Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “computational physics applications”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,045 records · Page 58

Self-Consistent Relativistic Electron Scattering using the Sherlock Scattering Model for X-ray Diagnostics

We present on a new, self-consistent, arbitrary-temperature Romberg integration scheme for modeling electron scattering in materials in a LANL Lagrangian Shock Hydro (LSH) code. Electron beam-target interactions are fundamental to a wide range of scientific and technological applications. When high-energy electron beams hit their target, they may scatter, deposit energy, or ionize the source. These processes govern the behavior and outcomes in nanotechnology manufacturing, electron microscopy, and modern X-ray diagnostics. Simulating these interactions is essential for interpreting experimental results, predicting material responses, and designing efficient tools and experiments. At Los Alamos, this is done using a LSH code, which is a multi-dimension, multi-material, massively parallel, multi-physics code used to simulate applications from asteroid impacts to electron beam interactions. By effectively and efficiently modeling the way that electrons scatter from the beam we can bolster these simulations and more accurately predict experimental outcomes. The model currently implemented in the LSH of interest is based on work by Papp and does not self-consistently preserve momentum in the slightly relativistic regime; here we adopt a model proposed by Braams and Karney and implement a Romberg integration scheme to compute the diffusion tensor. In this paper we will provide background on the Braams-Karney diffusion tensor as well as the Romberg integration scheme we employed to numerically solve for it. We will show that our integration scheme is accurate in solving for the set of scalar potentials used to re-express the diffusion tensor in differential form, and in solving for the diffusion coefficients in the larger LSH code. By using this diffusion tensor rather than the existing Papp one, and numerically integrating it with a Romberg method, we produce much more accurate, self-consistent results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tale of Two Domains: Cyber - Physical

As devices and systems continue to modernize and adopt integrated circuits, the use of cyber technology to deploy an application is the expectation. This deployment through cyber assets brings new cyber risk and cybersecurity is the practice of managing this risk. Cyber-risk is constantly changing due to the speed of technology advancement and the changing quality of the adversary. Cyber-Informed Engineering (CIE) mitigates cyber-risk through engineering controls where as the traditional practice of cybersecurity mitigates cyber-risk through cybersecurity controls. By clearly defining the cyber-physical boundary, engineering controls and cybersecurity controls can clearly demonstrate their complementary nature to provide layered defenses and successfully mitigate cyber-risk through independent controls. In this paper, a layered model of device decomposition of the the cyber-physical boundary is presented to provide clarity where engineering controls are used to reduce cyber-risk within the physics, functional materials, electronic, or integrated circuit layers and where cybersecurity controls are used to reduce cyber-risk within the machine code and application layers. By implementing both traditional cybersecurity controls and engineering controls, a more holistic approach to cybersecurity is achieved in protecting modern devices and systems, as well as a clear awareness in identifying, documenting, and authorizing the system’s cybersecurity protection scheme is achieved.

42 - ENGINEERING↗

Demonstration of a new unstructured mesh IMC x-ray transport capability in LAP codes

The Advanced Simulation and Computing (ASC) Transport project’s Jayenne Implicit Monte Carlo (IMC) transport library now includes an unstructured mesh capability and is available in a Lagrangian Applications Project (LAP) code. In this presentation, we discuss recent work by the LAP and Transport projects that provides an IMC transport capability for radiation hydrodynamics in the Lagrangian frame. Verification problems testing the new capabilities have been simulated and analyzed, i.e. Marshak wave, Mach 45, Su-Olsen, picket fence, and crooked pipe, both in one and two dimensions. We also present results on two stretch goal problems: a simplified COAX high energy density physics experiment and a supernova shock simulation. Finally, we identify current limitations and future work needed to bring a full capability to the user community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of a BlueCRAB/MELCOR Framework for Supporting Realistic Mechanistic Source Term Calculations in Microreactors

