Numerical Modeling Framework Research Articles

Finite element simulation of restrained shrinkage cracking of cementitious materials: Considering moisture diffusion, aging viscoelasticity, aleatory uncertainty, and the effects of soft/stiff inclusions

Simulation of restrained ring shrinkage and cracking of cementitious materials in a multiphysics simulation framework (MOOSE) is discussed in this paper. The 3D numerical model analyzes residual stress development and crack initiation/propagation in cement pastes by applying an eigenstrain which varies over the depth of the specimen based on the relative humidity of the pores as moisture diffuses from the drying surface. The numerical modeling framework explicitly considers: (i) moisture diffusion that generates differential shrinkage along the depth of the specimen (ii) viscoelastic response of aging cementitious materials through a rate-type creep law based on generalized Maxwell model, (iii) isotropic damage model with Rankine′s criterion determining the failure initiation, and (iv) aleatory uncertainty-based distribution of tensile strengths of individual finite elements to account for statistical variability and associated microstructural size effects. The model is implemented for cement pastes containing compliant/stiff inclusions subjected to variable drying conditions. The numerical model can be used to compare the cracking propensity of different cementitious mixtures.

Fracture shearing of polycrystalline material simulations using the material point method

In this work, we present a newly developed workflow to study the combined effect of shear and normal stresses upon a preexisting fracture plane. This workflow is used to study the behavior of both single grain and polycrystalline materials, with varying material properties. The surface roughness and aperture of preexisting fractures are highly dependent upon the dynamic stress behavior within rock formations. Due to shear slippage, or variation in normal stress, a preexisting fracture may become more or less conductive, leading to changes in effective porosity, where such changes are caused by purely elastic deformation, plastic deformation, material failure, or a combination thereof. The numerical modeling framework demonstrated herein is based upon the meshless material point method (MPM). In using MPM, the workflow can capture large deformations due to applied shear and normal stresses. Additionally, no special geometric treatment is required at the point of contact between fracture surfaces. Models involving purely elastic, single-grain materials, as well as more complex, plastic, polycrystalline bodies, are presented, highlighting the flexibility of the proposed approach.

Historical Review of Combined Experimental and Computational Approaches for Investigating Annulus Fibrosus Mechanics.

Intervertebral disc research has sought to develop a deeper understanding of spine biomechanics, the complex relationship between disc health and back pain, and the mechanisms of spinal injury and repair. To do so, many researchers have focused on characterizing tissue-level properties of the disc, where the roles of tissue subcomponents can be more systematically investigated. Unfortunately, experimental challenges often limit the ability to measure important disc tissue- and subtissue-level behaviors, including fiber-matrix interactions, transient nutrient and electrolyte transport, and damage propagation. Numerous theoretical and numerical modeling frameworks have been introduced to explain, complement, guide, and optimize experimental research efforts. The synergy of experimental and computational work has significantly advanced the field, and these two aspects have continued to develop independently and jointly. Meanwhile, the relationship between experimental and computational work has become increasingly complex and interdependent. This has made it difficult to interpret and compare results between experimental and computational studies, as well as between solely computational studies. This paper seeks to explore issues of model translatability, robustness, and efficient study design, and to propose and motivate potential future directions for experimental, computational, and combined tissue-level investigations of the intervertebral disc.

A numerical-homogenization based phase-field fracture modeling of linear elastic heterogeneous porous media

Most porous media, such as geomaterials and biomaterials are highly heterogeneous in nature, and they contain large variations of microscopic pore structures, such as pore sizes, pore distribution, and pore shapes. The oscillation of microscopic structures is a substantial challenge in theoretical characterization and is usually ignored in continuous modeling. However, mechanical behavior of porous media such as deformation and failure, are essentially impacted by the microscopic heterogeneity which needs to be considered in modeling a porous media. This research proposes a numerical modeling framework with a capability to investigate the effect of microscopic heterogeneity on the macroscopic fracture behavior in porous media by using a numerical homogenization technique, combined with the phase-field fracture modeling method. This numerical modeling strategy computes a homogenized elasticity tensor based on microscopic heterogeneous pore structures heterogenous porous domain by solving boundary value problems at microscopic domain. The strain energy and subsequent propagation of macroscopic fractures will be updated using homogenized stiffness information. Using this numerical scheme, the microscopic pore structure’s impact on the fracture behavior through the homogenized elastic tensor will be taken into account. This multiscale technique is benchmarked against classical problems. The results highlight the importance of the underlying pore structure and reveal that both fracture strength and propagation path can be influenced by the microscopic heterogeneity.

