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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Single-Shot Diagnostics of Microbunched Electrons in Laser-Driven Plasma Accelerators and Free-Electron Lasers

aThe need for single-shot diagnostics of the periodic longitudinal density modulation of relativistic electrons at the resonant wavelength (microbunching) in a free-electron laser (FEL) or at broadband visible wavelengths as in a laser-driven plasma accelerator (LPA) has been reaffirmed. In the self-amplified spontaneous emission (SASE) FEL case, statistical fluctuations in the microbunching occur in the startup- from-noise process. In the LPA, the plasma itself is chaotic and varies shot to shot. Fortunately, we have shown that coherent optical transition radiation (COTR) techniques, can assess beam size, divergence, spectral evolution, and z-dependent gain (100,000) of microbunched electrons in a past SASE FEL experiment at 530 nm*. Recently, the application to LPAs has been demonstrated with single-shot near-field (NF) and far-field (FF) COTR imaging done at the exit of an LPA for the first time**. In this case few-micron beam sizes and extensive fringes due to su b-mrad divergences were measured based on point-spread-function effects and an analytical model for COTR interferometry (COTRI), respectively. A new COTR-based diagnostics application to pre-bunched electron beams formed by co-propagating a laser pulse and the electron pulse in a short undulator (modulator) is also described.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Emerging Diagnostic Developments from the NNSS

Presentation describes diagnostic capabilities at Nevada National Security Site and affiliated sites, providing overview of optical velocimetry diagnostic technologies, imager technologies, dynamic temperature measurement technologies, broad band laser ranging technologies, and others.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Diagnostics for Linac Optimization With Machine Learning

The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To counter fluctuations of Linac output due to various effects to be described below we are working on implementing dynamic longitudinal parameter optimization based on Machine Learning (ML). As inputs for the ML model, signals from beam diagnostics have to be well understood and reliable. In this paper we discuss the status and plans for ML-based optimization as well as preliminary results of diagnostics studies.

43 PARTICLE ACCELERATORS↗
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 OSTI2025

Prelude to Simulation Diagnostics in MOOSE: Diagnosing Meshes

As finite element simulations increase in complexity, so does the need for high quality meshes. Without proper diagnostics, issues pertaining to poor mesh quality or improper mesh construction may go undetected, causing simulations to fail unexpectedly. This paper details the new mesh diagnostic system available in MOOSE, which provides users with the tools to inspect mesh quality for both externally and internally generated meshes. This system can detect issues arising from element volume size, non-conformal elements, intersecting edges, missing sidesets, as well as other common mesh issues. As meshes increase in size and complexity, such issues become more difficult to diagnose through visual inspection alone.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Implementation of a Doppler-Free Saturation Spectroscopy (DFSS) Diagnostic for Helicon Wave Electric Field Vector Measurement in Edge Plasma in DIII-D

A laser-based technique known as Doppler-free saturation spectroscopy (DFSS) has been designed, fabricated, and installed on the DIII-D National Fusion Facility to measure the helicon wave electric field vector in the edge plasma. These experimental measurements quantify phenomena resulting in decreased current drive efficiency due to wave/edge plasma interactions. This implementation of DFSS on DIII-D is the first of its kind on a tokamak and thus presents unique engineering challenges, including integration of the system onto an existing multidiagnostic port flange without impacts to system serviceability, as well as maintaining precise laser alignment over a 2-m distance during disruptions and thermal drift of the vessel. Further, these challenges were resolved using innovative design approaches such as a novel decoupled shutter system to facilitate serviceability of the in-vessel mirror assemblies without the need for personnel vessel entry, as well as an ex-vessel piezo-mirror-based optical system for laser beam shaping and real-time steering of the measurement location. The solutions to these engineering challenges were demonstrated during the successful installation and operation of these diagnostic components during the 2022 DIII-D vent and subsequent experimental campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

