modular Four-Step Pipeline for Comprehensively Decoding Controller Area Network Data

Controller area networks (CANs) are a broadcast protocol for real-time communication of critical vehicle subsystems. Original equipment manufacturers of passenger vehicles hold secret their mappings of CAN data to vehicle signals, and these definitions vary according to make, model, and year. Without these mappings, the wealth of real-time vehicle information hidden in the CAN packets is uninterpretable, severely impeding vehicle-related research, including CAN cybersecurity and privacy studies, aftermarket tuning, efficiency and performance monitoring, and fault diagnosis to name a few. Guided by the four-part CAN signal definition, we present CAN-D (CAN-Decoder), a modular, four-step pipeline for identifying each signal's boundaries (start bit and length), endianness (byte ordering), signedness (bit-to-integer encoding), and by leveraging diagnostic standards, augmenting a subset of the extracted signals with meaningful, physical interpretation. En route to CAN-D, we provide a comprehensive review of the CAN signal reverse engineering research. All previous methods ignore endianness and signedness, rendering them incapable of decoding many standard CAN signal definitions. Incorporating endianness grows the search space from 128 to 4.72E21 signal tokenizations and introduces a web of changing dependencies. In response, we formulate, formally analyze, and provide an efficient solution to an optimization problem, allowing identification of the optimal set of signal boundaries and byte orderings. In addition, we provide two novel, state-of-the-art signal boundary classifiers—both of which are superior to previous approaches in precision and recall in three different test scenarios—and the first signedness classification algorithm, which exhibits a $>$ 97% F-score. Altogether, CAN-D is the only solution with the potential to extract any CAN signal that is also the state of the art. In evaluation on 10 vehicles of different makes, CAN-D's average $\ell ^1$ error is five times better (81% less) than all previous methods and exhibits lower average error, even when considering only signals that meet prior methods’ assumptions. Finally, CAN-D is implemented in lightweight hardware, allowing for an on-board diagnostic (OBD-II) plugin for real-time in-vehicle CAN decoding.

42 ENGINEERING↗

Gaia: An AI-enabled genomic context–aware platform for protein sequence annotation

Protein sequence similarity search is fundamental to biology research, but current methods are typically not able to consider crucial genomic context information indicative of protein function, especially in microbial systems. Here, we present Gaia (Genomic AI Annotator), a sequence annotation platform that enables rapid, context-aware protein sequence search across genomic datasets. Gaia leverages gLM2, a mixed-modality genomic language model trained on both amino acid sequences and their genomic neighborhoods to generate embeddings that integrate sequence-structure-context information. This approach allows for the identification of functionally and/or evolutionarily related genes that are found in conserved genomic contexts, which may be missed by traditional sequence- or structure-based search alone. Gaia enables real-time search of a curated database comprising more than 85 million protein clusters from 131,744 microbial genomes. We compare the homolog retrieval performance of Gaia search against other embedding and alignment-based approaches. We provide Gaia as a web-based, freely available tool.

Jha, Nishant↗

Fabrication of freeform potassium dihydrogen phosphate crystals by belt-on-wheel polishing for spatially tailored polarization control in high-power lasers

Large-aperture (>30 cm) optical components that provide spatially tailored control of the properties of a laser beam, such as phase, polarization, and amplitude, have been the focus of much research and development in recent years. Such optics can improve energy throughput and target implosion efficiency in high-power laser systems conducting inertial confinement fusion research. Here, a method is demonstrated for fabricating freeform surface topographies into the birefringent crystalline material, potassium dihydrogen phosphate (KDP). Belt-on-wheel polishing with an oil-based fluid, developed to mitigate the deliquescent properties of KDP, is used to deterministically polish a freeform topography into KDP, enabling the fabrication of a wave plate with spatially arbitrary retardance. Testing of the laser-induced damage threshold of belt-on-wheel polished KDP was conducted at a wavelength of 351 nm and a pulse duration of 1 ns. The results revealed that the polished surfaces are highly resistant to laser-induced damage, making them suitable for large-aperture, high-power laser applications.