Range–Doppler Analysis for Rain Detection at Ka-Band: Numerical and Experimental Results From Laboratory and Field Measurements

Radar technology in the millimeter-wave frequency band offers many interesting features for wind park surveillance, such as structural monitoring of rotor blades or the detection of bats and birds in the vicinity of wind turbines (WTs). Currently, the majority of WTs are affected by shutdown algorithms to minimize animal fatalities via direct collision with the rotor blades or barotrauma effects. The presence of rain is an important parameter in the definition of those algorithms together with wind speed, temperature, time of the day, and season of the year. A Ka-band frequency-modulated continuous-wave radar (33.4–36.0 GHz) installed at the tower of a 2-MW WT was used during a field study. We have observed characteristic rain-induced patterns, based on the range–Doppler algorithm. To better understand those signatures, we have developed a laboratory experiment and implemented a numerical modeling framework. Experimental and numerical results for rain detection and classification are presented and discussed here. Based on this article, a bat- and bird-friendly adaptive WT control can be developed for improved WT efficiency in periods of rain and, at the same time, reduced animal mortality.

Open-Hole Kenaf Fiber Composites Under Elevated Temperatures: Experimental And Numerical Approaches

An experimental programme to investigate the notched strength of open-hole woven fabric kenaf fiber-reinforced polymer (WKRP) composite plates under quasi-static tensile loading. It was found that all testing coupons were failed in net-section, fracture initiated at the hole edge due to stress concentrations and propagated to the plate edge. A two-dimensional numerical modelling framework was developed following previously experimental series. A constitutive model of the traction-separation relationship was incorporated by using extended finite element model (XFEM) and cohesive zone model (CZM). Moreover, the effects of elevated temperatures and thermal expansion coefficient was incorporated within the modelling framework. Both modelling techniques were evaluated and compared, albeit to insignificant differences of maximum load output in both techniques, XFEM does not require apriori failure path compared to CZM. Good agreements between the predicted modelling work and measured notched strength were obtained, with discrepancies in the range of 0.4 - 25%, both displayed consistency in the net-section failures.

Microstructural Modeling of the \u03b1\u2009+\u2009\u03b2 Phase in Ti-6Al-4V: A Diffusion-Based Approach

Complex heat treatment operations and advanced manufacturing processes such as laser or electron-beam welding will see the metallic workpiece experience a considerable range of temperatures and heating/cooling rates. These intrinsic conditions will have a significant bearing upon the microstructure of the material, and in turn upon the thermo-mechanical properties. In this work, a diffusion-based approach to model the growth and shrinkage of precipitates in the alpha + beta field of the common titanium alloy Ti-6Al-4V is established. Further, the numerical model is extended using a JMA-type approach to explore the dependency of the beta-transus temperature on extremely high heating rates, whereby dissolution alone is too slow to accurately describe the alpha to beta-phase transformation. Experimental heat treatments at rates of 5, 50, and 500 °C/s were performed, and metallographic analysis of the samples was used to validate the numerical modeling framework predictions for lamellar shrinkage, while data from the literature has been used to evaluate the numerical modeling framework for the growth of equiaxed microstructures. The agreement between measurements and numerical predictions was found to be good.

Stochastic Finite Element Analysis Framework for Modelling Mechanical Properties of Particulate Modified Polymer Composites.

Polymers have become indispensable in many engineering applications because of their attractive properties, including low volumetric mass density and excellent resistance to corrosion. However, polymers typically lack in mechanical, thermal, and electrical properties that may be required for certain engineering applications. Therefore, researchers have been seeking to improve properties by modifying polymers with particulate fillers. In the research presented herein, a numerical modeling framework was employed that is capable of predicting the properties of binary or higher order composites with randomly distributed fillers in a polymer matrix. Specifically, mechanical properties, i.e., elastic modulus, Poisson’s ratio, and thermal expansion coefficient, were herein explored for the case of size-distributed spherical filler particles. The modeling framework, employing stochastic finite element analysis, reduces efforts for assessing material properties compared to experimental work, while increasing the level of accuracy compared to other available approaches, such as analytical methods. Results from the modeling framework are presented and contrasted with findings from experimental works available in the technical literature. Numerical predictions agree well with the non-linear trends observed in the experiments, i.e., elastic modulus predictions are within the experimental data scatter, while numerical data deviate from experimental Poisson’s ratio data for filler volume fractions greater than 0.15. The latter may be the result of morphology changes in specimens at higher filler volume fractions that do not comply with modelling assumptions.