First measurement of the 10B(α,n)13N reaction in an inertial confinement fusion implosion at the National Ignition Facility: Initial steps toward the development of a radiochemistry mix diagnostic

We report the first measurement of the 10B(α,n)13N reaction in a polar-direct-drive exploding pusher (PDXP) at the National Ignition Facility (NIF). This work is motivated by the need to develop alternative mix diagnostics, radiochemistry being the focus here. The target is composed of a 65/35 at. % deuterium–tritium (DT) fill surrounded by a roughly 30 μm thick beryllium ablator. The inner portion of the beryllium ablator is doped with 10 at. % of 10B. Radiation-hydrodynamics calculations were performed in 1D to optimize both the remaining boron rho-R and the DT neutron yield. A charged-particle transport post-processor has been developed to study α-induced reactions on the ablator material. Results indicate a large 13N production from α-induced reactions on 10B, measurable by the radiochemical analysis of a gaseous samples system at the NIF. The PDXP target N201115-001 was successfully fielded on the NIF, and nitrogen from the 10B(α,n)13N reaction was measured. The 13N production yield, as well as the DT neutron yield, was, however, lower than expected. Some of the reduced yields can be explained by the oblate shape, but the ratios of the various radiochemical signals are not commensurate with expectations based on a simple reduction of the 1D results. Preliminary 2D radiation-hydrodynamics computations are consistent with the experimental measurements, and work is ongoing to extend the radiochemistry analysis into higher dimensions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

LBNL Fault Detection and Diagnostics Datasets

These datasets can be used to evaluate and benchmark the performance accuracy of Fault Detection and Diagnostics (FDD) algorithms or tools. It contains operational data from simulation, laboratory experiments, and field measurements from real buildings for seven HVAC systems/equipment (rooftop unit, single-duct air handler unit, dual-duct air handler unit, variable air volume box, fan coil unit, chiller plant, and boiler plant). Each dataset includes a .pdf file to document key information necessary to understand the content and scope, multiple csv files containing all the time-series data for faults at different severity levels and one fault-free case, and a ttl file to visualize the data according to BRICK schema. The dataset was created by LBNL, PNNL, NREL, ORNL and Drexel University.

AC↗
DOE OSTI2021

Evaluate the impact of sensor accuracy on model performance in data-driven building fault detection and diagnostics using Monte Carlo simulation

The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Sensor impact evaluation and verification for fault detection and diagnostics in building energy systems: A review

Sensors are the key information source for fault detection and diagnostics (FDD) in buildings. However, sensors are often not properly designed, installed, calibrated, located, and maintained, which negatively impacts FDD performance. Several sensor-related FDD topics have been widely studied, covering a wide range of fault types and applications. However, it is difficult to get a clear picture of the technical development of sensor-related topics in FDD. A systematic review of sensor topics is needed to summarize the existing research in a logical way, draw conclusions on the current development, and predict the future development of sensors in building FDD. To address this gap, we conducted a comprehensive literature review of more than 100 FDD-sensor-related papers. In this article, we subdivide the FDD tasks into building-level, system-level, and component-level FDD, and review sensor-related topics in each category. Our major conclusions are: (a) current data-driven FDD research focuses more on FDD algorithms than sensors, (b) sensor “hardware” research topics are less studied than sensor “software” topics, (c) very few papers focus on sensor engineering as an integral aspect of FDD development, and (d) some important sensor topics, such as sensor cost-effectiveness and sensor schema/layout/location, are not well studied. Finally, we discuss the need for a systematic framework of FDD sensors and models to integrate sensor design/selection, sensor data analysis/mining, feature selection, physics-based or data-driven algorithm development, sensor fault detection, sensor calibration, and sensor maintenance. Finally, expert interviews are conducted to validate the above findings and conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A scoping review of non-destructive testing (NDT) techniques in building performance diagnostic inspections

