5 resultados para PAIR DISTRIBUTION THEORIES

em Aston University Research Archive


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Rare-earth co-doping in inorganic materials has a long-held tradition of facilitating highly desirable optoelectronic properties for their application to the laser industry. This study concentrates specifically on rare-earth phosphate glasses, (R2O3)x(R'2O3)y(P2O5)1-(x+y), where (R, R') denotes (Ce, Er) or (La, Nd) co-doping and the total rare-earth composition corresponds to a range between metaphosphate, RP3O9, and ultraphosphate, RP5O14. Thereupon, the effects of rare-earth co-doping on the local structure are assessed at the atomic level. Pair-distribution function analysis of high-energy X-ray diffraction data (Qmax = 28 Å-1) is employed to make this assessment. Results reveal a stark structural invariance to rare-earth co-doping which bears testament to the open-framework and rigid nature of these glasses. A range of desirable attributes of these glasses unfold from this finding; in particular, a structural simplicity that will enable facile molecular engineering of rare-earth phosphate glasses with 'dial-up' lasing properties. When considered together with other factors, this finding also demonstrates additional prospects for these co-doped rare-earth phosphate glasses in nuclear waste storage applications. This study also reveals, for the first time, the ability to distinguish between P-O and PO bonding in these rare-earth phosphate glasses from X-ray diffraction data in a fully quantitative manner. Complementary analysis of high-energy X-ray diffraction data on single rare-earth phosphate glasses of similar rare-earth composition to the co-doped materials is also presented in this context. In a technical sense, all high-energy X-ray diffraction data on these glasses are compared with analogous low-energy diffraction data; their salient differences reveal distinct advantages of high-energy X-ray diffraction data for the study of amorphous materials. © 2013 The Owner Societies.

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We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

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The nucleotide sequence of a 3 kb region immediately upstream of the sef operon of Salmonella enteritidis was determined. A 1230 base pair insertion sequence which shared sequence identity (> 75%) with members of the IS3 family was revealed. This element, designated IS1230, had almost identical (90% identity) terminal inverted repeats to Escherichia coli IS3 but unlike other IS3-like sequences lacked the two characteristic open reading frames which encode the putative transposase. S. enteritidis possessed only one copy of this insertion sequence although Southern hybridisation analysis of restriction digests of genomic DNA revealed another fragment located in a region different from the sef operon which hybridised weakly which suggested the presence of an IS1230 homologue. The distribution of IS1230 and IS1230-like elements was shown to be widespread amongst salmonellas and the patterns of restriction fragments which hybridised differed significantly between Salmonella serotypes and it is suggested that IS1230 has potential for development as a differential diagnostic tool.

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This paper looks at potential distribution network stability problems under the Smart Grid scenario. This is to consider distributed energy resources (DERs) e.g. renewable power generations and intelligent loads with power-electronic controlled converters. The background of this topic is introduced and potential problems are defined from conventional power system stability and power electronic system stability theories. Challenges are identified with possible solutions from steady-state limits, small-signal, and large-signal stability indexes and criteria. Parallel computation techniques might be included for simulation or simplification approaches are required for a largescale distribution network analysis.

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The realisation of an eventual low-voltage (LV) Smart Grid with a complete communication infrastructure is a gradual process. During this evolution the protection scheme of distribution networks should be continuously adapted and optimised to fit the protection and cost requirements at the time. This paper aims to review practices and research around the design of an effective, adaptive and economical distribution network protection scheme. The background of this topic is introduced and potential problems are defined from conventional protection theories and new Smart Grid technologies. Challenges are identified with possible solutions defined as a pathway to the ultimate flexible and reliable LV protection systems.