Initial Grid Research Articles

An Automatic Isotropic Triangular Grid Generation Technique Based on an Artificial Neural Network and an Advancing Front Method

To improve the efficiency and automation of the traditional advancing front method (AFM) of unstructured grid generation, a novel isotropic triangular generation technique is developed based on an artificial neural network (ANN). First, some existing high-quality triangular grids are used as data sources, and then an automatic extraction method of training dataset is proposed. Second, the dataset is input into the ANN to train the network by the back-propagation (BP) algorithm, and then some typical patterns are identified through iterative learning. Third, after inputting the initial discretized fronts, the grid generator starts from the shortest front, and the adjacent front information is collected as the input of the neural network to choose the most proper pattern and predict the coordinates of the new point until the grid covers the whole computational domain. Finally, the initial grid is smoothed to further improve the grid quality. Some typical two-dimensional (2D) geometries are tested to validate the capability of the ANN-based advancing front triangle generator. The experimental results demonstrate that the efficiency of the proposed ANN-based triangular grid generator is about 30 percent higher than that of the traditional AFM, and grid quality has also been improved significantly.

Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things

It is a research topic of practical significance to study the path planning technology of mobile robot navigation technology. Aiming at the problems of slow convergence speed, redundant planning path, and easy to fall into local optimal value of ant colony algorithm in a complex environment, a robot path planning based on improved ant colony algorithm is proposed. First, the grid method is used to model the path environment, which marks each grid to make the ant colony move from the initial grid to the target grid for path search. Second, the ant colony is divided according to different planning tasks. Let some ants explore the way first, and carry out basic optimization planning for the map environment. The antecedent ants mark the basic advantage on a target value of the path with pheromone concentration so as to guide the subsequent route-finding operation of the main ant colony. Finally, in order to avoid the individual ants falling into a deadlock state in the early search, the obstacle avoidance factor is increased, the transition probability is improved, and the amount of information on each path is dynamically adjusted according to the local path information, so as to avoid the excessive concentration of pheromones. Experimental results show that the algorithm has high global search ability, significantly speeds up the convergence speed, and can effectively improve the efficiency of mobile robot in path planning.

Accuracy of power spectra in dissipationless cosmological simulations

AbstractWe exploit a suite of large N-body simulations (up to N = 40963) performed with abacus, of scale-free models with a range of spectral indices n, to better understand and quantify convergence of the matter power spectrum. Using self-similarity to identify converged regions, we show that the maximal wavenumber resolved at a given level of accuracy increases monotonically as a function of time. At 1 per cent level it starts at early times from a fraction of $k_\Lambda$, the Nyquist wavenumber of the initial grid, and reaches at most, if the force softening is sufficiently small, ${\sim}2{-}3 k_\Lambda$ at the very latest times we evolve to. At the $5{{\ \rm per\ cent}}$ level, accuracy extends up to wavenumbers of order $5k_\Lambda$ at late times. Expressed as a suitable function of the scale-factor, accuracy shows a very simple n-dependence, allowing a extrapolation to place conservative bounds on the accuracy of N-body simulations of non-scale-free models like LCDM. We note that deviations due to discretization in the converged range are not well modelled by shot noise, and subtracting it in fact degrades accuracy. Quantitatively our findings are broadly in line with the conservative assumptions about resolution adopted by recent studies using large cosmological simulations (e.g. Euclid Flagship) aiming to constrain the mildly non-linear regime. On the other hand, we remark that conclusions about small-scale clustering (e.g. concerning the validity of stable clustering) obtained using PS data at wavenumbers larger than a few $k_\Lambda$ may need revision in light of our convergence analysis.

