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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Beam test performance of AstroPix sensor with 120 GeV protons

AstroPix is a High-Voltage CMOS Monolithic Active Pixel Sensor (HV-CMOS MAPS) developed for precision gamma-ray imaging and spectroscopy in the medium-energy regime, as well as for precise shower imaging and tracking in the Barrel Imaging Calorimeter (BIC) of the Electron Proton/Ion Collider (ePIC) detector at the future Electron–Ion Collider (EIC). We present beam test results of the AstroPix_v3 sensor using a 120 GeV proton beam at the Fermilab Test Beam Facility (FTBF), performed as part of the broader experimental campaign for the BIC prototype calorimeter. The sensor’s 500 µm pixel pitch enabled precise measurement of the beam profile, providing important information for the calorimeter performance studies. Using the measured 120 GeV proton data, we measure the energy deposit of minimum ionizing particles (MIP) and use them to extract the corresponding effective depletion depth at a single bias voltage of −150 V .

AstroPix↗
DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as p2r, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these miniapps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as \ptor, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these mini-apps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

Atif, Mohammad [Brookhaven] (ORCID:000000026889770↗
DOE OSTI2026

An Autonomous MCP Bridge to Rucio: Enhancing Data Management Accessibility for High Energy Physics

The Rucio Data Management System [1] is an important tool used by High Energy Physics experiments, including those at Fermi National Accelerator Laboratory, to store and manage exabyte-scale scientific datasets. Despite its central role in coordinating data across globally distributed storage sites, Rucio's command line interface (CLI) presents a steep learning curve, and makes it difficult for scientists to navigate through. To solve this issue, a containerized Model Context Protocol (MCP) [2] server was built that connects Large Language Models directly to Rucio, allowing AI agents to handle data tasks by using simple, natural language rather than memorized terminal commands. The core engineering focus of this project was moving the server away from slow terminal commands that require text parsing and replacing them with a native Python Client API toolset and a planned REST API framework. Moving to the Python API handles data operations directly in memory, which helps clear up formatting errors, provides the AI with clean, structured JSON data and speeds up tool execution. To prove that the system actually works, a benchmarking pipeline was also built with various questions to test the AI across four different model configurations. The questions included finding data scopes, tracking down specific datasets, and checking replication rules. Through benchmarking, early runs showed that with raw terminal text, the model would get confused and stuck, whereas switching to the Python API to feed the AI clean, structured data yielded massive improvement. By creating an intelligent and autonomous bridge to a storage network, this project shows how AI can be implemented in scientific data management, which ultimately helps scientists at Fermilab spend less time sorting through data and more time focusing on their experiments and analysis.

Akella, Kashyap [William Rainey Harper Coll.]↗
DOE OSTI2025

Atmospheric River Detection Under Changing Seasonality and Mean-State Climate: ARTMIP Tier 2 Paleoclimate Experiments

Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single-forcing climate model experiments under the aegis of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO2 levels of the Last Glacial Maximum to a preindustrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds. In the low CO2 simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean-state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases.

Atmospheric river, paleoclimate↗
DOE OSTI2025

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗
DOE OSTI2024

Intelligent Pixel Detectors: Towards a Radiation Hard ASIC with On-Chip Machine Learning in 28 nm CMOS

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. With event rates as high as 40 MHz, these detectors will generate petabytes of data per second. To enable discovery within strict bandwidth and latency constraints, future trackers must be capable of fast, power efficient, and radiation hard data-reduction at the source. We are developing a radiation hard readout integrated circuit (ROIC) in 28nm CMOS with on-chip machine learning (ML) for future intelligent pixel detectors. We will show track parameter predictions using a neural network within a single layer of silicon and hardware tests on the first tape-outs produced with TSMC. Preliminary results indicate that reading out featurized clusters from particles above a modest momentum threshold could enable using pixel information at 40 MHz.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A Climatology and Life‐Cycle Characteristics of Atmospheric Fronts and Their Associated Precipitation

Abstract Atmospheric fronts are one of the main sources of mid‐latitude variability. We employ a novel method for identifying and tracking fronts and frontal precipitation. Thermal and dynamical variables are used to identify fronts as areal objects in space, which are tracked in time using the open‐source TempestExtremes software package. Precipitation objects are co‐located to identify frontal precipitation. The method is subjected to validation and sensitivity tests using manually curated data from the National Weather Service. Climatologies of fronts and frontal precipitation are computed from reanalysis and observations; fronts are present upwards of 14% of the time in the storm tracks, and represent the majority (up to 90%) of total and extreme precipitation. Novel aspects of the method are showcased through the lifetime characteristics of fronts across North America. Three sets of warm and cold fronts were discovered, and their duration, distance‐traveled, and translation velocity are examined. Plain Language Summary Mid‐latitude low‐pressure systems and weather fronts are important for our day‐to‐day experience of weather events, particularly in the mid‐latitudes. This work makes use of standardized atmospheric data and creates a method of automatically tracking these important atmospheric features and their precipitation to quantify their relative role in global precipitation. Weather fronts are persistent in the mid‐latitudes and are associated with the majority of precipitation–particularly the most intense precipitation. Trajectories of fronts over North America are categorized to create a set of archetypal fronts that occur in that region. The differences between these types of fronts are characterized. Key Points An automated, efficient, and skillful frontal detection algorithm is developed and validated Fronts contribute a larger fraction of extreme precipitation than all precipitation in mid‐latitude storm tracks Fronts across North America have substantial variation in characteristics depending on their origin location

extratropical cyclone↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Module Testing Procedures and Results for the CMS Phase-2 Outer Tracker Upgrade at Fermilab

