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At least 541 records · Page 30

Machine learning-enabled multiscale modeling of mechanical deformation of aluminum and Al-SiC nanocomposites

A machine learning-enabled multiscale framework is developed for modeling the mechanical response of both pure metal and nanoparticle-reinforced metal matrix nanocomposites (MMNCs). Using aluminum–silicon carbide (Al-SiC) as an example MMNC, atomistic simulations reveal three distinct deformation mechanisms (i.e., defect-free, dislocation-based, and interface separation) governed by the interfaces between the Al matrix and SiC nanoparticles. As compared with single crystal Al, the lattice undergoes a more abrupt failure once the dislocation network becomes extensive and void nucleation initiates, whereas in Al-SiC, nanoparticle interfaces enable a more gradual progression of damage. These mechanisms are captured through a combined classification-regression neural network surrogate model that bridges atomic-scale insights with continuum-scale finite element analysis. Machine learning-enabled multiscale modeling of pure Al accurately predicted strain localization and confirmed by in-situ scanning electron microscopic tensile testing on perforated Al specimens. This study underscores the promise of integrating physics-informed machine learning with hierarchical modeling to capture the interface dominated phenomena and guide the design of advanced MMNCs.

Al-SiC↗

E2 rotational invariants of 0$^{+}_{1}$ and 2$^{+}_{1}$ states for 106 Cd: The emergence of collective rotation

The collective structure of 106 Cd is elucidated by multi-step Coulomb excitation of a 3.849 MeV/A beam of 106 Cd on a 1.1 mg/cm 2 208 Pb target using GRETINA-CHICO2 at ATLAS. Fourteen E2 matrix elements were obtained. The nucleus 106 Cd is a prime example of emergent collectivity that possesses a simple structure: it is free of complexity caused by shape coexistence and has a small, but collectively active number of valence nucleons. This work follows in a long and currently active quest to answer the fundamental question of the origin of nuclear collectivity and deformation, notably in the cadmium isotopes. The results are discussed in terms of phenomenological models, the shell model, and Kumar-Cline sums of E2 matrix elements. The < 0$^{+}_{2}$ ||E2||2$^{+}_{1}$ > matrix element is determined for the first time, providing a total, converged measure of the electric quadrupole strength, < Q 2 >, of the first-excited 2$^{+}_{1}$ level relative to the 0$^{+}_{1}$ ground state, which does not show an increase as expected of harmonic and anharmonic vibrations. Strong evidence for triaxial shapes in weakly collective nuclei is indicated; collective vibrations are excluded. This is contrary to the only other cadmium result of this kind in 114 Cd by C. Fahlander et al., Nucl. Phys. A485, 327 (1988), which is complicated by low-lying shape coexistence near midshell.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics‐informed in vitro – in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics‐informed bottom‐up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine‐trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle‐out optimization of mechanistic models.

Scotcher, Daniel↗

Tensor network simulations of quasi-GPDs in the massive Schwinger model

Generalized parton distribution functions (GPDs) are off-diagonal light-cone matrix elements that encode the internal structure of hadrons in terms of quark and gluon degrees of freedom. In this work, we present the first nonperturbative study of quasi-GPDs in the massive Schwinger model, quantum electrodynamics in 1+1 dimensions (QED 2 ), within the Hamiltonian formulation of lattice field theory. Quasidistributions are spatial correlation functions of boosted states, which approach the relevant light-cone distributions in the luminal limit. Using tensor networks, we prepare the first excited state in the strongly coupled regime and boost it to close to the light-cone on lattices of up to 400 lattice sites. We compute both quasiparton distribution functions and, for the first time, quasi-GPDs, and study their convergence for increasingly boosted states. In addition, we perform analytic calculations of GPDs in the two-particle Fock-space approximation and in the Reggeized limit, providing qualitative benchmarks for the tensor network results. Our analysis establishes computational benchmarks for accessing partonic observables in low-dimensional gauge theories, offering a starting point for future extensions to higher dimensions, non-Abelian theories, and quantum simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Model-based Cyber-attack Detection for Voltage Source Converters in Island Microgrids

