Deep geothermal: The ‘Moon Landing’ mission in the unconventional energy and minerals space

Deep geothermal from the hot crystalline basement has remained an unsolved frontier for the geothermal industry for the past 30 years. This poses the challenge for developing a new unconventional geomechanics approach to stimulate such reservoirs. While a number of new unconventional brittle techniques are still available to improve stimulation on short time scales, the astonishing richness of failure modes of longer time scales in hot rocks has so far been overlooked. These failure modes represent a series of microscopic processes: brittle microfracturing prevails at low temperatures and fairly high deviatoric stresses, while upon increasing temperature and decreasing applied stress or longer time scales, the failure modes switch to transgranular and intergranular creep fractures. Accordingly, fluids play an active role and create their own pathways through facilitating shear localization by a process of time-dependent dissolution and precipitation creep, rather than being a passive constituent by simply following brittle fractures that are generated inside a shear zone caused by other localization mechanisms. We lay out a new theoretical approach for the design of new strategies to utilize, enhance and maintain the natural permeability in the deeper and hotter domain of geothermal reservoirs. The advantage of the approach is that, rather than engineering an entirely new EGS reservoir, we acknowledge a suite of creep-assisted geological processes that are driven by the current tectonic stress field. Such processes are particularly supported by higher temperatures potentially allowing in the future to target commercially viable combinations of temperatures and flow rates.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Improving monocular SLAM with altimeter hints for fixed-wing aircraft navigation and emergency landing

This paper presents a visual SLAM method for temporary satellite dropout navigation, here applied on fixed- wing aircraft. It is designed for flight altitudes beyond typical stereo ranges, but within the range of distance measurement sensors. The proposed visual SLAM method consists of a common localization step with monocular camera resectioning, and a mapping step which incorporates radar altimeter data for absolute scale estimation. With that, there will be no scale drift of the map and the estimated flight path. The method does not require simplifications like known landmarks and it is thus suitable for unknown and nearly arbitrary terrain. The method is tested with sensor datasets from a manned Cessna 172 aircraft. With 5% absolute scale error from radar measurements causing approximately 2-6% accumulation error over the flown distance, stable positioning is achieved over several minutes of flight time. The main limitations are flight altitudes above the radar range of 750 m where the monocular method will suffer from scale drift, and, depending on the flight speed, flights below 50 m where image processing gets difficult with a downwards-looking camera due to the high optical flow rates and the low image overlap.

An automated emergency landing system for fixed-wing aircraft: Planning and control

A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure and aircraft. To date, few field-demonstrated systems have been presented that show online re-planning and repeatability from failure to touchdown. This paper presents the development of the Guidance, Navigation and Control (GNC) component of an Automated Emergency Landing System (AELS) intended to address this gap, suited to a variety of fixed-wing aircraft. Field-tested on both a fixed-wing UAV and Cessna 172R during repeated emergency landing experiments, a trochoid-based path planner computes feasible trajectories and a simplified control system executes the required manoeuvres to guide the aircraft towards touchdown on a predefined landing site. This is achieved in zero-thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and re-plans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field-tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Deep transverse metatarsal ligaments mechanical response during landing

The deep transverse metatarsal ligaments play an important role in stabilizing the metatarsal bones and manipulating foot transverse arch deformation. However, the biomechanical research about transverse metatarsal ligaments in the foot maneuver is quite few. Due to the difficulties and lack of better measurement technology for these ligaments experimental monitor, the load transfer mechanism and internal stress state also hadn't been well addressed. The purpose of this study was to develop a detailing foot finite element model including transverse metatarsal ligaments tissues, to investigate the mechanical response of transverse metatarsal ligaments during the landing condition. The transverse metatarsal ligaments were considered as hyperelastic material model was used to represent the nonlinear and nearly incompressible nature of the ligament tissue. From the simulation results, it is clearly to find that the peak maiximal principal stress of transverse metatarsal ligaments was between the third and fourth metatarsals. Meanwhile, it seems the transverse metatarsal ligaments in the middle position experienced higher tension than the sides transverse metatarsal ligaments.

Footwear intervene of forefoot loading during landing movement

This study investigated the forefoot loading character under flexible sole condition while performing landing maneuver. Twenty healthy male volunteers have participated in the test. The insole and outsole loading were measured at the same time. The results of this study shown that the forefoot impact loading could be effectively relieved through the footwear during landing movement. The peak pressure value in the outsole was much higher than the barefoot, where the highest value in the first metatarsal of outsole was 63.6% higher than barefoot condition. Peak pressure of the third metatarsal of insole reduced the most, this has decreased about 51.2% of the barefoot experienced.