Efforts are currently underway to deploy microreactor modeling and simulation tools to better support vendors and regulatory authorities in submitting and reviewing licensing applications. In particular, the Nuclear Regulatory Commission is expected to rely on the Comprehensive Reactor Analysis Bundle (BlueCRAB) multiphysics toolset in performing design- and beyond-design-basis accident analyses. In addition, the Nuclear Regulatory Commission has been using the MELCOR code to estimate mechanistic source terms during accidents. As MELCOR relies on isotopic inventory and reactor temperature/power evolution profiles during accident conditions—all of which can theoretically be obtained from BlueCRAB—the ultimate goal of this activity is to establish a common BlueCRAB-MELCOR framework. However, prior to the present research, BlueCRAB had never been used to calculate such quantities of interest at the full-core level. While there are many Monte Carlo (MC) codes capable of computing such quantities of interest, they are unable to readily account for multiphysics feedback. BlueCRAB allows for the coupling of different physics codes together to perform multiphysics-informed calculations. Therefore, the purpose of this fiscal year 2023 work is to investigate the feasibility and challenges of performing such calculations within BlueCRAB so as to generate the data that MELCOR relies on. To demonstrate the methodology, the proposed workflow was applied to a prototypical heat pipe-cooled microreactor model. To predict isotopic concentrations (taking into account the ac- cumulation of fission products during operation), the necessary microscopic cross sections were generated via OpenMC and tabulated with respect to temperature and burnup. Next, a recently developed capability in Griffin (the reactor physics application in BlueCRAB) was used to convert the OpenMC output format into the ISOXML format used by Griffin. A multiphysics microscopic depletion calculation that involved performing a coupled full-core, heterogeneous neutron trans- port and thermal calculation at each depletion step was conducted to deplete the core to end of life (EOL) conditions so as to provide both isotopics and the initial condition for the transient calculation. Following a brief null-transient to verify that the initial condition had been properly restarted and was indeed in thermal equilibrium, a heat pipe failure transient was simulated. Thus, the entire workflow of using BlueCRAB to generate MELCOR inputs, from cross-section generation to producing isotopic inventory and power/temperature evolution profiles during transients, is demonstrated. This report also details the identified gaps in the workflow and how they were (for the most part) addressed. Future work should focus on directly including MEL- COR into the workflow by performing a MELCOR calculation using the BlueCRAB-generated input data. In addition, the heat pipe reactor design should be improved so as to reflect more prototypical burnup characteristics at EOL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Analyzing Production Rate and Carbon Utilization Trade-offs in CO 2 RR Electrolyzers

Carbon utilization is a crucially important performance characteristic of CO 2 electrolyzers; however, applications of simple and accurate descriptive models to experimental data on this topic are currently lacking. Here, we apply a simple analytical reactor model to parameterize single-pass conversion as a function of feed-gas flow rate and show that it captures a wide body of experimental data in the literature exceptionally well. In doing so, we demonstrate that this simple conceptual approach can characterize progress and capture recent innovations in reactor design. To validate the extracted parameters, we employ a well-established comprehensive model to confirm that the results agree with physical expectations. Lastly, we explore the implications of the descriptive model by examining the inherent trade-off between single-pass conversion efficiency and reactor productivity. Understanding such trade-offs is crucially important for advancing this electrolyzer technology toward commercial applications.

36 MATERIALS SCIENCE↗

Summer Internship Project: Set Topology [Slides]

Why a Set Topology? 1. Expand the array of tools given to physicists, educators, and students. 2. Through usages of PIC, MPM, and Monte Carlo. 3. My work at LANL was specified to handle requirements for the usage of MPM with FleCSI. 4. What we want it to do - phase change, simulating plasma, and other Multiphysics applications. 5. In FleCSI we already have mesh structures, we needed a way to represent those particles and certain behavior's of these particles that clients desire.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Computationally designed coiled coil ‘bundlemers’ as model colloidal nanoparticles for solution assembly and materials design (Final Report)

