Direct Simulation Research Articles

Photodissociation Dynamics of Formic Acid at 230 nm: A Computational Study of the CO and CO2 Forming Channels.

Recent photolysis experiments with formic acid suggest that the roaming mechanism is a significant CO-forming pathway at a photolysis energy of 230 nm. While previous computational studies have identified multiple dissociation pathways for CO-forming channels, the dynamic features of these pathways remain poorly understood. This study investigates the dissociation dynamics of the CO + H2O and CO2 + H2 channels in the ground state (S0) of formic acid using direct dynamics simulation and the generalized multi-center impulsive model (GMCIM) at 230 nm. Computational results summarize the characteristics of the product states from six different dissociation pathways, including two roaming pathways. A comparison of the simulated speed distribution of CO products with experimental observations shows that high-rotational CO products predominantly originate from the three-center dissociation pathway. Furthermore, while experimental results reveal a bimodal speed distribution of CO at low rotational states, our findings suggest that the OH roaming pathway contributes to the fast component of this distribution, rather than the slow component. Furthermore, another isomerization-mediated four-center pathway contributes negligibly to the experimental results. The agreement between computational results and experimental observations at 230 nm supports the previously proposed dissociation mechanism of the CO + H2O channel. For the CO2 + H2 channel, this study provides useful information for experimental identification of dissociation pathways in the future.

Liquid-Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl3) Enabled by Machine Learning Interatomic Potentials.

Molten salts are promising candidates in numerous clean energy applications, where knowledge of thermophysical properties and vapor pressure across their operating temperature ranges is critical for safe operations. Due to challenges in evaluating these properties using experimental methods, fast and scalable molecular simulations are essential to complement the experimental data. In this study, we developed machine learning interatomic potentials (MLIP) to study the AlCl3 molten salt across varied thermodynamic conditions (T = 473-613 K and P = 2.7-23.4 bar), which allowed us to predict temperature-surface tension correlations and liquid-vapor phase diagram from direct simulations of two-phase coexistence in this molten salt. Two MLIP architectures, a Kernel-based potential and neural network interatomic potential (NNIP), were considered to benchmark their performance for AlCl3 molten salt using experimental structure and density values. The NNIP potential employed in two-phase equilibrium simulations yields the critical temperature and critical density of AlCl3 that are within 10 K (∼3%) and 0.03 g/cm3 (∼7%) of the reported experimental values. An accurate correlation between temperature and viscosities is obtained as well. In doing so, we report that the inclusion of low-density configurations in their training is critical to more accurately represent the AlCl3 system across a wide phase-space. The MLIP trained using PBE-D3 functional in the ab initio molecular dynamics (AIMD) simulations (120 atoms) also showed close agreement with experimentally determined molten salt structure comprising Al2Cl6 dimers, as validated using Raman spectra and neutron structure factor. The PBE-D3 as well as its trained MLIP showed better liquid density and temperature correlation for AlCl3 system when compared to several other density functionals explored in this work. Overall, the demonstrated approach to predict temperature correlations for liquid and vapor densities in this study can be employed to screen nuclear reactors-relevant compositions, helping to mitigate safety concerns.

Design and implementation of airborne information-energy integrated directional energy air combat simulation system

Design and implementation of airborne information-energy integrated directional energy air combat simulation system

Progressive Collapse of Steel Structures Under Blast Loads Considering Soil‐Structure Interaction

This study focuses on the effect of soil‐structure interaction on the occurrence of progressive collapse due to an external blast. Therefore, a 3‐story fixed base steel moment‐resisting frame structure was first modeled and subjected to an external blast load. Then, the same structure was modeled considering soil‐structure interaction. In another stage of this study, the effect of plan irregularity on progressive failure resulting from the explosion was investigated, assuming the presence or absence of soil‐structure interaction. The direct simulation method and alternative load path method are all employed to simulate the progressive collapse process of steel frames using the commercial finite element program LS‐DYNA. The results of the numerical simulations demonstrated that the presence of soil‐structure interaction, significantly influences the response of the structure to the blast and this interaction increases the likelihood of progressive failure occurring even at symmetric and asymmetric structures. It was also shown that silty sand soil yields more critical conditions than other types of soil in the event of failure after the occurrence of an explosion in the structure.

