Macroscopic Simulation Research Articles (Page 1)

With the continuous improvement of national economic strength, the transportation field has also been developed at an unprecedented speed, and the transportation system simulation is an important technology and method in the field of transportation engineering. Establishing rele-vant models through traffic system simulation can not only improve the efficiency of urban traf-fic utilization in urban planning, but also optimize some existing traffic problems and promote the sustainable development of the traffic field. This paper first describes the specific concept of the traffic system simulation model, and discusses the development status of the traffic system simulation model from the microscopic traffic simulation model, the mesoscopic traffic simula-tion model, and the macroscopic traffic simulation model, as well as the characteristics and dif-ferences of the three types of models. Finally, it selects examples of each type of simulation model for specific analysis. The overview of the traffic system simulation model can improve the public's awareness of the traffic system simulation and help the specific development of urban traffic.

Slow wave dynamics of scalp EEG can be explained by simple statistical models of long-range connections.

During the laser cladding process, the distribution of the temperature field directly influences the morphology, microstructure, and residual stress state of the cladding layer. However, the process involves transient characteristics of rapid heating and cooling, making it challenging to study temperature field variations directly through experimental methods. Therefore, numerical simulation has become a crucial tool for gaining a deeper understanding of the laser cladding mechanism, providing theoretical basis and guidance for optimizing process parameters. This study systematically integrates COMSOL Multiphysics coupling simulation with Jmatpro material thermal property data to perform simulations of temperature field evolution, melt pool flow behavior, and Marangoni effects during laser cladding of nickel-based alloy (IN718) onto an EA4T steel substrate. It highlights the influence patterns of different process parameters (e.g., laser power, scanning speed) on the temperature gradient and flow characteristics of the molten pool, providing an in-depth theoretical basis for understanding the formation mechanism of the molten pool and microstructure control.

Objective.DNA damage, particularly double-strand break (DSB), is the primary mechanism for cell death in radiation therapy. High-linear energy transfer particles, like protons and helium ions, induce more complex DSB than photons, increasing their biological effectiveness. Simulating particle transport at the DNA level with Monte Carlo (MC) codes is computationally intensive, often limiting studies to single cells. This study presents an efficient method using the microdosimetric gamma model (MGM) to estimate DSB numbers and complexity in macroscopic setups.Approach.The MGM analytically predicts the number of DSBs and their complexity induced by protons orα-particles. We integrated it into the TOPAS MC toolkit (TOPAS-MGM), enabling the calculation of DNA damage at macroscale scenarios. We have calculated DNA damage distributions inin-vitro-like geometries and water phantoms with proton and helium beams.Results.Cross-comparisons with TOPAS-nBio show that the DNA damage outputs from macroscopic simulations are consistent and 100 000 times faster than DNA scale simulations. We tested DNA damage induction with proton and helium ion beams and alpha-emitting radiopharmaceuticals. For clinical beams, the DNA along the beam path showed a significant increase in the number of induced DSB and their complexity at the Bragg peak, especially with helium ions. Radiopharmaceuticals induced a markedly heterogeneous number of damages compared to beams.Significance. This work offers a method to simulate DNA damage and its complexity in macroscale scenarios for protons andα-particles. The output could potentially be used to predict cell killing based on DNA repair models or to assess the biological effectiveness of particle therapy using DNA damage and complexity as key metrics.

Nanopores evolve in dealloying to dictate alloy corrosion while enabling the creation of functional metallic nanomaterials. Yet, the nanoscale dynamics of the porosity evolution have long eluded experimental characterizations. With aberration-corrected transmission electron microscopy, we reveal the evolution of nanoporous Co from the vapor phase dealloying (VPD) of γ-CoZn across scales. The insitu characterization confirms key aspects of the dealloying mechanism based on macroscopic characterizations and simulations, including dissolution by repeated step flow and vacancy-cluster nucleation as well as ligament and pore bifurcation. It also separates the step flow kinetics from that of VPD, revealing that a bond energy difference between the alloy constituents can determine the dealloying kinetics and affect the morphology. The findings refine the classic dealloying theory for potentially new fabrications.

