Efficient Simulation Research Articles

Minimum Energy Atomic Deposition: A novel, efficient atomistic simulation method for thin film growth

Thin-film growth is an area of research concerned with complex phenomena happening at atomic scales. Therefore, molecular simulation has been an important tool to confront experimental results to theoretical assumptions. However, the traditional thin film growth simulation methods, i.e., Molecular Dynamics (MD) and kinetic Monte-Carlo (kMC) and combinations thereof, suffer from limitations inherent to their design, i.e., limitations in system size and simulation time for MD and predetermined reaction rates and reaction sites for kMC. Consequently, it is practically impossible to simulate the evolution of polycrystalline growth resulting in ∼100nm thick films with realistic stress fields and defect structures, such as grain boundaries, stacking faults, etc. In this work, we propose a versatile and efficient atomistic simulation method (Minimum Energy Atomic Deposition) which works by direct insertion of atoms at points of minimal potential energy through efficient scanning of candidate positions and rapid relaxation of the system. This method allows simulating ≥100nm film thickness while mimicking experimental growth rates and high crystallinity and low-defect concentration and enables in-depth studies of atomic growth mechanisms, the evolution of crystal defects, and residual stress build-up. We demonstrate the efficiency and versatility of the method through the deposition of Al on Si, Al on Al, and Si on Si. The simulation results are systematically compared with experimental observations of thin-film deposition, yielding consistent observations. The method has been implemented in open-source LAMMPS software, making it easily accessible to the research community.

Characterization of weakly nonlinear effects in relationship to transducer parameters in focused ultrasound therapy.

Focused ultrasound therapy has been widely used for the treatment of various diseases, employing different types of transducers. The focused ultrasound pressure fields inevitably exhibit nonlinear effects, which can influence the ablation region. However, the nonlinear effects exhibit noticeable variations across different applications. The characterization of the nonlinear pressure fields of ultrasound is important for the effective implementation of focused ultrasound therapy. The traditional angular spectrum method (ASM) was extended to accurately and efficiently simulate the propagation of weakly nonlinear ultrasound in heterogeneous mediums of clinical model. The nonlinear effects were further analyzed in relationship to the transducer parameters that are different in various applications. The pressure fields were simulated using the extended ASM, incorporating calculations for phase aberration in the frequency domain and magnitude compensation in the spatial domain to account for heterogeneous acoustic impedance mismatch. Validation was performed by comparison to k-Wave simulation results using two simplified clinical models, an abdominal soft tissue and a transcranial skull model. The nonlinear effects were then analyzed in relation to the transducer parameters of f-number and effective source area based on the same acoustic output power. The analysis of nonlinear effects was conducted under both homogeneous medium and the clinical models. The simulation results demonstrated a maximum error of 3.93% in the calculated harmonic pressure of the abdominal model, and a maximum error of 4.89% within the transcranial model when comparing the extended ASM simulation results to those obtained from k-Wave simulations. The characterization of the nonlinear effects reveals a strong correlation with the transducer parameters. Specifically, the results indicate that the nonlinear effects intensify with an increase in the effective source area and f-number, under the same acoustic output power of the transducer. However, the clinical model also showed an influence on the nonlinear effects in relation to the f-number. The extended ASM was demonstrated as an accurate and efficient simulation tool, and the simulation results provide a reference for evaluating the intensity of nonlinear effects in various transducer designs.

GaAs-based red micro-light-emitting diodes with an oxide perimeter region for improved external quantum efficiency

Red micro-light-emitting diodes (μ-LEDs) with AlGaInP/GaInP multiple quantum wells are fabricated with an oxide perimeter region to control the current injection path. When the values of the external quantum efficiency (EQE) of the 30 μm-size μ-LED with the oxide perimeter region are compared with those of the device without the oxide perimeter region, an improvement as high as 40% is observed at current densities <80 A/cm2. From the finite-difference time-domain simulation of the light-extraction efficiency (LEE), which shows that the LEE of the device with the oxide perimeter region is ∼12% smaller than that of the device without the oxide perimeter region, it can be seen that the increased EQE is attributed to the improvement of the internal quantum efficiency (IQE). Since the oxide perimeter region limits the current paths to the sidewalls of the μ-LED chips, the nonradiative recombination via sidewall defects is considered suppressed, resulting in the improvement of the IQE. The oxidation of the AlGaAs layer utilized in this work is easy to implement and accurately controllable, suitable for mass-production of high-efficiency red μ-LEDs for display applications.