With the upgrading of communication and control in microgrids, cyber threats on the power converters are increasing. Here, in this paper, a novel model-based cyber-attack detection methodology is proposed for each voltage source converter in microgrids. The Harmonics State Space Matrix (H-Matrix) is used to build the closed-loop transfer function, providing model-based estimation with the grid voltage and control reference. Then, the space phase model (SPM) is used to calculate residual to detect cyber-attacks in voltage source converter (VSC). As controller and converter parameters are included in the H-matrix, the proposed method also could detect cyber-attacks when voltage fluctuation occurs in the grid. To verify the feasibility of the proposed method, several attacks targeting VSC in an islanded microgrid are simulated in MATLAB. Simulation and detection results are introduced to demonstrate the resilience and feasibility of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Aligned yet large dipoles: a SMEFT study

We study a non-universal flavor scenario at the level of the Standard Model Effective Field Theory, according to which the matrix of Wilson coefficients cuW of an up-type electroweak quark dipole operator is aligned with the up-type Yukawa coupling. Such an alignment usually follows from the assumption of Minimal Flavor Violation (MFV), away from which we step by allowing the entries of cuW to be sizable along the first quark generations. A particular example, which we refer to as “inverse hierarchy MFV”, features Wilson coefficients inversely proportional to quark masses, and arises from BSM models respecting MFV and containing heavy fields that replicate the mass hierarchy of SM quarks. We then analyze the phenomenology driven by cuW at colliders and at lower-energy flavor experiments. We show that precision measurements of the process pp → Wh → γγℓν at FCC-hh could set an upper bound on |cuW| ≲ O (10 -2 )(Λ/TeV) 2 , with Λ the cutoff of the effective field theory. This bound is an order of magnitude stronger than the existing LHC bounds. Moreover, we estimate that Wh → b$\overline{b}$ℓν at HL-LHC could also give competitive bounds. In the low-energy regime, we consider bounds arising from rare kaon decays, which turn out to be loose, |c$_{uW}^{11}$ | < O (1)(Λ/TeV) 2 . We finally demonstrate that our flavor and operator assumptions can be derived from a weakly-coupled UV model, which we choose to simultaneously illustrate the UV origin of inverse hierarchy MFV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Parametrizations of the spin density matrix

Highlights: • Proposed two methods for parametrizing the SDM of spinning, unstable particles. • All non-negativity conditions fulfilled; adaptability to various constraints. • First method: based on a theorem; applicable in a simple and flexible way. • Second method: particularly suitable for especial conditions. • Applications: two of them interesting in the search for new physics. We propose for the spin density matrix two parametrizations which automatically fulfill the non-negativity conditions, without setting any bound on the parameters. The first one relies on a theorem, that we prove, and it is rather simple and easily adaptable to some specific reactions, where, for example, parity is conserved or angular momentum conservation entails selection rules. Moreover, in the case when the rank is less than the order of the density matrix, we show how to improve the fits to the data, either by implementing previous suggestions, or by elaborating an alternative method, for which we prove a second theorem. Our second parametrization is a variant of previous treatments, it appears suitable for some particular processes. Moreover, we discuss about the possibility of inferring the elements of the density matrix from the differential decay width. Last, we illustrate various examples of current interest, both in strong and weak decays; some of them may be helpful in the investigation of physics beyond the standard model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Novel method to control explosive shock sensitivity: A mesoscale study to understand the effect of thermally expandable microsphere (TEM) inclusions in high explosives (HE) microstructure

When the void content and/or void structure of a high explosive (HE) is altered by some means (i.e., bulk heating or mechanical damage), the shock initiation behavior of the material changes. The ability to precisely predict the change in shock sensitivity after an HE has undergone microstructural changes is a crucial capability in multi-scale reactive flow models. Here, we utilize thermally expandable microspheres (TEMs) as a dopant in a polymer bonded explosive (PBX) matrix to alter the shock initiation properties in a controlled fashion. Here, using a mesoscale modeling approach, we evaluated how a single TEM (before and after thermal expansion) behaves under shock compression, as well as how the matrix PBX in the direct vicinity of the TEM is affected. We first examined the effect of an unexpanded TEM in the explosive matrix and found that its presence does not significantly perturb the bulk flow and by extension will not affect bulk sensitivity. Next, we examined the effect of an expanded TEM and found that its presence significantly perturbs the flow via hydrodynamic jetting, which causes a secondary shock wave with a strength that exceeds that of the incident wave. Finally, we showed that this secondary shock interacts with the downstream porosity to ignite a larger fraction of the overall pore volume, commensurate with the secondary shock strength and the affected volume, increasing the global (bulk) shock sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Performance Analysis and Optimal Node-aware Communication for Enlarged Conjugate Gradient Methods

