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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-347: Validation of the Condensed History Algorithm of Geant4 Using the Fano Test

Purpose: To validate the condensed history algorithm and physics of the Geant4 Monte Carlo toolkit for simulations of ionization chambers (ICs). This study is the first step to validate Geant4 for calculations of photon beam quality correction factors under the presence of a strong magnetic field for magnetic resonance guided linac system applications. Methods: The electron transport and boundary crossing algorithms of Geant4 version 9.6.p02 were tested under Fano conditions using the Geant4 example/application FanoCavity. User-defined parameters of the condensed history and multiple scattering algorithms were investigated under Fano test conditions for three scattering models (physics lists): G4UrbanMscModel95 (PhysListEmStandard-option3), G4GoudsmitSaundersonMsc (PhysListEmStandard-GS), and G4WentzelVIModel/G4CoulombScattering (PhysListEmStandard-WVI). Simulations were conducted using monoenergetic photon beams, ranging from 0.5 to 7 MeV and emphasizing energies from 0.8 to 3 MeV. Results: The GS and WVI physics lists provided consistent Fano test results (within ±0.5%) for maximum step sizes under 0.01 mm at 1.25 MeV, with improved performance at 3 MeV (within ±0.25%). The option3 physics list provided consistent Fano test results (within ±0.5%) for maximum step sizes above 1 mm. Optimal parameters for the option3 physics list were 10 km maximum step size with default values for other user-defined parameters: 0.2 dRoverRange, 0.01 mm final range, 0.04 range factor, 2.5 geometrical factor, and 1 skin. Simulations using the option3 physics list were ∼70 – 100 times faster compared to GS and WVI under optimal parameters. Conclusion: This work indicated that the option3 physics list passes the Fano test within ±0.5% when using a maximum step size of 10 km for energies suitable for IC calculations in a 6 MV spectrum without extensive computational times. Optimal user-defined parameters using the option3 physics list will be used in future IC simulations to calculate beam quality correction factors under the presence of a magnetic field. Elekta-MD Anderson Research Agreement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-QI-13: Predictable Models for Radio-Sensitizing Agent Kinetics: Application to Stereotactic Synchrotron Radiation Therapy

Purpose: Iodine-enhanced radiotherapy is an innovative treatment combining the selective accumulation of an iodinated contrast agent in brain tumors with irradiations using monochromatic medium energy x-rays. The radiation dose enhancement depends on the time course of iodine in the tumors. A prolonged CT scanning (∼30 min) is required to follow-up iodine kinetics for recruited patients. This protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce the acquisition time. Methods: 12 patients received an intravenous bolus of iodinated contrast agent, followed by a steady-state infusion to ensure stable intra-tumoral amounts of iodine during the treatment. Absolute iodine concentrations (IC) were derived from 40 multi-slice dynamic conventional CT images of the brain. The impulse response function (IRF) to the bolus was estimated using the adiabatic approximation of the Johnson and Wilson's model. The arterial input function (AIF) of the steady-state infusion was fitted with several models: Gamma, Gamma with recirculation and hybrid. Estimated IC were calculated by convolving the IRF with the modeled AIF and were compared to the measured data. Results: The gamma variate function was not relevant to model the AIF due to high differences with the measured AIF. The hybrid and the gamma with recirculation models provided differences below 8% during the whole acquisition time. The absolute difference between the measured and the estimated IC was lower than 0.5 mg/ml, which corresponds to 5% of dose enhancement error. Conclusion: The proposed method allows a good estimation of the iodine time course with reduced scanning delays (3 instead of 30 min) and dose to the patient. The results suggest that the dose errors may stay within the radiotherapy standards.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-P-24: Simplified EDW Profile Measurements Using Two Commonly Available Detector Arrays

