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1

Removal of uranium(VI) from aqueous solution by rice husk

Xia L., Li R., Xiao Y., Zheng W., Tan K.

Environment Protection Engineering

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2017

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Vol. 43, nr 4

41--53

EN

Basic aspects of uranium adsorption by rice husk have been investigated. The influences of various experimental parameters such as pH, time, adsorbent dosage, rice husk size, temperature and various concentrations of uranium on uptake were evaluated. The thermodynamics and kinetics of adsorption were analyzed by FT-IR and SEM. The adsorption capacity for uranium on rice husk increased upon increasing initial concentration of uranium and temperature, while decreased with the increase of the amount of rice husk. Maximum uranium adsorption was observed at pH = 3 and particle size between 120 μm and 150 μm. Adsorption equilibrium was achieved within 60 min. At 25 °C, the saturated adsorption capacity qmax was up to 15.14 mg/g when the initial concentration of uranium ranged from 10 to 400 mg/dm3. The adsorption of uranium followed Langmuir adsorption isotherm and according to quasi-second order kinetic equation. The calculated values of ΔH°, ΔS°, and ΔG° indicated that the biosorption process was endothermic and spontaneous. Based on FT-IR spectra it may be concluded that hydroxyl, carbonyl, P–O and Si=O groups are the main active sites.

2

A POD/PGD reduction approach for an efficient parameterization of data - driven material microstructure models

Xia L., Raghavan B., Breitkopf P., Zhang W.

Computer Methods in Materials Science

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2013

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Vol. 13, No. 2

219--225

EN

The general idea here is to produce a high quality representation of the indicator function of different phases of the material while adequately scaling with the storage requirements for high resolution Digital Material Representation (DMR). To this end, we propose a three-stage reduction algorithm combining Proper Orthogonal Decomposition (POD) and Proper Generalized Decomposition (PGD)- first, each snapshot pixel/voxel matrix is decomposed into a linear combination of tensor products of 1D basis vectors. Next a common basis is determined for the entire set of microstructure snapshots. Finally, the analysis of the dimensionality of the resulting nonlinear space yields the minimal set of parameters needed in order to represent the microstructure with sufficient precision. We showcase this approach by constructing a low-dimensional model of a two-phase composite microstructure.

PL

Ogólna idea pracy polega na automatycznej generacji precyzyjnej funkcji reprezentującej topologię i geometrię poszczególnych faz materiału celem uzyskania modelu obliczeniowego o minimalnej liczbie parametrów. W tym celu proponujemy trzystopniowy algorytm redukcji obrazu, łączący cechy dekompozycji POD i PGD. W pierwszym etapie, macierz obrazu reprezentatywnego elementu objętościowego jest rozłożona na liniową kombinację tensorowych produktów jednowymiarowych wektorów bazowych. Następnie budujemy wspólną bazę dla całego zbioru obrazów mikrostruktury. W trzecim etapie, analiza wymiaru otrzymanej rozmaitości topologicznej daje minimalny zestaw parametrów potrzebnych do reprezentowania mikrostruktury z odpowiednią dokładnością. Jako przykład podajemy budowę niskowymiarowego modelu dwufazowej mikrostruktury kompozytu.

3

On minimal models of the Region Connection Calculus

Xia L., Li S.

Fundamenta Informaticae

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2006

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Vol. 69, nr 4

427-446

EN

Region Connection Calculus (RCC) is one primary formalism of qualitative spatial reasoning. Standard RCC models are continuous ones where each region is infinitely divisible. This contrasts sharply with the predominant use of finite, discrete models in applications. In a recent paper, Li et al. (2004) initiate a study of countable models that can be constructed step by step from finite models. Of course, some basic problems are left unsolved, for example, how many non-isomorphic countable RCC models are there? This paper investigates these problems and obtains the following results: (i) the exotic RCC model described by Gotts (1996) is isomorphic to the minimal model given by Li and Ying (2004); (ii) there are continuum many non-isomorphic minimal RCC models, where a model is minimal if it can be isomorphically embedded in each RCC model.