The Influence of Interpolated Point Location and Density on 3D Bathymetric Models Generated by Kriging Methods: An Application on the Giglio Island Seabed (Italy)

In relation to 3D bathymetric modelling, this article aims to analyze the performance of Kriging approaches in dependence of the location and density of the measured depth points. The experiments were carried out on a multi-beam sonar (MBS) dataset that includes 240,000 soundings covering a sea-bottom area near Giglio Island (Italy). Seven subsets were derived in random way from the initial regular MBS dataset, selecting an increasing number of points uniformly spaced. Seven models were generated for both Ordinary Kriging and Universal Kriging. Each model was submitted to leave-one-out cross-validation to define the exactness of the predictive values and compared with the initial grid to better evaluate the accuracy in dependence of the point number and dissemination. To investigate this relationship, a new index called MVI (Morphological Variation Index) was introduced as a measurement of the level of variation of seabed morphology. The results validate the efficiency of the Kriging methods and remark the influence of the dataset distribution on the 3D model, highlighting MVI as a useful index to represent the seabed variation as a unique value. Finally, in no rugged areas using 1 point every 1000 m2, the RMSE of the differences between measured and interpolated values falls below 1 m, while a further increment of soundings is required in the presence of a high level of variation of seabed morphology.

Convergence and proposed optimality of adaptive finite element methods for nonlinear optimal control problems

<abstract><p>This paper investigates the adaptive finite element method for nonlinear optimal control problem, and the research content of reference (<sup>[<xref ref-type="bibr" rid="b21">21</xref>]</sup> H. Leng and Y. Chen, 2017) is extended accordingly. Linear discretisation of the equation of state and the equation of common state is performed using continuous segmentation functions. At the same time, we use the bubble function technique to prove that the posterior error estimates are obtained from the upper and lower bounds. What is more, for the adaptive finite element method, we also consider convergence and quasi-optimality, where we find that the demand $ h_0\ll 1 $ on the initial grid is unconstrained for the convergence analysis of the proposed adaptive algorithm for the nonlinear optimal control problem. Simultaneously, some numerical simulation is used to verify our theoretical analysis.</p></abstract>

Simulation of the self-propagating hydrogen-air premixed flame in a closed-vessel by an open-source CFD code

ABSTRACT The three-dimensional simulations of the combustion of self-propagating hydrogen-air premixed flame are performed by an open-source CFD code. The characteristics of the flame such as flame propagation behavior, flame radius, temperature, and pressure are analysed by varying the initial laminar flame speed and grid size. When the initial laminar speed increases, the thermal expansion effects become strong which leads the increase of flame radius along with the increase of flame surface area, flame temperature, and pressure. The fluctuation of pressure appears and it leads the temperature to fluctuate further. The increase in flame radius is directly related to the flame temperature. A new laminar flame speed model derived previously from the results of experiment is also introduced to the code and the obtained flame radii are compared with those from the experiments. The formation of cellular flame fronts is captured by simulation and the cell separation on the flame surface vividly appears when the grid resolution becomes sufficiently higher. The propagation behavior of cellular flame front and the flame radius obtained from the simulations have the reasonable agreement with the previous experiments.

Digital and automatic design of free-form single-layer grid structures

Grid shells have been widely used in various long-span public buildings, and many of them are defined over free-form surfaces with complex boundaries. This emphasizes the importance of general and digitalised grid generation and optimization methods in the initial design stage to achieve visually sound grid shells. In this paper, a framework is presented for the development of a digital tool and to generate regular and fluent grids for structural design over free-form surfaces, especially those with complex boundaries. Both triangular and quadrilateral grid generation are addressed. To generate regular and fluent grids for free-form surfaces, a simple yet practical framework is proposed based on a spring-mass model. Firstly, an initial casual quadrilateral grid is tiled on the surface based on surface discretization and mesh parameterization. Secondly, the distribution of the initial grid vertices is adjusted by a dynamic relaxation procedure, assuming the grid as a spring-mass system. Thirdly, the grid vertices corresponding to the adjusted particles in the equilibrium state are then reconnected to produce a grid with a predefined pattern (triangular or quadrilateral). Finally, the generated grid is relaxed with the spring-mass model, alongside additional geometric operations including grid size adjustment and filtering techniques, to further improve the grid regularity and fluency. As part of its contribution, this paper also broadens the application scope of the fluency index, which can be used to quantitatively evaluate the suitability of a given triangular or quadrilateral grid for architectural and structural expression. Examples are presented and show that the proposed framework is effective for the triangular and quadrilateral grid generation over various surfaces and to optimize the resulted grids along complex boundaries. The method proposed can be useful for rapid design and performance evaluation of free-form grid structures.

