Results for “Measure control” — Page 38

DOE OSTI2024

133Xe Noble Gas Mass Spectrometry Measurement for High Purity Germanium Detector Performance Verification

Idaho National Laboratory produces quality control standards for laboratories that operate xenon radionuclide monitoring systems. Activities reported with each quality control standard are quantified using high purity germanium detectors. A collection of measurement capabilities are being set up at Idaho National Laboratory to establish an in-house high purity germanium detector performance verification system, with noble gas mass spectrometry being one of these measurement capabilities. The first noble gas mass spectrometry and high purity germanium measurement comparison is presented here. A Xe-133 gas sample was prepared and the activity was quantified with high purity germanium detectors. The Xe-133 sample was diluted with a known quantity of isotopically enriched Xe-126 gas; the resulting Xe-133 : Xe-126 atom ratio was calculated to be 1.15x10-4 +/- 2% at reference time t. An aliquot of this gas sample containing approximately 10 million Xe-133 atoms was introduced into a ThermoFisher Scientific Helix MC Plus noble gas mass spectrometer for analysis. The measured Xe-133 : Xe-126 atom ratio was determined to be 1.10x10-4 +/- 2% (1-sigma uncertainty) at reference time t, about 4.3% lower than the atom ratio determined with the measured high purity germanium activity.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2021

DSP Implementation of a Novel Recurrent Neural Network Controller into a TI Solar Microinverter

Single-phase grid-tied inverters are widely used to integrate small-scale renewable energy sources and distributed generations to the utility grid. A novel Recurrent Neural Network (RNN) current controller is introduced to solve the resonant problem associated with LCL based inverters. The well-trained RNN controller was validated through a Texas Instruments (TI) LCL filter based solar microinverter kit that contains a C2000 TI microcontroller. The inverter closed current loop test without the grid connection was conducted in a laboratory setup to verify the RNN contoller functionality. The laboratory waveform results verified that the RNN current controller produced the strong tracking of the measured inverter AC current to its reference value even at a low sampling frequency of 5KHz. The proposed RNN current controller also proved to perform better than the built-in three-pole-three-zero (3P3Z) current controller provided by TI and produce lower values of Total Harmonic Distortion (THD).

digital signal processor↗

DOE OSTI2023

Measurement of Beam Energy in the Fermilab's Linac taken at the Transfer Line

Linac is the first machine in the accelerator chain at Fermilab where H$^{-}$ ions are accelerated from 35 keV to 401.5\,MeV and then injected into a synchronton known as Booster where they are stripped of their electrons to become protons. One of the tools used during tuning of the Linac extraction energy is two beam pickups known as Griffin Detectors. Our goal is to control the output energy using machine learning techniques to increase the reliability and quality of the beam delivered from Linac. The first step is to understand the data from the diagnostics to develop reliable and accurate energy measurement, and control methods before implementing machine learning techniques. Two methods of energy measurement were studied, and their results are compared. The first method was the time of flight measurement using Beam Position Monitors that provide beam phase measurement. The second method used the relation between beam transverse positions and dispersion values to calculate momentum variation. The results of these two measurement methods are found to be consistent.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Results for Gamma-Ray Spectroscopy Characterization of Residual Radioactivity on Personal Protective Clothing

In early 2019, Health Physics Services (HPS) personnel put together a test plan to use the shielded gamma-ray spectroscopy instruments in the Health Physics Services Technical Laboratory (HPSTL) to perform a series of measurements on laundered personal protective clothing used in radiological areas at the Savannah River Site (SRS). That test plan describes the methodology used to determine the quantities of laundry to be obtained from operational facilities, the methods for quality control checking the instruments throughout the measurement period, and the physical arrangement of samples in the counting shields. The test plan is documented in SRNS-J6700-2019-00037 (Reference 1).

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Direct Measurement of the Selective Microwave-Induced Heating of Agglomerates of Dipolar Molecules: The Origin of and Parameters Controlling a Microwave Specific Superheating Effect

