Computer Simulation Research Articles

Damage evolution and fracture characteristics of coal rock impacted by self‐excited pulse water jet under different stress loading conditions

AbstractIn this paper, based on smoothed‐particle hydrodynamics‐finite element method, numerical models of plunger squeezing water at a sinusoidal velocity were established to simulate self‐excited pulse water jet (SEPWJ). RHT constitutive model was adopted to describe the damage and failure of coal rock impacted by water jet. The morphological evolutions of broken pits and timeliness of rock‐breaking efficiency of SEPWJ and continuous water jet (CWJ) under the conditions with and without stress loadings were obtained and compared. The evolution laws of damage and stress inner coal rock induced by jet impact, and the failure mechanism were revealed. And the influences of different stress loading magnitudes on the fracture characteristics of coal rock were investigated. The results show that the morphologies of broken pits formed by self‐excited pulse jet undergo changes in a semi‐circular, U‐shaped, V‐shaped, and bullet shaped in sequence under the stress‐free loading condition. When applying one‐dimensional (1D) and 2D stress loadings, the shallow but wide broken pits with laminar main cracks along the stress loading direction and the inverted trapezoidal bowl broken pits are formed, respectively. With the increase of 1D stress, the depth and width of broken pits slightly decrease as a quadratic parabolic function and linearly increase, respectively. And the broken pit width and area both show an exponential slow decreasing trends with the increasing 2D stress. SEPWJ can induce higher stresses to cause the earlier occurrence of initial damage and the shorter duration of damage accumulation to coal rock than CWJ, which leads to a better rock‐breaking effect. The surface and deeper coal rock elements are broken mainly due to compressive shear stresses. The 2D stress loading delays the initial damage occurrence and prolongs the damage accumulation duration due to inhibitory effect of stress loading on jet impact.

Seismic behavior of a hollow precast concrete shear wall with insulation under high axial compression ratios

A hollow precast concrete shear wall (HPCSW) with multiple vertical hollow cores that is advanced in lightweight and thermal insulation is studied in this paper. Novel tapered grouted sleeves (TGSs) are developed to connect the adjacent shear walls, which can avoid grouting defects through visible grouting processes. Seven full-size specimens with an aspect ratio of 3.3, including three solid precast shear walls, three hollow precast shear walls, and a cast-in-place (CIP) shear wall, were subjected to cyclic loading tests, which considered different and high axial compression ratios (ACRs) of 0.3, 0.45, and 0.6. The results show that the solid precast shear wall with the TGS connection displays comparable failure mode and seismic behavior with the CIP one. In contrast, the HPCSW suffers hollow core crushing under high ACRs, leading to a significant reduction in deformation and energy dissipation capacity. Finally, numerical models of HPCSW specimens with different layouts of the hollow cores were established using ABAQUS to evidence the test results and optimize the structure. The results show that the configuration of the outer hollow cores influences the seismic behavior of the HPCSW vastly. It is recommended that the concrete is partially filled into the outer hollow cores to obtain good insulation and seismic capacity simultaneously, with the filling height greater than the predicted crushing height.

Numerical modeling of development of Leandras and Double Bopper Caves, Grand Canyon, USA

Numerical modeling of development of Leandras and Double Bopper Caves, Grand Canyon, USA

High-dimensional multi-objective optimization of coupled cross-laminated timber walls building using deep learning

