Search NASA⌕ Search

SEARCH · Search NASA

Results for “evaluation platform”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59

BSMV-mediated genome editing exhibits host-specific heritability: germline transmission in barley and somatic edits in Nicotiana benthamiana

Plant RNA virus–mediated guide RNA (gRNA) delivery represents a transformative advance in genome editing technologies. Unlike conventional transformation methods that rely on labor-intensive tissue culture and regeneration for each individual gRNA delivery, viral vectors can rapidly and systemically transmit gRNAs into pre-established Cas-expressing plants, providing an accelerated route for functional genomics and trait discovery directly in planta . However, key design parameters, including subgenomic promoter choice, transcript architecture, and their effects on viral fitness and editing outcomes, remain to be elucidated for most viral platforms. We developed five Barley stripe mosaic virus (BSMV) vectors, each with distinct subgenomic promoter elements to drive single gRNA expression. These were initially evaluated in Cas9-expressing transgenic Nicotiana benthamiana plants targeting the Phytoene desaturase ( PDS ) gene to compare their editing efficiencies. Single gRNAs expressed under the duplicated γb subgenomic promoter or when fused directly to the γb genome achieved the highest mutation frequencies (up to 90% at 60 days post-inoculation), whereas β1- and β2-driven sgRNAs produced delayed and reduced editing. Thus, promoter selection critically determines gRNA accumulation and the efficacy of BSMV-mediated genome editing. The top-performing design was then applied to Cas9-expressing barley ( Hordeum vulgare ) targeting HvCMF7 (conferring green-white variegation) and HvGW2.1 (impacts grain width and weight). BSMV spread systemically throughout barley, inducing somatic and heritable mutations at frequencies up to 100%, with virus-free edited progeny. In contrast, despite robust somatic editing in N. benthamiana, no heritable mutations were detected indicating species-dependent limitations in germline transmission. Our systematic comparison of subgenomic promoter architectures establishes clear design principles for optimizing viral vector–mediated delivery. Promoter choice and transcript structure critically shape editing efficiency and viral stability. The host-specific boundary for germline editing, defined by efficient heritable editing in barley but not N. benthamiana , highlights where BSMV offers advantages and where alternative vectors or hybrid strategies are required, guiding rational platform selection for diverse crop species and applications. Collectively, these findings establish BSMV as a promising next-generation vector for rapid, tissue culture–free, and transformation-independent genome editing in cereals and other recalcitrant monocots.

barley↗

Jump-Down Performance Alterations after Space Flight

INTRODUCTION: Successful jump performance requires functional coordination of visual, vestibular, and somatosensory systems, which are affected by prolonged exposure to microgravity. Astronauts returning from space flight exhibit impaired ability to coordinate effective landing strategies when jumping from a platform to the ground. This study compares jump strategies used by astronauts before and after flight, changes to those strategies within a test session, and recoveries in jump-down performance parameters across several postflight test sessions. These data were obtained as part of an ongoing interdisciplinary study (Functional Task Test, FTT) designed to evaluate both astronaut postflight functional performance and related physiological changes. METHODS: Seven astronauts from short-duration (Shuttle) and three from long-duration (International Space Station) flights performed 3 two-footed jumps from a platform 30 cm high onto a force plate that measured the ground reaction forces and center-of-pressure displacement from the landings. Neuromuscular activation data were collected from the medial gastrocnemius and anterior tibialis of both legs using surface electromyography electrodes. Two load cells in the platform measured the load exerted by each foot during the takeoff phase of the jump. Data were collected in 2 preflight sessions, on landing day (Shuttle only), and 1, 6, and 30 days after flight. RESULTS: Postural settling time was significantly increased on the first postflight test session and many of the astronauts tested were unable to maintain balance on their first jump landing but recovered by the third jump, showing a learning progression in which performance improvements could be attributed to adjustments in takeoff or landing strategy. Jump strategy changes were evident in reduced air time (time between takeoff and landing) and also in increased asymmetry in foot latencies on takeoff. CONCLUSIONS: The test results revealed significant decrements in astronauts abilities to maintain balance and achieve a postural stability upon landing from a jump early after flight. However, the jump landing adaptation process often begins after the first jump with full recovery of most performance parameters within days after space flight. As expected, performance of ISS astronauts on the first day after flight was similar to that of Shuttle crewmembers on landing day.