Agglomerates of polar molecules in nonpolar solvents are selectively heated by microwave radiation. The magnitude of the selective heating was directly measured by using the temperature dependence of the intensities of the Stokes and anti-Stokes bands in the Raman spectra of p-nitroanisole (pNA) and mesitylene. Under dynamic heating conditions, a large apparent temperature difference (ΔT) of over 100 °C was observed between the polar pNA solute and the nonpolar mesitylene solvent. This represents the first direct measurement of the selective microwave heating process. The magnitude of the selective microwave heating was affected by the properties of the agglomerated pNA. As the concentration of the pNA increases, the magnitude of the selective heating of the pNA was observed to decrease. This is explained by the tendency of the pNA dipoles to orient in an antiparallel fashion in the aggregates as measured by the Kirkwood g value, which decreased with increasing concentration. This effect reduces the net dipole moment of the agglomerates, which decreases the microwave absorption. After the radiation was terminated, the effective temperature of the dipolar molecules returned slowly to that of the medium. The slow heat transfer was modeled successfully by treating the solutions as a biphasic solvent/solute system. Based on modeling and the fact that the agglomerate can be heated above the boiling temperature of the solvent, an insulating layer of solvent vapor is suggested to form around the heated agglomerate, slowing convective heat transfer out of the agglomerate. Furthermore, this is an effect unique to microwave heating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Kinetic Isotope Effects: Interpretation and Prediction Using Degrees of Rate Control

Kinetic isotope effects (KIEs) have been used for decades in catalysis research as a tool for clarifying reaction mechanisms. Significant primary kinetic isotope effects have usually been interpreted as being a result of isotope substitution at a site of bond breaking (or forming) in the rate-determining step in the reaction mechanism. However, quantitative analysis of the magnitude of the KIE in complex multistep reaction mechanisms is seldom reported. We prove here that the logarithm of the rate ratio for two isotopes is the weighted average over all species in the mechanism of their standard-state free energy difference between the two isotopes, divided by RT. The weighting factor is the degree of rate control (DRC) for that species (e.g., transition state, intermediate, reactant) when the rate is measured separately for each isotope. It is instead the degree of selectivity ratio control (DSRC) when the KIE is measured as the product selectivity in a parallel competition between two isotopes within the same reactant molecule. Since only a few species have non-zero DRCs (or DSRCs) for most reactions, only these few contribute to this weighted average and the KIE. We show that this provides a simple way to interpret and quantitatively predict kinetic isotope effects that is powerful in the insights it provides, allowing one to evaluate directly which species contribute most to the KIE. By applying it to H/D KIEs in several example mechanisms, we further show that the traditional way of interpreting KIEs that focuses only on the rate-determining step can easily lead to misunderstanding of KIE and the reaction mechanism. Finally, this highlights the importance to consider the effect of isotope substitution on the energies of all species with large DRCs (i.e, those whose energies are kinetically relevant). This method also offers opportunities for quantitative validation of mechanism-based microkinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Development of real-time density feedback control on MAST-U in L-mode

In this paper we report on the development and demonstration of density feedback control for MAST-U. Sinusoidal perturbations are used to measure the frequency response from a deuterium gas valve (actuator) to line-integrated core electron density measured by the interferometer (sensor). In the frequency range relevant for control design, only two system-identification experiments were needed to regress a first-order dynamic model. This control-oriented model informs the offline design of a proportional integral controller with the established loop-shaping controller design method. After offline verification of the controller implementation, control is demonstrated by experimentally tracking a staircase reference for the line-integrated electron density. This paper demonstrates the efficiency of controller design using system-identification and loop-shaping, providing reliable density control for MAST-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Optical O 2 Sensors Also Respond to Redox Active Molecules Commonly Secreted by Bacteria

From a metabolic perspective, molecular oxygen (O 2 ) is arguably the most significant constituent of Earth’s atmosphere. Nearly every facet of microbial physiology is sensitive to the presence and concentration of O 2 , which is the most favorable terminal electron acceptor used by organisms and also a dangerously reactive oxidant. As O 2 has such sweeping implications for physiology, researchers have developed diverse approaches to measure O 2 concentrations in natural and laboratory settings. Recent improvements to phosphorescent O 2 sensors piqued our interest due to the promise of optical measurement of spatiotemporal O 2 dynamics. However, we found that our preferred bacterial model, Pseudomonas aeruginosa PA14, secretes more than one molecule that quenches such sen sors, complicating O 2 measurements in PA14 cultures and biofilms. Assaying supernatants from cultures of 9 bacterial species demonstrated that this phenotype is common: all super natants quenched a soluble O 2 probe substantially. Phosphorescent O 2 probes are often embedded in solid support for protection, but an embedded probe called O 2 NS was quenched by most supernatants as well. Measurements using pure compounds indicated that quenching is due to interactions with redox-active small molecules, including phena zines and flavins. Uncharged and weakly polar molecules like pyocyanin were especially potent quenchers of O 2 NS. These findings underscore that optical O 2 measurements made in the presence of bacteria should be carefully controlled to ensure that O 2 , and not bacterial secretions, is measured, and motivate the design of custom O 2 probes for specific organisms to circumvent sensitivity to redox-active metabolites.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Controllable X-ray Pulse Trains from Enhanced Self-Amplified Spontaneous Emission

