Service condition of railroad corridors around the insulated rail joints

Railroad corridors contain large number of Insulated Rail Joints (IRJs) that act as safety critical elements in the circuitries of the signaling and broken rail identification systems. IRJs are regarded as sources of excitation for the passage of loaded wheels leading to high impact forces; these forces in turn cause dips, cross levels and twists to the railroad geometry in close proximity to the sections containing the IRJs in addition to the local damages to the railhead of the IRJs. Therefore, a systematic monitoring of the IRJs in railroad is prudent to mitigate potential risk of their sudden failure (e.g., broken tie plates) under the traffic. This paper presents a simple method of periodic recording of images using time-lapse photography and total station surveying measurements to understand the ongoing deterioration of the IRJs and their surroundings. Over a 500 day period, data were collected to examine the trends in narrowing of the joint gap due to plastic deformation the railhead edges and the dips, cross levels and twists caused to the railroad geometry due to the settlement of ties (sleepers) around the IRJs. The results reflect that the average progressive settlement beneath the IRJs is larger than that under the continuously welded rail, which leads to excessive deviation of railroad profile, cross levels and twists.

Analysis of productive performance of crop production systems: an integrated analytical framework

Recent literature has argued that environmental efficiency (EE), which is built on the materials balance (MB) principle, is more suitable than other EE measures in situations where the law of mass conversation regulates production processes. In addition, the MB-based EE method is particularly useful in analysing possible trade-offs between cost and environmental performance. Identifying determinants of MB-based EE can provide useful information to decision makers but there are very few empirical investigations into this issue. This article proposes the use of data envelopment analysis and stochastic frontier analysis techniques to analyse variation in MB-based EE. Specifically, the article develops a stochastic nutrient frontier and nutrient inefficiency model to analyse determinants of MB-based EE. The empirical study applies both techniques to investigate MB-based EE of 96 rice farms in South Korea. The size of land, fertiliser consumption intensity, cost allocative efficiency, and the share of owned land out of total land are found to be correlated with MB-based EE. The results confirm the presence of a trade-off between MB-based EE and cost allocative efficiency and this finding, favouring policy interventions to help farms simultaneously achieve cost efficiency and MP-based EE.

Condition-based maintenance optimisation without a predetermined strategy structure for a two-component series system

Most existing research on maintenance optimisation for multi-component systems only considers the lifetime distribution of the components. When the condition-based maintenance (CBM) strategy is adopted for multi-component systems, the strategy structure becomes complex due to the large number of component states and their combinations. Consequently, some predetermined maintenance strategy structures are often assumed before the maintenance optimisation of a multi-component system in a CBM context. Developing these predetermined strategy structure needs expert experience and the optimality of these strategies is often not proofed. This paper proposed a maintenance optimisation method that does not require any predetermined strategy structure for a two-component series system. The proposed method is developed based on the semi-Markov decision process (SMDP). A simulation study shows that the proposed method can identify the optimal maintenance strategy adaptively for different maintenance costs and parameters of degradation processes. The optimal maintenance strategy structure is also investigated in the simulation study, which provides reference for further research in maintenance optimisation of multi-component systems.

Nutritional analysis of gastric contents and body condition score at a single time point in feral horses in Australia

Objective: To determine the impact of a free-choice diet on nutritional intake and body condition of feral horses. Animals: Cadavers of 41 feral horses from 5 Australian locations. Procedures: Body condition score (BCS) was determined (scale of 1 to 9), and the stomach was removed from horses during postmortem examination. Stomach contents were analyzed for nutritional variables and macroelement and microelement concentrations. Data were compared among the locations and also compared with recommended daily intakes for horses. Results: Mean BCS varied by location; all horses were judged to be moderately thin. The BCS for males was 1 to 3 points higher than that of females. Amount of protein in the stomach contents varied from 4.3% to 14.9% and was significantly associated with BCS. Amounts of water-soluble carbohydrate and ethanol-soluble carbohydrate in stomach contents of feral horses from all 5 locations were higher than those expected for horses eating high-quality forage. Some macroelement and microelement concentrations were grossly excessive, whereas others were grossly deficient. There was no evidence of ill health among the horses. Conclusions and Clinical Relevance: Results suggested that the diet for several populations of feral horses in Australia appeared less than optimal. However, neither low BCS nor trace mineral deficiency appeared to affect survival of the horses. Additional studies on food sources in these regions, including analysis of water-soluble carbohydrate, ethanol-soluble carbohydrate, and mineral concentrations, are warranted to determine the provenance of such rich sources of nutrients. Determination of the optimal diet for horses may need revision.