Purpose: Enhanced dynamic wedge (EDW) profiles are needed as part of the commissioning of a treatment planning system. This work compares the acquisition of EDW profiles using a linear diode array (LDA) with two commonly used detector arrays available in the clinics, with the goal of identifying the simplest approach for these measurements. Methods: The measurements of EDW profiles were performed on a Varian TrueBeam linear accelerator for 6, 10, and 18 MV photon beams for all seven wedge angles at four depths. The measurements were done using the LDA 99 in Blue Phantom2 (IBA Dosimetry), and IC Profiler and MapCHECK2 (Sun Nuclear) in solid water phantoms. The water phantom was set up at 100 cm SSD, whereas the two other devices were set up at 75 cm due to the size limitations of the devices. The largest possible field size was used. The average and maximum percentage differences were examined within the central 90% of the field and in the penumbra. Results: Dose profiles measured with IC Profiler were in a good agreement with LDA 99 data. The average percentage difference within the field did not exceed 0.5% for all energies. MapCHECK2 measurements matched well with LDA 99 for 10 and 18 MV (within 0.3%) with discrepancies of up to 1.4% observed for the 6 MV beam. The maximum percentage differences for both devices in the penumbra exhibited larger variations than LDA 99 results due to differences in detector spacing and high dose gradient, as expected. Conclusion: Common linac QA devices such as IC Profiler or MapCHECK2 provide EDW beam profile data of reasonable accuracy as compared to measurements performed using a linear diode array in a water phantom, saving the expense and time involved in acquiring and setting up a LDA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Practical dose point-based methods to characterize dose distribution in a stationary elliptical body phantom for a cone-beam C-arm CT system

Purpose: To propose new dose point measurement-based metrics to characterize the dose distributions and the mean dose from a single partial rotation of an automatic exposure control-enabled, C-arm-based, wide cone angle computed tomography system over a stationary, large, body-shaped phantom. Methods: A small 0.6 cm{sup 3} ion chamber (IC) was used to measure the radiation dose in an elliptical body-shaped phantom made of tissue-equivalent material. The IC was placed at 23 well-distributed holes in the central and peripheral regions of the phantom and dose was recorded for six acquisition protocols with different combinations of minimum kVp (109 and 125 kVp) and z-collimator aperture (full: 22.2 cm; medium: 14.0 cm; small: 8.4 cm). Monte Carlo (MC) simulations were carried out to generate complete 2D dose distributions in the central plane (z = 0). The MC model was validated at the 23 dose points against IC experimental data. The planar dose distributions were then estimated using subsets of the point dose measurements using two proposed methods: (1) the proximity-based weighting method (method 1) and (2) the dose point surface fitting method (method 2). Twenty-eight different dose point distributions with six different point number cases (4, 5, 6, 7, 14, and 23 dose points) were evaluated to determine the optimal number of dose points and their placement in the phantom. The performances of the methods were determined by comparing their results with those of the validated MC simulations. The performances of the methods in the presence of measurement uncertainties were evaluated. Results: The 5-, 6-, and 7-point cases had differences below 2%, ranging from 1.0% to 1.7% for both methods, which is a performance comparable to that of the methods with a relatively large number of points, i.e., the 14- and 23-point cases. However, with the 4-point case, the performances of the two methods decreased sharply. Among the 4-, 5-, 6-, and 7-point cases, the 7-point case (1.0% [±0.6%] difference) and the 6-point case (0.7% [±0.6%] difference) performed best for method 1 and method 2, respectively. Moreover, method 2 demonstrated high-fidelity surface reconstruction with as few as 5 points, showing pixelwise absolute differences of 3.80 mGy (±0.32 mGy). Although the performance was shown to be sensitive to the phantom displacement from the isocenter, the performance changed by less than 2% for shifts up to 2 cm in the x- and y-axes in the central phantom plane. Conclusions: With as few as five points, method 1 and method 2 were able to compute the mean dose with reasonable accuracy, demonstrating differences of 1.7% (±1.2%) and 1.3% (±1.0%), respectively. A larger number of points do not necessarily guarantee better performance of the methods; optimal choice of point placement is necessary. The performance of the methods is sensitive to the alignment of the center of the body phantom relative to the isocenter. In body applications where dose distributions are important, method 2 is a better choice than method 1, as it reconstructs the dose surface with high fidelity, using as few as five points.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography–based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline—FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC 50 ). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC 50 . Further optimization led to analogs with IC 50 values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science & Technology - Other Topics↗
DOE OSTI2026

