Initial Grid Research Articles

Numerical construction tests to assess the feasibility of placement grids for Cubipod Homogeneous Low-Crested Structures

Placement grid design is a key phase when constructing armor layers in mound breakwaters. Homogeneous Low-Crested Structures (HLCS) are low-crested structures designed as artificial reefs for marine colonization, coral reef regeneration and beach protection. The placement grid affects the construction feasibility, hydraulic stability and wave transmission of HLCS. This study presents a numerical methodology to simulate a realistic placement procedure for armor units during the construction of HLCS. This numerical simulator is based on the open-source physics engine Bullet Physics Engine (BPE), which applies Newton's laws of motion to rigid bodies. From an initial theorical placement grid for Cubipod HLCS, a series of numerical realistic unit placement tests are carried out to emulate the placement process at prototype scale; placement velocity and spatial deviation of crawler cranes are given parameters associated with each specific project. Considering the placement velocity and spatial deviation during construction, the quality of each specific placement grid is associated with the measured placement errors and the corresponding initial construction deviation to HLCS. This numerical methodology is valuable to understand the influence and the uncertaintly of the construction procedure of armor layers in mound breakwaters.

Toward high-fidelity Numerical Wave Tank development: Scale resolving Partially-Averaged Navier–Stokes simulations of dam-break flow

Numerical Wave Tanks (NWTs) based on Navier–Stokes equations are emerging as valuable tools for simulating various ocean and coastal engineering flows. By capturing essential hydrodynamic non-linearities, including turbulent processes, these Navier–Stokes based NWTs can potentially provide high-accuracy data to complement traditional experimental wave basins for design and development applications. Many NWT approaches currently use the RANS (Reynolds Averaged Navier–Stokes) method. For many coastal resiliency and wave-energy converter applications, a higher fidelity turbulence treatment may be needed. In this work, we explore the applicability of the scale-resolving Partially-Averaged Navier–Stokes (PANS) technique for NWT computation. The PANS model is employed to study the dam-break benchmark case which is an important benchmark case for seawall and wave energy converter hydrodynamics analysis. Computations using RANS are also provided as a reference for accuracy and computational effort. The objectives are to: (i) investigate the effect of enhancing turbulence scale resolution on the pressure field, wave elevation and three-dimensional effects within the tank; and (ii) examine the influence of initial kinetic energy and grid resolution on the results. It is shown that, the early transient behavior is reasonably insensitive to scale resolution or initial turbulence level. Indeed, RANS and PANS of different scale resolutions yield similar results in the early stages as the flow physics is dominated by quasi-linear flow processes. The differences between RANS and PANS appear at later times. The so-called second pressure peak, standing wave amplitude and three-dimensional effects are better captured with increasing scale resolution for the same grid resolution. Overall, the results indicate that PANS is a viable model for NWT applications, with more detail being captured at a similar computational cost compared to RANS.

Enhanced Checkerboard Detection Using Gaussian Processes

Accurate checkerboard detection is of vital importance for computer vision applications, and a variety of checkerboard detectors have been developed in the past decades. While some detectors are able to handle partially occluded checkerboards, they fail when a large occlusion completely divides the checkerboard. We propose a new checkerboard detection pipeline for occluded checkerboards that has a robust performance under varying levels of noise, blurring, and distortion, and for a variety of imaging modalities. This pipeline consists of a checkerboard detector and checkerboard enhancement with Gaussian processes (GP). By learning a mapping from local board coordinates to image pixel coordinates via a Gaussian process, we can fill in occluded corners, expand the board beyond the image borders, allocate detected corners that do not fit an initial grid, and remove noise on the detected corner locations. We show that our method can improve the performance of other publicly available state-of-the-art checkerboard detectors, both in terms of accuracy and the number of corners detected. Our code and datasets are made publicly available. The checkerboard detector pipeline is contained within our Python checkerboard detection library, called PyCBD. The pipeline itself is modular and easy to adapt to different use cases.

