An integrated SOFC plant dynamic model for power systems simulation
- J. Padulles, G. Ault, J. Mcdonald
- Engineering
- 1 March 2000
Modern power system planning
- X. Wang, J. Mcdonald
- Engineering
- 1994
This work provides a comprehensive approach to the planning and reliability calculations for the expansion of power generation systems, transmission networks and plant maintenance scheduling. The…
Modular multilevel inverter: Pulse width modulation and capacitor balancing technique
- G. Adam, O. Anaya‐Lara, G. Burt, D. Telford, B. Williams, J. Mcdonald
- Engineering
- 26 August 2010
The principle of operation, carrier-based pulse width modulation and a capacitors voltage balancing technique for three-level and five-level modular inverters are discussed and the results are discussed.
Electricity Network Scenarios for Great Britain in 2050
- I. Elders, G. Ault, E. Lampaditou
- Economics
- 14 March 2006
The next fifty years are likely to see great developments in the technologies deployed in electricity systems, with consequent changes in the structure and operation of power networks. This paper,…
Generator maintenance scheduling using a genetic algorithm with a fuzzy evaluation function
- K. Dahal, C. Aldridge, J. Mcdonald
- Computer ScienceFuzzy Sets Syst.
- 16 February 1999
The development of wind damage bands for buildings
- C. Unanwa, J. Mcdonald, K. Mehta, D. A. Smith
- Engineering
- 2000
Using physics-based modeler outputs to train probabilistic neural networks for unexploded ordnance (UXO) classification in magnetometry surveys
- S. Hart, R. E. Shaffer, S. Rose-Pehrsson, J. Mcdonald
- Computer ScienceIEEE Transactions on Geoscience and Remote…
- 1 April 2001
The outputs from a physics-based modeler of magnetometry data have been successfully used with a probabilistic neural network (PNN) to discriminate unexploded ordnance (UXO) from ordnance-related…
Multisensor towed array detection system for UXO detection
- H. Nelson, J. Mcdonald
- GeologyIEEE Transactions on Geoscience and Remote…
- 1 June 2001
The MTADS has shown the ability to detect ordnance at its likely self-penetration depths with a probability of detection of 0.95 or better, making remediation much quicker and less costly than with standard techniques.
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