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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Novel Control Strategy for Multiple Run-of-the-River Hydro Power Plants to Provide Grid Ancillary Services

Hydropower plant (HPP) generation comprises a considerable portion of bulk electricity generation and is delivered with a low-carbon footprint. In fact, HPP electricity generation provides the largest share from renewable energy resources, which include wind and solar. Increasing penetration levels of wind and solar lead to a lower inertia on the electric grid, which poses stability challenges. In recent years, breakthroughs in energy storage technologies have demonstrated the economic and technical feasibility of extensive deployments of renewable energy resources on electric grids. If integrated with scalable, multi-time-step energy storage so that the total output can be controlled, multiple run-of-the-river (ROR) HPPs can be deployed. Although the size of a single energy storage system is much smaller than that of a typical reservoir, the ratings of storages and multiple ROR HPPs approximately equal the rating of a large, conventional HPP. This paper proposes cohesively managing multiple sets of energy storage systems distributed in different locations. This paper also describes the challenges associated with ROR HPP system architecture and operation.

13 HYDRO ENERGY↗
DOE OSTI2019

Robust Network Interdiction Considering Multiple Defense Resources

We extend the network interdiction problem in order to consider multiple options for defending arcs in a network. We apply our model to select an optimal set of countermeasures for nuclear material smuggling. In order account for the joint impact of multiple countermeasures, we consider multiple components of defense: situational awareness, detection, and interdiction. We develop a bi-level programming model, where the adversary's goal is to maximize damage to the system while the defender seeks to minimize damage by selecting countermeasure options under a restricted bud- get. Furthermore, since effectiveness of countermeasures is often difficult to assess with high accuracy, we use robust optimization to allow for parametric uncertainty. We test our method on a synthetic example of the U.S. supply chain network that includes rail, air, and maritime transportation between both domestic and international locations. For this test example, we find that increasing the budget for countermeasures has the greatest impact within the first 1-2% of the cost to implement all countermeasures and that the uncertainty tolerance has a greater impact on expected damage than the countermeasure budget does. Thus, when strategically selecting countermeasures it is important to precisely understand the effectiveness of each option and the adversary's probability of subverting them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Total Measurement Uncertainty in Neutron Coincidence Multiplicity Analysis

Neutron multiplicity analysis is a widely used technique in international safeguards and is most commonly applied to the assay of product and scrap materials in the production of mixed oxide fuel. The typical neutron multiplicity analysis applies only a crude, almost cursory, uncertainty analysis limited to propagation of statistical errors in the derived singles, doubles, and triples count rates through the point source model. While these analyses do not account for uncertainties in basic detector parameters (e.g., efficiency or gate utilization factors), nuclear data, or covariances between any of these values, measurement uncertainties are often quoted in the range of 1–2% of the resulting mass values. In this work, we examined the impact of the nuclear data and instrumentation uncertainties on the multiplicity assay result for various counting regimes using the point-model equations as the basis for discussion. Potential biases introduced by the current nuclear data set on the measurement and the need for a more complete error treatment when we progress beyond empirical calibrations based on highly representative items will be discussed.

Mcelroy Jr, Robert↗
DOE OSTI2019

Method of increasing expression of nucleic acid molecules in plants using multiple transcription units

A method of increasing expression of a product encoded by a nucleic acid molecule is provided where in one embodiment multiple plant transcription units comprising a promoter and the nucleic acid molecule are provided. In another embodiment multiple plant transcription units are provided where each promoter is different from the other. In an embodiment the multiple plant transcription units may comprise two, three, four or more plant transcription units. In another embodiment the promoter may be selected from an embryo promoter. Another embodiment provides the promoter may be a globulin promoter. A further embodiment provides the product encoded may be selected from hepatitis b, aprotinin, or a cellulase. Still further embodiments provide the product may be selected from the cellulases E1 and CBH1.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Results of Multiple Tracer Injections into Fractures in the EGS Collab Testbed-1