We report the demonstration of optical compression of an electron beam and the production of controllable trains of femtosecond, soft x-ray pulses with the Linac Coherent Light Source (LCLS) freeelectron laser (FEL). This is achieved by enhanced self-amplified spontaneous emission with a 2 μm laser and a dechirper device. Optical compression was achieved by modulating the energy of an electron beam with the laser and then compressing with a chicane, resulting in high current spikes on the beam which we observe to lase. A dechirper was then used to selectively control the lasing region of the electron beam. Field autocorrelation measurements indicate a train of pulses, and we find that the number of pulses within the train can be controlled (from 1 to 5 pulses) by varying the dechirper position and undulator taper. These results are a step toward attosecond spectroscopy with x-ray FELs as well as future FEL schemes relying on optical compression of an electron beam.

Duris, Joseph P↗

DOE OSTI2023

Measurement of Beam Energy in the Fermilab's Linac taken at the transfer Line

Linac is the first machine in the Accelerator chain at Fermilab where 𝐻− particles are accelerated from 35 keV to 400 MeV and travel to the Booster where they are stripped. of the extra electrons to become protons. The Booster requires stable beam energy at injection. The Linac extraction energy tuning has been performed using two Beam Velocity Monitors (a.k.a Griffin detectors) to maintain stable relative energy between the Booster and the Linac. Our goal is to control the Linac energy parameters using Machine Learning techniques to increase reliability and quality of beam delivered from Linac. The first step is to understand the data from the Linac extraction diagnostics; and develop reliable, accurate methods for energy measurement and control before implementing machine learning. There were two methods of energy measurement implemented, and the results of these are compared. The first method was time of flight measurements using the Phase probes inside B eam Position Monitors (BPM) that provide the beam’s phase of arrival data. The second method used the relation between beam position data from the BPMs and dispersion values from the 400MeV MAD-X model to calculate momentum variation. The results of these two energy measurement methods compare well as the Linac energy is varied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Self-Assembly of Silica Nanoparticles at Water–Hydrocarbon Interfaces: Insights from In Operando Small-Angle X-ray Scattering Measurements and Molecular Dynamics Simulations

To achieve tunable controls on the interactions of siliceous materials in subsurface environments bearing water and hydrocarbons, it is essential to determine the influence of hydrocarbon–water interfaces on the self-assembly of the silica particles. The hydrophilic silica particle have a tendency to aggregate on the water front of the interface. Self-assembly of silica nanoparticles proceeds via the migration of these nanoparticles to the water–hydrocarbon interface followed by aggregation at the interface. Fractal-like morphologies of assembled silica nanoparticles at water–hydrocarbon interfaces are observed. Rapid assembly of the hydrophilic silica nanoparticles at water–hydrocarbon interfaces corresponds to an overall reduction in the surface tension of water–toluene and water–heptane systems. These studies demonstrate the silica aggregation that is the precursor of silica polymerization, or nucleation and growth is influenced by the presence of hydrocarbons in subsurface geologic environments. These insights were derived from in operando ultrasmall and small-angle X-ray scattering (USAXS/SAXS) measurements, cryo-scanning electron microscopy (Cryo-SEM) imaging, and classical molecular dynamics simulations. As a result, these studies are intended to inform current and future efforts aimed at tuning silica reactivity in subsurface geologic environments to enhance permeability, the design and use of silica-based proppants to enhance fractures, and the development of effective strategies to control silica-based scaling behavior in subsurface reservoirs.

42 ENGINEERING↗

DOE OSTI2023

Reinforcement learning for real-time process control in high-temperature superconductor manufacturing

With high efficiency and low energy loss, high-temperature superconductors (HTS) have demonstrated their profound applications in various fields, such as medical imaging, transportation, accelerators, microwave devices, and power systems. The high-field applications of HTS tapes have raised the demand for producing cost-effective tapes with long lengths in superconductor manufacturing. However, achieving the uniform and enhanced performance of a long HTS tape is challenging due to the unstable growth conditions in the manufacturing process. Although it is confirmed that the process parameters during the advanced metal organic chemical vapor deposition (A-MOCVD) process influence the uniformity of the produced HTS tapes, the high-dimensional process parameter signals and their complicated interactions make it difficult to develop an effective control policy. In this paper, we propose a local measure for the uniformity of HTS tapes to provide instant feedback for our control policy. Then, we model the manufacturing of HTS tapes as a Markov decision process (MDP) with continuous state and action spaces to assess the instant reward in real time in our feedback control model. As our MDP involves continuous and high-dimensional state and action spaces, a neural fitted Q-iteration (NFQ) algorithm is adopted to solve the MDP with artificial neural network (ANN) function approximation. The collinearity of process parameters can restrict our capability of adjusting the process parameters, which is addressed by the principal component analysis (PCA) in our method. The control policy adjusts the PCA of process parameters using the NFQ algorithm. In conclusion, based on our case studies on real A-MOCVD dataset, the obtained control policy increases the average uniformity of tapes by 5.6% and performs especially well on sample HTS tapes with a low uniformity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

