Efficient Numerical Model Research Articles

Toward understanding the hydrologic, ecologic and community flooding implications of coastal restoration strategies: Sediment diversions

Evaluating the real-world impacts of proposed restoration strategies is a complex process. Typically, restoration is pursued to achieve a number of primary and secondary objectives as most coastal and deltaic areas support a variety of functions and activities with substantial social and economic values. In this analysis, we demonstrate the importance of considering the broad implications of planning and implementing restoration projects. We use a recently developed simplified and computationally efficient biophysical numerical model. The Mid-Barataria Sediment Diversion, a restoration project approximately 60 km down the Mississippi River from New Orleans, Louisiana, USA, offers an opportunity to quantify the benefits and potential impacts of large-scale restoration. Operation plans of the diversion are employed in this analysis to reveal the delicate balance between its potential benefits and possible adverse effects. Evaluation metrics include net land change and landscape evolution, change in salinity and subsequent shift in the distribution of marsh types, long-term change in the hydroperiod and marsh inundation, and change in the flood risk for unique local coastal communities and culture. We also consider subaqueous basin infilling, spatial sediment deposition, and creation of shallow water areas that might be of ecological value. These metrics are evaluated collectively under a set of future scenarios capturing long-term impacts of sea level rise and subsidence. This analysis provides evidence in favor of using a multi-metric approach to holistically evaluate restoration during the planning and design phases, as well as to guide the process of adaptively managing restoration projects post construction.

An efficient numerical model for the sound radiation from a supported rail

In this work, the sound radiation of a supported rail is investigated using a numerical 2.5D Finite Element model that is coupled with a 2.5D Boundary Element model. The vibration of the track is modelled by coupling the infinite rail to an equivalent continuous double-layer support and is used as input for calculating the consequent sound radiation. An interpolation method that allows for a quick solution of the boundary element calculations is proposed and validated by comparison with an analytical solution, showing differences less than 0.1 dB. The assembled model is used for calculating the sound radiation from the rail in terms of sound power per unit squared force applied to the rail head in vertical and lateral directions for three different rail configurations. The transfer functions obtained can be used in rolling noise calculations. The proposed interpolation method allows calculations that are more than 100 times faster than the regular procedure for the case considered.

Modeling of a moving point source in inhomogeneous and turbulent media - Application to aircraft noise

Engineering solutions for the modeling of aircraft noise often rely on simplified approaches that consider quasi-static sources and homogenous propagation conditions. These hypothesis may lead to significant inaccuracies on sound pressure level predictions in certain configurations, especially for source traveling at high mach number and at several hundred meters from the receiver. In order to overcome these limitations, an efficient numerical model based on the coupling of a heuristic formulation and a ray-tracing model is proposed. The modeling takes into account source motion effect (Doppler effect and convective amplification), as well as the sound propagation phenomena in inhomogeneous media (waves refraction and scattering by atmospheric turbulence). Several case study related to aircraft noise are presented, for which wind and temperature profiles correspond to experimental measurements. The influence of atmospheric turbulence for such configuration is finally discussed. This work is part of the program MAMBO (Advanced methods for engine and aicraft noise modelling" coordinated by Airbus SAS and supported by the Direction Générale de l'Aviation Civile (DGAC).

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. The highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

Nonlocal Strain Gradient Theory for Free Vibration Analysis of FG Nano-scale Beams in Thermal Environments Using an Efficient Numerical Model

Nonlocal Strain Gradient Theory for Free Vibration Analysis of FG Nano-scale Beams in Thermal Environments Using an Efficient Numerical Model

Numerical Investigation of Funicular Liquid Bridges between Three Spherical Grains in a Bidisperse Particulate System.

Appropriate capillary effects are beneficial for controlling the wet powder performance and agglomerate formation. As water content rises, the funicular regime supplants the pendular regime as the predominant state in wet granular media. The displacement of grains leading to the stretching of funicular liquid bridges until rupture is an interesting and common phenomenon. Utilizing Surface Evolver software (an energy minimization approach), this work develops an efficient and accurate numerical model to describe liquid interactions among three spherical grains. The effects of liquid volume, contact angle, grain size ratio, grain-pair gap, and separation distance on the capillary forces and rupture distances are investigated. Notably, we present a modified closed-form equation for predicting the rupture distance of funicular bridges between three grains, which reflects the coupled effects of the contact angle, grain size, and liquid volume on rupture distance. This present study provides insights for incorporating capillary effects into mechanical models relying on microassembly composed of several grains in bidisperse particulate systems. Additionally, the numerical findings confirm some findings regarding the splitting of funicular bridges.