The EGS Collab project constructed an intermediate scale (~10-20 m) testbed at the 4850 level of the Stanford Underground Research Facility (SURF) in South Dakota for testing and validating fracture stimulation and flow/transport models. This testbed consists of eight ~200 ft (~60 m) HQ-diameter (9.6 cm) boreholes that are drilled into the crystalline rocks of the Poorman Formation from the West Access Drift tunnel. Of the eight boreholes, one borehole is used as an injection/stimulation well, while another sub-parallel borehole located about 10 m away from the injection well is used as a production well, and rest of the other boreholes are used as geophysical/fluid sampling monitoring wells. Hydraulic stimulation activities were conducted at three locations along the injection hole in an attempt to create direct fracture connections to the production hole. A flow system has been established between injection and production boreholes through a set of hydraulically stimulated fractures propagated from a notch located at 164 ft in the injection hole. Although we planned for a single production well, a set of natural fractures in the testbed is believed to have intersected the stimulated hydraulic fractures and provided additional flow paths for water to be transported to the drift through multiple monitoring boreholes and weep zones. As the flow tests continued after stimulation activities, single or a combination of two or three producers become dominant producers at different times, mostly as a response to intersection of hydraulic fracture and testbed wells, activation of natural fractures and making new leak points to the monitoring wells, resealing of leaky wells, and so on. Since late October 2018, multiple tracers were injected into the fracture system at the 164 ft location that involves both stimulated and natural fractures, and tracers were recovered from multiple locations in nearby wells and weep. The cumulative water recoveries over the time have ranged from 50 to 90%; however, the injected tracer recoveries from various production sources are much less (ranging from a few percentages to 38%). Changes in water/tracer recoveries, shifting of major producing wells from one well to the others, and other observations (e.g., microseismic, electric resistivity tomography, etc.) indicate a testbed that has undergone several changes since October 2018. In this paper, we present tracer recovery data accumulated during several tracer campaigns, provide conceptual testbed flow pathways, and provide observations that suggest a evolutionary nature of fracture volume and fracture geometry in the testbed.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Analysis of MINERvA tunings of GENIE based on Hadron Multiplicity using Machine Learning

Scientists with the MINERvA neutrino interaction experiment have long studied distributions of hadrons (protons and pions) to improve the models for these reactions. Until now, most work has relied on easy to find, energetic, and well tracked hadrons. But in order to take full advantage of MINERνA data it is necessary to develop an efficient enough tool to recognize hadron tracks with lower energy, more transverse angle and more challenging patterns of activity. In this analysis, a Machine Learning tool based on Convolutional Neural Network and Transfer Learning has been developed to tackle that issue. It is found to be extremely capable of recognizing hadron activities especially when there are few and not very energetic hadrons, the accuracy is 76%. But it is also found that this network is very reluctant to classify too many hadrons. The classification is also affected by the presence of other particles in the event such photons, hadrons below a threshold or neutrons. This network is used to compare hadron multiplicity of data to the MC models and distinguish between different MC tunes. Some MINERνA tunes are explored in this analysis, but none of them described the data very well, especially not for all different hadrons multiplicities at once. Four combinations of those tunes were more successful, but none of them could be recognized as the best one. Nevertheless, this analysis develops an ML network that sets the basis of further exploration of hadron multiplicity as a tool to analyze MC tunes at MINERνA and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Vectoring into Potential Blind Geothermal Systems in the Granite Springs Valley Area, Western Nevada: Application of the Play Fairway Analysis at Multiple Scales

The Great Basin region of the western USA is capable of generating much greater amounts of geothermal energy than currently produced. Most geothermal resources in this region are blind, and thus the favorable characteristics for geothermal activity must be synthesized and methodologies developed to discover new commercial-grade systems. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity as a means of identifying promising areas for new development. In the Nevada play fairway project, nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new geothermal potential map of 96,000 km2. Granite Springs Valley in western Nevada is a particularly promising site selected for detailed study. It contains several favorable structural settings, including terminations of major Quaternary normal faults and fault intersections. Geologic, geophysical, and geochemical techniques were employed to define the most likely sites for high permeability and select drilling targets for temperature-gradient holes. Local and intermediate permeability models were revised to reflect results of detailed analyses and generate new detailed play fairway maps of the area. The most promising site lies in the northeastern part of the basin directly east of Adobe Flat, where the horse-tailing termination of a major normal fault (as revealed by new gravity data), opaline sinter deposits, warm shallow wells, and a low-resistivity anomaly are collocated. Geothermometry suggests a blind system with temperatures as high as ~130°C in this area. Four new temperature-gradient holes document temperatures of ~80°C at ~150 m depth. Lessons learned in the detailed studies of this project include: 1) initially identified sites commonly include multiple favorable settings at a finer scale; 2) promising sites in Cenozoic basins cannot be well defined without detailed geophysical surveys; and 3) play fairway analysis is critical at multiple scales, providing a means to select regional prospects as well as vectoring into drilling targets at individual sites.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Multiple-objective Reinforcement Learning for Inverse Design and Identification