A front tracking method for simulation of two-phase interfacial flows on adaptive unstructured meshes for complex geometries

A novel numerical algorithm and modeling framework of a front tracking method based on adaptive anisotropic unstructured meshes for simulating two-phase interfacial flows is presented. In the traditional front tracking methods, a fixed uniform Eulerian Cartesian mesh is used for solving the fluid flow, and adaptive unstructured grid markers are used for tracking the phase-interface front. In the new algorithm, an adaptive anisotropic unstructured mesh is used for solving the fluid flow, as well as for tracking the phase-interface front. Special attentions are focused on developing an algorithm for physical variable interpolation between the two sets of unstructured meshes for both the fluid flow and the front movement. A modeling framework for the described numerical algorithm is implemented on the platform of the commercial CFD package ANSYS Fluent through user-defined functions. The advanced ANSYS Fluent fluid flow solver feature of using adaptive unstructured mesh is integrated with the front tracking method, which can handle complex boundary geometries and has high numerical efficiency. These advanced features are demonstrated through three numerical test examples of simulating a single gas bubble rising freely in a viscous liquid, a buoyancy-driven liquid droplet rising in a periodically constricted capillary tube, and a pressure-driven droplet passing through a small throat hole in a pipe. The accuracy of the simulation results is demonstrated through the comparison with those observed in experiments or obtained using other simulation methods.

Understanding Charge-Transfer and Kinetic Processes in Particulate Photoelectrode Morphologies for Solar Water Splitting

Z-scheme semiconductor particles, either as suspended solids in an aqueous solution1–3 with soluble redox shuttles, or as particulate sheets4,5 with solid-state electronic contacts, is a promising two-step approach to use solar energy to split water to produce hydrogen and oxygen. For Z-scheme particles to operate efficiently, it is important to realize efficient electron-transfer from the oxygen evolution particle to the hydrogen evolution particle, and to selectively drive the reactions of interest at the semiconductor-electrolyte interface. I will present on the development of a numerical modeling framework to evaluate the transport and kinetics of photogenerated charge-carriers inside a spherical semiconductor particle and across the semiconductor–electrolyte interface for Z-scheme systems with and without soluble redox shuttles. The boundary conditions applied at the electron-transfer interfaces are formulated to take into account all plausible particle surface-mediated redox reactions. The model is used to elucidate the impacts of particle size, recombination pathways, kinetic parameters and the electrochemical potential of the redox species on the performance of these particles. Results are further interpreted to identify strategies to boost the energy conversion efficiency and quantify the influence of the electrode morphologies on the overall rates of hydrogen production in Z-scheme solar water splitting systems. References Fabian, D. M. et al. Particle suspension reactors and materials for solar-driven water splitting. Energy Environ. Sci. 8, 2825–2850 (2015).Bala Chandran, R., Breen, S., Shao, Y., Ardo, S. & Weber, A. Z. Evaluating particle-suspension reactor designs for Z-scheme solar water splitting via transport and kinetic modeling. Energy Environ. Sci. 11, 115–135 (2018).Keene, S., Bala Chandran, R. & Ardo, S. Calculations of theoretical efficiencies for electrochemically-mediated tandem solar water splitting as a function of bandgap energies and redox shuttle potential. Energy Environ. Sci. (2019). doi:10.1039/C8EE01828FChen, S., Takata, T. & Domen, K. Particulate photocatalysts for overall water splitting. Nat. Rev. Mater. 2, 17050 (2017).Goto, Y. et al. A Particulate Photocatalyst Water-Splitting Panel for Large-Scale Solar Hydrogen Generation. Joule 0, (2018). Figure 1