Urban, Nathaniel D. [Univ. of Rochester, NY (Unite↗

Crystallographic variant mapping using precession electron diffraction data

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities.

Crystallographic variant mapping↗

Developing an Efficient Cyanobacterial Sugar Production System

Researchers at the LBNL Advanced Biofuels Process Development Unit, in collaboration with Sandia National Laboratory and HelioBioSys, Inc., demonstrated pilot scale recovery and purification of polysaccharides produced by a unique marine cyanobacterial consortium. LBNL researchers tested new methods to quantify biomass and exopolysaccharide content during cultivation, and demonstrated separation of biomass and salt from polysaccharides at the 1,000L scale. Production of marine cyanobacterial polysaccharides from the consortium requires no fresh water, added carbon dioxide, or added nutrients, enabling use of marginal land and water resources for production of these unique biopolymers.

09 BIOMASS FUELS↗

Transition Core Planning and Safety Analyses in Support of LEU Fuel Conversion of the University of Missouri Research Reactor (MURR)

The University of Missouri Research Reactor (MURR®) is one of six U.S. High Performance Research Reactors (USHPRR), including one critical facility, that is working with the National Nuclear Security Administration (NNSA) Office of Material Management and Minimization (M3) Reactor Conversion Program to convert from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel. The M3 Reactor Conversion USHPRR Project objectives include the development of LEU fuel element designs that will ensure safe reactor operations and to maintain the existing experimental performance of each facility. The work is being conducted through many inter-related activities being completed by four Project Pillars: Fuel Qualification (FQ), Fuel Fabrication (FF), Reactor Conversion (RC), and Cross Cutting (CC). A new type of LEU fuel based on an alloy of uranium-10 wt% molybdenum (U-10Mo) is expected to allow the conversion of those USHPRR, like MURR, requiring higher density fuels. The very-high-density LEU U-10Mo monolithic fuel is currently undergoing irradiation testing and post-irradiation examination under a planned and documented fuel qualification effort. The FQ Pillar will document fuel property and fuel performance data and qualify the fuel for use in these reactors. The FF Pillar is fabricating fuel for ongoing and future irradiation tests, as well as conducting fabrication demonstrations to validate or update preliminary fabrication assumptions. The FF Pillar is also working to develop and install commercial manufacturing capacity with the U-10Mo monolithic fuel to produce prototypic fuel. Working with the RC Pillar at Argonne, MURR has progressed through a preliminary fuel element design using preliminary data for the proposed monolithic alloy of U-10Mo. Analyses were completed in previous work that found for typical equilibrium operations with the preliminary LEU fuel element design, in conjunction with a power uprate to 12 MW and appropriate changes to the MURR Limiting safety system settings (LSSS), MURR will have adequate margins to safety for steady-state operations and postulated transient accidents and will have experimental performance in key locations that meets or exceeds current operations with HEU fuel. The purpose of this work is to develop a sequence of transition cycles that will enable MURR to transition from operation with the reactor core loaded with fresh LEU fuel elements only to typical equilibrium operations with mixed-burnup cores following conversion while meeting operational requirements on safety and experimental performance. It is expected that the use of fresh LEU fuel at conversion and subsequent low burnup of the LEU fuel elements that will initially be available for use following conversion will result in critical control blade positions that will substantially change the axial power distribution in the core and the neutron flux available in key experimental locations relative to equilibrium LEU operations. Given the constraints of MURR safety margins, operational practices, and production and research, a novel method has been developed to identify a transition sequence that minimizes the time MURR operates atypically compared to the current prototypic cycles using HEU fuel. The proposed transition sequence moves quickly to the same sort of equilibrium cycles for the LEU fuel that have already been evaluated in documented preliminary safety analyses. Although shifting the neutron flux peak to the lower half of the core during initial cycles with LEU at 12 MW reduces the experiment performance in some key locations relative to current HEU operations at 10 MW, all LEU cores provide an average performance that meets or exceeds that of HEU. An LEU cycle is reached that meets or exceeds the level of experimental performance predicted for current HEU and equilibrium LEU operations in more than 450 key locations identified by