Calculation of radiation characteristics of shock heated air by Direct Simulation Monte Carlo method

The results of modeling the radiation characteristics of air behind the front of a strong shock wave, performed using the Direct Simulation Monte Carlo method, are presented. The model used takes into account various physical and chemical processes occurring in shock-heated air, including translational-rotational and translational-vibrational energy exchange, kinetics of chemical reactions, excitation of electronic levels of atoms and molecules, as well as emission and absorption processes for a discrete spectrum. As a result of the calculations, timeintegrated spectrograms of the volumetric radiation power of shock-heated air were obtained in absolute units in the range of shock wave velocities from 7.4 to 10.7 km/s at a gas pressure in front of the shock wave front of 0.25 Torr. The calculation data are compared with experimental data obtained on the double-diaphragm shock tube DDST-M of the Institute of Mechanics of Moscow State University.

Modeling of Surface Ablation for Hypersonic Reentry Vehicles Using Direct Simulation Monte Carlo Method

The surface ablation of hypersonic reentry vehicles is modeled at the microscopic level based on direct simulation Monte Carlo method with the open-source SPARTA code. The expression of surface recession rate is derived together with a new ablation rule, which enables a better description of the coupling process between surface ablation and flow. Additionally, the grid cell size independence of the ablation rate is reached, and satisfactory results are obtained for the test cases. The simulation results of the two-dimensional wedge indicate that ablation starts from the stagnation point at the front side while the flow region near the local roughness is highly rarefied. The reentry and ablation of a three-dimensional CubeSat is also simulated to show the effectiveness of the present ablation procedure and, at the same time, may provide practical guidance for end-of-life disposal schemes of in-orbit spacecraft.

Modeling Diffusive Motion of Ferredoxin and Plastocyanin on the PSI Domain of Procholorococcus marinus MIT9313.

Diffusion of mobile charge carriers, such as ferredoxin and plastocyanin, often constitutes a rate-determining step in photosynthetic energy conversion. The diffusion time scales typically exceed that of other primary bioenergetic processes and remain beyond the reach of direct simulation at the molecular level. We characterize the diffusive kinetics of ferredoxin and plastocyanin upon the photosystem I-rich domain of Prochlorococcus, the most abundant phototroph on Earth by mass. A modeling approach for ferredoxin and plastocyanin diffusion is presented that uses ensembles of coarse-grained molecular dynamics simulations in Martini 2.2P with GROMACS 2021.2. The simulation ensembles are used to construct the diffusion coefficient and drift for ferredoxin and plastocyanin as spatial functions in the photosystem I domain of the MIT9313 ecotype. Four separate models are constructed, corresponding to ferredoxin and plastocyanin in reduced and oxidized states. A single scaling constant of 0.7 is found to be sufficient to adjust the diffusion coefficient obtained from the Martini simulation ensemble to match the in vitro values for both ferredoxin and plastocyanin. A comparison of Martini versions (2.2P, 2.2, 3) is presented with respect to diffusion scaling. The diffusion coefficient and drift together quantify the inhomogeneity of diffusive behavior. Notably, a funnel-like convergence toward the corresponding putative binding positions is observed for both ferredoxin and plastocyanin, even without such a priori foreknowledge supplied in the simulation protocol. The approach presented here is of relevance for studying diffusion kinetics in photosynthetic and other bioenergetic processes.

Dependencies between effective parameters in coarse-grained models for phase separation of DNA-based fluids.

DNA is now firmly established as a versatile and robust platform for achieving synthetic nanostructures. While the folding of single molecules into complex structures is routinely achieved through engineering basepair sequences, very little is known about the emergence of structure on larger scales in DNA fluids. The fact that polymeric DNA fluids can undergo phase separation into dense fluid and dilute gas opens avenues to design hierachical and multifarious assemblies. Here, we investigate to which extent the phase behavior of single-stranded DNA fluids can be captured by a minimal model of semiflexible charged homopolymers while neglecting specific hybridization interactions. We first characterize the single-polymer behavior and then perform direct coexistence simulations to test the model against experimental data. While low-resolution models show great promise to bridge the gap to relevant length and time scales, obtaining consistent and transferable parameters is challenging. In particular, we conclude that counterions not only determine the effective range of direct electrostatic interactions but also contribute to the effective attractions.

