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The purpose of this paper is to develop a three dimensional (3D) geological model, based on geographic information system (GIS), of the Barwon Downs Graben aquifer system in Victoria, Australia, and to visualize the complex geometry as a decision support tool for sustainable water management.

A 3D visualization of the aquifer is completed, based on subsurface geological modelling. The existing borehole database, hydrogeological data, geological information and surface topography are used to model the subsurface aquifer. ArcGIS 9.2 is employed for two‐dimensional (2D) GIS analysis and for 3D visualization and modelling geological objects computer aided design (GOCAD) 2.5.2 is used. The developed methodology of ArcGIS and GOCAD is implemented for creating the 3D geological model of the aquifer system.

The 3D geomodel of the Barwon Downs Graben provides a new perspective of the complex subsurface aquifer geometry and its relation with surface hydrogeology in a more interactive manner. Considering the geometry, estimated volume of the unconfined Eastern View aquifer is as 0.83 × 10¹⁰ m³ and for the confined aquifer is about 1.02 × 10¹⁰ m³. The total volume of overlying strata of this aquifer is about 3.0⁹ × 10¹⁰ m³. The water resources of the study area are affected by the pumping from this aquifer. This is also significantly influenced by the geometry of the Graben.

The 3D model utilises comprehensive and generally available datasets in the public domain. Although the used 3D geomodelling tools are mainly developed for applications in the petroleum industry, the current paper shows its ability to be adapted to hydrogeological investigations.

A principle prerequisite for designing and constructing an underground structure is to estimate the subsurface's properties and obtain a realistic picture of stratigraphy. Obtaining direct measure of these values in any location of the built environment is not affordable. Therefore, any evaluation is afflicted with uncertainty, and we need to combine all available measurements, observations and previous knowledge to achieve an informed estimate and quantify the involved uncertainties. This study aims to enhance the geotechnical surveys based on a spatial estimation of subsoil to customised data structures and integrating the ground models into digital design environments.

The present study's objective is to enhance the geotechnical surveys based on a spatial estimation of subsoil to customised data structures and integrating the ground models into digital design environments. A ground model consisting of voxels is developed via Revit-Dynamo to represent spatial uncertainties employing the kriging interpolation method. The local arrangement of new surveys are evaluated to be optimised.

The visualisation model's computational performance is modified by using an octree structure. The results show that it adapts the structure to be modelled more efficiently. The proposed concept can identify the geological models' risky locations for further geological investigations and reveal an optimised experimental design. The modifications criteria are defined in global and local considerations.

It provides a transparent and repeatable approach to construct a spatial ground model for subsequent experimental or numerical analysis. In the first attempt, the ground model was discretised by a grid of voxels. In general, the required computing time primarily depends on the size of the voxels. This issue is addressed by implementing octree voxels to reduce the computational efforts. This applies especially to the cases that a higher resolution is required. The investigations using a synthetic soil model showed that the developed methodology fulfilled the kriging method's requirements. The effects of variogram parameters, such as the range and the covariance function, were investigated based on some parameter studies. Moreover, a synthetic model is used to demonstrate the optimal experimental design concept. Through the implementation, alternative locations for new boreholes are generated, and their uncertainties are quantified. The impact of the new borehole on the uncertainty measures are quantified based on local and global approaches. For further research to identify the geological models' risky spots, the development of this approach with additional criteria regarding the search neighbourhood and consideration of barriers and trends in real cases (by employing different interpolation methodologies) should be considered.

The purpose of this paper aims to design an optimization control for tunnel boring machine (TBM) based on geological identification. For unknown geological condition, the authors need to identify them before further optimization. For fully considering multiple crucial performance of TBM, the authors establish an optimization problem for TBM so that it can be adapted to varying geology. That is, TBM can operate optimally under corresponding geology, which is called geology-adaptability.

This paper adopted k-nearest neighbor (KNN) algorithm with modification to identify geological conditions. The modification includes adjustment of weights in voting procedure and similarity distance measurement, which at suitable for engineering and enhance accuracy of prediction. The authors also design several key performances of TBM during operation, and built a multi-objective function. Further, the multi-objective function has been transformed into a single objective function by weighted-combination. The reformulated optimization was solved by genetic algorithm in the end.

This paper provides a support for decision-making in TBM control. Through proposed optimization control, the advance speed of TBM has been enhanced dramatically in each geological condition, compared with the results before optimizing. Meanwhile, other performances are acceptable and the method is verified by in situ data.

This paper fulfills an optimization control of TBM considering several key performances during excavating. The optimization is conducted under different geological conditions so that TBM has geological-adaptability.

This paper aims to give an oversight of what is being done by researchers in GIS and remote sensing (field) to explore minerals. The main objective of this review is to explore how GIS and remote sensing have been beneficial in identifying mineral deposits for easier and cost-effective mining.

The approach of this research used Web of Science to generate a database of published articles on the application of GIS and remote sensing techniques for mineral exploration. The literature was further digested, noting the main findings, adopted method, illustration and research scales.

When applied alone, each technique seems effective, but it is important to know that combining different methods is more effective in identifying ore deposits.

This paper also examined and provided possible solutions to both current and future perspective issues relating to the application of GIS and remote sensing to mineral exploration. The authors believe that the conclusions and recommendations drawn from case studies and literature review will be of great importance to geoscientists and policymakers.

The purpose of this paper is to establish a strain prediction model of mining overburden deformation, to predict the strain in the subsequent mining stage. In this way, the mining area can be divided into zones with different degrees of risk, and the prevention measures can be taken for the areas predicted to have large deformation.

