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A bilayer Double Semion model with symmetry-enriched topological order

We construct a new model of two-dimensional quantum spin systems that combines intrinsic topological orders and a global symmetry called flavour symmetry. It is referred as the bilayer Doubled Semion model (bDS) and is an instance of symmetry-enriched topological order. A honeycomb bilayer lattice is introduced to combine a Double Semion Topological Order with a global spin–flavour symmetry to get the fractionalization of its quasiparticles. The bDS model exhibits non-trivial braiding self-statistics of excitations and its dual model constitutes a Symmetry-Protected Topological Order with novel edge states. This dual model gives rise to a bilayer Non-Trivial Paramagnet that is invariant under the flavour symmetry and the well-known spin flip symmetry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Report on FY 2023 Research and Development on Specially Designed Creep-fatigue Experiments on Alloy 617 in Support of Improving Creep-fatigue Evaluation Approaches

Experimental and numerical studies in support of developing the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY 2023. This report focuses on the methods for extrapolating the EPP+SMT creep-fatigue life curves at long hold times and low strain ranges at elevated temperatures. In this work, the available uniaxial creep-fatigue failure data on Alloy 617 at temperatures of 950°C and 850°C were analyzed to provide a guidance on the development of the extrapolation method and the creep-fatigue failure criteria. A viscoplastic constitutive model for Alloy 617 was adopted to extrapolate the mechanical responses to low strain ranges and long hold times. A set of design curves of Alloy 617 at temperatures of 950°C, 850°C, and 800°C with tensile hold times of 1 hr, 100 hr, and 1,000 hr are developed. Furthermore, creep-fatigue testing on two notch specimen geometries, shallow-notch and sharp V-notch, on Alloy 617 was performed 950°C to understand the multiaxial stress relaxation behavior. The experimental and numerical results on the notch specimens were compared with those on the standard uniaxial smooth bar specimens. The effect of multi-axial stress state combined with elastic follow-up on the stress relaxation behavior was investigated in this report.

36 MATERIALS SCIENCE↗

SU-F-303-17: Real Time Dose Calculation of MRI Guided Co-60 Radiotherapy Treatments On Free Breathing Patients, Using a Motion Model and Fast Monte Carlo Dose Calculation

Purpose: To demonstrate real-time dose calculation of free-breathing MRI guided Co−60 treatments, using a motion model and Monte-Carlo dose calculation to accurately account for the interplay between irregular breathing motion and an IMRT delivery. Methods: ViewRay Co-60 dose distributions were optimized on ITVs contoured from free-breathing CT images of lung cancer patients. Each treatment plan was separated into 0.25s segments, accounting for the MLC positions and beam angles at each time point. A voxel-specific motion model derived from multiple fast-helical free-breathing CTs and deformable registration was calculated for each patient. 3D images for every 0.25s of a simulated treatment were generated in real time, here using a bellows signal as a surrogate to accurately account for breathing irregularities. Monte-Carlo dose calculation was performed every 0.25s of the treatment, with the number of histories in each calculation scaled to give an overall 1% statistical uncertainty. Each dose calculation was deformed back to the reference image using the motion model and accumulated. The static and real-time dose calculations were compared. Results: Image generation was performed in real time at 4 frames per second (GPU). Monte-Carlo dose calculation was performed at approximately 1frame per second (CPU), giving a total calculation time of approximately 30 minutes per treatment. Results show both cold- and hot-spots in and around the ITV, and increased dose to contralateral lung as the tumor moves in and out of the beam during treatment. Conclusion: An accurate motion model combined with a fast Monte-Carlo dose calculation allows almost real-time dose calculation of a free-breathing treatment. When combined with sagittal 2D-cine-mode MRI during treatment to update the motion model in real time, this will allow the true delivered dose of a treatment to be calculated, providing a useful tool for adaptive planning and assessing the effectiveness of gated treatments.