Inverse chemical design using generative deep learning (DL) models is an emerging tool, which has early success in generating molecular structures with desired properties. We enhance this tool by developing heuristics for curriculum-learning based multiple-objective (20+ objectives) reinforcement learning, and apply it to the context of chemical identi?cation. We develop a generative DL framework that utilizes constraints pertaining to the unknown molecule’s mass and functional group composition, and show that multiple-objective RL-based generative DL models can correctly identify unknown molecules with a 80% success rate, compared to the baseline approach of 0%. Lastly, the heuristics developed are not limited to just chemistry research challenges; we anticipate any problem that utilizes reinforcement learning with multiple-objectives will bene?t from it.

Artificial Intelligence, Data Science, deep learni↗
DOE OSTI2022

Towards a neutron multiplicity measurement with the Accelerator Neutrino Neutron Interaction Experiment

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26 ton Gadolinium (Gd)-loaded water Cherenkov detector located on the Booster Neutrino Beam line at Fermilab. Its main goals are the measurement of the neutron multiplicity in neutrino-nucleus interactions as well as the cross-section of Charged Current Quasi-Elastic (CCQE) neutrino interactions on water. Besides the physics goals, the experiment also aims to be a testbed for new technologies such as Large Area Picosecond Photodetectors (LAPPDs) and Water-based Liquid Scintillators (WbLS). This thesis presents a preliminary measurement of the neutron multiplicity with {ANNIE}, using an analysis conducted on a fraction of the 2021 beam year. As preparatory measures, the efficiency of ANNIE's Front Muon Veto (FMV) was determined to be {$\bar{\varepsilon}_{\mathrm{FMV}} = (95.6 \pm 1.6)\%$} while the average efficiency for active scintillator paddles in the Muon Range Detector (MRD) was found to be {$\bar{\varepsilon}_ {\mathrm{MRD}} = (92.1 \pm 7.9)\%$}. Furthermore, the simulation framework used for ANNIE was validated and adapted to reproduce the experimental data by comparing the detector response for samples of Michel electrons, Americium Beryllium neutrons, and through-going muons. The analysis finds average neutron yields of {$\bar{n}_{\mathrm{data}} (\mathrm{beam}) = (0.272 \pm 0.010_{\mathrm{stat}})$} for an inclusive set of all identified muon neutrino candidates and {$\bar{n}_{\mathrm{data}} (\mathrm{beam,FV}) = (0.287 \pm 0.044_{\mathrm{stat}})$ for interactions which happened inside of the Fiducial Volume of ANNIE, which was optimized to increase the neutron detection acceptance. The presented neutron multiplicity values represent the number of detected neutrons after all event selection cuts and are not yet corrected for the neutron detection efficiency. An equivalent analysis on a simulated beam sample predicts neutron yields of $\bar{n}_{\mathrm{MC}}(\mathrm{beam}) = (0.515 \pm 0.0 07_{\mathrm{stat}})$ and $\bar{n}_{\mathrm{MC}}(\mathrm{beam,FV}) = (0.627 \pm 0.031_{\mathrm{stat}})$, indicating that the models tend to overpredict the number of neutrons produced in such interactions. Systematic errors have been briefly considered to contribute {$\sigma_{\mathrm{sys,FMV}} \sim 0.01\,$neutrons/$\nu$-interaction} due to the slight FMV inefficiency and {$\sigma_{\mathrm{sys,n}} \sim 0.05\,$neutrons/$\nu$-interaction} due to the neutron detection efficiency. Simulation studies further highlighted the importance of neutron detection in Diffuse Supernova Background (DSNB) searches. A combination of neutron tagging and Convolutional Neural Networks was found to reduce the most relevant Neutral Current Quasi-Elastic (NCQE) interaction background below the signal level, achieving a Signal-to-Background ratio of 4:1. In a further study, we investigated the positive impact of a deployment of a WbLS target on the energy reconstruction in ANNIE. WbLS provides a scintillation signal from hadronic recoils in addition to the charged lepton that can be included in neutrino energy reconstruction. It was found that a deployed WbLS volume in ANNIE improves the neutrino energy reconstruction from 14\% to 12\%, with the potential of going beyond this if more sophisticated reconstruction algorithms are developed in the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Method and apparatus for implementing ultra-high stability stages with combined degrees of freedom for multiple axes of motion

