Numerical Modeling Framework Research Articles

Seismic behavior of soil-tunnel-building system considering earthquake frequency contents

Rapid urbanization has led to limited land availability, prompting the construction of residential and underground utility facilities in close proximity, forming an interconnected system with the surrounding soil. However, studies on the seismic behavior of such integrated systems are scarce due to their complex soil-structure interaction (SSI) mechanism. Furthermore, the dynamic behavior of these coupled structures depends heavily on earthquake characteristics like frequency content, an aspect that remains largely unexplored. This study aims to investigate the effects of earthquake frequency on the dynamic behavior of soil-underground structure-aboveground structure coupled systems. Using a novel experimental-numerical approach, two centrifuge tests were used to validate the numerical modeling framework. Three cases (soil-building, soil-tunnel, and soil-tunnel-building coupled systems) are then analyzed under earthquakes with varying frequency content. Results demonstrate how seismic response and SSI indicators of the structures evolve with changing seismic frequencies, offering valuable insights for enhancing safety measures in urban megacities.

Influence of Mechanical Degradation in Polycrystalline NMC Particles on the Electrochemical Performance of Lithium-Ion Batteries

Lithium-ion batteries (LIBs) have gained widespread popularity for energy storage systems owing to their high coulombic efficiency and energy density. Within the cathode electrode materials of LIBs, the structural integrity of secondary particles, composed of randomly oriented single-crystal primary active particles, is crucial for sustained performance. The fracture of these particles can occur due to both mechanical stress and chemical interactions within the solid. Modeling LIBs presents a multiphysics challenge as it involves addressing the electro-chemo-mechanical phenomena and their interactions across various length scales. During electrochemical cycling, volume changes in active particles induce mechanical stresses, while the mechanical state of the battery influences the diffusion of lithium.This study proposes a numerical modeling framework to investigate the degradation of active material particles and its impact on electrochemical performance. The model integrates mechanical and electrochemical processes, solving nonlinear equations related to surface charge transfer, lithium diffusion, and mechanical stresses. By incorporating phase field damage, the model tracks crack evolution and mechanical failure of active particles. The coupled equations are solved within a finite element framework using COMSOL Multiphysics.Notably, the model offers numerical insights into intergranular and transgranular fracture within secondary active material particles. The infiltration of liquid electrolyte into cracks is identified as a positive effect, reducing electrochemical overpotential by increasing electrochemically active surface area from particle cracking. However, prolonged cycling with particle cracking poses a notable threat to battery performance and capacity. This comprehensive numerical modeling approach provides valuable insights into the intricate interplay of mechanical and electrochemical factors governing LIB performance and degradation.

A study on radial characteristics of North Indian Ocean tropical cyclones and associated energy indices through numerical modeling

The structural characteristics of North Indian Ocean (NIO) Tropical Cyclones (TCs) are emphasized in this study by adopting Weather Research and Forecasting (WRF) numerical modeling framework. TCs that occurred during 2001–2020, were simulated using WRF model in the CTRL, and scatterometer wind vortices from four satellites were considered for assimilation purpose in the WRFDA experiment. Considering the results from both types of simulations, best-track data sets, and ERA5 global analyses, several aspects including radial parameters, the thermodynamic and dynamic properties, horizontal structure, etc., were analyzed besides developing some robust empirical relationships. In the process, model performance was evaluated too. The study emphasized on sub-basin, sectorial, intensity-based, range-based, and frequency-based analysis for the radial parameters. Also, yearly, and seasonal variations were considered, inter-comparisons were carried out, the inter-relationships with numerous environmental and storm-related characteristics have been explored. The study provides valuable insights into the TC radial characteristics over NIO, and associated thermodynamic and dynamic behavior. It upholds that the relatively greater intensity TCs occurring during October–November months are mostly observed to have genesis over the East Arabian Sea (EAS), Middle Bay of Bengal (MBOB), and North Bay of Bengal (NBOB) sectors. The EAS region exhibits higher values for the energy indices and maximum sustained wind (MSW), compared to the Western Arabian Sea (WAS), while the maximum convective potential values show an opposite trend. The assimilation of scatterometer wind data has a limited impact on model results, although it is more effective over the Arabian Sea (AS) than the Bay of Bengal (BOB). WRFDA could provide a relatively better estimate for most of the TC radial features over both AS and BOB. The extensive analysis of TC radial features facilitated developing several empirical relationships involving radial characteristics, MSW and minimum central pressure, which are valid for NIO region.