60 APPLIED LIFE SCIENCES↗

Considerations for improving the biosphere assessment methodology and the associated conceptual and mathematical models for application to LLW/ILW radioactive wastes in Spain - 15194

We give consideration to future needs in assessment studies relating to the disposal of very low level radioactive waste (VLLW), low level radioactive waste (LLW) and intermediate level radioactive waste (ILW) in Spain. As these wastes are primarily disposed at El Cabril, particular attention is given to the characteristics of that site. The focus is on post-closure performance assessment studies and specifically on the biosphere aspect of those studies. In particular, it gives consideration to the assessment methodology that should be used, taking into account the recommendations made in the international BIOMASS and BIOCLIM programs, as well as more recent developments. It then goes on to consider the conceptual models of the biosphere that should be developed and comments on how these should be transformed into mathematical models. The issues arising in conceptual and mathematical model development are illustrated by reference to El Cabril, but several of these issues would also be applicable to other engineered facilities excavated from the surface in a variety of geographical and geological contexts. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nuclear Archaeology for Gaseous Diffusion Enrichment Plants

Gaseous diffusion was historically the most widely used technology for military production of highly enriched uranium. Since June 2013, all gaseous diffusion enrichment plants worldwide are permanently shut down. The experience with decommissioning some of these plants has shown that they contain large amounts of uranium particles deposited in the cascade equipment. This article evaluates the potential of using uranium particle deposition to understand and reconstruct the operating histories of gaseous diffusion enrichment plants. First, a squared-off cascade enrichment model is derived to estimate the enrichment capacity of a reference plant. Then, using a cross-flow filtration model, the mass of solid uranium particles deposited over time in the tubular separation membranes of the stage diffusers is calculated. Lastly, potential techniques to characterize these uranium deposits and help reconstruct the operating history of the plant are assessed.

07 ISOTOPE AND RADIATION SOURCES↗

Coda Calibration Tool

CCT is a Java based application for calibrating 10 shear wave coda measurement models to observed data using a much smaller set of reference moment magnitudes (MWs) calculated from other means (waveform modeling, etc.). These calibrated measurement models can then be used in other tools to generate coda moment magnitude measurements, source spectra, estimated stress drop, and other useful measurements for any additional events and any new data collected in the calibrated region.

Addair, Travis↗

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗

Definition of the IEA Wind 22-Megawatt Offshore Reference Wind Turbine

This technical report describes the design of a new 22 Megawatt reference wind turbine (RWT). The turbine model was designed collaboratively by two teams at the Denmark Technical University and at the National Renewable Energy Laboratory within the International Energy Agency (IEA) Wind Technology Commercialization Programme (TCP) Task 55 on Reference Wind Turbines and Farms. RWTs serve an important purpose in the wind energy community, since they provide openly available data for models representative of current wind turbine technology, which can be used by practitioners for a variety of modeling purposes, ranging from aerodynamic, structural, and aeroelastic turbine modeling to wind farm flow modeling, across a range of fidelities. The IEA 22 RWT aims to model machines with projected installation in the 2025-2030 time frame. The turbine has a rotor diameter of 284 meters and a hub height of 170 meters. It is a class 1-B machine with a rotor specific power nearing 350 W m -2 and it is mounted on either a fixed-bottom offshore foundation or a semi-submersible floating platform.

17 WIND ENERGY↗

Disorder effect on the anisotropic resistivity of phosphorene determined by a tight-binding model

In this work we develop a compact multiorbital tight-binding model for phosphorene that accurately describes states near the main band gap. The model parameters are adjusted using as reference the band structure obtained by a density functional theory calculation with the hybrid HSE06 functional. We use the optimized tight-binding model to study the effects of disorder on the anisotropic transport properties of phosphorene. In particular, we evaluate how the longitudinal resistivity depends on the lattice orientation for two typical disorder models: dilute scatterers with high potential fluctuation amplitudes, mimicking screened charges in the substrate, and dense scatterers with lower amplitudes, simulating weakly bounded adsorbates. We show that the intrinsic anisotropy associated to the band structure of this material, although sensitive to the type and intensity of the disorder, is robust.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Retrospective Analysis of Backwater Habitat Availability Using Remote Sensing