Small modular reactor reinforcement learning framework: Automating reactor core startup

A small modular reactor (SMR) has been considered a potential alternative for achieving carbon neutrality, and therefore, an increasing number of countries are performing extensive research and development. However, this is still in the development stage, and there are several technological or economical challenges that need to be overcome. Minimizing manual operations may be considered a wise approach to reduce the number of operators. Reactor core startup, which is a manual operation, is considered as an example. A method to automate the reactor core startup via the reinforcement learning (RL) algorithm is proposed in this paper. Further, an efficient SMR dynamic simulation model that performs simulations considering the action of the RL agent to achieve states and reward is developed. The suggested SMR dynamic simulation model is validated by the data available in the existing literature. The proposed method can perform automatic reactor core startup. The proposed framework that incorporates the SMR simulator to the RL algorithm is expected to be applied to various cases for reducing manual operations and contributing to realizing a higher level of SMR automation.

A Novel Approach Integrating the Method of Characteristics with Large Time-Step Scheme (MOC-LTS) for Efficient Transient Flow Simulation in Liquid Pipelines

Water hammer incidents pose a significant risk to the safety and stability of pipeline operations. Therefore, rapid and precise transient flow simulation is essential for efficiently developing scientific water hammer control strategies. Nevertheless, the prevailing transient flow simulation methods for liquid pipelines predominantly employ explicit schemes to solve transient flow control equations, necessitating adherence to the stability criterion of Courant-Friedrichs-Lewy (CFL) ≤ 1. This results in limited time step sizes, which in turn constrains computational efficiency, particularly when simulating hydraulic behavior in large-scale pipeline networks. In this paper, a novel approach integrating the method of characteristics (MOC) with a large time-step scheme (LTS) is proposed to enable rapid and accurate simulation of transient flow in liquid pipelines. The proposed approach discretizes the computational domain into contiguous control volumes, ategorizing them as either boundary or internal control volumes depending on whether they are affected by boundary conditions within a large time step. For internal control volumes, an LTS scheme based on the first-order Godunov format is employed to improve computational efficiency. For boundary control volumes, MOC is applied iteratively to accurately capture boundary dynamics until the simulated time matches that of the internal control volumes. Quantitative analysis is conducted to verify the performance of the proposed approach. The results confirm that the proposed approach outperforms the MOC in computational efficiency while maintaining minimal accuracy loss.

A multi-level-variable correlated mechanistic model system for irradiation-induced multi-scale volume growths of U-10Mo/Zr dispersion nuclear fuels

Irradiation-induced volumetric deformations in dispersion nuclear fuels arouse a critical concern in nuclear fuel design. Utilizing the concepts from mesomechanics and homogenization, a multi-level-variable correlated mechanistic model system called the Dispersion Fuel Swelling Analysis Model System (DFSAMS) is developed for the irradiation-induced multi-scale volume growths of U-10Mo/Zr dispersion nuclear fuels. These models could directly correlate the macroscopic irradiation-induced volume growth strain with the dynamically varying multi-level information, including the obtained particle volume fractions, the current porosities of recrystallized zones of fuel grains, the macroscale porosities of fuel particles, the average numbers of fission gas atoms within fuel bubbles, the average bubble pressures and the macroscale pressures of fuel particles related to the macroscale hydrostatic pressures of dispersion fuels. The obtained theoretical results align favorably with finite element predictions and a diverse range of experimental data, demonstrating the effectiveness of the newly developed model system. It is indicated that: (1) the irradiation creep performance of the Zr matrix becomes the predominant factor influencing the macroscale volume growth deformations of U-10Mo/Zr dispersion fuels, due to the differed resistance to volumetric deformations of U-10Mo particles; (2) the as-fabricated bubbles of fuel particles will gradually decrease in size under the macroscale hydrostatic pressures due to the irradiation creep deformations occurring in the surrounding solid skeleton, contributing negatively to the macroscale volumetric expansion of U-10Mo/Zr dispersion fuels, especially in cases with higher initial porosity. The important theoretical models are supplied here for efficient numerical simulation of the irradiation-induced thermal-mechanical coupling behaviors in U-10Mo/Zr dispersion fuel elements.

