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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ionization Profile Monitors for the IOTA Proton Beam

Ionization profile monitors (IPMs) are widely used in accelerators for non-destructive and fast diagnostics of high energy particle beams. Two such monitors - one vertical and one horizontal - are being developed for installation in the IOTA storage ring at Fermilab. They will be used for turn-by-turn (microseconds scale) measurements of the 70 MeV/c IOTA proton beam sizes. In this paper we present the IPMs design (largely following the FNAL Booster IPMs which employ no external guiding magnetic fields), their mechanical, vacuum, and electric subsystems and DAQ, and discuss anticipated effects on the beams circulating in IOTA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

High-Throughput Custom Monitoring for the Mu2e TDAQ System

In this project we are studying the application of programmable network hardware to provide a custom monitoring capability for the Mu2e Trigger and Data Acquisition System (TDAQ) system. The goal of the Mu2e experiment is to search for a charged-lepton flavor violating processes where a negative muon converts into an electron in the field of an aluminum nucleus. This experiment is intended to improve by four orders of magnitude the search sensitivity reached so far. We have a working prototype of a system that provides high-throughput, custom monitoring for the Mu2e TDAQ system. The custom Mu2e network packet header format is parsed as it crosses the network switch. Parsing extracts bits that convey information about error states at read-out controllers (ROCs). This information is periodically relayed to the switch controller, which in turn alerts experiment operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Monitoring Helium Cryogen Usage with iFix Software at IB1 Test Facility

At the IB1 facility of the Applied Physics and Superconducting Technology Directorate within the Cryogenic Division at Fermilab, Liquid Helium is essential to the testing activities. The test stands require large amounts of Helium to test the thermal and superconducting cavities and magnets. The Liquid Helium that enters the test stand is monitored through a series of valves and controls to determine the start and stop for monitoring time. There are 3 phases of cryogen usage that must be considered for each stand, cooldown, warming and overnight mode. With a new system in place, cold hour tracking will be more objective and precise within each test stand ensuring better calculations for User s fees which are charged to various groups that employ the facility and aid replenishment of Helium and continual operation at IB1.

Trillo, Angelica↗
DOE OSTI2024

Low Energy Muon Beam Diagnostics: Scintillating Fiber Profile Monitor

The MeV Test Area (MTA) houses the 400 MeV H- Beam at the end of the Linac and a secondary beamline of muons and pions created from hitting a Tungsten target. The MTA is in the Irradiation Test Area (ITA), where experiments involve studying the effects of radiation on materials in the MTA beam. There is a need for a retractable detector to monitor the secondary beam’s intensity and coarse profile. The SFPM was chosen when considering factors like ability to measure low rates and handle high intensities. The plan was to test different scintillating fibers & Silicon Photomultiplier (SiPM) models to figure out which combination gives the best signals, and gain familiarity with the detector assembly, operation, and data acquisition software before using with final detectors in beamline. The SiPM circuit has been tested with a LED pulser successfully. The immediate steps that follow will be to set the SiPM up on the monitor with three different types of optical fibers, use the Caen software to configure the best mode of data acquisition, and proceed with an offline source test using Strontium-90. Once the most efficient measurement method is clear, they will be ready for use in the beamline.

Leith, Justin↗
DOE OSTI2024

A Molten Salt Aerosol Spectroscopy Approach to Online Process Monitoring in Molten Salt Reactors

Recent research and development in molten salt reactors (MSRs) has led to many advanced reactor designs, many of which have demonstrations planned in the next decade. However, a significant challenge that must be overcome before liquid fueled MSRs become viable globally is nuclear material accountancy (NMA) and safeguards. Liquid-fueled MSRs are problematic to safeguards because the nuclear material is in the bulk phase, inventories are constantly changing, and there are potentially many outlet pathways that must be monitored, especially in designs with online chemical processing. At the Idaho National Laboratory, we have developed a process monitoring tool to circulate molten salt through a nebulizer and optical cell, where laser-induced breakdown spectroscopy (LIBS) and ultraviolet-visible (UV-VIS) are applied to track the elemental and oxidation states of the constituents in the salt aerosol. This approach has the potential to provide information on the actinides, fission products, and corrosion in the reactor or process. Preliminary testing in aqueous praseodymium chloride (PrCl3) and neodymium chloride (NdCl3) showed good sensitivity detection limits n developed calibration curves. Additional tests and analysis or ongoing in aqueous solutions while equipment is being scaled up for high temperature molten salt testing. Results for continued testing as well as a status of the molten salt design and anticipated commissioning will be presented.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2024

In-situ digital image correlation and thermal monitoring in directed energy deposition

A method and a system for digital image correlation and thermal monitoring during directed energy deposition are provided. The method and the system include global off-axis 3D mapping of surfaces features at high frame rates using the natural surface roughness of the additive build. Infrared thermography is projected onto these surface features to record the thermo-mechanical history of the finished component. As set forth herein, the method and the system provide a low-cost solution to monitoring and optimizing the unique temporal artifacts induced by complex scan strategies.