The High-Luminosity LHC (HL-LHC) will operate at significantly increased luminosities and is expected to deliver about 3000 $fb^{-1}$ of proton-proton collision data at $\sqrt{s}=14$ TeV over a decade of operation. To maintain efficient tracking and triggering performance under high pileup and radiation conditions, the CMS experiment is upgrading its tracking detector for Phase-2 operations. The upgraded Outer Tracker (OT) will consist of Pixel-Strip (PS) and Strip-Strip (2S) silicon modules capable of providing tracking information to the Level-1 trigger at 40 MHz. Production and qualification of OT modules have been ongoing for about one year across several assembly and testing centers in the US, Europe, India, and Pakistan, requiring extensive testing to ensure stable operation in the HL-LHC environment. Fermilab is responsible for the production and testing of a significant fraction of the OT modules. The testing activities include IV characterization of silicon sensors, noise and pedestal measurements, verification of communication between module components, and burn-in studies using cold-box systems operated under controlled thermal conditions. Results from module testing and qualification studies performed during production will be presented.

Baradia, Sweta [UC, Davis (main)]↗
DOE OSTI2025

Videos and front speeds of frontal ring-opening metathesis polymerization (FROMP) of DCPD/ENB with norbornene-functionalized PDMS comonomers

This dataset contains videos and front speed measurements for 16 frontal ring-opening metastasis polymerization experiments of dicyclopentadiene (DCPD)/5-ethylidene-2-norbornene (ENB) resins and norbornene-functionalized polydimethylsiloxane (nor-PDMS) comonomers. Each run was carried out in a 10 mm diameter glass test tube and recorded to quantify front propagation behavior. Reported front speeds were extracted by video tracking and reported maximum front temperatures were measured with a thermocouple.

Clarke, Brandon R.↗
DOE OSTI2024

Overview of the New Beam Physics Research at the IOTA/FAST Facility

The Fermilab Accelerator Science and Technology (FAST) facility is dedicated to the exploration of novel concepts in accelerator and beam physics, and the development of a robust workforce, in order to enable and enhance next-generation particle accelerators. FAST comprises a high-brightness superconducting electron linac, and a storage ring, the Integrable Optics Test Accelerator (IOTA). Experiments in the most recent operational run include studies of nonlinear integrable lattices; tracking of single electrons; precise characterization of undulator radiation; studies with low-momentum-compaction lattices; and ultra-wide range beam diagnostics based on Photomultiplier tubes. In the linac, experiments on noise in intense electron bunches were conducted. The IOTA proton injector, currently being commissioned, will enable a diverse program on space-charge-dominated beams. Research areas include non-invasive beam profile monitoring for proton beams; beam dynamics with electron lenses; halo suppression, feedback systems, and electron cooling. In this presentation, we provide an overview of the recent results and highlight future plans together with opportunities for collaboration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

US HL-LHC cryo-assemblies at FNAL - testing and lessons learned

The U.S. High-Luminosity LHC Accelerator Upgrade Project (AUP) is fabricating ten cryogenic assemblies for the HL-LHC Q1/Q3 quadrupole optics at CERN, each integrating two Nb_{3}Sn-based magnets. Fermilab has tested three assemblies (LQXFA/B01–03) at its upgraded horizontal test stand under 1.9 K conditions. Overview of the test stand and the cryo-assembly tests is given along with main results. Challenges met and lessons learned are discussed. Successful testing validates the design and integration of U.S.-produced cryo-assemblies, keeping the project on track for timely delivery to CERN.

Stoynev, Stoyan [Fermilab] (ORCID:0000000345637702↗
DOE OSTI2026

Performance Validation of Endcap Timing Layer Detector Modules for CMS Phase-2 Upgrade

The High-Luminosity Large Hadron Collider (HL-LHC) will operate up to 200 simultaneous collisions per bunch crossing, which is a significant jump from the current value of about 30 collisions per bunch crossing, producing significant pileup that challenges accurate event reconstruction. To address this, the Compact Muon Solenoid (CMS) experiment is implementing the Endcap Timing Layer (ETL), a precision timing detector designed to provide timing measurements with a resolution of approximately 50 ps per hit and 35 ps per reconstructed track. This project focuses on the characterization and validation of ETL detector modules using laboratory laser test data. ETL performance is evaluated by analyzing key quantities such as Bunch Crossing Identification (BCID), Time-of-Arrival (TOA), Time-over-Threshold (TOT), Noise Stability etc. The resulting analysis provides insight into the timing performance and operational stability of ETL modules, contributing to the quality assurance process req uired before their installation in the CMS experiment and ensure that the modules can meet the long-term reliability requirements of approximately 10 years of operation without replacement.