Acquiring musculoskeletal skills with curriculum-based reinforcement learning

Efficient musculoskeletal simulators and powerful learning algorithms provide computational tools to tackle the grand challenge of understanding biological motor control. Our winning solution for the inaugural NeurIPS MyoChallenge leverages an approach mirroring human skill learning. Using a novel curriculum learning approach, we trained a recurrent neural network to control a realistic model of the human hand with 39 muscles to rotate two Baoding balls in the palm of the hand. In agreement with data from human subjects, the policy uncovers a small number of kinematic synergies, even though it is not explicitly biased toward low-dimensional solutions. However, selectively inactivating parts of the control signal, we found that more dimensions contribute to the task performance than suggested by traditional synergy analysis. Overall, our work illustrates the emerging possibilities at the interface of musculoskeletal physics engines, reinforcement learning, and neuroscience to advance our understanding of biological motor control.

Hybrid multiscale computational approach for heat transfer in GaN semiconductors

Abstract With ongoing advancements in semiconductor technology, understanding thermal transport in semiconductor devices—where phonons are the primary charge carriers—is crucial. This involves a multiscale process in which phenomena at different scales are governed by distinct control equations, necessitating various numerical methods. In this context, this paper introduces a novel multiscale simulation method called the Second-Order Reconstruction Operator Finite Difference Lattice Boltzmann Method (ROsFDLBM). This method effectively combines the Lattice Boltzmann Method (LBM) with the Finite Difference Method (FDM). ROsFDLBM employs reconstruction operators to accurately map the relationship between distribution functions and macroscopic physical quantities, significantly reducing errors caused by the transmission of interface information. The efficacy of this coupling scheme has been confirmed through an interface-coupled thermal diffusion model. Comparative analyses have revealed that the relative error of ROsFDLBM does not exceed 1.2%, demonstrating its superior accuracy. Further simulations of GaN devices have confirmed that traditional macroscopic methods tend to underestimate the temperature in the heat source area at micro-nano scales, with discrepancies reaching up to 60.9 K. Overall, the ROsFDLBM aligns with current research findings and offers an accurate and efficient simulation strategy for addressing complex heat transfer problems.

Efficient simulation of spatially correlated non-stationary ground motions by wavelet-packet algorithm and spectral representation method

Efficient simulation of spatially correlated non-stationary ground motions by wavelet-packet algorithm and spectral representation method

Application of BIM and Virtual Reality of System Integration Design and Development in Medical Building Projects: A Case Study in China

Design outcomes in the Medical Building Projects (MBPs) must satisfy the demand of the medical staff and stakeholders. However, they often do not have the relevant engineering expertise, so the design team is prone to misunderstandings when communicating with them using traditional two-dimensional (2D) Computer-Aided Design (CAD) drawings. The medical staff may not readily visualize and understand the design and then provide feedback to the designer through professional medical requirements or advice, which results in the need to redesign and carry out additional work during the design phase, thus delaying the progress of the MBPs. To address these challenges, this study aims to develop an integrated system based on BIM, advanced rendering engines, and VR technology for use in non-immersive and immersive VR environments. Moreover, in this study, the integrated system was applied to the infection-building project of the People's Hospital of Qingbaijiang District, Chengdu City, and semi-structured interviews were distributed to 16 engineers, designers, contractors, and medical staff who had been involved in the whole project to validate the practicality and effectiveness of the integrated system. The results indicate that this system integration is an efficient visual communication and simulation tool in medical design. Key advantages include enhanced communication efficiency between the design team and medical stakeholders, improved visual interaction, and streamlined decision-making processes within a 3D VR/BIM environment. The successful implementation of this integrated system is expected to significantly aid design teams and stakeholders in effectively managing medical design tasks in future projects.