Determination of the bone tissue mechanical properties by a numerical-digital method using CT data

Modeling of elements of inhomogeneous media is an actual direction in the study of composite materials and biomechanics objects. The need for research is determined by the insufficient development of methods for describing mechanical parameters, taking into account the anisotropy of materials. In this case, one of the directions is the use of digital prototyping and numerical modeling methods. In the field of biomechanics, the applicability of approaches to numerical modeling based on image data correlates with cases of clinical practice, which is due to the peculiarities of non-destructive testing methods and allows obtaining results that affect the quality of treatment. The paper considers a method for restoring effective mechanical properties of a material based on computational and field experiments. The simulation was based on the finite element method and assumed the use of data from a digital prototype obtained by computed tomography. The restoration of the calculated area was performed by filtering the initial grid relative to the proportion of the content of the material. The presented method makes it possible to restore the effective values of the elastic modulus and tangential modules based on the relationship established within the framework of the approach between the mechanical properties of the material and the loading parameters of the model sample. In the course of the work, the bone organs of pigs were modeled. Animal husbandry and experimental procedures were carried out in compliance with bioethical norms. Physical tests and numerical modeling were carried out under the conditions of bending action. Validation of the obtained distribution of values of the stress-strain state was performed according to the data of full-scale experiments. The presented solution showed a weak dependence of the results (less than 1 %) relative to the degree of discretization of the computational domain, which made it possible to perform calculations using fewer finite elements, avoiding the use of resource-intensive methods to restore the geometry of the sample. The results obtained in the framework of the work correspond to the literature data and determine the true values, the use of which in calculations makes it possible to assess the strength of the elements of an inhomogeneous structure under the action of external loads, taking into account the spatial distribution of the material.

Synthesis of Large Ultrawideband Sparse Planar Arrays by Utilizing a Cooperative Coevolutionary Iterative Fourier Transform

This letter introduces a cooperative coevolutionary iterative Fourier transform (CCIFT) technique to extend the conventional IFT to large ultra-wideband (UWB) sparse planar array synthesis. In the proposed CCIFT, a dense initial element position grid such as a spacing of half a wavelength at the highest frequency is adopted to avoid the presence of grating lobes at high frequency band, and a probability-assisted element selection mechanism is presented to guarantee the obtained array layout to meet a preset minimum spacing constraint, enabling the placement of physical UWB antenna elements. In addition, a cooperative coevolutionary strategy is presented to avoid prematurity by establishing the information interaction between different excitation distributions from multiple parallel IFT procedures. Two examples are conducted and results show that the CCIFT can achieve a considerably lower peak sidelobe level (PSL) than some state-of-art algorithms within an acceptable CPU time, which demonstrates its effectiveness and superiority.

Self-Adaptive Mesh Generator for Global Complex Roots and Poles Finding Algorithm

In any global method of searching for roots and poles, increasing the number of samples increases the chances of finding them precisely in a given area. However, the global complex roots and poles finding algorithm (GRPF) (as one of the few) has direct control over the accuracy of the results. In addition, this algorithm has a simple condition for finding all roots and poles in a given area: it only requires a sufficiently dense initial grid. However, in practice, this requirement may turn out to be very difficult to implement. For a complex and sophisticated function, the use of a regular high-density mesh may be ineffective or even impossible due to limited computational resources. In this article, a method for creating a self-adaptive initial mesh for this algorithm is presented. The proposed solution uses gradient calculation to identify areas that require mesh refinement, including areas where a zero and a pole are in close proximity. The adaptive mesh allows for faster and more accurate analysis of functions with a much smaller number of samples. As shown in the numerical examples, this approach reduces the number of function calls by several orders of magnitude, and thus significantly reduces the computational time.

Adaptive Grid Refinement Method for DOA Estimation via Sparse Bayesian Learning

In sparse signal recovery methods for direction of arrival (DOA) estimation, a set of uniform angular grid points is usually predefined. Dense grid points will improve the resolution and precision, but increase computational workload distinctly. To improve the efficiency and performance when using coarse initial grid points, an adaptive grid refinement (AGR) sparse Bayesian learning (SBL) method is proposed. The key idea of the proposed method is to adaptively insert new grid points based on the spatial spectrum learned from SBL iterations, as a result, grid points become denser and denser around the potential DOAs. The number of total grid points in the AGR process is much smaller than that of traditional uniform grid points, which enhances the computation efficiency. After the improved on-grid estimation of the AGR process, a post-processing DOA search procedure is implemented to reduce the off-grid DOA error. Furthermore, the proposed method is extended into the wideband case. Simulation results demonstrate that the proposed method has higher computation efficiency and precision than the classical off-grid SBL methods in scenarios of low SNR and limited snapshots. The effectiveness of the proposed method is also validated using the data of the SWellEx-96 ocean acoustic experiment.