An automatic isotropic/anisotropic hybrid grid generation technique for viscous flow simulations based on an artificial neural network

Based on the author's previous research, a novel hybrid grid generation technique is developed by introducing an Artificial Neural Network (ANN) approach for realistic viscous flow simulations. An initial hybrid grid over a typical geometry with anisotropic quadrilaterals in the boundary layer and isotropic triangles in the off-body region is generated by the classical mesh generation method to train two ANNs on how to predict the advancing direction of the new point and to control the grid size. After inputting the initial discretized fronts, the ANN-based Advancing Layer Method (ALM) is adopted to generate the anisotropic quadrilaterals in boundary layers. When the high aspect ratio of the anisotropic grid reaches a specified value, the ANN-based Advancing Front Method (AFM) is adopted to generate isotropic triangles in the off-body computational domain. The initial isotropic triangles are smoothed to further improve the grid quality. Three typical cases are tested and compared with experimental data to validate the effectiveness of grids generated by the ANN-based hybrid grid generation method. The experimental results show that the two ANNs can predict the advancing direction and the grid size very well, and improve the adaptability of the isotropic/anisotropic hybrid grid generation for viscous flow simulations.

Smooth Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

Aiming at the problems of slow convergence, easy to fall into local optimum, and poor smoothness of traditional ant colony algorithm in mobile robot path planning, an improved ant colony algorithm based on path smoothing factor was proposed. Firstly, the environment map was constructed based on the grid method, and each grid was marked to make the ant colony move from the initial grid to the target grid for path search. Then, the heuristic information is improved by referring to the direction information of the starting point and the end point and combining with the turning angle. By improving the heuristic information, the direction of the search is increased and the turning angle of the robot is reduced. Finally, the pheromone updating rules were improved, the smoothness of the two-dimensional path was considered, the turning times of the robot were reduced, and a new path evaluation function was introduced to enhance the pheromone differentiation of the effective path. At the same time, the Max-Min Ant System (MMAS) algorithm was used to limit the pheromone concentration to avoid being trapped in the local optimum path. The simulation results show that the improved ant colony algorithm can search the optimal path length and plan a smoother and safer path with fast convergence speed, which effectively solves the global path planning problem of mobile robot.

Optimal Spatial Sensor Design for Magnetic Tracking in a Myokinetic Control Interface

Background and ObjectivesMagnetic tracking involves the use of magnetic sensors to localize one or more magnetic objectives, in those applications in which a free line-of-sight between them and the operator is hampered. We applied this concept to prosthetic hands, which could be controlled by tracking permanent magnets implanted in the forearm muscles of amputees (the myokinetic control interface). Concerning the system design, the definition of a sensor distribution which maximizes the information, while minimizing the computational cost of localization, is still an open problem. We present a simple yet effective strategy to define an optimal sensor set for tracking multiple magnets, which we called the Peaks method. MethodsWe simulated a proximal amputation using a 3D CAD model of a human forearm, and the implantation of 11 magnets in the residual muscles. The Peaks method was applied to select a subset of sensors from an initial grid of 480 elements. The approach involves setting an appropriate threshold to select those sensors associated with the peaks in the magnetic flux density and its gradient distributions. Selected sensors were used to track the magnets during muscle contraction. For validating our strategy, an alternative method based on state-of-the-art solutions was implemented. We finally proposed a calibration phase to customize the sensor distribution on the specific patient's anatomy. Results80 sensors were selected with the Peaks method, and 101 with the alternative one. A localization accuracy below 0.22 mm and 1.86° for position and orientation, respectively, was always achieved. Unlike alternative methods from the literature, neither iterative or analytical solution, nor a-priori knowledge on the magnet positions or trajectories were required, and yet the outcomes achieved with the two strategies proved statistically comparable. The calibration phase proved useful to adapt the sensors to the patient's stump and to increase the signal-to-noise ratio against intrinsic noise. ConclusionsWe demonstrated an efficient and general solution for solving the design optimization problem (i.e. identifying an optimal sensor set) and reducing the computational cost of localization. The optimal sensor distribution mirrors the field shape traced by the magnets on the sensing surface, being an intuitive and fast way of achieving the same results of more complex and application-specific methods. Several applications in the (bio)medical field involving magnetic tracking will benefit from the outcomes of this work.

