Post-processing Simulations Research Articles

A waypoint based approach to visibility in performance based fire safety design

In performance-based fire safety design, ensuring safe egress, e.g. by visibility of safety signs, is a crucial safety goal. Compliance with the building requirements is often demonstrated by simulations of smoke spread. Numerical models like the Fire Dynamics Simulator generally compute visibility as a local quantity using the light extinction coefficient, without the consideration of the actual light path to a safety sign. Here, visibility maps are introduced, providing an approach for post-processing fire simulation data. They indicate safe areas along egress routes, with respect to visibility. At each location, the available visibility is calculated using Jin’s empirical relation, as an integrated value of the extinction coefficient along the line of sight to the closest exit sign. The required visibility results from the distance between those points. Additional parameters like view angle or visual obstructions are considered. The presented method allows for temporal visibility assessment, e.g. in an ASET-RSET analysis.

Spectral Calculations of 3D Radiation Magnetohydrodynamic Simulations of Super-Eddington Accretion onto a Stellar-mass Black Hole

We use the Athena++ Monte Carlo (MC) radiation transfer module to postprocess simulation snapshots from nonrelativistic Athena++ radiation magnetohydrodynamic (RMHD) simulations. These simulations were run using a gray (frequency-integrated) approach but were also restarted and ran with a multigroup approach that accounts for Compton scattering with a Kompaneets operator. These simulations produced moderately super-Eddington accretion rates onto a 6.62 M ⊙ black hole. Since we only achieve inflow equilibrium out to 20–25 gravitational radii, we focus on the hard X-ray emission. We provide a comparison between the MC and RMHD simulations, showing that the treatment of Compton scattering in the gray RMHD simulations underestimates the gas temperature in the funnel regions above and below the accretion disk. In contrast, the restarted multigroup snapshots provide a treatment for the radiation field that is more consistent with the MC calculations, and result in postprocessed spectra with harder X-ray emission compared to their gray snapshot counterparts. We characterize these MC postprocessed spectra using commonly employed phenomenological spectral fitting models. We also attempt to fit our MC spectra directly to observations of the ultraluminous X-ray source (ULX) NGC 1313 X-1, finding best-fit values that are competitive to phenomenological model fits, indicating that first principle models of super-Eddington accretion may adequately explain the observed hard X-ray spectra in some ULX sources.

Investigations of atomic and molecular processes of NBI-heated discharges in the MAST Upgrade Super-X divertor with implications for reactors

This experimental study presents an in-depth investigation of the performance of the MAST-U Super-X divertor during NBI-heated operation (up to 2.5 MW) focussing on volumetric ion sources and sinks as well as power losses during detachment. The particle balance and power loss analysis revealed the crucial role of Molecular Activated Recombination and Dissociation (MAR and MAD) ion sinks in divertor particle and power balance, which remain pronounced in the change from ohmic to higher power (NBI heated) L-mode conditions. The importance of MAR and MAD remains with double the absorbed NBI heating. MAD results in significant power dissipation (up to ∼20% of PSOL ), mostly in the cold ( Te<5 eV) detached region. Theoretical and experimental evidence is found for the potential contribution of D− to MAR and MAD, which warrants further study. These results suggest that MAR and MAD can be relevant in higher power conditions than the ohmic conditions studied previously. Post-processing reactor-scale simulations suggests that MAR and MAD can play a significant role in divertor physics and synthetic diagnostic signals of reactor-scale devices, which are currently underestimated in exhaust simulations. This raises implications for the accuracy of reactor-scale divertor simulations of particularly tightly baffled (alternative) divertor configurations.