Krylov methods are a key way of solving large sparse linear systems of equations but suffer from poor strong scalability on distributed memory machines. Furthermore, this is due to high synchronization costs from large numbers of collective communication calls alongside a low computational workload. Enlarged Krylov methods address this issue by decreasing the total iterations to convergence, an artifact of splitting the initial residual and resulting in operations on block vectors. In this article, we present a performance study of an enlarged Krylov method, Enlarged Conjugate Gradients (ECG), noting the impact of block vectors on parallel performance at scale. Most notably, we observe the increased overhead of point-to-point communication as a result of denser messages in the sparse matrix-block vector multiplication kernel. Additionally, we present models to analyze expected performance of ECG, as well as motivate design decisions. Most importantly, we introduce a new point-to-point communication approach based on node-aware communication techniques that increases efficiency of the method at scale.

97 MATHEMATICS AND COMPUTING↗

Pulse-level noisy quantum circuits with QuTiP

The study of the impact of noise on quantum circuits is especially relevant to guide the progress of Noisy Intermediate-Scale Quantum (NISQ) computing. In this paper, we address the pulse-level simulation of noisy quantum circuits with the Quantum Toolbox in Python (QuTiP). We introduce new tools in qutip-qip, QuTiP's quantum information processing package. These tools simulate quantum circuits at the pulse level, leveraging QuTiP's quantum dynamics solvers and control optimization features. We show how quantum circuits can be compiled on simulated processors, with control pulses acting on a target Hamiltonian that describes the unitary evolution of the physical qubits. Various types of noise can be introduced based on the physical model, e.g., by simulating the Lindblad density-matrix dynamics or Monte Carlo quantum trajectories. In particular, the user can define environment-induced decoherence at the processor level and include noise simulation at the level of control pulses. We illustrate how the Deutsch-Jozsa algorithm is compiled and executed on a superconducting-qubit-based processor, on a spin-chain-based processor and using control optimization algorithms. We also show how to easily reproduce experimental results on cross-talk noise in an ion-based processor, and how a Ramsey experiment can be modeled with Lindblad dynamics. Finally, we illustrate how to integrate these features with other software frameworks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hydrolytic Aging in Rubber-Like Materials: A Micro-Mechanical Approach to Modeling

Abstract The effect of hydrolytic aging on mechanical responses of Rubber likes materials, in particular, Mullins effect and the permanent set has been modeled. Hydrolytic aging is considered as the result of the competition between two phenomena (1) chain scission and (2) cross-link scission/reformation. Both phenomena were modeled and thus, the strain energy of the polymer matrix is written with respect to three independent mechanisms; i) the shrinking original matrix which has not been attacked by water, ii) conversion of the first network to a new network due to the reduction of the crosslinks, and iii) energy loss from network degradation due to water attacks to ester groups. The model is validated with respect to a set of experimental data. Besides accuracy, the simplicity and few numbers of fitting parameters make the model a good choice for further implementations.

Bahrololoumi, Amir↗

Simulation of Deuterium Oxidation in a Room with a Fire

A series of experiments where deuterium was released in trace amounts into a room with a fire were performed at Sandia National Laboratories. This report describes the corresponding effort to model the test series using SIERRA/FUEGO. The objective of this modeling effort was to produce a simulation test matrix that can be utilized to help interpret the corresponding experiments and be used to assess the credibility of using the SIERRA/FUEGO simulations as a surrogate for real tritium reaction data for mock fire and release studies. The simulations assessed multiple configurations of fire size and location and overall found that there was low conversion of deuterium to oxidized deuterium. There are some notable differences between the simulation predictions and the experimental results, such as the simulations generally predicting higher amounts of deuterium conversion compared to the experiment. A strategy to address modeling uncertainties and unknowns is also given in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Embedding PbS Quantum Dots (QDs) in Pb-Halide Perovskite Matrices: QD Surface Chemistry and Antisolvent Effects on QD Dispersion and Confinement Properties