НЕОБРАТИМЫЙ ГИСТЕРЕЗИС ТРЕХМЕРНЫХ ТОПОЛОГИЧЕСКИХ ЗАПУТАННЫХ ЛАЗЕРНЫХ СОЛИТОНОВ

In a laser medium with saturable amplification and absorption or in a laser with such a medium and a sufficiently large cavity length, the authors previously demonstrated a class of dissipative three-dimensional topological solitons (Veretenov et al., 2016, 2017). Such solitons have “skeletons” – a set of several closed and unclosed vortex lines, on which the field turns to 0 and the phase of which bypass is incremented by a multiple of 2π. It is significant that the regions of the scheme parameters in which different types of topological solitons exist and are stable, overlap. Accordingly, the question arises about the nature of changes in the structure of solitons and their skeletons with a slow change in the parameters. The answer to this question, mainly in the framework of numerical modeling, is the subject of this report. The initial equation is the generalized Ginzburg-Landau complex equation for a slowly varying envelope of the field, with the longitudinal coordinate along the path of preferential propagation z (Veretenov et al., 2017) serving as an evolution variable. The control parameter is the coefficient of linear (unsaturated) field gain g0. The initial value of this parameter corresponds to the central part of the stability region of the original soliton (for definiteness, the “Solomon soliton”). Then g0 slowly increases, crossing the stability boundary, after which it stabilizes and slowly decreases, eventually returning to its original value. We demonstrate that as a result of such a hysteresis cycle, the soliton does not return to the initial one — its structure is drastically simplified. This is reflected in a decrease in the values of various topological indices, as well as in a decrease in the field energy and an increase in the energy of the active medium (minus its constant background). At the g0 reduction stage, the topological characteristics do not change (two “soliton-apples”). The transient process includes a series of elementary reactions of reconnection of the vortex lines and detachment of closed loops after a strong bend of the “parent” vortex line. In addition, during the transition process, a number of new types of localized topological metastable structures arise. The analytical part of the research was supported by the RAS Presidium Program “Nonlinear Dynamics: Fundamental Problems and Applications”. Numerical modeling was carried out with the support of the grant of the RNF 18-12-00075.

Improved reliability of stormwater detention basin performance through water quality data-informed real-time control

Stormwater detentions basins are designed to capture stormwater to reduce and delay peak flows and to improve water quality. A novel technology proposed to improve basin performance is real-time, active control of the basin outflow, in so-called “smart” stormwater systems. Existing studies demonstrate the performance of active controls that respond in real-time to basin water level, detention time, and rainfall forecast for one or a small number of rainfall events. We hypothesize that the performance of these active controls can be improved by incorporating real-time water quality data into the control algorithm. In addition, we hypothesize that active control performance depends on hydrologic variability, specifically the frequency and intensity of runoff inputs. In this paper, we test these hypotheses using a numerical modeling framework for systems-level reliability analysis of active and passive stormwater basin outflow control using a Monte Carlo method. The analysis is performed using the urban hydrology model EPA-SWMM driven by stochastic rainfall time-series generated from the Modified Bartlett-Lewis Rectangular Pulses Model. Water quality-informed real-time active control algorithms are developed, tested, and shown to display an improvement over traditional, passive (no control) systems and other storage-based active controls for water and pollutant capture. Seasonal and duration curve analysis showed that water level- and water quality- informed control performance varied for different storm return periods and this variability could partly be attributed to the fraction of time the valve is closed. In addition, control performance was sensitive to rainfall variability, generally decreasing as storms become less frequent and more intense. Therefore, control system performance may depend on seasonal and longer time-scale variability in climate and rainfall-runoff processes. We anticipate this study to be a starting point to incorporate theories of reliability to assess detention basin and conveyance network performance under more complex real-time control algorithms and failure modes.