The digital transformation of the transport sector in our cities will be led by the deployment of large-scale digital twins, interacting with their real world counterpart to model, predict, and improve movements and reoccurring patterns. Traffic simulation is an essential tool in this area. While both macroscopic and microscopic simulations are possible, only the latter provide enough detail to realize sophisticated Intelligent Traffic Systems (ITS).One of the biggest challenges is accurately modeling road traffic on a large scale due to limitations in both reliable data sources, as well as the quickly increasing complexity of size. Only a handful of city-scale traffic scenarios exist, and only a few of them include public transport modalities. With this paper, our aim is to extend this list by integrating bus traffic within the Berlin SUMO Traffic scenario (BeST). We provide an overview of potential data sources and a detailed description of the applied methodology. As the scenario was initially calibrated with only individual private traffic, we conduct an evaluation on how the added traffic volume affects the stability of the scenario.

Macroscopic models of inertial flows in porous media have many practical applications where direct numerical simulations are not feasible. The Forchheimer equation describes macroscopic momentum transport accounting for inertial effects at the pore scale through a nonlinear correction tensor Fβ to the permeability. The goal of this work is to study the effects of inertial flow orientation on the Forchheimer correction. Using up-scaling approaches such as the volume averaging method, Fβ can be determined. However, the procedure requires to deal with a nonlinear problem for the deviations of the local velocity field. This is commonly tackled by assuming that the inertial convective velocity is decoupled from the velocity deviations. Here, we propose an alternative approach based on regular perturbation expansion leading to a series of linear closure problems. The values of Fβ predicted by both approaches are compared for various values of the Reynolds number and flow orientation. Compared to the local inertial–convection approach, the proposed linearized closure problem has the advantage of being self-consistent, independent of the pore Reynolds number and of flow orientation. It is, however, limited in validity by Reynolds number below one and requires the solution of closure problems of higher dimensions. Then, macroscopic simulations are performed to evaluate the importance of varying pressure gradient orientation on the macroscopic inertial flow. Numerical results of the general macroscopic model obtained by the volume averaging method highlight the necessity to account for extra-diagonal terms as well as macroscopic gradient orientation in the determination of the Forchheimer tensor.

Microfluidic chips represent visualization-enabled miniaturized analytical platforms that serve as powerful investigative tools for multiscale process characterization, enabling multiscale analysis from pore-level processes to macroscopic system behaviors. These systems provide high-resolution insights into fluid–rock interactions within geological formations, where multiphase flow dynamics and biogeochemical processes fundamentally control hydrocarbon recovery efficiency and subsurface storage performance. At the microscale, fluid–solid interfacial phenomena dictate multiphase displacement mechanisms across diverse lithologies, while microfluidic platforms accurately replicate subsurface flow conditions in hydrocarbon reservoirs, coal seams, and gas-bearing formations through geometrically constrained microenvironments. This review systematically examines the technological implementation of microfluidic chips in subsurface reservoir engineering, specifically categorized into four strategic areas: geological carbon sequestration, underground hydrogen storage, gas hydrate/coalbed methane extraction, and enhanced oil recovery. Across these applications, microfluidic systems primarily function to decode immiscible fluid displacement physics under reservoir-relevant conditions. Systematic investigations have identified critical governing factors including interfacial wettability, viscosity contrast, injection dynamics (flow rate/pressure), thermodynamic conditions, pore-throat geometry, surface morphology, reservoir heterogeneity, and microbial mediation. Integration of these microscale findings enhances predictive capabilities in macroscopic simulations such as core flooding experiments and reservoir-scale flow modeling, ultimately advancing strategic optimization of energy resource management and environmental sustainability at engineering-relevant scales. Meanwhile, microchips face challenges such as scale mismatch and limited material performance in actual geological simulations. In the future, technological innovation in the field of energy geology can be promoted by developing high-performance chip materials and establishing multiscale coupling experimental platforms.

We perform detailed macroscopic simulations of high harmonic generation in a He gas cell by combining a few-cycle, carrier-envelope-phase-stabilized 4-µm driving laser pulse with a single-cycle, 400-nm pulse, demonstrating that the two-color laser configuration significantly boosts harmonic generation efficiency in the 1.05-1.25 keV photon-energy range compared to a single-color scheme. Additionally, we show that isolated keV attosecond pulses can be successfully produced through the combined approach of phase matching and two-color waveform control.