Optimization method for shape design of Auxetic Bending-Active Gridshells using discrete differential geometry

The purpose of this paper is to propose an optimization method for shape design of Auxetic Bending-Active Gridshells (ABAGs). A 2-dimensional auxetic structure has negative Poisson’s ratio for in-plane deformation. Positive Gaussian curvature distributed on a curved surface of ABAG is obtained by out-of-plane deformation of the initial flat grid composed of reentrant structural units. We introduce discrete differential geometry into shape design of the surface of ABAG, which can be easily discretized into triangular meshes in accordance with the discrete member locations. The objective function of the proposed optimization problem is formulated using discrete Gaussian curvature, which is defined as the angle defect at node. In addition, discrete mean curvature vector is used for specifying the direction of convexity. We use particle swarm optimization for solving the problem. It is shown in the numerical examples, that surfaces with specified distribution of convex region on an ABAG can be obtained using the proposed method.

Investigating the influence of the variation of the load characteristic on the occurrence frequency of Grid-related Loss of Offsite Power using a probabilistic-deterministic methodology

Generic frequencies are used for Grid-related Loss of Offsite Power (GR-LOOP) in the Probabilistic Safety Analysis (PSA) of Nuclear Power Plants (NPPs). When historical databases are used, the influence of variation in the grid conditions over time and the impact of the NPP location are not considered in the estimation of GR-LOOP frequency. Therefore, relying purely on historical data induces uncertainty in total Core Damage Frequency (CDF).This paper aims at assessing the influence of the dynamic load behavior on the GR-LOOP frequency, for different locations. For that purpose, sensitivity cases are defined. The occurrence frequency of GR-LOOP following the occurrence of a three-phase-short-circuit fault on a transmission line is evaluated via a probabilistic-deterministic methodology for all cases.The minimum and maximum estimated values of the GR-LOOP frequency, 2.98E-04/year and 9.95E-03/year respectively, indicate the dependence on the variation in either the dynamic load behaviors or the NPP locations.The results reveal that GR-LOOP frequency varies with load model in the initial grid. In the presented probabilistic-deterministic methodology it is beneficial to consider the influence of timely changes of the grid conditions on the GR-LOOP occurrence frequency for different NPPs’ locations, especially where relevant or sufficient generic databases are not available.

Surface Reconstruction Pattern Recognition Technology Based on Scattered Point Cloud Data.

