Mechanical Technology January 2016

⎪ Computer-aided engineering ⎪

Winners of the 2015 antenna design competition

T ing-Yen Shih, a PhD student from the University of Wiscon- sin-Madison, was announced the 2015 winner of the FEKO Student Competition. The contest, now in its 11 th year, supports engineering education and academic excellence and is aimed at students interested in anten- nas, microwave devices, bio-electromag- netics, electromagnetic compatibility, and other electromagnetic related fields. FEKO is a software tool for optimising antenna design and placement using characteristic mode analysis (CMA). Shih’s winning entry, entitled ‘Design of Platform-Mounted HF Antennas with Enhanced Bandwidth Using the Characteristic Mode Configuration in FEKO’ , successfully developed a method using the characteristic mode configuration in FEKO to systematically and efficiently approach the bandwidth limitation of a platform mode. This re- sulted in Shih achieving the bandwidths that stand-alone antennas were not able to achieve. “Many antennas working at the high frequency (HF) band tend to have sig- nificantly smaller dimensions than the

wavelength at which they operate, and, therefore, suffer from narrow bandwidths. Since HF antennas are often mounted on metallic platforms that are physically larger than the antennas themselves, if the platform can be used as part of the antenna, the maximum linear dimension of the antenna can be increased, resulting in an enhanced bandwidth. Our goal was to design platform-mounted HF antennas with enhanced bandwidth using the char- acteristic mode configuration in FEKO,” explained Shih. “We were so impressed with the qual- ity of entries that we decided to give out three honourable mentions in addition to the winning project,” said Matthias Goelke, senior director – business de- velopment academic markets. These were: Mahrukh Khan, PhD student from the University of Missouri, USA, Marno van Rooyen, a Masters student from the University of Pretoria, South Africa and Stanley Kuja, a Master student from Stellenbosch University, also in South Africa. Details on the 2016 FEKO Student Competition will be announced in March 2016. q

Ting-Yen Shih (top), a PhD student from the University of Wisconsin-Madison, was announced the 2015 win- ner of the FEKO Student

Competition. South Africans, Stanley Kuju, photographed above right with his University of Pretoria advisor Gideon Wiid (Centre), and Marno van Rooyen (right) from Stellenbosch University were awarded honourable mentions.

Big data analytics for improved energy efficiency By Syed Mansoor Ahmad, EcoEnergy, Wipro S ophisticated sensor technology has given rise to the Internet of Things (IoT) and Machine-to-Machine (M2M) communication, embed- around the world is to achieve sustainability targets. Many enterprises are tasked with achieving this in a massively distributed infrastructure environment, which may include large office buildings, warehouses, and even water treatment plants. Achieving energy efficiency in such scenarios is excep- tionally challenging.

often unique to a customer. Practices, there- fore, must be tailored to each individual organisation. In order to achieve this, it is essential to have sufficient data available to aid in the decision-making process around how operations, services, locations and energy consumption can be optimised. Not only will the availability and analy- sis of big data around energy usage assist organisations to optimise their consump- tion, it can also provide significant insight to utility providers. Utilities can use the data to drive programmes and incentives that encourage users to adopt more energy efficient devices, which in turn will reduce overall demand. By reducing the overall demand, the utilities will be better able to provide adequate supply. This will help bridge the growing demand-supply gap. The effectiveness of this approach is well proven. There are credible industry case studies in which Wipro clients have saved up to 20% on energy costs, maintenance and operational expenses across their portfolios, simply by leveraging big data and analytics. q

ding intelligence, integrating more data sources than ever and providing the poten- tial for informed decision-making based on comprehensive insight. However, as a greater proportion of our world is driven by electricity, and populations continue to increase, we are seeing a year-on-year increase in the de- mand for energy. Harnessing the power of big data analytics, organisations can become empowered not only to reduce energy consumption, but to leverage wider supply-side optimisation, including demand management, energy procurement, and tariff-based savings. This not only helps to improve energy efficiency, it also reduces energy costs, and helps organisations to meet carbon emission reduction targets. Another challenge facing organisations

The IoT, M2M communication and the availability of big data and analytics can help to generate greater awareness of op- erations, and the analysis of this data can assist in delivering actionable insight for improvement and optimisation. Energy management also ensures that assets are run as and when they are needed, reducing the running time of equipment, which results in reduced wear and tear, ultimately extending the lifespan of assets. In addition, by running assets at the optimum set points, organisations can optimise the performance of various assets. Energy management requirements are

Mechanical Technology — January 2016

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