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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sub-THz passive detector performance evaluation with RadiaBeam photoinjector

Wakefield accelerators, based on THz and mm-wave structures, promise to reach the highest energies in record small footprints. However, operation at such frequencies is associated with strong generation of dipole modes that can destroy the beams, which requires controlling the electron beam position at the micron scale. The existing conventional techniques for electron beam position monitoring are not applicable for sub-THz structures due to the space constraints. Here, on the other hand, if dipole modes amplitudes can be measured precisely at different planes, one can derive beam position relative to the central axis. For such a technique a reliable and cost-effective sensor capable of operating in high repletion rate regime is required. In this paper we review the experimental evaluation of a passive sensor candidate for such applications using RadiaBeam 4.5 MeV photoinjector.

Accelerator↗
DOE OSTI2025

Development of a versatile plate spectrometer for electron beam characterization

A new instrument for electron beam characterization has been developed, based on measuring the range of beam electrons in different thicknesses of aluminum, to determine both the current and energy of an electron beam traveling in open air. This instrument is referred to as a ‘plate spectrometer’ as the thickness of the spectrometer is adjusted by adding or removing aluminum plates. This spectrometer was assembled and then characterized at the Idaho Accelerator Center (IAC) with three different beam energies and with one beam energy at the University of Maryland Radiation Facilities. The plate spectrometer was able to match the median energies and provide a reasonable constraint to the beam distributions seen in the IAC magnetic spectrometer. Finally, in a separate experiment, the plate spectrometer was also seen to agree with a dosimetry characterization of the beam at the University of Maryland Radiation Facilities and improved upon the uncertainties of this measurement.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Nondestructive Characterization of Antireflective Coatings on PV Modules

Antireflective coatings (ARCs) are used on the vast majority of solar photovoltaic (PV) modules to increase power production. However, ARC longevity can vary from less than 1 to over 15 years depending on coating quality and deployment conditions. A technique that can quantify ARC degradation nondestructively on commercial modules would be useful both for in-field diagnostics and accelerated aging tests. In this article, we demonstrate that accurate measurements of ARC spectral reflectance can be performed using a modified commercially available integrating-sphere probe. The measurement is fast, accurate, nondestructive, and can be performed outdoors in full-sun conditions. We develop an interferometric model that estimates coating porosity, thickness, and fractional area coverage from the measured reflectance spectrum for a uniform single-layer coating. We demonstrate the measurement outdoors on an active PV installation, identify the presence of an ARC, and estimate the properties of the coating.

14 SOLAR ENERGY↗
DOE OSTI2024

A differentiable simulation package for performing inference of synchrotron-radiation-based diagnostics

The direction of particle accelerator development is ever-increasing beam quality, currents and repetition rates. This poses a challenge to traditional diagnostics that directly intercept the beam due to the mutual destruction of both the beam and the diagnostic. An alternative approach is to infer beam parameters non-invasively from the synchrotron radiation emitted in bending magnets. However, inferring the beam distribution from a measured radiation pattern is a complex and computationally expensive task. To address this challenge we present SYRIPY ( SYnchrotron Radiation In PYthon ), a software package intended as a tool for performing inference of synchrotron-radiation-based diagnostics. SYRIPY has been developed using PyTorch , which makes it both differentiable and able to leverage the high performance of GPUs, two vital characteristics for performing statistical inference. The package consists of three modules: a particle tracker, Lienard–Wiechert solver and Fourier optics propagator, allowing start-to-end simulation of synchrotron radiation detection to be carried out. SYRIPY has been benchmarked against SRW , the prevalent numerical package in the field, showing good agreement and up to a 50× speed improvement. Finally, we have demonstrated how SYRIPY can be used to perform Bayesian inference of beam parameters using stochastic variational inference.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Laser and optical transport line for laser-based ion beam diagnostics and control in the SNS linear accelerator

We report our recent upgrade of the laser and optical transport line for the laser-based ion beam diagnostics (laser wire) system at the linear accelerator (linac) of the Spallation Neutron Source (SNS). A new light source based on diodepumped solid-state laser amplifiers has been developed to provide near diffraction-limited laser beam with a variety of pulse structures. The free-space optical transport line has been modified to include image relay optics with remote control, which greatly improved the laser beam quality and position stability at individual measurement stations. The upgraded system enables novel beam diagnostics/control capabilities including longitudinal profile measurement and high-energy proton beam extraction from the SNS linac.

