Mesoscale Simulations Research Articles

Mesoscale formation and energy release characteristics of PTFE/Al reactive jet

AbstractIn order to investigate the mechanical formation, the mechanical‐thermo coupling mesoscale mechanism and the corresponding energy release characteristics of PTFE/Al composite material reactive jet, a mesoscale discretization model of PTFE/Al reactive liner with a mass ratio of 73.5 %/26.5 % is developed on the basis of the random delivery principle. The mesoscale numerical simulation is used to perform PTFE/Al reactive jet formation, obtaining the relative distribution characteristics of material, pressure, and temperature. The overpressure experiments for the energy release of reactive jets are conducted. The results show that there is an increasing tendency in the amount of Al particles from the jet's tip to its tail due to the velocity variance between PTFE and Al. The high temperature zones are found to be concentrated on the tip and axis of the jet, with particle deformation, collision and friction in the reactive jet accounting for the temperature rise. Moreover, the Al particle size has a significantly influence on the particle distribution and the mechanical‐thermo coupling behavior in the reactive jet, and the decrease of particle size is beneficial to the chemical reaction among the components of the reactive jet. To be more specifically, under the conditions of Al particle size of 400 μm, 600 μm and 800 μm, the overpressure peaks of reactive jet in 13 L chamber are 3.32 MPa, 2.86 MPa and 2.61 MPa, respectively. The variation of the overpressure with Al particle size obtained by experiment is consistent with the analysis of the mechanical‐thermo coupling characteristics of mesoscale numerical simulation.

Modeling fission gas release at the mesoscale using multiscale DenseNet regression with attention mechanism and inception blocks

Mesoscale simulations of fission gas release (FGR) in nuclear fuel provide a powerful tool for understanding how microstructure evolution impacts FGR, but they are computationally intensive. In this study, we present an alternate, data-driven approach, using deep learning to predict instantaneous FGR flux from 2D simulated nuclear fuel microstructure images. Four convolutional neural network (CNN) architectures with multiscale regression are trained and evaluated on simulated FGR data generated using a hybrid phase field/cluster dynamics model. All four networks show high predictive power, with R2 values above 98%. The best performing network combines a Convolutional Block Attention Module (CBAM) and InceptionNet mechanisms to provide superior accuracy (mean absolute percentage error of 4.4%), training stability, and robustness on very low instantaneous FGR flux values. The trained model demonstrates the utility of deep learning in this context, but has no validity outside the 2D model and conditions used to generate the training data.

Mesoscale modelling and simulation of irradiation-induced expansion in concrete

The effects of irradiation on concrete is a topic of concern in nuclear applications, where for some specific members the material may be exposed at long-term to significant levels of neutron radiation. In this study, the effects of radiation-induced volumetric expansion (RIVE) of aggregates on concrete behaviour are investigated numerically at the mesoscale. Cylindrical concrete specimens constituted of 3 phases, namely mortar matrix, polyhedral aggregates and interfaces between both of these phases, are generated in 3D. Besides RIVE of aggregates, temperature increase due to the energy deposited during the irradiation, drying and damage development are considered in the finite element simulations. A phase-field approach and a cohesive-zone model are applied to describe damage in the matrix and interfaces, respectively. The simulation results are compared to experimental data of concrete specimens exposed to significant neutron fluences exceeding 6 × 10–19 n/cm2, in terms of residual Young modulus, compressive strength, temperatures evolution and overall expansion of the specimens. Globally, with an adequate calibration of parameters and in particular those related to the damage evolution laws, the simulation results of residual mechanical properties are in relatively good agreement with the experimental data. In addition, specimen expansions are well reproduced, providing that RIVE effects are also considered for the mortar phase, which is justified by the significant volume fraction of embedded sand grains. Mortar RIVE is modelled with the same approach as aggregate RIVE by applying a proportionality parameter, whose effect is discussed. Finally, simulations predict an intense drying of the specimens due to temperature increase.