Low-velocity channel-margin habitats serve as important nursery habitats for the endangered Colorado pikeminnow (Ptychocheilus lucius) in the middle Green River between Jensen and Ouray, Utah. These habitats, known as backwaters, are associated with emergent sandbars, and are shaped and reformed annually by peak flows. Our recent knowledge about backwater characteristics and dynamics that is summarized in the synthesis report (Grippo et al. 2015) was based on detailed annual survey data from a relatively small sample of backwaters that were collected from 2003 to 2014 and reach-wide evaluations of backwater surface area based on manual interpretation of aerial and satellite imagery. Methods that bridge the gap between the detailed surveys from a small number of backwaters and the reach-wide assessment of their surface area would enable an assessment of the availability of backwater habitats that meet the minimum depth requirements for suitable habitat for Colorado pikeminnow. In 2015 Argonne National Laboratory (Argonne) tested three regression models—linear, multiple, and partial least square (PLS) regression models—for estimating backwater depth using National Agriculture Imagery Program (NAIP) imagery collected in July 2006 that covered the Jensen-Ouray reach of the Green River (Hamada and LaGory 2016). The results suggested that a PLS regression model showed high correlation with the reference depth (R 2 = 0.69) and had the most unbiased and consistent estimate of backwater depth. The results also indicated that the PLS model would provide reasonable estimates of the amount of habitat providing a minimum suitable depth of 30 cm for young-of-the-year Colorado pikeminnow, even though absolute depth estimates may be uncertain for backwater areas deeper than approximately 40 cm. The study also provided insights regarding the amount and the selection of calibration and validation (cal-val) data needed for improving the accuracy of depth prediction.

54 ENVIRONMENTAL SCIENCES↗

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by the observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.

54 ENVIRONMENTAL SCIENCES↗

Deployment of neural-network-based neutron microscopic cross sections in the Griffin reactor physics application

The capability to utilize neural networks to predict macroscopic and microscopic cross section parametric spaces has been developed for the Griffin reactor physics application. The LibTorch interface enables Griffin's MOOSE-based materials to interact with LibTorch-trained models, allowing for the evaluation of complex macroscopic or microscopic cross section spaces, which are then used to evaluate the neutronic properties of the Griffin finite element model. This study benchmarks traditional ISOXML-formatted tabulation libraries against neural network-based models for 279 nuclides on 20,160 grid points for zero-dimensional and two-dimensional reactor models. Benchmark metrics include the fundamental mode eigenvalue, fission and absorption rates, and various temperature coefficients of reactivity (isothermal, fuel, and moderator). From the perspective of storage space, the complete set of LibTorch models uses 11 MB on disk, compared to the 10 GB for the ISOXML multigroup library that covers the same grid space. For the two-dimensional performance case considered in Griffin, the Torch model uses 97% less RAM than the reference ISOXML dataset while runtime increases by a factor of 3 when using the LibTorch model compared to the ISOXML dataset with multi-linear interpolation. The LibTorch model consistently yields errors within 0.01% for most analyzed quantities except for the temperature coefficients of reactivity where the maximum discrepancies are up to 0.3 $\frac{pcm}{K}$. Due to the neural network attempting to best predict quantities with no regard for a positive or negative bias for any given quantity, predictions may experience random fluctuations, resulting in both positive and negative errors. Future work will entail both depletion and coupled transient analysis to determine the predictive capabilities of Griffin with neural network-based cross sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Seismic inversion of the solar entropy: setting a cat among the pigeons

