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At least 1,063 records · Page 59

Multi-Layer RF Tissue Phantoms for Mimicking a Human Core

This work presents the design recipe, fabrication process and characterization of tissue-simulating materials, configured as a physical model to mimic the electrical and some physical properties of an abdominal cavity. The complete three-layer design is called the human core model (HCM) see Fig. 1. To our knowledge, presented is the first hybrid skin-muscle phantom developed to mimic the electrical properties of the intervening tissue layers of an abdominal cavity within the frequency band of 1 GHz - 2 GHz, a band of interest for human body sensing due to its deep detection depth.

Biomedical Microwave Sensing↗

Evaluation of SSME test data reduction methods

Accurate prediction of hardware and flow characteristics within the Space Shuttle Main Engine (SSME) during transient and main-stage operation requires a significant integration of ground test data, flight experience, and computational models. The process of integrating SSME test measurements with physical model predictions is commonly referred to as data reduction. Uncertainties within both test measurements and simplified models of the SSME flow environment compound the data integration problem. The first objective of this effort was to establish an acceptability criterion for data reduction solutions. The second objective of this effort was to investigate the data reduction potential of the ROCETS (Rocket Engine Transient Simulation) simulation platform. A simplified ROCETS model of the SSME was obtained from the MSFC Performance Analysis Branch . This model was examined and tested for physical consistency. Two modules were constructed and added to the ROCETS library to independently check the mass and energy balances of selected engine subsystems including the low pressure fuel turbopump, the high pressure fuel turbopump, the low pressure oxidizer turbopump, the high pressure oxidizer turbopump, the fuel preburner, the oxidizer preburner, the main combustion chamber coolant circuit, and the nozzle coolant circuit. A sensitivity study was then conducted to determine the individual influences of forty-two hardware characteristics on fourteen high pressure region prediction variables as returned by the SSME ROCETS model.

Santi, L. Michael↗

Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

Kang, Do Hyuk↗

Integrated Multiscale Modeling for Design of Robust 3D Solid-State Lithium Batteries - FY21 Annual Report

This project is developing a multiscale, multi-physics modeling framework for probing the effects of materials microstructure and device architecture on ion transport within 3D ceramic solid-state battery materials, with the goal of enhancing performance and reliability. The project has three primary objectives: (1) integrate multi physics and multiscale model components; (2) understand interface- and microstructure-derived limitations on ion transport; and (3) derive key structure-performance relations for enabling future optimization.

25 ENERGY STORAGE↗

Constraining computational modeling of indirect drive double shell capsule implosions using experiments

Double shell capsule implosions are an alternative approach to achieving alpha heating on the National Ignition Facility. Current machining techniques construct the outer shell as two hemispheres that are glued together, and the deuterium and tritium (DT) liquid inside the inner shell will be injected by a fill tube. These features introduce asymmetries and jetting that may disrupt the confinement of the DT fuel if not carefully controlled. Simulations indicate that in order to achieve high yields in the laboratory, these features as well as susceptibility to the Rayleigh–Taylor instability (RTI) must be mitigated. Furthermore, due to uncertainties in computational models and the expense of using the best physics models at adequate resolution in three dimensions, our computational modeling must be constrained by experiments. We report on the results of recent hydrogrowth radiography and dual-axis keyhole experiments with double shell targets that have been used to evaluate our modeling of the outer shell joint as well as the impacts of high-energy x-ray preheat that strongly impacts RTI growth. Our simulations show good agreement with the experimental data and inform several important modeling choices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NuSTAR detection of high-energy X-ray emission and rapid variability from Sagittarius A{sup *} flares

Sagittarius A{sup *} harbors the supermassive black hole that lies at the dynamical center of our Galaxy. Sagittarius A{sup *} spends most of its time in a low luminosity emission state but flares frequently in the infrared and X-ray, increasing up to a few hundred fold in brightness for up to a few hours at a time. The physical processes giving rise to the X-ray flares are uncertain. Here we report the detection with the NuSTAR observatory in Summer and Fall 2012 of four low to medium amplitude X-ray flares to energies up to 79 keV. For the first time, we clearly see that the power-law spectrum of Sagittarius A{sup *} X-ray flares extends to high energy, with no evidence for a cutoff. Although the photon index of the absorbed power-law fits are in agreement with past observations, we find a difference between the photon index of two of the flares (significant at the 95% confidence level). The spectra of the two brightest flares (∼55 times quiescence in the 2-10 keV band) are compared to simple physical models in an attempt to identify the main X-ray emission mechanism, but the data do not allow us to significantly discriminate between them. However, we confirm the previous finding that the parameters obtained with synchrotron models are, for the X-ray emission, physically more reasonable than those obtained with inverse Compton models. One flare exhibits large and rapid (<100 s) variability, which, considering the total energy radiated, constrains the location of the flaring region to be within ∼10 Schwarzschild radii of the black hole.