A novel improved actuator line method for tandem-arranged wind turbines wake analysis and its application

For a typical wind farm layout, the disturbance caused by wind turbine wakes typically exerts a significant negative impact on power generation. However, due to the insufficient reliability of existing multiple turbines wake simulations, the improved effects of wind farm layout modifications cannot be fully verified. In this paper, we employ a high-fidelity model, the Improved Actuator Line Model (I-ALM), combined with Large Eddy Simulation (LES) based on the OpenFOAM solver, to investigate the active yaw strategy of wind farms. The improvements in the ALM primarily include the Gaussian anisotropic force projection method, the integral velocity sampling method, and the enhanced nacelle-tower projection method. Firstly, we conduct numerical simulations of the NTNU "Blind Test" experimental cases using the combination of the I-ALM method and LES, mainly focusing on aerodynamic forces and wake development characteristics. Then, the proposed method is applied to the wake prediction of three NREL 5 MW tandem-arranged yaw wind turbines after benchmarking. The power generation and wake characteristics under different yaw angles is comprehensively predicted, leading to the development of a preliminary active yaw strategy (including rated state and maximum TSR state). This strategy holds significant guiding value for the accurate and efficient simulation of wind farms.

Study on the 2D equivalent nonlinear dynamics simulation model related to high speed precision bearing and spindle

The stiffness and contact stress of the bearing spindle system are the key factors affecting its machining accuracy and service life under the condition of high-speed service, which will be affected by different structural parameters and service conditions. It is essential to establish an efficient and accurate computational simulation model to understand the influence of complex factors on the nonlinear dynamic characteristics of the bearing spindle system. Firstly, in the paper, a 2D axisymmetric finite element model of the bearing, aims at the relationship between stiffness and contact stress of the bearing under high-speed service, has been built based on a classical dynamic analysis model and the reversed method of material parameters of equivalent rolling balls. Additionally, for the BT30 spindle, the 2D axisymmetric finite element model of the bearing spindle system also has been built and applied in mechanical analysis of spindle under different conditions of assembly and service, based on the bearing model. The results show that the axial force of bearings decreases as the rotational speed increases, and an augmentation in speed will result in a reduction in the axial stiffness of the BT30 spindle. In addition, the maximum contact stress exhibits a slight decline as the rotational speed increases. Furthermore, with an escalating preload, the stiffness and contact stress of the spindle undergo substantial increments, however, these parameters will cease to alter once a certain threshold is reached.

On the Calibration of the Kennedy Model

The Kennedy model offers a robust framework for modeling forward rates, leveraging Gaussian random fields to accommodate emerging phenomena such as negative rates. In our study, we employ maximum likelihood estimations to determine the parameters of the Kennedy field, utilizing Radon–Nikodym derivatives for enhanced accuracy. We introduce an efficient simulation method for the Kennedy field and develop a Black–Scholes-like analytical pricing formula for diverse financial assets. Additionally, we present a novel parameter estimation algorithm grounded in numerical extreme value optimization, enabling the recalibration of parameters based on observed financial product prices. To validate the efficacy of our approach, we assess its performance using real-world par swap rates in the latter part of this article.

Efficient simulation of open quantum systems coupled to a reservoir through multiple channels.

It is challenging to simulate open quantum systems that are connected to a reservoir through multiple channels. For example, vibrations may induce fluctuations in both energy gaps and electronic couplings, which represent two independent channels of system-bath couplings. Systems of this kind are ubiquitous in the processes of excited state radiationless decay. Combined with density matrix renormalization group (DMRG) and matrix product states (MPS) methods, we develop an interaction-picture chain mapping strategy for vibrational reservoirs to simulate the dynamics of these open systems, resulting in time-dependent spatially local system-bath couplings in the chain-mapped Hamiltonian. This transformation causes the entanglement generated by the system-bath interactions to be restricted within a narrow frequency window of vibrational modes, enabling efficient DMRG/MPS dynamical simulations. We demonstrate the utility of this approach by simulating singlet fission dynamics using a generalized spin-boson Hamiltonian with both diagonal and off-diagonal system-bath couplings. This approach generalizes an earlier interaction-picture chain mapping scheme, allowing for efficient and exact simulation of systems with multi-channel system-bath couplings using matrix product states, which may further our understanding of nonlocal exciton-phonon couplings in exciton transport and the non-Condon effect in energy and electron transfer.

