Mathematical modelling and optimisation of the formulation and manufacture of aggregate food products

In this PhD study, mathematical modelling and optimisation of granola production has been carried out. Granola is an aggregated food product used in breakfast cereals and cereal bars. It is a baked crispy food product typically incorporating oats, other cereals and nuts bound together with a binder, such as honey, water and oil, to form a structured unit aggregate. In this work, the design and operation of two parallel processes to produce aggregate granola products were incorporated: i) a high shear mixing granulation stage (in a designated granulator) followed by drying/toasting in an oven. ii) a continuous fluidised bed followed by drying/toasting in an oven. In addition, the particle breakage of granola during pneumatic conveying produced by both a high shear granulator (HSG) and fluidised bed granulator (FBG) process were examined. Products were pneumatically conveyed in a purpose built conveying rig designed to mimic product conveying and packaging. Three different conveying rig configurations were employed; a straight pipe, a rig consisting two 45° bends and one with 90° bend. It was observed that the least amount of breakage occurred in the straight pipe while the most breakage occurred at 90° bend pipe. Moreover, lower levels of breakage were observed in two 45° bend pipe than the 90° bend vi pipe configuration. In general, increasing the impact angle increases the degree of breakage. Additionally for the granules produced in the HSG, those produced at 300 rpm have the lowest breakage rates while the granules produced at 150 rpm have the highest breakage rates. This effect clearly the importance of shear history (during granule production) on breakage rates during subsequent processing. In terms of the FBG there was no single operating parameter that was deemed to have a significant effect on breakage during subsequent conveying. A population balance model was developed to analyse the particle breakage occurring during pneumatic conveying. The population balance equations that govern this breakage process are solved using discretization. The Markov chain method was used for the solution of PBEs for this process. This study found that increasing the air velocity (by increasing the air pressure to the rig), results in increased breakage among granola aggregates. Furthermore, the analysis carried out in this work provides that a greater degree of breakage of granola aggregates occur in line with an increase in bend angle.

An dátheangachas agus an t-aitheantas: déagóirí Éireannacha sa 21ú haois

Tugann an staidéar taighde aghaidh ar an dátheangachas i bPoblacht na hÉireann agus go háirithe ar thuairimí dhaoine óga dátheangacha sa 21ú haois. Is é cuspóir an staidéir ná iniúchadh a dhéanamh ar mheonta déagóirí Éireannacha dátheangacha i leith na Gaeilge agus a gcuid aitheantais mar dhéagóirí dátheangacha. Déanann an staidéar anailís ar mheonta daltaí a fhreastalaíonn ar iar-bhunscoileanna lán-Ghaeilge. Féachtar ar thuairimí tuismitheoirí, múinteoirí agus iar-scoláirí freisin. Is í príomhcheist an staidéir seo ná: Cad iad meonta déagóirí Éireannacha dátheangacha i leith teanga na Gaeilge agus cad iad a n-aitheantais mar Éireannaigh óga dátheangacha? Baineadh úsáid as modhanna cáilíochtúla idir agallaimh, agallamh grúpa, scríbhneoireacht phearsanta agus ríomhphoist chun eolas a bhailiú i scoil an staidéir cháis. Roghnaíodh modh cainníochtúil an cheistneora náisiúnta chun cur leis an eolas. Tugann an taighde le tuiscint go mothaíonn déagóirí Éireannacha dearfach faoi theanga na Gaeilge agus faoin a gcuid aitheantais mar dhaoine dátheangacha. Léiríonn torthaí an taighde gurb ionann teanga na Gaeilge dóibh agus seoid luachmhar a sholáthraíonn buntáistí, deiseanna agus féidearthachtaí dóibh. Maidir le cruthú aitheantais, chuaigh formhór na ndéagóirí i scoil an staidéir cháis i dtreo a ndá ghrúpa teangeolaíochta agus chruthaigh siad “linguistic brokerage” (Shenk, 2008) a tharraing a taobh Gaelach is Béarla le chéile. Mothaíonn formhór na ndéagóirí dátheangacha seo go bhfuil aitheantas amháin acu ach go bhfuil an dá theanga, an dá chultúr agus an dá pháirt dá saoil mar pháirt den gcomhaitheantas sin. Ach ba léir go raibh éagsúlachtaí i measc na rannpháirtithe freisin. Tacaíonn torthaí an taighde le gnéithe den litríocht ar a rinneadh athbhreithniú chun ról lárnach na teanga i gcruthú aitheantais an déagóra a léiriú. Cuireann an taighde seo leis an réimse toisc go soláthraíonn sé eolas luachmhar agus fiúntach faoin dátheangachas agus aitheantas i bPoblacht na hÉireann sa 21ú haois.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.