79 ASTRONOMY AND ASTROPHYSICS↗

Spray combustion model improvement study, 1

This study involves the development of numerical and physical modeling in spray combustion. These modeling efforts are mainly motivated to improve the physical submodels of turbulence, combustion, atomization, dense spray effects, and group vaporization. The present mathematical formulation can be easily implemented in any time-marching multiple pressure correction methodologies such as MAST code. A sequence of validation cases includes the nonevaporating, evaporating and_burnin dense_sprays.

Chen, C. P.↗

NuSTAR Detection of High-Energy X-Ray Emission and Rapid Variability from Sagittarius A(star) Flares

Sagittarius A(star) harbors the supermassive black hole that lies at the dynamical center of our Galaxy. Sagittarius A(star) spends most of its time in a low luminosity emission state but flares frequently in the infrared and X-ray, increasing up to a few hundred fold in brightness for up to a few hours at a time. The physical processes giving rise to the X-ray flares are uncertain. Here we report the detection with the NuSTAR observatory in Summer and Fall 2012 of four low to medium amplitude X-ray flares to energies up to 79 keV. For the first time, we clearly see that the power-law spectrum of Sagittarius A(star) X-ray flares extends to high energy, with no evidence for a cut off. Although the photon index of the absorbed power-law fits are in agreement with past observations, we find a difference between the photon index of two of the flares (significant at the 95% confidence level). The spectra of the two brightest flares (approx. 55 times quiescence in the 2- 10 keV band) are compared to simple physical models in an attempt to identify the main X-ray emission mechanism, but the data do not allow us to significantly discriminate between them. However, we confirm the previous finding that the parameters obtained with synchrotron models are, for the X-ray emission, physically more reasonable than those obtained with inverse-Compton models. One flare exhibits large and rapid (less than 100 s) variability, which, considering the total energy radiated, constrains the location of the flaring region to be within approx. 10 Schwarzschild radii of the black hole.

NuSTAR detection of high-energy X-ray emission and↗

Breeding Realistic D‐Brane Models

Abstract Intersecting branes provide a useful mechanism to construct particle physics models from string theory with a wide variety of desirable characteristics. The landscape of such models can be enormous, and navigating towards regions which are most phenomenologically interesting is potentially challenging. Machine learning techniques can be used to efficiently construct large numbers of consistent and phenomenologically desirable models. In this work we phrase the problem of finding consistent intersecting D‐brane models in terms of genetic algorithms, which mimic natural selection to evolve a population collectively towards optimal solutions. For a four‐dimensional supersymmetric type IIA orientifold with intersecting D6‐branes, we demonstrate that unique, fully consistent models can be easily constructed, and, by a judicious choice of search environment and hyper‐parameters, of the found models contain the desired Standard Model gauge group factor. Having a sizable sample allows us to draw some preliminary landscape statistics of intersecting brane models both with and without the restriction of having the Standard Model gauge factor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