Cross-fade sampling: extremely efficient Bayesian inversion for a variety of geophysical problems

SUMMARY This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (PDF). Secondly, it is much faster to evaluate the posterior probability of each sample than conventional sampling methods for simulating Bayesian posterior PDFs. Conventional methods require evaluating the prior probability (which describes your a priori constraints) and data likelihood (which describes the fit between the observations and the predictions of the model) for each sample model. However, cross-fading does not require evaluating the data likelihood, meaning that ‘big data’ can be fit with zero additional computational cost. Further, the cross-fading approach can be used to calculate the marginal likelihood associated with a model design, facilitating model comparison and Bayesian model averaging. Topics covered in this paper include derivation of the cross-fade approach and how it can be used to simulate Bayesian posterior PDFs and compute the marginal likelihood, discussion of the class of problems to which cross-fading can be applied (with examples from earthquake statistics, earthquake ground motion modelling, volcanic eruption forecasting, and finite fault slip modelling), demonstration of efficiency relative to existing sampling methods and discussion of how cross-fading can be used to account for prediction errors (i.e. epistemic errors) as part of the geophysical inverse problem.

Accurate and efficient analytical simulation of free vibration for embedded nonlocal CNTRC beams with general boundary conditions

This study aims to evaluate the free vibrational response of embedded restrained nanobeams enriched by nanocomposites based on an exact Fourier series approach. In order to capture the small-scale effects on the dynamical response, Eringen's differential form of nonlocal elasticity is used which employs a scale (nonlocal) parameter. Within the framework of Rayleigh and Bernoulli-Euler beam theories, including the effect of nonlocality and employing the Fourier sine series together with Stokes' transformation, systems of linear equations are obtained and solved using the coefficient matrices. The combined effects of elastic boundary conditions, elastic foundation, dispersion patterns and volume fractions of carbon nanotubes, and nonlocal parameter are examined by solving eigenvalue problems constructed with Fourier infinite series. Free vibration frequencies are calculated for carbon nanotube-reinforced nanobeams under different rigid or restrained boundary conditions, including Winkler-Pasternak type elastic foundation. A comprehensive parametric study is performed, focusing on various effects for the free vibrational response of the composite nanobeam reinforced with carbon nanotubes. It is concluded that adding a small amount of carbon nanotube material can reinforce the stiffness of the composite nanobeam, and its free vibration performance is significantly affected by the distribution patterns, elastic medium, and boundary conditions.

Study on behavior rules of the licorice-soil-licorice oscillating harvester coupled system using numerical method

Licorice oscillating harvester is a new type of energy-saving and resistance-reducing licorice harvester, and the interaction of licorice-soil-harvester is the critical factor affecting the working performance. Based on the licorice distribution in the harvested field and soil characteristics, a licorice-soil-licorice oscillating harvester coupled model was developed using the discrete element method. An efficient simulation method of a complex mechanism combined with a kinematic solution was proposed to study the behavior rules of the coupled system. The results indicate that licorice on the working surface was transported and separated by the topsoil’s holding effect and the front soil’s pushing effect; more than 70 % of the soil fell to the surface through the dispersion area, and the soil separation velocity in the dispersion area was lower than 0.3 m/s. When the harvester’s amplitude and forward speed increased, the licorice’s horizontal displacement was reduced, and the translational kinetic energy increased to obtain a strong transport ability. When the harvester’s amplitude and vibration frequency increased, the licorice’s separation velocity, the licorice force, and the rotational kinetic energy increased, and the relative motion between the licorice and shovel-rod working surface was violent, reducing the licorice’s buried mass. The forward speed has the greatest influence on the driving force of harvester. With an amplitude of 10 mm, a vibration frequency of 9 Hz, and a forward speed of 0.2 m/s, the shovel-rod working surface has a strong transporting ability for licorice, a strong relative motion, and a simulated licorice harvesting rate of 98.04 %. The field test results showed that the harvester worked smoothly, and the licorice harvesting rate was 97.26 %. The simulation model can predict the behavior rules of the coupled system. This study provides technical support for researching new principles and methods for deep-rooted crop harvesting.