HDG-1 Graphite Preirradiation Data Package Report

This report documents all pre-irradiation examination material-property measurement data for graphite specimens that are going to be used within the first high dose graphite (HDG) -1 irradiation capsule. The two new HDG capsules signify a major change to the AGC Experiment. HDG-1 and HDG-2 will replace the last two Advanced Graphite Creep (AGC) capsules (AGC-5 and AGC-6) which were designed to irradiate graphite at the extreme upper operational temperatures for a very-high-temperature reactor (VHTR) design, 1100°C. These very high temperature AGC-5 and AGC-6 capsules have been repurposed to re-irradiated specimens (from AGC-2, AGC-3, and AGC-4) at the lower temperatures of 600°C and 800°C. HDG-1 will be irradiated at 600°C and HDG-2 will be irradiated at 800°C. By re-irradiating the previous AGC specimens a total maximum neutron dose of around 15 dpa (displacements per atom) can be achieved for all major graphite grades at irradiation temperatures of 600°C and 800°C. Specimens in the HDG-1 capsule are made up of previously irradiated specimens from the AGC-2 capsule and unirradiated specimens prepared for the now discontinued AGC-5 capsule. Utilizing the irradiated specimens, a maximum neutron dose of around 15 dpa is anticipated. These new maximum dose levels will provide irradiated material property data over a total neutron dose range of 1-15 dpa at a temperature of 600°C when combined with the previous AGC-1 and AGC-2 irradiation data. This will provide quantitative data necessary for predicting the irradiation behavior and operating performance of new nuclear graphite grades for use within high temperature reactor designs. Similar to previous AGC test trains, HDG-1 includes the major graphite grades (IG-110, NBG-17, NBG-18, PCEA, and 2114) as well as adding the very fine-grain grade IG-430 which is of interest to the Molten Salt Reactor (MSR) designs. Also new to the HDG-1 capsule are 90 smaller geometry specimens designated as pencil specimens. These specimens take up only one third the space of a standard creep size specimen. This increased number of specimens will enhance property measurement statistics because they will provide 3 times the control specimen data at a position that would otherwise only have a single measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

HDG-1 Graphite Preirradiation Data Package Report

This report documents all pre-irradiation examination material-property measurement data for graphite specimens that are going to be used within the first high dose graphite (HDG) -1 irradiation capsule. The two new HDG capsules signify a major change to the AGC Experiment. HDG-1 and HDG-2 will replace the last two Advanced Graphite Creep (AGC) capsules (AGC-5 and AGC-6) which were designed to irradiate graphite at the extreme upper operational temperatures for a very-high-temperature reactor (VHTR) design, 1100°C. These very high temperature AGC-5 and AGC-6 capsules have been repurposed to re-irradiated specimens (from AGC-2, AGC-3, and AGC-4) at the lower temperatures of 600°C and 800°C. HDG-1 will be irradiated at 600°C and HDG-2 will be irradiated at 800°C. By re-irradiating the previous AGC specimens a total maximum neutron dose of around 15 dpa (displacements per atom) can be achieved for all major graphite grades at irradiation temperatures of 600°C and 800°C. Specimens in the HDG-1 capsule are made up of previously irradiated specimens from the AGC-2 capsule and unirradiated specimens prepared for the now discontinued AGC-5 capsule. Utilizing the irradiated specimens, a maximum neutron dose of around 15 dpa is anticipated. These new maximum dose levels will provide irradiated material property data over a total neutron dose range of 1-15 dpa at a temperature of 600°C when combined with the previous AGC-1 and AGC-2 irradiation data. This will provide quantitative data necessary for predicting the irradiation behavior and operating performance of new nuclear graphite grades for use within high temperature reactor designs. Similar to previous AGC test trains, HDG-1 includes the major graphite grades (IG-110, NBG-17, NBG-18, PCEA, and 2114) as well as adding the very fine-grain grade IG-430 which is of interest to the Molten Salt Reactor (MSR) designs. Also new to the HDG-1 capsule are 90 smaller geometry specimens designated as pencil specimens. These specimens take up only one third the space of a standard creep size specimen. This increased number of specimens will enhance property measurement statistics because they will provide 3 times the control specimen data at a position that would otherwise only have a single measurement.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

