Parallel Simulation Research Articles

Quantifying Induced Dipole Effects in Small Molecule Permeation in a Model Phospholipid Bilayer.

The cell membrane functions as a semipermeable barrier that governs the transport of materials into and out of cells. The bilayer features a distinct dielectric gradient due to the amphiphilic nature of its lipid components. This gradient influences various aspects of small molecule permeation and the folding and functioning of membrane proteins. Here, we employ polarizable molecular dynamics simulations to elucidate the impact of the electronic environment on the permeation process. We simulated eight distinct amino-acid side chain analogs within a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayer using the Drude polarizable force field (FF). Our approach includes both unbiased and umbrella sampling simulations. By using a polarizable FF, we sought to investigate explicit dipole responses in relation to local electric fields along the membrane normal. We evaluate molecular dipole moments, which exhibit variation based on their localization within the membrane, and compare the outcomes with analogous simulations using the nonpolarizable CHARMM36 FF. This comparative analysis aims to discern characteristic differences in the free energy surfaces of permeation for the various amino-acid analogs. Our results provide the first systematic quantification of the impact of employing an explicitly polarizable FF in this context compared to the fixed-charge convention inherent to nonpolarizable FFs, which may not fully capture the influence of the membrane dielectric gradient.

Axial compression behaviour of square concrete-filled stainless-clad bimetallic steel tubular stub columns

Concrete-filled stainless-clad bimetallic steel tube (CFSCBST) members combines the advantages of excellent corrosion-resistance and good economy compared with conventional concrete-filled steel tube (CFST) members, which has great prospects in engineering application. This paper presents a comprehensive experimental and numerical investigation into the axial compression behaviour of CFSCBST stub columns with square sections. A total of eight specimens was conducted on CFSCBST specimens, incorporating varying width-to-thickness ratios, clad ratios and steel strengths, The experimental investigation provided a detailed report on failure modes, load versus displacement and strain response. The experimental results were utilized in a parallel numerical simulation to validate the finite element (FE) model. Subsequently, an extended parametric analysis was conducted to investigate the influence of the strength of the concrete, the substrate steel grade, the clad ratio, and the width-to-thickness ratio were carried out. The data obtained from tests and numerical studies were used to evaluate the applicability of existing design codes AISC/ANSI 360-22, EN 1994–1-1, GB 50936–2014 and DBJ/T 13-51-2020 for predicting the compressive capacity of square CFSCBST stub columns. Overall, a modified design method was proposed, adapted from DBJ/T 13-51-2020, was proposed for CFSCBST stub columns, demonstrating enhanced accuracy in predictions.

Performance evaluation of an automatic resonant switched capacitor-based voltage balancing circuits for series connected batteries

Electrical energy storage (EES) plays a crucial role in various power applications. Voltage imbalance is a common issue that can negatively affect the efficiency, reliability, and safety of EESs. Several types of voltage balancing (VB) circuits have been proposed in much of the literature. Among these VB circuits, switched capacitor (SC)-based circuits have attracted significant interest due to their efficiency, cost-effectiveness, compact size, and ease of control, but their balancing performance is not yet satisfactory. As a result, structural modifications in SC-based circuits have been widely proposed to improve balancing performance. However, not all of these circuit structures have been implemented into a resonant switched capacitor (RSC)-based voltage balancing, which has higher efficiency. Hence, this study aims to assess the efficiency of RSC-based VB circuits by conducting analog simulation using the Matlab Simulink software. This research evaluates the performance of the VB circuit not only in terms of its speed and efficiency, but also in terms of its energy distribution. The results show that the delta structure is the fastest in terms of balancing speed when completing the balancing process, followed by the mesh structure and the parallel structure. The best energy distribution is produced by a parallel structure, as indicated by the change in voltage of all battery cells always moving towards a convergent value, regardless of the variations in initial imbalance conditions. Meanwhile, other circuit structures distribute energy randomly, allowing the voltage of the battery cells to change not directly towards a convergent value. Lastly, the paper summarizes the balancing speed, efficiency, circuit complexity, and quality of energy distribution.

