The application of parallel processing methods to vibrational analysis

The trend in modal extraction algorithms is to use all the available frequency response functions data to obtain a global estimate of the natural frequencies, damping ratio and mode shapes. Improvements in transducer and signal processing technology allow the simultaneous measurement of many hundreds of channels of response data. The quantity of data available and the complexity of the extraction algorithms make considerable demands on the available computer power and require a powerful computer or dedicated workstation to perform satisfactorily. An alternative to waiting for faster sequential processors is to implement the algorithm in parallel, for example on a network of Transputers. Parallel architectures are a cost effective means of increasing computational power, and a larger number of response channels would simply require more processors. This thesis considers how two typical modal extraction algorithms, the Rational Fraction Polynomial method and the Ibrahim Time Domain method, may be implemented on a network of transputers. The Rational Fraction Polynomial Method is a well known and robust frequency domain 'curve fitting' algorithm. The Ibrahim Time Domain method is an efficient algorithm that 'curve fits' in the time domain. This thesis reviews the algorithms, considers the problems involved in a parallel implementation, and shows how they were implemented on a real Transputer network.

A micro gas turbines for UK domestic combined heat and power

Various micro-radial compressor configurations were investigated using one-dimensional meanline and computational fluid dynamics (CFD) techniques for use in a micro gas turbine (MGT) domestic combined heat and power (DCHP) application. Blade backsweep, shaft speed, and blade height were varied at a constant pressure ratio. Shaft speeds were limited to 220 000 r/min, to enable the use of a turbocharger bearing platform. Off-design compressor performance was established and used to determine the MGT performance envelope; this in turn was used to assess potential cost and environmental savings in a heat-led DCHP operating scenario within the target market of a detached family home. A low target-stage pressure ratio provided an opportunity to reduce diffusion within the impeller. Critically for DCHP, this produced very regular flow, which improved impeller performance for a wider operating envelope. The best performing impeller was a low-speed, 170 000 r/min, low-backsweep, 15° configuration producing 71.76 per cent stage efficiency at a pressure ratio of 2.20. This produced an MGT design point system efficiency of 14.85 per cent at 993 W, matching prime movers in the latest commercial DCHP units. Cost and CO2 savings were 10.7 per cent and 6.3 per cent, respectively, for annual power demands of 17.4 MWht and 6.1 MWhe compared to a standard condensing boiler (with grid) installation. The maximum cost saving (on design point) was 14.2 per cent for annual power demands of 22.62 MWht and 6.1 MWhe corresponding to an 8.1 per cent CO2 saving. When sizing, maximum savings were found with larger heat demands. When sized, maximum savings could be made by encouraging more electricity export either by reducing household electricity consumption or by increasing machine efficiency.

Intra-cavity dynamics in high power mode-locked fiber lasers

A theoretical model allows for the characterization and optimization of the intra-cavity pulse evolutions in high-power fiber lasers. Multi-parameter analysis of laser performance can be made at a fraction of the computational cost.

Intra-cavity dynamics in high power mode-locked fiber lasers

A theoretical model allows for the characterization and optimization of the intra-cavity pulse evolutions in high-power fiber lasers. Multi-parameter analysis of laser performance can be made at a fraction of the computational cost. © 2010 Optical Society of America.

A bi-objective weighted model for improving the discrimination power in MCDEA

Lack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the said problems in a multi-objective framework. We found GPDEA models to be invalid and demonstrate that our proposed bi-objective multiple criteria DEA (BiO-MCDEA) outperforms the GPDEA models in the aspects of discrimination power and weight dispersion, as well as requiring less computational codes. An application of energy dependency among 25 European Union member countries is further used to describe the efficacy of our approach. © 2013 Elsevier B.V. All rights reserved.

Exploration of a simple, low cost, micro gas turbine recuperator solution for a domestic combined heat and power unit

For micro gas turbines (MGT) of around 1 kW or less, a commercially suitable recuperator must be used to produce a thermal efficiency suitable for use in UK Domestic Combined Heat and Power (DCHP). This paper uses computational fluid dynamics (CFD) to investigate a recuperator design based on a helically coiled pipe-in-pipe heat exchanger which utilises industry standard stock materials and manufacturing techniques. A suitable mesh strategy was established by geometrically modelling separate boundary layer volumes to satisfy y + near wall conditions. A higher mesh density was then used to resolve the core flow. A coiled pipe-in-pipe recuperator solution for a 1 kW MGT DCHP unit was established within the volume envelope suitable for a domestic wall-hung boiler. Using a low MGT pressure ratio (necessitated by using a turbocharger oil cooled journal bearing platform) meant unit size was larger than anticipated. Raising MGT pressure ratio from 2.15 to 2.5 could significantly reduce recuperator volume. Dimensional reasoning confirmed the existence of optimum pipe diameter combinations for minimum pressure drop. Maximum heat exchanger effectiveness was achieved using an optimum or minimum pressure drop pipe combination with large pipe length as opposed to a large pressure drop pipe combination with shorter pipe length. © 2011 Elsevier Ltd. All rights reserved.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.