Impact of Model Resolution and Initial/Boundary Conditions in Forecasting Low-Level Atmospheric Fields over the Incheon International Airport

Abstract This study investigates the impact of initial conditions/boundary conditions (ICs/BCs) and horizontal resolutions on forecast for average weather conditions, focusing on low-level weather variables such as 2-m temperature (T2m), 2-m water vapor mixing ratio (Q2m), and 10-m wind speed (WS10). A Weather Research and Forecasting (WRF) Model is used for regional mesoscale model simulations and large-eddy simulations (LESs). The 6-h-interval forecast fields generated by the Global Forecast System of the National Centers for Environmental Prediction and the Korean Integrated Model of the Korea Meteorological Administration are utilized as ICs/BCs for the regional models. Numerical experiments are performed for 24 h starting at 0000 UTC on each day in April 2021 when the average monthly wind speed was strongest during 10 years (2011–20). A comparison of model simulations with observations obtained around the Yeongjong Island, where Incheon International Airport is situated, shows that the regional models capture the time series of T2m, Q2m, and WS10 more effectively than the global model forecasts. Moreover, the LES experiments with a 100-m horizontal grid spacing simulate higher Q2m and lower WS10 during the daytime compared to the 1-km WRF. This results in a deterioration of their time-series correlation with the observations. Meanwhile, the 100-m LES forecasts time series of T2m over ocean stations and Q2m over land stations, as well as probability density functions of low-level weather variables, more accurately than that of the 1-km WRF. Our study also emphasizes the need for caution when comparing high-resolution model results with observation values at specific stations due to the high spatial variability in low-level meteorological fields.

Mesoscale and Large-Eddy Simulation of the Boundary-Layer Process of Cumulus Development over Naqu, Tibetan Plateau Part B: The Low-level Baroclinic Vortex and its Contribution to Cumulus Clouds Formation

Mesoscale and Large-Eddy Simulation of the Boundary-Layer Process of Cumulus Development over Naqu, Tibetan Plateau Part B: The Low-level Baroclinic Vortex and its Contribution to Cumulus Clouds Formation

Framework for integrated multi-scale computational fluid dynamics simulations in natural ventilation design

The wind flow field constitutes an important input parameter for computational fluid dynamics (CFD) simulations that are used in architectural design for the design and analysis of natural ventilation strategies. Despite indications that the wind flow field may vary between places, CFD simulations that do not adequately account for this potential variation are still commonplace. This may significantly compromise the integrity and accuracy of the CFD simulations. This study was a two-pronged investigation with the ultimate objective of contributing towards efforts aimed at improving the accuracy of the CFD simulations. Firstly, a framework for integrated meso-scale and micro-scale CFD simulations was developed. Secondly, the newly developed framework was then implemented by deploying it to study the variation of the wind flow field between a reference meteorological station, and a selected local building site. The findings confirmed the indications that the wind flow field might vary spatially. The integrated multi-scale framework that was developed as part of the study was not only able to capture the wind flow field variation, but it also provided a way to quantify it, ultimately, leading to the generation of a more accurate wind flow field characterization representative of the local conditions. Through its ability to integrate multiple spatial scales that typically influence one another, this framework can help to enhance the accuracy and integrity of the CFD simulations that are used for natural ventilation design. Practical application: The findings from this study can be particularly useful when undertaking spatially integrated CFD simulations to design and analyse natural ventilation strategies in the building design process.

Vapor bubble nucleation in flowing liquids

In this work, a stochastic diffuse interface model coupled with the Navier–Stokes equations has been exploited to numerically investigate vapor nucleation in a non-equilibrium system (a flowing liquid). Both homogeneous and heterogeneous nucleation is addressed and the influence of macroscopic flows on nucleation observables is discussed. The extended mesoscale simulations allow us to infer the spatial distributions of the nucleated bubbles via Voronoi tessellation analysis and to represent the nucleation phenomenon as a stochastic Random Poisson Point process. The findings open the way to design multiscale fluid simulations experiencing phase change.

The acquisition and calibration of coarse-grained force field parameters for graphene/nitrile rubber nanocomposites

Graphene (GNS) is an ideal reinforcing material for developing high-performance nitrile rubber (NBR) nanocomposites to withstand complex and harsh working conditions. The mesoscale molecular simulation is significant in exploring the microscopic mechanism of nanocomposites. Initially, a coarse-grained (CG) scheme for NBR was established, and the potential parameter files were obtained through the iterative Boltzmann inversion method. Then, the bond and angle parameters were fitted by harmonic potential, the non-bonded interactions were fitted by LJ 12–6 potential. The CG force field parameters were coefficients of the potential function. The parameters such as the stiffness values, potential well parameter, etc., were calibrated by stretching the NBR molecular chains, and comparing the density and stretching performances of the NBR all-atomic and CG models. A rapid method for obtaining the non-bonded parameters between NBR and GNS was proposed based on the radial distribution function curves. The non-bonded parameters were calibrated by comparing GNS pull-out simulations, and the density and tensile properties of the GNS/NBR models. Finally, the CG force field parameters applicable to the GNS/NBR nanocomposites were obtained. The study is expected to be significant for subsequent mesoscale studies on GNS/NBR nanocomposites.

