Unstructured Simulation Research Articles

Fuzzy logic system-based force tracking control of robot in highly dynamic environments

PurposeThe study aims to equip robots with the ability to precisely maintain interaction forces, which is crucial for tasks such as polishing in highly dynamic environments with unknown and varying stiffness and geometry, including those found in airplane wings or thin, soft materials. The purpose of this study is to develop a novel adaptive force-tracking admittance control scheme aimed at achieving a faster response rate with higher tracking accuracy for robot force control.Design/methodology/approachIn the proposed method, the traditional admittance model is improved by introducing a pre-proportional-derivative controller to accelerate parameter convergence. Subsequently, the authors design an adaptive law based on fuzzy logic systems (FLS) to compensate for uncertainties in the unknown environment. Stability conditions are established for the proposed method through Lyapunov analysis, which ensures the force tracking accuracy and the stability of the coupled system consisting of the robot and the interaction environment. Furthermore, the effectiveness and robustness of the proposed control algorithm are demonstrated by simulation and experiment.FindingsA variety of unstructured simulations and experimental scenarios are designed to validate the effectiveness of the proposed algorithm in force control. The outcomes demonstrate that this control strategy excels in providing fast response, precise tracking accuracy and robust performance.Practical implicationsIn real-world applications spanning industrial, service and medical fields where accurate force control by robots is essential, the proposed method stands out as both practical and straightforward, delivering consistently satisfactory performance across various scenarios.Originality/valueThis research introduces a novel adaptive force-tracking admittance controller based on FLS and validated through both simulations and experiments. The proposed controller demonstrates exceptional performance in force control within environments characterized by unknown and varying.

Isotropic and anisotropic mesh adaptation for RANS simulations of a nacelle under crosswind conditions

Mesh adaptation of unstructured meshes for aerodynamic simulations, that typically resolve the Reynolds Averaged Navier-Stokes (RANS) equations, is a promising approach to enable high numerical precision on complex geometries. Its objective is to minimize the discretization error without using empirical meshing guidelines. The most common approach of mesh adaptation is the “feature-based” isotropic mesh adaptation: from an initial flow prediction on an isotropic unstructured mesh, a local error estimator is computed using a flow variable. It is then used to adapt the mesh using isotropic tetrahedra. Additional near-wall resolution can be achieved by extruding prism layers from the walls. A more efficient approach is to use anisotropic mesh adaptation purely with tetrahedra that are stretched to follow the flow's preferential directions. In this work, we demonstrate the abilities of feature-based isotropic and anisotropic mesh adaptation on a complex flow phenomenon of importance for jet engines: flow separation in a nacelle under crosswind conditions. Two different solvers, adapted for either isotropic or anisotropic meshes, are employed. Results are compared with standard unstructured simulations with user-imposed mesh refinements and highlight the ability of mesh adaptation to automatically capture all the relevant flow phenomena without any user input and at reduced mesh size.

Hybrid Dynamic Mesh Redistribution - Immersed Boundary Method for Acoustic Simulation of Flow Around a Propeller

A novel hybrid dynamic mesh redistribution – immersed boundary method for simulation of turbulent flows around rotating obstacles of complex geometry and analysis of tonal acoustics is proposed. The feasibility of the approach is demonstrated by considering a drone propeller problem. The results of three-dimensional Reynolds-averaged Navier–Stokes simulations using the proposed approach are compared to the results of body-fitted unstructured simulations in noninertial reference frame. The dynamic mesh redistribution method allows the reposition of mesh points taking into account the shape of the moving body while retaining the mesh topology. The cell size and quality of the dynamically redistributed mesh strongly depend on the curvature of the body surface. The position and shape of the moving obstacle is prescribed by a distance function defined on an adaptive octree. The results of simulations using the proposed method are in good agreement with both the results of body-fitted simulations and the experimental data.