A conditional extreme value distribution method for dynamic reliability analysis of stochastic structures

An efficient post-processing simulation method is proposed to estimate small failure probabilities of stochastic dynamic structures involving the inherent randomness of structural physical-geometrical parameters and external excitations. To extract a small failure probability, the proposed method introduces an intermediate event to represent the realizations of extreme structural response in the tail of distribution. With the aid of this intermediate event, structural failure probability is reformulated as a product of the event’s occurrence probability and the conditional exceedance probability of extreme response when the event occurs. The latter corresponds to a distribution of extreme response under the condition of the intermediate event, referred to as the conditional extreme value distribution (CEVD). Accordingly, the proposed method is termed the CEVD method. To reconstruct the CEVD, a truncated shifted generalized lognormal distribution model is employed. Bayesian estimation method is utilized to determine the two shape parameters of this model based on the samples of both original extreme value distribution and CEVD, where the CEVD samples are generated by Markov chain Monte Carlo sampling. The efficiency and accuracy of the proposed method are demonstrated through two numerical examples considering seismic reliability analyses of a 10-story nonlinear frame and a soil-foundation-structure interaction system.

Measuring the photoionization rate, neutral fraction, and mean free path of H i ionizing photons at 4.9 ≤ z ≤ 6.0 from a large sample of XShooter and ESI spectra

ABSTRACT We measure the mean free path ($\lambda _{\rm mfp,H\, \small {I}}$), photoionization rate ($\langle \Gamma _{\rm H\, \small {I}} \rangle$), and neutral fraction ($\langle f_{\rm H\, \small {I}} \rangle$) of hydrogen in 12 redshift bins at 4.85 &amp;lt; z &amp;lt; 6.05 from a large sample of moderate resolution XShooter and ESI QSO absorption spectra. The fluctuations in ionizing radiation field are modelled by post-processing simulations from the Sherwood suite using our new code ‘EXtended reionization based on the Code for Ionization and Temperature Evolution’ (ex-cite). ex-cite uses efficient Octree summation for computing intergalactic medium attenuation and can generate large number of high resolution $\Gamma _{\rm H\, \small {I}}$ fluctuation models. Our simulation with ex-cite shows remarkable agreement with simulations performed with the radiative transfer code Aton and can recover the simulated parameters within 1σ uncertainty. We measure the three parameters by forward-modelling the Lyα forest and comparing the effective optical depth ($\tau _{\rm eff, H\, \small {I}}$) distribution in simulations and observations. The final uncertainties in our measured parameters account for the uncertainties due to thermal parameters, modelling parameters, observational systematics, and cosmic variance. Our best-fitting parameters show significant evolution with redshift such that $\lambda _{\rm mfp,H\, \small {I}}$ and $\langle f_{\rm H\, \small {I}} \rangle$ decreases and increases by a factor ∼6 and ∼104, respectively from z ∼ 5 to z ∼ 6. By comparing our $\lambda _{\rm mfp,H\, \small {I}}$, $\langle \Gamma _{\rm H\, \small {I}} \rangle$ and $\langle f_{\rm H\, \small {I}} \rangle$ evolution with that in state-of-the-art Aton radiative transfer simulations and the Thesan and CoDa-III simulations, we find that our best-fitting parameter evolution is consistent with a model in which reionization completes by z ∼ 5.2. Our best-fitting model that matches the $\tau _{\rm eff, H\, \small {I}}$ distribution also reproduces the dark gap length distribution and transmission spike height distribution suggesting robustness and accuracy of our measured parameters.

SpK: A fast atomic and microphysics code for the high-energy-density regime

SpK is part of the numerical codebase at Imperial College London used to model high energy density physics (HEDP) experiments. SpK is an efficient atomic and microphysics code used to perform detailed configuration accounting calculations of electronic and ionic stage populations, opacities and emissivities for use in post-processing and radiation hydrodynamics simulations. This is done using screened hydrogenic atomic data supplemented by the NIST energy level database. An extended Saha model solves for chemical equilibrium with extensions for non-ideal physics, such as ionisation potential depression, and non thermal equilibrium corrections. A tree-heap (treap) data structure is used to store spectral data, such as opacity, which is dynamic thus allowing easy insertion of points around spectral lines without a-priori knowledge of the ion stage populations. Results from SpK are compared to other codes and descriptions of radiation transport solutions which use SpK data are given. The treap data structure and SpK’s computational efficiency allows inline post-processing of 3D hydrodynamics simulations with a dynamically evolving spectrum stored in a treap.

Protein-ligand interactions from a quantum fragmentation perspective: The case of the SARS-CoV-2 main protease interacting with α-ketoamide inhibitors.