a reactor specialist at MURR by the 23rd cycle following conversion and that afterwards will enable MURR to consistently meet its experimental performance requirements. The proposed transition sequence only requires the fabrication of 34 fresh LEU elements in the first year of operation and does not exceed the anticipated availability of fresh elements that can be produced by the fuel fabricator. By the third year after conversion, 22 fresh LEU elements will be required each year, which is the same as expected for equilibrium LEU operations and the same as current operations with HEU fuel. The proposed transition sequence thus combines a relatively short time period before equilibrium burnup is achieved, a temporary increase of fuel elements needed annually relative to typical operations that are within the production capabilities of the fuel fabricator, and demonstrates comparable experimental performance of the LEU cores relative to current HEU operations. Further measures may be taken to reduce any initial experimental performance penalty even further, where possible, by repositioning certain experiments to leverage the increased performance in the lower axial experimental positions in the initial cycles following conversion or leaving the experiments in the irradiation facilities longer in order to achieve the required neutron fluence. This analysis may require refinement depending on the experimental facilities in use at the time of conversion. Nonetheless, the results presented here, including the experimental performance, core burnup, and critical control blade positions throughout the transition cycles, show that the proposed transition cycle fuel management patterns are consistent with what is expected and desired for MURR operation with LEU U-10Mo fuel. Detailed core power distributions from the neutronics models were also used to evaluate safety margins during steady-state operations for the selected transition cycles and the equilibrium LEU core. It is shown that there are adequate safety margins for both steady-state operations and postulated accident scenarios. For the steady-state operations with the preliminary LEU fuel element design the analysis predicts at least 2.49 MW margin to the onset of flow instability at the LSSS power of 15 MW. Considering the LSSS power is 125% of full license power, the margin to OFI is sufficient. In addition, the critical heat flux ratio at LSSS power is well above the requirement of CHFR > 2.0 from NUREG-1537 for all considered cases. For postulated transient accidents, the minimum margin to the fuel temperature safety limit is at least 109 °C. In summary, the proposed sequence of core loadings for MURR operations following conversion to LEU fuel and a power uprate to 12 MW provides sufficient safety margins for both steady-state operations and postulated transient accidents during a proposed sequence of transition cycles to equilibrium operations. Analysis has shown that there are some local experimental performance penalties during the initial cycles. Although there are local shifts in the experimental performance, on average all LEU cores at 12 MW have equal or higher performance than HEU at 10 MW. Temporary adjustments are being planned that will produce suitable experimental performance during these cycles. The results indicate that for the equilibrium LEU core the experimental performance exceeds that of current HEU operations in all key locations while also demonstrating sufficient safety margins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

X-ray Computed Tomography on UNESE Core: FY2020 Data Report to Support Fracture and Multiphase Fluid Flow Studies

Natural and induced fractures are potential preferential pathways for migration of radioactive gases to earths surface from underground nuclear explosions (UNEs). This report documents X-ray computed tomography (XRCT) imaging on 26 samples of rock core that was collected to support the Underground Nuclear Explosion Signatures Experiment (UNESE) program. The XRCT datasets are intended to help fill a data gap on the three-dimensional (3D) characteristics of natural and/or induced fractures at the centimeter and smaller scale, which may strongly influence multiphase fluid flow and transport properties of preferential flow paths and interaction with the matrix of the surrounding host rock. Pre- and post-UNE rock samples were carefully chosen to enable comparison of fractures as a function of lithologic and petrophysical properties, as well as distance to the past UNEs. This report serves as documentation for the data, including an introduction with the research motivation, a methods and materials section, descriptions of the XRCT datasets without post-processing, and recommendations for 3D quantification via image analysis and digital rock physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Computational Modeling and Simulation for Nonproliferation: The History (and Present) of Monte Carlo and the MCNP(R) Code at Los Alamos [Slides]