Successful stereoelectroencephalography re-evaluation in epilepsy patients after failed initial subdural grid evaluation.

Epilepsy surgery success is dependent on accurate localization of the epileptogenic zone. Despite the use of invasive EEG using subdural grids and strips, surgical failures can occur. In this series, we explore the utility of a second evaluation with stereoelectroencephalography in patients whose initial invasive evaluation with subdural grid electrodes was unsuccessful in localizing seizure origin. We conducted a retrospective review of patients who underwent subdural grid evaluation (SDE) at our center and identified patients who underwent a re-evaluation with stereoelectroencephalography (SEEG). We identified three patients who had both subdural and SEEG electrodes in the region of the identified epileptogenic zone in whom the initial SDE evaluation failed to make the patients seizure-free. Two of these patients underwent a second resection and became seizure-free. Stereoelectroencephalography can be useful in the re-evaluation and re-operation of patients who previously had surgical failure using SDE.

Optimal Load Redistribution in Distribution Systems Using a Mixed-Integer Convex Model Based on Electrical Momentum

This paper addresses the problem concerning the efficient minimization of power losses in asymmetric distribution grids from the perspective of convex optimization. This research’s main objective is to propose an approximation optimization model to reduce the total power losses in a three-phase network using the concept of electrical momentum. To obtain a mixed-integer convex formulation, the voltage variables at each node are relaxed by assuming them to be equal to those at the substation bus. With this assumption, the power balance constraints are reduced to flow restrictions, allowing us to formulate a set of linear rules. The objective function is formulated as a strictly convex objective function by applying the concept of average electrical momentum, by representing the current flows in distribution lines as the active and reactive power variables. To solve the relaxed MIQC model, the GAMS software (Version 28.1.2) and its CPLEX, SBB, and XPRESS solvers are used. In order to validate the effectiveness of load redistribution in power loss minimization, the initial and final grid configurations are tested with the triangular-based power flow method for asymmetric distribution networks. Numerical results show that the proposed mixed-integer model allows for reductions of 24.34%, 18.64%, and 4.14% for the 8-, 15-, and 25-node test feeders, respectively, in comparison with the benchmark case. The sine–cosine algorithm and the black hole optimization method are also used for comparison, demonstrating the efficiency of the MIQC approach in minimizing the expected grid power losses for three-phase unbalanced networks.

Anisotropic Cartesian Grid Generation Strategy for Arbitrarily Complex Geometry Based on a Fully Threaded Tree

In this work, we present a powerful method for anisotropic Cartesian grid generation for arbitrarily complex 3D geometry. The proposed method addresses a number of challenging topics to achieve robustness and efficiency in mesh generation. In addition to displaying the basic information, including the generation of the initial uniform grid, the cell size, the cell number, and the cell centre coordinates, a modified fully threaded tree (FTT) data structure for use in the anisotropic Cartesian grid framework is also developed. Moreover, three criteria are proposed to ensure reasonable neighbourhood relations. A five-step adaptive mesh refinement strategy is developed to portray complex geometric details with high fidelity and maintain a reasonable number of cells. Three three-dimensional meshing experiments are implemented to illustrate and evaluate the present mesh generation performance, such as the number of cells, neighbour query runtime, total runtime, and memory consumption. Our results show that the proposed method overcomes the problems of a large number of cells and high memory consumption compared to the conventional isotropic Cartesian grid method. Additionally, mesh generation based on the modified FTT data structure outperforms the conventional 2 n tree data structure in terms of the neighbour query runtime, total runtime, and memory consumption. At last, a solution example is given to verify the proposed strategy. • A powerful strategy for anisotropic Cartesian grid generation is proposed. • A fully threaded tree (FTT) data structure for use in the anisotropic Cartesian grid framework is developed. • A five-step adaptive mesh refinement strategy is described. • The efficiency of anisotropic Cartesian grid generation for complex 3D geometry is assessed.