A Voronoi-based gaussian smoothing algorithm for efficiently generating RVEs of multi-phase composites with graded aggregates and random pores

This paper presents an innovative numerical modeling framework capable of generating highly realistic 3D mesoscale multi-phase concrete models with unprecedented efficiency and accuracy. Addressing a significant wide range in aggregate volume fraction (0 to 80%) and featuring rapid model generation capabilities, our framework marks a breakthrough in reducing computational time—achieving simulations of 1 million elements within mere 30 s on readily available hardware. By analyzing randomly generated concrete samples across varying compositions, our algorithm can provide deep mesoscopic insights into their compressive properties, validated against a wide array of experimental results. Additionally, our comprehensive analytical model sheds light on the intricate roles of aggregate volume fraction and porosity, enhancing understanding of the meso-scale compressive behavior. We also make the source code available on GitHub, offering a valuable tool for the engineering and research community to optimize concrete material design and performance.

Subglacial Discharge Accelerates Dynamic Retreat of Aurora Subglacial Basin Outlet Glaciers, East Antarctica, Over the 21st Century

AbstractRecent studies have revealed the presence of a complex freshwater system underlying the Aurora Subglacial Basin (ASB), a region of East Antarctica that contains ∼7 m of global sea level potential in ice mainly grounded below sea level. However, the impact that subglacial freshwater has on driving the evolution of the dynamic outlet glaciers that drain this basin has yet to be tested in a coupled ice sheet‐subglacial hydrology numerical modeling framework. Here, we project the evolution of the primary outlet glaciers draining the ASB (Moscow University Ice Shelf, Totten, Vanderford, and Adams Glaciers) in response to an evolving subglacial hydrology system and to ocean forcing through 2100, following low and high CMIP6 emission scenarios. By 2100, ice‐hydrology feedbacks enhance the ASB's 2100 sea level contribution by ∼30% (7.50–9.80 mm) in high emission scenarios and accelerate the retreat of Totten Glacier's main ice stream by 25 years. Ice‐hydrology feedbacks are particularly influential in the retreat of the Vanderford and Adams Glaciers, driving an additional 10 km of retreat in fully coupled simulations relative to uncoupled simulations. Hydrology‐driven ice shelf melt enhancements are the primary cause of domain‐wide mass loss in low emission scenarios, but are secondary to ice sheet frictional feedbacks under high emission scenarios. The results presented here demonstrate that ice‐subglacial hydrology interactions can significantly accelerate retreat of dynamic Antarctic glaciers and that future Antarctic sea level assessments that do not take these interactions into account might be severely underestimating Antarctic Ice Sheet mass loss.

Model-Based Analysis of Arsenic Retention by Stimulated Iron Mineral Transformation under Coastal Aquifer Conditions.

A multitude of geochemical processes control the aqueous concentration and transport properties of trace metal contaminants such as arsenic (As) in groundwater environments. Effective As remediation, especially under reducing conditions, has remained a significant challenge. Fe(II) nitrate treatments are a promising option for As immobilization but require optimization to be most effective. Here, we develop a process-based numerical modeling framework to provide an in-depth understanding of the geochemical mechanisms controlling the response of As-contaminated sediments to Fe(II) nitrate treatment. The analyzed data sets included time series from two batch experiments (control vs treatment) and effluent concentrations from a flow-through column experiment. The reaction network incorporates a mixture of homogeneous and heterogeneous reactions affecting Fe redox chemistry. Modeling revealed that the precipitation of the Fe treatment caused a rapid pH decline, which then triggered multiple heterogeneous buffering processes. The model quantifies key processes for effective remediation, including the transfer of aqueous As to adsorbed As and the transformation of Fe minerals, which act as sorption hosts, from amorphous to more stable phases. The developed model provides the basis for predictions of the remedial benefits of Fe(II) nitrate treatments under varying geochemical and hydrogeological conditions, particularly in high-As coastal environments.

