Effects of transit quality of service characteristics on daily bus ridership

A case study of Brisbane, the capital city of Queensland, Australia, explored how explicit measures of transit quality of service (e.g., service frequency, service span, and travel time ratio) and implicit environmental predictors (e.g., topographic grade factor) influenced bus ridership. The primary hypothesis tested was that bus ridership was higher in suburbs with high transit quality of service than in suburbs with limited service quality. Multiple linear regression, used to identify a strong positive relationship between route intensity (bus-km/h-km2) and bus ridership, indicated that both increased service frequency and spatial route density corresponded to higher bus ridership. Additionally, the travel time ratio (i.e., the ratio of in-vehicle transit travel time to in-vehicle automobile travel time) had a significant negative association with suburban ridership: transit use declined as travel time ratio increased. In contrast, topographic grade and service span did not significantly affect suburban bus ridership. The study findings enhance the fundamental understanding of traveler behavior, which is informative to urban transportation policy, planning, and provision.

Experimental investigation of die wear in small-batch hammer-forging under unlubricated conditions

Wear of dies is a serious problem in the forging industry. The materials used for the dies are generally expensive steel alloys and the dies require costly heat treatment and surface finishing operations. Degeneration of the die profile implies rejection of forged components and necessitates resinking or replacement of the die. Measures which reduce wear of the die can therefore aid in the reduction of production costs. The work reported here is the first phase of a study of the causes of die wear in forging production where the batch size is small and the machine employed is a light hammer. This is a problem characteristic of the medium and small scale area of the forging industry where the cost of dies is a significant proportion of the total capital investment. For the same energy input and under unlubricated conditions, die wear has been found to be sensitive to forging temperature; in cold forging the yield strength of the die material is the prime factor governing the degeneration of the die profile, whilst in hot forging the wear resistance of the die material is the main factor which determines the rate of die wear. At an intermediate temperature, such as that characteristic of warm forging, the die wear is found to be less than that in both cold and hot forging. This preliminary study therefore points to the fact that the forging temperature must be taken into account in the selection of die material. Further, the forging industry must take serious note of the warm forging process, as it not only provides good surface finish, as claimed by many authors, but also has an inherent tendency to minimize die wear.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

Wear Next: An Exploration into the Future of Wearable Technology

Technology is increasingly infiltrating all aspects of our lives and the rapid uptake of devices that live near, on or in our bodies are facilitating radical new ways of working, relating and socialising. This distribution of technology into the very fabric of our everyday life creates new possibilities, but also raises questions regarding our future relationship with data and the quantified self. By embedding technology into the fabric of our clothes and accessories, it becomes ‘wearable’. Such ‘wearables’ enable the acquisition of and the connection to vast amounts of data about people and environments in order to provide life-augmenting levels of interactivity. Wearable sensors for example, offer the potential for significant benefits in the future management of our wellbeing. Fitness trackers such as ‘Fitbit’ and ‘Garmen’ provide wearers with the ability to monitor their personal fitness indicators while other wearables provide healthcare professionals with information that improves diagnosis. While the rapid uptake of wearables may offer unique and innovative opportunities, there are also concerns surrounding the high levels of data sharing that come as a consequence of these technologies. As more ‘smart’ devices connect to the Internet, and as technology becomes increasingly available (e.g. via Wi-Fi, Bluetooth), more products, artefacts and things are becoming interconnected. This digital connection of devices is called The ‘Internet of Things’ (IoT). IoT is spreading rapidly, with many traditionally non-online devices becoming increasingly connected; products such as mobile phones, fridges, pedometers, coffee machines, video cameras, cars and clothing. The IoT is growing at a rapid rate with estimates indicating that by 2020 there will be over 25 billion connected things globally. As the number of devices connected to the Internet increases, so too does the amount of data collected and type of information that is stored and potentially shared. The ability to collect massive amounts of data - known as ‘big data’ - can be used to better understand and predict behaviours across all areas of research from societal and economic to environmental and biological. With this kind of information at our disposal, we have a more powerful lens with which to perceive the world, and the resulting insights can be used to design more appropriate products, services and systems. It can however, also be used as a method of surveillance, suppression and coercion by governments or large organisations. This is becoming particularly apparent in advertising that targets audiences based on the individual preferences revealed by the data collected from social media and online devices such as GPS systems or pedometers. This type of technology also provides fertile ground for public debates around future fashion, identity and broader social issues such as culture, politics and the environment. The potential implications of these type of technological interactions via wearables, through and with the IoT, have never been more real or more accessible. But, as highlighted, this interconnectedness also brings with it complex technical, ethical and moral challenges. Data security and the protection of privacy and personal information will become ever more present in current and future ethical and moral debates of the 21st century. This type of technology is also a stepping-stone to a future that includes implantable technology, biotechnologies, interspecies communication and augmented humans (cyborgs). Technologies that live symbiotically and perpetually in our bodies, the built environment and the natural environment are no longer the stuff of science fiction; it is in fact a reality. So, where next?... The works exhibited in Wear Next_ provide a snapshot into the broad spectrum of wearables in design and in development internationally. This exhibition has been curated to serve as a platform for enhanced broader debate around future technology, our mediated future-selves and the evolution of human interactions. As you explore the exhibition, may we ask that you pause and think to yourself, what might we... Wear Next_? WEARNEXT ONLINE LISTINGS AND MEDIA COVERAGE: http://indulgemagazine.net/wear-next/ http://www.weekendnotes.com/wear-next-exhibition-gallery-artisan/ http://concreteplayground.com/brisbane/event/wear-next_/ http://www.nationalcraftinitiative.com.au/news_and_events/event/48/wear-next http://bneart.com/whats-on/wear-next_/ http://creativelysould.tumblr.com/post/124899079611/creative-weekend-art-edition http://www.abc.net.au/radionational/programs/breakfast/smartly-dressed-the-future-of-wearable-technology/6744374 http://couriermail.newspaperdirect.com/epaper/viewer.aspx RADIO COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 TELEVISION COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 https://au.news.yahoo.com/video/watch/29439742/how-you-could-soon-be-wearing-smart-clothes/#page1

