How similar are two-unit bicycle and motorcycle crashes?

This paper explores the similarities and differences between bicycle and motorcycle crashes with other motor vehicles. If similar treatments can be effective for both bicycle and motorcycle crashes, then greater benefits in terms of crash costs saved may be possible for the same investment in treatments. To reduce the biases associated with under-reporting of these crashes to police, property damage and minor injury crashes were excluded. The most common crash type for both bicycles (31.1%) and motorcycles (24.5%) was intersection from adjacent approaches. Drivers of other vehicles were coded most at fault in the majority of two-unit bicycle (57.0%) and motorcycle crashes (62.7%). The crash types, patterns of fault and factors affecting fault were generally similar for bicycle and motorcycle crashes. This confirms the need to combat the factors contributing to failure of other drivers to yield right of way to two-wheelers, and suggest that some of these actions should prove beneficial to the safety of both motorized and non-motorized two-wheelers. In contrast, child bicyclists were more often at fault, particularly in crashes involving a vehicle leaving the driveway or footpath. The greater reporting of violations by riders and drivers in motorcycle crashes also deserves further investigation.     

Binning algorithm for high-resolution IRS-P4 OCM chlorophyll image

Daily chlorophyll-a concentration from the Ocean Colour Monitor (OCM) sensor onboard the Indian Remote Sensing satellite (IRS-P4) is used to make weekly and monthly chlorophyll-a concentration maps. The pathwise swath data at 12 noon for every alternate day over the north Indian Ocean (NIO) during February 2004 and February 2005 were used to compare the existing algorithms for binning the data. Atmospherically corrected and geocorrected OCM data were used in the comparative study of three averaging algorithms – arithmetic mean (AVG), geometric mean (GEO) and maximum likelihood estimator (MLE). The analysis shows that the AVG algorithm is best suited when compared with the two other algorithms. However, for case 1 water, MLE gives nearly the same value as AVG. Based on this result, AVG was selected for operational weekly and monthly averaging of OCM data over the NIO. These high-resolution-derived chlorophyll-a weekly and monthly products will be useful to resolve inter-annual-to-decadal changes in chlorophyll-a concentration over the NIO.     

Multifunctional glow discharge analyzer for spacecraft monitoring

In this study the main objective was to develop and demonstrate a glow discharge microplasma coupled to a miniature spectrometer for detection of fire signatures from pyrolyzing and burning spacecraft materials. Our experimental results demonstrate that combustion-produced carbonaceous aerosols can serve to identify the burning materials. Demonstrating versatility for chemistry analysis, the plasma detector could differentiate carbonaceous aerosols with different C/H ratios and distinguish inorganic samples such as salts and metal oxides from carbonaceous aerosols. In addition, in situ analysis of aerosol samples validated the microplasma’s analytical utility by linearity of its optical emission intensity with aerosol elemental composition.     

Numerical simulation of particulate processes for control and estimation by spectral methods

Results of application of pseudospectral methods, also known as spectral collocation methods, to practical particulate processes including growth, nucleation, aggregation, and breakage are presented. For growth‐dominated processes, a considerable reduction in model dimension can be achieved; for pure aggregation and breakage they form a viable option. To handle problems that include aggregation, breakage, and growth phenomena simultaneously, we introduce a hybrid algorithm combining the advantages of spectral methods and cell average or fixed pivot methods for aggregation and breakage. Results are shown for analytical examples as well as real processes taken from the fields of granulation and crystallization. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2309–2319, 2012     

Numerical implementation of drop and tilt method of five-axis tool positioning for tensor product surfaces

The Drop and Tilt tool position method for five-axis machining positions a toroidal tool to have two points of contact with a tensor product Bézier surface. The method results in high order simultaneous non-linear transcendental equations that are slow to solve. In this paper, an efficient numerical implementation of the Drop and Tilt Method of multi-point tool positioning on tensor product surfaces is presented. The method was implemented in C++, and is a direct method that does not convert the tensor product surface into an intermediate representation such as triangles or point clouds. The method is successfully demonstrated on a number of tensor product Bézier surfaces.     

