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DOE OSTI2026

Calculating beam extinction in a pulsed proton beam using FPGA-based peak detection

The Mu2e experiment at Fermilab imposes stringent requirements on the elimination of out-of-time beam in its pulsed proton beam, a requirement known as “extinction”. Utilizing a new μTCA-based FPGA data acquisition system, we recorded live particle data from scattered particles incident on an array of quartz Cherenkov radiators and photomultiplier tubes to measure the extinction in the inter-pulse gaps in the pulsed proton beam. Minuscule errors in the derived signal period can make a measurement of the extinction impossible, so after taking a Fourier transform, further optimizations on the period were done based on the assumption that the signal period is stable over the full time of the beam spill while it is being resonantly extracted. After these optimizations, the beam extinction was shown to be on the level of 10^3.

Hensley, Ryan [UC, Davis]↗

DOE OSTI2024

Two-terminator RF adapter for background/environment noise measurement

A two-terminator RF adapter for background noise measurement in a test environment comprises a system test port comprising a system test port termination and a system test port connector to connect to a system under test; and a data acquisition port, comprising a data acquisition port termination and a data acquisition port connector to connect to a data acquisition system.

Kolski, Jeffrey↗

DOE OSTI2022

Software Architecture and Hardware Organization in Mu2e Solenoid Field Mapping System

Herein, the Mu2e field mapping system is designed to produce high accuracy field maps of the detector solenoid used in the experiment. The data acquisition system is mobile and uses a self-propelled mapper with rotating arms equipped with 3D Hall probes. The measurements require not only accurate magnetic field readouts, but also accurate locations of all Hall probes while measuring data. The latter is accomplished by using the laser tracker to measure positions of several retroreflectors on the field mapper during data acquisition. The measurement process requires scanning the whole space inside the large solenoid and takes many hours to complete, which necessitates its full automation. The automation software includes control of the mapper, readout of Hall and NMR probes and control of a laser tracker, including prediction of retroreflector positions and execution of quality control checks. The software architecture and data acquisition hardware of the field mapping system are described, with special attention given to control of the laser tracker and its integration with the rest of the system.

3d hall probes↗

DOE OSTI2025

Detecting anomalous SRF cavity behavior with unsupervised learning

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a scheduled shutdown, the system successfully identified several issues with DAQ signals, confirming its effectiveness. Despite access to only a fraction of CEBAF’s SRF cavity signals, the framework efficiently detected several instances requiring intervention, demonstrating a significant improvement over traditional, labor-intensive methods of manual plot inspection. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Misuse Detection for a Generalized SFR Test Reactor

Sodium-cooled Fast Reactors (SFRs) present unique challenges for international safeguards. SFRs possess neutron physics characteristics that if configured appropriately could produce more fissile material than consumed. An adversary state may choose to build an SFR, justified by a lack of domestic natural uranium and limited access or interest to procuring uranium from international markets. Once constructed, the state may choose to misuse the SFR for the purpose of diverting fissile plutonium from declared operation. This work shows that a demonstration SFR does not need to be configured as a plutonium breeder to create one Significant Quantity (SQ) of plutonium in a short amount of time (e.g., one to few years). However, such an extreme case of misuse would change the core reactivity in such a way as to be easily indicated by deviations of control rod position compared to declared operation. In this work a contrived SFR demonstration reactor was modeled for the purpose of exploring proliferation scenarios and how such misuse could be detected using the SFR's Reactor Data Acquisition System (RDAS). Typically, the International Atomic Energy Agency (IAEA) does not have access to the control rod position, power, thermal, pressure sensing and indicating systems of nuclear power plants. However, this work shows that such data streams can be compared against a parallel detailed simulation model (a Digital Twin) to detect possible misuse.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2022