Structured and Unstructured Simulations for the Third AIAA Sonic Boom Prediction Workshop

Predictions using the launch ascent and vehicle aerodynamics (LAVA) solver framework for the NASA shock–plume interaction biconvex model and C608 supersonic aircraft prototype geometries are compared in support of the Third AIAA Sonic Boom Prediction workshop. Descriptions of the mesh generation techniques and numerical methods are provided along with a comparison of near-field and far-field predictions with available experimental data as well as other workshop submissions. Strong agreement was observed between the LAVA structured curvilinear and unstructured solver near-field predictions for the biconvex model and the C608 aircraft: predictions that were also compared against validation and verification data. Additionally, near-field and far-field ground signature results using the combination of a truncated computational fluid dynamics (CFD) domain coupled to a midfield space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM but at less computational cost.

Immersed boundary method for high-order flux reconstruction based on volume penalization

In the last decade, there has been a lot of interest in developing high-order methods as a viable option for unsteady scale-resolving-simulations which are increasingly important in the industrial design process. High-order methods offer the advantages of low numerical dissipation, high efficiency on modern architectures and quasi mesh-independence. Despite significant advance in high-order solution methods, the general CFD workflow (geometry, CAD preparation, meshing, solution, post-processing) has largely remained unchanged, with mesh generation being a significant bottleneck and often determining the overall quality of the solution. In this work, we aim to combine the numerical advantages of the high-order Flux Reconstruction (FR) method and the simplicity of the mesh generation (or lack thereof) of the Immersed Boundary Method (IBM) for steady and unsteady problems over moving geometries. The volume penalization (penalty-IBM) method is selected for its ease of implementation and robustness. Detailed discussions about numerical implementation, including the boundary representation, mask function, data reconstruction, and selection of the penalization parameter are given. Advantages of combining volume penalization in the high-order framework are shown by various numerical test cases. The approach is firstly demonstrated for the linear advection-diffusion equation by investigating the numerical convergence for the coupled FR-IBM approach. Thereafter, the accuracy of the approach is demonstrated for canonical (static) test cases in 2D and 3D when compared to a standard body-fitted unstructured simulation. Finally, the efficiency of the method to handle moving geometries is demonstrated for the flow around an airfoil with pitching and plunging motions.

Predictive accuracy of wall-modelled large-eddy simulation on unstructured grids

The predictive accuracy of wall-modelled LES is influenced by a combination of the subgrid model, the wall model, the numerical dissipation induced primarily by the convective numerical scheme, and also by the density and topology of the computational grid. The latter factor is of particular importance for industrial flow problems, where unstructured grids are typically employed due to the necessity to handle complex geometries. Here, a systematic simulation-based study is presented, investigating the effect of grid-cell type on the predictive accuracy of wall-modelled LES in the framework of a general-purpose finite-volume solver. Following standard practice for meshing near-wall regions, it is proposed to use prismatic cells. Three candidate shapes for the base of the prisms are considered: a triangle, a quadrilateral, and an arbitrary polygon. The cell-centre distance is proposed as a metric to determine the spatial resolution of grids with different cell types. The simulation campaign covers two test cases with attached boundary layers: fully-developed turbulent channel flow, and a zero-pressure-gradient flat-plate turbulent boundary layer. A grid construction strategy is employed, which adapts the grid metric to the outer length scale of the boundary layer. The results are compared with DNS data concerning mean wall shear stress and profiles of flow statistics. The principle outcome is that unstructured simulations may provide the same accuracy as simulations on structured orthogonal hexahedral grids. The choice of base shape of the near-wall cells has a significant impact on the computational cost, but in terms of accuracy appears to be a factor of secondary importance.

3D printed airway simulators: Adding a dimension to bronchoscopy training.

3D printed airway simulators: Adding a dimension to bronchoscopy training.