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗
DOE OSTI2016

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

In this paper, an experimental soil moisture drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity model (VIC) over southwestern China (SW) is presented. Satellite precipitation data are used to force VIC for a near-real-time estimate of land surface hydrologic conditions. Initialized with satellite-aided monitoring (MONIT), the climate model (CFSv2)-based forecast (MONIT+CFSv2) and ensemble streamflow prediction (ESP)-based forecast (MONIT+ESP) are both performed. One dry season drought and one wet season drought are employed to test the ability of this framework in terms of real-time tracking and predicting the evolution of soil moisture (SM) drought, respectively. The results show that the skillful CFSv2 climate forecasts (CFs) are only found at the first month. The satellite-aided monitoring is able to provide a reasonable estimate of forecast initial conditions (ICs) in real-time mode. In the presented cases, MONIT+CFSv2 forecast exhibits comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1 month. Compared to MONIT+ESP, MONIT+CFSv2 ensembles give more skillful SM drought forecast during the dry season, as indicated by a smaller ensemble range, while the added value of MONIT+CFSv2 is marginal during the wet season. Furthermore, a quantitative attribution analysis of SM forecast uncertainty demonstrates that SM forecast skill is mostly controlled by ICs at the first month and that uncertainties in CFs have the largest contribution to SM forecast errors at longer lead times. This study highlights a value of this framework in generating near-real-time ICs and providing a reliable SM drought prediction with 1 month ahead, which may greatly benefit drought diagnosis, assessment, and early warning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Total metal, carbon, anion, iron speciation, and sulfide concentrations; Slate River, East River, and Trail Creek surface water and floodplains, Crested Butte, CO; May 2023–August 2023

This data package comprises analytical results and metadata from stream and groundwater samples collected from the Slate River, East River, Trail Creek, and their respective floodplains. This dataset contains five files: (1) a samples file (2023_SFA_Field_samples.csv) that contains site information; (2) a chemical analysis data file (2023_FieldWaterSampleData_IC__ICPOES__ICPMS__TOC__Fe__S_chem_data.csv) that contains sample analysis values; (3) a file-level metadata file (flmd.csv) that lists each file contained in the dataset with associated metadata; (4) a data dictionary file (dd.csv) that contains column/row headers used throughout the files along with definitions, units, and data types; and (5) a methods file (methods.csv) that contains ID, type, description, instrument, and lab information for each method.The samples’ anion concentrations were measured using ion chromatography (IC), total metal concentrations using inductively coupled plasma emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS), non-purgeable organic carbon using total organic carbon (TOC) analysis, dissolved sulfide concentration using methylene blue spectrophotometry, and iron speciation using the ferrozine assay. To support bulk chemical analyses and colloid characterization, samples were collected from multiple depths ranging from the surface to 3.5 meters below ground.Update on 2024-10-18: Updates were made to the 2023_FieldWaterSampleData_IC__ICPOES__ICPMS__TOC__Fe__S_chem_data.csv and dd.csv files to correct units (ppb instead of ppm).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Comparing vis–NIRS, LIBS, and Combined vis–NIRS‐LIBS for Intact Soil Core Soil Carbon Measurement