Local Energy Minima and Density of Energy Barriers in Dense Clusters of Magnetic Nanoparticles

In this paper, we focus on the properties of local energy minima and energy barriers in immobilized dense clusters of magnetic nanoparticles. Understanding of these features is highly interesting both for the fundamental physics of disordered systems with long-range interparticle interaction and for numerous applications of modern ferrofluids consisting of such clusters. In particular, it is needed to predict the ac-susceptibility of these systems and their magnetization relaxation after a sudden change in the external field, because both processes occur via magnetization jumps over energy barriers that separate the energy minima. Due to the exponential increase in the corresponding jump time with barrier height (tsw∼exp(ΔE/kT)), direct Langevin dynamics simulations of this process are not feasible. For this reason, we have developed efficient numerical methods both for finding as many energy minima as possible and for the reliable evaluation of energy barriers between them. Our results for the distribution of overlaps between the local energy minima imply that there is no spin-glass state in such clusters even when they consist of particles with a small anisotropy. Further, we show that the distributions of energy barrier heights are qualitatively different for clusters of particles with small, intermediate, and large anisotropies, which has important consequences for the magnetization dynamics of these systems.

Characterization of Electrospun and Commercial Gas Diffusion Layers for PEMFC Using High-Resolution 3D Imaging and Direct Simulations

Characterization of Electrospun and Commercial Gas Diffusion Layers for PEMFC Using High-Resolution 3D Imaging and Direct Simulations

Sunflower Crop Yield Prediction Using Machine Learning Methods

Sunflower, one of the most important crops, is produced in many countries to meet especially for edible oil demand. Since the sunflower plant is affected by many factors, such as the amount of rain and air temperature, the yield changes from year to year, which has adverse effects on the balance between demand and supply. Because of the product produced in many countries is not enough; it has to be imported. Turkey is one of the world’s leading sunflower importers. The yield must be accurately estimated for the imported quantity to be correct. Importing in large quantities causes inventories, while small quantities cause the sunflower oil demand to not be met. It is used methods such as the direct method, simulation, and remote sensing to estimate sunflower yield. However, these methods have some shortcomings. In this article, machine learning methods, such as Artificial Neural Network, Decision Tree, Support Vector Machine and Random Forest, are used for production prediction. In order to increase the effectiveness of the methods, the values of the hyperparameters are determined by Halving Grid Search method that is tuning method. The methods were implemented in Edirne, which is among the province with the highest sunflower yield in Turkey. The results were evaluated with ANOVA method and performance evaluation metrics, RMSE, RRSE, AE, and R. Decision Tree method, providing the prediction with the lowest error, is determined a suitable method for sunflower yield prediction and then accurate buying decision making.

FOCUS GROUP DISCUSSION SEBAGAI METODE PENGENALAN SISTEM INFORMASI MANAJEMEN KKP BERBASIS WEB DI UNIVERSITAS ISLAM NEGERI MATARAM

This community service activity aims to introduce and introduce the web-based Practical Work Lecture (KKP) management information system at the State Islamic University (UIN) Mataram through the Focus Group Discussion (FGD) method. The activity, which was carried out on September 5, 2024, involved UIN Mataram lecturers who were directly involved in KKP management. In this activity, participants were given an explanation of the benefits and purposes of using a web-based information system, and were involved in a direct simulation to operate the system. The evaluation results showed a positive response from participants to the development of the system, with most feeling satisfied and ready to implement this system in KKP management. Through this activity, it is hoped that the KKP management information system can simplify and accelerate the KKP administration process at UIN Mataram, as well as support digital transformation in the academic environment.

