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Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS
Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.
Connecting dark matter annihilation to the vertex functions of Standard Model fermions
We consider here scenarios in which dark matter is a Majorana fermion which couples to Standard Model fermions through the exchange of charged mediating particles. The matrix elements for various dark matter annihilation processes are then related to one-loop corrections to the fermion-photon vertex, where dark matter and the charged mediators run in the loop. In particular, in the limit where Standard Model fermion helicity mixing is suppressed, the cross section for dark matter annihilation to various final states is related to corrections to the Standard Model fermion charge form factor. These corrections can be extracted in a gauge-invariant manner from collider cross sections. While current measurements from colliders are not precise enough to provide useful constraints on dark matter annihilation, improved measurements at future experiments, such as the International Linear Collider, could improve these constraints by several orders of magnitude, allowing them to surpass the limits obtainable by direct observation
Measurement of a radial flow profile with eddy current flow meters and deep neural networks
Eddy current flow meters (ECFMs) measure flows of conductive fluids. Recent interest in ECFMs has increased due to applications in advanced nuclear reactors. ECFMs are well suited for such applications, as they can provide non-invasive measurements of flow in fluids that are often difficult to measure. Traditionally, ECFMs are operated using an alternating current at a single frequency, limiting ECFMs to measure average fluid velocities, blockages, or voids. Here, we expand the capabilities of ECFMs by measuring the fluid radial velocity profile of liquid mercury. To accomplish this, we made several ECFM sensitivity measurements at a range of frequencies. Different frequencies vary the electromagnetic skin depth of the device. By adjusting frequencies, we probed the fluid velocity at various radial locations and constructed a flow-velocity profile. The relationship between the ECFM measurements and velocity profile is nonlinear and requires solving an inverse problem. Using electromagnetic finite-element simulations to train a deep neural network (DNN), we created a model that provides a stable general relationship between the sensitivity measurements of an ECFM and the fluid velocity profile. Using ECFM measurements of liquid mercury, our DNN model calculates a flow profile that agrees well with computational fluid dynamics (CFD) simulations. This technique has potential to improve flow monitoring for optimization, safe operation of conductive fluid loops, and/or validating complex CFD models.
PELICAN Status Report for Year 2021
The Pressure Drop Experimental Loop for Investigations of Core Assemblies in Advanced Nuclear Reactors, PELICAN, is a novel experimental facility designed and constructed to recreate the prototypic full scale hydraulic flow conditions for the Versatile Test Reactor (VTR) currently under development by the U.S. Department of Energy. To support VTR design efforts, PELICAN is used to replicate VTR’s primary heat transport system (PHTS) in the core assembly region. The measurement objectives for data generated from this test facility are to mimic the prototypic VTR assembly and to meet the validation needs for code calculations and simulations of the reference design for the VTR core. These objectives focus on the need to validate pressure drop results across the various segments of the fuel assembly, including the axial reflectors, fuel, and transition regions, as they relate directly to the pumping power and safety behavior of the reactor. In the following sections, the major milestones for the experimental work performed on PELICAN over the calendar year (CY) 2021 are presented. In the next section, we discuss the assembly and shakedown testing of the facility. In Section 3, an analysis of the errors in the major measurements is performed. In Section 4 and 5 we present the results from the first set of test articles placed inside the loop. The design of the remaining test articles as part of the full assembly are shown in Section 6 and the conclusion and path forward for the following year, CY22 is given in the final section.
A critical review of irradiation-induced changes in reactor pressure vessel steels
A large body of work has been conducted to investigate the embrittlement and degradation of reactor pressure vessel (RPV) steels. This includes experiments on alloys with different compositions, performed in research and test reactors and ion accelerators that span various temperatures, fluxes, and fluences. In this paper, we perform a critical review of the published experimental data and compile experimentally reported values for dislocation loop size/density, precipitate size/density and yield stress into an easily downloadable format that can be used by both experimentalists and modelers. This thorough experimental review is complemented by a brief review of simulation efforts at atomistic and mesoscopic length scales. Finally, this paper highlights key aspects of the behavior of RPV steels under irradiation, identifies gaps or discrepancies in current understanding, and identifies priority future research directions.
