ORCID Profile
0000-0001-6662-3823
Current Organisation
University of Adelaide
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Publisher: Elsevier BV
Date: 03-2018
Publisher: Elsevier BV
Date: 06-2012
Publisher: American Society of Civil Engineers (ASCE)
Date: 12-2021
Publisher: Elsevier BV
Date: 04-1994
Publisher: MDPI AG
Date: 29-03-2021
DOI: 10.3390/GEOSCIENCES11040153
Abstract: Most rock masses contain natural fractures. In many engineering applications, a detailed understanding of the characteristics of fluid flow through a fractured rock mass is critically important for design, performance analysis, and uncertainty/risk assessment. In this context, rock fractures and fracture networks play a decisive role in conducting fluid through the rock mass as the permeability of fractures is in general orders of magnitudes greater than that of intact rock matrices, particularly in hard rock settings. This paper reviews the modelling methods developed over the past four decades for the generation of representative fracture networks in rock masses. It then reviews some of the authors’ recent developments in numerical modelling and experimental studies of linear and non-linear fluid flow through fractures and fracture networks, including challenging issues such as fracture wall roughness, aperture variations, flow tortuosity, fracture intersection geometry, fracture connectivity, and inertia effects at high Reynolds numbers. Finally, it provides a brief review of two applications of methods developed by the authors: the Habanero coupled hydro-thermal heat extraction model for fractured reservoirs and the Kapunda in-situ recovery of copper minerals from fractures, which is based on a coupled hydro-chemical model.
Publisher: Springer Science and Business Media LLC
Date: 13-09-2007
Publisher: Elsevier BV
Date: 04-2023
Publisher: Elsevier BV
Date: 03-2016
Publisher: Springer Science and Business Media LLC
Date: 25-02-2014
Publisher: Elsevier BV
Date: 11-2016
Publisher: American Geophysical Union (AGU)
Date: 02-2012
DOI: 10.1029/2011GL050519
Publisher: Springer Science and Business Media LLC
Date: 19-06-2012
Publisher: Elsevier BV
Date: 08-2022
Publisher: Informa UK Limited
Date: 11-2007
Publisher: Springer International Publishing
Date: 2018
Publisher: Informa UK Limited
Date: 22-04-2019
Publisher: Elsevier BV
Date: 08-2020
Publisher: Informa UK Limited
Date: 05-10-2019
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 12-1994
Publisher: American Society of Mechanical Engineers
Date: 09-11-2012
Abstract: Fluid flow in Enhanced Geothermal Systems (EGS) occurs primarily through fractures which are embedded in an almost impermeable granite rock matrix. Experimental and numerical studies have shown that flow in fractures exhibits channeling effects this means that flow occurs along preferred pathways, most likely the paths of least resistance. There has been evidence to date of dendritic and star-like patterns in granite and as a result, authors have used fractal theory in order to address flow phenomena in these patterns. The application of Bejan’s Constructal theory to this problem however has never been attempted. We base our model on dendritic patterns of flow paths in heterogeneous rock fractures. Flow enters into a main channel which bifurcates into daughter channels of unique dimensions of length and height. We study these parameters for consecutive channels in the flow path and show that for minimization of resistance to flow within a plane using area and volume constraints for a T-shaped channel, a simple relationship holds for the ratios of lengths and heights which will enable maximum flow for this configuration.
Publisher: Elsevier BV
Date: 10-2016
Publisher: Springer Science and Business Media LLC
Date: 25-08-2016
Publisher: Springer Science and Business Media LLC
Date: 08-11-2017
Publisher: Springer Science and Business Media LLC
Date: 12-05-2006
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 1995
Publisher: Springer Science and Business Media LLC
Date: 25-04-2017
Publisher: Springer Science and Business Media LLC
Date: 26-07-2014
Publisher: Elsevier BV
Date: 12-1994
Publisher: Elsevier BV
Date: 08-2013
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 05-2017
Publisher: Springer Science and Business Media LLC
Date: 24-09-2022
Publisher: Elsevier BV
Date: 2012
Publisher: American Chemical Society (ACS)
Date: 14-08-2009
DOI: 10.1021/IE800033A
Publisher: MDPI AG
Date: 27-10-2022
DOI: 10.3390/MIN12111364
Abstract: Sensor-based sorting techniques offer the potential to improve ore grades and reduce the amount of waste material processed. Previous studies show that sensor-based sorting can reduce energy, water and reagent consumption and fine waste production by discarding waste prior to further processing. In this literature review, recent investigations of sensor-based sorting and the fundamental mechanisms of the main sorting techniques are evaluated to inform optimal sensor selection. Additionally, the fusing of data from multiple sensing techniques to improve characterization of the sensed material and hence sorting capability is investigated. It was found that the key to effective implementation of sensor-based sorting is the selection of a sensing technique which can sense a characteristic capable of separating ore from waste with a s ling distribution sufficient for the considered sorting method. Classes of potential sensor fusion sorting applications in mineral processing are proposed and illustrated with ex le cases. It was also determined that the main holdup for implementing sensor fusion is a lack of correlatable data on the response of multiple sensing techniques for the same ore s le. A combined approach of experimental testing supplemented by simulations is proposed to provide data to enable the evaluation and development of sensor fusion techniques.
