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At least 37 records · Page 2

Learning effective SDEs from Brownian dynamic simulations of colloidal particles

We construct a reduced, data-driven, parameter dependent effective stochastic differential equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian dynamics simulations. We use diffusion maps (a manifold learning algorithm) to identify a set of useful latent observables. In this latent space we identify an eSDE using a deep learning architecture inspired by numerical stochastic integrators and compare it with the traditional Kramers–Moyal expansion estimation. We show that the obtained variables and the learned dynamics accurately encode the physics of the Brownian dynamic simulations. We further illustrate that our reduced model captures the dynamics of corresponding experimental data. Further, our dimension reduction/reduced model identification approach can be easily ported to a broad class of particle systems dynamics experiments/models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamical Evolution of Simulated Particles Ejected from Asteroid Bennu

In early 2019, the OSIRIS-REx spacecraft discovered small particles being ejected from the surface of the near-Earth asteroid Bennu. Although they were seen to be ejected at slow speeds, on the order of tens of cm/s, a number of particles were surprisingly seen to orbit for multiple revolutions and days, which requires a dynamical mechanism to quickly and substantially modify the orbit to prevent re-impact upon their first periapse passage. This paper demonstrates that, based on simulations constrained by the conditions of the observed events, the combined effects of gravity, solar radiation pressure, and thermal radiation pressure from Bennu can produce many sustained orbits for ejected particles. Furthermore, the simulated populations exhibit two interesting phenomena that could play an important role in the geophysical evolution of bodies such as Bennu. First, small particles (< 1 cm radius) are preferentially removed from the system, which could lead to a deficit of such particles on the surface. Second, re-impacting particles preferentially land near or on the equatorial bulge of Bennu. Over time, this can lead to crater in-filling and growth of the equatorial radius without requiring landslides.

Jay W. McMahon↗

Simulating single-particle dynamics in magnetized plasmas: The RMF code

The RMF (Rotating Magnetic Field) code is designed to calculate the motion of a charged particle in a given electromagnetic field. It integrates Hamilton’s equations in cylindrical coordinates using an adaptive predictor-corrector double-precision variable-coefficient ordinary differential equation solver for speed and accuracy. RMF has multiple capabilities for the field. Particle motion is initialized by specifying the position and velocity vectors. Here, the six-dimensional state vector and derived quantities are saved as functions of time. A post-processing graphics code, XDRAW, is used on the stored output to plot up to 12 windows of any two quantities using different colors to denote successive time intervals. Multiple cases of RMF may be run in parallel and perform data mining on the results. Recent features are a synthetic diagnostic for simulating the observations of charge-exchange-neutral energy distributions and RF grids to explore a Fermi acceleration parallel to static magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A modified many-body dissipative particle dynamics model for mesoscopic fluid simulation: methodology, calibration, and application for hydrocarbon and water

The many-body dissipative particle dynamics (mDPD) is a prominent mesoscopic multiphase model for fluid transport in mesoconfinement. However, it has been a long-standing challenge for mDPD (and other multiphase-enabled DPD models) to accurately predict real-fluid static and dynamic properties simultaneously. We have developed a modified mDPD model to overcome the issue and a rigorous calibration approach that uses reference data, including experimental and/or molecular dynamics (MD) simulations to parameterise the modified mDPD for real fluids. We choose heptane as a representative example of hydrocarbon in source rocks to demonstrate the model's capability to accurately predict the equation of state (EOS), free surface tension, diffusivity, and viscosity. Our timing test shows that the modified mDPD is 400–500 times faster than its MD counterpart for simulating bulk heptane in equivalent volumes. To further demonstrate the robustness of the model, we revisited the benchmark problem of mesoscopic modelling of water, in which all the previous works on DPD reported only a limited portion of the water properties. Here, we show that the modified mDPD can provide accurate modelling of water static and dynamic properties and an EOS that matches the experimental data to a large range of confinement pressure.

42 ENGINEERING↗

Modeling of advanced accelerator concepts

Computer modeling is essential to research on Advanced Accelerator Concepts (AAC), as well as to their design and operation. This paper summarizes the current status and future needs of AAC systems and reports on several key aspects of (i) high-performance computing (including performance, portability, scalability, advanced algorithms, scalable I/Os and In-Situ analysis), (ii) the benefits of ecosystems with integrated workflows based on standardized input and output and with integrated frameworks developed as a community, and (iii) sustainability and reliability (including code robustness and usability).