This paper introduces a deep learning-based multi-objective optimization framework, applying for advancing the design of the Cross-Laminated Timber Coupled Wall system. While traditional optimization methods often struggle with the curse of dimensionality in high-dimensional problems, the approach proposed in this study employs an autoencoder to effectively reduce the dimensionality of the design space. Subsequently, a neural network establishes a mapping between input variables and latent spaces, with another neural network forming the crucial link between these latent variables and the output responses. The proposed framework is integrated into the design process of a 20-story Cross-Laminated Timber Coupled Wall system, where uncertainties inherent in connection elements are systematically addressed to optimize the structural parameters. The non-dominated sorting genetic algorithm-II is utilized to estimate optimal design variables by minimizing three conflicting objective functions, thereby generating a Pareto front. This optimized design is then bench-marked against three deterministic models with varying coupling beam shear strengths. A two-dimensional numerical model developed in OpenSees facilitates nonlinear time history analysis using 50 bi-directional ground motion records, representative of the seismicity of Vancouver, Canada. The results of this study not only highlight the efficacy of the deep learning-based framework in enhancing the structural integrity and resilience of high-rise timber structures in seismic regions but also significantly contribute to the evolution of computational approaches in structural engineering.

Holocene thinning in central Greenland controlled by the Northeast Greenland Ice Stream

Ice-core records from the interior of the Greenland ice sheet suggest widespread thinning during the Holocene. However, the recurring underestimation of this thinning in numerical models raises concerns about both the veracity of such reconstructions and the reliability of glaciological models. Recent work suggests the 8000-year-old Northeast Greenland Ice Stream (NEGIS), including a now-extinct northern tributary, may have been an early influence on Greenland ice-sheet dynamics. Yet, the inaccurate reproduction of NEGIS-like dynamics in most models hampers investigation of whether this feature played a role in Holocene ice-sheet thinning. Here we show that grounding-line retreat in northeast Greenland triggers elevation changes at the northern summit via ice-dynamic effects modulated by the paleo NEGIS system. In our simulations, fast ice-stream flow caused by transiently imposed reduced basal shear stress following the northeast retreat explains 55% ( ± 18%) of the estimated ice thinning, showing that ice-stream dynamics is one of the main drivers of the NGRIP Holocene surface elevation drop. Our findings show that the ice-flow in northeast Greenland plays a large role in ice-surface elevation changes in central Greenland.

Numerical simulating the blood flow model via nonhomogeneous Riemann solver scheme

This paper examines a one-dimensional (1D) model that appears in arterial blood flow. The mathematical model for blood flow via arteries is similar to that of unstable incompressible flows in thin-walled collapsible tubes. We present the Riemann invariants of the suggested model, which is one of the fundamental components of this work. For numerical modeling of blood flow model, we present a nonhomogeneous Riemann solver (NHRS) technique. Next, we demonstrate the simulation of how pressure, velocity, and cross section area waveforms propagate through arteries. Specifically, we present numerical test cases with various initial data sets. In addition, we compare the NHRS scheme to the classic Rusanov, Lax–Friedrichs, and Roe schemes. Theoretical models for thin-walled collapsible tubes are applicable to a wide range of physiological events and may be used to build clinical devices for actual biomedical science. The NHRS method’s accuracy and efficiency are demonstrated by the numerical tests.

Relating Hydro‐Mechanical and Elastodynamic Properties of Dynamically Stressed Tensile‐Fractured Rock in Relation to Applied Normal Stress, Fracture Aperture, and Contact Area

AbstractWe exploit nonlinear elastodynamic properties of fractured rock to probe the micro‐scale mechanics of fractures and understand the relation between fluid transport and fracture aperture under dynamic stressing. Experiments were conducted on rough, tensile‐fractured Westerly granite subject to triaxial stresses. We measure fracture permeability for steady‐state fluid flow with deionized water. Pore pressure oscillations are applied at amplitudes ranging from 0.2 to 1 MPa at 1 Hz frequency. During dynamic stressing we transmit ultrasonic signals through the fracture using an array of piezoelectric transducers (PZTs) to monitor evolution of interface properties. We examine the influence of fracture aperture and contact area by conducting measurements at effective normal stresses of 10–20 MPa. Additionally, the evolution of contact area with stress is characterized using pressure sensitive film. These experiments are conducted separately with the same fracture and map contact area at stresses from 9 to 21 MPa. The measurements are a proxy for “true” contact area for the fracture surface and we relate them to elastic properties using the calculated PZT sensor footprints via numerical modeling of Fresnel zones. We compare the elastodynamic response of the fracture using the stress‐induced changes in ultrasonic wave velocities for transmitter‐receiver pairs to image spatial variations in contact properties. We show that nonlinear elasticity and permeability enhancement decrease with increasing normal stress. Additionally, post‐oscillation wave velocity and permeability exhibit quick recoveries toward pre‐oscillation values. Estimates of fracture contact area (global and local) demonstrate that the elastodynamic and permeability responses are dominated by fracture topology.