Chipara, Munashe [Fermilab]↗
DOE OSTI2024

Test Beam Results of Planar Pixel Sensor for the CMS Phase 2 Inner Tracker Upgrade

Results of the test beam measurements that characterise the performance of CMS Readout Chip (CROC) sensors to be used in the High Luminosity era of the Large Hadron Collider (HL-LHC) are presented. The HL-LHC peak instantaneous luminosity of $7.5 \times 10^{34} \ \text{cm}^{-2} s^{-1}$ corresponds to an average of around 200 inelastic proton-proton collisions per beam-crossing every 25 ns. In order to efficiently reconstruct and track particles in this extreme and challenging conditions, the present CMS tracking detector will be completely replaced. The new tracking detector consists of an Inner Tracker closest to the beamline and an Outer Tracker surrounding it. These are populated with modules that comprise of readout chips and silicon sensors. The test beam measurements of these modules are vital to understand the performance of the related technologies. Using a primary 120 GeV proton beam from the Main Injector at Fermilab, data was collected at the Fermilab Test Beam Facility (FTBF) using the silicon tracker telescope that provides a precision position measurement of the track impact point with less than 5 $\mu$m uncertainty. The proton beam was incident on a 1x2 planar CROC module developed by Hamamatsu. The sensor has 100x25 $\mu m^2$ standard pixels and also a smaller number of 225x25 $\mu m^2$ longer pixels at the boundary between the two ROCs. We present characterization of these modules that includes pixel efficiency, resolution, cluster size and charge distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Statistical Correlation of Heliostat Pointing Deviation With Wind

This work was carried out as part of the Heliostat Consortium (HelioCon) Field Deployment subtask with the aim to develop a reduced order model framework for correlating wind speed and pointing deviation of a heliostat facet. There are only sparse field measurements of heliostat pointing deviations and accompanying wind conditions published in the literature. Heliostat test standards, such as IEC 62862-4-3, propose a suite of tests including laser pointing repeatability at wind speeds below 4 m/s, and provide technical requirements for heliostat slope and tracking deviations in coarse average wind speed bins of 4 m/s, 6 m/s, and 8 m/s. In addressing the gap of the variation of heliostat pointing deviation with wind speed, field measurements of laser pointing on a grid target and wind conditions were analyzed in this study at the Third-Party Metrology Platform at the National Laboratory of the Rockies (NLR) Flatirons Campus. Horizontal pointing deviations were found to follow a logarithmic relationship with peak wind speed, whereas vertical pointing deviations follow an exponential relationship with peak wind speed. Both horizontal and vertical pointing deviations also follow a second order polynomial relationship, as expected from the proportionality of elastic loads and deformations with the square of wind speed. The results indicate that heliostat facet pointing deviations in the vertical direction increase at a faster rate than in the horizontal direction with increasing wind speed over the tested range, however these are dependent on the heliostat structural design. Next steps are recommended for additional field measurements to confirm a linear relationship of pointing deviation with applied moment on a heliostat facet, and to distinguish between gravity-induced and wind-induced pointing deviations at different elevation angles. The derived correlations in the preliminary analysis in this report serve as a case study for heliostat developers and plant operators to estimate the wind-induced pointing deviations and their variation with peak gust wind speed. Next steps in future work would recommend higher resolution and longer duration datasets for different elevation angles and wind directions to reduce uncertainties and variance of collected laser beam spot data and their correlations with bin-averaged wind speed.

17 WIND ENERGY↗
DOE OSTI2026

Queen bees offload pesticide burden to eggs when social buffering is overwhelmed

Honey bee colonies pollinate about one-third of the world’s food crops, and their rapid decline directly threatens agricultural productivity and ecosystem stability. Understanding how colony-level social defenses influence pesticide fate and the circumstances under which they fail is therefore a crucial question in pollinator biology. We used biological accelerator mass spectrometry (BioAMS), a sensitive radiotracer technique, to track the movement of a model pesticide through a small honey bee colony under laboratory conditions. We tested the hypothesis that social buffering protects honey bees from toxic accumulation and that this protection can be overcome, leading to maternal offloading of the pesticide to developing eggs. Consistent with this hypothesis, our results identified three key mechanisms governing chemical movement within a social insect colony: (1) worker bees initially decrease dietary pesticide levels by 95% through diet filtering and deposition in honeycombs, though this declines to 86% by day 10; (2) queen bees maintain markedly lower pesticide levels than workers but, over time, they accumulate the pesticide in their ovaries and transfer it into developing eggs, revealing a previously undocumented protective mechanism in reproductive individuals; and (3) the presence of a queen bee shifts colony-wide chemical distribution by concentrating worker exposure and increasing pesticide deposition in wax. Our findings show that honey bee colonies function as integrated detoxification networks, in which chemical fate depends on complex social behaviors and caste-specific physiology. When social buffering is overwhelmed, reproductive queens may survive by transferring their chemical burden to their offspring.

Biological and medical sciences↗