New Theories for Physics beyond the Standard Model

The theoretical particle physics and cosmology group at Case Western Reserve University has a great tradition in this field of research. The PI is a new professor at CWRU, and his main goal is to establish a new theoretical effort in particle physics and cosmology. The PI has been working on physics beyond the Standard Model for more than 12 years and have published more than 75 publications in this field. The proposed research project will be crucial for the postdocs and students to understand the different theories for physics beyond the Standard Model and become world experts in this field of research. The main goal of this project is to investigate new theories for physics beyond the Standard Model. The Standard Model of Particle Physics is one of the most successful theories of nature, but it cannot explain many open issues in particle physics and cosmology. In this proposal we propose to investigate new ideas which could lead to a more complete theory. The PI has proposed new theories for physics beyond the Standard Model where the baryon and lepton numbers can be defined as local gauge symmetries spontaneously broken at the low scale. In these theories one can understand the proton stability and one have some interesting predictions for cosmology. These theories have the potential to change the standard paradigm for physics beyond the Standard Model, where one assumes a great desert between the electroweak scale and the scale where one has the possible unification of fundamental forces. In this context one does not need to postulate the great desert, the proton is stable, and one can have the unification of the gauge forces at the low scale. We propose to investigate theoretical, cosmological and phenomenological aspects of the theories where the baryon and lepton numbers are local gauge symmetries. We plan to investigate new possible baryogenesis mechanisms in the case where the local baryon number is spontaneously broken at the low scale. In this case there could be a relation between the baryon asymmetry and the asymmetry in the dark matter sector. In the context of these theories, one has different candidates for the cold dark matter in the Universe and we plan to investigate all predictions for direct detection experiments and the possible signals at gamma-ray telescopes. The different signatures at the Large Hadron Collider will be investigated in great detail. In these theories one predicts the existence of new particle with baryon and lepton numbers called lepto- baryons which can give rise to exotic signatures at the Large Hadron Collider. One of the most interesting aspects to study in this context is the unification of gauge forces. Since the proton is stable in this theory one can realized the unification at the low scale and understand the embedding of these theories in grand unified theories. These studies could define a new way to think about physics beyond the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Coupling to rotational manifolds to improve gas-phase pump–probe spectroscopic models

The physical picture of gas-phase optical transitions is normally presented as an isolated two-level system balanced by upward and downward processes. Isolated models assume a phenomenological treatment of collisional dephasing but do not strictly account for collisional population exchange with the rotational baths. While this assumption is valid under low-intensity conditions, where excitation is rate-limiting, isolated models can deviate from Beer’s Law at sufficient pressures and monochromatic intensities when both collisional broadening and power broadening are comparable to (or greater than) lifetime broadening, which are not uncommon conditions for cavity enhanced spectroscopies in the mid-IR spectral range. Although this problem has been addressed by rate-equation models for linear absorption measurements, a general treatment for multi-level quantum mechanical models suitable for non-linear absorption measurements (two-photon/two-color/pump–probe) is lacking. Isolated models require physical parameter inputs that disagree with expected values by at least an order of magnitude. These non-physical models undermine the ability to predict non-linear signal strengths under untested conditions and thereby limit the potential to optimize the sensitivity of non-linear spectroscopies and to expand their analytical applications (e.g., new analytes and/or buffer gases, changes in cavity free-spectral-range, changes in intracavity powers or wavelengths, and accurate investigation of physical phenomena). In this study, we derive bath-coupled models for gaseous pump–probe spectroscopy by application of the quantum Lindblad equation and detailed balance. Bath-coupled models are shown to fit data consistently across variations in intensity and agree with all physically expected values.

Cavity ring-down spectroscopy↗

A Physics-Based Analytical Model for Perovskite Solar Cells

Perovskites are promising next-generation absorber materials for low-cost and high-efficiency solar cells. Although perovskite cells are configured similar to the classical solar cells, their operation is unique and requires development of a new physical model for characterization, optimization of the cells, and prediction of the panel performance. Here, we develop such a physicsbased analytical model to describe the operation of different types of perovskite solar cells, explicitly accounting for nonuniform generation, carrier selective transport layers, and voltage-dependent carrier collection. Lastly, the model would allow experimentalists to characterize key parameters of existing cells, understand performance bottlenecks, and predict performance of perovskite-based solar panel—the obvious next step to the evolution of perovskite solar cell technology.

14 SOLAR ENERGY↗

Modeling of time-lapse seismic monitoring using CO 2 leakage simulations for a model CO 2 storage site with realistic geology: Application in assessment of early leak-detection capabilities