47 OTHER INSTRUMENTATION↗

Parallel Simulation of Beam Dynamics in Particle Accelerators [Slides]

Particle accelerators are among the most versatile and important tools of scientific discovery. The Nation's accelerators are responsible for a wealth of advances in materials science, chemistry, the biosciences, particle physics, and nuclear physics. They also have important applications to national security, the environment, energy, medicine, and on the quality of people's lives. LANL has a long history of making pioneering contributions to Accelerator Science including key contributions to the field of Computational Accelerator Physics. These include the development of early beam dynamics codes with space charge (such as PARMILA and PARMELA), the development of rf cavity codes and magnet codes (including Poisson and Superfish), and the development and distribution of codes to the accelerator community through the Los Alamos Accelerator Code Group. LANL researchers also helped pioneer the development of massively parallel space-charge codes. In project t22_accelsim we have moved beyond electrostatic models of collective effects (i.e., solving the Poisson equation in the bunch frame) to fully electromagnetic models based on the Lienard-Wiechert formalism. This approach enables the large-scale simulation of radiation production and collective effects in high brightness electron beams. This is highly relevant to LANL given its future goal of developing an X-ray Free Electron Laser (XFEL). It also directly impacts a LANL LDRD project to develop an undulator-based non-invasive beam profile monitor for beams created in laser-plasma accelerator systems.

43 PARTICLE ACCELERATORS↗

Understanding the origin of softness in structurally tailored and engineered macromolecular (STEM) gels: A DPD study

Structurally tailored and engineered macromolecular (STEM) gels are polymer networks containing a primary network (the “STEM-0” gel) and side chains that are anchored to this network (forming the “STEM-1” gel). The ability to vary the features of the side chains provides a robust means of tailoring the macroscopic properties of the material. We use dissipative particle dynamics (DPD) simulations to determine the mechanical response of STEM-1 gels to uniaxial compression for various values of the side chain length, n sc . While the Young’s modulus of the material is significantly decreased with increasing n sc (at a fixed density of grafted side chains), above a certain saturation value, increasing n sc does not lead to any further softening of the sample. Using the simulations, we calculate the relevant stresses, which are related to the Young’s modulus and the number of entanglements in the network. We show that the backbone chains become more spread out upon addition of sidechains, leading to a decrease in the physical entanglements between backbone segments. This observation accounts for the decrease of stress in the backbone network and the softening of the networks through the addition of sidechains. For long chains, however, the number density of physical crosslinks between side chains is independent of side chain length; this observation explains the observed stress saturation in the STEM-1 gels. Our approach allows us to correlate the molecular architecture of the gels to the resultant macroscopic mechanical behavior and provide guidelines for fabricating STEM gels with well-defined mechanical properties, which allow the materials to be used for a variety of applications.

36 MATERIALS SCIENCE↗

Parallel Simulation of Beam Dynamics in Particle Accelerators [Slides]

LW3D was used to explore the expected CSR from an undulator-based diagnostic using a first-principles approach. It was also used for comparison with an analytic Green-function approach. LW3D was extended to model transport systems involving dipoles and quadrupoles. It was used to explore the radiation produced in a 4-dipole bunch compressor. Radiation ahead of the electron bunch at the beamline exit was shown to be associated with wavefronts produced in upstream dipoles overtaking the bunch.

43 PARTICLE ACCELERATORS↗

Transport and losses of energetic particles in tokamaks in the presence of Alfvén activity using the new full orbit TAPaS code coupled to FAR3d

Recent developments and tools integrated into the TAPaS code are presented, enabling realistic scenario simulations of particle dynamics within experimental tokamak magnetic equilibria. In particular, the enhanced capabilities of TAPaS enable seamless coupling with external simulations, provided the metric and equilibrium magnetic field of the external code are known. Coupling TAPaS with the gyro-fluid code FAR3d, the transport and losses of energetic particles in the presence Alfvén eigenmodes (AEs) in DIII-D plasma discharge #159243 were investigated. Detailed analyses of prompt losses with and without collisions were performed. Then, further analysis was performed in the presence of electromagnetic perturbations resulting from AEs activity. The results indicate that, for the energies and the initial conditions considered here, the presence of AEs enhances the particle losses.