Schur Complement-based Substructuring of Stiff Multibody Systems with Contact

Substructuring permits parallelization of physics simulation on multi-core CPUs. We present a new substructuring approach for solving stiff multibody systems containing both bilateral and unilateral constraints. Our approach is based on non-overlapping domain decomposition with the Schur complement method, which we extend to systems involving contact formulated as a mixed bounds linear complementarity problem. At each time step, we alternate between solving the subsystem and interface constraint impulses, which leads to the identification of the active constraints. By using the active constraints to compute the effective mass of subsystems within the interface solve, we obtain an exact solution. We demonstrate that our simulations have preferable behavior compared to standard iterative solvers and substructuring techniques based on the exchange of forces at interface bodies. We observe considerable speedups for structured simulations where a user-defined partitioning can be applied, and moderate speedups for unstructured simulations, such as piles of bodies. In the latter case, we propose an automatic partitioning strategy based on the degree of bodies in the constraint graph. Because our method makes use of direct solvers, we are able to achieve interactive and real-time frame rates for a number of challenging scenarios involving large mass ratios, redundant constraints, and ill-conditioned systems.

Embedded Discrete Fracture Modeling With Artificial Intelligence in Permian Basin

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 187202, “Field Study: Embedded Discrete Fracture Modeling With Artificial Intelligence in Permian Basin for Shale Formation,” by Song Du, Baosheng Liang, and Lin Yuanbo, Chevron, prepared for the 2017 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 9–11 October. The paper has not been peer reviewed. Full-field models using unstructured grids can capture detailed geometric information such as fracture distribution. However, these are computationally expensive and often numerically unstable because of convergence issues. In the complete paper, the authors investigated embedded discrete fracture modeling (EDFM) using artificial intelligence (AI) to overcome challenges associated with unstructured modeling. Introduction It has been proved that EDFM enables flexible fracture geometry because the fracture domain is relatively independent of the matrix regions. EDFM has been widely accepted recently because of its simplicity and computational efficiency. The authors’ studies applied EDFM with AI optimization for fracture-network representation. The growth of computational power and the availability of large quantities of data have led to the widespread promotion of applications of AI technologies. AI has been used in the oil and gas industry in the areas of production optimization, operating-cost reduction, and efficiency improvement. Currently, almost all AI technologies are still limited to executing specific tasks, also known as specialized AI, an application that lacks the capability of generalized AI in adaptive learning. However, specialized AI still has advantages of high speed, superior consistency and unmatchable repeatability over human intelligence. In the complete paper, application of AI technology in processing the fracture network for successive simulation is described. Methodology EDFM. This method has drawn considerable attention because of its efficiency. EDFM minimizes the local grid resolution while preserving flow behavior between fracture and matrix by maintaining the original fracture orientation and distribution. The EDFM method is composed of two major elements: matrix and fracture. A long fracture is subdivided into small segments at the interconnecting points. A simple material-balance equation can show the flow behaviors at the cross sections. The fractures and matrix are modeled as two different domains. As de-scribed previously, fluid communication between fractures and the matrix uses mass-balance equations. Nonneighbor connection (NNC) must be calculated explicitly for a reservoir simulator. EDFM With Mangrove. Mangrove, an engineered stimulation design package, is a hydraulic-fracture simulator that links reservoir characterization and simulation and helps optimize completion designs in unconventional reservoirs. It has been of considerable use in unconventional-field development and has provided guidance for well-landing, completion-design, and well-/fracture-optimization decisions. However, the package creates unstructured simulation grids that can lead to convergence issues, and is also computationally expensive.

Prediction of Chemical Nonequilibrium Flow Structure at Different Free-Stream Knudsen Numbers

AbstractA numerical study is conducted to investigate the effects of the inflow Knudsen number (Kn) on hypersonic chemical nonequilibrium rarefied flows using the unstructured direct simulation Monte-Carlo (DSMC) method, and an empirical formula for fast prediction of flow-field structure for different values of Kn is proposed and verified. First, the flow around a vertical plate is analyzed at a free-stream velocity of 7,500 m/s using a perfect-gas model with inflow Kn values ranging from 0.035 to 13.36. Through analysis of the flow-field characteristics with varying Kn values, a linear expansion law of flow-field versus the square root of Kn is discovered and an empirical formula based on least-squares fitting is developed for fast prediction of the flow structure at different values of Kn. Further, the effects of chemical nonequilibrium on hypersonic rarefied flow-field structure are investigated to verify the applicability of the empirical formula. Finally, cases of the cylinder flow are simulated in...