Weak shock compaction on granular salt

This study conducted integrated experiments and computational modeling to investigate the speeds of a developing shock within granular salt and analyzed the effect of various impact velocities up to 245 m/s. Experiments were conducted on table salt utilizing a novel setup with a considerable bore length for the sample, enabling visualization of a moving shock wave. Experimental analysis using particle image velocimetry enabled the characterization of shock velocity and particle velocity histories. Mesoscale simulations further enabled advanced analysis of the shock wave’s substructure. In simulations, the shock front’s precursor was shown to have a heterogeneous nature, which is usually modeled as uniform in continuum analyses. The presence of force chains results in a spread out of the shock precursor over a greater ramp distance. With increasing impact velocity, the shock front thickness reduces, and the precursor of the shock front becomes less heterogeneous. Furthermore, mesoscale modeling suggests the formation of force chains behind the shock front, even under the conditions of weak shock. This study presents novel mesoscale simulation results on salt corroborated with data from experiments, thereby characterizing the compaction front speeds in the weak shock regime.

Multiscale Modeling of CO2 Electrochemical Reduction on Copper Electrocatalysts: A Review of Advancements, Challenges, and Future Directions.

Although CO2 contributes to global warming, it also offers potential as a raw material for the production of hydrocarbons (CH4, C2H4 and CH3OH). Electrochemical CO2 reduction reaction (eCO2RR) is an emerging technology that utilizes renewable energy to convert CO2 into valuable fuels, solving environmental and energy problems simultaneously. Insights gained at any individual scale can only provide a limited view of that specific scale. Multiscale modeling, which involves coupling atomistic-level insights (DFT) and (MD), with mesoscale (KMCand MK) and macroscale (CFD) simulations, has received significant attention recently. While multiscale modeling of eCO2RR on electrocatalysts across all scales is limited due to its complexity, this review offers an overview of recent works on single scales and the coupling of two and three scales, such as "DFT+MD", "DFT+KMC", "DFT+MK", "KMC/MK+CFD" and "DFT+MK/KMC+CFD", focusing particularly on Cu-based electrocatalysts. This sets it apart from other reviews that solely focus exclusively on a single scale or only on a combination of DFT and MK/KMC scales. Furthermore, this review offers a concise overview of machine learning (ML) applications for eCO2RR, an emerging approach that has not yet been reviewed. Finally, this review highlights the key challenges, research gaps and perspectives of multiscale modeling for eCO2RR.

Adversarial image-to-image model to obtain highly detailed wind fields from mesoscale simulations in mountainous and urban areas

The characterisation of wind is of great interest in multiple disciplines such as city planning, pedestrian comfort and energy generation. We propose a conditional Generative Adversarial Network (cGAN), based on the Pix2Pix model [1], that can generate detailed local wind fields in areas with complex orography or an urban layout, which are comparable in level of detail to those from Computational Fluid Dynamics (CFD) simulations, from coarser Numerical Weather Prediction (NWP) data.

Jaime Milla - Adversarial image to image model to obtain highly detailed wind fields from mesoscale simulations in mountainous and urban areas

Jaime Milla - Adversarial image to image model to obtain highly detailed wind fields from mesoscale simulations in mountainous and urban areas

Mechanism analysis on tensile fracture properties of heterogeneous BFLAC at cryogenic temperature: Experimental investigation and mesoscale simulation

This study aims to investigate the tensile failure behaviours and corresponding fracture mechanisms of basalt fiber reinforced lightweight-aggregate concrete (BFLAC) at various temperatures via a comprehensive cryogenic tests and mesoscale simulations, with a special focus on the quantitative effects of cryogenic temperature and fiber volume fraction. Firstly, Macro- and micro-scale split-tensile tests of BFLAC with fiber volume fractions of 0.0–0.3 % at 20∼-90 °C were conducted. Secondly, a two-steps sequentially thermo-mechanical coupled meso-scale analysis approach with explicit modelling of fibers and pore ice was developed to simulate the corresponding direct-tensile failures of BFLAC with more fiber volume fractions. The results show that as the temperature falls from 20 °C to −90 °C, the dominant action mechanism of basalt fibers changes from Mode-1 (pull-out of fibers) to Mode-2 (rupture of fibers) due to the ice formation and the interactions between meso-components. Tensile strengths of BFLAC present a significant low-temperature enhancing effect, with a maximum increase of 90 % for direct-tensile strength while 104 % for split-tensile strength. Besides, as the temperature drops, although a larger proportion of fibers are in a low bridging stress state and a smaller proportion reach yield stress for rupture, the average fiber stress increases and the utilization degree of fibers with more stresses transferred improves, which results in that the fiber reinforcement effect is strengthened. Finally, based on experimental and numerical results, the quantitative relationships between split-tensile and direct-tensile strengths at different cryogenic temperatures were given. The present research results can better understand the cryogenic mechanical properties of BFLAC, which have important reference value for its extensive promotions and applications in engineering structures exposed to extreme low-temperature environments.

