Geochemistry, Hydrothermal alteration and Ore mineralogy of Skarn Mineralization at Wethey-Pheshey area, Thabeikkyin Township, Mandalay Region, Myanmar

Wethey-Pheshy area is located 80 km north of Mandalay at Thabeikkyin Township, Mandalay Region. X-ray Diffraction (XRD) Analysis and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) were applied in this study. Geochemical studies on the host rocks indicate that major and minor oxides compositions of metamorphicrocks show some degree of variation. CaO, MgO, FeO, TiO2 and P2O5 concentration of the metamorphic rock samples show a coherent negative correlation with SiO2 whereas Na2O is positively correlated with SiO2. The metamorphic rocks are strongly enriched in light rare earth elements (LREE) and relatively depleted in heavy rare earth element (HREE). The depleted Eu-nomalies in the chondrite-normalized REE diagrams indicate a plagioclase-depleted Eu crustal source or fractionation during magmatic differentiation. Intrusion of granitic rocks in the diopside marble caused the base metal ore mineralization and associated skarn alterations. Granite shows the sub-alkaline nature and peraluminous character. It is identified as I-type granite (magnetite series) developed in the volcanic arc setting. Hydrothermal alteration types associated with gold and skarn mineralization in the study area include calc-silicate alteration, propylitization, sericitization (argillitization) and hematization. Based on the nature and characteristics of host rocks, mineralization and alteration style and geochemical characteristics in the study area is identified as intrusion-related skarn mineralization. Common ore minerals include chalcopyrite, galena, sphalerite, pyrite, gold and Fe-oxides.

Frequency-Power Control of VSWTG for Improved Frequency Regulation

With increasing wind energy penetration and impending grid codes, it is important to enable wind-based power plants to provide sensitive frequency response in grids that may experience irregular frequency fluctuations with noise induced. Transient low-frequency deviations are handled by inertial control, while active power frequency response controller is needed for high-frequency control. A frequency processor-based frequency-active power set point controller architecture for variable speed wind turbine generator (VSWTG) is presented in this paper. Grid frequency processor based on moving averaged frequency and dynamic dead-band is tested for two different grid codes. Generated active power set point is provided to a modified torque-pitch control loop in type 3 and type 4 variable speed wind turbine generator generic models. Delay model of hydro system in a single area load frequency control is applied to investigate frequency support from proposed frequency response controller-based VSWTG. Area frequency response along with VSWTG electrical power support is compared with other droop-based VSWTG model to establish the superiority of proposed frequency-active power controller-based VSWTG over other droop-based VSWTG models

Osmotic Dehydration of Toddy Fruit Cubes in Sugar Solution Using Response Surface Methodology

The response surface methodology (RSM) was applied to optimize the effects of immersion time (60, 90 and 120 min), temperature (35, 45 and 55°C) and concentration of sucrose solution (30, 40 and 50°Brix) in osmotic dehydration of toddy fruit tubes (1cm3). Box-Behnken Design was used with water loss (WL, %), solid gain (SG, %), and weight reduction (WR, %) as responses. The models obtained for all the responses were significant (P≤0.05) without a significant lack of fit. The optimum conditions were temperature (45°C), immersion time (120min), concentration of sucrose solution (40°Brix) in order to obtain WL of (33.867g/100g initial sample), SG of (4.478g/100g initial sample) and WR of 29.39 g/100g initial sample, respectively

A Model HACCP Plan for Fish Seasoning Powder Production

Many kinds of seasoning powder available in market contain high amount of monosodium glutamate (MSG) in Myanmar. So, natural seasoning powder without MSG from fish and vegetables seasoning powder was considered for safe and healthy product as substitute of MSG. The main aim of this research is to design Hazard Analysis and Critical Control Point (HACCP) plan for fish based seasoning powder production. Local indigenous raw materials such as Ngar-Gyin (Mrigal fish), cabbage, carrot, cauliflower, chinese cabbage, garlic and ginger were used in the formulation of fish based seasoning powder. The prerequisite programs (PRPs), operational prerequisite programs (OPRPs), hazards, critical control point, preventive measure, critical limits, monitoring procedure and corrective actions have been designed in this HACCP plan. A sample generic HACCP plan was recommended. Three Critical Control Points (CCPs) in the processing; cold storage of raw fish; pressure cooking and packaging were identified. A HACCP plan was completed with perquisite programs dealing with the identified hazards

Issues and mitigations of wind energy penetrated network: Australian network case study

Longest geographically connected Australian power system is undergoing an unprecedented transition, under the effect of increased integration of renewable energy systems. This change in generation mix has implications for the whole interconnected system designs, its operational strategies and the regulatory framework. Frequency control policies about real-time balancing of demand and supply is one of the prominent and priority operational challenge requiring urgent attention. This paper reviews the Australian electricity market structure in presence of wind energy and its governance. Various issues related to increased wind generation systems integration are discussed in detail. Currently applied mitigations along with prospective mitigation methods requiring new or improved policies are also discussed. It is concluded that developing prospective frequency regulation ancillary services market desires further encouraging policies from governing authority to keep pace with current grid transition and maintain its security

Integration of technical equipment in a project driven learning environment

Purpose: This paper describes the integration of technical equipment in a project driven learning environment in the School of Engineering in the Faculty of Science, Engineering and Built Environment at Deakin University, Geelong, Australia. Technical or laboratory equipment is a critical factor when designing learning environments and more so in a project driven learning environment. Important Findings: Deakin University has strong partnerships with industry and the community and with its cloud and located based learning policy has extremely flexible learning environments tailored to the needs of the students, with all the programs being offered in on-campus mode as well as off-campus mode. The off-campus study mode has made it even more important to have flexibility in the usage and access of the technical equipment in the laboratories. Conclusion: The School of Engineering at Deakin University Australia has developed a project-oriented design based learning environment which allows students to learn through design activities while being driven by the deliverables and outputs of a project. The technical equipment is required to be able to be used for traditional laboratory experiments in order to achieve fundamental knowledge requirements as well as project oriented knowledge and practice

The effectiveness of feature selection method in solar power prediction

This paper empirically shows that the effect of applying selected feature subsets on machine learning techniques significantly improves the accuracy for solar power prediction. Experiments are performed using five well-known wrapper feature selection methods to obtain the solar power prediction accuracy of machine learning techniques with selected feature subsets. For all the experiments, the machine learning techniques, namely, least median square (LMS), multilayer perceptron (MLP), and support vector machine (SVM), are used. Afterwards, these results are compared with the solar power prediction accuracy of those same machine leaning techniques (i.e., LMS, MLP, and SVM) but without applying feature selection methods (WAFS). Experiments are carried out using reliable and real life historical meteorological data. The comparison between the results clearly shows that LMS, MLP, and SVM provide better prediction accuracy (i.e., reduced MAE and MASE) with selected feature subsets than without selected feature subsets. Experimental results of this paper facilitate to make a concrete verdict that providing more attention and effort towards the feature subset selection aspect (e.g., selected feature subsets on prediction accuracy which is investigated in this paper) can significantly contribute to improve the accuracy of solar power prediction