Predicting crack initiation due to ratchetting in rail heads using critical element analysis

This paper presents a strategy to predict the lifetime of rails subjected to large rolling contact loads that induce ratchetting strains in the rail head. A critical element concept is used to calculate the number of loading cycles needed for crack initiation to occur in the rail head surface. In this technique the finite element method (FEM) is used to determine the maximum equivalent ratchetting strain per load cycle, which is calculated by combining longitudinal and shear stains in the critical element. This technique builds on a previously developed critical plane concept that has been used to calculate the number of cycles to crack initiation in rolling contact fatigue under ratchetting failure conditions. The critical element concept simplifies the analytical difficulties of critical plane analysis. Finite element analysis (FEA) is used to identify the critical element in the mesh, and then the strain values of the critical element are used to calculate the ratchetting rate analytically. Finally, a ratchetting criterion is used to calculate the number of cycles to crack initiation from the ratchetting rate calculated.

Fatigue damage initiation life prediction for heterogeneous metals

In particle-strengthened metallic alloys, fatigue damage incubates at inclusion particles near the surface or at the change of geometries. Micromechanical simulation of inclusions such that the fatigue damage incubation mechanisms can be categorized. As micro-plasticity gradient field around different inclusions is different, a novel concept for nonlocal evaluation of micro-plasticity intensity is introduced. The effects of void aspects ration and spatial distributions are quantified for fatigue incubation life in the high-cycle fatigue regime. At last, these effects are integrated based on the statistical facts of inclusions to predict the fatigue life of structural components.

A short-term production scheduling methodology for open-pit mines

A multi-resource multi-stage scheduling methodology is developed to solve short-term open-pit mine production scheduling problems as a generic multi-resource multi-stage scheduling problem. It is modelled using essential characteristics of short-term mining production operations such as drilling, sampling, blasting and excavating under the capacity constraints of mining equipment at each processing stage. Based on an extended disjunctive graph model, a shifting-bottleneck-procedure algorithm is enhanced and applied to obtain feasible short-term open-pit mine production schedules and near-optimal solutions. The proposed methodology and its solution quality are verified and validated using a real mining case study.

Development and pilot study of the Primary Care Practice Improvement Tool (PC-PIT) : an innovative approach

Objective To assess the usability and validity of the Primary Care Practice Improvement Tool (PC-PIT), a practice performance improvement tool based on 13 key elements identified by a systematic review. It was co-created with a range of partners and designed specifically for primary health care. Design This pilot study examined the PC-PIT using a formative assessment framework and mixed-methods research design. Setting and participants Six high-functioning general practices in Queensland, Australia, between February and July 2013. A total of 28 staff participated — 10 general practitioners, six practice or community nurses, 12 administrators (four practice managers; one business manager and eight reception or general administrative staff). Main outcome measures Readability, content validity and staff perceptions of the PC-PIT. Results The PC-PIT offers an appropriate and acceptable approach to internal quality improvement in general practice. Quantitative assessment scores and qualitative data from all staff identified two areas in which the PC-PIT required modification: a reduction in the indicative reading age, and simplification of governance-related terms and concepts. Conclusion The PC-PIT provides an innovative approach to address the complexity of organisational improvement in general practice and primary health care. This initial validation will be used to develop a suite of supporting, high-quality and free-to-access resources to enhance the use of the PC-PIT in general practice. Based on these findings, a national trial is now underway.

Community pharmacy dispensing of prescription medicine sample packs: Changing the business of medicine initiation?

Prescription medicine samples (or starter packs) are provided by pharmaceutical manufacturers to prescribing doctors as one component in the suite of marketing products used to convince them to prescribe a particular medicine [1,2]. Samples are generally newer, more expensive treatment options still covered by patent [3,4]. Safe, effective, judicious and appropriate medicine use (quality use of medicines) [5] could be enhanced by involving community pharmacists in the dispensing of starter packs. Doctors who use samples show a trend towards prescribing more expensive medicines overall [6] and also prescribe more medicines [7]. Cardiovascular health and mental health are Australian National Health Priority Areas [8] and account for approximately 30% and 17%, respectively, of annual government Pharmaceutical Benefits System (PBS) in 2006 [9]. The PBS is Australia's universal prescription subsidy scheme [9]. Antihypertensives were a major contributor to the estimated 80 000 medicine-related hospital admissions in Australia in 1999 [10] and also internationally [11,12]. The aim of this study was to pilot an alternative model for supply of free sample or starter packs of prescription medicines and ascertain if it is a viable model in daily practice.