A size‐dependent energy‐based strain burst criterion

AbstractThis paper presents a size‐dependent energy‐based strain burst criterion linking strength, elasticity, fracture energies and specimen size effect with stress state due to changes in boundary conditions. It proposes the concept of a ‘Burst Envelope’, a surface in three‐dimensional principal stress space derived based on energy storing and dissipation characteristics of a rock sample, taking into account the size of the specimen and potential localised failure pattern. A scalar burst index is also proposed to quantify the bursting scale. To illustrate and verify its functioning, a numerical modelling framework based on the distinct element method and employing a new cohesive‐frictional contact model is used to perform virtual strain burst experiments under different polyaxial loading‐unloading scenarios, mimicking various underground excavation scenarios. The obtained results are in good agreement with the theoretical prediction of burst occurrence. On that basis, the variation of burst possibility and magnitude are investigated with key factors, including confinement level and the material's elastic, strength and fracture properties. The effect of the specimen's aspect ratio and size on the rock burst potential is elaborated and verified using virtual strain burst experiments, facilitating the linking of the proposed theoretical framework with the evaluation of in‐situ strain bursts in rock masses around underground openings.

Impact of Mechanical Degradation in Polycrystalline NMC Particle on the Electrochemical Performance of Lithium-Ion Batteries

Lithium-ion batteries (LIBs) are widely chosen for energy storage owing to their high coulombic efficiency and energy density. Within the positive electrode materials of LIBs, the structural integrity of secondary particles, composed of randomly oriented single-crystal primary particles, is crucial for sustained performance. These particles can fracture as a result of both mechanical stress and chemical interactions within the solid. Modelling LIBs is a complex task involving electro-chemo-mechanical phenomena and their interactions on different length scales. This study proposes a numerical modeling framework to investigate the active particle degradation and its impact on electrochemical performance. The model integrates mechanical and electrochemical processes, tracking crack evolution and mechanical failure through phase field damage. The coupled time-dependent non-linear partial differential equations are solved in a finite element framework using COMSOL Multiphysics. The model offers numerical insights into intergranular and transgranular fracture within secondary particles. The electrolyte infiltration into cracks reduces the electrochemical overpotential due to the increase in electrochemically active surface area, positively affecting performance. However, prolonged cycling with particle cracking poses severe threat to the battery performance and capacity. This comprehensive numerical modeling approach provides valuable insights into the intricate interplay of mechanical and electrochemical factors governing LIB performance and degradation.

Modelling of a Floating-Type Hybrid Wind-Wave System with Oscillating Water Column Wave Energy Converters: A Study Towards Floater Motion Reduction

The integration of floating offshore wind turbines with wave energy converters is regarded as a promising solution for offshore renewable energy development. Given the early stage of wave energy conversion technologies and the substantial influence of control methods on overall system dynamics, a faithful aero-hydro-thermo-elastic-servo-mooring coupled model, along with an engineering environment offering high flexibility for control implementations, is essential. To address the requirement, a numerical modeling framework is developed in this study based on Simulink, known for its superiority in control design and implementation, and OpenFAST, which offers a reliable floating wind turbine model. The model incorporates the thermodynamics of the air in chambers, power take-off dynamics, and oscillating water column dynamics. Furthermore, bypass valves are utilized for the wave energy converters to adjust chamber pressure and reduce floater motion, with a control law proposed to regulate the valve opening ratio. A case study is conducted under harsh ocean conditions to validate the model. The numerical results not only demonstrate the feasibility of the model but also underscore the effectiveness of the control law in improving floater motion performance.

Numerical Modelling simulation technology of Nonlinear Multi-Field Coupled Ground Foundation

Contemporary civil engineering practices demand sophisticated computational tools to navigate the complexities of structural systems and their interactions with the ground. This paper introduces a novel numerical modelling simulation technology tailored for nonlinear multi-field coupled ground foundations. Ground foundations, pivotal interfaces between structures and underlying soil, undergo intricate interactions influenced by various physical phenomena, including soil-structure interaction, soil-structure-fluid interaction, and thermal effects. Traditional analytical methods often falter in capturing the nuanced nonlinear behavior of these coupled systems. Consequently, this paper proposes a comprehensive numerical modelling framework integrating advanced computational techniques to accurately simulate the complex interplay of multiple fields within ground foundations. The methodology incorporates finite element analysis, multi-physics coupling algorithms, and advanced constitutive models to capture the nonlinear behavior of soil, structure, and fluid interactions. Through detailed case studies and validation against experimental data, the efficacy and accuracy of the proposed simulation technology are demonstrated, emphasizing its potential to revolutionize the design and analysis of ground foundation systems in civil engineering applications. This paper represents a foundational contribution towards advancing the state-of-the-art in numerical modelling simulation technologies for nonlinear multi-field coupled ground foundations, fostering innovation and optimization in civil engineering practice.

