Predicting flow and transport in highly heterogeneous alluvial aquifers

Successful prediction of groundwater flow and solute transport through highly heterogeneous aquifers has remained elusive due to the limitations of methods to characterize hydraulic conductivity (K) and generate realistic stochastic fields from such data. As a result, many studies have suggested that the classical advective-dispersive equation (ADE) cannot reproduce such transport behavior. Here we demonstrate that when high-resolution K data are used with a fractal stochastic method that produces K fields with adequate connectivity, the classical ADE can accurately predict solute transport at the macrodispersion experiment site in Mississippi. This development provides great promise to accurately predict contaminant plume migration, design more effective remediation schemes, and reduce environmental risks. Key Points Non-Gaussian transport behavior at the MADE site is unraveledADE can reproduce tracer transport in heterogeneous aquifers with no calibrationNew fractal method generates heterogeneous K fields with adequate connectivity

Effects of magnetite on high-frequency ground-penetrating radar

Large concentrations of magnetite in sedimentary deposits and soils with igneous parent material have been reported to affect geophysical sensor performance. We have undertaken the first systematic experimental effort to understand the effects of magnetite for ground-penetrating radar (GPR) characterization of the shallow subsurface. Laboratory experiments were conducted to study how homogeneous magnetite-sand mixtures and magnetite concentrated in layers affect the propagation behavior (velocity, attenuation) of high-frequency GPR waves and the reflection characteristics of a buried target. Important observations were that magnetite had a strong effect on signal velocity and reflection, at magnitudes comparable to what has been observed in small-scale laboratory experiments that measured electromagnetic properties of magnetite-silica mixtures. Magnetite also altered signal attenuation and affected the reflection characteristics of buried targets. Our results indicated important implications for several fields, including land mine detection, Martian exploration, engineering, and moisture mapping using satellite remote sensing and radiometers.

Hydraulic conductivity fields: Gaussian or not?

Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high-resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.

Hydrostratigraphic analysis of the MADE site with full-resolution GPR and direct-push hydraulic profiling

Full-resolution 3D Ground-Penetrating Radar (GPR) data were combined with high-resolution hydraulic conductivity (K) data from vertical Direct-Push (DP) profiles to characterize a portion of the highly heterogeneous MAcro Dispersion Experiment (MADE) site. This is an important first step to better understand the influence of aquifer heterogeneities on observed anomalous transport. Statistical evaluation of DP data indicates non-normal distributions that have much higher similarity within each GPR facies than between facies. The analysis of GPR and DP data provides high-resolution estimates of the 3D geometry of hydrostratigraphic zones, which can then be populated with stochastic K fields. The lack of such estimates has been a significant limitation for testing and parameterizing a range of novel transport theories at sites where the traditional advection-dispersion model has proven inadequate.

Soil Magnetism Research: State of the Art and Future Directions

Magnetic properties of soils have been highlighted as a primary detrimental environmental effect on the performance of geophysical systems for detection of unexploded ordnance (UXO) and mine targets. A recent workshop at Cranfield University, U.K., aimed to identify knowledge gaps related to soil magnetism. Eight invited speakers from multidisciplinary areas provided briefings on state‐of‐the‐art research linked to soil magnetism and geophysical sensing. Contributions from other participants provided additional insights from a range of disciplines through case studies and applications. The workshop included break‐out sessions to identify current gaps in knowledge and to determine priority areas for investment in research to further developments in UXO and mine detection in magnetic soil environments. Key recommendations for future research investments have been grouped in categories including soils, theory and modeling, instrumentation, and communication.

Dragline swing automation

Draglines are used extensively for overburden stripping in Australian open cut coal mines. This paper outlines the design of a computer control system to implement an automated swing cycle on a production dragline. Subsystems and sensors have been developed to satisfy the constraints imposed by the task, the harsh operating environment and the mine's production requirements.

Evaluation of internal navigation sensor suites for underground mining vehicle navigation

This paper describes a series of trials that were done at an underground mine in New South Wales, Australia. Experimental results are presented from the data obtained during the field trials and suitable sensor suites for an autonomous mining vehicle navigation system are evaluated.

Automation of underground truck haulage

This paper reviews the state-of-the art in the automation of underground truck haulage. Past attemps at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tram...

Dragline swing automation

Draglines are very large machines that are used to remove overburden in open-cut coal mines. This paper outlines the design of a computer control system to implement an automated swing cycle on a production dragline. Subsystems and sensors have been developed to satisfy the constraints imposed by the task, the harsh operating environment and the mine's production requirements.