A Systematic review of a statistical vacuum circuit breaker model for condition monitoring

Vacuum circuit breaker (VCB) overvoltage failure and its catastrophic failures during shunt reactor switching have been analyzed through computer simulations for multiple reignitions with a statistical VCB model found in the literature. However, a systematic review (SR) that is related to the multiple reignitions with a statistical VCB model does not yet exist. Therefore, this paper aims to analyze and explore the multiple reignitions with a statistical VCB model. It examines the salient points, research gaps and limitations of the multiple reignition phenomenon to assist with future investigations following the SR search. Based on the SR results, seven issues and two approaches to enhance the current statistical VCB model are identified. These results will be useful as an input to improve the computer modeling accuracy as well as the development of a reignition switch model with point-on-wave controlled switching for condition monitoring

Drying condition effects on fluidization quality and fluidization velocity at initial and final stages of cubical particulates for pet food

In this research fluidization behavior of cubical Bovine intestine samples was studied. Bovine intestine samples were heat pump dried at atmospheric pressure and at emperatures below and above the material freezing points. Experiments were conducted to study fluidization characteristics and drying kinetics at different drying conditions. Bovine particles were characterized according to Geldart classification and minimum fluidization velocity was calculated using Ergun Equation and generalized equation for all drying conditions at the beginning of the trials and end of the trials. Walli’s model was used to categorize stability of the fluidization at the beginning and end of the drying for each trial. Walli’s values determined were positive at the beginning and end of all trials indicating stable fluidisation at the beginning and end for each drying condition.

Damage identification and condition assessment of building structures using frequency response functions and neural networks

This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

Characterisation of combustion related acoustic emission sources for diesel engine condition monitoring

This thesis represents a major step forward in understanding the link between the development of combustion related faults in diesel engines and the generation of acoustic emissions. The findings presented throughout the thesis provide a foundation so that future diesel engine monitoring systems are able to more effectively detect and monitor developing faults. In undertaking this research knowledge concerning engine function and relevant failure mechanisms was combined with different modelling methods to generate a framework that was used to effectively identify fault related activity within acoustic emissions recorded from different engines.

Studies on the clarification of juice from whole sugar cane crop

In the sugar industry, processing juice derived from the whole sugar cane plant adversely affects the yield and quality of the product sugar. Dr Thai investigated the aggregation behaviour of sugar cane juice particles and developed strategies to improve the removal of non-sucrose impurities.

Condition monitoring and operational decision making in semiconductor manufacturing

Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Acoustic emission condition monitoring : an application for wind turbine fault detection

Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

Whole-genome sequencing reveals untapped genetic potential in Africa’s indigenous cereal crop sorghum

Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16–45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

Linking ecological condition and the soundscape in fragmented Australian forests

Natural landscapes are increasingly subjected to anthropogenic pressure and fragmentation resulting in reduced ecological condition. In this study we examined the relationship between ecological condition and the soundscape in fragmented forest remnants of south-east Queensland, Australia. The region is noted for its high biodiversity value and increased pressure associated with habitat fragmentation and urbanisation. Ten sites defined by a distinct open eucalypt forest community dominated by spotted gum (Corymbia citriodora ssp. variegata) were stratified based on patch size and patch connectivity. Each site underwent a series of detailed vegetation condition and landscape assessments, together with bird surveys and acoustic analysis using relative soundscape power. Univariate and multivariate analyses indicated that the measurement of relative soundscape power reflects ecological condition and bird species richness, and is dependent on the extent of landscape fragmentation. We conclude that acoustic monitoring technologies provide a cost effective tool for measuring ecological condition, especially in conjunction with established field observations and recordings.

Impact of a change in tillage and crop residue management practice on soil chemical and microbiological properties in a cereal-producing red duplex soil in NSW, Australia

The effect of a change of tillage and crop residue management practice on the chemical and micro-biological properties of a cereal-producing red duplex soil was investigated by superimposing each of three management practices (CC: conventional cultivation, stubble burnt, crop conventionally sown; DD: direct-drilling, stubble retained, no cultivation, crop direct-drilled; SI: stubble incorporated with a single cultivation, crop conventionally sown), for a 3-year period on plots previously managed with each of the same three practices for 14 years. A change from DD to CC or SI practice resulted in a significant decline, in the top 0-5 cm of soil, in organic C, total N, electrical conductivity, NH4-N, NO3-N, soil moisture holding capacity, microbial biomass and CO2 respiration as well as a decline in the microbial quotient (the ratio of microbial biomass C to organic C; P <0.05). In contrast, a change from SI to DD or CC practice or a change from CC to DD or SI practice had only negligible impact on soil chemical properties (P >0.05). However, there was a significant increase in microbial biomass and the microbial quotient in the top 0-5 cm of soil following the change from CC to DD or SI practice and with the change from SI to DD practice (P <0.05). Analysis of ester-linked fatty acid methyl esters (EL-FAMEs) extracted from the 0- to 5-cm and 5- to 10-cm layers of the soils of the various treatments detected changes in the FAME profiles following a change in tillage practice. A change from DD practice to SI or CC practice was associated with a significant decline in the ratio of fungal to bacterial fatty acids in the 0- to 5-cm soil (P <0.05). The results show that a change in tillage practice, particularly the cultivation of a previously minimum-tilled (direct-drilled) soil, will result in significant changes in soil chemical and microbiological properties within a 3-year period. They also show that soil microbiological properties are sensitive indicators of a change in tillage practice.