Finite element analysis of deep transverse metatarsal ligaments mechanical response during landing

The deep transverse metatarsal ligaments (DTML) play an important role in stabilizing the metatarsal bones and manipulating foot transverse arch deformation. However, the biomechanical research about DTML in the foot maneuver is quite few. Due to the difficulties and lack of better measurement technology for these ligaments experimental monitor, the load transfer mechanism and internal stress state also hadn't been well addressed. The purpose of this study was to develop a detailing foot finite element model including DTML tissues, to investigate the mechanical response of DTML during the landing condition. The DTML was considered as hyperelastic material model was used to represent the nonlinear and nearly incompressible nature of the ligament tissue. From the simulation results, it is clearly to find that the peak maiximal principal stress of DTML was between the third and fourth metatarsals. Meanwhile, it seems the DTML in the middle position experienced higher tension than the sides DTML.

Evaluation of Two MCDM Methods for UAV Emergency Landing

One of the major impediments for the use of UAVs in civilian environment is the capability to replicate some of the functionality of safe manned aircraft operations. One critical aspect is emergency landing. Once the possible landing sites have been rated, a decision on the most suitable choice to land is required. This is a multi-criteria decision making (MCDM) problem which needs to take into account various factors in its selection of landing site. This report summarises relevant literature in MCDM in the context of emergency forced landing and proposes and compares two algorithms and methods for this task.

Modelling discard ogives from Irish demersal fisheries

Annual discard ogives were estimated using generalized additive models (GAMs) for four demersal fish species: whiting, haddock, megrim, and plaice. The analysis was based on data collected on board commercial vessels and at Irish fishing ports from 1995 to 2003. For all species the most important factors influencing annual discard ogives were fleet (combination of gear, fishing ground, and targeted species), mean length of the catch and year, and, for megrim, also minimum landing size. The length at which fish are discarded has increased since 2000 for haddock, whiting, and plaice. In contrast, discarded length has decreased for megrim, accompanying a reduction in minimum landing size in 2000.

Estimation of gear tooth deflection by the finite element method

The finite element method (FEM) is used to determine for pitch-point, mid-point and tip loading, the deflection curve of a Image 1 diamentral pitch (DP) standard spur gear tooth corresponding to number of teeth of 14, 21, 26 and 34. In all these cases the deflection of the gear tooth at the point of loading obtained by FEM is in good agreement with the experimental value. The contraflexure in the deflection curve at the point of loading observed experimentally in the cases of pitch-point and mid-point loading, is predicted correctly by the FEM analysis.

Gear selectivity of large-mesh nets and drumlines used to catch sharks in the Queensland Shark Control Program.

Catches of sharks and bycatch in large-mesh nets and baited drumlines used by the Queensland Shark Control Program were examined to determine the efficacy of both gear types and assess fishing strategies that minimise their impacts. There were few significant differences in the size of both sharks and bycatch in the two gear types, apart from significantly smaller (p < 0.05) tiger sharks Galeocerdo cuvier being taken on drumlines and smaller green turtles Chelonia mydas in nets. Catch per unit effort showed orders of magnitude differences among species, even within the same family. Hammerhead sharks and rays were particularly vulnerable to net capture, whereas higher catch rates of tiger sharks were observed for drumlines. Nets caught more marine mammals, teleost fish and rays, whereas drumlines exhibited higher catch rates of the threatened loggerhead turtle Caretta caretta. Survival of most taxa (particularly obligate ram ventilators) was lower in nets than drumlines. Bycatch species (turtles and marine mammals) were able to swim to the surface to breathe when they were hooked on drumlines, enhancing their survival potential. Fishing strategies that recognise the different selectivity patterns of the gear can be developed to suit local biotic and abiotic conditions, although it is recognised that quantification of both ecological risk and risk to bathers is not a simple task.

Assessment of novel gear designs to reduce interactions between species

This project tested modified gillnets designed by commercial net fishers in the Queensland East Coast Inshore Finfish Fishery (ECIFF) to try and identify gears that would mitigate and/or improve interactions between fishing nets and Species of Conservation Interest (SOCI). The study also documents previously unrecognised initiatives by pro-active commercial net fishers that reflect a conservation-minded approach to their fishing practices, which is the opposite of what is perceived publicly. Between 2011 and 2014, scientists from James Cook University and the Queensland Department of Agriculture and Fisheries teamed with commercial fishers representing the Queensland Seafood Industry Association and the Moreton Bay Seafood Industry Association to conduct field trials of various modified net designs under normal fishery conditions. Trials were conducted in Moreton Bay (southern part of the fishery) and Bowling Green Bay (northern) and tested different net designs developed by fishers to improve the nature of interactions between net fishing gear and SOCI.

Leopold Landsberger dressed in flying gear standing in front of a propeller airplane.

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Staircase and first floor landing; Steinharter residence; Munich Architecture; Residences; Interior

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