The Formation of 2D Holograms of a Noise Source and Bearing Estimation by a Vector Scalar Receiver in the High-Frequency Band

The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of holographic signal processing for a noise source by the VSR. The developed method is based on the formation of the 2D interferogram and 2D hologram of a noise source in a shallow-water waveguide. The 2D interferograms and 2D holograms for different channels of the VSR (P sound pressure and VX and VY vibration velocity components) are considered. It is shown that the 2D interferogram consists of parallel interference fingers in the presence of a moving noise source. As a result, the 2D hologram contains focal points located on a straight line, and the angular distribution of the holograms has the main extreme value. It is shown in the paper that the holographic signal-processing method allows detecting the source, estimating the source bearing, and filtering the useful signal from the noise. The results of the source detection, source bearing estimation, and noise filtering are presented within the framework of experimental data processing and numerical modeling.

Incorporating surface roughness into numerical modeling for predicting fatigue properties of L-PBF AlSi10Mg specimens

Laser-powder bed fusion (L-PBF) is a popular additive manufacturing method for fabricating metal parts with complex geometries. However, one of the primary setbacks lies in the surface quality of the as-built components. Poor surface quality influences the dynamic fatigue properties of L-PBF parts. Experimental investigation of fatigue properties is time-intensive and expensive. Hence, computational modeling can be implemented to critically evaluate the impact of surface roughness on fatigue. In this work, a numerical modeling framework is developed that considers the influence of part-scale surface roughness on fatigue properties. To calibrate and validate the numerical modeling framework, mechanical investigations of miniature AlSi10Mg specimens are conducted in a custom-built tensile-fatigue testing apparatus. First, the tensile properties are evaluated to find out the reliability of the apparatus. Thereafter, the fatigue investigations of two sets of specimens are conducted: five specimens (FS1-FS5) for calibrating the numerical model and three specimens (VFS1-VFS3) for model validation. The numerical modeling framework involves the 3D reconstructed specimen geometries from computed tomography (CT) imaging of the VFS1-VFS3 specimens. The resultant 3D geometries are discretized using Ansys finite element software and analyzed to simulate the fatigue behavior. The numerical results of fatigue life and failure locations of the VFS1-VFS3 specimens are compared with the experimental observations. The comparison shows that the numerical results are within 5 % of the experimental observations. Additionally, the location of maximum strain localization in numerical modeling matches the crack initiation location. In conclusion, the numerical modeling can predict low cycle fatigue life and failure location of L-PBF AM specimens.

A new numerical modelling framework for fixed oscillating water column wave energy conversion device combining BEM and CFD methods: Validation with experiments

The Oscillating Water Column (OWC) wave energy converter has been shown to have high potential, thus rendering extensive development in recent years. In order to further accelerate its development, highly accurate yet computationally efficient tools are necessary particularly when studying the interaction of multiple OWC devices. This paper proposes a new framework for fixed OWC devices with an orifice, that uses the input from a high fidelity non-linear numerical model to improve the accuracy of a low fidelity linear numerical model keeping computational costs low. This is done by accounting for the non-linearities in the pressure-flow of an orifice in the input to the linear numerical model. Experimental data is used to validate the framework, thus providing an accurate and computationally efficient linear numerical model, that can be used for the preliminary analysis of fixed OWC devices.