Modeling the unphysical pseudomode model with physical ensembles: Simulation, mitigation, and restructuring of non-Markovian quantum noise

The influence of a Gaussian environment on a quantum system can be described by effectively replacing the continuum with a discrete set of ancillary quantum and classical degrees of freedom. This defines a pseudomode model which can be used to classically simulate the reduced system dynamics. Here we consider an alternative point of view and analyze the potential benefits of an analog or digital quantum simulation of the pseudomode model itself. Superficially, such a direct experimental implementation is, in general, impossible due to the unphysical properties of the effective degrees of freedom involved. However, we show that the effects of the unphysical pseudomode model can still be reproduced using measurement results over an ensemble of physical systems involving ancillary harmonic modes and an optional stochastic driving field. This is done by introducing an extrapolation technique whose efficiency is limited by stability against imprecision in the measurement data. We examine how such a simulation would allow us to (i) perform a quantum simulation of the effects of complex nonperturbative and non-Markovian environments in regimes that are challenging for classical simulation; (ii) conversely, mitigate potential unwanted non-Markovian noise present in quantum devices; and (iii) restructure some of the properties of a given physical bath, such as its temperature. Published by the American Physical Society 2024

Stochastic computer experiments of the thermodynamic irreversibility of bulk nanobubbles in supersaturated and weak gas-liquid solutions.

Spontaneous gas-bubble nucleation in weak gas-liquid solutions has been a challenging topic in theory, experimentation, and computer simulations. In analogy with recent advances in crystallization and droplet formation studies, the diffusive-shielding stabilization and thermodynamic irreversibility of bulk nanobubble (bNB) mechanisms are revisited and deployed to characterize nucleation processes in a stochastic framework of computer experiments using the large-scale atomic/molecular massively parallel simulator code. Theoretical bases, assumptions, and limitations underlying the irreversibility hypothesis of bNBs, and their computational counterparts, are extensively described and illustrated. In essence, it is established that the irreversibility hypothesis can be numerically investigated by converging the system volume (due to the finiteness of interatomic forces) and the initial dissolved-gas concentration in the solution (due to the single-bNB limitation). Helium nucleation in liquid Pb17Li alloy is selected as a representative case study, where it exhibits typical characteristics of noble-gas/liquid-metal systems. The proposed framework lays down the bases on which the stability of gas-bNBs in weak and supersaturated gas-liquid solutions can be inferred and explained from a novel perspective. In essence, it stochastically marches toward a unique irreversible state along out-of-equilibrium nucleation/growth trajectories. Moreover, it does not attempt to characterize the interface or any interface-related properties, neither theoretically nor computationally. It was concluded that bNBs of a few tens of He-atoms are irreversible when dissolved-He concentrations in the weak gas-liquid solution are at least ∼50 and ∼105 molm-3 at 600 and 1000K (and ∼80 MPa), respectively, whereas classical molecular dynamics -estimated solubilities are at least two orders of magnitude smaller.

Preface

From 22nd to 24th December 2023, the 2023 3rd International Conference on Computational Modeling, Simulation and Data Analysis (CMSDA 2023) was held in Sanya, China via virtual form. The Conference attracted about 150 researchers, engineers, teachers and students worldwide working in or interested in the fields related to computational modeling, simulation and data analysis. The general objectives of the CMSDA 2023 were: To generate an adequate academic and scientific forum to present the work and experiences of researchers/teachers/students, contributing, in this way, to the production of new knowledge in the fields of computational modeling and data analysis. To create a path of establishing certain relationships for the speakers, authors and listeners, and providing opportunities for collaboration among the universities and institutions, in order to promote scientific research activities and develop relevant technologies. The subject areas in which the accepted papers were presented cover but are but not limited to: Perceptual Issues in Visualization and Modeling; Mathematical and Numerical Methods in Simulation and Modeling; Parallel and Distributed Computing Simulation; Big Data Visual Analysis; Data Analysis Algorithms and Systems, etc. We have invited renowned professors at home and abroad in these academic fields who shared with the attendees the latest innovations and research results in the domains of computational modeling, data mining and analysis. The Conference mainly featured keynote speeches by renowned experts and presentations of peer-reviewed papers by the authors. Among them, Prof. Daowen Qiu (Sun Yat-Sen University, China) shared his research on Distributed Quantum Algorithm for Simon’s Problem. Limited by today’s physical devices, quantum circuits are usually noisy and difficult to be designed deeply. The novel computing architecture of distributed quantum computing is expected to reduce the noise and depth of quantum circuits. And in his study, he presented the Simon’s problem in distributed scenarios and designed a distributed quantum algorithm to solve the problem. The algorithm proposed by him has the advantage of not only exponential acceleration compared with the classical distributed computing, but also square acceleration compared with the best distributed quantum algorithm proposed before. The Conference Proceedings was made so fruitful with all the excellent contributions collected from both domestic and international channels including the wonderful presentations in the Conference. It is a pleasure to thank the organizers, sponsors and all the participants and contributors for making the Conference possible and interesting. And our appreciation also to the members of Journal of Physics: Conference Series for providing us help in publishing this paper volume. The Committee of CMSDA 2023 List of Committee Member is available in this pdf.