Influence of external magnetic field on nanofluid dynamics using a two-phase Lattice Boltzmann Mixture Model at low Reynolds numbers

This work examines the behavior of an external magnetic field-induced Al2O3-water nanofluid flow between two parallel plates, with a particular emphasis on low Reynolds number scenarios. Understanding the dynamics of magnetohydrodynamic (MHD) flows in applications including energy systems, cooling systems, and medicinal devices depends on solving this problem. For the first time, a new two-phase lattice Boltzmann method was used to simulate the flow in conjunction with the mixture model. This methodology was specifically designed for nanofluid flow in the presence of magnetic field. Three coupled transport equations for flow velocity, concentration of nanoparticles, and magnetic field intensity are solved using this method. Three various cases were examined numerically. By comparing the simulated velocity profiles with analytical solutions in the first case, model validation was accomplished, demonstrating a strong agreement with less than 1 % variance. The impact of different inflow nanoparticle volume fractions (0.05 and 0.01) on the velocity field at various Reynolds numbers (0.5, 1, 10) and Hartmann numbers (0, 10, 20) was investigated in the second case. The findings showed that for Reynolds numbers of 0.5, 1, and 10, respectively, the velocity magnitude dramatically fell by approximately 75 %, 68 %, and 30 % as the Hartmann number grew from 0 to 20. Alongside this decrease, vortices began to form at Hartmann numbers of 10 and 20. Furthermore, the influence of the magnetic field diminished as the Reynolds number increased from 0.5 to 10, resulting in a noticeable reduction in vortex intensity. In the third case, where the nanoparticle volume fractions at the inlet were closer (e.g., 0.03 and 0.02), the intensity of the vortices decreased compared to the second case. The study demonstrates the robustness of the proposed model and its applicability across scientific and engineering domains. The novelty lies in quantifying MHD effects on nanofluid flow and particle distribution using a two-phase lattice Boltzmann approach, offering more precise and efficient simulations than existing methods. The findings provide new insights into the interaction between magnetic fields and nanofluids, especially at low Reynolds numbers, and emphasize the critical role of nanoparticle distribution in flow dynamics.

Structure of Multi-State Correlation in Electronic Systems.

Beyond the Hohenberg-Kohn density functional theory for the ground state, it has been established that the Hamiltonian matrix for a finite number (N) of lowest eigenstates is a matrix density functional. Its fundamental variable─the matrix density D(r)─can be represented by, or mapped to, a set of auxiliary, multiconfigurational wave functions expressed as a linear combination of no more than N2 determinant configurations. The latter defines a minimal active space (MAS), which naturally leads to the introduction of the correlation matrix functional, responsible for the electronic correlation effects outside the MAS. In this study, we report a set of rigorous conditions in the Hamiltonian matrix functional, derived by enforcing the symmetry of a Hilbert subspace, namely the subspace invariance property. We further establish a fundamental theorem on the correlation matrix functional. That is, given the correlation functional for a single state in the N-dimensional subspace, all elements of the correlation matrix functional for the entire subspace are uniquely determined. These findings reveal the intricate structure of electronic correlation within the Hilbert subspace of lowest eigenstates and suggest a promising direction for efficient simulation of excited states.

An explicit dynamics framework suited to highly non-smooth interface behaviors

Dynamic systems, and in particular mechanical structures, may be subjected to non-smooth loadings such as impacts or shocks. Moreover, their behavior itself may exhibit more or less non-smooth evolutions, as when fracture occurs. Therefore, robust simulation models are of interest to capture such behaviors. A particular focus is made herein on time-stepping explicit dynamics schemes to allow efficient simulations, and non-smoothness is embedded within the discrete resolution model, so that robust simulations can be obtained, with a minimum number of numerical parameters. The original contributions of this article lie in the way the non-smooth behavior is formulated to be embedded in an explicit dynamics framework. This study focuses on the solver for dynamics with non-smooth interface behavior, rather than on the behavior models themselves. The applications concern non-smooth interface behaviors at macroscopic scale, between displacement jump on the 2D interface surface with no thickness, and interfacial force distributions acting on the bodies apart the interface. The proposed test cases which can serve as benchmarks for simulation codes, concern in a first step contact and perfectly plastic interface behavior (for illustrative purpose, on a 0D example). The last numerical test deals with contact, friction, fracture and adhesion for an extrinsic perfectly brittle interface behavior, to exemplify the feasibility on a full 3D finite element model.