ARLS: A MapReduce-based output analysis tool for large-scale simulations

As simulations are becoming popular in the analysis of the complex behavior of large-scale systems with immense inputs and outputs, there is an increasing demand to efficiently store, manage, and analyze massive simulation outputs. Hadoop and MapReduce have been used in various applications to speed up the process of analyzing large amounts of datasets. In this paper, we present ARLS (After-action Reviewer for Large-scale Simulations), a MapReduce-based output analysis tool for simulation outputs. ARLS clusters distributed storages using Hadoop and automatically composes Map and Reduce functions to process the simulation outputs. ARLS has been applied to our SAM (Surface-to-Air Missile) simulator. The SAM simulator has been developed to analyze the dynamics of a missile in designing air-defense systems. ARLS takes a large amount of unstructured simulation outputs from SAM simulator, automatically generates Map and Reduce functions to analyze the missile and the aircraft component of SAM simulator, and executes Map and Reduce jobs in parallel. The results of our experiments show that ARLS can efficiently analyze a large amount of unstructured simulation datasets by distributing datasets and computations over the cluster of commodity machines.

An improved local remeshing algorithm for moving boundary problems

ABSTRACTThree issues are tackled in this study to improve the robustness of local remeshing techniques. Firstly, the local remeshing region (hereafter referred to as ‘hole’) is initialized by removing low-quality elements and then continuously expanded until a certain element quality is reached after remeshing. The effect of the number of the expansion cycle on the hole size and element quality after remeshing is experimentally analyzed. Secondly, the grid sources for element size control are attached to moving bodies and will move along with their host bodies to ensure reasonable grid resolution inside the hole. Thirdly, the boundary recovery procedure of a Delaunay grid generation approach is enhanced by a new grid topology transformation technique (namely shell transformation) so that the new grid created inside the hole is therefore free of elements of extremely deformed/skewed shape, whilst also respecting the hole boundary. The proposed local remeshing algorithm has been integrated with an in-house unstructured grid-based simulation system for solving moving boundary problems. The robustness and accuracy of the developed local remeshing technique are successfully demonstrated via industry-scale applications for complex flow simulations.

Unstructured Road Spectrum α-stable Distribution Parameters Interval Estimation and Reconstruction Based on Moving Block Bootstrap Method

Symmetrical α-stable distribution is used to express the amplitude non-Gaussian characteristics of the unstructured road spectrum.In the in-situ road spectrum collection implementation,the route length limitation and road surface diversity may decrease the spectrum accuracy.The moving block bootstrap confidence interval estimation method is adopted to estimate the interval of the stable distribution parameters.According to both the stable distribution random series generation theory and the simulation capability of road simulation test bench,the reconstructed spectrum is composed by the amplitude truncated stable distribution random series.The validity and practicality of proposed methods are verified by reconstructing the spectrum of an off-highway vehicle riding through a test ground.An effect time domain road spectrum reconstruction method is provided for the unstructured road simulation and virtual reliability test.