An Alfvenic reconnecting plasmoid thruster
A new concept for the generation of thrust for space propulsion is introduced. Energetic thrust is generated in the form of plasmoids (confined plasma in closed magnetic loops) when magnetic helicity (linked magnetic field lines) is injected into an annular channel. Using a novel configuration of static electric and magnetic fields, the concept utilizes a current-sheet instability to spontaneously and continuously create plasmoids via magnetic reconnection. Here, the generated low-temperature plasma is simulated in a global annular geometry using the extended magnetohydrodynamic model. Because the system-size plasmoid is an Alfvenic outflow from the reconnection site, its thrust is proportional to the square of the magnetic field strength and does not ideally depend on the mass of the ion species of the plasma. Exhaust velocities in the range of 20 to $500\ \textrm {km}\ \textrm {s}^{-1}$ , controllable by the coil currents, are observed in the simulations.
Regions of hepatitis C virus E2 required for membrane association
Hepatitis C virus (HCV) uses a hybrid entry mechanism. Current structural data suggest that upon exposure to low pH and Cluster of Differentiation 81 (CD81), the amino terminus of envelope glycoprotein E2 becomes ordered and releases an internal loop with two invariant aromatic residues into the host membrane. Here, we present the structure of an amino-terminally truncated E2 with the membrane binding loop in a bent conformation and the aromatic side chains sequestered. Comparison with three previously reported E2 structures with the same Fab indicates that this internal loop is flexible, and that local context influences the exposure of hydrophobic residues. Biochemical assays show that the amino-terminally truncated E2 lacks the baseline membrane-binding capacity of the E2 ectodomain. Thus, the amino terminal region is a critical determinant for both CD81 and membrane interaction. These results provide new insights into the HCV entry mechanism.
STREAM2016: Streaming Requirements, Experience, Applications and Middleware Workshop
The Department of Energy (DOE) Office of Science (SC) facilities including accelerators, light sources and neutron sources and sensors that study, the environment, and the atmosphere, are producing streaming data that needs to be analyzed for next-generation scientific discoveries. There has been an explosion of new research and technologies for stream analytics arising from the academic and private sectors. However, there has been no corresponding effort in either documenting the critical research opportunities or building a community that can create and foster productive collaborations. The two-part workshop series, STREAM: Streaming Requirements, Experience, Applications and Middleware Workshop (STREAM2015 and STREAM2016), were conducted to bring the community together and identify gaps and future efforts needed by both NSF and DOE. This report describes the discussions, outcomes and conclusions from STREAM2016: Streaming Requirements, Experience, Applications and Middleware Workshop, the second of these workshops held on March 22-23, 2016 in Tysons, VA. STREAM2016 focused on the Department of Energy (DOE) applications, computational and experimental facilities, as well software systems. Thus, the role of “streaming and steering” as a critical mode of connecting the experimental and computing facilities was pervasive through the workshop. Given the overlap in interests and challenges with industry, the workshop had significant presence from several innovative companies and major contributors. The requirements that drive the proposed research directions, identified in this report, show an important opportunity for building competitive research and development program around streaming data. These findings and recommendations are consistent with vision outlined in NRC Frontiers of Data and National Strategic Computing Initiative (NCSI) [1, 2]. The discussions from the workshop are captured as topic areas covered in this report's sections. The report discusses four research directions driven by current and future application requirements reflecting the areas identified as important by STREAM2016. These include (i) Algorithms, (ii) Programming Models, Languages and Runtime Systems (iii) Human-in-the-loop and Steering in Scientific Workflow and (iv) Facilities.
Tritium Transport Phenomena in Molten-Salt Reactors: Molten Salt Tritium Transport Experiment Design
Tritium is produced from neutron interactions with both lithium and beryllium. Large quantities of tritium are generated in Molten Salt Reactors (MSRs) which use LiF/BeF2 (FLiBe) as the fuel salt. Tritium is unique among the radionuclide hazards as it readily permeates through metal structural materials at high temperatures. All metal surfaces are potential release paths for tritium. For adequate safety analysis and eventual licensing of new reactors, predictive models for tritium transport and release from MSRs must be developed. These models must account for the multiple transport phenomena involved with tritium: fuel salt phase mass transport, dissociation/recombination reactions on metal surfaces, interstitial diffusion through the metal structure, and salt or gas phase mass transport in the downstream fluid. These models also must also be validated with representative experiments. Our previous report outlined tritium transport phenomena involved in MSRs, made suggestions on gaps in the transport dataset, and proposed an experimental test stand to test combined transport effects – tritium transport through pipe walls in a convective salt flow. In this report, we summarize an updated analysis framework for tritium transport in MSRs, report our results on hydrogen and deuterium permeation through Hastelloy N, and describe the final design of the Molten Salt Tritium Transport Experiment (MSTTE, pronounced “misty”). The MSRE provides the only wholistic experimental data set for tritium transport in MSRs and understanding the transport phenomena involved in the MSRE is crucial for future model development. One set of parameters in our analysis framework was unknown for the MSRE—surface reaction rates for tritium on Hastelloy N. This warranted our hydrogen and deuterium permeation campaign to assess the permeability, diffusivity, and solubility of hydrogen isotopes in clean Hastelloy N. Surface reaction rate constants were probed by low pressure measurements, however, no surface effects were observed in the limits of our permeation apparatus. Permeation experiments on oxidized Hastelloy N were not performed for this report but are planned in future work. The experimental test stand, MSTTE, measures combined transport properties of the salt-metal system. MSTTE is a forced convection FLiBe loop with custom designed test section to measure tritium transport through candidate structural materials. We use MSRE relevant dimensionless numbers to design and scale the test section. Hastelloy N is a candidate loop and test section material due to the relevance for the MSRE and related designs, however, other metals are being considered (e.g. 316H SS) which may better align with current vendor concepts.