Liu, Yun↗
DOE OSTI2023

High-Performance Accelerator Modeling: Toward Improving Controls and Diagnostics for High-Brightness Beams in Experiment

One of the main charges of beam physics is to improve the overall beam quality delivered to experiments and applications, which is generally quantified by the beam brightness. High brightness beams have numerous applications, including x-ray free electron lasers and ultrafast electron diffraction (UED). To these ends, this thesis details efforts to use high-performance models --- high-fidelity models that execute quickly --- for controls and diagnostics. To demonstrate the generality of these techniques, this thesis focuses on three of the most successful photoinjector designs currently used worldwide: the UCLA/SLAC/BNL-type high-gradient S-band gun, the continuous-wave high-repetition rate VHF APEX gun and the L-band DESY-PITZ-type gun. Work will be shown from Pegasus (UCLA), HiRES (LBNL) and FAST (FNAL).Specifically, data-driven models for online virtual diagnostics are presented, in this case, in the context of UED at HiRES, leading to a temporal resolution improvement. Methods for improving the fidelity of physics-based models are discussed, with examples at HiRES, Pegasus and FAST. Markov-chain Monte Carlo analysis is applied to match simulations, in the context of photocathode studies at HiRES and Pegasus. Lastly, the augmentation of online model-based predictions with model-independent optimization is explored in a fluctuating environment at Pegasus and HiRES. A central theme of this dissertation is working with parameter fluctuations when modeling an accelerator beamline. Long-term drifts and shot-to-shot jitter exist in every accelerator to a varying degree and therefore play an important role in every chapter of this dissertation. This thesis attempts to address the issues associated with these fluctuations when trying to develop faithful model representations of the system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

We discuss the implementation of a suite of virtual diagnostics at the FACET-II facility currently under commissioning at SLAC National Accelerator Laboratory. The diagnostics will be used for the prediction of the longitudinal phase space along the linac, spectral reconstruction of the bunch profile, and non-destructive inference of transverse beam quality (emittance) while using edge radiation at the injector dogleg and bunch compressor locations. These measurements will be folded into adaptive feedbacks and Machine Learning (ML)-based reinforcement learning controls to improve the stability and optimize the performance of the machine for different experimental configurations. In this paper we describe each of these diagnostics with expected measurement results that are based on simulation data and discuss progress towards implementation in regular operations.

Emma, Claudio (ORCID:0000000247191831)↗
DOE OSTI2023

A flexible proton beam imaging energy spectrometer (PROBIES) for high repetition rate or single-shot high energy density (HED) experiments (invited)

The PROBIES diagnostic is a new, highly flexible, imaging and energy spectrometer designed for laser-accelerated protons. The diagnostic can detect low-mode spatial variations in the proton beam profile while resolving multiple energies on a single detector or more. When a radiochromic film stack is employed for “single-shot mode,” the energy resolution of the stack can be greatly increased while reducing the need for large numbers of films; for example, a recently deployed version allowed for 180 unique energy measurements spanning ~3 to 75 MeV with <0.4 MeV resolution using just 20 films vs 180 for a comparable traditional film and filter stack. When utilized with a scintillator, the diagnostic can be run in high-rep-rate (>Hz rate) mode to recover nine proton energy bins. Here, we also demonstrate a deep learning-based method to analyze data from synthetic PROBIES images with greater than 95% accuracy on sub-millisecond timescales and retrained with experimental data to analyze real-world images on sub-millisecond time-scales with comparable accuracy.

3D printing↗
DOE OSTI2023

Radiation, optical, power flow, and electrical diagnostics at the Z facility: Layout and techniques utilized to operate in the harsh environment

The Z machine is a current driver producing up to 30 MA in 100 ns that utilizes a wide range of diagnostics to assess accelerator performance and target behavior conduct experiments that use the Z target as a source of radiation or high pressures. Here, we review the existing suite of diagnostic systems, including their locations and primary configurations. The diagnostics are grouped in the following categories: pulsed power diagnostics, x-ray power and energy, x-ray spectroscopy, x-ray imaging (including backlighting, power flow, and velocimetry), and nuclear detectors (including neutron activation). We will also briefly summarize the primary imaging detectors we use at Z: image plates, x-ray and visible film, microchannel plates, and the ultrafast x-ray imager. The Z shot produces a harsh environment that interferes with diagnostic operation and data retrieval. We term these detrimental processes “threats” of which only partial quantifications and precise sources are known. Finally, we summarize the threats and describe techniques utilized in many of the systems to reduce noise and backgrounds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Adaptive Machine Learning for Robust Diagnostics and Control of Time-Varying Particle Accelerator Components and Beams