Alfven eigenmodes↗

Numerical simulations of particle orbits around 2060 Chiron

Scattered light from orbiting or coorbiting dust is a primary signature by which Earth-based observers study the activity and atmosphere of the unusual outer solar system object 2060 Chiron. Therefore, it is important to understand the lifetime, dynamics, and loss rates of dust in its coma. We report here dynamical simulations of particles in Chiron's collisionless coma. The orbits of 17,920 dust particles were numerically integrated under the gravitational influence of Chiron, the Sun, and solar radiation pressure. These simulations show that particles ejected from Chiron are more likely to follow suborbital trajectories, or to escape altogether, than to enter quasistable orbits. Significant orbital lifetimes can only be achieved for very specific launch conditions. These results call into question models of a long-term, bound coma generated by discrete outbursts, and instead suggest that Chiron's coma state is closely coupled to the nearly instantaneous level of Chiron's surface activity.

Stern, S. A.↗

Machine Learning of Performance Space Mapping for the DPD Simulation of Drug Delivery to Endothelial Cells

Despite huge effort over the years, the design of functionalised nanocarriers (NCs) for targeted drug delivery to endothelial cells is still to be completely unveiled. Dissipative particle dynamics (DPD) simulation is used to study the adhesion of NCs to endothelial cells under the influence of series of parameters such as shape, size, and ligand density of the NCs. However, preparing a performance space mapping that illustrates the penetration depths of NCs as a function of variations in their properties requires simulations of all possible NCs with the above-mentioned properties, which is not feasible. This challenge was addressed by leveraging a Gaussian process regression (GPR)-informed active learning strategy and an extensive exploration of numerous samples, each representing different properties of NCs. The performance space mapping reveals that NCs with rod and disc shapes exhibit superior penetration capabilities compared to those with a spherical shape. Furthermore, it demonstrates that smaller-sized rod-shaped NCs and larger-sized disc-shaped NCs tend to achieve better penetration. When considering smaller NCs, the influence of ligand density appears to be limited. On the contrary, for larger NCs, an increase in ligand density correlates with greater penetration depth, underscoring its substantial role in shaping their penetration capabilities.

36 MATERIALS SCIENCE↗

Parallel implementation of a particle simulation for modeling rarefied gas dynamic flow

When the conditions of flow are rarefied and hypersonic, a more suitable alternative to the use of the Navier-Stokes equations for developing a numerical solution is the Direct Simulation Monte Carlo method (DSMC), a method of simulation which employs a large number of particles in modeling a rarefied gas. The performance of a parallel DSMC code developed for the Intel iPSC/860 Touchstone Gamma prototype computer is studied and the scaleup is found to be very nearly over the range of 16-128 processors.

Fallavollita, M. A.↗

Thermodynamic stability versus kinetic accessibility: Pareto fronts for programmable self-assembly

A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. Additionally, the tradeoff disappears when the number of particle types reaches a value m *, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic–kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.

36 MATERIALS SCIENCE↗

Platinum nanoparticle compression: Combining in situ TEM and atomistic modeling

The mechanical behavior of nanoparticles governs their performance and stability in many applications. However, the small sizes of technologically relevant nanoparticles, with diameters in the range of 10 nm or less, significantly complicate experimental examination. These small nanoparticles are difficult to manipulate onto commercial test platforms and deform at loads that are below the typical noise floor of the testing instruments. Here, we synthesized small platinum nanoparticles directly onto a mechanical tester and used a modified nanomanipulator to enhance load resolution to the nanonewton scale. We demonstrated the in situ compression of an 11.5-nm platinum nanoparticle with simultaneous high-resolution measurements of load and particle morphology. Molecular dynamics simulations were performed on similarly sized particles to achieve complementary measurements of load and morphology, along with atomic resolution of dislocations. The experimental and simulation results revealed comparable values for the critical resolved shear stress for failure, 1.28 and 1.15 GPa, respectively. Altogether, this investigation demonstrated the promise of, and some initial results from, the combination of atomistic simulations and in situ experiments with an unprecedented combination of high spatial resolution and high load resolution to understand the behavior of metal nanoparticles under compression.

42 ENGINEERING↗