Numerical modeling and thermal performance analysis of deep borehole heat exchangers considering groundwater seepage

Exploitation of deep geothermal energy based on a deep borehole heat exchanger (DBHE) system significantly promotes green and low-carbon development. The DBHE is the core apparatus of this system, and many mathematical models have been proposed to investigate its thermal performance. However, groundwater seepage which is one of the most important factors has not been considered in most previous numerical models. In addition, the temperature distribution of rock and soil with different seepage velocities during the thermal recovery period is still unclear. Therefore, to fill this research gap, there is a strong need to propose a novel numerical model for DBHEs that considers groundwater seepage and can be solved quickly. In this paper, a computationally efficient numerical model that considers groundwater seepage is proposed. Compared with the experimental data from a field test, the model’s root mean square error is 1.33 °C. Moreover, the time required for the simulation of DBHE operation for one year using this model is only 47.3 s. Then, the effects of groundwater seepage on the DBHE and rocky soil are investigated. The findings demonstrate that when the seepage velocity is high, the thermal performance of the DBHE will be underestimated if groundwater seepage is neglected. At the seepage velocities of 1 × 10-7, 3 × 10-7 and 5 × 10-7 m/s, the heat extraction rate of the DBHE increased by 4.92 %, 10.83 %, and 15.34 %, respectively, compared to the heat extraction rate of the DBHE calculated without taking the groundwater seepage into account. Furthermore, groundwater seepage can increase the temperature recovery capacity of rock and soil. The natural temperature recovery rate of rock and soil without seepage is 86.20 %, and the temperature recovery rate is 93.11 % if the seepage velocity reaches 1 × 10-7 m/s. This study provides essential theoretical guidance for DBHE system design in areas with high groundwater seepage velocities.

Enhanced forming height and accuracy of thin-walled aluminum alloy by impact pneumatic forming

To enhance the plastic deformation capacity of hard-to-deform metal materials, the utilization of impact pneumatic forming technology is proposed for shaping complex thin-walled structures within milliseconds at room temperature. In this study, an efficient numerical simulation model is established and experiments were performed to investigate the forming height, limits, and accuracy of aluminum alloy components. The experimental results show a 21.4 % increase in the ultimate forming height when employing impact pneumatic forming as compared to quasi-static pneumatic forming. Moreover, as the initial gas pressure increases, part forming height experiences an increase but the gas compression rate experiences a decline. The simulation results reveal a maximum deformation velocity of 43.19 m/s and a limited strain rate exceeding 134 s−1, affirming the connection between increased forming height and high strain rate. Furthermore, the actual contours of parts under different gas pressures align with the simulation results, validating the reliability of the simulation. It is shown that a high gas pressure of more than 20 MPa applied for a long time can improve the forming accuracy of flat bottom and wave parts. Microstructural analysis shows that dislocations in the specimens subjected to IPF conditions are better distributed, and the dimples at the fracture sites are more pronounced. This further substantiates that the IPF process improves the plastic deformation capacity of hard-to-deform materials.

Modeling gas flow in low-permeability formations: An efficient combination of mixed finite elements and high order time integration schemes

Numerical simulation of gas flow in low permeability formations is a challenging task due to the high nonlinearity induced by (i) the compressibility of the gas, (ii) the Klinkenberg slippage effect and (iii) the Langmuir adsorption of the gas on the pore surface. Because of these nonlinearities, modeling gas flow in low permeability formations requires a great deal of computational effort. In this work, we develop an efficient numerical model using advanced spatial and temporal discretization methods for a simultaneous solution of the coupled equations of gas flow, cubic Peng-Robinson equation of state, slippage effect and Langmuir adsorption. The spatial discretization is performed with the lumped hybrid formulation of the mixed finite element method which is well adapted for fluid flow in heterogeneous porous media. The time integration is performed with high-order methods via the method of lines (MOL) which allows large time steps and efficient solution of the nonlinear system of equations. Numerical experiments, performed for gas extraction in a heterogeneous domain, point out the high efficiency of the new model since it can be until 10 times more efficient than the classical first-order time discretization method. Results of global sensitivity analysis show that the intrinsic gas-phase permeability and the Klinkenberg factor are the most influential parameters controlling the pumping rate in the case of gas extraction in a homogeneous domain.

Research On Numerical Wave Tank Based on SPH Method

Numerical wave-current flume is one of the effective methods to study waves and their effects on structures. In this paper, the Smoothed Particle Hydrodynamics (SPH) method is used to simulate and analyze the numerical wave flume. Based on the SPH method, an efficient and flexible numerical wave tank model is constructed to simulate complex water wave dynamics. Firstly, the basic principle of SPH method is summarized, and then the establishment process of numerical wave tank model is described in detail, including particle initialization, boundary condition setting and so on. Through the flume simulation under different wave conditions, the accuracy and stability of the model are verified. Finally, the interaction between wave and structure is studied. It provides a new and effective tool for the numerical simulation of wave flume, and also provides a useful reference for the related research in the fields of marine engineering and coastal protection.