Systematic review of research guidelines for numerical simulation of biomass gasification for bioenergy production

Sustainable energy production through conversion of biomass has recently found growing interest. Among thermochemical conversion techniques, gasification is of interest to replace direct combustion emitting air pollutants that threaten our environment. However, gasification process is still far from being efficient since most of the research studies have only focused on experimental implementation of the methods while numerical modeling has been limited to pilot scales, ignoring the performance optimization required for scaling up the gasification process. Gasification is a highly complex process, which involves the coupling of thermochemical equilibrium, kinetics, heat and mass transfer, and computational fluid dynamics. This complexity has currently prevented the proposed theoretical/computational models in the literature from achieving the required accuracy for optimizing the gasification process. Herein, we offer a comprehensive guideline to improve the numerical models which can be implemented in future sustainable biorefineries to improve their efficiency. The present study pursues two principal objectives: (1) Introducing the fundamental knowledge required for theoretical/computational modeling and (2) Reviewing alternative numerical models for gasification process. First, a brief overview of the knowledge needed to make a systematic model is gathered. The theory of gasification, the various types of gasifiers and their differences are reviewed. Furthermore, we discuss the importance of the type of biomass feedstock with concentration on advanced biofuels and focus on wood pellets for the modeling section. Second, CFD is introduced and chemical equilibrium, kinetics, and heat and mass transfer models are discussed in depth and the variation of different parameters with respect to the change of temperature within a gasifier is elaborated. The results of this study make a clear pathway for modeling of gasification process by anticipating the expected outputs from the model by using the existing experimental data. Finally, comprehensive application of these models is demonstrated and substantial parameters affecting the gasification process are introduced. This paper provides a framework for numerical modeling of the gasification process of biomass to optimize the efficiency of the conversion process.

Finite element–based numerical modeling framework for additive manufacturing process

Finite element–based numerical modeling framework for additive manufacturing process

The smoothed finite element method (S-FEM): A framework for the design of numerical models for desired solutions

The smoothed finite element method (S-FEM) was originated by G R Liu by combining some meshfree techniques with the well-established standard finite element method (FEM). It has a family of models carefully designed with innovative types of smoothing domains. These models are found having a number of important and theoretically profound properties. This article first provides a concise and easy-to-follow presentation of key formulations used in the S-FEM. A number of important properties and unique features of S-FEM models are discussed in detail, including 1) theoretically proven softening effects; 2) upper-bound solutions; 3) accurate solutions and higher convergence rates; 4) insensitivity to mesh distortion; 5) Jacobian-free; 6) volumetric-locking-free; and most importantly 7) working well with triangular and tetrahedral meshes that can be automatically generated. The S-FEM is thus ideal for automation in computations and adaptive analyses, and hence has profound impact on AI-assisted modeling and simulation. Most importantly, one can now purposely design an S-FEM model to obtain solutions with special properties as wish, meaning that S-FEM offers a framework for design numerical models with desired properties. This novel concept of numerical model on-demand may drastically change the landscape of modeling and simulation. Future directions of research are also provided.

Exploring Marine and Aeolian Controls on Coastal Foredune Growth Using a Coupled Numerical Model

Coastal landscape change represents aggregated sediment transport gradients from spatially and temporally variable marine and aeolian forces. Numerous tools exist that independently simulate subaqueous and subaerial coastal profile change in response to these physical forces on a range of time scales. In this capacity, coastal foredunes have been treated primarily as wind-driven features. However, there are several marine controls on coastal foredune growth, such as sediment supply and moisture effects on aeolian processes. To improve understanding of interactions across the land-sea interface, here the development of the new Windsurf-coupled numerical modeling framework is presented. Windsurf couples standalone subaqueous and subaerial coastal change models to simulate the co-evolution of the coastal zone in response to both marine and aeolian processes. Windsurf is applied to a progradational, dissipative coastal system in Washington, USA, demonstrating the ability of the model framework to simulate sediment exchanges between the nearshore, beach, and dune for a one-year period. Windsurf simulations generally reproduce observed cycles of seasonal beach progradation and retreat, as well as dune growth, with reasonable skill. Exploratory model simulations are used to further explore the implications of environmental forcing variability on annual-scale coastal profile evolution. The findings of this work support the hypothesis that there are both direct and indirect oceanographic and meteorological controls on coastal foredune progradation, with this new modeling tool providing a new means of exploring complex morphodynamic feedback mechanisms.