We present a hybrid, multi-method, computational scheme for protein/ligand systems well suited to be used on modern and forthcoming massively parallel computing systems. The scheme relies on a multi-scale polarizable molecular modeling, approach to perform molecular dynamics simulations, and on an efficient Density Functional Theory (DFT) linear scaling method to post-process simulation snapshots. We use this scheme to investigate recent α-ketoamide inhibitors targeting the main protease of the SARS-CoV-2 virus. We assessed the reliability and the coherence of the hybrid scheme, in particular, by checking the ability of MM and DFT to reproduce results from high-end abinitio computations regarding such inhibitors. The DFT approach enables an a posteriori fragmentation of the system and an investigation into the strength of interaction among identified fragment pairs. We show the necessity of accounting for a large set of plausible protease/inhibitor conformations to generate reliable interaction data. Finally, we point out ways to further improve α-ketoamide inhibitors to more strongly interact with particular protease domains neighboring the active site.

NIMPHS: Numerous Instruments to Manipulate and Post-process Hydraulic Simulations

NIMPHS: Numerous Instruments to Manipulate and Post-process Hydraulic Simulations

A Hybrid Embedded Discrete Fracture Model and Dual-Porosity, Dual-Permeability Workflow for Hierarchical Treatment of Fractures in Practical Field Studies

Summary Natural fracture systems comprise numerous small features and relatively few large ones. At field scale, it is impractical to treat all fractures explicitly. We represent the largest fractures using an embedded discrete fracture model (EDFM) and account for smaller ones using a dual-porosity, dual-permeability (DPDK) idealized representation of the fracture network. The hybrid EDFM + DPDK approach uses consistent discretization schemes and efficiently simulates realistic field cases. Further speedup can be obtained using aggregation-based upscaling. Capabilities to visualize and post-process simulation results facilitate understanding for effective management of fractured reservoirs. The proposed approach embeds large discrete fractures as EDFM within a DPDK grid (which contains both matrix and idealized fracture continua for smaller fractures) and captures all connections among the triple media. In contrast with existing EDFM formulations, we account for discrete fracture spacing within each matrix cell via a new matrix-fracture transfer term and use consistent assumptions for classical EDFM and DPDK calculations. In addition, the workflow enables coarse EDFM representations using flow-based cell-aggregation upscaling for computational efficiency. Using a synthetic case, we show that the proposed EDFM + DPDK approach provides a close match of simulation results from a reference model that represents all fractures explicitly, while providing runtime speedup. It is also more accurate than previous standard EDFM and DPDK models. We demonstrate that the matrix-fracture transfer function agrees with flow-based upscaling of high-resolution fracture models. Next, the automated workflow is applied to a waterflooding study for a giant carbonate reservoir, with an ensemble of stochastic fracture realizations. The overall workflow provides the computational efficiency needed for performance forecasts in practical field studies, and the 3D visualization allows for the derivation of insights into recovery mechanisms. Finally, we apply a finite-volume tracer-based flux post-processing scheme on simulation results to analyze production allocation and sweep for understanding expected waterflood performance.

MDSuite: comprehensive post-processing tool for particle simulations

Particle-Based (PB) simulations, including Molecular Dynamics (MD), provide access to system observables that are not easily available experimentally. However, in most cases, PB data needs to be processed after a simulation to extract these observables. One of the main challenges in post-processing PB simulations is managing the large amounts of data typically generated without incurring memory or computational capacity limitations. In this work, we introduce the post-processing tool: MDSuite. This software, developed in Python, combines state-of-the-art computing technologies such as TensorFlow, with modern data management tools such as HDF5 and SQL for a fast, scalable, and accurate PB data processing engine. This package, built around the principles of FAIR data, provides a memory safe, parallelized, and GPU accelerated environment for the analysis of particle simulations. The software currently offers 17 calculators for the computation of properties including diffusion coefficients, thermal conductivity, viscosity, radial distribution functions, coordination numbers, and more. Further, the object-oriented framework allows for the rapid implementation of new calculators or file-readers for different simulation software. The Python front-end provides a familiar interface for many users in the scientific community and a mild learning curve for the inexperienced. Future developments will include the introduction of more analysis associated with ab-initio methods, colloidal/macroscopic particle methods, and extension to experimental data.