Parallel Simulation for the Generalized Topology of Switched Capacitor Converter With Pillar-Connected-Double-Layer Structure

Parallel Simulation for the Generalized Topology of Switched Capacitor Converter With Pillar-Connected-Double-Layer Structure

Measurement and Simulation of the Propagation of Impulsive Acoustic Emission Sources in Pipes

Abstract: Acoustic Emission (AE) testing is a non-destructive evaluation technique that has gained significant attention in pipeline monitoring. Pencil-lead breaks (PLBs) are commonly used in reproducing and characterising sensors used in AE applications and have emerged as a valuable tool for calibration processes. This technique involves breaking a pencil lead by pressing it on the surface of the test structure and applying a bending moment at a given angle on a surface. The applied force produces a local deformation on the test surface, which is released when the lead breaks. The fracture in these PLBs is assumed to be a step unload; however, this is not the case. In this work, a series of PLB source experiments complemented with parallel numerical simulations were carried out to investigate the actual unload rate by correlating the relationship between AE speed, frequency, and power from PLBs. This was achieved by varying the simulation unload rates recorded over a duration of 2 s on a steel pipe and comparing to the experiment. Analysis of the investigated results from the experimental and numerical models suggests that although the AE line structure of a PLB can be reproduced by simulation for short times only (1 µs), the actual unload rate for PLBs is in the region of 10–8 s. It is concluded that FEA has the potential to help in the recovery of the temporal structure from real AE structures. The establishment of this model will provide a theoretical basis for future studies on the monitoring of non-impulsive AE sources such as impact on pipelines using finite element analysis.

Multilevel Schur-complement algorithms for scalable parallel reservoir simulation with temperature variation

In reservoir simulation, the non-isothermal multiphase flow problem introduces the temperature variable to account for thermal effects, simultaneously posing challenges in efficiently solving the nonlinear systems for large-scale simulations. In this paper, we introduce and investigate a family of Schur-complement-based field-split algorithms designed for addressing non-isothermal multiphase flow problems, particularly those characterized by high heterogeneity. This algorithm involves decomposing a large system into smaller, more manageable sub-systems for solving non-isothermal multiphase flow problems with multiple physical fields, which enables parallel computation and makes it suitable for high-performance computing environments. Furthermore, a multilevel Schur-complement preconditioner, which involves applying the Schur-complement technique at each level of the hierarchy by capturing the coupling between different fields and physics, is proposed to enhance the efficiency and robustness of the parallel simulator. Large-scale simulations for both benchmark and realistic problems are conducted on a supercomputer, showcasing the method's efficacy in managing heat diffusion, significantly reducing linear iterations, and demonstrating a good parallel scalability.