Effectiveness of compaction of the initial well grid in the late stage of oil and gas field development

The Kruk oil and gas field development is characterized by its geological structure and various technological indicators. A comprehensive evaluation of the field’s properties has allowed for the determination of recoverable oil reserves using water-based oil displacement techniques. Two scenarios were considered for field development: one with an initial well mesh and another with a densified well grid. The results demonstrated the high efficiency of well grid densification during the later stages of field development. This optimization strategy led to a notable increase in the rate of oil withdrawal and enhanced the recovery of geological reserves. The densification of the well grid improved the overall efficiency of oil production and contributed to maximizing the extraction of available oil reserves. The findings highlight the importance of employing advanced technological strategies to enhance oil and gas field development. By carefully considering the geological structure and implementing well grid densification when appropriate, it is possible to optimize oil recovery, increase productivity, and effectively utilize the available geological reserves in the Kruk field.

A structured grid generation framework based on parameterization for the design of free-form gridshells

Free-form gridshells have become a regional landmark because of their light and smooth architectural style. Structured grids with regular and straightforward topological connections are often the best choice for the holistic design of free-form gridshells. However, it is difficult to create a structured grid that can embody the architectural connotation and facilitate manufacturing and construction process over free-form surfaces, especially surfaces with complex shapes. To generate structured grids with fair lines, regular cells, and uniform edges over surfaces and to better interactively control the direction and size of grids, this paper proposes a parameterization-based grid generation framework. Firstly, a bubble-packing method is applied to obtain an initial grid over the given surface. Secondly, a grid parameterization algorithm that is as shape-preserving as possible is proposed and used to produce the parameter domain of the initial grid. Thirdly, a fair, regular, and uniform planar structured grid is generated in the parameter domain, and the direction and size of the grid can be adjusted by changing corresponding parameters. Finally, the planar structured grid is mapped to the given surface to obtain the final grid. As part of the new contribution of this paper, the calculation method of the fairness index is improved to quantitatively evaluate the fairness of the structured grid. The regularity and uniformity are also evaluated in terms of grid cell shape quality and grid edge lengths. Three case studies are presented to demonstrate the validity of the proposed framework. The proposed framework can be effective at reducing mapping distortion and can produce grids that meet the requirements of fairness, regularity, and uniformity.

An Improved CLIQUE Algorithm

CLIQUE is a clustering algorithm based on grid and density, which is sensitive to grid division parameter M and density threshold R, and has poor clustering accuracy. This paper proposes an improved algorithm, which is not sensitive to the initial grid division parameter M, and can automatically split the grid. Combined with the K-means algorithm, the clustering effect is improved. The F value on the S1 dataset is 36.9% higher than that of the classic CLIQUE algorithm.

Assessment of the grid-related loss of offsite power to the nuclear power plants in the presence of wind farms

Grid stability affects the progression of loss of offsite power scenarios to the nuclear power plants, as the most dominant core-damage-inducing initiating event. The ever-increasing tendency toward integration of large-scale wind farms into the transmission systems drastically challenges their dynamic behavior.In this study, we proposed a dynamic-probabilistic framework to evaluate the effect of wind penetration scenarios on the frequency of occurrence of LOOP to the NPPs. We developed 30 initial grid states, including 3 wind penetration percentages, 5 operational loading levels, in both optimal and normal power flows.We estimated 150 GR-LOOP frequencies for 5 NPP locations upon 3Ph-Shc faults on the transmission lines. Extending from 1.3 × 10−7 to 9.6 × 10−5 (year)−1 for the safest to the riskiest situations, the mean GR-LOOP frequencies have been assessed as 1.74 × 10−5, 2.96 × 10−5, and 2.77 × 10−5 (year)−1, for grids with 0%, 10%, and, 20% penetration percentage of installed wind generation, respectively.Our results indicate the undeniable influence of variations in the operational loadings and the wind penetration percentage on the GR-LOOP frequency, in addition to the NPPs’ locations. Such intensification effect was more pronounced in instantaneous frequencies of unique states than in the averaged ones. Furthermore, we observed more outstanding growth in the corresponding values of optimal cases. Our findings suggested that the reliability of the offsite grid to the NPPs be considered as a decision-making criterion, in addition to the existing security and economic issues in the grids with wind penetration.