Chiral matrix model of the semi-QGP in QCD
Previously, a matrix model of the region near the transition temperature, in the “semi”quark gluon plasma, was developed for the theory of SU(3) gluons without quarks. In this paper we develop a chiral matrix model applicable to QCD by including dynamical quarks with 2+1 flavors. This requires adding a nonet of scalar fields, with both parities, and coupling these to quarks through a Yukawa coupling, y. Treating the scalar fields in mean field approximation, the effective Lagrangian is computed by integrating out quarks to one loop order. As is standard, the potential for the scalar fields is chosen to be symmetric under the flavor symmetry of SU (3) L × SU(3) R × Z (3) A , except for a term linear in the current quark mass, m qk . In addition, at a nonzero temperature T it is necessary to add a new term, ~ m qk T 2 . The parameters of the gluon part of the matrix model are identical to those for the pure glue theory without quarks. The parameters in the chiral matrix model are fixed by the values, at zero temperature, of the pion decay constant and the masses of the pions, kaons, η , and η' . The temperature for the chiral crossover at T$χ$ = 155 MeV is determined by adjusting the Yukawa coupling y . We find reasonable agreement with the results of numerical simulations on the lattice for the pressure and related quantities. In the chiral limit, besides the divergence in the chiral susceptibility there is also a milder divergence in the susceptibility between the Polyakov loop and the chiral order parameter, with critical exponent β $-$ 1 . We compute derivatives with respect to a quark chemical potential to determine the susceptibilities for baryon number, the $χ$ 2n . Especially sensitive tests are provided by $χ$ 4 $-$ $χ$ 2 and by $χ$ 6 , which changes in sign about T$χ$ . In conclusion, the behavior of the susceptibilities in the chiral matrix model strongly suggests that as the temperature increases from T$χ$ , that the transition to deconfinement is significantly quicker than indicated by the measurements of the (renormalized) Polyakov loop on the lattice.
Power-Hardware-in-the-Loop Interfaces for Inverter-Based Microgrid Experiments Including Transitions
Microgrids continue to proliferate, particularly those that rely on inverter-based resources as the microgrid's voltage and frequency leader. Hardware-in-the-loop simulations can de-risk microgrid deployments, and therefore we need power-hardware-in-the-loop (PHIL) interfaces for grid-forming (GFM) inverters to enable simulations of seamless transitions between islanded and grid-connected operation. Such interfaces are particularly challenging when the inverters need to switch modes, i.e., between grid-following (GFL) and GFM as the microgrid transitions between grid-connected and islanded operation. This paper presents two PHIL interfaces for such microgrids and the preliminary experimental results.
Stability of superconducting strings
We investigate the stability of superconducting strings as bound states of strings and fermion zero modes at both the classical and quantum levels. The dynamics of these superconducting strings can result in a stable configuration, known as a vorton . We mainly focus on global strings, but the majority of the discussion can be applied to local strings. Using lattice simulations, we study the classical dynamics of superconducting strings and confirm that they relax to the vorton configuration through Nambu-Goldstone boson radiation, with no evidence of over-shooting that would destabilize the vorton. We explore the tunneling of fermion zero modes out of the strings. Both our classical analysis and quantum calculations yield consistent results: the maximum energy of the zero mode significantly exceeds the fermion mass, in contrast to previous literature. Additionally, we introduce a world-sheet formalism to evaluate the decay rate of zero modes into other particles, which constitute the dominant decay channel. We also identify additional processes that trigger zero-mode decay due to non-adiabatic changes of the string configuration. In these decay processes, the rates are suppressed by the curvature of string loops, with exponential suppression for large masses of the final states. We further study the scattering with light charged particles surrounding the string core produced by the zero-mode current and find that a wide zero-mode wavefunction can enhance vorton stability.