Elastic response of trabecular bone under compression calculated using the firm and floppy boundary lattice element method

Micro-Finite Element analysis (μFEA) has become widely used in biomechanical research as a reliable tool for the prediction of bone mechanical properties within its microstructure such as apparent elastic modulus and strength. However, this method requires substantial computational resources and processing time. Here, we propose a computationally efficient alternative to FEA that can provide an accurate estimation of bone trabecular mechanical properties in a fast and quantitative way. A lattice element method (LEM) framework based on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) open-source software package is employed to calculate the elastic response of trabecular bone cores. A novel procedure to handle pore-material boundaries is presented, referred to as the Firm and Floppy Boundary LEM (FFB-LEM). Our FFB-LEM calculations are compared to voxel- and geometry-based FEA benchmarks incorporating bovine and human trabecular bone cores imaged by micro Computed Tomography (μCT). Using 14 computer cores, the apparent elastic modulus calculation of a trabecular bone core from a μCT-based input with FFB-LEM required about 15 min, including conversion of the μCT data into a LAMMPS input file. In contrast, the FEA calculations on the same system including the mesh generation, required approximately 30 and 50 min for voxel- and geometry-based FEA, respectively. There were no statistically significant differences between FFB-LEM and voxel- or geometry-based FEA apparent elastic moduli (+24.3% or +7.41%, and +0.630% or -5.29% differences for bovine and human samples, respectively).

An Efficient FEniCS implementation for coupling lithium-ion battery charge/discharge processes with fatigue phase-field fracture

Accurately predicting the fatigue failure of lithium-ion battery electrode particles during charge–discharge cycles is essential for enhancing their structural reliability and lifespan. The fatigue failure of lithium-ion battery electrode particles during charge–discharge cycles poses a significant challenge in maintaining structural reliability and lifespan. To address this critical issue, this study presents a mathematical formulation for fatigue failure in lithium-ion batteries, utilizing the phase-field approach to fracture modeling. This approach, widely employed for fracture failure analysis, offers a comprehensive framework for capturing the complex interplay between mechanical deformation, chemical lithium concentration, and crack formation. Specifically, an additive decomposition of the strain tensor is employed to account for the swelling and shrinkage effects induced by lithium diffusion. Moreover, open-source code (https://github.com/noiiG) is provided, constituting a convenient platform for future developments, e.g., multi-field coupled problems. The developed chemo-mechanical model undergoes fatigue failure package is written in FEniCS as a popular free open-source computing platform for solving partial differential equations in which simplifies the implementation of parallel FEM simulations. Several numerical simulations with two different case studies corresponding to monotonic charge process and fatigue charge/discharge process are performed to demonstrate the correctness of our algorithmic developments.

Simulation study of compressive mechanical properties of spheroidal cytosolic lattice structures

Ultra-lightweight metallic lattice structures are lightweight functional materials, and the design of their cell elements is a focus of research. Based on the idea of hollow sphere and lattice structure, this paper designs a kind of spherical cytosolic lattice structure, investigates its mechanical properties when compressed by numerical simulation, analyzes its deformation law, derives the nominal stress-strain curve, and investigates the effects of the rod diameter and the cytosolic sphere center distance on the structure’s properties of the effective modulus of elasticity, yield limit, plateau stress, energy absorption and specific energy absorption. The results of the study show that the compressive deformation of the structure exhibits three types depending on the spherical center distance. The mechanical properties of the structure, such as effective modulus of elasticity, yield limit, and plateau stress, show a pattern of decreasing and then increasing with the increase of the spherical center distance, and the minimum value is reached when the spherical center distance is 9.0, but the specific energy absorption of the structure shows a pattern of increasing and then decreasing, and it reaches the maximum value when the spherical center distance is 9.6 mm. The validity of the numerical analog simulation analysis was experimentally verified by 3D printing specimens.

HPC challenges and opportunities of industrial-scale reactive fluidized bed simulation using meshes of several billion cells on the route of Exascale

