Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

A PCR-based method to distinguish fungi of the rice sheath-blight complex, Rhizoctonia solani, R. oryzae and R. oryzae-sativae

Identification of Rhizoctonia solani, R. oryzae and R. oryzae-sativae, components of the rice sheath disease complex, is extremely difficult and often inaccurate and as a result may hinder the success of extensive breeding programmes throughout Asia. In this study, primers designed from unique regions within the rDNA internal transcribed spacers have been used to develop a rapid PCR-based diagnostic test to provide an accurate identification of the species on rice. Tests on the specificity of the primers concerned showed that they provide the means for accurate identification of the Rhizoctonia species responsible for sheath diseases in rice.

A PCR-based method to characterise and identify benzimidazole resistance in Helminthosporium solani

Control of Helminthosporium solani, the cause of silver scurf in potato tubers, has been impaired by selection of benzimidazole-resistant strains as a result of repeated use of the fungicide thiabendazole. Identification of thiabendazole-resistant strains of H. solani by conventional techniques takes several weeks. Primers designed from conserved regions of the fungal beta-tubulin gene were used to PCR amplify and sequence a portion of the gene. A point mutation was detected at codon 198 in thiabendazole-resistant isolates causing a change in the amino acid sequence from glutamic acid to alanine or glutamine. Species-specific PCR primers designed to amplify this region were used in conjunction with a restriction endonuclease to cause cleavage in sensitive isolates only and thus provide a rapid diagnostic test to differentiate field isolates.

Identification of benzimidazole resistance in Cladobotryum dendroides using a PCR-based method

Cladobotryutn dendroides, causal agent of cobweb disease of Agaricus bisporus, has become increasingly resistant to methylbenzimidazole carbamate (MBC) fungicides following the extensive use of MBC in cultivated mushroom production in Ireland. Of 38 isolates of C. dendroides obtained from Irish mushroom units, 34 were resistant to carbendazim. Primers based on conserved regions of the -tubulin gene were used to amplify and sequence a portion of the -tubulin gene in C. dendroides. A point mutation was detected at codon 50 in isolates resistant to benzimidazole fungicides, causing an amino acid substitution from tyrosine to cysteine. Species-specific PCR primers were designed to amplify the region of the -tubulin gene containing this substitution. The point mutation removed an Ace I restriction site in the -tubulin gene sequence of resistant isolates. Digestion of the PCR product with Ace I thus provides a rapid diagnostic test to differentiate sensitive and resistant isolates of this fungus. EMBL accession number: YI2256.

Measurement-based Method for Wind Farm Power System Oscillation Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

An EPID-based method for comprehensive verification of gantry, EPID and the MLC carriage positional accuracy in Varian linacs during arc treatments

Background

]In modern radiotherapy, it is crucial to monitor the performance of all linac components including gantry, collimation system and electronic portal imaging device (EPID) during arc deliveries. In this study, a simple EPID-based measurement method has been introduced in conjunction with an algorithm to investigate the stability of these systems during arc treatments with the aim of ensuring the accuracy of linac mechanical performance.

The Varian EPID sag, gantry sag, changes in source-to-detector distance (SDD), EPID and collimator skewness, EPID tilt, and the sag in MLC carriages as a result of linac rotation were separately investigated by acquisition of EPID images of a simple phantom comprised of 5 ball-bearings during arc delivery. A fast and robust software package was developed for automated analysis of image data. Twelve Varian linacs of different models were investigated.

The average EPID sag was within 1 mm for all tested linacs. All machines showed less than 1 mm gantry sag. Changes in SDD values were within 1.7 mm except for three linacs of one centre which were within 9 mm. Values of EPID skewness and tilt were negligible in all tested linacs. The maximum sag in MLC leaf bank assemblies was around 1 mm. The EPID sag showed a considerable improvement in TrueBeam linacs.

The methodology and software developed in this study provide a simple tool for effective investigation of the behaviour of linac components with gantry rotation. It is reproducible and accurate and can be easily performed as a routine test in clinics.

A new performance based method for design and maintenance of reinforced concrete structures

Best concrete research paper by a student - Research has shown that the cost of managing structures puts high strain on the infrastructure budget, with
estimates of over 50% of the European construction budget being dedicated to repair and maintenance. If reinforced concrete
structures are not suitably designed and adequately maintained, their service life is compromised, resulting in the full economic
value of the investment not realised. The issue is more prevalent in coastal structures as a result of combinations of aggressive
actions, such as those caused by chlorides, sulphates and cyclic freezing and thawing.
It is a common practice nowadays to ensure durability of reinforced concrete structures by specifying a concrete mix and a
nominal cover at the design stage to cater for the exposure environment. This in theory should produce the performance required
to achieve a specified service life. Although the European Standard EN 206-1 specifies variations in the exposure environment,
it does not take into account the macro and micro climates surrounding structures, which have a significant influence on their
performance and service life. Therefore, in order to construct structures which will perform satisfactorily in different exposure
environments, the following two aspects need to be developed: a performance based specification to supplement EN 206-1
which will outline the expected performance of the structure in a given environment; and a simple yet transferrable procedure
for assessing the performance of structures in service termed KPI Theory. This will allow the asset managers not only to design
structures for the intended service life, but also to take informed maintenance decisions should the performance in service fall
short of what was specified. This paper aims to discuss this further.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Engaging the Senses: Object-based learning in higher education

The use of museum collections as a path to learning for university students is fast becoming a new pedagogy for higher education. Despite a strong tradition of using lectures as a way of delivering the curriculum, the positive benefits of ‘active’ and ‘experiential learning’ are being recognised in universities at both a strategic level and in daily teaching practice. As museum artefacts, specimens and art works are used to evoke, provoke, and challenge students’ engagement with their subject, so transformational learning can take place. This unique book presents the first comprehensive exploration of ‘object-based learning’ as a pedagogy for higher education in a broad context. An international group of authors offer a spectrum of approaches at work in higher education today. They explore contemporary principles and practice of object-based learning in higher education, demonstrating the value of using collections in this context and considering the relationship between academic discipline and object-based learning as a teaching strategy.