A method and apparatus are provided for implementing an ultra-high stability stage with combined degrees of freedom for multiple axes of motion. The ultra-high stability stage includes a base, a driving wedge supported by the base and a following wedge supported by the driving wedge. The base and each wedge are formed of a selected stable material having predefined rigidity and low thermal expansion coefficient. Integrated air bearings, respective driving mechanics associated with each of the wedges and guiding components having selected degrees of freedom enable movement about multiple axes of motion, such as X, Y, Z translation axes, and rotation X and rotation Y axes. Another ultra-high stability stage with combined degrees of freedom for multiple axes of motion includes an intermediate wedge between the driving wedge and the following wedge to enable additional movement about a rotation X axis.

Preissner, Curt Alfred↗
DOE OSTI2022

Multiplication of freestanding III-V semiconductor membranes from a single wafer by alternating growth with amorphous graphene interlayer

Freestanding single-crystalline III-V compound semiconductors are important building blocks for functional devices due to their high electron mobilities, a wide range of bandgaps, and excellent optoelectronic properties. Despite efforts to produce such membranes by detaching epitaxial layers from donor wafers, current methods suffer from either slow processes or poor material quality. Here, we demonstrate a technique to grow and harvest multiple epitaxial membranes with extremely high throughput at the wafer scale. For this, a process to directly grow amorphous graphene on III-V substrates in metal-organic chemical vapor deposition reactors is developed, which enables an advanced remote epitaxy scheme comprised of multiple alternating layers of amorphous graphene and III-V epitaxial layers that can be formed by a single epitaxy run. Each epilayer in the multi-stack structure is then harvested by layer-by-layer peeling, producing multiple freestanding membranes with unprecedented throughput from a single wafer. Because amorphous graphene provides a weak van der Waals interface that allows peeling at the interface without damaging the epilayer or the substrate, wafers can be reused for subsequent membrane production. Therefore, this work represents a meaningful step toward high-throughput and low-cost production of single-crystal membranes that can be heterointegrated.

Han, Ne Myo↗
DOE OSTI2022

Analog vector-matrix multiplication by capacitive elements with resistive state storage

An array circuit includes a plurality of vector-matrix multiplication (VMM) elements arranged in rows and columns. The VMM elements are configured to collectively perform multiplication of an input vector by a programmed input matrix to generate a plurality of output values that are representative of a result matrix that is the result of multiplication of the input vector and the input matrix. The VMM elements store states of the input matrix. Input voltages to the array are representative of elements of the input vector. A VMM element draws charge from a column read line based upon charging of a capacitor in the VMM. An integrator circuit connected to the column read line outputs a voltage that is indicative of a total charge drawn from the column read line by elements connected to the read line, which voltage is further indicative of an element of a result matrix.

Agarwal, Sapan↗
DOE OSTI2016

Optimizing a Multiple Right-Hand Side Dslash Kernel for Intel Knights Corner

Lattice Quantum Chromo-dynamics (LQCD) stands unique as the only computationally tractable, non-perturbative, and model-independent quantum field theory of the strong nuclear force. LQCD achieves tractability by discretizing our familiar 4-dimensional space-time onto a hypercubic lattice. The core component of the linear solver used in LQCD is the Wilson-Dirac operator whose finite difference component is called the Dslash operator. Dslash is a nearest neighbor stencil operator summing matrix-vector multiplications over lattice points. The arithmetic intensity of a regular Dslash operator acting on a single vector in single precision is between 0.88-2.29 (depending on the tricks employed) making it memory bandwidth bound on most current architectures, including Xeon Phi. Maximizing the performance of Dslash on Xeon Phi requires deliberate exploitation of its architectural features. One key feature of Xeon Phi is its powerful vector processing unit with lengthy vector registers. There is a class of LQCD computations which aims to solve the Dirac equation for the same lattice gauge fields multiple times. In this case one can gain additional reuse of the gauge field, and potentially simplified vectorization, through applying Dslash to several vectors at the same time; often referred to as Multiple Right Hand Side (MRHS) Dslash. Previous work in this area focused on applying this approach to the Highly Improved Staggered operator, and in cases to the multi-Grid algorithm for Wilson clover fermions. Here, we present two approaches to MRHS Dslash: a vector register blocking approach and one using the software package QPhiX with a custom Code Generator for low-level intrinsics. We explore the Knights Corner instruction set, memory hierarchy, and threading capabilities. For standard lattice sizes used in testing, we observed significant speedups, with sustained performance of over 700 GFLOPS (single precision) in one instance. We achieved up to 27% of theoretical peak performance compared to a maximum of 12% obtained by the previous single RHS method in QPhiX.

