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At least 19 records

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN

The data acquisition system of the LZ dark matter detector: FADR

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. Furthermore, the hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Data Acquisition and Control for Marine Energy Devices: Cost Considerations

This document discusses the process involved with developing a data acquisition system specifically in the context of applications for Marine Renewable Energy (MRE) technologies however, much of what is presented is applicable to applications requiring data acquisition in general. The detail on the process is provided to highlight the critical steps and needs for a successful measurement campaign and to understand what can impact the overall outcome, cost, and schedule. The process presented is an amalgamation of best practices, lessons learned, recommendations, and prudent technical project planning and management. Data acquisition systems may be tightly integrated with or into the device under measurement and it often has its own dependencies that must be met. Therefore, early consideration and planning for the data acquisition system are stressed throughout this document.

13 HYDRO ENERGY

Advancing $otsdaq$ for Optimized Data Acquisition

High-energy physics (HEP) experiments demand data acquisition (DAQ) systems capable of orchestrating complex detector operations, high data throughput, and responsive, real-time feedback. Traditional systems often have steep learning curves, making onboarding difficult for new users. The Off-The-Shelf Data Acquisition $otsdaq$ framework was developed to address these issues by providing a modular and flexible interface that is easier to operate while remaining customizable enough for experimental setups. As the upcoming Mu2e experiment prepares for deployment, improving stability, usability, and performance has become increasingly critical. Our work enhances $otsdaq$ with features that streamline visualization, correct data metrics, improve debugging workflows, and stabilize the user interface.

Mohammed, Ali (ORCID:0009000860386626)

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

Developing and Managing Data Acquisition Software Using Spack

The Data Acquisition systems of particle physics experiments regularly push the boundaries of high-throughput computing, demanding low-latency collection of data from thousands of devices, collating data into time-sliced events, processing these events and making trigger decisions, and writing the selected data streams to disk. To accomplish these tasks, the DAQ Engineering and Operations department at Fermilab leverages multiple software libraries and builds reusable DAQ frameworks on top. These libraries must be delivered in well-defined bundles and are thoroughly tested for compatibility and functionality before being deployed to live detectors. We have several techniques used to ensure that a consistent set of dependencies can be delivered and re-created at need. We must also support active development of DAQ software components, ideally in an environment as close as possible to that of the detectors. This development often occurs across multiple packages which have to be built in concert and features tested in a consistent and reproducible manner. I will present our scheme for accomplishing these goals using Spack environments, bundle packages, and Github Actions-based CI.

Flumerfelt, Eric [Fermilab]

Towards Online Machine Learning in DUNE Data Acquisition

Processing the large volumes of data produced by liquid argon time projection chamber (LArTPC) experiments presents a significant challenge, especially those at the scale of DUNE. This is a particular challenge when aiming to trigger on low-energy neutrinos from core-collapse supernovae, which are typically buried in a high-rate radiological background. To enable real-time event selection suitable for such rare signals, we are developing machine learning based data filtering methods. In order to demonstrate the feasibility of this approach, we implemented such pipeline using the ICEBERG detector at Fermilab as a small-scale LArTPC, with a focus on identifying Michel electrons as a proxy for low-energy neutrino interactions. This poster will present the current status of integrating these machine learning models into the data acquisition (DAQ) system of this detector.

Dalager, Olivia [Fermilab]

MODAQ 2.0 (Modular Ocean Data AcQuisition System v2.0) [SWR-24-138]

MODAQ 2.0 is the continuation of the Modular Ocean/Offshore Data AcQuisition system which offers new benefits of being based on generally available hardware and open-source development tools. The MODAQ 2.0 project is the amalgamation of ROS packages, tools, and guidance for developing data acquisition and control applications for marine energy devices using a ROS2 based architecture. The MODAQ 2.0 Reference Design includes several packages that are targeted for the marine energy sector and allow most developers with a basic background in programming to spin up a high-quality DAQ and control system. It is comprised of multiple software repositories which can be found at the MODAQ2 GitHub Organization: https://github.com/NREL-MODAQ2