Experimental and Numerical Study of Carbon Fibre-Reinforced Polymer-Strengthened Reinforced Concrete Beams under Static and Impact Loads

This study aims to investigate the behaviour of reinforced concrete (RC) beams strengthened by Carbon Fibre-Reinforced Polymer (CFRP) under static and impact loads. A series of RC beams were tested and categorized into four groups, namely, unstrengthened RC beams (B1), RC beams strengthened with a CFRP longitudinal strip in the tension zone (B2), RC beams wrapped with CFRP fabric (B3), and RC beams strengthened with a combination of both CFRP longitudinal strips and wraps (B4). The results show that the average load–displacement capacity of RC beam group (B4) was improved by 84.88% as compared with the unstrengthened beam (B1) under static loads. The dynamic test results demonstrated an increase in the deflection resistance of RC beam group (B4) by −57.89% as compared with unstrengthened RC beam group (B1) under identical drop weights of 1 m. In addition, a collapse failure mode was noticed in the unstrengthened beams, while minor damage was recorded mainly in the case of RC beam group (B4). Furthermore, the numerical analysis conducted using LS-DYNA software (V 971 R6.0.0) proved that the adopted numerical models can efficiently predict the behaviour of RC beams under dynamic loads, with maximum differences reaching up to −12.5% compared with the experimental test results.

Advancing Offshore Renewable Energy: Integrative Approaches in Floating Offshore Wind Turbine-Oscillating Water Column Systems Using Artificial Intelligence-Driven Regressive Modeling and Proportional-Integral-Derivative Control

This research investigates the integration of Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs) to enhance sustainable energy generation, focusing on addressing dynamic complexities and uncertainties inherent in such systems. The novelty of this study lies in its dual approach, which integrates regressive modeling with an aero-hydro-elasto-servo-mooring coupled system with a deep data-driven network and implements a proportional-integral-derivative (PID) control mechanism to improve system stability. By employing Artificial Neural Networks (ANNs), the study circumvents the challenges of real-time closed-loop control on FOWT structures using the OpenFAST simulation tool. Data-driven models, trained on OpenFAST datasets, facilitate real-time predictive behavior analysis and decision-making. Advanced computational learning techniques, particularly ANNs, accurately replicate the dynamics of FOWT-OWC numerical models. An intelligent PID control mechanism is subsequently applied to mitigate structural vibrations, ensuring effective control. A comparative analysis with traditional barge-based FOWT systems underscores the enhanced modeling and control methodologies’ effectiveness. In this sense, the experimental results demonstrate substantial reductions in the mean oscillation amplitude, with reductions from 5% to 35% observed across various scenarios. Specifically, at a wave period from 20 s and a wind speed of 5 m/s, the fore-aft displacement was reduced by 35%, exemplifying the PID control system’s robustness and efficacy under diverse conditions. This study highlights the potential of ANN-driven modeling as an alternative to managing the complex non-linear dynamics of NREL 5 MW FOWT models and underscores the significant improvements in system stability through tailored PID gain scheduling across various operational scenarios.