Core Ideas First rigorous integration of VisNIR and LIBS spectroscopic techniques for soil profile C measurement. Field‐moist intact soil cores scanned with LIBS and VisNIR simulating in situ measurements. Combined VisNIR‐LIBS wavelengths selected by MRCE were split nearly equally between sensors, suggesting molecular and elemental information was successfully integrated for predicting TC, IC, and SOC. Stoichiometric relationships in LIBS elemental emissions are more strongly correlated to IC concentration than were carbonate absorptions in VisNIR. Lack of variation and consistent, definable chemical composition and stoichiometry likely contributed to poor LIBS and combined VisNIR – LIBS prediction accuracy for SOC. Soil organic carbon (SOC) measurement is critically important to quantify regional and global soil C stocks and better understand soil C biogeochemical processes. Recent studies employing laser‐induced breakdown spectroscopy (LIBS) and visible‐near infrared diffuse reflectance spectroscopy (vis–NIRS) indicate their potential for in situ soil C determination. Visible and near infrared diffuse reflectance spectroscopy and LIBS spectroscopy fundamentally differ and we hypothesize that their integration would provide improved soil C predictions. We report the first rigorous integration of vis–NIRS and LIBS, evaluating the precision of vis–NIRS, LIBS, and combined vis–NIRS‐LIBS spectra for simulated in situ soil profile total C (TC), inorganic C (IC) and SOC measurement. Three multivariate variable selection and regression approaches were evaluated for soil C prediction. The highest soil C prediction accuracies were observed using multivariate regression with covariance estimation (MRCE). Inorganic C was best predicted by LIBS, vis–NIRS provided better SOC predictions, and TC was best predicted using combined vis–NIRS‐LIBS data. Combined vis–NIRS‐LIBS did not consistently increase soil C prediction accuracy. Soil organic C was not well predicted, presumably due to challenges associated with scanning surfaces of intact soil cores, variable SOC chemistries, and low SOC variation in the dataset. Considering the challenging conditions under which combined vis–NIRS– LIBS was tested for soil C measurement, data integration and model calibrations had acceptable performance. Further testing under more controlled soil conditions with samples containing greater SOC diversity is necessary to determine the technical potential of combined vis–NIRS/LIBS for soil C determination.

Bricklemyer, Ross S.↗
DOE OSTI2013

Development Of Ion Chromatography Methods To Support Testing Of The Glycolic Acid Reductant Flowsheet In The Defense Waste Processing Facility

Ion Chromatography (IC) is the principal analytical method used to support studies of Sludge Reciept and Adjustment Tank (SRAT) chemistry at DWPF. A series of prior analytical ''Round Robin'' (RR) studies included both supernate and sludge samples from SRAT simulant, previously reported as memos, are tabulated in this report.2,3 From these studies it was determined to standardize IC column size to 4 mm diameter, eliminating the capillary column from use. As a follow on test, the DWPF laboratory, the PSAL laboratory, and the AD laboratory participated in the current analytical RR to determine a suite of anions in SRAT simulant by IC, results also are tabulated in this report. The particular goal was to confirm the laboratories ability to measure and quantitate glycolate ion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

FInal Technical Repot of the Project: Design and Implementation of Low-Power 10Gb/s/channel Laser/Silicon Photonics Modulator Drivers with SEU Tolerance for HL-LHC

During the funding period of this award from May 1, 2014 through March 30, 2016, we have accomplished the design, implementation and measurement results of two laser driver chips: LpGBLD10+ which is a low-power single-channel 10Gb/s laser driver IC, and LDQ10P, which is a 4x10Gb/s driver array chip for High Energy Physics (HEP) applications. With new circuit techniques, the driver consumes a record-low power consumption, 31 mW @10Gb/s/channel and occupies a small area of 400 µm × 1750 µm for the single-channel driver IC and 1900umx1700um for the LDQ10P chip. These characteristics allow for both the LpGBLD10+ ICs and LDQ10P suitable candidate for the Versatile Link PLUS (VL+) project, offering flexibility in configuring multiple Transmitters and receivers.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Apparent Fracture Toughness of Pressureless Sintered Silver Interconnects