Reschke, M. F.↗

Spaceflight Autonomous Multigenerational Microbial Sequencer in Support of Plant-Growth Systems

The CubeSat platform has proven successful in obtaining meaningful life science information when biological payloads are incorporated. Examples include: 1) the first-ever CubeSat with a biological payload, GeneSat-1, which demonstrated decreased growth rates for flight samples of Escherichia coli in low Earth orbit (Parra et al. 2008); 2) PharmaSat, demonstrated that Saccharomyces cerevisiae in the microgravity environment exhibits a significant level of metabolic activity even at high doses of applied antifungal (Ricco et al. 2011); 3) O/OREOS, which used Bacillus subtilis(bacteria) to demonstrate for the first time that microorganisms can be loaded in a dried, dormant form and then rehydrated and grown in orbit months after launch (Nicholson et al. 2011; Ehrenfreund et al. 2014; 4) the SporeSat payload, which investigated Ceratopteris richardii(fern spores) using lab-on-a-chip devices (BioCDs) and minicentrifuges to produce artificial gravitational forces in ground studies (Park et al. 2017), with demonstration of the BioCD and minicentrifuge in space; 5) EcAMSat, the first CubeSat to be directly deployed from the ISS for an experiment assessing antibiotic resistance of E. coli in the microgravity environment (Padgen et al. 2020); 6) BioSentinel, exposed a culture of yeast to galactic cosmic radiation (GCR) and solar particle events while in heliocentric orbit to measure the rate of double-strand-break repair using DNA-repair-deficient mutants. This effort measures the metabolic parameters of yeast in a deep-space environment compared to Earth ambient conditions using a 3-color LED detection system (Ricco et al. 2020; Padgen et al. 2021). We aim to expand this list to include a Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS). SAMMS will allow for the genome level understanding of changes in growth and metabolic activity for any organism. While microbes are suitable for early studies in our proposed platform because of their small size, small and relatively less-complicated genomes, fast generation times, and relevance to life support systems; multicellular organisms can similarly be evaluated for their genetic response to the spaceflight environment. The Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) will enable autonomous sequencing of biological samples in plant production units, cislunar orbit and on the lunar surface to examine spaceflight effects (ie. radiation, altered gravity, reduced pressures) on plant and microbial genomes.On this team a Kennedy Space Center (KSC) space crop production and water systems microbiologist/molecular biologist works with a Johnson Space Center (JSC) International Space Station (ISS) microbial sequencing expert and an Ames Research Center (ARC) CubeSat Engineering team to convert an automated Oxford Nanopore librarypreparation and sequencing method to a fluidic CubeSat payload system. The Oxford Nanopore MinION sequencing platform has proven successful in the spaceflight environment onboard the ISS (Stahl-Rommel et al. 2021). Further long-duration spaceflight and exposure to high levels of radiation will cause genotypic effects in biological organisms that may affect their function. Monitoring the adaption of a population to the spaceflight environment and any subsequent beneficial mutations will allow for the harnessing of organisms best suited for use in life support systems. This will ensure that the selected life support-essential microorganisms maintain their intended specified function over generations of culturing in the relevant spaceflight environment without becoming hazardous to crew or spacecraft systems.

Aubrie E Orourke↗

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

Battery Electrolyte Design for Electric Vertical Takeoff and Landing (eVTOL) Platforms

Here, the development of robust and high-performance battery systems is crucial for the advancement of Electric Vertical Takeoff and Landing (eVTOL) vehicles for urban air mobility. This study evaluates the performance of different lithium-ion battery chemistries under Electric Vertical Takeoff and Landing (eVTOL) load profiles. The actual flight data coupled with physical models is used to create discharge profiles for testing on developed lithium-ion cells for eVTOLs. The performance of a standard liquid electrolyte (1.2 M LiPF 6 in EC:EMC), labeled Gen-2, is benchmarked and compared with a fast-charging electrolyte (1.2 M LiFSI in EC:EMC), labeled XFC. Cell analysis involves the use of various techniques, such as impedance spectroscopy, polarization curves, and capacity retention measurements. Capacity retention is stable for both systems over 500 cycles, but unique discharge capacity trends are observed for different mission segments. During the initial takeoff hover stages, Gen-2 electrolytes experience substantial voltage fade, while XFC electrolytes maintain consistent behavior. In general, the Gen-2 electrolyte demonstrated lower discharge overpotentials and higher decay during cycling compared to the XFC electrolyte. This work highlights the complexity of eVTOL battery behavior and provides insights into battery system design, contributing to the advancement of battery energy storage solutions for urban air mobility.