Haley, James↗
DOE OSTI2024

Optical device having a light-emitting structure and a waveguide integrated capacitor to monitor light

Examples described herein relate to an optical device with an integrated light-emitting structure to generate light and a waveguide integrated capacitor to monitor light. The light-emitting structure may emit light upon the application of electricity to the optical device. The waveguide integrated capacitor may be formed under the light-emitting structure to monitor the light emitted by the light-emitting structure. The waveguide integrated capacitor includes a waveguide region carrying at least a portion of the light. The waveguide region includes one or more photon absorption sites causing the generation of free charge carriers relative to an intensity of the light confined in the waveguide region resulting in a change in the conductance of the waveguide region.

Srinivasan, Sudharsanan↗
DOE OSTI2024

Systems and methods for monitoring fuel cell membrane degradation

Systems and methods for real-time continuous monitoring of fuel cell membrane degradation are provided. At least one microsensor can be used as an inline sensor integrated at the cathode exhaust and/or the anode exhaust of a fuel cell, such as a proton exchange membrane fuel cell (PEMFC)). The microsensor can monitor the PEMFC degradation status by sensing the emission of fluoride.

Dong, Dongmei↗
DOE OSTI2025

Analysis of SPND Material Candidates for Real-Time Neutron Spectrum Monitoring Poster

The future of the nuclear industry will be shaped by advanced reactor designs requiring innovative instrumentation for safe operation. A key area of innovation is the ability to accurately and reliably monitor the neutron energy spectrum during operations, which would also enhance the experimental capabilities of existing research reactors. To address this need, our research focuses on the potential use of Self-Powered Neutron Detectors (SPNDs) for real-time neutron spectrum monitoring. We investigated various candidate materials for SPNDs by evaluating their energy-dependent reaction rates. Promising materials were further modeled using MCNP to determine the free electron production per neutron across the neutron energy spectrum, approximating their energy-dependent signal sensitivity. Our findings identified Samarium (Sm) and Gadolinium (Gd) as top candidates for thermal neutrons, Hafnium (Hf) and Thulium (Tm) for epithermal neutrons, and Tantalum (Ta) for fast neutrons. These materials will undergo future experimental validation to confirm the modeled responses and assess their feasibility for real-time neutron spectrum measurements.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2026

Using Best Basis Inventory Data to Direct Strategies for Real Time Monitoring of Hanford High Level Waste – 26226

The potential to accelerate the processing of low- and high-level tank waste by applying real-time monitoring (RTM) of chemical and physical properties has prompted research into the suitability of multiple analytical methods for that purpose. The broad variety of waste stream properties and the large number of analytes of interest (as evidenced by Waste Acceptance Criteria (WAC) and Process Control Limit (PCL) lists) lead to an overwhelming set of possible analytical scenarios. This report describes the use of Best Basis Inventory (BBI) data to find the most relevant analytical targets for the specific case of monitoring the blending of High Level Waste from multiple tanks prior to introduction into a vitrification facility. Campaigns for blending this waste to minimize the risk of exceeding WACs and PCLs have been proposed. However, the predicted compositions of the blended materials do not incorporate any uncertainties that may be associated with the representativeness of the waste layer samples or the laboratory analyses that generated the BBI data. Also, they do not include any uncertainty associated with the precision of collecting highly specific fractions of the layers during a blending campaign or any inhomogeneities that may exist in those layers. Monte Carlo methods are used to apply uncertainties to the compositions of the individual layers specified in the campaign recipes. The resulting variations in the compositions of the blended materials allow estimation of the risks of exceeding WACs and PCLs for each campaign. A critical subset of WACs/PCLs – NOx, NaK, AlFeZr, and S – are especially at risk of being exceeded in multiple campaigns. These analytes should be the focus of instrument development. We also have extracted the expected solid/supernate distribution for these analytes, which establishes important performance criteria for individual analytical methods. The BBI data also permits an understanding of the different chemical forms in which the analytes appear. Thus, the need to establish instrumental sensitivity to these forms can be gainfully addressed. Although concentrating on one specific application – the blending of tank waste - this approach should be generalizable for the analysis of other possible RTM applications for waste processing.

Lascola, Robert [Savannah River National Laborator↗
DOE OSTI2026

Universal monitored dynamics in multimode bosonic systems

We propose a route to study monitored many-body dynamics in multimode bosonic systems using circuit quantum electrodynamics. In this experimental setting, we construct several bosonic models comprising brickwork circuits built from beam-splitter gates, local parity measurements, and optional on-site Hubbard interactions, and diagnose their monitored dynamics via ancilla purification and a learnability-based probe. Under parity measurements, generic gate sets exhibit behavior that is largely consistent with a conventional measurement-induced phase transition, while a special class of beam-splitter circuits shows an apparent critical-like high-measurement regime in which purification times scale linearly with system size. We show that for realistic noise, gate, and measurement rates, these signatures are observable with near-term circuit QED hardware.