This study uses three-point flexural testing to estimate the room-temperature apparent fracture toughness ( K Ic_app ) of a pressureless sintered-silver interconnect - a candidate material for use in power electronic devices. The K Ic_app estimation occurs via work-of-fracture measurement of a chevron-shaped sintered-silver joint centrally located in an “interconnect bend test specimen”. The chevron-shape was stencil-printed on a silver (Ag)-plated direct bonded copper (DBC) substrate, mated to an Ag-plated DBC substrate, and then sintered. The chevron-shape, used for decades in fracture mechanics examinations and in standardized tests of monolithic materials, enables controlled stable crack initiation and propagation that are prerequisites for valid K Ic_app estimation. The employed combination of an interconnect bend test specimen and bend test method is robust and simple, enables a means for interpreting the resistance to crack growth and delamination in an interconnect, provides a dependable way to judge the efficacies of sintered-silver processing conditions, and ultimately supports process optimization of sintered-silver interconnects.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Concept for Cyber-Physical Consequence Process

The Department of Homeland Security’s Office of Cyber and Infrastructure Analysis (DHS/OCIA) has a mission and vision that promotes innovation as central to expanding the organization’s capability to conduct consequence analysis. To pursue such innovation, OCIA is sponsoring a seedling effort with Idaho National Laboratory (INL) to leverage data from the proposed Automated Vulnerability Assessment (AVA) capability, which the DHS Science and Technology (S&T) Directorate is developing through a separate INL effort. The first phase of this effort is to develop a process by which recognized vulnerabilities can be scored relative to importance, reflected primarily in the ability to initiate high consequence and potentially cascading events. This report documents a cyber-physical metrics process (CPMP) to tie physical impact to the malicious exploitation of cyber vulnerabilities in industrial control systems (ICS) with the potential for initiating consequence in the critical infrastructure. The scale of achieving any particular physical consequence is dependent upon the ICS Component the vulnerability exists on, the Level of Access that the exploit would allow to component function and the Physical Impact (CLAPI) to the power system that the component is tied. A modified common vulnerability scoring system (CVSS) was detailed and demonstrated for the power sector with three case studies associated with a recognized vulnerability, with significant consequence detail provided to apply the process across the power sector. A detailed table that provides background on the power system components, ICS-enabled monitoring and control, potential consequence effects, and CVSS scoring is provided. To demonstrate the applicability of the CPMP, tables are provided as examples for other sectors that include chemical, water/wastewater and oil/gas.

42 ENGINEERING↗
DOE OSTI2021

Portable Industrial Control Systems Simulator (Final Report)

Industrial Control Systems (ICS) are more integrated than they have ever been before, but also the division between IT (Information Technology) and OT (Operational Technology) is becoming a grey area. As the integration of IT and OT occurs more often, cyber attack will also increase. Cyber attacks on Critical Infrastructure can be highly detrimental to society, notably via compromised Industrial Control Systems (ICS). Virtual and physical simulation has been used in medical fields, mathematics, architecture, aeronautics, space, and many more. Virtualization & Simulation in a lab environment is ideal because there is a need for the ability to test theories and designs is a safe and cost-effective way without risking equipment damage or, more importantly, human life. Furthermore, OT and ICS are some of the most difficult systems to use for research and development. They are either committed to operations or widely expensive to set up in a life-like environment. Virtualization and simulation will allow these otherwise accessible systems to be a test bed for the training, development, and research of SRNL customers or engineers and scientists at SRNL. This will allow the testbed to fit into a small form factor and interact with a simulator with minimum hardware components for easy transports and replication effort within the environment.