25 ENERGY STORAGE↗

SU-C-BRB-03: Cross-Institutional Validation of An Ultrafast Automatic Planning Platform for Breast Irradiation

Purpose: Recently an ultrafast automatic planning system for breast irradiation using tangential beams was developed by modeling relationships between patient anatomy and achieved dose distribution. This study evaluates the performance of this system when applied to a different patient population and dose calculation algorithm. Methods: The system and its anatomy-to-dose models was developed at institution A based on 20 cases, which were planned using manual fluence painting technique and calculated WITH heterogeneity correction. Institution B uses field-in-field planning technique and dose calculation WITHOUT heterogeneity correction. 11 breast cases treated at Institution B were randomly selected for retrospective study, including left and right sides, and different breast size (irradiated volumes defined by Jaw/MLC opening range from 875cc to 3516cc). Comparisons between plans generated automatically (Auto-Plans) and those used for treatment (Clinical-Plans) included: energy choice (single/mixed), volumes receiving 95%/100%/105%/110% Rx dose (V95%/V100%/V105%/V100%) relative to irradiated volume, D1cc, and LungV20Gy. Results: In 9 out of 11 cases single/mixed energy choice made by the software agreed with Clinical-Plans. For the remaining 2 cases software recommended using mixed energy and dosimetric improvements were observed. V100% were similar (p=0.223, Wilcoxon Signed-Rank test) between Auto-Plans and Clinical-Plans (57.6±8.9% vs. 54.8±9.5%). V95% is 2.3±3.0% higher for Auto-Plans (p=0.027), indicating reduced cold areas. Hot spot volume V105% were significantly reduced in Auto-Plan by 14.4±7.2% (p=0.004). Absolute V105% was reduced from 395.6±359.9cc for Clinical-Plans to 108.7±163cc for Auto-Plans. D1cc was 107.4±2.8% for Auto-Plans, and 109.2±2.4% for Clinical-Plans (p=0.056). LungV20Gy were 13.6±4.0% for Auto-Plan vs. 14.0±4.1% for Clinical-Plans (p=0.043). All optimizations were finished within 1.5min. Conclusion: The performance of this breast auto-planning system remained stable and satisfactory when applied to a different patient population and dose calculation algorithm. The auto-planning system was able to produce clinically similar Rx dose coverage with significantly improved homogeneity inside breast tissue, in less than 1.5min.

60 APPLIED LIFE SCIENCES↗

Combining RNA-SEQ Datasets from NASA GENELAB: An Evaluation of Correction Methods

Background: Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. Methods: In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, the median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. Results: The results showed that the reference-based approach introduced several additional (and likely artificial) differentially expressed genes when compared with the respective standard approach. Conclusions: Of the methods tested, standard ComBat_seq and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

Finsam Samson↗

Microstructure actuation and gas sensing by the Knudsen thermal force

The generation of forces and moments on structures immersed in rarefied non-isothermal gas flows has received limited practical implementation since first being discovered over a century ago. The formation of significant thermal stresses requires both large thermal gradients and characteristic dimensions which are comparable to the gas molecular mean free path. For macroscopic geometries, this necessitates impractically high temperatures and very low pressures. At the microscale, however, these conditions are easily achieved, allowing the effects to be exploited, namely, for gas-property sensing and microstructure actuation. In this letter, we introduce and experimentally evaluate performance of a microelectromechanical in-plane Knudsen radiometric actuator, a self-contained device having Knudsen thermal force generation, sensing, and tuning mechanisms integrated onto the same platform. Sensitivity to ambient pressure, temperature gradient, as well as gas composition is demonstrated. Results are presented in terms of a non-dimensional force coefficient, allowing measurements to be directly compared to the previous experimental and computational data on out-of-plane cantilevered configurations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Study of a Docker Use-Case for HEP