Determining the Limits of Fast Charging of a High-Energy Lithium-Ion NMC/Graphite Pouch Cell Through Combined Modeling and Experiments

This article presents the development, parameterization, and experimental validation of a pseudo-three-dimensional (P3D) multiphysics aging model of a 500 mAh high-energy lithium-ion pouch cell with graphite negative electrode and lithium nickel manganese cobalt oxide (NMC) positive electrode. This model includes electrochemical reactions for solid electrolyte interphase (SEI) formation at the graphite negative electrode, lithium plating, and SEI formation on plated lithium. The thermodynamics of the aging reactions are modeled depending on temperature and ion concentration and the reactions kinetics are described with an Arrhenius-type rate law. Good agreement of model predictions with galvanostatic charge/discharge measurements and electrochemical impedance spectroscopy is observed over a wide range of operating conditions. The model allows to quantify capacity loss due to cycling near beginning-of-life as function of operating conditions and the visualization of aging colormaps as function of both temperature and C-rate (0.05 to 2 C charge and discharge, −20 °C to 60 °C). The model predictions are also qualitatively verified through voltage relaxation, cell expansion and cell cycling measurements. Based on this full model, six different aging indicators for determination of the limits of fast charging are derived from post-processing simulations of a reduced, pseudo-two-dimensional isothermal model without aging mechanisms. The most successful aging indicator, compared to results from the full model, is based on combined lithium plating and SEI kinetics calculated from battery states available in the reduced model. This methodology is applicable to standard pseudo-two-dimensional models available today both commercially and as open source.

Predicting sub-millimetre flux densities from global galaxy properties

ABSTRACT Recent years have seen growing interest in post-processing cosmological simulations with radiative transfer codes to predict observable fluxes for simulated galaxies. However, this can be slow, and requires a number of assumptions in cases where simulations do not resolve the interstellar medium (ISM). Zoom-in simulations better resolve the detailed structure of the ISM and the geometry of stars and gas; however, statistics are limited due to the computational cost of simulating even a single halo. In this paper, we make use of a set of high-resolution, cosmological zoom-in simulations of massive ($M_{\star }\gtrsim 10^{10.5}\, \rm {M_{\odot }}$ at z = 2), star-forming galaxies from the FIRE suite. We run the skirt radiative transfer code on hundreds of snapshots in the redshift range 1.5 &amp;lt; z &amp;lt; 5 and calibrate a power-law scaling relation between dust mass, star formation rate, and $870\, \mu \rm {m}$ flux density. The derived scaling relation shows encouraging consistency with observational results from the sub-millimetre-selected AS2UDS sample. We extend this to other wavelengths, deriving scaling relations between dust mass, stellar mass, star formation rate, and redshift and sub-millimetre flux density at observed-frame wavelengths between $\sim \! 340$ and $\sim \! 870\, \mu \rm {m}$. We then apply the scaling relations to galaxies drawn from EAGLE, a large box cosmological simulation. We show that the scaling relations predict EAGLE sub-millimetre number counts that agree well with previous results that were derived using far more computationally expensive radiative transfer techniques. Our scaling relations can be applied to other simulations and semi-analytical or semi-empirical models to generate robust and fast predictions for sub-millimetre number counts.

Automatização na geração de malha de um transdutor de ondas gravitacionais cilíndrico de safira

ABSTRACT: The main objective of this work is to develop an automation for a mesh generation process of a cylindrical geometry made of sapphire. The use of commercial programs that have as main technology the Finite Element Method (Ansys, Comsol Multiphysics, Abaqus) in development of gravitational wave transducers encompasses most of the theses and articles performed. The great importance of using these technologies is due to the difficulty of obtaining materials with high electrical, mechanical quality factors and experiments performed with prototypes. Given this, the idea of the author of this article is to create an automation process for mesh generation using an Open Source software called Salome-Meca. Salome is a solution that provides a generic platform for pre- and post-processing numerical simulation.

