Aerothermal-strucutral analysis of a rocket launched Mach 8 scramjet experiment : ascent

This paper reports on the methodology and results of a weak-coupled aerothermalstructural analysis on the ascent phase of the SCRAMSPACE Mach 8 scramjet flight experiment. This vehicle was essentially un-shrouded during the flight trajectory, relying on the thin, 5mm thick aluminium external shell of the payload to maintain structural integrity and protect the flight experiment. As such, understanding the thermal-structural response of the vehicle was imperative to mission success. Using two- and three-dimensional models, an iterative procedure was employed to compute the flowfield, convective heating, wall temperatures and structural coupling at flight times covering both peak heating and peak surface temperature. Accounting for such coupling resulted in a 150K reduction in wall temperature compared to the more conservative cold wall assumption. Despite this, peak temperatures remained of the order of 550 K. Further, thermally induced stresses within these regions were in excess of four times the material failure limits. Irreversible material failure during ascent was therefore concluded likely to occur on the external shell. Two alternate materials, steel 1006 and copper, were therefore assessed with the results indicating that steel sections on the external shell resulted in the best thermal-structural response of the payload.

Utilizing micropellets as building blocks in cartilage tissue engineering

Osteoarthritis is the most common cause of pain and disability in Australia. This project describes a method where hundreds of cartilage microtissues are generated as tiny building blocks for assembly into larger tissues suitable for cartilage defect repair. Tissue engineering applications has the potential to overcome natural barriers and effectively repair damaged cartilage tissue. However, engineering few-millimeter thick cartilage, similar to human cartilage in the knee, remains a challenge. Utilizing micropellets as building blocks has the potential to overcome some of the challenges in cartilage tissue engineering.

Surface engineering of reduced graphene oxide for controllable ambipolar flash memories

Tunable charge-trapping behaviors including unipolar charge trapping of one type of charge carrier and ambipolar trapping of both electrons and holes in a complementary manner is highly desirable for low power consumption multibit flash memory design. Here, we adopt a strategy of tuning the Fermi level of reduced graphene oxide (rGO) through self-assembled monolayer (SAM) functionalization and form p-type and n-type doped rGO with a wide range of manipulation on work function. The functionalized rGO can act as charge-trapping layer in ambipolar flash memories, and a dramatic transition of charging behavior from unipolar trapping of electrons to ambipolar trapping and eventually to unipolar trapping of holes was achieved. Adjustable hole/electron injection barriers induce controllable Vth shift in the memory transistor after programming operation. Finally, we transfer the ambipolar memory on flexible substrates and study their charge-trapping properties at various bending cycles. The SAM-functionalized rGO can be a promising candidate for next-generation nonvolatile memories.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Environments for zonal cartilage tissue engineering

Articular cartilage is a highly organized tissue with cellular and matrix properties that vary with depth zones. Regenerating this zonal organization has proven difficult in tissue-engineered cartilage to treat damaged cartilage. In this thesis, we evaluated the effects of culture environments that mimic aspects of the native cartilage environment on chondrocyte subpopulations. We found that decellularized cartilage matrix can improve zonal tissue-engineered cartilage. Also, chondrocytes respond to signals from bone cells and compressive stimulation in a zone-dependent manner. These results highlight the importance of a zone-specific environment to improve tissue-engineered cartilage in vitro.

Science, Technology, Engineering, and Maths (STEM)

"Historically, science had a place in education before the time of Plato and Aristotle (e.g., Stonehenge). Technology gradually increased since early human inventions (e.g., indigenous tools and weapons), rose up dramatically through the industrial revolution and escalated exponentially during the twentieth and twenty-first centuries, particularly with the advent of the Internet. Engineering accomplishments were evident in the constructs of early civil works, including roads and structural feats such as the Egyptian pyramids. Mathematics was not as clearly defined BC (Seeds 2010), but was utilized for more than two millennia (e.g., Archimedes, Kepler, and Newton) and paved its way into education as an essential scientific tool and a way of discovering new possibilities. Hence, combining science, technology, engineering, and mathematics (STEM) areas should not come as a surprise but rather as a unique way of packaging what has been ..."--Publisher Website

Localization and place recognition using an ultra-wide band (UWB) radar

This paper presents an approach to mobile robot localization, place recognition and loop closure using a monostatic ultra-wide band (UWB) radar system. The UWB radar is a time-of-flight based range measurement sensor that transmits short pulses and receives reflected waves from objects in the environment. The main idea of the poposed localization method is to treat the received waveform as a signature of place. The resulting echo waveform is very complex and highly depends on the position of the sensor with respect to surrounding objects. On the other hand, the sensor receives similar waveforms from the same positions.Moreover, the directional characteristics of dipole antenna is almost omnidirectional. Therefore, we can localize the sensor position to find similar waveform from waveform database. This paper proposes a place recognitionmethod based on waveform matching, presents a number of experiments that illustrate the high positon estimation accuracy of our UWB radar-based localization system, and shows the resulting loop detection performance in a typical indoor office environment and a forest.

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.