Numerical modeling of an ASE suppression and power scalable approach in 1908nm LMA-TDFO

Numerical modeling of an ASE suppression and power scalable approach in 1908nm LMA-TDFO

Impact of the expansion ratio on the properties of hydrogen recirculation ejectors

Exploring the development characteristics and influencing factors of the mixing layer (ML) inside the hydrogen recirculation ejector is of great importance for enhancing the recirculation properties of the ejector and promoting green and sustainable energy development. However, the evolution of ML in the ejector and the transport and diffusion characteristics of the fluid are problematic, in particular, the influence of the expansion ratio on the properties of the ejector is unclear. Therefore, in this study, a CFD numerical model of an ejector was established to simulate the flow of fluids in the ejector. The evolution of ML was elucidated, and the interaction mechanism between the mixing and the recirculation performance of the ejector was revealed. The findings showed that the velocity difference is a significant driving force for the development of ML, and the formation of an adverse pressure gradient contributes to the diffusion of hydrogen and the rapid development of ML. The development process of ML in the ejector can be divided into three stages under the interaction of the velocity difference and the convective Mach number: the rapid growth stage, the slow growth stage, and the exponential growth stage. By studying the evolution of ML at different expansion ratios, it was found that there exists a critical expansion ratio for the ejector, which results in the largest of the non-mixing length ratio and the effective mixing thickness, the strongest relative mass transfer capability of the entrained flow, the fullest development of ML, and the optimal hydrogen recirculation performance.

Cold-formed Q1200 ultra-high strength steel angle- and channel-section stub columns

This paper presents the experimental and numerical analysis of cold-formed Q1200 ultra-high-strength steel (UHSS) angle- and channel-section stub columns to elucidate their resistance performance. Initially, the mechanical property test including the flat and corner coupon specimens was conducted to quantify the effect of the cold-forming process on Q1200 UHSS. Then, the stub column test was conducted on 16 cold-formed Q1200 UHSS angle- and channel-section stub columns. Based on the experimental results, a finite element model was established to simulate the resistance performance of the cold-formed Q1200 UHSS angle- and channel-section stub columns. Subsequently, a parametric study involving 133 numerical models was performed. Then, the suitability of the design approaches in EN 1993-1-12, AISI S100, AS/NZS 4600, and the direct strength method (DSM) was evaluated. For angle-section stub columns, the design approach outlined in EN 1993-1-12 was deemed suitable and the effective cross-sectional area design approach and DSM in AISI S100 were found to be safe. However, these approaches were excessively conservative for slender cross-sections in directly predicting the ultimate resistance of angle sections. Because of unsafe predictions, the design approaches in EN 1993-1-12, AISI S100, and DSM were deemed inappropriate for channel-section stub columns. The modification suggestions were proposed for the current design approaches, where the beneficial effects from the strain hardening were included. Based on the comparisons, the revised design approaches in EN 1993-1-12, AISI S100, and DSM could be used to accurately predict the ultimate resistance of the cold-formed Q1200 UHSS angle- and channel-section stub columns.

A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)

Abstract. A new calving algorithm is developed in the glacier model Elmer/Ice that allows unrestricted calving and terminus advance in 3D. The algorithm uses the meshing software Mmg to implement anisotropic remeshing and allow mesh adaptation at each time step. The development of the algorithm, along with the implementation of the crevasse depth law, produces a new full-Stokes calving model capable of simulating calving and terminus advance across an array of complex geometries. Using a synthetic tidewater glacier geometry, the model is tested to highlight the numerical model parameters that can alter calving when using the crevasse depth law. For a system with no clear attractor at a pinning point, the model time step and mesh resolution are shown to alter the simulated calving. In particular, the vertical mesh resolution has a large impact, increasing calving, as the frontal bending stresses are better resolved. However, when the system has a strong attractor, provided by basal pinning points, numerical model parameters have a limited effect on the terminus evolution. Conversely, transient systems with no clear attractors are highly influenced by the choice of numerical model parameters. The new algorithm is capable of implementing unlimited terminus advance and retreat, as well as unrestricted calving geometries, applying any vertically varying melt distribution to the front for use in conjunction with any calving law or potentially advecting variables downstream. In overcoming previous technical hurdles, the algorithm opens up the opportunity to improve both our understanding of the physical processes and our ability to predict calving.

