Loss to assets : production of power from speed breaker

In this work, prospect and feasibility of power generation by using speed breakers has been investigated. In this project a mechanism to generate power by converting the potential energy generated by a vehicle going up on a speed breaker into kinetic energy. This arrangement is made one rotation as soon as the vehicle moves over the speed breaker and has been increased using gears. After the production electricity, a storing unit has been used to hoard the generated electricity during the day and will be used during the night. Two prototypes have made using rack and pinion gear, spur gear, springs and generator .From which a considerable amount of energy is obtained. Nonetheless the cost of the prototype was inexpensive which proves the feasibility of this project and the idea can be applied on heavy traffic roads. Further investigation is being carried on to introduce the technology for practical approach.

Assessing the energy efficiency of gear oils via the FZG test machine

Energy efficient lubricants are becoming increasingly popular. This is due to a global increase in environmental awareness combined with the potential of reducing operating costs. A new test method of evaluating the energy efficiency of gear oils has been described in this report. The method involves measuring the power required by an FZG test rig to run while using a particular test lubricant. For each oil that was being evaluated, the rig was run for 10 minutes at a load stage of 10. Six extreme pressure (EP) industrial gear oils of mineral base were tested. The difference in power requirements between the best and the worst performing oils was 2.77 and 3.24 kW, respectively. This equates to a 14.6% reduction in power, a significant amount if considered in relation to a high powered industrial machine. The oils of superior performance were noticed to run at reduced temperatures. They were also more expensive than the other products of lesser performance.

Top Gear, top journalism : three lessons for political journalists from the world's most popular TV show

This article examines the BBC program Top Gear, discussing why it has become one of the world’s most-watched TV programs, and how it has very successfully captivated an audience who might otherwise not be particularly interested in cars. The analysis of the show is here framed in the form of three ‘lessons’ for journalists, suggesting that some of the entertaining (and highly engaging) ways in which Top Gear presents information to its viewers could be usefully applied in the coverage of politics – a domain of knowledge which, like cars, many citizens find abstract or boring.

Manufacturing challenges with fabrication of large size mechanical harmonic drives

Mechanical harmonic transmissions are relatively new kind of drives having several unusual features. For example, they can provide reduction ratio up to 500:1 in one stage, have very small teeth module compared to conventional drives and very large number of teeth (up to 1000) on a flexible gear. If for conventional drives manufacturing methods are well-developed, fabrication of large size harmonic drives presents a challenge. For example, how to fabricate a thin shell of 1.7m in diameter and wall thickness of 30mm having high precision external teeth at one end and internal splines at the other end? It is so flexible that conventional fabrication methods become unsuitable. In this paper special fabrication methods are discussed that can be used for manufacturing of large size harmonic drive components. They include electro-slag welding and refining, the use of special expandable devices to locate and hold a flexible gear, welding peripheral parts of disks with wear resistant materials with subsequent machining and others. These fabrication methods proved to be effective and harmonic drives built with the use of these innovative technologies have been installed on heavy metallurgical equipment and successfully tested.

Simulations of pollutant dispersion at toll plazas using three-dimensional CFD models

Toll plazas are particularly susceptible to build-ups of vehicle-emitted pollutants because vehicles pass through in low gear. To look at this, three-dimensional computational fluid dynamics simulations of pollutant dispersion are used on the standard k e turbulence model. The effects of wind speed, wind direction and topography on pollutant dispersion were discussed. The Wuzhuang toll plaza on the Hefei-Nanjing expressway is considered, and the effects of the retaining walls along both sides of the plaza on pollutant dispersion is analysed. There are greater pollutant concentrations near the tollbooths as the angle between the direction of the wind and traffic increases implying that retaining walls impede dispersion. The slope of the walls has little influence on the variations in pollutant concentration.

Vibration isolation for autonomous helicopter flight

The mechanisms of helicopter flight create a unique, high-vibration environment which can play havoc with the accurate operation of on-board sensors. Vibration isolation of electronic sensors from structural borne oscillations is paramount to their reliable and accurate use. Effective isolation is achieved by realising a trade-off between the properties of the suspended instrument package, and the isolation mechanism. This is made more difficult as the weight and size of the sensors and computing hardware decreases with advances in technology. This paper presents a history of the design, challenges, constraints and construction of an integrated isolated vision and sensor platform and landing gear for the CSIRO autonomous X-Cell helicopter. The results of isolation performance and in-flight tests of the platform in autonomous flight are presented.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Latent degradation indicators estimation and prediction : a Monte Carlo approach

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Motorcycle protective clothing : protection from injury or just the weather?

Background Apart from helmets, little is known about the effectiveness of motorcycle protective clothing in reducing injuries in crashes. The study aimed to quantify the association between usage of motorcycle clothing and injury in crashes. Methods and findings Cross-sectional analytic study. Crashed motorcyclists (n = 212, 71% of identified eligible cases) were recruited through hospitals and motorcycle repair services. Data was obtained through structured face-to-face interviews. The main outcome was hospitalization and motorcycle crash-related injury. Poisson regression was used to estimate relative risk (RR) and 95% confidence intervals for injury adjusting for potential confounders. Results Motorcyclists were significantly less likely to be admitted to hospital if they crashed wearing motorcycle jackets (RR = 0.79, 95% CI: 0.69–0.91), pants (RR = 0.49, 95% CI: 0.25–0.94), or gloves (RR = 0.41, 95% CI: 0.26–0.66). When garments included fitted body armour there was a significantly reduced risk of injury to the upper body (RR = 0.77, 95% CI: 0.66–0.89), hands and wrists (RR = 0.55, 95% CI: 0.38–0.81), legs (RR = 0.60, 95% CI: 0.40–0.90), feet and ankles (RR = 0.54, 95% CI: 0.35–0.83). Non-motorcycle boots were also associated with a reduced risk of injury compared to shoes or joggers (RR = 0.46, 95% CI: 0.28–0.75). No association between use of body armour and risk of fracture injuries was detected. A substantial proportion of motorcycle designed gloves (25.7%), jackets (29.7%) and pants (28.1%) were assessed to have failed due to material damage in the crash. Conclusions Motorcycle protective clothing is associated with reduced risk and severity of crash related injury and hospitalization, particularly when fitted with body armour. The proportion of clothing items that failed under crash conditions indicates a need for improved quality control. While mandating usage of protective clothing is not recommended, consideration could be given to providing incentives for usage of protective clothing, such as tax exemptions for safety gear, health insurance premium reductions and rebates.

Facilitating Malaysia towards innovative society : arguing the case for open access policy

The Malaysian National Innovation Model blueprint states that there is an urgent need to pursue an innovation-oriented economy to improve the nation’s capacity for knowledge, creativity and innovation. In nurturing a pervasive innovation culture, the Malaysian government has declared the year 2010 as an Innovative Year whereby creativity among its population is highly celebrated. However, while Malaysian citizens are encouraged to be creative and innovative, scientific data and information generated from publicly funded research in Malaysia is locked up because of rigid intellectual property licensing regimes and traditional publishing models. Reflecting on these circumstances, this paper looks at, and argue why, scientific data and information should be made available, accessible and re-useable freely to promote the grassroots level of innovation in Malaysia. Using innovation theory as its platform of argument, this paper calls for an open access policy for publicly funded research output to be adopted and implemented in Malaysia. Simultaneously, a normative analytic approach is used to determine the types of open access policy that ought to be adopted to spur greater innovation among Malaysians.