Efficient multimode vectorial nonlinear propagation solver beyond the weak guidance approximation

In this paper, we present an efficient numerical model able to solve the vectorial nonlinear pulse propagation equation in circularly symmetric multimode waveguides. The algorithm takes advantage of the conservation of total angular momentum of light upon propagation and takes into account the vectorial nature of the propagating modes, making it particularly relevant for studies in ring-core fibers. While conventional propagation solvers exhibit a computational complexity scaling as Nmode4, where Nmode is the number of considered modes, the present solver scales as Nmode3/2. As a first example, it is shown that orbital angular momentum modulation instability processes take place in ring-core fibers in realistic conditions. Finally, it is predicted that the modulation instability process is followed by the appearance of breather-like angular structures.

Modelling progressive collapse of timber buildings

An efficient and accurate numerical model is indispensable for assessing structural robustness and progressive collapses. This paper presents a parametric numerical framework for the modelling of progressive collapses of inelastic timber buildings subjected to the loss of arbitrary members using dynamic analysis with large deformations and an incremental damping scheme. The model can simulate true separation and removal of elements, as well as debris tracking and impact loading derived from classical mechanics. The framework is demonstrated on a moment-resisting timber frame building with linear-elastic members and inelastic beam–column connections with hysteresis subjected to ground-floor column-loss scenarios. It can be used for large-scale analyses to assess the structural robustness of a wide range of building types, materials, and damage scenarios.

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.

Simulation of wave scattering over a floating platform in the ocean with a coupled CFD-IBM model

A numerical study of linear wave scattering over a floating platform has been simulated by an efficient numerical model in this letter. The non-hydrostatic model is used to simulate the free surface and the uneven bottom. For the solid body modelling, the immersed boundary method (IBM) is implemented by introducing a virtual boundary force into the momentum equations to emulate the boundary conditions. This implementation enhances the ability of the model to simulate interactions between waves and floating structures. A numerical case involving wave interactions with a floating platform is studied to validate the numerical model. By simulating the wave propagation, the numerical model captures the variation of the wave scattering very well, which verifies the performance of the numerical model and the robust strategy of the IBM.

An immersed boundary method coupled non-hydrostatic model for free surface flow

An efficient numerical model has been developed for the study of three-dimensional free surface flow, which combines a non-hydrostatic model with the immersed boundary method (IBM). The model utilizes the transformed σ coordinate in the vertical direction, which has been found to be highly effective in accurately capturing the free surface and uneven bottom. In addition, IBM is implemented by introducing a virtual boundary force into the momentum equations to emulate the natural boundary conditions. This implementation enhances the ability of the model in simulating the interactions of wave and solid structures. A robust boundary recognition method is used to identify the location of IB cells neighboring the virtual boundary. Furthermore, a water elevation correction method has been proposed to handle the integral discontinuity in the vertical direction caused by the submerged solid bodies. By adding the virtual boundary forces to the IB cells, the no-slip velocity condition at the solid boundary is effectively enforced. To validate the performance of the model, the numerical results have been compared with experimental data. The benchmark tests focused on the free surface evolution, velocity distributions and the dynamic pressures verified the performance of the numerical model and the robust strategy of the IBM.

The evolution of Arctic permafrost over the last 3 centuries from ensemble simulations with the CryoGridLite permafrost model

Abstract. Understanding the future evolution of permafrost requires a better understanding of its climatological past. This requires permafrost models to efficiently simulate the thermal dynamics of permafrost over the past centuries to millennia, taking into account highly uncertain soil and snow properties. In this study, we present a computationally efficient numerical permafrost model which satisfactorily reproduces the current ground temperatures and active layer thicknesses of permafrost in the Arctic and their trends over recent centuries. The performed simulations provide insights into the evolution of permafrost since the 18th century and show that permafrost on the North American continent is subject to early degradation, while permafrost on the Eurasian continent is relatively stable over the investigated 300-year period. Permafrost warming since industrialization has occurred primarily in three “hotspot” regions in northeastern Canada, northern Alaska, and, to a lesser extent, western Siberia. We find that the extent of areas with a high probability (p3 m>0.9) of near-surface permafrost (i.e., 3 m of permafrost within the upper 10 m of the subsurface) has declined substantially since the early 19th century, with loss accelerating during the last 50 years. Our simulations further indicate that short-term climate cooling due to large volcanic eruptions in the Northern Hemisphere in some cases favors permafrost aggradation within the uppermost 10 m of the ground, but the effect only lasts for a relatively short period of a few decades. Despite some limitations, e.g., with respect to the representation of vegetation, the presented model shows great potential for further investigation of the climatological past of permafrost, especially in conjunction with paleoclimate modeling.