Nichols, Casey

The Data Acquisition System for Phase-III of the BeEST Experiment

The BeEST experiment is a precision laboratory search for physics beyond the standard model that measures the electron capture decay of 7 Be implanted into superconducting tunnel junction (STJ) detectors. For Phase-III of the experiment, we constructed a continuously sampling data acquisition system to extract pulse shape and timing information from 16 STJ pixels offline. Four additional pixels are read out with a fast list-mode digitizer, and one with a nuclear MCA already used in the earlier limit-setting phases of the experiment. Here, we present the performance of the data acquisition system and discuss the relative advantages of the different digitizers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Constellation: The autonomous control and data acquisition system for dynamic experimental setups

The operation of instruments and detectors in laboratory or beamline environments presents a complex challenge, requiring stable operation of multiple concurrent devices, often controlled by separate hardware and software solutions. These environments frequently undergo modifications, such as the inclusion of different auxiliary devices depending on the experiment or facility, adding further complexity. The successful management of such dynamic configurations demands a flexible and robust system capable of controlling data acquisition, monitoring experimental setups, enabling seamless reconfiguration, and integrating new devices with limited effort. This paper presents Constellation, a flexible and network-distributed control and data acquisition software framework tailored to laboratory and beamline environments, that addresses the limitations of existing solutions. The framework is designed with a focus on extensibility, providing a streamlined interface for instrument integration. It supports efficient system setup via network discovery mechanisms, promotes stability through autonomous operational features, and provides comprehensive documentation and supporting tools for operators and application developers such as controllers and logging interfaces. At the core of the architectural design is the autonomy of the individual components, called satellites, which can make independent decisions about their operation and communicate these decisions to other components. This paper introduces the design principles and framework architecture of Constellation, presents the available graphical user interfaces, shares insights from initial successful deployments, and provides an outlook on future developments and applications.

Autonomy

Remote Instrumentation and Data Acquisition

This poster outlines the development and implementation of a remote data acquisition system for waveform analysis using a Rohde & Schwarz oscilloscope. The project involved capturing waveform data, and transferring it to a local machine for visualization and analysis. The core logic was developed in C++ with a focus on object oriented programming and the use of polymorphism so the main application can interact with any instrument without knowing its exact type, simplifying the overall logic and making it easier to add or swap out components without changing the rest of the codebase.. The system issues Standard Commands for Programmable Instruments (SCPI) via a socket connection and parses the oscilloscope s ASCII waveform data. The C++ application was containerized using Docker for ease of portability, and reproducibility. Emphasis was placed on secure networking practices, error handling, and effective data capture. The report describes the technical steps taken, challenges encountered, and future work, providing insight into the practical integration of hardware interfacing with remote computational environments.

Parikh, Jaymil [Illinois U., Urbana]

Five-analyzer Johann spectrometer for hard X-ray photon-in/photon-out spectroscopy at the Inner Shell Spectroscopy beamline at NSLS-II: design, alignment and data acquisition

Here, a recently commissioned five-analyzer Johann spectrometer at the Inner Shell Spectroscopy beamline (8-ID) at the National Synchrotron Light Source II (NSLS-II) is presented. Designed for hard X-ray photon-in/photon-out spectroscopy, the spectrometer achieves a resolution in the 0.5–2 eV range, depending on the element and/or emission line, providing detailed insights into the local electronic and geometric structure of materials. It serves a diverse user community, including fields such as physical, chemical, biological, environmental and materials sciences. This article details the mechanical design, alignment procedures and data-acquisition scheme of the spectrometer, with a particular focus on the continuous asynchronous data-acquisition approach that significantly enhances experimental efficiency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN

Remote Instrumentation and Data Acquisition: An Internship Research Report

This report outlines the development and implementation of a remote data acquisition system for waveform analysis using a Rohde & Schwarz oscilloscope. The project involved capturing waveform data, and transferring it to a local machine for visualization and analysis. The core logic was developed in C++ with a focus on object oriented programming and the use of polymorphism so the main application can interact with any instrument without knowing its exact type, simplifying the overall logic and making it easier to add or swap out components without changing the rest of the codebase.. The system issues Standard Commands for Programmable Instruments (SCPI) via a socket connection and parses the oscilloscope’s ASCII waveform data. The C++ application was containerized using Docker for ease of portability, and reproducibility. Emphasis was placed on secure networking practices, error handling, and effective data capture. The report describes the technical steps taken, challenges encountered, and lessons learned, providing insight into the practical integration of hardware interfacing with remote computational environments.