Machine learning (ML) is growing in popularity for various particle accelerator applications including anomaly detection such as faulty beam position monitor or RF fault identification, for non-invasive diagnostics, and for creating surrogate models. ML methods such as neural networks (NN) are useful because they can learn input-output relationships in large complex systems based on large data sets. Once they are trained, methods such as NNs give instant predictions of complex phenomenon, which makes their use as surrogate models especially appealing for speeding up large parameter space searches which otherwise require computationally expensive simulations. However, quickly time varying systems are challenging for ML-based approaches because the actual system dynamics quickly drifts away from the description provided by any fixed data set, degrading the predictive power of any ML method, and limits their applicability for real time feedback control of quickly time-varying accelerator components and beams. In contrast to ML methods, adaptive model-independent feedback algorithms are by design robust to un-modeled changes and disturbances in dynamic systems, but are usually local in nature and susceptible to local extrema. In this work, we propose that the combination of adaptive feedback and machine learning, adaptive machine learning (AML), is a way to combine the global feature learning power of ML methods such as deep neural networks with the robustness of model-independent control. We present an overview of several ML and adaptive control methods, their strengths and limitations, and an overview of AML approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Online charge measurement for petawatt laser-driven ion acceleration

Laser-driven ion beams have gained considerable attention for their potential use in multidisciplinary research and technology. Preclinical studies into their radiobiological effectiveness have established the prospect of using laser-driven ion beams for radiotherapy. In particular, research into the beneficial effects of ultrahigh instantaneous dose rates is enabled by the high ion bunch charge and uniquely short bunch lengths present for laser-driven ion beams. Such studies require reliable, online dosimetry methods to monitor the bunch charge for every laser shot to ensure that the prescribed dose is accurately applied to the biological sample. In this paper, we present the first successful use of an Integrating Current Transformer (ICT) for laser-driven ion accelerators. This is a noninvasive diagnostic to measure the charge of the accelerated ion bunch. It enables online estimates of the applied dose in radiobiological experiments and facilitates ion beam tuning, in particular, optimization of the laser ion source, and alignment of the proton transport beamline. We present the ICT implementation and the correlation with other diagnostics, such as radiochromic films, a Thomson parabola spectrometer, and a scintillator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Pulse Length Monitor for Breakdown Diagnostics in THz and Mm-Wave Accelerators

The development of novel high-gradient accelerating structures operating at THz frequencies is critical for future free-electron lasers and TeV scale linear colliders. To reach high energies with reasonable length requires high accelerating gradients of ~100 MV/m. The main limitation to reaching these high-energy gradients is the vacuum RF breakdown phenomenon, which disrupts normal accelerator operations. For stable operations and to understand the breakdown microscopic dynamics, a new device capable of detecting the breakdown occurrences is required. In this paper, we provide the design of a pulse length monitor based on an analog to digital converter for fast signal digitization without the need to use high-speed digitizers to be used in a commercial mm-wave heterodyne spectrometer.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Assessment of errors in analytic modeling of permanent magnet electron spectrometers for laser-plasma accelerators

Here, we assess the error in three treatments of a critical electron beam diagnostic for laser-plasma acceleration (LPA) experiments: a permanent magnet electron spectrometer. Since LPA electron spectrometers are often difficult to calibrate due to the scarcity of well-characterized, tunable electron beam sources in the appropriate energy range and the mechanical complexity of electron spectrometers, the standard of calibration is Hall probe measurements. We first compare the electron spectrometer performance between SIMION calculations and the Hall probe measurements. We find up to a 60% (<8%) error in determining the absolute energy for electrons below (above) 80 MeV when using the SIMION-modeled magnetic field vs the measured magnetic field due to SIMION overpredicting fringe field strength. The difference in spectrometer energy resolution is within ∼10% between the modeled and measured fields. We then assess a simple block model, which is commonly used. We find that the simple block model presented here sufficiently captures the predicted as-built spectrometer performance for any application provided that the user can tolerate uncertainties on absolute energy determination up to 5% and errors on energy resolution up to 1%.

Electromagnetic optics↗