As a collaborative team at the University of Delaware and the University of Pennsylvania, Kloxin, Pochan and Saven designed new biomimetic nanomaterials de novo, leveraging a variety of complementary areas of expertise: computational design of biopolymers (Saven at the University of Pennsylvania), and synthesis and characterization (Kloxin and Pochan at the University of Delaware). Overall activities included: sequence-specific peptide synthesis; covalent crosslinking; noncovalent assembly; site-specific functionalization; and nanostructural characterization using electron microscopy and solution-phase (x-ray and neutron) scattering. Using natural and non-natural amino acids, the team created modular, functional peptide building blocks for elaboration of new nanostructured materials. Ultimately, the development of robust peptide-based, building blocks provides tools for researchers to readily produce complex nanomaterial structures in a wide range of applications. The project had three, interconnecting goals in an effort to provide the broader scientific community with a new peptide-based paradigm for materials design and characterization. First, we further developed the coiled-coil bundle-based toolbox (otherwise known as the ‘bundlemer’ toolbox) via computational design with experimental bundle assembly verification. Second, we developed new uses of covalent interactions, in addition to desired physical (noncovalent) interactions, to assemble bundlemers into 1-D polymer chains with targeted chain rigidity, length, and dispersity. Thirds, we used the above designs to experimentally realize (physical or covalent) polymers to target the creation of liquid crystals or to realize interparticle assembly into nanoporous lattices. The close integration of the three groups was instrumental in success of the biomolecular materials design, formation, and understanding for future designs.

36 MATERIALS SCIENCE↗

Floquet engineering of tilted and gapped Dirac bandstructure in 1T$$^\prime$$-MoS$$_2$$

Abstract We have developed a rigorous theoretical formalism for Floquet engineering, investigating, and subsequently tailoring most crucial electronic properties of 1T $$^\prime$$ ′ -MoS $$_2$$ 2 by applying an external high-frequency dressing field within the off-resonance regime. It was recently demonstrated that monolayer semiconducting 1T $$^\prime$$ ′ -MoS $$_2$$ 2 exhibits tunable and gapped spin- and valley-polarized tilted Dirac bands. The electron-photon dressed states depend strongly on the polarization of the applied irradiation and reflect a full complexity of the low-energy Hamiltonian for non-irradiated material. We have calculated and analyzed the properties of the electron dressed states corresponding to linear and circular polarization of a dressing field by focusing on their symmetry, anisotropy, tilting, direct and indirect band gaps. Circularly polarized dressing field is known for transition into a new electronic state with broken time-reversal symmetry and a non-zero Chern number, and therefore, the combination of these topologically non-trivial phases and transitions between them could reveal some truly unique and previously unknown phenomena and applications. We have also computed and discussed the density of states for various types of 1T $$^\prime$$ ′ -MoS $$_2$$ 2 materials and its modification in the presence of a dressing field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Inherent stochasticity during insulator–metal transition in VO 2

Vanadium dioxide (VO 2 ), which exhibits a near-room-temperature insulator–metal transition, has great potential in applications of neuromorphic computing devices. Although its volatile switching property, which could emulate neuron spiking, has been studied widely, nanoscale studies of the structural stochasticity across the phase transition are still lacking. In this study, using in situ transmission electron microscopy and ex situ resistive switching measurement, we successfully characterized the structural phase transition between monoclinic and rutile VO 2 at local areas in planar VO 2 /TiO 2 device configuration under external biasing. After each resistive switching, different VO 2 monoclinic crystal orientations are observed, forming different equilibrium states. We have evaluated a statistical cycle-to-cycle variation, demonstrated a stochastic nature of the volatile resistive switching, and presented an approach to study in-plane structural anisotropy. Furthermore, our microscopic studies move a big step forward toward understanding the volatile switching mechanisms and the related applications of VO 2 as the key material of neuromorphic computing.

36 MATERIALS SCIENCE↗

Accurate real space iterative reconstruction (RESIRE) algorithm for tomography

Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at https://zenodo.org/record/7273314.

97 MATHEMATICS AND COMPUTING↗

Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data

Abstract Artificial intelligence (AI) and machine learning (ML) have been increasingly used in materials science to build predictive models and accelerate discovery. For selected properties, availability of large databases has also facilitated application of deep learning (DL) and transfer learning (TL). However, unavailability of large datasets for a majority of properties prohibits widespread application of DL/TL. We present a cross-property deep-transfer-learning framework that leverages models trained on large datasets to build models on small datasets of different properties. We test the proposed framework on 39 computational and two experimental datasets and find that the TL models with only elemental fractions as input outperform ML/DL models trained from scratch even when they are allowed to use physical attributes as input, for 27/39 (≈ 69%) computational and both the experimental datasets. We believe that the proposed framework can be widely useful to tackle the small data challenge in applying AI/ML in materials science.