Over the past few years, container technology has become increasingly promising as a means to seamlessly make our software available across a wider range of platforms. In December 2015, we decided to put together a set of docker images that serve as a demonstration of this container technology for managing a run-time environment for art-related software projects, and also serve as a set of test cases for evaluation of performance. Docker[1] containers provide a way to “wrap up a piece of software in a complete filesystem that contains everything it needs to run”. In combination with Shifter[2], such containers provide a way to run software developed and deployed on “typical” HEP platforms (such as SLF 6, in common use at Fermilab and on OSG platforms) on HPC facilities at NERSC. Docker containers provide a means of delivering software that can be run on a variety of hosts without needing to be compiled specially for each OS to be supported. This could substantially reduce the effort required to create and validate a new release, since one build could be suitable for use on both grid machines (both FermiGrid and OSG) as well as any machine capable of running the Docker container. In addition, docker containers may provide for a quick and easy way for users to install and use a software release in a standardized environment. This report contains the results and status of this demonstration and evaluation.

97 MATHEMATICS AND COMPUTING↗

TH-EF-207A-04: A Dynamic Contrast Enhanced Cone Beam CT Technique for Evaluation of Renal Functions

Purpose: To develop a simple but robust method for the early detection and evaluation of renal functions using dynamic contrast enhanced cone beam CT technique. Methods: Experiments were performed on an integrated imaging and radiation research platform developed by our lab. Animals (n=3) were anesthetized with 20uL Ketamine/Xylazine cocktail, and then received 200uL injection of iodinated contrast agent Iopamidol via tail vein. Cone beam CT was acquired following contrast injection once per minute and up to 25 minutes. The cone beam CT was reconstructed with a dimension of 300×300×800 voxels of 130×130×130um voxel resolution. The middle kidney slices in the transvers and coronal planes were selected for image analysis. A double exponential function was used to fit the contrast enhanced signal intensity versus the time after contrast injection. Both pixel-based and region of interest (ROI)-based curve fitting were performed. Four parameters obtained from the curve fitting, namely the amplitude and flow constant for both contrast wash in and wash out phases, were investigated for further analysis. Results: Robust curve fitting was demonstrated for both pixel based (with R{sup 2}>0.8 for >85% pixels within the kidney contour) and ROI based (R{sup 2}>0.9 for all regions) analysis. Three different functional regions: renal pelvis, medulla and cortex, were clearly differentiated in the functional parameter map in the pixel based analysis. ROI based analysis showed the half-life T1/2 for contrast wash in and wash out phases were 0.98±0.15 and 17.04±7.16, 0.63±0.07 and 17.88±4.51, and 1.48±0.40 and 10.79±3.88 minutes for the renal pelvis, medulla and cortex, respectively. Conclusion: A robust method based on dynamic contrast enhanced cone beam CT and double exponential curve fitting has been developed to analyze the renal functions for different functional regions. Future study will be performed to investigate the sensitivity of this technique in the detection of radiation induced kidney dysfunction.

60 APPLIED LIFE SCIENCES↗

End-to-end Analytics for Grid Arch Design & All-hazard Assessment

Resiliency, reliability, and security of the next-generation smart grid depend upon leveraging advanced communication and computing technologies, integrating them with physical power systems, and developing real-time, fast, data-based applications to help in wide-area monitoring and control of the grid. Using a high sampling data rate from phasor measurement units (PMUs) to develop applications has opened the door to achieving the next-generation grid requirements. The North American Synchrophasor Initiative Network (NASPlnet) was developed in 2007-09 to create a standard and guide for PMU data exchanges. With the advancement in both networking and grid requirements, it is necessary to evaluate the performance of different NASPInet versions and their impact on applications. Therefore, we need a cyber-power cosimulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents a cyber-physical co-simulation testbed using NS3 to model the communication network, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application based on PMU data in an Institute of Electrical and Electronics Engineers 39-bus test system is presented using this co-simulation testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Autonomous Medical Officer Support (AMOS) ISS Technology Demonstration: Enabling Earth-Independnt Procedure Guidance