Patel, Shivam [Rutgers U., Piscataway]↗
DOE OSTI2025

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗
DOE OSTI2022

Using advanced data structures to enable responsive security monitoring

Write-optimized data structures (WODS), offer the potential to keep up with cyberstream event rates and give sub-second query response for key items like IP addresses. These data structures organize logs as the events are observed. To work in a real-world environment and not fill up the disk, WODS must efficiently expire older events. As the basis for our research into organizing security monitoring data, we implemented a tool, called Diventi, to index IP addresses in connection logs using RocksDB (a write-optimized LSM tree). In this work, we extended Diventi to automatically expire data as part of the data structures’ normal operations. We guarantee that Diventi always tracks the N most recent events and tracks no more than N + k events for a parameter k < N, while ensuring the index is opportunistically pruned. To test Diventi at scale in a controlled environment, we used anonymized traces of IP communications collected at SuperComputing 2019. We synthetically extended the 2.4 billion connection events to 100 billion events. We tested Diventi vs. Elasticsearch, a common log indexing tool. In our test environment, Elasticsearch saw an ingestion rate of at best 37,000 events/s while Diventi sustained ingestion rates greater than 171,000 events/s. Our query response times were as much as 100 times faster, typically answering queries in under 80 ms. Furthermore, we saw no noticeable degradation in Diventi from expiration. We have deployed Diventi for many months where it has performed well and supported new security analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Detecting missing struts in metallic micro-lattices using high speed melt pool thermal monitoring

Metal lattices are an important class of cellular materials that offer great advantages by providing high-strength and lightweight structures as compared to bulk materials. Progress in additive manufacturing techniques has led to increased complexity in design and shape of produced objects and is greatly beneficial for the development of metallic lattice structures. However additive manufacturing of lattices suffers from unpredictable defect creation that can compromise its mechanical integrity. Although post-build inspection techniques can provide quality assurance of the process, accurate assessment can be technically challenging, time consuming and costly. In this work, we investigate the use of high-speed measurements of thermal emission from the melt pool to identify defective individual struts formed with a missing bottom half in an otherwise fully built lattice structure produced with laser powder bed fusion. Surprisingly, results indicate lower photodiode signal, suggesting colder melt pool surface temperature, when printing struts with missing bottom half as compared to nominal struts. Additional thermographic imaging and multi-physics simulations reveal that the low photodiode signal is accompanied by presence of hot spatters carrying heat away from detection and continuous avalanche of powder on the melt pool. Based on these observations, a method was developed to identify defective individual struts with missing bottom half in full built lattices. This prediction approach provides valuable insights about part quality which are important for process qualification and illustrates the utility of melt pool thermal emission monitoring for identifying specific defects introduced by laser powder bed fusion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗
DOE OSTI2025

New generation bunch shape monitor for ion accelerators

Measuring longitudinal beam parameters is important for operation and development of high intensity linear accelerators, but it is notoriously difficult for proton and ion beams at non-relativistic energies. The Bunch Shape Monitor (BSM) is a device used for measuring the longitudinal bunch distribution in ion linacs. The existing BSM models have poor electron collection efficiency from the wire and are limited to one-dimensional measurements of the phase coordinate. In response to this problem, we have developed a new generation BSM with improved performance. The proposed design incorporates three major innovations: First, the collection efficiency was improved by adding a focusing field between the wire and the entrance slit, which will also allow measurements over a much wider dynamic range. Second, an improvement in the measurement speed was achieved by sampling longitudinal profiles of multiple energy slices simultaneously, where the BSM wire is placed at the exit of an ion spectrometer so that ions with different energies hit the wire at different horizontal coordinates along the wire. Finally, the design incorporates a motion system that can shift the wire and deflecting cavity together, enabling transverse profile measurements like a wire scanner. Here, in this paper, we will provide the design of the new BSM and report on its beam test results at the Spallation Neutron Source facility in Oak Ridge National Laboratory.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Synchronized Waveforms – A Frontier of Data-Based Power System and Apparatus Monitoring, Protection, and Control

Voltage and current waveforms contain the most authentic and granular information on the behaviors of power systems. In recent years, it has become possible to synchronize waveform data measured from different locations. Thus large-scale coordinated analyses of multiple waveforms over a wide area are within our reach. This development could unleash a set of new concepts, strategies, and tools for monitoring, protecting, and controlling power systems and apparatuses. This paper presents an in-depth review and analysis of the advancements in synchronized waveform data, including measurement devices, data characteristics, use cases, and comparisons with synchrophasor data. Based on the findings, five strategies are proposed to discover and develop synchronized waveform based applications over multiple application areas. The paper also presents three complementary measurement platforms and two data screening algorithms for application implementation. It further discusses committee activities and standard developments useful to explore the full potential of the data.

24 POWER TRANSMISSION AND DISTRIBUTION↗