Understanding building envelope thermodynamics is an essential foundation of building sciences, mainly due to the envelope’s role as a boundary layer for exterior environments, as well as a container and regulator of internal microclimates. This paper presents a scoping literature review of select Non-destructive Testing (NDT) techniques for building envelope scanning and surveying for thermodynamic diagnostics. The investigation focuses specifically on reviewing six NDT techniques: Ground Penetrating Radar (GPR), Light Detection and Ranging (LiDAR)/Laser Scanning, Thermography, Ultrasound, Close-Range Photogrammetry and Through Wall Imaging Radar (TWIR). The aim is to identify knowledge gaps in terms of their use in accurately characterizing envelope compositions for further integration in Building Energy Modeling (BEM). Each technique was evaluated according to set categories imbibed from the American Society of Heating, Refrigerating, and Air Conditioning Engineering (ASHRAE) Standard 211P that showcase the technique’s ability to extract various relevant information. A framework is then developed to inform users on how to use hybrid NDT-based workflows applied in building envelope energy audits. The study concludes by discussing possibilities of utilizing NDT in large-scale audit automation, BEM integration, and developing built environment policies focusing on increasing existing building performance through retrofitting design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Implementation and test of an automated control hunting fault correction algorithm in a fault detection and diagnostics tool

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings

Data-driven building fault detection and diagnostics (FDD) is heavily dependent on sensors. However, common sensors from Building Automation Systems are not optimized to maximize accuracy in FDD. Installing additional sensors that provide more detailed building system information is key to maximizing the performance of FDD solutions. Here in this paper, we present a sensor cost analysis workflow to quantify the economic implications of installing new sensors for FDD using the concept of sensor threshold marginal cost (STMC). STMC does not represent actual sensor cost. Rather, it represents a target cost based on the economic benefit that would be realized through improved FDD performance and one or more specified economic criteria. We calculate STMCs for multiple possible fault types and use fault prevalence information to aggregate STMCs into a single dollar value to determine the cost-effectiveness of a potential sensor investment. We conducted a case study using Oak Ridge National Laboratory's Flexible Research Platform (FRP) test facility as a reference. The case study demonstrates the feasibility of the analysis and highlights the key cost considerations in sensor selection for FDD. The results also indicate that identifying and installing the few key sensor(s) is critical to cost-effectively improve FDD performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Novel design and diagnostics improvements for increased production capacity and improved reliability at the Los Alamos Isotope Production Facility

The Isotope Production Facility (IPF) at Los Alamos National Laboratory (LANL) is used to produce an array of isotopes for medical, global security, and research applications with an intense beam of protons supplied by the linear accelerator at the Los Alamos Neutron Science Center (LANSCE). An Accelerator Improvement Project (AIP) was recently conducted at IPF to improve facility reliability and reduce programmatic risk while increasing general isotope production capacity and flexibility. This was accomplished through the installation of an improved beam window assembly, more robust beam diagnostics, an active and adjustable collimator, and a new beam rastering system. This paper will highlight the four exciting innovations and how they were designed, validated, and installed in parallel as well as the significant operational advantages they provide to IPF. Key experiments and the increased currents achieved in routine production runs demonstrating the enhanced capability from the AIP will be presented. As a result, the most notable capability enhancements include irradiations with beam currents ranging from 100 nA experimental runs up to 300 μA on routine production targets and utilization of a range of cylindrical target diameters.