Estimating the Effects of Autonomous Vehicle-Exclusive Underground Roadways Using Microscopic–Macroscopic Simulation Analysis

In the steel industry, small billets have become the main type of billet for steel production due to the efficiency of the continuous casting process. However, the segregation that occurs during solidification remains a significant issue affecting billet quality. This study conducted a macroscopic segregation analysis on 172 mm × 172 mm small square billets and investigated the influence of various process parameters on the distribution of carbon within the cast billets. The results showed that an increase in superheat led to a 0.036% rise in the carbon difference and an increase in the central segregation value from 0.357% to 0.364%. Increasing the cooling intensity resulted in a 0.037% rise in the carbon difference and a decrease in the negative segregation value from 0.266% to 0.250%. Higher casting speeds caused the carbon difference to reach a minimum of 0.107% at a speed of 1.6 m·min−1, while the central segregation value reached its lowest point of 0.353% at a casting speed of 2.6 m·min−1.

Traffic flow phenomena in large sporting events — Empirical analysis and macroscopic simulation of the Vasaloppet

PCEs and HPMC are vital to PVA-FRC, where imbalance causes bleeding and viscosity issues, affecting fiber distribution and performance. This study investigates the synergistic mechanisms of PCEs and HPMC on fiber dispersion and mechanical properties through macroscopic experiments and microscopic simulations. Experimental results show that an increase in HPMC dosage or a decrease in PCE dosage reduces fiber uniformity. The mechanical properties of PVA-FRC are influenced by multiple factors, leading to complex non-linear trends. The best performance is achieved when PCE is 0.4% of cement mass and HPMC does not exceed 0.1%. Molecular dynamics simulations show that PCEs and HPMC influence the hydration behavior of C.S.H. gel, transforming it from a single-point adsorption mode to a multi-point adsorption mode. PCEs promote fluidity by displacing water molecules from the active sites, while HPMC forms charge transfer complexes with C.S.H. gel, preventing gel particle aggregation and improving the slurry's viscosity and stability.

A comprehensive understanding of thermal transport properties at the material level for Lithium-ion batteries (LIBs) is often overlooked, despite being crucial for accurately reconstructing thermal behavior in macroscopic simulations for LIBs. To address this gap, a nitrogen-protected testing method integrated with an electrochemical cycling platform is first developed to measure the intrinsic thermal conductivity (k) of the electrodes and separator in LIBs, as well as the thermal contact resistance (R c) between them. The effects of the state of charge (SOC) and the charging rate (C-rate) on both k and R c are systematically evaluated, and the constituent of internal thermal resistance within the unit battery is clarified in detail. Results reveal that the k of the cathode increases monotonically with SOC, while the k of the anode exhibits a non-monotonic relationship whose trend depends on the C-rate. Notably, the R c between electrodes and separator, which constitutes the nonnegligible component of total thermal resistance, is marginally affected by SOC but increases significantly with higher C-rate. Additional experiments examining the effects of the testing environment underscore the necessity of nitrogen protection for accurate measurements of thermal transport properties. These findings provide valuable insights for improving thermal management strategies of LIBs in real-world applications.

Macroscopic simulation of hydrogen diffusion across the grain-boundary networks in cold-sprayed Ti6Al4V

It has been discovered that the surface passivation degree of aluminum nanoparticles (ANPs) is closely related to the melting point, and it is possible to quantify the equivalent relationship between the surface passivation properties of ANPs coated with organic acids and ANP oxidation. The Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is applied to study the passivation mechanism of palmitic acid adsorption on the ANP surface, and further completed the molecular dynamic simulation of ANP phase transition with different palmitic acid-coating degrees and oxidation degrees. It is found that the microscopic angle quantification of palmitic acid using single-molecule simulations is very effective for the passivation simulations of ANP surfaces. However, in the macroscopic quantitative verification simulation of ANPs’ melting point, it is found unexpectedly that the melting point of ANPs would decrease with the increase in palmitic acid coating degree. Interestingly, this was exactly the opposite of the expected trend. Therefore, we also drew the conclusion that although the organic acid coating completed the surface passivation of ANPs on the micro level, it increased the reactivity of ANPs on the macro level.