Error-driven adaptive mesh refinement for unsteady turbulent flows in spectral-element simulations

The simulation of turbulent flows requires high spatial resolution in potentially a priori unknown, solution-dependent locations. To achieve adaptive refinement of the mesh, we rely on error indicators. We assess the differences between an error measure relying on the local convergence properties of the numerical solution and a goal-oriented error measure based on the computation of an adjoint problem. The latter method aims at optimizing the mesh for the calculation of a predefined integral quantity, or functional of interest. This work follows on from a previous study conducted on steady flows in Offermans et al. (2020) and we extend the use of the so-called adjoint error estimator to three-dimensional, turbulent flows. They both represent a way to achieve error control and automatic mesh refinement (AMR) for the numerical approximation of the Navier–Stokes equations, with a spectral element method discretization and non-conforming h-refinement.The current study consists of running the same physical flow case on gradually finer meshes, starting from a coarse initial grid, and to compare the results and mesh refinement patterns when using both error measures. As a flow case, we consider the turbulent flow in a constricted, periodic channel, also known as the periodic hill flow, at four different Reynolds numbers: Re = 700, Re = 1400, Re = 2800 and Re = 5600. Our results show that both error measures allow for effective control of the error, but they adjust the mesh differently. Well-resolved simulations are achieved by automatically focusing refinement on the most critical regions of the domain, while significant saving in the overall number of elements is attained, compared to statically generated meshes. At all Reynolds numbers, we show that relevant physical quantities, such as mean velocity profiles and reattachment/separation points, converge well to reference literature data. At the highest Reynolds number achieved (Re = 5600), relevant quantities, i.e. reattachment and separation locations, are estimated with the same level of accuracy as the reference data while only using one-third of the degrees of freedom of the reference. Moreover, we observe distinct mesh refinement patterns for both error measures. With the spectral error indicator, the mesh resolution is more uniform and turbulent structures are more resolved within the whole domain. On the other hand, the adjoint error estimator tends to focus the refinement within a localized zone in the domain, dependent on the functional of interest, leaving large parts of the domain marginally resolved.

Ground point extraction using self-adaptive-grid and point to surface comparison

Extracting accurate ground points by using laser point clouds at the complex terrain of the mining area and the dense vegetation environment is a challenging problem. To address this problem, this paper proposes a combined filtering method based on the Self-Adaptive-Grid method (SAG) and Point to Surface Comparison (PSC). First, the adaptive grid is used to extract initial ground seed points, and then, based on the seed points, a Triangulated Irregular Network (TIN) is constructed, and the distance from the reference surface and TIN is computed. These steps are repeated, In each loop, the non-ground points that are significantly far away from the reference surface will be culled, until the ground point is close to the real terrain, where the initial grid size and the distance from the point to the reference surface are gradually reduced according to the gradient. The proposed algorithm overcomes the difficulty of extracting bare ground due to terrain fluctuations. The ground points are effectively separated from the non-ground points in the laser lidar scan data, and the extracted high-precision ground points can be used as important basic data in the terrain modeling of the mining area, surface subsidence monitoring, and research on the laws of surface subsidence, which has great value in popularization and application.

Adaptive control arc length-based time grid refinement control parameterisation method for unmanned hypersonic vehicle reentry trajectory optimisation

An adaptive control arc length-based trajectory optimisation approach, which combines the control vector parameterisation (CVP) method with Gauss time grid distribution and adaptive grid refinement strategy, is proposed to further improve the downrange of unmanned hypersonic vehicles. Firstly, the Gauss time grid strategy is introduced to obtain a nonuniform Gauss time grid to calculate the original control profiles. By employing the curve integral formula to analyse the control arc length, an adaptive time grid refinement concept is proposed and the refinement process is derived in detail. The initial time grid nodes are then adaptively subdivided and combined. Finally, the control arc length-based nonuniform time grid refinement optimisation method is implemented. Numerical tests are carried out on common aero hypersonic vehicles and comparisons are made with other CVP methods. The test results reveal that the proposed approach can efficiently improve the downrange and decrease the path constraint oscillation.