Experimental distinction of the molecularly induced Balmer emission contribution and its application for inferring molecular divertor density with 2D filtered camera measurements during detachment in JET L-mode plasmas

A previously presented model for generating 2D estimates of the divertor plasma conditions at JET from deuterium Balmer line intensity ratios, obtained from tomographic reconstructions of divertor camera images, was amended to consider also the Balmer emission arising from molecular processes. Utilizing the AMJUEL and H2VIBR atomic and molecular databases of EIRENE enabled also inference of the molecular divertor density from the distinguished molecularly induced emission. Analysis of a JET L-mode density scan suggests the molecularly induced emission accounting for up to 60%–70% and 10%–20% of the Balmer D and D intensities, respectively, at the onset of detachment, while electron-ion recombination becomes increasingly dominant with deepening detachment. Similar observations were made by post-processing EDGE2D-EIRENE simulations, which indicated significant roles of molecular D ions and vibrational excitation of the D2 molecules as precursors for the molecularly induced emission. The experimentally inferred molecular density at the outer strike point was found to increase monotonously with decreasing strike point temperature, reaching approximately 30%–50% of the local electron density at 1–2 m−3 at 0.7 eV. A further steep increase by a factor of 3–5 was observed with decrease of to 0.5 eV. The observations are in qualitative and reasonable quantitative agreement with EDGE2D-EIRENE predictions of within the uncertainties of the experimental data.

Multiwavelength emission from leptonic processes in ageing galaxy bubbles

ABSTRACT The evolutionary behaviour and multiwavelength emission properties of bubbles around galaxies, such as the Fermi bubbles of the Milky Way, is unsettled. We perform 3D magneto-hydrodynamical simulations to investigate the evolution of leptonic galaxy bubbles driven by a 0.3-Myr intense explosive outburst from the nucleus of Milky-Way-like galaxies. Adopting an ageing model for their leptonic cosmic rays, we post-process our simulations to compute the multiwavelength emission properties of these bubbles. We calculate the resulting spectra emitted from the bubbles from radio frequencies to γ-rays, and construct emission maps in four energy bands to show the the development of the spatial emission structure of the bubbles. The simulated bubbles show a progression in their spectral properties as they age. In particular, the TeV γ-ray emission is initially strong and dominated by inverse Compton scattering, but falls rapidly after ∼1 Myr. In contrast, the radio synchrotron emission remains relatively stable and fades slowly over the lifetime of the bubble. Based on the emission properties of our post-processed simulations, we demonstrate that γ-ray observations will be limited in their ability to detect galaxy bubbles, with only young bubbles around nearby galaxies being within reach. However, radio observations with, e.g. the upcoming Square Kilometer Array, would be able to detect substantially older bubbles at much greater distances, and would be better placed to capture the evolutionary progression and diversity of galaxy bubble populations.

A Study on Post-Processing and Machine Simulation of AC Type 5-Axis Machine Tool for Machining of Mold Surface

A Study on Post-Processing and Machine Simulation of AC Type 5-Axis Machine Tool for Machining of Mold Surface

Importance of microstructure modeling for additively manufactured metal post-process simulations

This work investigates the significance of microstructure-level modeling by simulating the material response of an inhomogeneous selective laser melted (SLM) Inconel 625 specimen subjected to two different post-process operations, namely micro-milling and laser shock peening (LSP). A physics-based thermal finite element simulation is executed to obtain the SLM thermal history from which a 3-dimensional inhomogeneous microstructure representative volume element (RVE) is generated via the Dynamic Kinetic Monte Carlo predictive model. A Johnson–Cook plasticity definition coupled with Hall–Petch strengthening is used to define unique yield surfaces for individual grains based on their major diameters. Micro-milling and LSP simulations are subsequently executed with and without considering an inhomogeneous microstructure RVE in attempt to elucidate differences in the plastic strain, temperature, induced stress magnitude and distribution, as well as differences that arise during material removal for the micro-milling only. The micro-milling simulations reveal a greater volumetric distribution of plastic strain and temperature for the inhomogeneous case, although the homogeneous case with isotropic assumption reveals greater heat dissipation at the tool-workpiece interface with 27% greater contact pressure and 39% greater frictional shear stress. Examining the ductile and shear damage progression at a specific time increment reveals that the inhomogeneous model has a slightly lower damage propensity in comparison the homogeneous case, despite having identical damage models and boundary conditions. Variation in the SLM process-dependent yield surfaces, for grains at different locations, results in spatial variations of the computed stress triaxiality, which influences the material removal, as well as the stress concentrations developed near the tool-workpiece interface. Thus, a process-structure-property relationship is captured with the microstructure modeling. This work is the first to illuminate the importance of capturing SLM-induced anisotropy, considering the additively manufactured grain structure subject to micro-milling and LSP post-processes.