42 ENGINEERING↗
DOE OSTI2021

MindSynchro

This report presents the developments and results of MindSynchro project as part of DOE OE FOA 1861. DOE and Pacific Northwest National Laboratory (PNNL) have made available to FOA awardees datasets containing years of real historical data recorded from various phasor measurement units (PMUs) which are installed in three large US interconnections: Texas (IC A), Western (IC B), and Eastern (IC C). The main goal of the project, which was successfully achieved, was to develop methods for detection and identification of events which are relevant for power grid operation. Tasks performed for achieving the project goals included data exploration and pre-processing, the development and application of physics-based features, data analysis and labeling based on unsupervised learning approaches, training and testing of DSSL models for classification of events which are relevant for power grid operation, and deployment of solutions to cloud environments. The methods developed in the project can potentially provide relevant benefits to power grid asset owners/operators in general in terms of situational awareness. Two main types of outcomes can be provided by these tools: Identification of specific relevant power grid event types: Semi-supervised ML methods developed in the project can adequately employ not only the relatively scarce labeled data but also the large amount of available unlabeled data to train models for detection of specific event types. Such methods enable the application of trained models for the detection of events in a population of PMUs much larger than that associated to the labeled events. Support in data labeling / label validation: Labels are critical for training of models for identification of specific types of events. However, labeling large amounts of data is a manual and tedious process. This means that such process is error prone and is not scalable. Methods developed in the project, based on ensembles of clustering models, have been successfully employed for turning manual labeling into a scalable process. Accurate identification of specific relevant events can provide the operators with immediate situational awareness that could otherwise require hours or days of analysis from domain experts. We envision that such methods could be initially employed in support of post-mortem analysis of events and, as confidence is gained, they could be employed for online/real-time support, providing, among other benefits, insights for avoiding major events which could happen due to a combination of smaller ones. On the longer term, related methods could potentially be employed to improve protection and control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

LANL Institutional Computing Close-out Report for Project t22_ocean_time_step

This year, my team made a very productive use of LANL IC time. Four papers were published that used IC resources, and two more are under review. These publications fall into three categories: 1.) Improving tide modeling in the global ocean by adding self attraction and loading (Barton et. al. 2022), ice shelf cavities (Pal et al. 2023), and local time stepping (Lilly et al. 2023). 2.) A new sea ice numerical formulation (Capodaglio 2023). 3.) Performance comparisons, methods, and test cases for ocean model development, This includes a verification suite for ocean models (Bishnu, submitted) and a comparison between Julia and Fortran (Strauss, submitted). A new time-stepping method was introduced in Calandrini et al. (2022). These publications, and the use of LANL IC resources, go hand-in-hand with our mentoring efforts to train young scientists. Two of the lead authors are graduate students who are conducting their PhD research: Kristin Barton at the University of Michigan and Jeremy Lilly at Oregon State. These are both their first publications, and they both have DOE funding and DOE mentors. In addition, Bishnu is a post-doctoral researcher at LANL; Strauss conducted his research as a senior in high school; and Capodaglio, Calandrini and Pal are all early-career scientists who were converted to staff in 2021 or 2022. Here we highlight two publications on improvements in tidal modeling: Barton et al. 2022 and Lilly et al. 2023.

58 GEOSCIENCES↗
DOE OSTI2023

Virtualizing Industrial Control Networks for Cyber Resilience Experiments

Industrial control systems (ICS) networks are undergoing constant shifts to accommodate new security measures. It is challenging to test varying network configurations and security tools with physical systems as they typically include large, expensive equipment. Not only this, but researchers often do not have access to this type of equipment for development of new security tools and techniques. As a solution to these issues, this work presents a set of tools for utilizing GNS3 and Docker as a virtual ICS network. Additionally, the virtual network can be attached to physical devices including network switches, hardware simulations, and intelligent electronic devices (IEDs). Two case studies showcase a relatively complex automatically generated network and an attack on a simple ICS network with an example mitigation.

42 ENGINEERING↗
DOE OSTI2026

Cummins PEM Fuel Cell System for Heavy Duty Applications

The motivation for this project was to develop a high-pressure 100+ kW fuel cell stack that can be used in a modular fashion to power HD applications up to 1 MW. One of the issues that was identified during fuel cell system integration was the need for extra space for heat rejection systems(radiators) as well as additional fans and associated energy consumption to compensate for lower operating temperatures of fuel cells compared to internal combustion (IC) engines. To maximize the heat rejection capability of existing water-based coolant systems that are prevalent on IC engine-based systems, fuel cell stack design was developed to withstand and operate at IC engine coolant temperatures or higher, which in turn helps to reduce the radiator size requirement.

08 HYDROGEN↗