Towards an efficient multi-scale numerical model of the impact behavior of woven materials with global/local approach

This paper presents the global/local approach in the multi-scale modeling of woven material impact behavior. This approach optimally considers important microscopic mechanisms to accurately predict outcomes and reduce computational time. The inspiration for this approach stems from the specific behavior exhibited by woven materials under ballistic impact:(1) Zone 1 (Local) is a small square around the impact position, requiring comprehensive microscopic modeling to describe complex physical phenomena accurately.(2) Zone 2 (Global) represents the remaining fabric outside of Zone 1, exhibiting more global behavior and modeled with a mesoscopic model.Building upon a previous work's joining technique, an interface between these two zones is implemented and validated through numerical tensile testing. The proposed approach is then compared to the complete mesoscopic model already validated in the case of a 2D Kevlar KM2 woven fabric submitted to ballistic impact. The global/local approach demonstrates slightly greater flexibility due to the presence of microscopic yarns. It successfully predicts all microscopic phenomena while significantly reducing the degrees of freedom compared to full microscopic modeling along the entire yarn length.

An efficient nonlinear hybrid model of energy dissipation piers utilizing fiber beam and self-developed hysteretic spring elements

Energy dissipation piers comprised of concrete filled steel tubular (CFST) columns and steel shear links can exhibit good seismic performance by reasonable collaborative optimization design of columns and links. Considering the time and economic costs of experiments and fine element analysis (FEA), an efficient and accurate numerical model is critical to investigate the hysteretic behavior of energy dissipation piers under earthquake action. Therefore, a hysteretic constitutive law for steel shear links is first proposed including the theoretical shear force-deformation skeleton curve and the unloading and reloading rules during hysteretic loading. Next, a hysteretic spring model is developed for efficiently simulating the hysteretic mechanical behavior of steel shear links, which is validated to have good accuracy with comparison to fine FEA and experimental results. Then, a simplified hybrid model consisting of the self-developed spring model and fiber beam model and two multi-scale FEA models with different levels of refinement are established for nonlinear analysis of energy dissipation piers, respectively. The comparison of numerical and test results confirms that the innovative fiber beam-spring hybrid model can accurately describe the hysteretic performance of energy dissipation piers, especially the detailed mechanical behavior of steel shear links and column feet, which provides an efficient numerical tool for analysing the collaborative working mechanism of energy dissipation piers and similar energy dissipation structures.

A machine learning model of liquid bridge force and its application in discrete element method

Developing an accurate and efficient contact model for discrete element method (DEM) simulation that can describe the microscopic dynamics of low moisture content wet granular systems continues to be a major challenge. In this study, a improved energetic approach based on the traditional linear unit discretization method is introduced to solve liquid bridge problems. This improved approach significantly ameliorates the efficiency of constructing the databases while ensuring high data accuracy. Using this method, we generated databases consisting of 163,440,000 and 2043,000 data points for the sphere-sphere and sphere-wall systems, respectively. Machine learning capillary force models (ML-Capillary) are trained using the Catboost algorithm. These models demonstrate excellent performance in predicting capillary force between particles as well as between particles and walls, considering different particle sizes, moisture levels, and contact angles, while neglecting the influence of gravity. The corresponding relative errors are below 1.5% and 2%, respectively, which are lower than existing simulation models. We incorporated the obtained models into the discrete element method and calculated capillary force between particle pairs and simulated wet granular column collapse tests. The simulation results show good agreement with experimental results in terms of parameters such as inter-particle capillary forces and particle column collapse run-out length. This study will provide an accurate and efficient numerical model for simulating low saturation wet granular systems using the discrete element method.

A running-in strategy based on an efficient wear simulation model for double circular-arc spiral bevel gears

A proper running-in process is necessary for double circular-arc spiral bevel gears to achieve desirable meshing performance. However, this type of gear transmission lacks a suitable running-in wear model, which brings great difficulties to the design of appropriate running-in strategies. To address this problem, the present study establishes an efficient numerical wear model to reveal the wear behavior of double circular-arc spiral bevel gear pairs, based on which a step-wise load running-in strategy is proposed. The established Archard's wear model considers the meshing characteristics of double circular-arc spiral bevel gears and sets a small threshold value, which can reflect the wear behavior of this gear in the running-in stage. To improve the computation efficiency, a two-step parameter updating strategy is proposed to enhance the iteration of p and s. The wear simulation reveals the quantitative relationship contact pressure and running-in cycle during the running-in process. Based on the reveal relationship, a step-wise load running-in strategy is proposed to sharpen the running-in period. The developed wear model and the proposed running-in strategy can be extended to other types of gears with circular-arc profiles.