High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC

We present a comprehensive end-to-end pipeline to classify triggers versus background events in this paper. This pipeline makes online decisions to select signal data and enables the intelligent trigger system for efficient data collection in the Data Acquisition System (DAQ) of the upcoming sPHENIX and future EIC (Electron-Ion Collider) experiments. Starting from the coordinates of pixel hits that are lightened by passing particles in the detector, the pipeline applies three-stage of event processing (hits clustering, track reconstruction, and trigger detection) and labels all processed events with the binary tag of trigger versus background events. The pipeline consists of deterministic algorithms such as clustering pixels to reduce event size, tracking reconstruction to predict candidate edges, and advanced graph neural network-based models for recognizing the entire jet pattern. In particular, we apply the message-passing graph neural network to predict links between hits and reconstruct tracks and a hierarchical pooling algorithm (DiffPool) to make the graph-level trigger detection. We obtain an impressive performance (≥70% accuracy) for trigger detection with only 3200 neuron weights in the end-to-end pipeline. We deploy the end-to-end pipeline into a field-programmable gate array (FPGA) and accelerate the three stages with speedup factors of 1152, 280, and 21, respectively.

Instruments & Instrumentation↗

DOE OSTI2021

The Event Detection System in the NEXT-White Detector

This article describes the event detection system of the NEXT-White detector, a 5 kg high pressure xenon TPC with electroluminescent amplification, located in the Laboratorio Subterráneo de Canfranc (LSC), Spain. The detector is based on a plane of photomultipliers (PMTs) for energy measurements and a silicon photomultiplier (SiPM) tracking plane for offline topological event filtering. The event detection system, based on the SRS-ATCA data acquisition system developed in the framework of the CERN RD51 collaboration, has been designed to detect multiple events based on online PMT signal energy measurements and a coincidence-detection algorithm. Implemented on FPGA, the system has been successfully running and evolving during NEXT-White operation. The event detection system brings some relevant and new functionalities in the field. A distributed double event processor has been implemented to detect simultaneously two different types of events thus allowing simultaneous calibration and physics runs. This special feature provides constant monitoring of the detector conditions, being especially relevant to the lifetime and geometrical map computations which are needed to correct high-energy physics events. Other features, like primary scintillation event rejection, or a double buffer associated with the type of event being searched, help reduce the unnecessary data throughput thus minimizing dead time and improving trigger efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Waveform processing using neural network algorithms on the front-end electronics

In a multi-channel radiation detector readout system, waveform sampling, digitization, and raw data transmission to the data acquisition system constitute a conventional processing chain. The deposited energy on the sensor is estimated by extracting peak amplitudes, area under pulse envelopes from the raw data, and starting times of signals or time of arrivals. However, such quantities can be estimated using machine learning algorithms on the front-end Application-Specific Integrated Circuits (ASICs), often termed as “edge computing”. Edge computation offers enormous benefits, especially when the analytical forms are not fully known or the registered waveform suffers from noise and imperfections of practical implementations. In this work, we aim to predict peak amplitude from a single waveform snippet whose rising and falling edges containing only 3 to 4 samples. We thoroughly studied two well-accepted neural network algorithms, Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) by varying their model sizes. Further, to better fit front-end electronics, neural network model reduction techniques, such as network pruning methods and variable-bit quantization approaches, were also studied. By combining pruning and quantization, our best performing model has the size of 1.5 KB, reduced from 16.6 KB of its full model counterpart. It can reach mean absolute error of 0.034 comparing to that of a naive baseline of 0.135. Such parameter-efficient and predictive neural network models established feasibility and practicality of their deployment on front-end ASICs.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

The Fuel Motion Monitoring System at TREAT - Current Status and Future Plans

An important component of the United States Nuclear Fuel Safety Transient Testing Program, the Fuel Motion Monitoring System (FMMS) at Idaho National Laboratory's Transient Reactor Test Facility (TREAT) is fast-neutron hodoscope capable of imaging the location, movement, and relocation of nuclear fuel experiments under simulated transient accident conditions. The FMMS was refurbished in parallel with the TREAT restart program starting in 2014, restoring 96-channels of fast-neutron detection. Since returning to operation in 2017 the FMMS has supported many fuel safety experiments supporting accident tolerant fuel development, light-water reactor safety, space thermal nuclear propulsion fuel development, and advanced reactor research and development. In Phase 2 of the FMMS restoration. work is now under way to expand the FMMS' field-of-view by adding an additional 96 channels of fast neutron detectors to the system's hodoscope, along with an expanded data acquisition system and associated transient timing electronics. An overview of the FMSS system and its fast-neutron detectors will be presented along with examples of current FMMS imaging performance and associated information.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2022