Non-stationary grid generation algorithm for deformed volumes of revolution

The algorithm is designed for multi-component hydrodynamic simulation and for solving other physical and engineering problems. It is suggested for generating structured grids in the volume of revolution (main body) deformed by another volume of revolution (deforming body). In the deformation process, the deforming body is assumed infinitely stiff and strong (i.e. it does not deform, only the main body deforms). The algorithm is developed within the original variational approach for constructing optimal grids satisfying different requirements. The requirements of closeness of a grid to uniform and orthogonal are considered. The algorithm is performed on the basis of the grid generation technology elaborated earlier within the utilized approach for the volume of revolution. The volume of revolution is obtained by the rotation through 180° around an axis of a plane generatrix curve consisting of segments of straight lines and arcs of circles and ellipses. The technology is fully three-dimensional one and is not reduced to constructing rotational grids obtained by the rotation of two-dimensional grids around the axis. The developed algorithm represents the non-stationary procedure generating three-dimensional structured grids in domains with moving boundaries during which the form of the domain is changing from the volume of revolution to the desired deformed volume. The non-stationary algorithm is an iterative process where, at each stage, the deformation of a grid and then its optimization are carried out. Such algorithm allows to generate grids in very complex geometries. For this there is no need to describe the complex geometry of the deformed domain which is not obvious in the general case. It is necessary to do this only for the volumes of revolutions of the main and deforming bodies by the definition of generatrix curves for them which is essentially easier. It also permits to exclude some other stages of the traditional grid generation for the deformed volume such as generation of an initial grid. The algorithm is realized in the computer code written in C++. Examples of constructed grids are given.

Aerodynamic Load Prediction on a Patrol Vessel Using Computational Fluid Dynamics

Aerodynamic loads and moments on a naval patrol vessel are investigated using computational fluid dynamic simulations based on the OpenFOAM solver. After the initial turbulence, time, and grid dependency study, model scale simulations were performed for a wide range of inflow angles to predict aerodynamic forces and moments acting on the vessel at different heading conditions. For validation, model scale results were compared with wind tunnel data for similar hull forms. Finally, full-scale simulations were performed for a few cases to investigate possible scale effects on simulation results. The revealed scale effect turned out significant only for the yaw moment response. In this study, we aimed to produce reliable aerodynamic load data for the high-speed vessel, which is essential to developing reliable manoeuvring models. We conclude that Computational Fluid Dynamics is capable of providing reliable aerodynamic load predictions for high-speed vessels with sophisticated superstructures, in an economical manner.

Urban Acupuncture as a Method of Open Space Regeneration in Greek Ex-Refugee Areas. The Case of Nikea, Piraeus

The paper explores the potential of implementing the principles of urban acupuncture in a selected Greek case study, taking into account international experience in the field. The research includes literature review and field work. The area of study is Nikea, an ex-refugee urban area in the Attica metropolitan region. It was founded during the 1930s to host refugees from Asia Minor. The initial Hippodamian grid offers beneficial intermediate communal spaces inside each city block and there are also larger green spaces in proximity. However, the area suffers from urban blight owed largely to the poor quality of preservation of the old refugee housing estates. A mixture of factors contributes to the complex contemporary situation characterized by opportunities and challenges. On the one hand, there is great potential for regenerating the existing intermediate communal spaces and on the other decaying refugee houses and vulnerable households intricate the already convoluted situation. The paper provides cartographic depiction and categorization of the existing open spaces highlighting also contemporary socio-spatial challenges and market driven limitations. The research describes the obstacles that hinder the activation of “urban sensitive points” in terms of urban acupuncture, also advocating for possible solutions. The paper opens dialogue on the Greek case study in terms of urban acupuncture with the view to suggest strategies to foster socio-spatial cohesion in degraded ex -refugee urban areas. This is a pilot case study with further application in other post-refugee urban areas in Greece that share common socio-spatial attributes. Thus, the topic of the paper may have a greater impact within the Greek urban context.