Wear Next exhibition: What's next for wearable technology?

There was a time when 'smart attire' was simply a dress code—a happy medium between formal and informal clothes. But as technological advancements continue to change our lives, the clothes and accessories we wear are increasingly embedded with smart technology. Wearable technology is nothing new, if you cast your mind back to the popular calculator watch of the '80s. But as more advanced products like Apple Watch and FitBit become mainstream, a new exhibition in Brisbane asks what's next for wearable technology.

Investigations on the influence of graphite filler on dry sliding wear and abrasive wear behaviour of carbon fabric reinforced epoxy composites

In this experimental study, the dry sliding wear and two-body abrasive wear behaviour of graphite filled carbon fabric reinforced epoxy composites were investigated. Carbon fabric reinforced epoxy composite was used as a reference material. Sliding wear experiments were conducted using a pin-on-disc wear tester under dry contact condition. Mass loss was determined as a function of sliding velocity for loads of 25, 50, 75, and 100 N at a constant sliding distance of 6000 m. Two-body abrasive wear experiments were performed under multi-pass condition using silicon carbide (SiC) of 150 and 320 grit abrasive papers. The effects of abrading distance and different loads have been studied. Abrasive wear volume and specific wear rate as a function of applied normal load and abrading distance were also determined. The results show that in dry sliding wear situations, for increased load and sliding velocity, higher wear loss was recorded. The excellent wear characteristics were obtained with carbon-epoxy containing graphite as filler. Especially, 10 wt.% of graphite in carbon-epoxy gave a low wear rate. A graphite surface film formed on the counterface was confirmed to be effective in improving the wear characteristics of graphite filled carbon-epoxy composites. In case of two-body abrasive wear, the wear volume increases with increasing load/abrading distance. Experimental results showed the type of counterface (hardened steel disc and SiC paper) material greatly influences the wear behaviour of the composites. Wear mechanisms of the composites were investigated using scanning electron microscopy. Wear of carbon-epoxy composite was found to be mainly due to a microcracking and fiber fracture mechanisms. It was found that the microcracking mechanism had been caused by progressive surface damage. Further, it was also noticed that carbon-epoxy composite wear is reduced to a greater extent by addition of the graphite filler, in which wear was dominated by microplowing/microcutting mechanisms instead of microcracking.

Nonlinear ensemble prediction of chaotic daily rainfall

The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

Pressure and thermally induced stages of wear in dry sliding of a steel ball against an aluminium-silicon alloy flat

Wear of etched near-eutectic aluminium silicon alloy slid against a steel ball under ambient is explored. The sliding velocity is kept low (0.01 m/s) and the nominal contact pressure is varied in a 15-40 MPa range. Four stages of wear are identified; ultra mild wear, mild wear, severe wear and post severe oxidative wear. The first transition is controlled by the protrusions of silicon particles, projecting out of the aluminium alloy matrix. Once these protrusions disappear under pressure and sliding, oxidation and bulk energy dissipation mechanisms take over to institute transitions to other stages of wear. The phenomenological characteristics of wear stages are explored using a variety of techniques including nanoindentation, focused ion beam milling, electron microscopy, X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray spectroscopy (EDS) and optical interferometry. (c) 2010 Elsevier B.V. All rights reserved.