Peridynamic modelling of cryogenic deuterium pellet fragmentation for shattered pellet injection in tokamaks

Abstract Shattered pellet injection (SPI) is a promising method for controlling plasma disruptions in tokamaks. In this study, we present numerical modelling of the fragmentation of cryogenic deuterium pellets within the context of SPI, using the peridynamic (PD) theory. A dedicated in-house code has been developed, leveraging the meshfree method and GPU parallelization. The mechanical properties of cryogenic solid deuterium are obtained from available literature, and calibrated based on the shatter threshold along with the remaining solid mass fraction after shatter. The results from the bond-based peridynamics (BB-PD) successfully reproduce the main experimental results reported in the literature, both qualitatively and quantitatively.

Impact of screw tip design on screw anchorage: mechanical testing and numerical simulation

BackgroundScrew loosening is a commonly reported issue following spinal screw fixation and can lead to various complications. The initial cause of screw loosening is biomechanical deterioration. Previous studies have demonstrated that modifications in screw design can impact the local biomechanical environment, specifically the stress distribution on bone-screw interfaces. There are several different designs of screw tips available for clinically used pedicle screws; however, it remains unclear whether these variations affect the local stress distribution and subsequent screw anchorage ability.MethodsThis study conducted comprehensive biomechanical research using polyurethane foam mechanical tests and corresponding numerical simulations to investigate this topic. Models of pedicle screw-fixed osteoporotic polyurethane foam were created with two different clinically used screw tip designs (flat and steep) featuring varying tip lengths, taper angles, and diameters, as well as identical flank overlap areas and thread designs. The anchorage ability of the different models was assessed through toggle and pull-out test. Additionally, numerical mechanical models were utilized to compute the stress distributions at the screw and bone-screw interfaces in the different models.ResultsMechanical tests revealed superior anchorage ability in models utilizing flat-tipped screws. Furthermore, numerical modeling indicated improved anchorage ability and reduced stress concentration tendency in these models.ConclusionChanges in screw tip design can significantly impact the biomechanical anchoring capability of screws. Specifically, flatter tip pedicle screws may mitigate the risk of screw loosening by alleviating stress concentration on bone-screw interfaces.

Scaffolded team-based computational modeling and simulation projects for promoting representational competence and regulatory skills

BackgroundThis study posits that scaffolded team-based computational modeling and simulation projects can support model-based learning that can result in evidence of representational competence and regulatory skills. The study involved 116 students from a second-year thermodynamics undergraduate course organized into 24 teams, who worked on three two-week-long team-based computational modeling and simulation projects and reflected upon their experience.ResultsResults characterized different levels of engagement with computational model-based learning in the form of problem formulation and model planning, implementation and use of the computational model, evaluation, and interpretation of the outputs of the model, as well as reflection on the process. Results report on students’ levels of representational competence as related to the computational model, meaning-making of the underlying code of the computational model, graphical representations generated by the model, and explanations and interpretations of the output representations. Results also described regulatory skills as challenges and strategies related to programming skills, challenges and strategies related to meaning-making skills for understanding and connecting the science to the code and the results, and challenges and strategies related to process management mainly focused on project management skills.ConclusionCharacterizing dimensions of computational model-based reasoning provides insights that showcase students’ learning, benefits, and challenges when engaging in team-based computational modeling and simulation projects. This study also contributes to evidence-based scaffolding strategies that can support undergraduate students' engagement in the context of computational modeling and simulation.