RESPONSE OF COMPOSITE STEEL PLATE GIRDER BRIDGES SUBJECTED TO DEBRIS FIRES

Bridge fires have been a serious concern for asset owners for decades. Considerable research work has been published on the assessment of bridges subjected to hydrocarbon fires and Wildland Urban Interfaces (WUI) fires like bushfires. However, the impact from fires that may have been generated due to onsite-accumulated debris, has been largely overlooked in the past. Prolonged duration of debris fires might well cause significant damage to the bridges, unless properly accounted during the design stage. The current study investigates the influence from debris-generated fires on steel girder bridges, using a reasonably validated advanced numerical modelling framework. Fire development was modelled first as a static, and then a travelling fire, using fire dynamic simulation (FDS) to capture the Adiabatic Surface Temperature (AST) development of the structure. The resulted AST was coupled with thermo-mechanical analysis using sequentially coupled thermo-mechanical analysis procedure in ABAQUS. The numerical model was used to estimate the temperature and displacement development of the bridge. The outcome from the study will facilitate asset managers for conducting necessary risk assessments incorporating the influence of onsite flammable debris for bridges.

Stochastic finite element analysis framework for modelling thermal conductivity of particulate modified polymer composites

Abstract Polymers possess desirable properties such as low specific gravity and good corrosion resistance, which make them attractive for a variety of applications. However, polymers typically lack in mechanical, thermal and electrical properties. Therefore, considerable research efforts are spent to improve polymer properties using particulate fillers. A multitude of filler materials and shapes are available, such as fiber/rod, plate-like or spherical geometries. Composite morphologies may also differ based on particle distribution, dispersion and alignment, all of which may be affected by filler loading and manufacturing routes. Given the significant efforts associated with experimental analyses, modeling approaches are expedient for providing a fundamental understanding for particulate modified polymers. In the present study a numerical modeling framework was developed for predicting the effective properties, specifically, thermal conductivity, of particulate modified polymers considering filler-matrix and particle-to-particle interfacial effects. Employing a stochastic finite element analysis, composites with randomly distributed spherical particles were modeled and validated against experimental data. The developed modeling framework, which can accommodate a broad range of filler shapes and composite morphologies, provides an effective means for elucidating experimental studies and guiding the design of particulate modified polymer composites.

FE modeling and simulation framework for the forming of hybrid metal-composites clinching joints

A 3D elasto-plastic numerical modeling and simulation framework is proposed for the forming of hybrid metal-composites clinching processes. The framework is employed in the commercial finite element software ABAQUS. The proposed FE procedures are presented and discussed in detail. Then, an experimental-numerical validation example of a metal-composites hybrid clinching process is presented. The material pairing of PA6GF30 and EN AW 5754 is chosen for this purpose. Accordingly, a user-defined constitutive model is employed for the PA6GF30 sheet to represent the sophisticated constitutive behavior of composites in more realistic manner. A brief description of the model and the parameter identification is provided. For the EN AW 5754 material, the standard von Mises model is used. The simulation results presented show the applicability and accuracy of the modeling framework, which can serve as a tool to investigate and to improve the mechanical behavior of hybrid clinching joints.

Modelling and experimental validation of microstructure evolution during the cooling stage of homogenization heat treatment of Al–Mg–Si alloys

A CALPHAD-coupled multi-component multi-phase Kampmann–Wagner Numerical modelling framework has been adapted and coupled with a homogenization model to predict the competitive nucleation and growth of multi-sized metastable/stable phase particles during the cooling stage of a homogenization heat treatment. The reported model is the continuation of our previous work on the homogenization soaking modelling (Du et al., 2013). It takes the experimentally verified soaking modelling prediction results as the initial microstructural status and predicts the microstructural evolution during the very last step of the homogenization treatment, i.e. the final cooling process. The model has been applied to two Al–Mg–Si alloys: AA6061 and AA6082. The simulation shows a multi-modal MgSi particle size distribution forms due to multiple nucleation events. For the AA6082 alloy the multiple nucleation events occur mainly due to the local micro-chemistry variations along a dendrite while for AA6061 it is due to the two opposite contributions to supersaturation: the positive contribution by the cooling and the negative contribution by the particles' growth. The interaction of intergranular and intragranular MgSi containing particles have been captured, and the partitioning of Mg and Si solutes among the two different sized MgSi particles has been predicted. The model predictions are in reasonable agreement with the microstructure characterization results obtained with Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and Electrical Resistivity Measurement on the quenched samples from some dedicated laboratory-scale homogenization heat treatment experiments. It is concluded that the extended KWN modelling framework is applicable to predict the microstructure evolution during the non-isothermal heat treatment of multicomponent aluminium alloys.