Hybrid materials of metal chalcogenide colloidal quantum dots (QDs) embedded in metal halide perovskites (MHPs) have led to composites with synergistic properties. Here, we investigate how QD size, surface chemistry, and MHP film formation methods affect the resulting optoelectronic properties of QD/MHP “dot-in-matrix” systems. We monitor the QD absorption and photoluminescence throughout synthesis, ligand exchange, and transfer into the MHP ink, and we characterize the final QD/MHP films via electron microscopy and transient absorption. In addition, we are the first to globally map how PbS QDs are distributed on the micrometer scale within these dot-in-matrix systems, using three-dimensional (3D) tomography time-of-flight secondary ion mass spectrometry. The surface chemistry imparted during synthesis directly affects the optical properties of the dot-in-matrix composites. Pb-halide passivation leads to QD/MHP dot-in-matrix samples with optical properties that are well-described by a theoretical model, based on a Type I finite-barrier heterostructure between the PbS QD and the MHP matrix. Samples without Pb-halide passivation show complicated size-dependent behavior, indicating a transition from a Type I heterostructure between the PbS QD wells and MHP barriers for small-sized QDs to PbS QDs that are electronically decoupled from the MHP matrix for larger QDs. Furthermore, the choice in perovskite antisolvent crystallization method leads to a difference in the spatial QD distribution within the perovskite matrix, differences in carrier lifetime, and photoluminescence shifts of up to 180 meV for PbS in methylammonium lead iodide. This work establishes an understanding of such emerging synergistic systems relevant for technologies such as photovoltaics, infrared emitters and detectors, and other unexplored technological applications.

92 SC - Basic Energy Sciences (BES) (SC-22)↗

Image Characterization of Reactions Generated by an Aeroengine Micromixing Injector for Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blend

An aeroengine micromixing injector, originally designed for lean direct injection of jet fuel, was adapted to work with hydrogen, natural gas, and any blend in between. The ultimate goal of the design was to achieve low NOx emissions when operated on pure hydrogen; to better characterize its performance, flame imaging diagnostics was implemented. Three types of cameras mounted parallel to the injector base and pointing towards the quartz combustor cylinder with the same angle were operated simultaneously: Nikon D90, Dynacolor FB-N9-U, and Phantom v7.1, to capture the visible spectrum, OH* chemiluminescence, and dynamic behavior of the flames, respectively. The current work also includes the overlapping of visible spectrum and OH* chemiluminescence, as an effort to qualitatively define the heat release over the flame area, i.e., UV over visible domain. Additionally, a z-type schlieren configuration was employed to reinforce the presence of some small-scale details occurring near the injector outlet ports. Using the airbox pressure drop, preheat temperature, fuel composition and flame temperature as the factors of study, a Box Behnken model was designed yielding into a 16-points matrix for the operability region, at atmospheric pressure. The main responses were extracted from the OH* images, because of its correlation with the flame heat release, these being the flame area and its average brightness, the heat release area and its center of gravity and leading edge. To assess the importance of the main factors and their interactions, an analysis of variance (ANOVA) was performed for each response, considering as significant each contributor with a p-value below 0.05. For these five responses it was found that all four main factors need to be included into the model (most of them because its own significance, others to ensure the model hierarchy), as well as some common interactions as the preheat and flame temperatures or pressure drop and fuel composition, and quadratic terms from fuel composition or flame temperature. Three of the five models presented R2 and coefficient of variance (C.V.) indicators around 0.97 and 5%, respectively; the leading edge ANOVA yielded into R2=0.78 and C.V.=18.88%; and the heat release area showed R2=0.91 and C.V.=24.13%. Lastly, the confinement ratio effect of the combustor over the flame structure was quantified, for three different conditions: the original 80 mm inner diameter and 200 mm length cylinder was compared against a shorter 150 mm tube (same inner diameter) and a narrower 47 mm inner diameter one (same 200 mm length). The length had a smaller effect than the inner diameter, even though both factors were not strong enough to make a significant deviation on most of the flame parameters: the difference was within the repeatability margin of error for the brightness, flame area, and center of gravity and leading edge of the heat release area.