Surface reconstruction technology based on cloud data has broad prospects in the fields of reverse engineering, cultural heritage protection, and smart city construction. This article studies the surface reconstruction pattern recognition technology based on scattered point cloud data. The candidate feature points are extracted according to the surface variation, and the precise method of point cloud is used to fit the clustering plane, and the feature points are selected from the candidate feature points. Use the area increase method to construct the initial grid of the specific three-dimensional point group data. In the construction process, the normal vector of the point group data does not need to be separated, but defines the angle of the normal vector of the adjacent triangular grids, thereby separating relatively flat areas. Using the projection parameterization method, the scattering points in the domain are projected onto the curved surface, and the parameter values of the projection points are counted as the parameter values of the scattering points. All sampling points on the common boundary have tangent vectors along the two directions of the boundary. The direction of the bisector of the angle between the two tangent vectors is calculated as the direction of the connection vector outside the boundary of the sampling point. It can be seen from the experimental data that the search radius of the normal vector and feature descriptor when calculating the feature description operator is 0.01 and 0.02 m, instead of 0.005 and 0.006 m of the bunny data. Using the local feature size to refine the point cloud data can reduce the number of point clouds, remove redundant data in the point cloud, and realize dynamic adjustment and adaptive reconstruction of nonuniform point clouds.

Ionization correction factors and dust depletion patterns in giant H ii regions

ABSTRACT We provide new ionization correction factors (ICFs) for carbon, nitrogen, neon, sulfur, chlorine, and argon in giant H ii regions. The ICFs were computed using the most representative photoionization models from a large initial grid. The models were selected using an observational sample of 985 giant H ii regions (GHR) in spiral galaxies and blue compact galaxies (BCG). The observational sample was also used to assign a weight to each model describing how well it agrees with observations in the [O iii]/H β versus [N ii]/H α diagram. In addition to the ICFs we provide, for the first time, analytical expressions for their formal uncertainties. We use our ICFs to compute the abundances of nitrogen, neon, sulfur, and argon in our samples. Our abundances are robust within the adopted framework, but may require revision in the case of important changes in atomic data or in the spectral energy distribution of the ionizing radiation in H ii regions. Considering the abundance patterns we obtained for the BCG sample (abundances for the GHR sample are less reliable) we find that oxygen is depleted into dust grains at a rate increasing with metallicity and reaching 0.12 dex at solar abundances. The discussion of possible depletion of sulfur and argon requires considering recent Type Ia Supernova yields, which are still uncertain.

Forward modelling of gravity data on unstructured grids using an adaptive mimetic finite-difference method

One of the techniques to optimize the gradient-based inversion of geophysical gravity data is to deal with the large and dense Jacobian matrices implicitly. This is made possible by solving the normal systems iteratively and to use pseudo-forward problems to calculate the effect of the Jacobian matrices. For this, numerical forward solvers should be used instead of analytical solvers. In this study, we propose mimetic finite-difference schemes for the solution of the forward gravity problem on unstructured grids. While the mimetic finite-difference method shares many traits with the finite-element and finite-volume methods, it has the advantage of naturally accommodating grids with arbitrary polyhedral elements. We use cell-based and vertex-based mimetic finite-difference schemes to solve a diffusion problem in mixed form, and Poisson's problem, respectively. The cell-based scheme is solved for the gravitational potential and attraction at the centroids and the facets of the elements, respectively, and the vertex-based scheme is solved for the potential at the vertices of the elements. We compare these mimetic finite-difference schemes with cell-based and vertex-based finite-volume schemes and a vertex-based finite-element scheme, in terms of accuracy of the potential. We then utilize the versatility of the mimetic finite-difference method, in accommodating arbitrary elements, and develop an adaptive mesh refinement tool. The mesh adaptivity is performed by an iterative h-refinement where goal-oriented error estimates are used to mark the elements for refinement. The marked elements are decomposed into new tetrahedra by regular subdivision. Since arbitrary polyhedra are naturally permitted in the mimetic finite-difference method, the added nodes are not regarded as hanging nodes, and therefore, any modification of the scheme or extra refinement is avoided. This characteristic allows preserving the quality of the initial grid and simplifying the refinement procedure. We demonstrate the practicality of the presented mesh adaptivity for the forward modelling of gravity and gravity gradient data using realistic geological models. We show that the cell-based mimetic scheme is more efficient than the vertex-based scheme in terms of computational resources. We also demonstrate that in the presence of irregular interfaces in the input domain, the regular refinement approach, presented in this study, is more reliable than a standard mesh regeneration technique.