Counseling on Optimizing Knowledge Sharing at MSMEs Sambal Ijo Bang Juna, Pematangsiantar City

This service activity aims to provide counseling regarding optimizing knowledge sharing at Sambal Ijo Bang Juna MSMEs in Pematangsiantar City. Knowledge sharing is important in developing small and medium businesses, especially in increasing efficiency and productivity. Through this outreach activity, MSME owners and employees can understand how to share knowledge effectively between fellow employees and business partners to create innovation and increase the competitiveness of green chili products. The method used in this activity is a participatory approach through discussion, training, and direct simulation. This counseling focuses on knowledge-sharing strategies, information management, and the application of simple technology that can support the knowledge-sharing process. The results of this activity will likely encourage Sambal Ijo Bang Juna MSMEs to be more adaptive to market changes and utilize their knowledge for product development and improving service quality.

Kinetic description of flow detachment at a smooth micro-step: the near-free-molecular regime

We study the pressure-driven steady gas flow, imposed by temperature or density gradients, over a backward-facing step in a two-dimensional microchannel. Focusing on the near-free-molecular regime of high Knudsen (Kn) numbers, the problem is analyzed asymptotically based on the Bhatnagar, Gross and Krook kinetic model, and supported by numerical Discrete Velocity Method and Direct Simulation Monte Carlo calculations. The wall conditions are formulated using the Maxwell model, superposing specular and diffuse surface conditions. The asymptotic solution contains the leading-order free-molecular description and a first-order integral representation of the near-free-molecular correction. Our results indicate that flow separation at the step can occur at arbitrarily large (yet finite) Knudsen numbers in channels with specular surfaces (i.e., having an accommodation coefficient of α=0), driven by temperature differences between the inlet and outlet reservoirs. It is then shown that detachment is significantly suppressed by density variations between reservoirs and partially diffuse surfaces (with α≳0.3). While the mass flow rate in a specular channel decreases with decreasing Kn≫1 in a density-driven setup (in line with the Knudsen Paradox), it increases in a temperature-driven flow. The results are obtained for arbitrary differences between the inlet and outlet reservoir equilibrium properties, and are rationalized using the linearized problem formulation.

The role of the hot porous layer in the gas flow in the inner coma

The objective of this work is to study the influence of a highly non-isothermal porous dust layer on the formation of a comet's inner coma. We studied the water gas activity of comet 67P/Churyumov-Gerasimenko to find a link between the gas properties around the comet and the properties of the dust surface crust. The effects on the radiative transfer spectral lines were studied and compared with MIRO remote sensing observations. For cases of spherical and complex nucleus shapes, we validated surface boundary conditions for gas flow obtained from the two-layer consistent thermophysical model. This model accurately estimates the properties of the sublimation products as the gas diffuses through the layer. The gas expansion was then modeled using a 3D parallel implementation of a direct simulation Monte Carlo algorithm. A multi-beam linear interpolation was used to extract the gas density, velocity, and temperature profiles along a given line of sight. Finally, the radiative transfer equation was used to calculate the brightness temperature of the water vapor. The presence of a porous layer results in an increase in gas temperature and a decrease in gas density at the surface. The gas has a greater acceleration due to the higher initial temperature and increased conversion of translational energy to kinetic energy. This reduces the difference in density between the different models, with the densest gas being the coolest, and increases the terminal expansion velocity of the hotter gas. While the gas density differences are small at large distances, the observable water absorption lines are significantly affected. The presence of a porous layer has a large effect on the properties of the gas in the coma, which can be seen by comparing the spectral lines. This demonstrates the potential interest of the approach in improving surface activity models and placing physical constraints on the dust layer.

Kinetic Theory of Self-Propelled Particles with Nematic Alignment.

We present the results from kinetic theory for a system of self-propelled particles with alignment interactions of higher-order symmetry, particularly nematic ones. To this end, we use the Landau equation approach, a systematic approximation to the BBGKY hierarchy for small effective couplings. Our calculations are presented in a pedagogical way with the explicit goal of serving as a tutorial from a physicists' perspective into applying kinetic theory ideas beyond mean-field to active matter systems with essentially no prerequisites and yield predictions without free parameters that are in quantitative agreement with direct agent-based simulations.