DAISY Complement Protein ML-Ready Data

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was not consistent for all children. There were 47 of the children who had samples taken and evaluated prior to IA (Pre-IA), and 131 children had measurements at or after IA, but prior to diagnosis of clinical T1D (Post-IA). The control children were frequency matched on HLA genotypes and age and sex with an observed lower frequency of first degree relatives within the control group versus the cases For machine learning the children that will develop islet autoantibodies the 40 control and 47 Pre-IA children were down-selected to a single sample time point. For the 40 control children this was the earliest sample collected and for the 47 Pre-IA children it was a random selection of the first or second time point prior to the detection of autoantibodies to assure the age distributions were not significantly different.

machine learning, proteomics, Type 1 Diabetes, com↗

DOE OSTI2023

DAISY Complement Protein ML-Ready Data

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was not consistent for all children. There were 47 of the children who had samples taken and evaluated prior to IA (Pre-IA), and 131 children had measurements at or after IA, but prior to diagnosis of clinical T1D (Post-IA). The control children were frequency matched on HLA genotypes and age and sex with an observed lower frequency of first degree relatives within the control group versus the cases For machine learning the children that will develop islet autoantibodies the 40 control and 47 Pre-IA children were down-selected to a single sample time point. For the 40 control children this was the earliest sample collected and for the 47 Pre-IA children it was a random selection of the first or second time point prior to the detection of autoantibodies to assure the age distributions were not significantly different.

Webb-Robertson, Bobbie-Jo M↗

DOE OSTI2024

Distributed strain sensing using Bi-metallic coated fiber optic sensors embedded in stainless steel

Silica fiber optic sensors are resistant to corrosive environments and high temperatures, making them attractive candidates for harsh conditions found in nuclear and aerospace industries. Moreover, fibers can be deployed remotely for continuous measuring of spatially distributed temperatures and strains. Here, this study investigated embedding a Ni/Cu bi-metallic coated fiber in a stainless-steel 316 (SS316) matrix using laser powder bed fusion towards functionalizing metal components for site-specific health monitoring. The embedded fiber was continuously interrogated during controlled heating to 1000°C. The measured fiber strains were similar to the expected differential thermal strains between the fiber and the SS316 matrix, until divergent behavior was observed at temperatures >500°C. No debonding at the matrix–coating–fiber interfaces was observed during microscopy, but significant interactions between the coatings and matrix resulted in diffusion-driven chemistry variations and Kirkendall void formation. Applying the strain-lag theory revealed plastic behavior in the Ni coating at temperatures >500°C, limiting the strain transfer to the fiber at higher temperatures. It was estimated that the elastic modulus in the Ni coating had decreased from ~200 GPa at room temperature to below 40 GPa, starting at 600°C. The low elastic modulus above 600°C is within the margin of what the tangent modulus would be in the case of bilinear isotropic hardening. Regardless of the divergent strain transfer at higher temperatures, the fiber was exposed to the equivalent of 1.9 % engineering strain at 1000°C, but measured only a 0.7 % engineering strain due to the poor strain transfer. Although compensating for the plastic behavior of Ni proved challenging, the bonding of a brittle silica fiber to a metal matrix surviving to 1000°C invites potential iterations on coating material for future application. For example, the embedded fiber is sufficient for acoustic energy transfer, realizing high temperature distributed acoustic sensing.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Scalable Parallel Measurement of Individual Nitrogen-Vacancy Centers

The nitrogen-vacancy (NV) center in diamond is a solid-state spin defect that has been widely adopted for quantum sensing and quantum information processing applications. Typically, experiments are performed either with a single isolated NV center or with an unresolved ensemble of many NV centers, resulting in a trade-off between measurement speed and spatial resolution or control over individual defects. In this work, we introduce an experimental platform that bypasses this trade-off by addressing multiple optically resolved NV centers in parallel. We perform charge- and spin-state manipulations selectively on multiple NV centers from within a larger set, and we manipulate and measure the electronic spin states of over 100 NV centers in parallel. We show that the high signal-to-noise ratio of the measurements enables the detection of shot-to-shot pairwise correlations between the spin states of 108 NV centers, corresponding to the simultaneous measurement of 5778 unique correlation coefficients. We discuss how our platform can be scaled to parallel experiments with thousands of individually resolved NV centers. These results enable parallelized high-throughput sensing experiments that retain the spatial resolution of single defects and will, thereby, help to unlock advances in applications such as single-molecule NMR and characterization of integrated circuits. In addition, our approach to multiplexing provides a natural platform for the application of recently developed correlated sensing techniques.

NV centers↗