Successful performance of medical procedures during missions beyond low Earth orbit requires novel solutions to replace real-time support from the ground since the communication delay will be longer as the crew travels farther from Earth. The Autonomous Medical Officer Support software Technology Demonstration project (AMOS Tech Demo) on the International Space Station (ISS) evaluates a novel software tool that shifts the emphasis from preflight training and real-time guidance (current ISS paradigm) to in-flight just-in-time (JIT) instruction (a new paradigm for crew medical autonomy). The AMOS platform introduces a novel, streamlined, skill-management archetype for exploration missions; the current AMOS version features comprehensive training and guidance modules for urinary bladder and kidney ultrasound examinations. The primary goal of the AMOS Tech Demo was to confirm telemedical proof-of-concept through initial use of the platform for autonomous imaging activities in an operational setting. Success metrics encompassed 1) successful software deployment, 2) collection of click tracking data, and 3) recording of ultrasound images. Additional aims included collecting crew feedback on a) AMOS implementation, and b) integrated training and procedure support concepts, as well as c) evaluation of AMOS use in an operational setting.

D. Ebert↗

Decoupling Carrier Dynamics and Energy Transport in Ultrafast Near-Field Nanoscopy

Ultrafast near-field optical nanoscopy has emerged as a powerful platform to characterize low-dimensional materials. While analytical and numerical models have been established to account for photoexcited carrier dynamics, quantitative evaluation of the associated pulsed laser heating remains elusive. Here, we decouple the photocarrier density and temperature increase in near-field nanoscopy by integrating the two-temperature model (TTM) with finite-difference time-domain (FDTD) simulations. These results reveal that the electron–phonon coupling in a silicon film after femtosecond laser excitation is most pronounced within approximately 3 ps–substantially shorter than the photocarrier decay time scale at tens of picoseconds. Moreover, the coupled TTM-FDTD method indicates that ultrafast laser heating can cause up to a 14% variation in the near-field signal at a 220 μJ/cm 2 pump pulse fluence. Our numerical results are further validated by transient experiments, highlighting the potential of this method for investigations of carrier and thermal phenomena in emerging nanomaterials and nanodevices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗

Transactive Energy Simulation Platform

Transactive Energy Simulation Platform (TESP) combines existing domain simulators in the electric power grid, buildings, and communication systems, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, EnergyPlus for large buildings and ns-3 for communication systems. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others. Growth Model - a means for simulating system changes over a multiyear period, including both normal load growth and specific investment decisions. Customizable in Python code. Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP will run on Linux, Windows and Mac OS X.

McDermott, Tom↗

An Initial Investigation of the Design Challenges Associated with Reliable 100GigE Packet Capture

Network security researchers often rely on Emulytics TM to provide a way to evaluate the safety and security of real world systems. This work involves running a large number of virtual machines on a distributed platform to observe how software and hardware will respond to different types of attacks. While Emulytics TM software such as minimega provide a scalable system for conducting experiments, the sheer volume of network traffic produced in an experiment can easily exceed the rate at which data can be recorded for offline analysis. As such, researchers must perform live analytics, narrow their monitoring scope or accept that they must run an experiment multiple times to capture all the information they require. In support of Sandia's commitment to Emulytics TM , we are developing new storage components for the Carlin cluster that will enable researchers to capture significantly more network traffic from their experiments. This report provides a summary of Haoda Wang's initial investigation of how new AMD Epyc storage nodes can be adapted to perform packet capture at 100Gbps speeds with minimal loss. This work found that the NVMe storage capabilities of the Epyc architecture are suitable for capturing 100Gbps Ethernet traffic. While capturing traffic with existing libraries was surprisingly challenging, we were able to develop a DPDK-based software tool that recorded network traffic to disk with minimal packet loss.

97 MATHEMATICS AND COMPUTING↗

Co-Optimization of Boost Converter Reliability and Volumetric Power Density [Brief]

Optimized designs were achieved using a genetic algorithm to evaluate multi-objective trade space, including Mean-Time-Between-Failure (MTBF) and volumetric power density. This work provides a foundational platform that can be used to optimize additional power converters, such as an inverter for the EV traction drive system as well as trade-offs in thermal management due to the use of different device substrate materials.

33 ADVANCED PROPULSION SYSTEMS↗