100 MeV protons↗
DOE OSTI2021

Synthetic proteins for COVID-19 diagnostics

There is an urgent need for inexpensive, rapid and specific antigen-based assays to test for vaccine efficacy and detect infection with SARS-CoV-2 and its variants. We have identified a small, synthetic protein (JS7), representing a region of maximum variability within the receptor binding domain (RBD), which binds antibodies in sera from nine patients with PCR-verified COVID-19 of varying severity. Antibodies binding to either JS7 or the SARS-CoV-2 recombinant RBD, as well as those that disrupt binding between a fragment of the ACE2 receptor and the RBD, are proportional to disease severity and clinical outcome. Binding to JS7 was inhibited by linear peptides from the RBD interface with ACE2. Variants of JS7, such as E484K or N501Y, can be quickly synthesized in pure form in large quantities by automated methods. JS7 and related synthetic antigens can provide a basis for specific diagnostics for SARS-CoV-2 infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Neural network reconstruction of the DIII-D tokamak plasma boundary using a reduced set of diagnostics

This study investigates the feasibility of reconstructing the last closed flux surface in the DIII-D tokamak using neural network models trained on reduced input feature sets, addressing an ill-posed task. Two models are compared: one trained solely on coil currents and another incorporating coil currents, plasma current and loop voltage. The model trained exclusively on coil currents achieved a mean point displacement of $0.04$ m on a held-out test set, while the inclusion of plasma current and loop voltage reduced the error to $0.03$ m. This comparison highlights the trade-offs between input feature complexity and reconstruction accuracy, demonstrating the potential of machine learning algorithms to perform effectively in data-limited environments, such as those expected in fusion power plants due to diagnostic constraints imposed by the presence of blankets and shielding.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Elucidating the Dynamic Nature of Fuel Cell Electrodes as a Function of Conditioning: An ex Situ Material Characterization and in Situ Electrochemical Diagnostic Study

To increase the commercialization of fuel cell electric vehicles, it is imperative to improve the activity and performance of electrocatalysts through combined efforts focused on material characterization and device-level integration. Obtaining fundamental insights into the ongoing structural and compositional changes of electrocatalysts is crucial for not only transitioning an electrode from its as-prepared to functional state, also known as 'conditioning', but also for establishing intrinsic electrochemical performances. Here, we investigated several oxygen reduction reaction (ORR) electrocatalysts via in situ and ex situ characterization techniques to provide fundamental insights into the interfacial phenomena that enable peak ORR mass activity and high current density performance. A mechanistic understanding of a fuel cell conditioning procedure is described, which encompasses voltage cycling and subsequent voltage recovery (VR) steps at low potential. In particular, ex situ membrane electrode assembly characterization using transmission electron microscopy and ultra-small angle X-ray scattering were performed to determine changes in carbon and Pt particle size and morphology, while in situ electrochemical diagnostics were performed either during or after specific points in the testing protocol to determine the electrochemical and interfacial changes occurring on the catalyst surface responsible for oxygen transport resistances through ionomer films. The results demonstrate that the voltage cycling (break-in) step aids in the removal of sulfate and fluoride and concomitantly reduces non-Fickian oxygen transport resistances, especially for catalysts where Pt is located within the pores of the carbon support. Subsequent low voltage holds at low temperature and oversaturated conditions, i.e., VR cycles, serve to improve mass activities by a factor of two to three, through a combined removal of contaminants, surface-blocking species (e.g., oxides), and rearrangement of the catalyst atomic structure (e.g., Pt-Pt and Pt-Co coordination).

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

A next generation ultra short pulse reflectometry (USPR) diagnostic

Ultrashort Pulse Reflectometry (USPR) is a plasma diagnostic technique involving the propagation and reflection of ultrashort duration (~few ns) chirps. The reflected packets pass through a multichannel filter with time-of-flight measurements performed on each of the filtered packets. A next generation USPR system is under development, spanning 28–75 GHz, for use on compact, short duration, magnetically confined fusion devices. This system presents a dramatic increase in performance compared with an earlier USPR system employed on the LLNL Sustained Spheromak Physics Experiment device more than a decade ago. The new system replaces upconverting mixers with higher power active multiplier chains to generate mm-wave transmitter chirps, with custom time-of-flight electronics reducing the time per measurement by a factor of 3X. Finally, the system is equipped with a field programmable gate array for data acquisition and analysis.

47 OTHER INSTRUMENTATION↗