Time series semi-Markov decision process with variable costs for maintenance planning

Deciding when and how to maintain offshore wind turbines is becoming even more complex as the size of wind farms increases, while accessibility is challenging compared to onshore wind farms. Planning future maintenance actions requires the wind farm operator to consider factors such as the current condition of the turbine, the cost of a given maintenance action, revenue generated by the asset, weather factors and vessel availability. Rather than making case-by-case decisions for each turbine, the approach described in this paper allows the wind farm operators to automate the process of short to-medium term maintenance planning through application of a Semi-Markov Decision Process (SMDP). The model proposed here is capable of suggesting the cost-optimal maintenance policy given weather forecast, future vessel costs and availability and the current condition of the turbine. Using the semi-Markov approach, allows the user to implement time varying failure rate. As the model is capable of utilising time-series data, future weather and vessel constraints can be applied depending on the information available to the user at the time, which will be reflected in the optimal policy suggested by the model. The model proposed here facilitates maintenance decision making in wind farms and will lead to cost reduction through more efficient planning. In addition to that, the model can be used to carry out a cost-benefit analysis of using vessels with different properties

Semigroup analysis of structured parasite populations

Motivated by structured parasite populations in aquaculture we consider a class of size-structured population models, where individuals may be recruited into the population with distributed states at birth. The mathematical model which describes the evolution of such a population is a first-order nonlinear partial integro-differential equation of hyperbolic type. First, we use positive perturbation arguments and utilise results from the spectral theory of semigroups to establish conditions for the existence of a positive equilibrium solution of our model. Then, we formulate conditions that guarantee that the linearised system is governed by a positive quasicontraction semigroup on the biologically relevant state space. We also show that the governing linear semigroup is eventually compact, hence growth properties of the semigroup are determined by the spectrum of its generator. In the case of a separable fertility function, we deduce a characteristic equation, and investigate the stability of equilibrium solutions in the general case using positive perturbation arguments.Comment: to appear in Mathematical Modelling of Natural Phenomen

ANALISA STATIK DAN DINAMIK GEDUNG BERTINGKAT BANYAK AKIBAT GEMPA BERDASARKAN SNI 1726-2012 DENGAN VARIASI JUMLAH TINGKAT

Diterapkannya SNI 1726-2012 sebagai standar yang baru telah menambah dan mengubah ruang lingkup tata cara perhitungan gempa menjadi lebih luas sehingga dapat mengikuti perkembangan zaman yang ada. Beban gempa dapat dianalisis secara statik maupun dinamik. Untuk analisa statik digunakan metode gaya lateral ekivalen, dan untuk analisa dinamik digunakan metode spektrum respons ragam. Penelitian ini bertujuan untuk membandingkan hasil kedua metode tersebut, sehingga kita dapat mengetahui metode mana yang lebih optimal dalam merencanakan struktur gedung tahan gempa. Struktur gedung yang dimodelkan merupakan gedung beraturan, dengan jumlah tingkat yang divariasikan. Model struktur dibagi kedalam portal 5 tingkat, 10 tingkat, dan 15 tingkat. Penelitian ini menggunakan bantuan program SAP2000 v18 untuk mempermudah proses analisa gempa. Hasil penelitian yang akan dibandingkan adalah displacement antar tingkat dan base shear yang terjadi akibat gaya gempa. Hasil analisa telah menunjukkan bahwa analisa statik mengeluarkan hasil yang lebih besar untuk ketiga model struktur dibandingkan dengan analisa dinamik. Perbedaan displacement antar tingkat yang dihasilkan oleh kedua metode pada ketiga model struktur masih masuk dalam batasan displacement antar tingkat ijin yang disyaratkan dalam SNI 1726-2012, sehingga ketiga model masih bisa dianalisa dengan analisa statik dan analisa dinamik. Karena hasil displacement dan base shear pada analisa statik lebih besar dari analisa dinamik, maka analisa statik lebih aman jika digunakan untuk pembebanan gaya gempa dalam perhitungan struktur secara umum. Walaupun dalam analisa gempa, analisa dinamik merupakan analisa yang lebih akurat karena proses analisa yang lebih mendekati ke keadaan yang sebenarnya. Kata Kunci : SNI 1726-2012, analisa statik, analisa dinamik, SAP200

Diabetic Retinopathy Screening Using Computer Vision

6-pagesDiabetic Retinopathy (DR) is one of the main causes of blindness and visual impairment in developed countries, stemming solely from diabetes mellitus. Current screening methods using fundus images rely on the experience of the operator as they are manually examined. Automated methods based on neural networks and other approaches have not provided sensitivity or specificity above 85%. This work presents a computer vision based method that directly identifies hard exudates and dot haemorrhages (DH) from 100 digital fundus images from a graded database of images using standard computer vision techniques, and clinical observation and knowledge. Sensitivity and specificity in diagnosis are 95-100% in both cases. Positive and negative prediction values (PPV, NPV) were 95-100% for both cases. The overall method is general, computationally efficient and suitable for further clinical trials to test both accuracy and the ability to the track DR status over time