Demonstration of reconstruction-free static magnetic control of DIII-D plasma with deep reinforcement learning
This paper presents the development and experimental validation of a reinforcement learning (RL)-based magnetic controller on the DIII-D tokamak. The controller directly maps raw magnetic diagnostic signals to actuator commands, replacing the traditional isoflux control algorithm based on equilibrium reconstruction. Four RL controllers are trained using the Soft Actor–Critic algorithm with an asymmetric Actor–Critic architecture in the NSFsim simulator. All controllers are deployed in the DIII-D Plasma Control System and operated with a 4 kHz feedback loop. Two randomization strategies are evaluated during training: evolving kinetic profiles and fixed kinetic profiles within each episode. The latter approach is found to better capture experimental deviations in the current density profile and to provide overall improved control performance. Robust operation is demonstrated across heating power scans in both L- and H-mode plasmas, as well as during transient events such as L–H transitions and pellet injections. Control errors in plasma shape and radial position remained within 1.5–2.0 cm and 1 cm, respectively. A notable discrepancy was observed in the vertical X-point position, with errors of up to approximately 4 cm, attributed to the current density distribution mismatches between simulations and experiments.
Persistent-current magnetizations of Nb 3 Sn Rutherford cables and extracted strands
The magnetizations of eight high-gradient quadrupole cables designated HQ and QXF and a pair of strands, identical in architecture but with different effective strand diameters extracted from an HQ and a related QXF cable, were measured. In the service of field quality assessment, the cable magnetizations and losses were measured by pickup coil magnetometry at 4.2 K in face-on fields, B m , of ± 400 mT at frequencies, f, of up to 60 mHz. Based on the coupling component of loss, Q coup , the coupling magnetization M coup = Q coup /4B m was derived for a ramp rate of 7.5 mT/s. Persistent current (shielding) magnetization and loss (M sh and Q h,strand ) were measured on short pieces of extracted strand by vibrating sample magnetometry at 4.2 K. Unpenetrated M-B loops to ±400 mT and fully penetrated loops to ±14 T were obtained. M coup can be easily controlled and reduced to relatively small values by introducing cores and adjusting the preparation conditions. But in low fields near injection Nb 3 Sn's high J c and correspondingly high M sh,cable may call for magnetic compensation to preserve field quality. The suitably adjusted cable and strand fully penetrated M-B loops were in reasonable accord leading to the conclusion that strand magnetization is a useful measure of cable magnetization, and that when suitably manipulated can provide input to magnet field error calculations.
Inference-Engine v0.1.0
Given a pre-trained neural network, Inference-Engine performs maps network inputs to outputs by executing the forward pass through the provided network. Although the predominant programming language for machine-learning is Python, most high-performance computing (HPC) applications are written in Fortran, C, or C++. Inference-Engine aims to support HPC programs and is written in Fortran, a language with a large feature set supporting interoperability with C. This software exposes concurrency in a portable way by using standard language features that some modern Fortran compilers can exploit with various optimizations, including offloading computation to a Graphics Processing Unit (GPU). In particular, this software makes extensive use of Fortran's "do concurrent" parallel loop construct, implicitly parallel array statements, and pure procedures that can be invoked inside "do concurrent" blocks. Inference-Engine also supports dynamic choice of inference methods at runtime. Two current options include one method that uses Fortran's "dot_product" intrinsic function inside "do concurrent" blocks and another method that instead uses Fortran' "matmul" array intrinsic function. We plan to investigate automatic compiler offloading of "do concurrent" calculations to GPUs and compile-time substitution of optimized libraries such as the Basic Linear Algebra Library (BLAS) for "matmul" invocations. We also envision the potential for the choice of which method to use could happen at program launch based on in situ performance measurements on any given platform.