The emergence of the Monte Carlo method as a research tool springs from work done at Los Alamos in the 1940s.Monte Carlo and the MCNP Code have been and continue to be developed at Los Alamos for many decades. From basic science in support of understanding nuclear interaction physics to global security applications, application uses of the code are extensive. Recent R&D projects and code modernization efforts make the MCNP code a great tool for nuclear nonproliferation applications. In collaboration with nuclear safeguards experts, new training has just recently been developed to help new practitioners learn how to use the code for nuclear safeguards applications.

97 MATHEMATICS AND COMPUTING↗

MIDAS: Modeling Individual Differences using Advanced Statistics

This research explores novel methods for extracting relevant information from EEG data to characterize individual differences in cognitive processing. Our approach combines expertise in machine learning, statistics, and cognitive science, advancing the state-of-the art in all three domains. Specifically, by using cognitive science expertise to interpret results and inform algorithm development, we have developed a generalizable and interpretable machine learning method that can accurately predict individual differences in cognition. The output of the machine learning method revealed surprising features of the EEG data that, when interpreted by the cognitive science experts, provided novel insights to the underlying cognitive task. Additionally, the outputs of the statistical methods show promise as a principled approach to quickly find regions within the EEG data where individual differences lie, thereby supporting cognitive science analysis and informing machine learning models. This work lays methodological ground work for applying the large body of cognitive science literature on individual differences to high consequence mission applications.

97 MATHEMATICS AND COMPUTING↗

Impact of FERC Order 2222 on DER Participation Rules in US Electricity Markets

Electricity markets in the bulk grid are beginning to implement market mechanisms that support the procurement of flexible capabilities from wide range of technologies, including distributed energy resources (DERs). The flexibility of these resources will help counterbalance supply uncertainties from large-scale integration of variable renewable generation. To encourage development of distributed and aggregated market participants, FERC Order 2222 was issued in September 2020 to require each Independent System Operator (ISO) in the US to implement rules that enable broader participation from aggregations of DERs in the bulk market. The following paper first describes the generic design of ISO markets before introducing the new market participation rules that ISOs have proposed for compliance with Order 2222. The paper then describes how software performance issues may continue to affect the eligibility requirements and offer structures for DER aggregations participating in ISOs, noting that continued research on computational methods may help reduce burdens for DER integration. The prospects for transmission and distribution system coordination is second major issue discussed, which will require minor changes to existing processes in the short term. In the longer term, there is more opportunity for more wide-ranging reforms, such as the development of a Distribution System Operator (DSO) framework. Newly proposed market rules may affect how Transactive Energy Systems (TES) will help facilitate efficient formation of DER aggregations and operation of the individual DERs within an aggregation. Within the TES context, the challenge is to fully understand how resource eligibility and operational and planning coordination methods will affect the design and implementation of TES.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High efficiency, high-current laser-driven electron injector (CRADA Final Report)

Owing to ultra-high fields sustainable in a plasma, laser-plasma accelerator technology enables compact, high-brightness, sources of electron beams. This work investigates novel electron injection methods. Key to this research is to understand laser energy and pointing stability and to develop methods and techniques to control fluctuations. This project benefits other areas of scientific inquiry by developing a high-repetition rate, high-brightness electron source for probing materials and ultra-fast processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High efficiency, high-current laser-driven electron injector (CRADA Final Report)

Owing to ultra-high fields sustainable in a plasma, laser-plasma accelerator technology enables compact, high-brightness, sources of electron beams. This work investigates novel electron injection methods. Key to this research is to understand laser energy and pointing stability and to develop methods and techniques to control fluctuations. This project benefits other areas of scientific inquiry by developing a high-repetition rate, high-brightness electron source for probing materials and ultra-fast processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