Imaging diagnostics, flame characterization, OH* c↗

Quantum Melting of Generalized Wigner Crystals in Transition Metal Dichalcogenide Moiré Systems

The generalized Wigner crystal (GWC) is a novel quantum phase of matter driven by further-range interaction at fractional fillings of a lattice. The role of further-range interaction as the driver for the incompressible state is akin to the Wigner crystal. On the other hand, the significant role of commensurate filling is akin to the Mott insulator. Recent progress in simulator platforms presents unprecedented opportunities to investigate quantum melting in the strongly interacting regime through synergy between theory and experiments. However, the earlier theory literature presents diverging predictions. We study the quantum freezing of GWC through large-scale density matrix renormalization group simulations of a triangular lattice extended Hubbard model. We find a single first-order phase transition between the Fermi liquid and the √3×√3 GWC state. Furthermore, the GWC state shows long-range antiferromagnetic 120° Néel order. Our results present the simplest answers to the question of the quantum phase transition into the GWC phase and the properties of the GWC phase.

Density matrix renormalization group↗

Analysis of Unpolarised p+p¿ Photoproduction with the GlueX Experiment

This thesis presents measurements of spin-density matrix elements in unpolarised p+p? photoproduction on a proton target. The dominant resonance contribution to the dipion system is the r(770) meson. Due to the large production cross section for this resonance, a valid comparison can be made between the obtained final results and r(770) spin-density matrix elements measured previously with other experiments. The measurement was performed over the 3:0 ? 11:6 GeV beam energy regime, which is a more extensive energy range than has ever been studied previously for the r(770). Results were obtained by analysing data from the GlueX experiment based at Jefferson Lab. Extended maximum likelihood fits were applied to extract three spin-density matrix elements using Markov chain Monte Carlo based parameter estimations. This was performed using various binning configurations to probe the energy, mass, and four-momentum transfer dependence of the determined physics observables. Spin-density matrix elements are shown to be consistent with the model of s-channel helicity conservation at low ?t. The effects of pomeron and f2 exchanges are clearly visible in the energy dependence of the measured observables. These observations provide valuable insights into the relative strengths of both processes as a function of the photon energy, and may enable theorists to disentangle the f2=P coupling ratio. Spin-density matrix elements are seen to be highly dependent on the reconstructed resonance mass. This observation is likely to be a result of non-resonant S-wave background processes, and emphasises the need for a more detailed model of the p+p? angular distribution that considers all of the competing angular momentum components that contribute to the measured final state. The statistical precision of measurements performed for this thesis surpass what was achievable in previous studies of the r(770) by several orders of magnitude. Studies of the energy and four-momentum transfer dependence, and insights into the effects of non r(770) background contributions provide valuable input for production models. This will help inform the choice of wave-sets used for partial wave analyses, supporting GlueX in its search for exotic hybrid meson states.

Fitches, James↗

A Python Library for Radiance Matrix-based Simulation Control and EnergyPlus Integration

Radiance matrix-based methods enable efficient parametric simulations, allowing users to vary sky conditions, fenestration systems, and other model parameters at a minimal cost to computation. However, the steep learning curve and complex workflow hinder the widespread adoption of matrix-based methods. The frads Python library with a series of command-line tools was developed to automate the entire matrix-based simulation process, lowering entry barriers and reducing human error. Co-simulation between EnergyPlus and Radiance was also enabled using the Python library from EnergyPlus. Key Innovations • Command-line based automation of Radiance matrix-based simulation methods • Python library facilitates broader adoption of Radiance matrix-based simulation methods • Radiance EnergyPlus run-time integration enabling the modeling of advanced control systems Practical Implications The frads library, with associated command-line tools, provides practitioners with the capability to easily adopt and use Radiance matrix-based simulation methods for various daylighting, solar control, and energy-related evaluations. Frads' current form is designed for 1) users familiar with a command-line interface and 2) software developers to integrate the matrix-based methods into existing software packages.

Wang, Taoning↗