Influence of Injection Well Location on CO2 Geological Storage Efficiency

An analysis of the influence of injection well location on CO2 storage efficiency was carried out for three well-known geological structures (traps) in deep aquifers of the Lower Jurassic Polish Lowlands. Geological models of the structures were used to simulate CO2 injection at fifty different injection well locations. A computer simulation showed that the dynamic CO2 storage capacity varies depending on the injection well location. It was found that the CO2 storage efficiency for structures with good reservoir properties increases with increasing distance of the injection well from the top of the structure and with increasing depth difference to the top of the structure. The opposite is true for a structure with poor reservoir properties. As the quality of the petrophysical reservoir parameters (porosity and permeability) improves, the location of the injection well becomes more important when assessing the CO2 storage efficiency. Maps of dynamic CO2 storage capacity and CO2 storage efficiency are interesting tools to determine the best location of a carbon dioxide injection well in terms of gas storage capacity.

Intelligent Classification Method of Low Occupancy Big Data Based on Grid Index

In order to enhance the load balance in the big data storage process and improve the storage efficiency, an intelligent classification method of low occupancy big data based on grid index is studied. A low occupancy big data classification platform was built, the infrastructure layer was designed using grid technology, grid basic services were provided through grid system management nodes and grid public service nodes, and grid application services were provided using local resource servers and enterprise grid application services. Based on each server node in the infrastructure layer, the basic management layer provides load forecasting, image backup, and other functional services. The application interface layer includes the interfaces required for the connection between the platform and each server node, and the advanced access layer provides the human-computer interaction interface for the operation of the platform. Finally, based on the obtained main structure, the depth confidence network is constructed by stacking several RBM layers, the new samples are expanded by adding adjacent values to obtain the mean value, and the depth confidence network is used to classify them. The experimental results show that the load of different virtual machines in the low occupancy big data storage process is less than 40%, and the load of each virtual machine is basically the same, indicating that this method can enhance the load balance in the data storage process and improve the storage efficiency.

Experimental Investigation on Finned Solar Still with Enhanced Thermal Energy Storage

In the present study, a novel solar still incorporated with fins and phase change material (PCM) based energy storage, was designed. To investigate the influence of fins and energy storage unit, four cases of stills were considered. In case I, a conventional type was considered, whereas square hollow fins were fitted over the basin liner of the still in case II. In addition to fins as in case II, case III employs energy storage unit wherein PCM was packed beneath the basin liner. Case IV was similar to case III except the extension of fins into the storage unit. The addition of fins above the base liner improved the absorber surface area and the extension of the same beneath the basin liner enhanced the storage efficiency. Experiments were carried out on all the four modules with a constant basin water depth of 2 cm. The maximum productivity of the conventional solar still was found to be 3.25 litre/m2/day. On the other hand, the results reveal improvement in productivity of 17.54%, 48.61% and 55.69% with cases II, III and IV, respectively. Although stills with energy storage unit exhibited higher exergy efficiency, the presence of fins in the PCM increases the internal irreversibilities. The cost of water yielded by modified solar still (MSS) used in case IV is proved to be less as compared to conventional solar still (CSS). Further, the payback period of MSS is found to be lesser than that of CSS.

Effect of roof size on the rainwater harvesting tank sizes and performances using Tangki NAHRIM 2.0

Global warming and increasing population have direct impacts on water demand all over the world. Usage of potable water in Malaysia is high if compared with other countries and the source of potable water is mainly surface water. Rainwater harvesting is one of the popular alternatives to water resources around the world. However, even Malaysia is a country with an abundance of rainfall, rainwater harvesting is still unpopular. Different size of houses has different roof sizes which will subsequently require different sizes of rainwater tanks. This study utilized Tangki NAHRIM 2.0 (TN2); a web application to determine the optimal tank size for a rainwater harvesting system for five different roof sizes for non-potable demand. TN2 simulation uses a daily water balance model with rainfall input from a built-in database by adopting the yield-after-spillage (YAS) convention. The optimum rainwater tank sizes for five different roof sizes are found to be between 2.6 m3 and 3.8 m3 with water-saving efficiency values between 59% to 76.2% and 30.9% to 53.9% for storage efficiency. A bigger tank size offers higher watersaving efficiency but with lower storage efficiency. The output will be useful for the application of RWHS to residential houses.