Investigation into chemistry of new particle formation and growth in subtropical urban environment

The role of different chemical compounds, particularly organics, involved in the new particle formation (NPF) and its consequent growth are not fully understood. Therefore, this study was conducted to investigate the chemistry of aerosol particles during NPF events in an urban subtropical environment. Aerosol chemical composition was measured along with particle number size distribution (PNSD) and several other air quality parameters at five sites across an urban subtropical environment. An Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (c-TOF-AMS) and a TSI Scanning Mobility Particle Sizer (SMPS) measured aerosol chemical composition and PNSD, respectively. Five NPF events, with growth rates in the range 3.3-4.6 nm, were detected at two sites. The NPF events happened on relatively warmer days with lower humidity and higher solar radiation. Temporal percent fractions of nitrate, sulphate, ammonium and organics were modelled using the Generalised Additive Model (GAM), with a basis of penalised spline. Percent fractions of organics increased after the NPF events, while the mass fraction of ammonium and sulphate decreased. This uncovered the important role of organics in the growth of newly formed particles. Three organic markers, factors f43, f44 and f57, were calculated and the f44 vs f43 trends were compared between nucleation and non-nucleation days. f44 vs f43 followed a different pattern on nucleation days compared to non-nucleation days, whereby f43 decreased for vehicle emission generated particles, while both f44 and f43 decreased for NPF generated particles. It was found for the first time that vehicle generated and newly formed particles cluster in different locations on f44 vs f43 plot and this finding can be used as a tool for source apportionment of measured particles.

Teaching manufacturing engineering at tertiary institutions in conjunction with engineering design and engineering materials

Tertiary institutions now face serious challenges. Modern industry requires engineering graduates with strong knowledge of modern technologies, highly practical focus, management skills, ability to work individually and in a team, understanding of environmental issues and many other skills and graduate attributes. Institutions in the tertiary sector change courses and modify curriculum to reflect challenges of the modern industry and make engineering graduates better prepared for the “real world”. Queensland University of Technology in the recent years introduced an innovative structure of engineering courses with a common core for Bachelor of Engineering Mechanical, Infomechatronics and Medical, where manufacturing is taught in conjunction with engineering design and engineering materials. In this paper we discuss the innovative curriculum structure, teaching and learning approaches of coherent delivery of manufacturing in conjunction with engineering design and

Driving toward user-centered engineering in automotive design

In an industry worth more than €500 billion annually, producing more than 80 million vehicles worldwide each year and consisting of over 50 major manufacturers worldwide, the automotive industry represents a lucrative but highly competitive manufacturing industry (Deloitte, 2009a; European Automobile Manufacturers Association, 2012). With sales falling in Europe in 2013 for the sixth consecutive year (Boston and Curtin, 2014), automotive manufacturers are increasingly turning to new strategies to retain their share of sales in a contracting market. Some strategies have focused on the industry approach to manufacturing, namely, a technically focused push for a build-toorder process rather than the current build-to-stock approach in order to reduce overall value-chain costs and to increase efficiency (Parry and Roehrich, 2013, p. 13). However, others stress a more customer-orientated approach, striving to develop products that meet customer requirements (Oliver Wyman Group, 2007).

First-principle engineering magnetism in low-dimensional boron nitride materials

Nanotubes and nanosheets are low-dimensional nanomaterials with unique properties that can be exploited for numerous applications. This book offers a complete overview of their structure, properties, development, modeling approaches, and practical use. It focuses attention on boron nitride (BN) nanotubes, which have had major interest given their special high-temperature properties, as well as graphene nanosheets, BN nanosheets, and metal oxide nanosheets. Key topics include surface functionalization of nanotubes for composite applications, wetting property changes for biocompatible environments, and graphene for energy storage applications

Autonomous helicopter hover using an artificial neural network

Details the developments to date of an unmanned air vehicle (UAV) based on a standard size 60 model helicopter. The design goal is to have the helicopter achieve stable hover with the aid of an INS and stereo vision. The focus of the paper is on the development of an artificial neural network (ANN) that makes use of only the INS data to generate hover commands, which are used to directly manipulate the flight servos. Current results show that networks incorporating some form of recurrency (state history) offer little advantage over those without. At this stage, the ANN has partially maintained periods of hover even with misaligned sensors.

System design for a small autonomous helicopter

The detailed system design of a small experimental autonomous helicopter is described. The system requires no ground-to-helicopter communications and hence all automation hardware is on-board the helicopter. All elements of the system are described including the control computer, the flight computer (the helicopter-to-control-computer interface), the sensors and the software. A number of critical implementation issues are also discussed.

Robust sensing for a 3,500 tonne field robot

The mining industry is highly suitable for the application of robotics and automation technology since the work is arduous, dangerous and often repetitive. This paper discusses a robust sensing system developed to find and trade the position of the hoist ropes of a dragline. Draglines are large `walking cranes' used in open-pit coal mining to remove the material covering the coal seam. The rope sensing system developed uses two time-of-flight laser scanners. The finding algorithm uses a novel data association and tracking strategy based on pairing rope data.