Joó, Bálint↗
DOE OSTI2023

High Multiplication Neutron Noise Measurements Using the 7uPCX Assembly

The Seven Percent Critical Experiment, or 7uPCX, is a system that mimics the physics of light water nuclear reactor systems by using uranium dioxide fuel pins at an enrichment of approximately 7%. 7uPCX is often used for benchmarking and nuclear data purposes. As part of a collaboration between Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Sandia National Laboratories, and the Institut de Radioprotection et de Sûreté Nucléaire, measurements were performed in support of a high-multiplication, subcritical benchmark candidate for a thermal system. The measurements were completed by making subcritical configurations using the fuel loading pattern of a well-documented configuration of the Seven Percent Critical Experiment at Sandia National Laboratories, which exists as a benchmark in the International Criticality Safety Benchmark Evaluation Project handbook. These measurements, which aimed to capture multiplications ranging from approximately 10 to 1,000, also serve as an intercomparison between both the fielded detector systems and analysis methodologies with the goal of better characterizing the detectors and their ability to capture the state of the criticality these types of systems. Los Alamos National Laboratory’s measurements for this collaboration were made with five linked helium-3 based neutron multiplicity detectors placed on the periphery of the reactor tank beyond the infinite reflector thickness of water, and four organic scintillators placed in dry-wells in-reactor near the edge of the upper fuel grid plate. This work captures the Los Alamos National Laboratory measurements, the Rossi-α and Feynman-Y results, provides an intercomparison between the results of the 3 He neutron detectors and the organic scintillators, compares to simulation where possible, and expands on future work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Development of a Research Reactor Protocol for Neutron Multiplication Measurements

Establishing a protocol for measurements on research reactors is the next step in advanced subcritical neutron multiplication inference measurements. Such measurements can help identify deficiencies and quantify uncertainties in nuclear data and validate predictive Monte Carlo radiation transport simulation capabilities related to subcritical neutron multiplication inference techniques. This work expands on previous benchmark-quality efforts performed at the National Criticality Experiments Research Center (NCERC) located in Nevada, including subcritical experiments with a 4.5-kg {alpha}-phase plutonium sphere surrounded by copper, tungsten and nickel. Evaluations of the nickel and tungsten measurements have both been accepted into the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The nickel benchmark was the first ICSBEP-accepted evaluation of measurements using the Feynman Variance-to-Mean method based on the Hage-Cifarelli formulism, and was the culmination of many years of subcritical experiment research. To help establish a protocol for research reactor-based subcritical measurements, a series of Critical and Subcritical {Phi}-Power Experiments at Rensselaer (CaSPER) have been designed. This neutron multiplication measurement series will be executed at the Rensselaer Polytechnic Institute Walthousen Reactor Critical Facility (RPI-RCF) in upstate New York. The RPI reactor facility can provide benchmark-quality integral experimental configurations where different reactivity states can be achieved by varying the control rod height/water height in the reactor. The diversity of achievable configurations are also unique in contrast to previous subcritical benchmark measurements in that they are spatially complex, involve different materials (fuel, moderator), and are characterized by system-specific neutron cross section sensitivities (various energy ranges and neutron reaction contributions). It is worth noting that previous proof-of-concept subcritical measurements have been performed on thermal systems at NCERC, at a variety of reactivity states by separation distance, yet it was not possible to know the reactivity of various configurations accurately for benchmarking (there are no control rod worth curves as there are no control rods). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Assembling Multiple Models Within the RAVEN Framework