Direct simulation and machine learning structure identification unravel soft martensitic transformation and twinning dynamics

Phase transition between ordered phases has garnered attention from the viewpoint of materials science as well as statistical physics. One interesting example is martensitic transformation and the resulting formation of twin structures, in which atoms or molecules that form one crystalline phase move in a concerted and diffusionless manner toward another crystalline phase. Recently martensitic transformation has been observed experimentally also in various soft materials. However, the complex internal structures involving many molecules have eluded direct investigation of the dynamical processes of martensitic transformation. Here, we carry out a direct simulation of mesoscale structural transition of a liquid crystalline blue phase (BP) of cubic symmetry, known as BP II. The dynamics is simulated by a Langevin-type equation for the orientational order parameter with thermal fluctuations. We demonstrate that machine-learning-aided analysis of local structures successfully unravels the transformation process from a perfect lattice of BP II to a twinned lattice of another BP (BP I). The nucleation of BP I is initiated by the breakup of junctions of line defects (disclinations), followed by the deformation of disclination network. We further show that twinned BP I is reversibly transformed to a perfect lattice of BP II by temperature variation. Order-parameter-based simulations with machine-learning-aided local structure identification provide valuable insights into not only the martensitic transformation of soft materials but also a wider class of complex structural transitions between ordered phases.

The optimization of phase change heat transfer model for direct contact condensation heat transfer simulation based on Bayesian inversion method

Direct contact condensation heat transfer between steam and water is widely applied across various industries. The utilization of phase change models significantly influences the precision of numerical simulation outcomes in this domain. This study presents numerical simulations of direct contact condensation between steam and liquid films generated by nozzles. Employing Bayesian inversion method, this research conducts optimizations on the Lee and Schrage models and examines the impact of varying treatments of interface area density. Additionally, it proposes enhancements to these methodologies. The findings of this study are expected to foster a more profound comprehension of phase change models and their role in numerical simulations.

Aerothermodynamics of a sphere in a monatomic gas based on ab initio interatomic potentials over a wide range of gas rarefaction: subsonic flows

Aerothermodynamic characteristics of a sphere in a subsonic flow are calculated over a broad range of gas rarefaction by the direct simulation Monte Carlo method based on ab initio interatomic potentials and Cercignani–Lampis surface scattering kernel. Calculations of the drag and average energy transfer coefficients are performed for various noble gases in the range of Mach number from 0.1 to 1. The obtained results point out that the influence of the interatomic potential is weak in subsonic flows. A comparison of the present results with a linear theory shows that the numerical solutions at Mach number equal to 0.1 are close to those obtained from the linearized kinetic equation in the transitional and free-molecular regimes. In the near-continuum flow regime, the difference between the present solution and the linear theory is significant. To reveal the effects of the gas–surface accommodation, a few sets of the tangential momentum and normal energy accommodation coefficients are considered in simulations. It is shown that the effect of the accommodation coefficients on the sphere drag is not trivial, and, for non-diffuse scattering, the drag coefficient can be either larger or smaller than that for diffuse scattering. The effect of the sphere temperature is also investigated and the calculated values of the average energy transfer coefficient are used to find the Stanton number, recovery factor and adiabatic surface temperature. The numerical results for the sphere drag and energy transfer are compared with the semi-empirical fitting equations known from the literature.

Solitons in composite linear-nonlinear moiré lattices.

We produce families of two-dimensional gap solitons (GSs) maintained by moiré lattices (MLs) composed of linear and nonlinear sublattices, with the defocusing sign of the nonlinearity. Depending on the angle between the sublattices, the ML may be quasiperiodic or periodic, composed of mutually incommensurate or commensurate sublattices, respectively (in the latter case, the inter-lattice angle corresponds to Pythagorean triples). The GSs include fundamental, quadrupole, and octupole solitons, as well as quadrupoles and octupoles carrying unitary vorticity. Stability segments of the GS families are identified by means of the linearized equation for small perturbations, and confirmed by direct simulations of perturbed evolution.