A ChatGPT-MATLAB framework for numerical modeling in geotechnical engineering applications

ChatGPT has recently emerged as a representative of Large Language Models (LLMs) that have brought evolutionary changes to our society, and the effectiveness of ChatGPT in various applications has been increasingly reported. This study aimed to explore the potential of employing programming performance driven by ChatGPT responses to conversational prompts in the field of geotechnical engineering. The tested examples included the analysis of seepage flow and slope stability, and the image processing of X-ray computed tomographic image for partially saturated sand. For each case, the prompt was initially fed by a narrative explanation of the problem attributes such as geometry, initial conditions, and boundary conditions to generate the MATLAB code that was in turn executed to evaluate the correctness and functionality. Any errors and unanticipated results were further refined by additional prompts until the correct outcome was achieved. ChatGPT was able to generate the numerical code at a considerable level, demonstrating creditable awareness of the refining process, when meticulous prompts were provided based on a comprehensive understanding of given problems. While ChatGPT may not be able to replace the entire process of programming, it can help minimize sloppy syntax errors and assist in designing a basic framework for logical programming.

On the dynamics of coalescence between droplets and partially filled microgrooves

When water vapor condenses on a hydrophobic surface equipped with microgrooves, a unique phenomenon of coalescence between droplets growing on the ridges and the microgrooves partially imbibed with a condensate is manifested. Such coalescence is distinctly different from droplet–droplet coalescence and can trigger rapid removal of the condensate from the surface, a critical requirement for high thermodynamic efficiency of condensation. In this work, we investigate the dynamics of this coalescence process. We develop an experimentally validated, three-dimensional, volume of fluid method-based numerical modeling framework that accounts for dynamic contact angle variation during contact line motion. The condensate wetting the microgroove forms a liquid column with a meniscus pinned to the microgroove edges. We show that ridge droplet coalescence with this pinned meniscus triggers capillary ripples that traverse the microgroove in transverse and longitudinal directions and can trigger the depinning of the contact line from the opposing edge depending on the size of the coalescing droplet. The contact line depins when the local contact angle at the opposing edge reaches ∼180° and, simultaneously, the kinetic energy converted from the excess surface energy available reaches a maximum. Additionally, we show that the overall coalescence process is significantly affected by the microgroove aspect ratio. For the same liquid volume, relatively shallower microgrooves cause the condensate to overflow, thus attaining a morphology akin to large droplets in the Wenzel state. As a result, the coalescence dynamics on such microgrooved surfaces are similar to that on a planar surface.

Numerical erosion prediction of aluminum induced by cavitating jet using an Eulerian–Lagrangian method

Cavitation-induced erosion in pump machinery is a significant issue that leads to material loss and increased operating costs. This study develops a numerical method based on an energy balance approach to address the risk of cavitation erosion. Compared with other published methods, three improvements are made. Firstly, it assumes that the local instantaneous pressure is the driving force behind cavity collapse, rather than the far-away ambient pressure field. Secondly, it counts erosion only at the moment that the released shock wave is strong enough to cause surface damage. Thirdly, an Eulerian–Lagrangian method is introduced to simulate multiscale cavitation, in which the volume of fluid (VOF) method and a discrete bubble model (DBM) are combined to reproduce resolvable water-vapor interfaces and unresolvable discrete bubbles, respectively. The developed numerical modeling framework is validated by predicting the erosion of pure aluminum surface caused by a cavitating jet, and it is shown that the simulated erosion region fits well against the experimental results. Additionally, appropriate model coefficients of the erosion prediction method are introduced to achieve quantitative prediction of material mass loss, and the detailed erosion behavior is discussed.

A numerical modeling framework for predicting the effects of operational parameters on particle size distribution in the gas atomization process for Nickel-Silicon alloys

Gas atomization is utilized to produce good-quality metal powders. A numerical modeling framework is developed to simulate the gas atomization process. A two-phase VOF flow model in OpenFOAM is applied to track the primary breakup of the melt stream by a high-speed gas flow. The generation of primary melt droplets is extracted from the VOF field. A Lagrangian-Eulerian multiphase flow model in Ansys Fluent is adopted to track the secondary breakup of the primary melt droplets under the high-speed gas flow. The final particle size distribution is obtained by analyzing the particles sampled at the outlet of the atomization chamber. The process of gas atomization can be affected by many factors such as the atomization equipment, operating parameters, and material properties. Sensitivity analysis is conducted through modeling to investigate the effects of these factors on particle size distribution. The model predictions are validated by specially designed gas-atomization experiments.