A similar-material model was built by geological and mining conditions of Zhangzhuang Coal Mine. The evolution characteristics of overburden strain were studied by using the distributed optical fiber sensing (DOFS) technology and the predictive model about overburden deformation was established by applying machine learning. The modeling method of the predictive model based on the similar-material model test was summarized. Finally, this method was applied to engineering.

The strain value predicted by the proposed model was compared with the actual measured value and the accuracy is as high as 97%, which proves that it is feasible to combine DOFS technology with machine learning and introduce it into overburden deformation prediction. When this method was applied to engineering, it also showed good performance.

This paper helps to promote the application of machine learning in the geosciences and mining engineering. It provides a new way to solve similar problems.

Numerical methods are used to solve double diffusion driven reactive flow transport problems in deformable fluid‐saturated porous media. In particular, the temperature dependent reaction rate in the non‐equilibrium chemical reactions is considered. A general numerical solution method, which is a combination of the finite difference method in FLAC and the finite element method in FIDAP, to solve the fully coupled problem involving material deformation, pore‐fluid flow, heat transfer and species transport/chemical reactions in deformable fluid‐saturated porous media has been developed. The coupled problem is divided into two sub‐problems which are solved interactively until the convergence requirement is met. Owing to the approximate nature of the numerical method, it is essential to justify the numerical solutions through some kind of theoretical analysis. This has been highlighted in this paper. The related numerical results, which are justified by the theoretical analysis, have demonstrated that the proposed solution method is useful for and applicable to a wide range of fully coupled problems in the field of science and engineering.

The study aims to explore the composition and microstructure of clay functionally graded materials under the process of double-gradient direct ink writing (DIW).

The investigation focused specifically on the pore characteristics of barite-kaolin clay composite after three-dimensional (3D) printing and sintering as well as its bionic application in geophysical model.

The model with pore and material variations brought about spatial and nonlinear mechanical properties. Moreover, the vertical gradient and connected pores in the upper kaolin part simulated the natural phenomenon of the landslide model (take Chinese Majiagou landslides as an example). Both the thermal debinding behavior and the kaolin powder particles characteristics [large pore volume (0.019 cm³g^–1) and pore size (29.20 nm)] were attributed to the interconnection channels.

Hence, the macroscopic and microscopic pores achieved by dual-gradient DIW process make it possible to control the permeability and details of properties, precisely in the geological model.

The purpose of this paper is to utilise the interactive view capability of the geographical information system (GIS) for the geological interpretation in Klang Valley, Malaysia.

Topographical map scale of 1:10 000 was used to generate digital elevation model (DEM). The geological map was draped over the DEM to create a 3D perspective view. The geological interpretation was undertaken using the 3D capability of the GIS software.

From the study, five lineaments which could possibly be the newly identified faults and one lithological boundary have been delineated.

Although these findings need to be rechecked in the field, they show the capability of the DEM application in structural geology interpretation.

The results obtained from this study demonstrate the capability of utilising a geological map draped over DEM for structural geological interpretation. Thus the technique may increase the interpretation accuracy.

The major outcome of this research is the possible use of DEM in the application of geological study.

Traditional simulation research of geological and similar engineering models, such as landslides or other natural disaster scenarios, usually focuses on the change of stress and the state of the model before and after destruction. However, the transition of the inner change is usually invisible. To optimize and make models more intelligent, this paper aims to propose a perceptible design to detect the internal temperature change transformed by other energy versions like stress or torsion.

In this paper, micron diamond particles were embedded in 3D printed geopolymers as a potential thermal sensor material to detect the inner heat change. The authors use synthetic micron diamond powder to reinforced the anti-corrosion properties and thermal conductivity of geopolymer and apply this novel geopolymer slurry in the direct ink writing (DIW) technique.

As a result, the addition of micron diamond powder can greatly influence the rheology of geopolymer slurry and make the geopolymer slurry extrudable and suitable for DIW by reducing the slope of the viscosity of this inorganic colloid. The heat transfer coefficient of the micron diamond (15 Wt.%)/geopolymer was 50% higher than the pure geopolymer, which could be detected by the infrared thermal imager. Besides, the addition of diamond particles also increased the porous rates of geopolymer.

In conclusion, DIW slurry deposition of micron diamond-embedded geopolymer (MDG) composites could be used to manufacture the multi-functional geological model for thermal imaging and defect detection, which need the characteristic of lightweight, isolation, heat transfer and wave absorption.

Continua and discontinua coexist in natural rock materials. This paper aims to present an improved approach for addressing the mechanical response of rock masses based on the combined finite-discrete element method (FDEM) proposed by Munjiza.

Several algorithms have been programmed in the new approach. The algorithms include (1) a simpler and more efficient algorithm to calculate the contact force; (2) An algorithm for tangential contact force closer to the actual physical process; (3) a plastic yielding criterion (e.g. Mohr-Coulomb) to modify the elastic stress for fitting the mechanical behavior of elastoplastic materials; and (4) a complete code for the mechanical calculation to be implemented in Matrix Laboratory (MATLAB).

Three case studies, including two standard laboratory experiments (uniaxial compression and Brazilian split test) and one engineering-scale anti-dip slop model, are presented to illustrate the feasibility of the Y-Mat code and its ability to deal with multi-scale rock mechanics problems. The results, including the progressive failure process, failure mode and trajectory of each case, are acceptable compared to other corresponding studies. It is shown that, the code is capable of modeling geotechnical and geological engineering problems.

This article gives an improved FDEM-based numerical calculation code. And, feasibility of the code is verified through three cases. It can effectively solve the geotechnical and geological engineering problems.