An unstructured direct simulation Monte Carlo methodology with Kinetic-Moment inflow and outflow boundary conditions

The mathematical and computational aspects of the direct simulation Monte Carlo on unstructured tetrahedral grids (U3DSMC) with a Kinetic-Moment (KM) boundary conditions method are presented. The algorithms for particle injection, particle loading, particle motion, and particle tracking are presented. The KM method applicable to a subsonic or supersonic inflow/outflow boundary, couples kinetic (particle) U3DSMC properties with fluid (moment) properties. The KM method obtains the number density, temperature and mean velocity needed to define the equilibrium, drifting Maxwellian distribution at a boundary. The moment component of KM is based on the local one dimensional inviscid (LODI) boundary conditions method consistent with the 5-moment compressible Euler equations. The kinetic component of KM is based on U3DSMC for interior properties and the equilibrium drifting Maxwellian at the boundary. The KM method is supplemented with a time-averaging procedure, allows for choices in sampling-cell procedures, minimizes fluctuations and accelerates the convergence in subsonic flows. Collision sampling in U3DSMC implements the no-time-counter method and includes elastic and inelastic collisions. The U3DSMC with KM boundary conditions is validated and verified extensively with simulations of subsonic nitrogen flows in a cylindrical tube with imposed inlet pressure and density and imposed outlet pressure. The simulations cover the regime from slip to free-molecular with inlet Knudsen numbers between 0.183 and 18.27 and resulting inlet Mach numbers between 0.037 and 0.027. The pressure and velocity profiles from U3DSMC-KM simulations are compared with analytical solutions obtained from first-order and second-order slip boundary conditions. Mass flow rates from U3DSMC-KM are compared with validated analytical solutions for the entire Knudsen number regime considered. Error and sensitivity analysis is performed and numerical fractional errors are in agreement with theoretical errors. The KM method is shown to be a robust technique allowing efficient computation of subsonic flows. Additional verification of U3DSMC is achieved with simulations of the heat transfer process in a stationary argon gas between two flat plates. The numerical heat flux is in agreement with analytical results that cover the transitional to free molecular regimes. Additional validation of U3DSMC is achieved with simulations of hypersonic rarefied flows of nitrogen over a finite thickness flat pate at 0 and 10 degrees angle of attack. Numerical predictions of the pressure and heat flux to the plate are in agreement with experiments.

FACTORS OF AIRFLOW DISTRIBUTION FROM SYSTEM CEILING AIR DIFFUSERS AND ITS UNSTRUCTURED FINE ELEMENTS CFD SIMULATION

Computational Fluid Dynamics (hereafter, CFD) is one of the most useful techniques to predict the airflow distribution in air-conditioned and ventilated rooms. The previous studies show that the prescribed velocity method (hereafter, P. V. method) is effective to simulate complicated airflow from an air diffuser in CFD. However, the velocity distribution in the vicinity of the air diffuser as boundary conditions of coarse gird CFD using P. V. method can be affected by the airflow rate, the connecting conditions of the diffuser and supply air duct, and the buoyancy effect due to the temperature distribution.In this paper, the development of the versatile airflow data for P. V. method and the method for its application are discussed. In the first study, the unstructured fine elements CFD simulations under isothermal condition are carried out and the obtained airflow distributions of the system ceiling air diffuser are compared. The relationship between the airflow rate and the velocity near the diffuser, the influence of connecting conditions of the diffuser and air duct are confirmed by the comparison of CFD results. In the second study, the influence of the buoyancy near the diffuser is compared to the inertial force of discharged air on the basis of local Archimedes number obtained by the unstructured CFD simulations under non-isothermal condition.

Assessment of a fictitious domain method for patient-specific biomechanical modelling of press-fit orthopaedic implantation

In this article, we discuss an application of a fictitious domain method to the numerical simulation of the mechanical process induced by press-fitting cementless femoral implants in total hip replacement surgeries. Here, the primary goal is to demonstrate the feasibility of the method and its advantages over competing numerical methods for a wide range of applications for which the primary input originates from computed tomography-, magnetic resonance imaging- or other regular-grid medical imaging data. For this class of problems, the fictitious domain method is a natural choice, because it avoids the segmentation, surface reconstruction and meshing phases required by unstructured geometry-conforming simulation methods. We consider the implantation of a press-fit femoral artificial prosthesis as a prototype problem for sketching the application path of the methodology. Of concern is the assessment of the robustness and speed of the methodology, for both factors are critical if one were to consider patient-specific modelling. To this end, we report numerical results that exhibit optimal convergence rates and thus shed a favourable light on the approach.

