Radiation Campaign of HPK Prototype LGAD sensors for the High-Granularity Timing Detector (HGTD)

We report on the results of a radiation campaign with neutrons and protons of Low Gain Avalanche Detectors (LGAD) produced by Hamamatsu (HPK) as prototypes for the High-Granularity Timing Detector (HGTD) in ATLAS. Sensors with an active thickness of 50~$\mu$m were irradiated in steps of roughly 2$\times$ up to a fluence of $3\times10^{15}~\mathrm{n_{eq}cm^{-2}}$. As a function of the fluence, the collected charge and time resolution of the irradiated sensors will be reported for operation at $-30^{\circ}$

Coupling Molecular Dynamics and Direct Simulation Monte Carlo using a general and high-performance code coupling library

A domain-decomposed method to simultaneously couple the classical Molecular Dynamics (MD) and Direct Simulation Monte Carlo (DSMC) methods is proposed. This approach utilises the MPI-based general coupling library, the Multiscale Universal Interface. The method provides a direct coupling strategy and utilises two OpenFOAM based solvers, mdFoam+ and dsmcFoam+, enabling scenarios where both solvers assume one discrete particle is equal to one molecule or atom. The ultimate goal of this work is to enable complex multi-scale simulations involving micro, meso and macroscopic elements, as found with problems like evaporation.Results are presented to show the fundamental capabilities of the method in terms of mass and kinetic energy conservation between simulation regions handled by the different solvers. We demonstrate the capability of the method by deploying onto a large supercomputing resource, with attention paid to the scalability for a canonical NVT ensemble (a constant number of atoms N, constant volume V and constant temperature T) of Argon atoms. The results show that the method performs as expected in terms of mass conservation and the solution is also shown to scale reasonably on a supercomputing resource, within the known performance limits of the coupled codes. The wider future of this work is also considered, with focus placed on the next steps to expand the capabilities of the methodology to allow for indirect coupling (where the coarse-graining capability of the DSMC method is used), as well as how this will then fit into a larger coupled framework to allow a complete micro-meso-macro approach to be tackled

Velocity Slip and Temperature Jump in Hypersonic Aerothermodynamics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76543/1/AIAA-2007-208-226.pd

Putting the micro into the macro : a molecularly augmented hydrodynamic model of dynamic wetting applied to flow instabilities during forced dewetting

We report a molecularly augmented continuum-based computational model of dynamic wetting and apply it to the displacement of an externally driven liquid plug between two partially wetted parallel plates. The results closely follow those obtained in a recent molecular dynamics (MD) study of the same problem (Fernández-Toledano et al., J. Colloid Interface Sci., vol. 587, 2021, pp. 311-323), which we use as a benchmark. We are able to interpret the maximum speed of dewetting as a fold bifurcation in the steady phase diagram and show that its dependence on the true contact angle is quantitatively similar to that found using MD. A key feature of the model is that the contact angle is dependent on the speed of the contact line, with emerging as part of the solution. The model enables us to study the formation of a thin film at dewetting speeds U∗ across a range of length scales, including those that are computationally prohibitive to MD simulations. We show that the thickness of the film scales linearly with the channel width and is only weakly dependent on the capillary number. This work provides a link between matched asymptotic techniques (valid for larger geometries) and MD simulations (valid for smaller geometries). In addition, we find that the apparent angle, the experimentally visible contact angle at the fold bifurcation, is not zero. This is in contrast to the prediction of conventional treatments based on the lubrication model of flow near the contact line, but consistent with experiment

Hybrid molecular-continuum simulations of water flow through carbon nanotube membranes of realistic thickness

We present new hybrid molecular-continuum simulations of water flow through filtration membranes. The membranes consist of aligned carbon nanotubes (CNTs) of high aspect ratio, where the tube diameters are ~1–2 nm and the tube lengths (i.e. the membrane thicknesses) are 2–6 orders of magnitude larger than this. The flow in the CNTs is subcontinuum, meaning standard continuum fluid equations cannot adequately model the flow; also, full molecular dynamics (MD) simulations are too computationally expensive for modelling these membrane thicknesses. However, various degrees of scale separation in both time and space in this problem can be exploited by a multiscale method: we use the serial-network internal-flow multiscale method (SeN-IMM). Our results from this hybrid method compare very well with full MD simulations of flow cases up to a membrane thickness of 150 nm, beyond which any full MD simulation is computationally intractable. We proceed to use the SeN-IMM to predict the flow in membranes of thicknesses 150 nm–2 μm, and compare these results with both a modified Hagen–Poiseuille flow equation and experimental results for the same membrane configuration. We also find good agreement between experimental and our numerical results for a 1-mm-thick membrane made of CNTs with diameters around 1.1 nm. In this case, the hybrid simulation is orders of magnitude quicker than a full MD simulation would be

Molecular dynamics pre-simulations for nanoscale computational fluid dynamics

We present a procedure for using molecular dynamics (MD) simulations to provide essential fluid and interface properties for subsequent use in computational fluid dynamics (CFD) calculations of nanoscale fluid flows. The MD pre-simulations enable us to obtain an equation of state, constitutive relations, and boundary conditions for any given fluid/solid combination, in a form that can be conveniently implemented within an otherwise conventional Navier–Stokes solver. Our results demonstrate that these enhanced CFD simulations are then capable of providing good flow field results in a range of complex geometries at the nanoscale. Comparison for validation is with full-scale MD simulations here, but the computational cost of the enhanced CFD is negligible in comparison with the MD. Importantly, accurate predictions can be obtained in geometries that are more complex than the planar MD pre-simulation geometry that provides the nanoscale fluid properties. The robustness of the enhanced CFD is tested by application to water flow along a (15,15) carbon nanotube, and it is found that useful flow information can be obtained

Multiscale simulation of nanofluidic networks of arbitrary complexity

We present a hybrid molecular-continuum method for the simulation of general nanofluidic networks of long and narrow channels. This builds on the multiscale method of Borg et al. (Microfluid Nanofluid 15(4):541–557, 2013; J Comput Phys 233:400–413, 2013) for systems with a high aspect ratio in three main ways: (a) the method has been generalised to accurately model any nanofluidic network of connected channels, regardless of size or complexity; (b) a versatile density correction procedure enables the modelling of compressible fluids; (c) the method can be utilised as a design tool by applying mass-flow-rate boundary conditions (and then inlet/outlet pressures are the output of the simulation). The method decomposes the network into smaller components that are simulated individually using, in the cases in this paper, molecular dynamics micro-elements that are linked together by simple mass conservation and pressure continuity relations. Computational savings are primarily achieved by exploiting length-scale separation, i.e. modelling long channels as hydrodynamically equivalent shorter channel sections. In addition, these small micro-elements reach steady state much quicker than a full simulation of the network does. We test our multiscale method on several steady, isothermal network flow cases and show that it converges quickly (within three iterations) to good agreement with full molecular simulations of the same cases