Forward modelling of geophysical electromagnetic data on unstructured grids using an adaptive mimetic finite-difference method

While the mimetic finite-difference method shares many similarities with the finite-element and finite-volume methods, it has the advantage of naturally accommodating grids with arbitrary polyhedral elements. In this study, we use this attribute to develop an adaptive scheme for the solution of the geophysical electromagnetic modelling problem on unstructured grids. Starting with an initial tetrahedral grid, our mesh adaptivity implements an iterative h-refinement where a residual- and jump-based goal-oriented error estimator is used to mark a certain portion of the elements. The marked elements are decomposed into new tetrahedra by regular subdivision, creating an octree-like unstructured grid. Since arbitrary polyhedra are naturally permitted in the mimetic finite-difference method, the added nodes are not regarded as hanging nodes and hence any level of non-conformity can be implemented without a modification to the mimetic scheme. In this study, we consider 2-irregularity where two levels of non-conformity between the adjacent elements is permitted. We use a total field approach where the electric field is defined at the edges of the polyhedral elements and the electromagnetic source may have an arbitrary shape and location. The accuracy of the mimetic scheme and the effectiveness of the proposed mesh adaptivity are verified using benchmark and realistic examples that represent various magnetotelluric and controlled-source survey scenarios. The mesh adaptivity generates grids with refinement generally concentrated at the transmitter and receiver locations and the interfaces of materials with contrasting conductivities, and the mimetic finite-difference solutions have good agreement with the reference numerical and real data. We also demonstrate the practicality of our method using an example with an analytical solution and comparison with a standard mesh regeneration technique. The results show that our mesh adaptivity procedure can result in a higher accuracy, with similar numbers of elements, when compared with the mesh regeneration approach. Also, using a generic sparse direct solver, our method is found to be more efficient than the mesh regeneration approach in terms of computation time and memory usage. Moreover, a comparison between 1- and 2-irregularity shows the higher efficiency of the latter in terms of the number of elements required to reach a certain level of accuracy.

Micro-damage initiation evaluation of z-pinned laminates based on a new three-dimension RVE model

Z-pinning is an effective method to increase the delamination resistance of composite laminate. To optimize the design of z-pinned reinforced composite material, the paper proposes a new three-dimension RVE model for z-pinned laminates based on the manufacturing process, which involves the evolution of microstructures inside the laminate. First, an insertion and curing simulation is conducted by the finite element method to obtain an initial three-dimension microstructure RVE grid. Then, use the Delaunay triangulation method to regenerate the grids of resin-rich zone, matrix layer and steel z-pin. Finally, the regenerated grid is transformed into a finite element RVE model. Local material properties and local fiber orientation are determined by the Chamis model and grid geometries, respectively. Periodic boundary conditions are defined to confirm deformation compatibility and continuous stress. The RVE model is used to investigate the effects of z-pinned process parameters on the in-plane compressive strength and micro-damage evolution of laminates, and is eventually verified by the experimental results.

On Adaptive Haar Approximations of Random Flows

The adaptive approximations for some characteristic of random functions defined on arbitrary irregular grids are discussed in this paper. The mentioned functions can be examined as flows of random real values associated with an irregular grid. This paper considers the question of choosing an adaptive enlargement of the initial grid. The mentioned enlargement essentially depends on the formulation of the criterion in relation to which adaptability is considered. Several criteria are considered here, among which there are several criteria applicable to the processing of random flows. In particular, the criteria corresponding to the mathematical expectation, dispersion, as well as autocorrelation and cross-correlation of two random flows are considered. It is possible to consider criteria corresponding to various combinations of the mentioned characteristics. The number of knots of the initial (generally speaking, irregular) grid can be arbitrary, and the main grid can be any subset of the initial one. Decomposition algorithms are proposed, taking into account the nature of the changes in the initial flow. The number of arithmetic operations in the proposed algorithms is proportional to the length of the initial flow. Sequential processing of the initial flow is possible in real time.