Improved gas influx distribution estimation using interfacial area transport equation (IATE) enabled two-fluid model: An advanced modeling and full-scale experimental study

Gas influx management is a critical aspect of petroleum drilling operations, which aims to prevent the uncontrolled outflow of formation gas and the potential consequences caused by blowouts. This study investigates the distribution of gas influx and the interfacial area concentration (IAC) during gas influx circulation operations through a combination of full-scale experiments and advanced numerical simulations.Experiments were conducted to simulate downhole gas influxes by injecting Nitrogen gas into the base of a 5,160-foot-deep experimental wellbore, which was filled with water. A Distributed Fiber-Optic Sensing (DFOS) system was installed in the wellbore to obtain high-resolution acoustic and temperature data and monitor the gas influx behaviors when circulated out of the annulus. Various types of measurements were obtained to analyze the gas influx length, slip velocities, void fraction distribution, and dispersion behaviors. In addition, an advanced numerical simulator was developed based on a modified Two-Fluid Model and the Interfacial Area Transport Equation (IATE) to simulate the gas influx behaviors. The model estimations were compared to the experimental measurements for validation of accuracy and further insights.The numerical modeling framework, based on the interfacial area transport equation, effectively captured bubble interactions, including mechanisms including bubble breakage and coalescence, by estimating the interfacial area distribution. The gas influx dispersion during circulation was analyzed using both model estimations and experimental data. Good agreement was observed between the model predictions and experimental data, including multi-depths gauge measurements and the DFOS data.This is a novel application of the IATE in well-scale multiphase flow simulations, which has proved to be an effective tool for predicting the dynamics of gas influx distributions. The outcomes of this study provide critical insights into the design and optimization of gas influx management during Managed Pressure Drilling (MPD).

Modeling gypsum (calcium sulfate dihydrate) solubility in aqueous electrolyte solutions using extreme learning machine

Due to various operational conditions, experimental determination of gypsum solubility in water-based systems comprising multiple ionic compounds is often impractical or costly. In this regard, computer-based intelligent approaches can provide highly effective and economical alternatives. In this study, after providing a database with 2288 experimental data-points gathered from 31 various literatures, four advanced artificial intelligence techniques were developed: Adaptive Boosting-Support Vector Regression (AdaBoost-SVR), Extreme Learning Machine (ELM), Gradient Boosting-Support Vector Regression (GB-SVR), and Multivariate Adaptive Regression Splines (MARS). The aim of these techniques was to predict the gypsum solubility in aqueous electrolyte solutions as a function of the solutions' temperature and 22 distinct salts' Molal concentrations. After performing various statistical and graphical analyses, it was observed that the ELM model has a more accurate prediction capability for gypsum solubility in aqueous electrolyte solutions compared to the other three models. For this model, the highest Coefficient of Determination (R2 = 0.9926) and the lowest Root Mean Square Error (RMSE = 0.00373) were obtained. Furthermore, after conducting a sensitivity analysis to calculate the relevancy factors of the ELM model's input and output variables, the variation trend of gypsum solubility was evaluated. According to the multiple evaluations, the ELM model predictions reasonably agreed with the experimental data on gypsum solubility in the chosen solutions and temperature ranges. The ELM model can be implemented in numerical modeling frameworks for improving the treatment and reclamation operations of saline water sources, optimizing the oil and gas recovery and production processes, and controlling the complicated geotechnical issues.

Resilience of metro tunnel structures: monitoring deformation due to surrounding engineering activities and effect of remediation treatment

Long term performance of urban metro tunnels requires that the tunnel structure maintains not only a sound structural state, i.e., free from significant damages, but also a minimal change in the physical shape. Over-deformation can cause structural damage but more importantly can affect the safe operation of the metro lines, therefore is a primary target of monitoring and intervention where it becomes necessary. This paper presents an overview of recent developments in field monitoring and assessment of metro tunnels in soft soil concerning over-deformation. In particular, the over-deformation of shield tunnel rings due to nearby construction activities, especially deep excavation, and its rectification using grout treatment is discussed on the basis of relevant field experiment and numerical modelling reported in recent publications. Key considerations in the development of a Material Point Method (MPM) based numerical modelling framework for simulating explicitly the grouting operations are highlighted, and the general performance of the numerical model is examined with reference to the field test data and characteristic parametric observations. Further research needs in terms of more rigorous assessment and design of grouting treatment, in conjunction with the continued development of numerical modelling capabilities, are discussed.