Regards, the Pit

A solo exhibition by Joseph Breikers included in the MetroArts 2011 galleries Program. The exhbition comprised a series of predominantly sculptural works that reflected the artists ongoing interest in medieval, gothic and death metal visual motifs. The exhibition thus acted as a ironic meditation on ritual, belonging and cultural identity.

Integrated approach to optimize open-pit mine block sequencing

Critical stage in open-pit mining is to determine the optimal extraction sequence of blocks, which has significant impacts on mining profitability. In this paper, a more comprehensive block sequencing optimisation model is developed for the open-pit mines. In the model, material characteristics of blocks, grade control, excavator and block sequencing are investigated and integrated to maximise the short-term benefit of mining. Several case studies are modeled and solved by CPLEX MIP and CP engines. Numerical investigations are presented to illustrate and validate the proposed methodology.

An open pit multistage mine production scheduling model for drilling, blasting and excavating operations

This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

Phenotyping cotton ovule fibre initiation with spatial statistics

Yield in cultivated cotton (Gossypium spp.) is affected by the number and distribution of fibres initiated on the seed surface but, apart from simple statistical summaries, little has been done to assess this phenotype quantitatively. Here we use two types of spatial statistics to describe and quantify differences in patterning of cotton ovule fibre initials (FI). The following five different species of Gossypium were analysed: G. hirsutum L., G. barbadense L., G. arboreum, G. raimondii Ulbrich. and G. trilobum (DC.) Skovsted. Scanning electron micrographs of FIs were taken on the day of anthesis. Cell centres for fibre and epidermal cells were digitised and analysed by spatial statistics methods appropriate for marked point processes and tessellations. Results were consistent with previously published reports of fibre number and spacing. However, it was shown that the spatial distributions of FIs in all of species examined exhibit regularity, and are not completely random as previously implied. The regular arrangement indicates FIs do not appear independently of each other and we surmise there may be some form of mutual inhibition specifying fibre-initial development. It is concluded that genetic control of FIs differs from that of stomata, another well studied plant idioblast. Since spatial statistics show clear species differences in the distribution of FIs within this genus, they provide a useful method for phenotyping cotton. © CSIRO 2007.

Cerebral regions associated with verbal response initiation, suppression and strategy use

Cerebral activation associated with performance on a novel task involving two conditions was investigated with functional magnetic resonance imaging (fMRI). In the response initiation condition, subjects nominated the general superordinate category to which each of a series of exemplars (concrete nouns) belonged. In the response suppression condition, subjects were required to nominate a general superordinate category to which each exemplar did not belong, with the instruction that they were not to nominate the same category response twice in a row. Both conditions produced distinct patterns of activation relative to an articulation control condition employing identical stimuli. When initiation and suppression conditions were directly compared, response suppression produced activation in the right frontal pole, orbital frontal cortex and anterior cingulate, left dorsolateral prefrontal cortex and posterior cingulate, and bilaterally in the precuneus, visual association cortex and cerebellum. Response latencies were significantly longer in the suppression condition. Two broadly-defined strategies associated with the correct production of words during the suppression condition were a self-ordered selection from among the superordinate categories identified during the first section of the task and the generation of novel category responses. The neuroanatomical correlates of response initiation, suppression and strategy use are discussed, as are the respective roles of response suppression and strategy generation.

Towards the development of a low cost airborne sensing system to monitor dust particles after blasting at open-pit mine sites

Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.

Optimisation of open pit mine block sequencing

This study presents a comprehensive mathematical model for open pit mine block sequencing problem which considers technical aspects of real-life mine operations. As the open pit block sequencing problem is an NP-hard, state-of-the-art heuristics algorithms, including constructive heuristic, local search, simulated annealing, and tabu search are developed and coded using MATLAB programming language. Computational experiments show that the proposed algorithms are satisfactory to solve industrial-scale instances. Numerical investigation and sensitivity analysis based on real-world data are also conducted to provide insightful and quantitative recommendations for mine schedulers and planners.

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.