Case study: Dragline swing to dump automation

Dragline Swing to Dump Automation By Peter Corke, CSIRO Manufacturing Technology/CRC for Mining Technology and Equipment (CMTE) Peter Corke presented a case study of a project to automate the dragline swing to dump operation. The project is funded by ACARP, BHP Coal, Pacific Coal and the CMTE and is being carried out on a dragline at Pacific Coal's Meandu mine near Brisbane. Corke began by highlighting that the minerals industry makes extensive use of large, mechanised machines. However, unlike other industries, mining has not adopted automation and most machines are controlled by human operators on board the machine itself. Choosing an automation target The dragline automation was chosen because: ò draglines are one of the biggest capital assets in a mine; ò performance between operators vary significantly, so improved capital utilisation is possible; ò the dragline is often the bottleneck in production; ò a large part of the operation cycle is spent swinging from dig to dump; and ò it is technically feasible. There has been a history of drag line automation projects, none with great success.

Field and Service Robotics: Results of the 9th International Conference

The Field and Service Robotics (FSR) conference is a single track conference with a specific focus on field and service applications of robotics technology. The goal of FSR is to report and encourage the development of field and service robotics. These are non-factory robots, typically mobile, that must operate in complex and dynamic environments. Typical field robotics applications include mining, agriculture, building and construction, forestry, cargo handling and so on. Field robots may operate on the ground (of Earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans, importantly the elderly and sick, to help them with their lives. The first FSR conference was held in Canberra, Australia, in 1997. Since then the meeting has been held every 2 years in Asia, America, Europe and Australia. It has been held in Canberra, Australia (1997), Pittsburgh, USA (1999), Helsinki, Finland (2001), Mount Fuji, Japan (2003), Port Douglas, Australia (2005), Chamonix, France (2007), Cambridge, USA (2009), Sendai, Japan (2012) and most recently in Brisbane, Australia (2013). This year we had 54 submissions of which 36 were selected for oral presentation. The organisers would like to thank the international committee for their invaluable contribution in the review process ensuring the overall quality of contributions. The organising committee would also like to thank Ben Upcroft, Felipe Gonzalez and Aaron McFadyen for helping with the organisation and proceedings. and proceedings. The conference was sponsored by the Australian Robotics and Automation Association (ARAA), CSIRO, Queensland University of Technology (QUT), Defence Science and Technology Organisation Australia (DSTO) and the Rio Tinto Centre for Mine Automation, University of Sydney.

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

Raman and infrared spectroscopic study of turquoise minerals

Raman and infrared spectra of three well-defined turquoise samples, CuAl6(PO4)4(OH)8·4H2O, from Lavender Pit, Bisbee, Cochise county, Arizona; Kouroudaiko mine, Faleme river, Senegal and Lynch Station, Virginia were studied, interpreted and compared. Observed Raman and infrared bands were assigned to the stretching and bending vibrations of phosphate tetrahedra, water molecules and hydroxyl ions. Approximate O–H⋯O hydrogen bond lengths were inferred from the Raman and infrared spectra. No Raman and infrared bands attributable to the stretching and bending vibrations of (PO3OH)2− units were observed.

The largest Au deposits in the St Ives Goldfield (Yilgarn Craton, Western Australia) may be located in a major Neoarchean volcano-sedimentary depo-centre

The largest Neoarchean gold deposits in the world-class St Ives Goldfield, Western Australia, occur in an area known as the Argo-Junction region (e.g. Junction, Argo and Athena). Why this region is so well endowed with large deposits compared with other parts of the St Ives Goldfield is currently unclear, because gold deposits at St Ives are hosted by a variety of lithologic units and were formed during at least three different deformational events. This paper presents an investigation into the stratigraphic architecture and evolution of the Argo-Junction region to assess its implications for gold metallogenesis. The results show that the region's stratigraphy may be subdivided into five regionally correlatable packages: mafic lavas of the Paringa Basalt; contemporaneously resedimented feldspar-rich pyroclastic debris of the Early Black Flag Group; coarse polymictic volcanic debris of the Late Black Flag Group; thick piles of mafic lavas and sub-volcanic sills of the Athena Basalt and Condenser Dolerite; and the voluminous quartz-rich sedimentary successions of the Early Merougil Group. In the Argo-Junction region, these units have an interpreted maximum thickness of at least 7,130 m, and thus represent an unusually thick accumulation of the Neoarchean volcano-sedimentary successions. It is postulated that major basin-forming structures that were active during deposition and emplacement of the voluminous successions later acted as important conduits during mineralisation. Therefore, a correlation exists between the location of the largest gold deposits in the St Ives Goldfield and the thickest parts of the stratigraphy. Recognition of this association has important implications for camp-scale exploration.

Applications of real-time machine vision to the control of mining equipment

The mining industry presents us with a number of ideal applications for sensor based machine control because of the unstructured environment that exists within each mine. The aim of the research presented here is to increase the productivity of existing large compliant mining machines by retrofitting with enhanced sensing and control technology. The current research focusses on the automatic control of the swing motion cycle of a dragline and an automated roof bolting system. We have achieved: * closed-loop swing control of an one-tenth scale model dragline; * single degree of freedom closed-loop visual control of an electro-hydraulic manipulator in the lab developed from standard components.