An unstructured CVFEM and moving interface algorithm for non‐Newtonian Hele‐Shaw flows in injection molding

Purpose – The purpose of this paper is to develop a novel unstructured simulation approach for injection molding processes described by the Hele‐Shaw model.Design/methodology/approach – The scheme involves dual dynamic meshes with active and inactive cells determined from an initial background pointset. The quasi‐static pressure solution in each timestep for this evolving unstructured mesh system is approximated using a control volume finite element method formulation coupled to a corresponding modified volume of fluid method. The flow is considered to be isothermal and non‐Newtonian.Findings – Supporting numerical tests and performance studies for polystyrene described by Carreau, Cross, Ellis and Power‐law fluid models are conducted. Results for the present method are shown to be comparable to those from other methods for both Newtonian fluid and polystyrene fluid injected in different mold geometries.Research limitations/implications – With respect to the methodology, the background pointset infers a m...

Numerical Modeling of Gas Expansion from Microtubes

The expansion of argon jets from cylindrical microtubes is investigated using a three-dimensional unstructured direct simulation Monte Carlo (DSMC) method. The simulation results for a microtube with an aspect ratio (tube length to diameter) of 1.5 are shown to compare well with theoretical formulations of free-jet expansion. The DSMC simulations are performed in computational domains that feature both an internal microtube region and external jet expansion region. Microtubes with orifice diameters ranging between 100 μm and 100 nm are used in the simulations in order to investigate the effects of Knudsen number, aspect ratio, Reynolds number, and microtube scale on jet structure. The jet shape is shown to narrow with increasing Knudsen number, increasing aspect ratio and decreasing Reynolds number. The reduction in relative number density along the flow axis is shown to decrease with increasing Knudsen number and Reynolds number.

Quantitative Circulatory Physiology: an integrative mathematical model of human physiology for medical education

We have developed Quantitative Circulatory Physiology (QCP), a mathematical model of integrative human physiology containing over 4,000 variables of biological interactions. This model provides a teaching environment that mimics clinical problems encountered in the practice of medicine. The model structure is based on documented physiological responses within peer-reviewed literature and serves as a dynamic compendium of physiological knowledge. The model is solved using a desktop, Windows-based program, allowing students to calculate time-dependent solutions and interactively alter over 750 parameters that modify physiological function. The model can be used to understand proposed mechanisms of physiological function and the interactions among physiological variables that may not be otherwise intuitively evident. In addition to open-ended or unstructured simulations, we have developed 30 physiological simulations, including heart failure, anemia, diabetes, and hemorrhage. Additional stimulations include 29 patients in which students are challenged to diagnose the pathophysiology based on their understanding of integrative physiology. In summary, QCP allows students to examine, integrate, and understand a host of physiological factors without causing harm to patients. This model is available as a free download for Windows computers at http://physiology.umc.edu/themodelingworkshop.

Unstructured 3D gridding and upscaling for coarse modelling of geometrically complex reservoirs

The generation of accurate and reliable unstructured 3D models for reservoir simulation remains a challenge. In this paper, new developments for grid generation, upscaling and streamline simulation for such models are described. In combination, these techniques provide a prototype workflow for the construction of unstructured simulation models. The grid generation framework described here allows the incorporation of both geometrical constraints and grid-resolution targets. Flow adaptation of the unstructured grid (i.e. higher grid density in key regions) is accomplished through the use of single-phase flow calculations on the underlying geocellular grid, which are used to generate target grid resolution maps for the unstructured coarse model. A novel transmissibility upscaling procedure is introduced to capture the effects of fine-scale heterogeneity. A new method for streamline simulation on unstructured grids is also introduced. This technique provides an efficient flow-based diagnostic for the assessment of the coarse simulation model in terms of flow response. The performance of the various components of the methodology is demonstrated using several examples.