RAVEN (Risk Analysis Virtual Environment) is an INL-developed software tool that can be used to identify and increase the safety margin in complex systems. As a generic software framework, RAVEN is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN is currently able to construct multi-targets Reduced Order Models (ROMs), which are aimed to represent the response of a system (in a fixed configuration) for multiple Figures of Merits (FOMs) and time-dependent ROMs. These capabilities represent the initial steps for a larger implementation about the interaction of multiple models. In fact, in several cases, multiple models need to interface with each other since the initial conditions of one are dependent on the outcomes of another. To better understand the problem that here is solved, it is useful to consider a simple example: The following problem is considered: a weather forecast simulation code 'a' is used to compute the external (i.e. ambient) temperature in a certain location. A second model 'b' is inquired to compute the average temperature in a room having as boundary condition, among several others, the external ambient temperature. The response of the model 'b' depends on the outcome of the model 'a'. The reported example is only aimed to illustrate the reason why the creation of a framework to make interact different models is a key development for the advancement of RAVEN as a comprehensive calculation flow driver. Before reporting how the ensemble-models have been implemented, it is necessary to briefly describe the representative Model 'entities' that are available in RAVEN.

42 ENGINEERING↗
DOE OSTI2023

Design of Nuclear Criticality Safety Framework for Hands-on Construction of Fast Systems Over Ranges of Multiplication

Since 1945, Los Alamos National Laboratory (LANL) has performed critical experiments, primarily at the Los Alamos Critical Experiments Facility (LACEF) at Technical Area 18 (TA-18). Since 2011, these experiments have been conducted by the National Criticality Experiments Research Center (NCERC), operated by LANL, at the Device Assembly Facility (DAF) in the Nevada National Security Site (NNSS). These experiments utilize various types of Special Nuclear Material (SNM). Some of these experiments utilize what is referred to as the Rocky Flat Shells, which are called such as they came from the Rocky Flats Plant. These concentric hemi-shells are made of Highly Enriched Uranium (HEU), which is 93 w/o 235U. Fig. 1. Subset of the Rocky Flat Shells LANL is designing a new subcritical hands-on experiment with the goal of achieving a neutron multiplication in the range of 50 to 200, which correlates to Keff values of 0.98 to 0.995. ANSI/ANS-1 is the standard for Conduct of Critical Experiments which governs critical operations at NCERC. Section 3.9 of ANSI/ANS-1 states that when manipulating a critical assembly by hand, the predicted k eff of a known configuration should not exceed 0.95 (a neutron multiplication of 20). This presents a challenge, as this system would have a higher multiplication than 20 and the assembly would have to remain subcritical in normal and credible accident scenarios. To ensure the safety of such an assembly, the different normal and abnormal conditions that could alter the criticality 1 MCNP® and Monte Carlo N-Particle® are registered trademarks owned by Triad National Security, LLC, manager and operator of Los Alamos National Laboratory. Any third party use of such registered marks should be properly of the system must be considered and analyzed. If such a condition is deemed to be credible, it will be further investigated using the Monte Carlo N-Particle (MCNP) transport code. If the results of these simulations show that a k eff larger than one could be possible, modifications to the assembly will be made until such an event is deemed no longer possible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Vortex-Controlled Quasiparticle Multiplication and Self-Growth Dynamics in Superconducting Resonators

Even in the quantum limit, non-equilibrium quasiparticle (QP) populations induce QP poisoning that irreversibly relaxes the quantum state and significantly degrades the coherence of transmon qubits. A particularly detrimental yet previously unexplored mechanism arises from QP multiplication facilitated by vortex trapping in superconducting quantum circuits, where a high-energy QP relaxes by breaking additional Cooper pairs and amplifying the QP population due to the locally reduced excitation gap and enhanced quantum confinement within the vortex core. Here we directly resolve this elusive QP multiplication process by revealing vortex-controlled QP self-generation in a highly nonequilibrium regime preceding the phonon bottleneck of QP relaxation. At sufficiently low fluence, femtosecond-resolved magneto-reflection spectroscopy directly reveals a continuously increasing QP population that is strongly dependent on magnetic-field-tuned vortex density and absent at higher excitation fluences. Quantitative analysis of the emergent QP pre-bottleneck dynamics further reveals that, although the phonon population saturates within $\simeq$10~ps, both free and trapped QPs continue to grow in a self-sustained manner--hallmarks of the long-anticipated QP-vortex interactions in nonequilibrium superconductivity. We estimate a substantial increase of $\sim$34% in QP density at vortex densities of $\sim$ 100 magnetic flux quanta per $\mathrm{μm^{2}}$. Our findings establish a powerful spectroscopic tool for uncovering QP multiplication and reveal vortex-assisted QP relaxation as a critical materials bottleneck whose mitigation will be essential for resolving QP poisoning and enhancing coherence in superconducting qubits.

Park, Joong M. [Ames Lab]↗