Improving the Modeled Variability Estimates of Offshore Winds in Northern Europe by Nudging ASCAT-Derived Winds

Abstract The paper aims to demonstrate how to enhance the accuracy of offshore wind resource estimation, specifically by incorporating near-surface satellite-derived wind observations into mesoscale models. We utilized the Weather Research and Forecasting (WRF) Model and applied observational nudging by integrating ASCAT data over offshore areas to achieve this. We then evaluated the accuracy of the nudged WRF Model simulations by comparing them with data from ocean oil platforms, tall masts, and a wind lidar mounted on a commercial ferry crossing the southern Baltic Sea. Our findings indicate that including satellite-derived ASCAT wind speeds through nudging enhances the correlation and reduces the error of the mesoscale simulations across all validation platforms. Moreover, it consistently outperforms the control and previously published WRF-based wind atlases. Using satellite-derived winds directly in the model simulations also solves the issue of lifting near-surface winds to wind turbine heights, which has been challenging in estimating wind resources at such heights. The comparison of the 1-yr-long simulations with and without nudging reveals intriguing differences in the sign and magnitude between the Baltic and North Seas, which vary seasonally. The pattern highlights a distinct regional pattern attributed to regional dynamics, sea surface temperature, atmospheric stability, and the number of available ASCAT samples. Significance Statement We aim to showcase a method for improving the precision of hub-height estimation of wind resources offshore. This involves integrating wind observations obtained from near-surface satellites into the model simulations. To assess the accuracy of the simulations, we compare the simulated winds to data gathered from multiple offshore sources, including oil platforms, tall masts, and a wind lidar installed on a commercial ferry.

Mix-mode fracture behavior in asphalt concrete: Asymmetric semi-circular bending testing and random aggregate generation-based modelling

The thermal or reflective fracture in asphalt pavement often occurs due to both shear or tension stress, simultaneously, which can be referred to the mix-mode fracture. However, most of the research in the literature focused on the pure tension or shear fracture behavior but not the hybrid effects. Therefore, this study aims to investigate the mix-mode fracture behavior and fracture resistance performance of asphalt concrete through both indoor experiments and virtual modeling methods. The Asymmetric Semi-Circular Bending (ASCB) test was employed to assess the mix-mode fracture behavior of specimens. A meso-scale virtual finite element model of the asphalt concrete was also established to simulate the mix-mode fracture process and microcrack damage evolution based on polygonal random aggregate generation method. By comparing the simulation results with indoor test results, the reliability of the finite element simulation was verified. The results indicate that virtual experiments can effectively simulate the fracture process of asphalt concrete, and the fracture process always proceeds in the direction of lower energy consumption. Meso-scale simulation experiments revealed the crack evolution mechanism of mix-mode fracture in asphalt concrete. Microcracks in the pure tension fracture mode tend to connect and form a continuous fracture surface, exhibiting lower strength and apparent brittleness. With the increase in shear proportion, the connectivity of microcracks within the specimen decreases, demonstrating higher strength. The distribution pattern of microcracks in asphalt concrete at the meso-scale was analyzed based on the failure ratio of cohesive elements and the fracture modes, and the evolution degree of mix-mode fracture and the proportion of tensile failure mode in different fracture modes were quantitatively studied, thereby revealing the meso-scale cracking mechanism of asphalt concrete.