Time-lapse surface seismic surveys have been widely used at carbon sequestration sites for site characterization, monitoring subsurface CO 2 plume migration, and detecting potential CO 2 leakage from a storage reservoir. Monitoring in the first permeable unit directly above the primary seal is important for early detection of CO 2 leakage. Forward modeling of time-lapse seismic data can be used to assess the utility of the seismic method for CO 2 leakage detection. We develop a workflow for forward modeling of time-lapse seismic data, including constructing seismic velocity models using flow simulation outputs, modeling of pre-stack and post-stack synthetic seismic data following seismic data processing sequence and analysis of processed synthetic time-lapse seismic data. We apply the forward modeling and analysis workflow to assessing the detectability and the earliest detection time of seismic monitoring using the hypothetical CO 2 leakage scenarios for a model geologic storage site with realistic geology. We then derive the detection thresholds using the simulated normalized root-mean-square (NRMS) differences for the no-leakage case at a range of signal-to-noise ratios, representing the background noise levels in seismic data. We then compare NRMS differences triggered by the CO 2 leakage to the detection thresholds at each time step to quantify the detectability and the earliest detection time of seismic monitoring. We analyze the effects of the acquisition parameters and elastic parameters on the produced synthetic seismic data and earliest detection time. Our modeling results indicate that high signal-to-noise ratio is needed to detect the CO 2 leakage at the model site. Minimizing the background noise in seismic data is crucial for improving the detectability of the seismic method. Increasing the shot density or increasing the dominant frequency of the source wavelet is likely to increase the possibility of the leakage detection and reduce the time needed for the detection. The elastic parameters used in the rock physics modeling have significant effects on the resultant seismic velocity models and synthetic seismic data, highlighting their critical roles in understanding and interpreting time-lapse seismic reflection data associated with CO 2 monitoring, verification and accounting activities.

58 GEOSCIENCES↗

Interpolations of nuclide-specific scattering kernels generated with Serpent

The neutron group-to-group scattering cross section is an essential input parameter for any multi-energy group physics model. However, if the analyst prefers to use Monte Carlo transport to generate group constants this data is difficult to obtain for a single species of a material. Here, the Monte Carlo code Serpent was modified to return the group transfer probabilities on a per-nuclide basis. This ability is demonstrated in conjunction with an essential physics reactor model where cross section perturbations are used to dynamically generate reactor state dependent group constants via interpolation from pre-computed libraries. The modified version of Serpent was therefore verified with three interpolation cases designed to test the resilience of the interpolation scheme to changes in intra-group fluxes. For most species, interpolation resulted in errors of less than 5% of transport-computed values. For important scatterers, such as {sup 1}H, errors less than 2% were observed. For nuclides with high errors ( > 10%), the scattering channel typically only had a small probability of occurring. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A measurement of the calorimeter response to single hadrons and determination of the jet energy scale uncertainty using LHC Run-1 pp-collision data with the ATLAS detector

A measurement of the calorimeter response to isolated charged hadrons in the ATLAS detector at the LHC is presented. This measurement is performed with 3.2 nb –1 of proton–proton collision data at √s = 7 TeV from 2010 and 0.1 nb –1 of data at √s = 8 TeV from 2012. A number of aspects of the calorimeter response to isolated hadrons are explored. After accounting for energy deposited by neutral particles, there is a 5% discrepancy in the modelling, using various sets of Geant4 hadronic physics models, of the calorimeter response to isolated charged hadrons in the central calorimeter region. The description of the response to anti-protons at low momenta is found to be improved with respect to previous analyses. The electromagnetic and hadronic calorimeters are also examined separately, and the detector simulation is found to describe the response in the hadronic calorimeter well. The jet energy scale uncertainty and correlations in scale between jets of different momenta and pseudorapidity are derived based on these studies. The uncertainty is 2–5% for jets with transverse momenta above 2 TeV, where this method provides the jet energy scale uncertainty for ATLAS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of cross sections for production of a $Z$ boson in association with a flavor-inclusive or doubly $b$-tagged large-radius jet in proton-proton collisions at $\sqrt{s}$ = $13$ $\mathrm{TeV}$ with the ATLAS experiment

We present measurements of cross sections for production of a leptonically decaying $Z$ boson in association with a large-radius jet in 13 TeV proton-proton collisions at the LHC, using 36 fb –1 of data from the ATLAS detector. Integrated and differential cross sections are measured at particle level in both a flavor inclusive and a doubly $b$-tagged fiducial phase space. The large-radius jet mass and transverse momentum, its kinematic relationship to the Z boson, and the angular separation of $b$-tagged small-radius track jets within the large-radius jet are measured. This measurement constitutes an important test of perturbative quantum chromodynamics in kinematic and flavor configurations relevant to several Higgs boson and beyond-Standard-Model physics analyses. The results highlight issues with modeling of additional hadronic activity in the flavor-inclusive selection, and a distinction between flavor-number schemes in the $b$-tagged phase space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models.

In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model’s input parameters. Here we develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model’s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier–Stokes) flow simulator, using shock-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow.

42 ENGINEERING↗