Experimental studies on the wear of engine components

Wear studies of engine components of high-speed diesel engines running under various operating conditions are presented. Tests were conducted under controlled conditions over long periods. The results of the various tests are discussed and attempts have been made to examine the effects of engine operating variables and the quality of the lubricating oil on the wear of engine components.

Dry sliding wear behavior of Al2O3 fiber reinforced aluminum composites

Dry sliding wear behavior of die-cast ADC12 aluminum alloy composites reinforced with short alumina fibers were investigated by using a pin-on-disk wear tester. The Al2O3 fibers were 4 mu m in diameter and were present in volume fractions (T-f)ranging from 0.03 to 0.26, The length of the fiber varied from 40 to 200 mu m. Disks of aluminum-alumina composites were rubbed against a pin of nitrided stainless steel SUS440B with a load of 10 N at a sliding velocity of 0.1 m/s. The unreinforced ADC 12 aluminum alloy and their composites containing low volume fractions of alumina (V-f approximate to 0.05) showed a sliding-distance-dependent transition from severe to mild wear. However, composites containing high volume fractions of alumina ( V-f > 0.05) exhibited only mild wear for all sliding distances. The duration of occurrence of the severe wear regime and the wear rate both decrease with increasing volume fraction. In MMCs the wear rate in the mild wear regime decreases with increase in volume fraction: reaching a minimum value at V-f = 0.09 Beyond V-f = 0.09 the wear rate increasesmarginally. On the other hand, the wear rate of the counterface (steel pin) was found to increase moderately with increase in V-f. From the analysis of wear data and detailed examination of (a) worn surfaces, (b) their cross-sections and (c) wear debris, two modes of wear mechanisms have been identified to be operative, in these materials and these are: (i) adhesive wear in the case of unreinforced matrix material and in MMCs with low Vf and (ii) abrasive wear in the case of MMCs with high V-f. (C) 2000 Elsevier Science Ltd. All rights reserved.

Tool wear monitoring using ant behaviour

In this paper we show the applicability of Ant Colony Optimisation (ACO) techniques for pattern classification problem that arises in tool wear monitoring. In an earlier study, artificial neural networks and genetic programming have been successfully applied to tool wear monitoring problem. ACO is a recent addition to evolutionary computation technique that has gained attention for its ability to extract the underlying data relationships and express them in form of simple rules. Rules are extracted for data classification using training set of data points. These rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in ACO based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The classification accuracy obtained in ACO based approach is as good as obtained in other biologically inspired techniques.

Effect of densification and TiB2 reinforcement on the wear of molybdenum disilicide

Wear tests were done in a pin-on-disc machine by sliding MoSi2 pins against hard-steel discs in a normal load range of 5-140 N and a speed of 0.5 m/s under nominally dry conditions in the ambient. The specific wear rate of the pin undergoes two transitions: severe to mild at low load and mild to severe at high load. The mild-wear domain is distinguished by the formation of a protective mechanically mixed layer of steel and its oxides, transferred from the counterface in particulate form. Increasing the hardness by densification and TiB2 reinforcement lowers the specific wear rate and expands the mild-wear load domain. However, even when the volume wear rate is normalised with respect to the real contact area (load/hardness) the non-dimensional wear factor is still seen to decrease with densification and reinforcement. This indicates that fracture toughness may also play an important role in determining the wear-resistance of these materials. The surface coverage on the pin by the mechanically mixed layer increases with densification and reinforcement.

Nature of corrosive and abrasive wear in ball mill grinding

Laboratory results of marked-ball wear tests are used to discuss the relative significance of corrosive and abrasive wear in wet grinding. The electrochemical mechanism was investigated by correlating the corrosive wear with the corrosion current obtained from polarization curves under abrasion. Slurry rheology governs the manner in which ground slurries coat grinding balls, thereby influencing not only the grinding efficiency but also abrasive wear. The effects of percent solids and a grinding aid are illustrated.

Effect of magnesium addition and heat treatment on mild wear of hypoeutectic aluminium-silicon alloys

The effect of magnesium addition and subsequent heat treatment on mild wear of a cast hypoeutectic aluminium-silicon alloy when slid against EN 24 steel is studied. Morphology and chemistry of worn surface and subsurface are studied with a view to identify wear mechanism. Stability of an iron-aluminium mixed surface layer was found to be the key factor controlling wear resistance.