Inside fluidized bed reactors, gas–solid flows are very complex: multi-scale, coupled, reactive, turbulent and unsteady. Accounting for them in an Euler-nfluid framework induces significantly expensive numerical simulations at academic scales and even more at industrial scales. 3D numerical simulations of gas–particle fluidized beds at industrial scales are limited by the High Performances Computing (HPC) capabilities of Computational Fluid Dynamics (CFD) software and by available computational power. In recent years, pre-Exascale supercomputers came into operation with better energy efficiency and continuously increasing computational resources.The present article is a direct continuation of previous work, Neau et al. (2020) which demonstrated the feasibility of a massively parallel simulation of an industrial-scale polydispersed fluidized-bed reactor with a mesh of 1 billion cells. Since then, we tried to push simulations of these systems to their limits by performing large-scale computations on even more recent and powerful supercomputers, once again using up to the entirety of these supercomputers (up to 286,000 cores). We used the same fluidized bed reactor but with more refined unstructured meshes: 8 and 64 billion cells.This article focuses on efficiency and performances of neptune_cfd code (based on Euler-nfluid approach) measured on several supercomputers with meshes of 1, 8 and 64 billion cells. It presents sensitivity studies conducted to improve HPC at these very large scales.On the basis of these highly-refined simulations of industrial scale systems using pre-Exascale supercomputers with neptune_cfd, we defined the upper limits of simulations we can manage efficiently in terms of mesh size, count of MPI processes and of simulation time. One billion cells computations are the most refined computation for production. Eight billion cells computations perform well up to 60,000 cores from a HPC point of view with an efficiency >85% but are still very expensive. The size of restart and mesh files is very large, post-processing is complicated and data management becomes near-impossible. 64 billion cells computations go beyond all limits: solver, supercomputer, MPI, file size, post-processing, data management. For these reasons, we barely managed to execute more than a few iterations.Over the last 30 years, neptune_cfd HPC capabilities improved exponentially by tracking hardware evolution and by implementing state-of-the-art techniques for parallel and distributed computing. However, our last findings show that currently implemented MPI/Multigrid approaches are not sufficient to fully benefit from pre-Exascale system. This work allows us to identify current bottlenecks in neptune_cfd and to formulate guidelines for an upcoming Exascale-ready version of this code that will hopefully be able to manage even the most complex industrial-scale gas–particle systems.

Translations of Cellular Automata for Efficient Simulation

Cellular automata can be described in many different ways, one of which is to use a special purpose description language. Here, the language CDL is used as the source for translations into Java or C code for computer simulations. Several coding styles are generated automatically: The state transition function can be coded as Java, as C with stubs for integration into a Java simulation environment, as a lookup table, or as Java code consisting of boolean functions which allow the parallel simulation of 32 or 64 cells on one processor. The coding styles are compared for several examples and it is found that the boolean function style (also called multispin-coding) realized in Java is often, but not always, significantly more efficient than even native C code.

Many-objective optimization for overall performance of an electric sport utility vehicle under multiple temperature conditions based on natural gradient boosting model

In this study, significant efforts have been devoted to optimizing energy consumption and driving range of an electric sport utility vehicle (ESUV). Vehicle energy flow tests were conducted at different temperatures, and integrated simulation models were built and validated. Subsequently, Natural Gradient Boosting (NGBoost) model was constructed based on extensive datasets obtained by parallel simulation framework, and many-objective optimizations of ESUV design parameters were performed. The results show that energy consumption per 100 km under high and low temperatures increases by 19.3 % and 34.9 % compared to room temperature, while effective work of half-axis decreases by 12.9 % and 28 %, suggesting extreme environmental temperature significantly affects ESUV performance. Mean square errors (MSEs) of NGBoost model predictions are less than 0.12, indicating its reliable predictive capability for unknown data. Many-Objective Random Walk Grey Wolf Optimizer (MORW-GWO) algorithm achieves optimal or suboptimal results on 10 test problems, fully demonstrating its efficient convergence and excellent robustness. Battery recovered energy, effective work of half-axis and electricity consumption per 100 km of final optimization scheme are increased by 20.2 %, 9.0 % and 13.0 %, with the largest overall percentage improvement of 17.3 %. These findings can provide data support and directional guidance for optimization designs and performance improvements of ESUVs.

