Various systems for simulating particulate matter are developed and used in concrete technology for producing virtual cementitious materials on the different levels of the microstructure. Basically, the systems can be classified as two distinct families, namely random sequential addition systems (RSAs) and discrete element methods (DEMs). The first type is hardly being used for this purpose outside concrete technology, but became popular among concrete technologists. Hence, it is of utmost relevance to compare the two families in their capabilities, so that the reliability of produced data can be estimated. This paper pursues to do this on the basis of earlier published material of work performed by a succession of PhD students in the group of the second author. Limited references will be given to external sources.

This paper introduces and compares two types of GML-based data standards for indoor location-based services, i.e., iIndoorGML and iIndoorLocationGML. By elaborating the advantages of the both standards and their data models, we conclude that the two data standards are complementary to each other. A jointed data model is presented to show the integration of the two standards. iIndoorGML can supply subdivision of building for data of iIndoorLocationGML, and the semantics of locations defined in iIndoorLocationGML can be added to iIndoorGML. By proposing two use cases, we take the initiative in attempting to combine the use of the two standards. The first case is to collect details from files of the two standards for an indoor path; the second one is to generate verbal directions for indoor guidance from files of the two standards. Some future work is given for further development, such as automatic integration of separate data from both standards.

Foam can potentially solve the associated problems with gas injection by reducing the mobility of the injected gas leading to a more stable displacement front. It is known that under immiscible conditions, the presence of oil can be detrimental for foam stability through several mechanisms. Under miscible conditions, there is no separate oil or gas phase; instead, CO2 and oil mix in different proportions forming a phase with varying composition at the proximity of the displacement front. There are then two fundamental questions, which arise from addition of surfactant to the system: (1) what is the nature of the “mixed phase” in the presence of the surfactant, and (2) how do the properties of this mixture change with compositional variations? This study reports the results of core-flood experiments conducted using CO2 and decane (nC10) as the model oil under miscible conditions. Surfactant and a mixture of CO2-decane were co-injected with variations of CO2 molar fractions, mixture volume fractions and total flow rates. We found that separate injection of CO2 or oil with the surfactant solution into the cores creates in-situ fluids that exhibit both low-quality (increasing viscosity with decreasing fraction of surfactant) and high-quality (decreasing viscosity with decreasing fraction of surfactant) regimes. However, upon simultaneous injection of CO2 and oil with the surfactant solution and depending on the molar fraction of CO2 in CO2- decane mixture (xCO2), three distinct regimes were observed. In Regime 1 (xCO2>0.8) the apparent viscosity of the in-situ fluid was the highest and increased with increasing xCO2. In Regime 2 (xCO2<2) the apparent viscosity increased with decreasing xCO2. In Regime 3 (0.2< xCO2<0.8) the apparent viscosity of the fluid remained relatively low and insensitive to the value of xCO2. Shear-thinning rheology was observed in all three regimes: supercritical CO2 foam (xCO2 =1), decane emulsion (xCO2 = 0), as well as CO2-decane-surfactant floods. Moreover, in Regime 1 and Regime 2, there is a transition at shear rates from 10 s-1 to 100 s-1, where the apparent viscosity increases by one order of magnitude. In Regime 3, however, this transition is not observed. Finally, we found that the current implicit-texture foam model cannot simulate our experimental data.