This study investigates the effects of composite surfactants on the wettability of different coal types using a combination of macroscopic experiments, mesoscopic experiments, and microscopic molecular dynamics simulations, with coal samples of varying degrees of metamorphism as research subjects. First, contact angle and surface tension experiments were performed at the macroscopic level to determine the optimal concentration and ratio of the composite surfactants. The results showed that the composite solution formed by mixing SLES and AEO-9 in a 3:2 ratio significantly reduced both the surface tension of the solution and the contact angle of the coal samples at a mass concentration of 0.5 wt %. Second, the effects of the composite surfactants on the wetting properties of coal samples were analyzed at the mesoscopic level using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and ζ-potential measurements. The results revealed that the total content of hydrophobic groups (-CH3, -CH3&-CH2, C=C) in the coal molecules was significantly reduced after treatment with the composite solution, weakening the hydrophobicity of the coal samples. Additionally, the absolute value of the surface potential of the coal samples was significantly decreased, enhancing the aggregation tendency between coal particles. This facilitated the formation of larger agglomerated coal particles, which contributed to the settling of coal dust. Simultaneously, the cracks between coal particles promoted the penetration of aqueous solutions, aiding in the wetting of the coal seam. Finally, molecular dynamics simulations were conducted to analyze the synergistic wetting mechanism of the composite surfactants at the microscopic level. The results showed that the composite surfactant molecules were effectively adsorbed onto the surface of coal molecules, facilitating the movement of water molecules to the coal surface, increasing the diffusion coefficient of water molecules, and enhancing the interaction energy within the coal/composite surfactant/water system. These findings provide valuable insights for the development of new composite surfactants with wetting effects, offering significant potential for applications in mine dust control.

This study develops a hybrid multiscale Euler–Lagrange model to investigate the unsteady characteristics of cloud cavitation around a hydrofoil under different water qualities. A homogeneous mixture model is implemented for macroscopic cavity simulations, tracking the vapor–liquid interfaces. In the Lagrangian framework, the dynamics and motion of nuclei and bubbles are resolved. By incorporating more physically accurate conversion criteria to couple the two frameworks, the cavitation model is modified to ensure consistency with the assumption that cavitation inception arises from the expansion of nuclei. Numerical results, obtained under different size distributions of nuclei populations, align well with experimental data, validating the capability of the multiscale model to account for the effects of water quality. They also offer detailed insights into the influence of cavitation flows on microscale bubble behavior, particularly highlighting the significant role of reentry jets in bubble generation and motion. The results underscore the critical interplay between small-scale bubble dynamics and macroscopic cavitation flows. In addition, a statistical analysis of the size distribution of microbubbles reveals a distribution law consistent with experimental observations. This study provides a robust framework for investigating the comprehensive effects of water quality on cloud cavitation flows, offering a promising avenue for future research in this domain.

The Fused Filament Fabrication process (FFF) is an additive manufacturing process for thermoplastic polymers based on material extrusion. It offers a large range of material options and high potential for manufacturing parts with complex geometry. Mechanical properties of parts produced with this method are, however, highly anisotropic and depend on process parameters and resulting inner mesostructures. The relationships between process parameters, mesostructures and mechanical properties are complex. Characteristics of the FFF mesostructures, such as voids and the interfaces between filaments, cannot yet be sufficiently taken into account in macroscopic design methods. In this work, a method for homogenising mechanical properties is developed. This is based on the inner FFF mesostructure: shape and size of the voids are determined using micrographs and the size of the coalescence areas between the filaments is also estimated. Representative volume elements with periodic boundary conditions are then created in a finite element environment and homogenised mechanical properties are derived. These are compared with analytical and experimental values, and the results are discussed. The method presented here provides an approach on how different characteristics of FFF mesostructures can be transferred to macroscopic simulations. Results of the numerical approach are in good agreement with the experimental data.

As autonomous driving technology advances, connected and autonomous vehicles (CAVs) will coexist with human-driven vehicles (HDVs) for an extended period. The deployment of CAVs will alter traffic flow characteristics, making it crucial to investigate their impacts on mixed traffic. This study develops a hybrid control framework that integrates a platoon control strategy based on the "catch-up" mechanism with lane management for CAVs. The impacts of the proposed hybrid control framework on mixed traffic flow are evaluated through a series of macroscopic simulations, focusing on fundamental diagrams, traffic oscillations, and safety. The results illustrate a notable increase in road capacity with the rising market penetration rate (MPR) of CAVs, with significant improvements under the hybrid control framework, particularly at high MPRs. Additionally, traffic oscillations are mitigated, reducing shockwave propagation and enhancing efficiency under the hybrid control framework. Four surrogate safety measures, namely time to collision (TTC), criticality index function (CIF), deceleration rate to avoid a crash (DRAC), and total exposure time (TET), are utilized to evaluate traffic safety. The results indicate that collision risk is significantly reduced at high MPRs. The findings of this study provide valuable insights into the deployment of CAVs, using control strategies to improve mixed traffic flow operations.