Analog Simulation and the Indian Wars: Encountering the Other Through Board Wargames

Analog Simulation and the Indian Wars: Encountering the Other Through Board Wargames

Development and evaluation of parallel simulated annealing algorithm for reactor core optimization problems

Background The optimization of core loading patterns in nuclear reactors is one of the most studied optimization problems in nuclear engineering due to the enormous economical and safety benefits. Various algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), and Parallel Simulated Annealing (PSA) have been used in the past for such problems. Methods In this work, a PSA algorithm was developed and integrated into the Modularly Implemented Design Assistance Suite (MIDAS), a framework developed at North Carolina State University to solve nuclear engineering problems. The effectiveness of PSA was compared against the GA and SA algorithms available in MIDAS for a Pressurized Water Reactor first cycle core loading pattern optimization problem. Results PSA consistently generates more optimal solutions than SA and GA by having the higher average fitness, and showing less variance in its performance and thus being more robust. This provides confidence in the PSA implementation within MIDAS. The obtained loading pattern positions high reactive fuel in peripheral locations and low reactive fuel towards the centers in a strategy resembling both Out-In-Checkboard and L3P loading pattern approaches. Conclusions Future studies will involve applying the PSA algorithm to other optimization studies in larger combinatorial spaces, such as in multi-cycle optimization problems.

Analog quantum simulation of partial differential equations

Quantum simulators were originally proposed for simulating one partial differential equation (PDE) in particular—Schrödinger’s equation. Can quantum simulators also efficiently simulate other PDEs? While most computational methods for PDEs—both classical and quantum—are digital (they must be discretised first), PDEs have continuous degrees of freedom. This suggests that an analog representation can be more natural. While digital quantum degrees of freedom are usually described by qubits, the analog or continuous quantum degrees of freedom can be captured by qumodes. Based on a method called Schrödingerisation, we show how to directly map D-dimensional linear PDEs onto a (D+1) -qumode quantum system where analog or continuous-variable (CV) Hamiltonian simulation on D + 1 qumodes can be used. This very simple methodology does not require one to discretise PDEs first, and it is not only applicable to linear PDEs but also to some nonlinear PDEs and systems of nonlinear ordinary differential equations. We show some examples using this method, including the Liouville equation, heat equation, Fokker–Planck equation, Black–Scholes equations, wave equation and Maxwell’s equations. We also devise new protocols for linear PDEs with random coefficients, important in uncertainty quantification, where it is clear how the analog or CV framework is most natural. This also raises the possibility that some PDEs may be simulated directly on analog quantum systems by using Hamiltonians natural for those quantum systems.

Optimizing the Structures of Transformer Neural Networks Using Parallel Simulated Annealing

Abstract The Transformer is an important addition to the rapidly increasing list of different Artificial Neural Networks (ANNs) suited for extremely complex automation tasks. It has already gained the position of the tool of choice in automatic translation in many business solutions. In this paper, we present an automated approach to optimizing the Transformer structure based upon Simulated Annealing, an algorithm widely recognized for both its simplicity and usability in optimization tasks where the search space may be highly complex. The proposed method allows for the use of parallel computing and time-efficient optimization, thanks to modifying the structure while training the network rather than performing the two one after another. The algorithm presented does not reset the weights after changes in the transformer structure. Instead, it continues the training process to allow the results to be adapted without randomizing all the training parameters. The algorithm has shown a promising performance during experiments compared to traditional training methods without structural modifications. The solution has been released as open-source to facilitate further development and use by the machine learning community.

Influence of the magnetic flux on the dynamics of a self-sustaining system: analytical, numerical and analogical investigations

This paper investigates the nonlinear dynamics of a ferroelectric enzyme-substrate reaction modeled by the birhythmic van der Pol oscillator coupled to the magnetic flux. We derive the equilibrium points and study their stability. We analyze some bifurcation structures and the variation of the Lyapunov exponents. The phenomena of symmetric attractors and the anti-monotonicity are observed. By increasing the magnetic flux, we find that the equilibrium points are stable, tends to control chaotic regimes, and affects regular and quasi-regular ones. As the magnetic flux increases, the amplitude of the oscillations around the equilibrium points decreases and the amplitude of the limit cycles at the Hopf bifurcation tends to disappear. Further increasing the magnetic flux gives rise to chaotic dynamics. The electrical circuit and analogical simulations are derived using the PSpice software. The agreement between analogical and numerical results is acceptable.