Radiological and material characterization of high volume fly ash concrete

The main goal of research presented in this paper was the material and radiological characterization of high volume fly ash concrete (HVFAC) in terms of determination of natural radionuclide content and radon emanation and exhalation coefficients. All concrete samples were made with a fly ash content between 50% and 70% of the total amount of cementitious materials from one coal burning power plant in Serbia. Physical (fresh and hardened concrete density) and mechanical properties (compressive strength, splitting tensile strength and modulus of elasticity) of concrete were tested. The radionuclide content (226Ra, 232Th and 40K) and radon massic exhalation of HVFAC samples were determined using gamma spectrometry. Determination of massic exhalation rates of HVFAC and its components using radon accumulation chamber techniques combined with a radon monitor was performed. The results show a beneficial effect of pozzolanic activity since the increase in fly ash content resulted in an increase in compressive strength of HVFAC by approximately 20% for the same mass of cement used in the mixtures. On the basis of the obtained radionuclide content of concrete components the I -indices of different HVFAC samples were calculated and compared with measured values (0.27e0.32), which were significantly below the recommended 1.0 index value. The prediction was relatively close to the measured values as the ratio between the calculated and measured I-index ranged between 0.89 and 1.14. Collected results of mechanical and radiological properties and performed calculations clearly prove that all 10 designed concretes with a certain type of fly ash are suitable for structural and non-structural applications both from a material and radiological point of view.

The Evolution of 'Design Build Fly' Led Teaching in Aerospace Engineering

This paper describes the evolution of a ‘Design - Build-Fly’ (DBF) approach to the delivery and assessment of a Stage Three Aircraft Design module. It focuses on the primary learning outcomes around the design and manufacturing functions associated with the development of a remotely controlled aircraft. The work covers a six year period from 2011 to present mapping the transformation of the module from report based assessment to a more hands on approach resulting in a fully functioning remotely controlled aircraft. Results show that both the staff and student experience improved across key performance metrics including student feedback, learning and competency development. Challenges still remain in methods of placing students within teams and maintaining technical rigour in reporting as students develop vocational skills and more reflective writing styles.

Use of Gypsum and CKD to enhance early age strength of High Volume Fly Ash (HVFA) pastes

Use of higher proportions of fly ash as a cement replacement in concrete has obvious environmental and performance benefits but high volumes of fly ash are not commonly used due to perceived lower early age strengths. In this investigation, addition of cement kiln dust (CKD) and gypsum to activate the fly ash was studied and the proportions used in the paste mixes were designed to optimize the mixture ingredients to achieve the highest early age compressive strength. Change of mineral phase composition and micro structure of the composites was analyzed. It was found that CKD was much more effective in activating the fly ash than gypsum. Appreciable early age compressive strengths were achieved for fly ash contents up to 60% of the binder and these observations were supported by analysis of the mineral phases.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.