Publisher: Wiley
Date: 05-03-2015
DOI: 10.1002/NAG.2362
Publisher: Springer Science and Business Media LLC
Date: 18-04-2014
Publisher: ASME International
Date: 19-09-2011
DOI: 10.1115/1.4004369
Abstract: We present an analysis of fluid flow and heat transfer through a single horizontal channel with permeable walls which are at different temperatures. The problem is set in the context of hot dry rock geothermal energy extraction where water, introduced through an injection well, passes through a horizontal fracture by which transfer of heat is facilitated through advection of the fluid flowing toward the recovery well. We consider the walls of the fracture to have properties of a permeable medium and we study the effect of slip boundary conditions on velocity and temperature profiles for low Reynolds number ( 7) based on a similarity solution and perturbation expansion. We show that the velocity and heat transfer profiles are altered with the channel width, the permeability and a slip coefficient α, which is a dimensionless constant related to the inherent properties of the channel.
Publisher: Maney Publishing
Date: 15-02-2016
Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 12-1993
Publisher: Springer Science and Business Media LLC
Date: 05-04-2023
DOI: 10.1007/S11004-023-10056-Y
Abstract: One of the most challenging aspects of multivariate geostatistics is dealing with complex relationships between variables. Geostatistical co-simulation and spatial decorrelation methods, commonly used for modelling multiple variables, are ineffective in the presence of multivariate complexities. On the other hand, multi-Gaussian transforms are designed to deal with complex multivariate relationships, such as non-linearity, heteroscedasticity and geological constraints. These methods transform the variables into independent multi-Gaussian factors that can be in idually simulated. This study compares the performance of the following multi-Gaussian transforms: rotation based iterative Gaussianisation, projection pursuit multivariate transform and flow transformation. Case studies with bivariate complexities are used to evaluate and compare the realisations of the transformed values. For this purpose, commonly used geostatistical validation metrics are applied, including multivariate normality tests, reproduction of bivariate relationships, and histogram and variogram validation. Based on most of the metrics, all three methods produced results of similar quality. The most obvious difference is the execution speed for forward and back transformation, for which flow transformation is much slower.
Publisher: Elsevier BV
Date: 02-2015
Publisher: Springer Science and Business Media LLC
Date: 07-2006
Publisher: MDPI AG
Date: 07-07-2023
DOI: 10.3390/MIN13070918
Abstract: Identifying mineralization zones is a critical component of quantifying the distribution of target minerals using well-established mineral resource estimation techniques. Domains are used to define these zones and can be modelled using techniques such as manual interpretation, implicit modelling, and advanced geostatistical methods. In practise, domaining is commonly a manual exercise that is labour-intensive and prone to subjective judgement errors, resulting in a largely deterministic output that ignores the significant uncertainty associated with manual domain interpretation and boundary definitions. Addressing these issues requires an objective framework that can automatically define mineral domains and quantify the associated uncertainty. This paper presents a comparative study of PluriGaussian Simulation (PGS) and a Hybrid Domaining Framework (HDF) based on simulated assay grades and XGBoost, a machine-learning classification technique trained on lithological properties. The two domaining approaches are assessed on the basis of the domain boundaries produced using data from an Iron Oxide Copper Gold deposit. The results show that the proposed HDF domaining framework can quantify the uncertainty of domain boundaries and accommodate complex multiclass problems with imbalanced features. Geometallurgical models of the Net Smelter Return and grinding time are used to demonstrate the effectiveness of HDF. In addition, a preprocessing step involving a noise filtering method is used to improve the performance of the ML classification, especially in cases where domain boundaries are difficult to predict due to the similarity in geological characteristics and the inherent noise in the data.
Publisher: Elsevier BV
Date: 12-2013
Publisher: Informa UK Limited
Date: 22-08-2017
Publisher: Informa UK Limited
Date: 12-03-2018
Publisher: Springer Science and Business Media LLC
Date: 05-06-2014
Publisher: American Society of Civil Engineers (ASCE)
Date: 12-2023
Publisher: Elsevier BV
Date: 08-2018
Publisher: Elsevier BV
Date: 05-2020
Publisher: Elsevier BV
Date: 02-2016
Publisher: Springer Science and Business Media LLC
Date: 14-05-2018
Publisher: Springer Science and Business Media LLC
Date: 25-07-2018
Publisher: Elsevier BV
Date: 11-2012
Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 07-2009
Publisher: Elsevier BV
Date: 12-2006
Publisher: Informa UK Limited
Date: 09-2013
Publisher: Elsevier BV
Date: 03-2010
Publisher: Elsevier BV
Date: 07-2003
Publisher: Elsevier BV
Date: 11-2014
Publisher: Springer Science and Business Media LLC
Date: 02-01-2021
Publisher: Oxford University Press (OUP)
Date: 16-10-2018
Publisher: Elsevier BV
Date: 11-2018
Publisher: Springer Science and Business Media LLC
Date: 15-01-2013
Publisher: Elsevier BV
Date: 06-2018
Publisher: Elsevier BV
Date: 03-2003
Publisher: Springer Science and Business Media LLC
Date: 09-08-2007
Publisher: Elsevier BV
Date: 03-2018
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for C. Xu.