Micromechanical tensile test investigation to identify elastic and toughness properties of thin nitride compound layers

The measurement of thin-layer mechanical properties, like compounds generated by thermo-chemical nitriding process, is a key issue to optimize and predict the endurance of surface treatment against contact fatigue and wear. An original FIB micro-tensile test strategy involving plain and micro-notched tensile specimens is proposed. These specimens were FIB machined in a thin ε(50%)- γ’(50%) compound layer resulting from a common low pressure gaseous nitriding process (Allnit ©) and tested using a dedicated micro-testing system. Combined with DIC analysis, such micro-tensile test strategy allows extracting both the elastic modulus and the Poisson's ratio. Additionally, testing micro-notched specimens underlines the necessity to include FE simulations in order to take into account the radius of the micro-notch tip as well as the surface roughness induced by the FIB machining process. The investigation of this ε - γ’ compound layer suggests a Young's modulus E = 200 GPa, a Poisson's ratio ν =0.31 and a rather low fracture toughness KIC = 0.55 MPam. This methodology involving FIB machining, DIC analysis, test procedures and FE post processing simulations is fully detailed and the given results are discussed regarding literature.

A quantification methodology of Seismic Probabilistic Safety Assessment for nuclear power plant

A Seismic Probabilistic Safety Assessment (SPSA), unlike other internal or external event analyses, has a very high probability of basic events when a strong earthquake occurs. Because of this high probability, the Core Damage Frequency (CDF) might be overestimated by the Rare Events Approximation (REA) and Minimal Cutset Upper Bound (MCUB) method for general quantitative analysis. To compensate for this overestimation, the exact CDF value can be derived with post-processing software such as an Advanced Cutset Upper Bound Estimator (ACUBE) or Fault Tree Evaluation using Monte Carlo simulation (FTeMC). However, the Minimal Cut Sets (MCSs), which has the same result as the calculated CDF, cannot be derived with both methods. In this paper, we propose a Monte Carlo Simulation Allocation Method (MCSAM) to derive the exact CDF and MCSs. We expect that the MCSAM will easily identify the plant's vulnerabilities to review the exact MCSs consistent with CDF results without additional post-processing or Monte Carlo Simulation.

Full-scale topology optimization for fiber-reinforced structures with continuous fiber paths

Fiber-reinforced composite (FRC) structure design by topology optimization has become a hot spot in recent years. Nevertheless, the existing researches reveal several unfavorable issues including the fiber dis-continuity, the length scale separation, the decreased design freedom, as well as the complicated fiber orientation optimization. Thus, this paper proposes a full-scale fiber-reinforced structure topology optimization method that is capable of simultaneous design for the structural topology, continuous fiber path, and its morphology (i.e., fiber volume, spacing and thickness). The method builds upon a bi-material element-wise density-based topology optimization framework, where the matrix material and fiber material are considered in a uniform finite element model without the scale separation. Furthermore, a novel fiber generation scheme is developed, in which the bi-material constraint method is introduced by combining the total solid (composite) volume constraint and local fiber proportion constraint, so as to drive the evolution of the general topology, continuous fiber path and fiber morphology, respectively. In this way, it can avoid the above existing issues of the current FRC designs. The fiber-reinforced structures can be naturally generated with continuous fiber paths. Several numerical examples for compliance minimization problems are provided to show the merits of the full-scale optimization method for fiber-reinforced structures. The interpretation design procedure and post-processing error simulation analysis are also presented to further validate the applicability of the proposed method.