The Sun is the most constrained and well-studied of all stars. As a consequence, the physical ingredients entering solar models are used as a reference to study all other stars observed in the Universe. However, our understanding of the solar structure is still imperfect, as illustrated by the current debate on the heavy element abundances in the Sun. Aims. We wish to provide additional information on the solar structure by carrying out structural inversions of a new physical quantity, a proxy of the entropy of the solar plasma which properties are very sensitive to the temperature gradient below the convective zone. Methods. We use new structural kernels to carry out direct inversions of an entropy proxy of the solar plasma and compare the solar structure to various standard solar models built using various opacity tables and chemical abundances. We also link our results to classical tests commonly found in the literature. Results. Our analysis allows us to probe more efficiently the uncertain regions of the solar models, just below the convective zone, paving the way for new in-depth analyses of the Sun taking into account additional physical uncertainties of solar models beyond the specific question of chemical abundances.

79 ASTRONOMY AND ASTROPHYSICS↗

Modular Growth and Nucleation Formulations in Modular Plasticity Models

Recent investigations like the second and third Sandia Fracture Challenges have characterized and demonstrated the performance of a variety of failure techniques and models. These surveys have considered a wide breadth of models encapsulating both general failure criteria as well as those focusing on pore nucleation and growth. Extensive reviews exist on both topics. The former category generally consists of classic models like the Johnson-Cook or Wilkins criteria. These models were recently added to modular plasticity models in the Library of Advanced Materials for Engineering (LAME) as criteria for use with element death capabilities. The latter category was not treated in that effort. There exists a large class of failure models based on predicting the evolution of pores and failure associated with such microstructures. While the exact mechanisms and corresponding impact on the macroscale behavior remain an active area of research, a large suite of formulations have been proposed combining different features of both pore nucleation and subsequent growth. The most famous of these are based on the popular Gurson model of pore growth derived via micromechanical analysis assuming a plastically incompressible matrix. Numerous other models exist for both growth and nucleation and the Cocks-Ashby growth and Horstemeyer-Gokhale nucleation models have been used successfully in recent Sandia Fracture Challenges. This specific combination is colloquially referred to as the "BCJ-failure model as it has been frequently used with the Bammann-Chisea-Johnson plasticity model.

36 MATERIALS SCIENCE↗

TH-AB-207A-06: The Use of Realistic Phantoms to Predict CT Dose to Pediatric Patients

Purpose: To predict pediatric patient dose from diagnostic CT scans using Monte Carlo simulation of realistic reference phantoms of various ages, weights, and heights. Methods: A series of deformable pediatric reference phantoms using Non-Uniform Rational B-Splines (NURBS) was developed for a large range of ages, percentiles, and reference anatomy. Individual bones were modeled using age-dependent factors, and red marrow was modeled as functions of age and spatial distribution based on Cristy1. Organ and effective doses for the phantom series were calculated using Monte Carlo simulation of chest, abdominopelvic, and chest-abdomen-pelvis CT exams. Non-linear regression was performed to determine the relationship between dose-length-product (DLP)-normalized organ and effective doses and phantom diameter. Patient-specific voxel computational phantoms were also created by manual segmentation of previously acquired CT images for 40 pediatric patients (0.7 to 17 years). Organ and effective doses were determined by Monte Carlo simulation of these patient-specific phantoms. Each patient was matched to the closest pediatric reference phantom based primarily on age and diameter for all major organs within the torso. Results: A total of 80 NURBS phantoms were created ranging from newborn to 15 years with height/weight percentiles from 10 to 90%. Organ and effective dose normalized by DLP correlated strongly with exponentially decreasing average phantom diameter (R{sup 2} > 0.95 for most organs). A similar relationship was determined for the patient-specific voxel phantoms. Differences between patient-phantom matched organ-dose values ranged from 0.37 to 2.39 mGy (2.87% to 22.1%). Conclusion: Dose estimation using NURBS-based pediatric reference phantoms offers the ability to predict patient dose before and after CT examinations, and physicians and scientists can use this information in their analysis of dose prescriptions for particular subjects and study types. This may lead to practices that minimize radiation dose while still achieving high quality images and, ultimately, improved patient care. NIH/NCI 1 R01 CA155400-01A1.