36 MATERIALS SCIENCE↗

Broadband coherent XUV light from e − / e + microbunching in an intense laser pulse

Attosecond pulses of coherent extreme ultraviolet (XUV) light are instrumental for investigating subatomic dynamics and can be produced using a free-electron laser (FEL). It has been suggested that an optical FEL, which employs a laser pulse in place of a conventional undulator, could enable a dramatically more compact implementation of such a light source. Yet, the high electron density and subsequent high emittance implied by an optical FEL makes this concept challenging to realize with an electron beam. There has been impressive progress in recent years producing collimated dense and relativistic beams of electrons and positrons in the laboratory. As we demonstrate here, the inherent stability of a quasi-neutral electron-positron beam mitigates Coulomb expansion, and renders it a promising alternative source of coherent light. Specifically, we show via computer simulations that broadband coherent light in the XUV domain, which takes the form of 8-as pulses at 92-as intervals, can be generated by microbunching of relativistic electrons and positrons in a laser pulse. This process occurs over a sub-millimeter length scale, enabling the development of light sources which are orders-of-magnitude more compact than existing sources, with potential applications in physics, chemistry, biology, and industry.

47 OTHER INSTRUMENTATION↗

Physics of E × B discharges relevant to plasma propulsion and similar technologies

This paper provides perspectives on recent progress in understanding the physics of devices in which the external magnetic field is applied perpendicular to the discharge current. This configuration generates a strong electric field that acts to accelerate ions. The many applications of this set up include generation of thrust for spacecraft propulsion and separation of species in plasma mass separation devices. These “E × B” plasmas are subject to plasma–wall interaction effects and to various micro- and macroinstabilities. In many devices we also observe the emergence of anomalous transport. This perspective presents the current understanding of the physics of these phenomena and state-of-the-art computational results, identifies critical questions, and suggests directions for future research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Basis light-front quantization for a chiral nucleon-pion Lagrangian

We present the first application of the basis light-front quantization method to a simple chiral model of the nucleon-pion system as a relativistic bound state for the physical proton. In this work, the light-front mass-squared matrix of the nucleon-pion system is obtained within a truncated basis. The mass and the corresponding light-front wave function (LFWF) of the proton are computed by numerical diagonalization of the resulting mass-squared matrix. With the boost-invariant LFWF, we calculate the probability density distribution of the pion's longitudinal momentum fraction and the Dirac form factor of the proton.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A massively parallel time-domain coupled electrodynamics–micromagnetics solver

We present a high-performance coupled electrodynamics–micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain approach for Maxwell’s equations to a magnetization model described by the Landau–Lifshitz–Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59×) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.

97 MATHEMATICS AND COMPUTING↗

Multi-fidelity modeling to predict the rheological properties of fiber suspensions

Unveiling the rheological properties of fiber suspensions is of paramount interest to many industrial applications like biofuel production. The 3D numerical simulations of the suspension of fibers are often computationally expensive and time-consuming. Machine learning methods such as neural networks can simplify the prediction of rheological behavior; however, they require a relatively large training data set. Multi -fidelity models, which combine high-fidelity data from numerical simulations and less expensive lower fidelity data from resources such as simplified physical equations, can lead to optimized predictions. Here, we focus on a neural network with two levels of fidelity, i.e., high and low fidelity networks. To produce high-fidelity data, we perform direct numerical simulations to model the fibers as one-dimensional inextensible slender bodies that obey the Euler- Bernoulli beam equation. The Navier-Stokes equations govern the suspended fluid, and an immersed boundary method is used to couple the fluid and solid motion. The low-fidelity data is produced by using constitutive equations. Noticeable improvements have been observed in the accuracy of predicting the rheological behavior when a multi-fidelity network is used compared to the single-fidelity network.

Boodaghidizaji, Miad↗

FENIX: Towards a Fully Integrated Multiphysics Framework for Plasma Facing Component Modeling

Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