Atomistically informed mesoscale modelling of deformation behavior of bulk metallic glasses

Both atomistic and mesoscale simulation techniques have been extensively employed to gain fundamental understanding of the structures, deformation mechanisms, and structure-property relationships in bulk metallic glasses (BMGs), each with its unique strengths and limitations. Nevertheless, there is a limited degree of synergistic integration between the two approaches. In this study, we extract key properties of shear transformation zones (STZs) directly from the atomistic simulations, including their size, number of shear modes, eigenstrain, and most importantly, the activation energy barrier spectrum as a function of cooling history and strain rate. We then incorporate these STZ properties into a heterogeneously randomized STZ dynamic model implemented in a kinetic Monte Carlo algorithm to study parametrically the deformation microstructure, shear band formation and stress-strain behavior of BMGs. Two important characteristics of STZ activation that dictate the strength and ductility of a glass are identified. One is the average of the activation energy barrier spectrum (approximated by a Gaussian distribution), determined by the glass composition and processing history such as the cooling rate. The other is the amount of shift of the Gaussian distribution towards smaller activation energy barrier values during deformation, which is determined by the initial structural states and strain rate during deformation, and exhibits a saturation value. These findings have allowed us to gain important fundamental insights into the correlation between the degree of shear-induced softening and the general deformation behavior of BMGs, leading to a better understanding of the correlation between the processing history/loading condition and the mechanical behavior.

Investigation of thermal damage in explosive bridgewire detonators via discrete element method simulations

AbstractExploding bridgewire (EBW) detonators are used to rapidly and reliably initiate energetic reactions by exploding a bridgewire via Joule heating. While the mechanisms of EBW detonators have been studied extensively in nominal conditions, comparatively few studies have addressed thermally damaged detonator operability. We present a mesoscale simulation study of thermal damage in a representative EBW detonator, using discrete element method (DEM) simulations that explicitly account for individual particles in the pressed explosive powder. We use a simplified model of melting, where solid spherical particles undergo uniform shrinking, and fluid dynamics are ignored. The subsequent settling of particles results in the formation of a gap between the solid powder and the bridgewire, which we study under different conditions. In particular, particle cohesion has a significant effect on gap formation and settling behavior, where sufficiently high cohesion leads to coalescence of particles into a free‐standing pellet. This behavior is qualitatively compared to experimental visualization data, and simulations are shown to capture several key changes in pellet shape. We derive a minimum and maximum limit on gap formation during melting using simple geometric arguments. In the absence of cohesion, results agree with the maximum gap size. With increasing cohesion, the gap size decreases, eventually saturating at the minimum limit. We present results for different combinations of interparticle cohesion and detonator orientations with respect to gravity, demonstrating the complex behavior of these systems and the potential for DEM simulations to capture a range of scenarios.

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Recent years have shown that secondary ice production (SIP) is ubiquitous, affecting all clouds from polar to tropical regions. SIP is not described well in models and may explain biases in warm mixed-phase cloud ice content and structure. Through modeling constrained by in-situ observations and its synergy with radar we show that SIP in orographic clouds exert a profound impact on the vertical distribution of hydrometeors and precipitation, especially in seeder-feeder cloud configurations. The mesoscale model simulations coupled with a radar simulator strongly support that enhanced aggregation and SIP through ice-ice collisions contribute to observed spectral bimodalities, skewing the Doppler spectra toward the slower-falling side at temperatures within the dendritic growth layer, ranging from −20 °C to −10 °C. This unique signature provides an opportunity to infer long-term SIP occurrences from the global cloud radar data archive, particularly for this underexplored temperature regime.

The role of unit cell topology in modulating the compaction response of additively manufactured cellular materials using simulations and validation experiments

Additive manufacturing has enabled a transformational ability to create cellular structures (or foams) with tailored topology. Compared to their monolithic polymer counterparts, cellular structures are potentially suitable for systems requiring materials with high specific energy-absorbing capability to provide enhanced damping. In this work, we demonstrate the utility of controlling unit-cell topology with the intent of obtaining a desired stress–strain response and energy density. Using mesoscale simulations that resolve the unit-cell sub-structures, we validate the role of unit-cell topology in selectively activating a buckling mode and thereby modulating the characteristic stress–strain response. Simulations incorporate a linear viscoelastic constitutive model and a hyperelastic model for simulating large deformation of the polymer under both tension and compression. Simulated results for nine different cellular structures are compared with experimental data to gain insights into three different modes of buckling and the corresponding stress–strain response.

Benchmarking engineering wake models for farm-to-farm interactions

Inter-farm wakes between offshore wind farms can cause a significant production loss at the downstream wind farm. We compare the power production at two wind farms that are separated by approximately 20 km to engineering model results provided by three different wind farm developers. Model inflow conditions were derived from the nacelle anemometry of the wake-creating wind farm and a mesoscale simulation. The comparison reveals that the model results show in general a good approximation of the wake losses, but underestimate the increase of losses in stable stability conditions. Here, specifically the measured wakes appear to be much wider than the modelled wakes.