60 APPLIED LIFE SCIENCES↗

The structure and propagation of laminar flames under autoignitive conditions

The laminar flame speed s l is an important reference quantity for characterising and modelling combustion. Experimental measurements of laminar flame speed require the residence time of the fuel/air mixture (τ f ) to be shorter than the autoignition delay time (τ). This presents a considerable challenge for conditions where autoignition occurs rapidly, such as in compression ignition engines. As a result, experimental measurements in typical compression ignition engine conditions do not exist. Simulations of freely propagating premixed flames, where the burning velocity is found as an eigenvalue of the solution, are also not well posed in such conditions, since the mixture ahead of the flame can autoignite, leading to the so called “cold boundary problem”. In this paper, a numerical method for estimating a reference flame speed, s R , is proposed that is valid for laminar flame propagation at autoignitive conditions. Two isomer fuels are considered to test this method: ethanol, which in the considered conditions is a single-stage ignition fuel; and dimethyl ether, which has a temperature-dependent single- or two-stage ignition and a negative temperature coefficient regime for τ. Calculations are performed for the flame position in a one-dimensional computational domain with inflow-outflow boundary conditions, as a function of the inlet velocity U I and for stoichiometric fuel–air premixtures. The response of the flame position, L F , to U I shows distinct stabilisation regimes. For single-stage ignition fuels, at low U I the flame speed exceeds U I and the flame becomes attached to the inlet. Above a critical U I value, the flame detaches from the inlet and L f becomes extremely sensitive to U I until, for sufficiently high U I , the sensitivity decreases and L f corresponds to the location expected from a purely autoignition stabilised flame. The transition from the attached to the autoignition regimes has a corresponding peak dL f /dU I value which is proposed to be a unique reference flame speed s R for single-stage ignition fuels. For two-stage ignition fuels, there is an additional stable regime where a high-temperature flame propagates into a pool of combustion intermediates generated by the first stage of autoignition. This results in two peaks in dL f /dU I and therefore two reference flame speed values. The lower value corresponds to the definition of s R for single-stage ignition fuels, while the higher value exists only for two-stage ignition fuels and corresponds to a high temperature flame propagating into the first stage of autoignition and is denoted s R ' . Finally, a transport budget analysis for low- and high-temperature radical species is also performed, which confirms that the flame structures at U I = s R and U I = s R ' do indeed correspond to premixed flames (deflagrations), as opposed to spontaneous ignition fronts which do not have a unique propagation speed.

33 ADVANCED PROPULSION SYSTEMS↗

An extrapolation method for strain ranges and hold times in developing the EPP+SMT creep-fatigue design curves for Alloy 617

Experimental and numerical studies in developing the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY2022. This report focuses on the methods for extrapolating the EPP+SMT creep-fatigue (CF) design curves at long hold times and low strain ranges. In this study, the available CF failure data on Alloy 617 at 950°C were analyzed to determine a set of CF failure criteria. At very low strain ranges and long hold times, CF failure data are not accessible by experiments because of the extraordinarily long test durations and the inability of the test machines to accurately control these small strain ranges. A CF experimental approach with the concept of block-strain range CF testing protocol was developed. Tests using this protocol were conducted to generate the needed information for calibrating material parameters of the numerical material models. The Time Fraction based method and Dissipated Energy method were used to extrapolate the CF life curves to low strain ranges and long hold times. Based on the new experimental approach and CF life prediction methods, the CF life curves with various hold times were developed for Alloy 617 at 950°C. In addition, an experiment was designed and is being performed to verify the predicted CF curves at 950°C. The extrapolation procedure will be applied at lower temperatures to complete the development of the EPP+SMT CF design curves for Alloy 617 in F2023.

36 MATERIALS SCIENCE↗