Lindemann ratio for classical and quantum crystals

Based on the delocalized of melting criterion, a relatively simple analytical (i.e., without computer simulation) method for calculating the Lindemann ratio is proposed. It is shown that for classical single-component solids (in which the melting point (Tm) is greater than the Debye temperature (Θ): Tm/Θ > 1.5), the Lindemann ratio is determined only by the packing coefficient of the structure. Calculations for various structures of classical solids (both crystalline and amorphous) showed good agreement with the estimates of other authors. For quantum single-component crystals (in which Tm/Θ < 0.4), the Lindemann ratio is determined not only by the crystal structure, but also by the Θ/Tm function. Therefore, when passing from the classical to the quantum area, the Tm(Θ) function changes its functional dependence. It was shown that for quantum crystals, the Lindemann ratio decreases with increasing pressure along the melting line. For quantum nanocrystals, the Lindemann ratio increases with an isobaric decrease in a nanocrystal size. At this, the more noticeably the shape of the nanocrystal deviates from the energy-optimal shape, the greater the sized increase in the Lindemann ratio. Therefore, the use of the Lindemann criterion to study the melting of quantum crystals (as they tried to when studying the melting of atomic metallic hydrogen) showed incorrect results.

Computer simulation‐guided template selection for a molecularly imprinted polymer for selective trifluralin adsorption

AbstractTo meet selective adsorption toward trifluralin, a novel molecularly imprinted polymer (MIP) was fabricated by the dummy template molecular imprinting technology. First, computational simulation was performed to select a suitable dummy template, 3,5‐dinitro‐4‐methylbenzoic acid (T1), based on the maximum basis set superposition error (BSSE)‐corrected binding interaction energy (ΔE) of the monomer N‐vinylpyrrolidone (NVP)‐T1 complex and its structural overlap with trifluralin. Then, the MIP was prepared via the bulk polymerization. The adsorption experiments showed the MIP exhibited a trifluralin adsorption capacity of 5.1 mg g−1, an imprinting factor (IF) of 2.2, and short adsorption equilibrium time of 5 min. The adsorption of trifluralin conformed to the Freundlich adsorption (R2 = 0.985) and pseudo‐second‐order model (R2 = 0.999). In addition, the MIP exhibited selectivity to trifluralin over other adsorbents, including structural analogs (pendimethalin and oryzalin), pesticide (carbendazim), and nitrocompounds (nitrofurantoin, furazolidone, and furaltadone), with the selectivity factor (β) in the range of 1.2–3.0, respectively. In trifluralin/oryzalin mixture, the IF toward oryzalin was still as high as 1.9. The removal rate of the MIP to trifluralin in environmental water samples ranged from 90.08% to 99.04%. This study provides theoretical and experimental insights for the preparation of MIP using dummy templates.

A novel relative-equilibrium graphical plot for rapid reversible tracer studies in dynamic PET imaging

Objective. This study aims to address the issue of long scan durations required by traditional graphical analysis methods, such as the Logan plot and its variant, the reversible equilibrium (RE) Logan plot, for dynamic PET imaging of tracer kinetics. Approach. We propose a relative RE Logan model that builds on the principles of the Logan plot and its variant to significantly reduce scan time without compromising the accuracy of tracer kinetics analysis. The model is supported by theoretical evidence and experimental validations, including two computer simulations and one clinical data analysis. Main results. The proposed model demonstrates a significant linear relationship between the variable x and the slope DVT of the RE Logan plot, and the variable x′ and the slope DVT′ of the relative RE Logan plot. The Pearson correlation coefficients (r) of the linear fitting of the x′ to the x equal 0.9849 in the simulated data and 0.9912 in the clinical data. Similarly, the r values for the linear fitting of DVT′ to DVT equal 0.9989 and 0.9988 in the simulated data, and 0.9954 in the clinical data. Significance. These results demonstrate the model’s capability to maintain strong linear relationships and produce parametric images comparable to the traditional RE Logan plot, but with the considerable advantage of shorter scan durations. This innovation holds significant potential for enhancing the efficiency and feasibility of PET imaging in clinical settings.

Computational Simulation and Experimental Analysis of Activated Carbon from Agricultural Waste as Electromagnetic Absorber

Computational Simulation and Experimental Analysis of Activated Carbon from Agricultural Waste as Electromagnetic Absorber