Lifetime fatigue response due to wake steering on a pair of utility-scale wind turbines

Quantifying the impacts on turbine loads during wind farm control is an important consideration in assessing power production benefits. Wake steering controls aim to improve total wind farm performance by coordinating the control actions of individual turbines, wherein an upstream turbine is intentionally yawed at an offset angle from the measured wind direction. Consequently, this redirects its wake for improved power production and potentially reduces fatigue loads of the downstream turbines. This paper studies the lifetime fatigue loads associated with wake steering by using utility-scale wind turbine experimental data to conduct an analysis on a pair of wind turbines. This study was part of a large field experiment in which a group of five GE 1.5-MW SLE CWE turbines were selected as targets for conducting wake steering research. A standard loads instrumentation package and data acquisition system were installed on two turbines within the cluster to measure turbine fundamental loads. The time-series databases were used to calculate loads statistics as well as short-term and lifetime damage equivalent loads. Fatigue calculations followed the guidance in Annex H of the International Electrotechnical Commission standard 61400-1, Edition 4. Lifetime fatigue calculation results are presented in this analysis; three methods of assessing lifetime fatigue were used to determine percent difference for blade root moments, main shaft moments, main shaft torque, and tower top torque. For all three fatigue treatments, some components’ lifetime fatigue increases for the controlled turbine; however, the downwind turbine experienced a reduction in lifetime fatigue and combined effect for the turbine pair results in a reduction of fatigue when wake steering controls are applied.

17 WIND ENERGY↗

DOE OSTI2022

A Modern Ethernet Data Acquisition Architecture for Fermilab Beam Instrumentation

The Fermilab Accelerator Division, Instrumentation Department is adopting an open-source framework to replace our embedded VME-based data acquisition systems. Utilizing an iterative methodology, we first moved to embedded Linux, removing the need for VxWorks. Next, we adopted Ethernet on each data acquisition module eliminating the need for the VME backplane in addition to communicating with a rack mount server. Development of DDCP (Distributed Data Communications Protocol), allowed for an abstraction between the firmware and software layers. Each data acquisition module was adapted to read out using 1 GbE and aggregated at a switch which up linked to a 10 GbE network. Current development includes scaling the system to aggregate more modules, to increase bandwidth to support multiple systems and to adopt MicroTCA as a crate technology. The architecture was utilized on various beamlines around the Fermilab complex including PIP2IT, FAST/IOTA and the Muon Delivery Ring. In summary, we were able to develop a data acquisition framework which incrementally replaces VxWorks & VME hardware as well as increases our total bandwidth to 10 Gbit/s using off the shelf Ethernet technology.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

ESnet-JLab FPGA Accelerated Transport (data plane) [EJFAT (udplb)] v1.0

The ESnet-JLab FPGA Accelerated Transport system is a solution for streaming high-speed scientific measurement data from Data Acquisition Systems (DAQs) to high-performance computing facilties. It is generally compatible with many science workflows, and makes no assumptions about the specifics of any particular experiment. This program (udplb) implements the data plane portion of the EJFAT system. It is an FPGA design that rewrites and forwards data packets from a UDP-based scientific workflow to high-performance compute nodes. It depends on another program (udplbd, disclosed separately) to implement the control system.

Bengough, Peter [Malleable Networks, Inc.]↗

DOE OSTI2021

Simple and Scalable Streaming: The GRETA Data Pipeline

The Gamma Ray Energy Tracking Array (GRETA) is a state of the art gamma-ray spectrometer being built at Lawrence Berkeley National Laboratory to be first sited at the Facility for Rare Isotope Beams (FRIB) at Michigan State University. A key design requirement for the spectrometer is to perform gamma-ray tracking in near real time. To meet this requirement we have used an inline, streaming approach to signal processing in the GRETA data acquisition system, using a GPU-equipped computing cluster. The data stream will reach 480 thousand events per second at an aggregate data rate of 4 gigabytes per second at full design capacity. We have been able to simplify the architecture of the streaming system greatly by interfacing the FPGA-based detector electronics with the computing cluster using standard network technology. A set of highperformance software components to implement queuing, flow control, event processing and event building have been developed, all in a streaming environment which matches detector performance. Prototypes of all high-performance components have been completed and meet design specifications.