Exact method to solve of linear heat transfer problems

When approximating multidimensional partial differential equations, the values of the grid functions from neighboring layers are taken from the previous time layer or approximation. As a result, along with the approximation discrepancy, an additional discrepancy of the numerical solution is formed. To reduce this discrepancy when solving a stationary elliptic equation, parabolization is carried out, and the resulting equation is solved by the method of successive approximations. This discrepancy is eliminated in the approximate analytical method proposed below for solving two-dimensional equations of parabolic and elliptic types, and an exact solution of the system of finite difference equations for a fixed time is obtained. To solve problems with a boundary condition of the first kind on the first coordinate and arbitrary combinations of the first, second and third kinds of boundary conditions on the second coordinate, it is proposed to use the method of straight lines on the first coordinate and ordinary sweep method on the second coordinate. Approximating the equations on the first coordinate, a matrix equation is built relative to the grid functions. Using eigenvalues and vectors of the three-diagonal transition matrix, linear combinations of grid functions are compiled, where the coefficients are the elements of the eigenvectors of the three-diagonal transition matrix. Boundary conditions, and for a parabolic equation, initial conditions are formed for a given combination of grid functions. The resulting one-dimensional differential-difference equations are solved by the ordinary sweep method. From the resulting solution, proceed to the initial grid functions. The method provides a second order of approximation accuracy on coordinates. And the approximation accuracy in time when solving the parabolic equation can be increased to the second order using the central difference in time. The method is used to solve heat transfer problems when the boundary conditions are expressed by smooth and discontinuous functions of a stationary and non-stationary nature, and the right-hand side of the equation represents a moving source or outflow of heat.

GRASS GIS Modules for Topographic and Geophysical Analysis of the ETOPO1 DEM and Raster Data: North Fiji Basin, Pacific Ocean

The paper presents topographic analysis based on the raster data (NetCDF and grid formats) and visualization of the geophysical datasets that resembles the topographic surface. Geographically, the research focuses on the region of North Fiji Basin, South Pacific Ocean. North Fiji Basin is one of the marginal basins located at the converging boundary between the Pacific and Australian tectonic plates and is notable for complex geological settings. Methodology is based on GRASS GIS and includes scripting and cartographic visualization. Data include ETOPO1, GEBCO, EGM96 gravity and geoid raster grids imported to GRASS GIS via GDAL library (‘r.in.gdal’ module) from NetCDF and GRD formats, evaluated and visualized. Several GRASS modules were used as a sequential scripting for displaying and modelling data. Geomorphometric analysis (slopes, curvature, aspect, elevation) was performed by module ‘r.slope.aspect’ based on ETOPO1 grid. Statistical data analysis (histograms, polar diagram) for topographic and geoid gravitational fields were visualized by combination of GRASS modules d.rast, g.region, d.polar, d.histogram, d.grid, d.legend, d.text. Topographic analysis reveal that free-air gravity anomaly mark the continental shelf-slope border showing that generally, geophysical settings are dominated by the topographic effect. These observations are consistent with the inferred prominent role of the geophysical settings. The histograms reveal that topography (trenches, abyssal plains, shelf areas) has values between -5,000 and -1,000 m, and a clear peak with major values between 100 and 350 m above sea level. This distribution indicates that dominating depths of the ocean floor in North Fiji Basin are between -1,500 to -3,000 m. The aspect map of the ETOPO1 initial raw raster grid show that the surface has mostly 50°-110° oriented slope followed by data range in 250°-300° oriented slopes which is well correlating with submarine topography and general relief forms. The steepening of the gravity values between 50 and 55 mGal and 58 to 63 mGal indicates geoid undulations suggesting that bathymetry is controlled by the geological settings in the study area. Console- based scripts of GRASS GIS are presented together with cartographic outputs showing its effectiveness for the geographic spatial analysis.