Parikh, Jaymil [Fermilab]

MODAQ-BB (Modular Offshore Data Acquisition System - Blackbox) [SWR-24-72]

MODAQ-BB is a compact, rapid deployment data acquisition system that can withstand water depths up to 400m. Codenamed "BlackBox" (or simply BB), since its initial purpose was to track marine assets and record vital data streams that could later be recovered in the event of a mishap - much like a traditional black box used in aviation and shipping, the name has stuck. MODAQ BlackBox is a battery-operable microcontroller platform with internal inertial sensing, GPS, satellite communications, and additional I/O (input/output) support in a depth-rated pressure enclosure. Since BB is self-contained and relatively compact, it can be quickly deployed with minimal effort. The enclosure can be clamped to a tube (such as part of a railing) or mast in a location with unobstructed view of the sky using the available clamp accessory or a common hose clamp. While BB is designed to operate unattended, users can configure what data are uploaded and the frequency of satellite transmissions. Once data are uploaded, they can be relayed to an email distribution list, the MODAQ:Web operational dashboard, or a custom destination. BB has found utility in the National Laboratory of the Rockies' (NLR's) Waterpower projects beyond its original vision and has been configured and successfully deployed in more traditional data-gathering applications where a simple, battery-operated solution was indicated. As part of the MODAQ family, BB fills a space in the spectrum of missions that can be supported that were previously impractical using the traditional MODAQ hardware architecture due to factors such as weight, size, and cost.

Raye, Robert

Low Yield Nuclear Monitoring Physics Experiment 1 – Integrated Data Acquisition System Design and Initial Observations

The report documents the design of the Integrated Data AcQuisition (IDAQ) system and observations recorded during the first in a series of underground chemical explosions conducted on the Nevada National Security Site (NNSS) in southern Nevada. Experiments are funded as part of Low Yield Nuclear Monitoring (LYNM) research and development within the United States National Nuclear Security Administration NA-22 nuclear non-proliferation program. The series is part of the broader Physical Experiment 1 (PE1) being conducted in and around the P-tunnel facility on the NNSS. Each explosive experiment utilizes several tons of comp-B to generate signals recorded by a broad suite of instrumentation. The IDAQ serves as the backbone for all subsurface instrumentation providing precise time synchronization, remote control, data exfiltration and backup, along with recording several sensing modalities throughout the underground complex that includes ground motion, environmental conditions, and electromagnetic signals.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF

Upgrade of the CAESium-iodide scintillator ARray (CAESAR) electronics and data acquisition system for optimized performance at FRIB

Here, we report on the upgrade of the electronics and data acquisition (DAQ) of the high-efficiency CAESium-iodide scintillator ARray (CAESAR) at the Facility for Rare Isotope Beams (FRIB). With the on-going capability ramp-up of FRIB, CAESAR is expected to continue to be an in-demand -ray spectrometer owing to its high detection efficiency, compactness, and modularity, enabling easy integration with additional detection and DAQ systems. Within this context, the CAESAR electronics and DAQ were upgraded to remove obsolete modules, enhance the ease of integration with external instruments, and optimize the DAQ live time. We present the comprehensive results from offline (γ-ray sources) and online (in-beam experiment) commissioning, characterizing the performance of CAESAR’s new electronics and DAQ.

CsI(Na) scintillator array

The git based ATLAS data acquisition configuration service in LHC Run 3

The ATLAS experiment at the LHC at CERN uses a large, distributed trigger and data acquisition system composed of many computing nodes, networks, and hardware modules. Its configuration service is used to provide descriptions of control, monitoring, diagnostic, recovery, dataflow and data quality configurations, interconnections, and parameters for modules, chips, and channels of various online systems, detectors, and the whole ATLAS experiment. Those descriptions have historically been stored in more than one thousand interconnected XML files, which are updated by various experts many times per day. Maintaining error-free and consistent sets of such files and providing reliable and fast access to current and historical configurations is a major challenge. This paper gives details of the configuration service upgrade on the modern Git version control system backend for LHC Run 3 and its exploitation experience. It may be interesting for developers using human-readable file formats, where consistency of the files, performance, access control, traceability of modifications, and effective archiving are key requirements.

Soloviev, Igor [Univ. of California, Irvine, CA (U