Cromaz, Mario↗

DOE OSTI2024

Lead tungstate calorimeters at Jefferson Lab and perspectives for the Electron–Ion Collider

Electromagnetic calorimeters based on PbWO4 scintillating crystals have a widespread applica- tion in experiments at different accelerator facilities such as CERN, FNAL, GSI, and Jefferson Lab. The unique properties of PbWO4 crystals, including a small radiation length and Molire radius, make them ideal for building high-granularity, radiation-hard detectors. This enables excellent spa- tial separation and energy resolution of reconstructed electromagnetic showers, making PbWO4 crystals the material of choice for numerous experiments. Lead tungstate calorimeters have been successfully used in several experiments at Jefferson Lab. Two large-scale detectors have been re- cently fabricated for future experiments : the Neutral Particle Spectrometer and the lead tungstate calorimeter of the GlueX detector. The future application of PbWO4 crystals in the ElectronIon Collider further highlights their ongoing importance in advancing experimental capabilities. In planning new experiments, the development of calorimeter instrumentation technologies becomes paramount. The integration of modern photodetectors, such as Silicon photomultipliers that are capable of operating in strong magnetic fields, and the implementation of streaming readout data acquisition systems, sophisticated shower reconstruction algorithms, and real-time data analysis are some examples of the continuously growing requirements of experimental setups. I will give an overview of the lead tungstate scintillating calorimeters and discuss some recent advancement in the calorimeter instrumentation.

Somov, Alexander↗

DOE OSTI2025

ESnet-JLab FPGA Accelerated Transport (control plane) [EJFAT (udplbd2)] v2.0

The ESnet-JLab FPGA Accelerated Transport system is a solution for streaming high-speed scientific measurement data from Data Acquisition Systems (DAQs) to high-performance computing facilties. It is generally compatible with many science workflows, and makes no assumptions about the specifics of any particular experiment. This program (udplbd version 2) implements the control plane for the system. It is responsible for programming network forwarding rules into the data plane (implemented by the hardware designed named udplb, described separately). It also implements the control loop necessary to match up offered workload with available capacity on high-performance compute nodes.

Howard, Derek [Lawrence Berkeley National Laborato↗

DOE OSTI2025

Implementation of high-speed data acquisition at DIII-D

Research at the DIII-D National Fusion Facility in San Diego focuses on short pulse plasma discharges that specialize on various shaping profiles. High-speed data collection is a critical component for the operation of many of DIII-D’s diagnostics and is fundamental for capturing high-resolution data used in experimental data analysis. Differing techniques enable the plasma control system (PCS) to perform complex real-time feedback control on microsecond time scales. This work presents a comprehensive overview of data acquisition, focusing on the hardware and software used in reliable data acquisition at DIII-D. The robust nature of the data acquisition system allows for various techniques to coexist seamlessly. However, as modern systems capable of nanosecond resolution become more common, existing architectures will need to be modified. Here, by addressing the key challenges of high-speed data acquisition, DIII-D is able to provide real-time data used in plasma operation and has the ability to acquire high fidelity data needed for future experimental fusion reactors, such as ITER.

Control↗

DOE OSTI2025

Signal processing and spectral modeling for the BeEST experiment

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of 7 Be by precisely measuring the recoil energy of the 7 Li daughter. In Phase III, the BeEST experiment has been scaled from a singl superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. Here, we have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large datasets. Furthermore, this article presents the optimized procedures before unblinding the majority of the Phase III dataset to search for physics beyond the standard model.

6 ≤ A ≤ 19↗

DOE OSTI2026

DAISY: A Rapid Approach to Evaluating Marine Energy Converter Sound (Final Technical Report)

This project’s objective was to improve the quality of acoustic information about marine energy converters that could be collected from groups of drifting hydrophones, while reducing the costs of deployment and data analysis. This was achieved through technology development addressing four focus areas: (1) minimizing flow-noise and self-noise, (2) integrating metadata streams into a single data acquisition system, (3) developing post-processing routines to facilitate rapid data review, and (4) enabling objective identification of marine energy converter sound against a backdrop of ambient noise using time-delay-of-arrival localization.

16 TIDAL AND WAVE POWER↗