Modelling of wind energy‐based microgrid system implementing MMC

Nowadays, renewable energy systems have come up with more potential in power generation so as to meet the power demand. Among all the renewable systems, the wind energy generating system is believed to be at the peak. However, the wind energy‐based microgrid system is associated with many problems such as fluctuations in output voltage due to the fluctuated wind speeds and harmonics generations in the system. To address these issues, this article proposes a new method in order to achieve harmonic mitigation across its output by maintaining constant voltage. Nevertheless, particular attention has been given to the form and function of modular multilevel converter with multi‐winding transformer connected to the grid. Modular multilevel converter has been implemented with an advanced voltage controller tuned to control the voltage at its output. Also, a new system topology has been introduced with two wind turbines that are interconnected to multi‐winding transformer through asynchronous generators. The proposed system has been implemented with constant and variable wind speeds, and their respective results have also been analysed. The proposed scheme shows its effectiveness by theoretical calculations, verified by simulation and experimental results. Copyright © 2016 John Wiley & Sons, Ltd.     

Blast Fragility and Sensitivity Analyses of Steel Moment Frames with Plan Irregularities

Fragility functions are determined for braced steel moment frames (SMFs) with plans such as square-, T-, L-, U-, trapezoidal-, and semicircular-shaped, subjected to blast. The frames are designed for gravity and seismic loads, but not necessarily for the blast loads. The blast load is computed for a wide range of scenarios involving different parameters, viz. charge weight, standoff distance, and blast location relative to plan of the structure followed by nonlinear dynamic analysis of the frames. The members failing in rotation lead to partial collapse due to plastic mechanism formation. The probabilities of partial collapse of the SMFs, with and without bracing system, due to the blast loading are computed to plot fragility curves. The charge weight and standoff distance are taken as Gaussian random input variables. The extent of propagation of the uncertainties in the input parameters onto the response quantities and fragility of the SMFs is assessed by computing Sobol sensitivity indices. The probabilistic analysis is conducted using Monte Carlo simulations. The frames have least failure probability for blasts occurring in front of their corners or convex face. Further, the unbraced frames are observed to have higher fragility as compared to counterpart braced frames for far-off detonations.     

Analysis of steelmaking kinetics from IMPHOS pilot plant data

It is widely accepted that understanding the kinetics of steelmaking is a complex task, and reliable and validated kinetics models are required for developing successful steelmaking process models. Therefore, as an initial attempt, this paper analyses the applicability of first order kinetics to explain the steelmaking reaction kinetics using the published data in the IMproving Phosphorus Refining research report. The process data for 20 heats in a 6?tonne pilot plant were analysed for the removal of carbon, silicon, manganese and phosphorus using first order kinetics with static and dynamic equilibrium conditions. It was observed that the removal behaviour of silicon closely followed a first order kinetics relationship, while that of carbon only approximately followed a first order kinetics relationship. The removal of manganese did not show a good degree of fit with first order kinetics using static equilibrium condition, but a clear improvement was observed when calculated using dynamic equilibrium condition. In contrast, the kinetics of phosphorus oxidation did not follow any first order relationship.     

Availability and cost-centered preventive maintenance scheduling of continuous operating series systems using multi-objective genetic algorithm: A case study

This article presents a multi-objective (maximization of availability and minimization of maintenance cost) preventive maintenance (PM) scheduling model for a continuous operating series system (COSS) which do not provide an off-working period for PM. The objective functions are optimized by using a Multi-Objective Genetic Algorithm (MOGA). The effectiveness of the model is demonstrated through a coal-fired boiler-tube. The case study shows that the model can improve the availability along with profound reduction of the maintenance cost, i.e., increases the profit of the plant.