A search for the decay of a B meson into a kaon and a tau lepton pair at the BaBar experiment
The flavour changing neutral current (FCNC) process, $B^+$ → $K^+ τ^+ τ^-$ highly suppressed in the Standard Model (SM). This decay is forbidden at tree level and only occurs at lowest order via one-loop diagrams.$B^+$ → $K^+ τ^+ τ^-$ thus has the potential to provide a stringent test of the SM and a fertile ground for new physics searches. Contributions due to virtual particles in the loop allow one to probe, at relatively low energies, new physics at large mass scales. We search for the rare FCNC process $B^+$ → $K^+ τ^+ τ^-$ using data collected by the BaBaR detector at the SLAC National Accelerator Laboratory. The BaBaR data sample corresponds to a total integrated luminosity, at the energy of the Τ(4S) resonance, of 424.4 $fb^-1$ and 471 million $B\bar{B}$ pairs. For this search, hadronic $B_{tag}$ reconstruction is employed, where one B is exclusively reconstructed via one of many possible hadronic modes. The remaining decay products in an event are then attributed to the signal B, on which the search for $B^+$ → $K^+ τ^+ τ^-$ is performed. Each τ is required to decay leptonically, into either an electron or a muon and the lepton neutrinos. Furthermore, a multi-variate analysis technique (neural network) is used to select for signal events and suppress dominant background modes. No significant signal is observed. The resulting branching fraction is measured to be $\beta(B^+$ → $K^+ τ^+)$ = $1.31^{0:66}_{-0:61}$(stat.) $^{+0:35}_{-0:25}$(sys.) x 10$^{-3}$, which is consistent with zero at the 1.9σ level, with an upper limit of 2.25 x 10$^{-3}$, at the 90% confidence level.
10 MWE CDCL Large Pilot Plant – pre-FEED Study
Coal Direct Chemical Looping (CDCL) is an advanced oxy-combustion technology that has the potential to substantially reduce the energy penalty and the cost of electricity (COE) for coal-fired power generation with CO₂ capture. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been collaborating on the development of an iron oxide oxygen-carrier based chemical looping technology for clean power generation with inherent carbon capture. In this process, coal is dried and pulverized prior to being transported into a moving-bed reducer. In the reducer, coal reacts with the oxygen-carrier particles, forming combustion byproducts, predominantly CO₂ and H₂O, while reducing the iron oxide oxidation state from Fe₂O₃ to a mixture of FeO and Fe. The reduced state particles are then transported to a combustor reactor and re-oxidized with air. Following the oxidation, the oxygen-carrier particles are regenerated, and a large amount of heat is released for steam production. The produced steam is sent to a turbine for electricity generation. Meanwhile, the CO₂–rich stream leaving the reducer is cooled, cleaned, and compressed for subsequent pipeline transportation and sequestration. By combining air separation and fuel conversion into a single system, the CDCL technology enables the intensification of oxy-combustion processes by eliminating the energy and cost intensive cryogenic air separation unit and thereby results in higher overall plant efficiencies and lower COE’s. The use of a moving-bed reducer results in high conversions of volatile hydrocarbons and high CO₂ purity, which reduces the cost of downstream CO₂ purification for sequestration or utilization. The Babcock & Wilcox Company in collaboration with The Ohio State University, Johnson & Matthey, The Electric Power Research Institute, and Dover Light & Power completed a Preliminary Front-End Engineering and Design (Pre-FEED) study of a 10 MWe coal-direct chemical looping (CDCL) pilot plant. The planned system is a modular 10 MWe CDCL large pilot facility consisting in 4 modules of 2.5 MWe each, working in parallel and to be hosted within the current structure at the City of Dover’s Municipal Power Plant. The CDCL system can achieve auto-thermal operation and includes a sub-critical steam cycle for power generation. The pilot system was designed to demonstrate full commercial operation at a reduced scale. The coal distribution per plan area is a representative slice of larger commercial arrangements. The system includes a CO₂ recycle system, but it does not include a compression system. The large pilot includes all the environmental control equipment and oxygen carrier and ash handling systems. As part of the project, the Team performed laboratory testing and carried out multiple pilot test campaigns to obtain design and performance information at the 250 kWth CDCL pilot facility at the Babcock & Wilcox Company’s Research Center. The Team demonstrated sustained operations at designed coal inputs, high coal conversion, high CO₂ purity, heat generation on the combustor, low carbon carryover between reactors and low particle attrition. Emissions generated in the reducer reactor were identified as SO₂ and NO x . The commercial manufacturing cost of oxygen carrier particle was evaluated by JM. A particle manufacturing report was generated and submitted to the DOE. Based on the results from the pilot tests and the pre-FEED design efforts, a techno-economic analysis was performed. The study shows that the CDCL process is a promising carbon-friendly technology capable of producing electricity with high efficiency. The estimated COE of the supercritical CDCL plant is $83.3 / MWh, which meets DOE’s target of less than 30% increase in COE when compared to a supercritical PC plant without CO₂ capture. This is the lowest among the existing carbon capture technologies (post-combustion and oxy-combustion) for fossil fuel power plant. CDCL is evaluated to be the most promising technology for carbon capture from the economic aspect.