Using agent-based modelling to predict the role of wild refugia in the evolution of resistance of sea lice to chemotherapeutants

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments

Robust Rolling Horizon Optimisation Model for Offshore Wind Farm Installation Logistics

Our approach can be considered as both proactive and reactive, since uncertainty is considered both in creating the initial schedule and the schedule can be updated in real-time

Mate limitation in sea lice infesting wild salmon hosts : the influence of parasite sex ratio and aggregation

Mate limitation in dioecious parasite species has the potential to impact parasite population growth. Our focus of interest was the influence of parasite sex distribution among hosts on parasite reproduction and transmission dynamics for populations of ectoparasitic sea lice (Lepeophtheirus salmonis Krøyer) establishing on wild juvenile salmon hosts. The data included more than 139,000 out-migrating juvenile pink salmon (Oncorhynchus gorbuscha (Walbaum)) and chum salmon (Oncorhynchus keta (Walbaum)) in British Columbia, Canada, sampled over nine years. For almost all years, the sex ratio of the reproductive stages of the sea lice was female-biased. The probability of a female being able to mate (i.e., of being attached to a fish also carrying a male louse) increased with increasing parasite abundance and parasite aggregation. We compared, with expected modeling predictions, the observed prevalence of pairs of sea lice (i.e., one reproductive louse of each sex) on a given fish and the observed probability of a female being able to mate. These comparisons showed that male and female sea lice tend to be distributed together rather than separately on hosts. Distribution together means that sea lice are distributed randomly on hosts according to a common negative binomial distribution, whereas distribution separately means that males are distributed according to a negative binomial and females are distributed in their own negative binomial among hosts. Despite the tendency for distribution together we found that, in every year, at least 30% of reproductive female sea lice experience mate limitation. This Allee effect will result in submaximal rates of parasite reproduction at low parasite abundances and may limit parasite transmission. The work has important implications for salmon parasite management and the health both of captive farm salmon populations and migratory wild stocks. More broadly, these results demonstrate the potential impact of mate limitation as a constraint to the establishment and spread of wild ectoparasite populations

Intelligent integrated maintenance for wind power generation

A novel architecture and system for the provision of Reliability Centred Maintenance (RCM) for offshore wind power generation is presented. The architecture was developed by conducting a bottom-up analysis of the data required to support RCM within this specific industry, combined with a top-down analysis of the required maintenance functionality. The architecture and system consists of three integrated modules for Intelligent Condition Monitoring, Reliability and Maintenance Modelling, and Maintenance Scheduling that provide a scalable solution for performing dynamic, efficient and cost effective preventative maintenance management within this extremely demanding renewable energy generation sector. The system demonstrates for the first time, the integration of state-of-the-art advanced mathematical techniques: Random Forests, Dynamic Bayesian Networks, and Memetic Algorithms in the development of an intelligent autonomous solution. The results from the application of the intelligent integrated system illustrated the automated detection of faults within a wind farm consisting of over 100 turbines, the modelling and updating of the turbines’ survivability and creation of a hierarchy of maintenance actions, and the optimising of the maintenance schedule with a view to maximising the availability and revenue generation of the turbines

Modelling sea lice control by lumpfish on Atlantic salmon farms : interactions with mate limitation, temperature and treatment rules

Atlantic salmon farming is one of the largest aquaculture sectors in the world. A major impact on farm economics, fish welfare and, potentially, nearby wild salmonid populations, is the sea louse ectoparasite Lepeophtheirus salmonis. Sea louse infestations are most often controlled through application of chemicals, but in most farming regions, sea lice have evolved resistance to the small set of available chemicals. Therefore, alternative treatment methodologies are becoming more widely used. One increasingly common alternative treatment involves the co-culture of farmed salmon with cleaner fish, which prey on sea lice. However, despite their wide use, little is understood about the situations in which cleaner fish are most effective. For example, previous work suggests that a low parasite density results in sea lice finding it difficult to acquire mates, reducing fecundity and population growth. Other work suggests that environmental conditions such as temperature and external sea louse pressure have substantial impact on this mate limitation threshold and may even remove the effect entirely. We used an Agent-Based Model (ABM) to simulate cleaner fish on a salmon farm to explore interactions between sea louse mating behaviour, cleaner fish feeding rate, temperature and external sea louse pressure. We found that sea louse mating has a substantial effect on sea louse infestations under a variety of environmental conditions. Our results suggest that cleaner fish can control sea louse infestations most effectively by maintaining the population below critical density thresholds