Determination of ground thermal properties for energy piles by thermal response tests

Thermal properties of ground heat exchanger (GHE) such as effective thermal conductivity and borehole thermal resistance are commonly measured in the field by thermal response tests (TRTs). TRT has been proved to be a consolidated method to determine thermal properties of traditional borehole heat exchangers (BHEs). However, there is still lack of data for adopting TRT on energy piles with often a large diameter and deficiency in validation of TRT results with geological materials. In this study, ground thermal properties for typical configured GHEs of energy piles are investigated. Three TRTs are conducted and the obtained results are analyzed. Effective thermal conductivity, λ_eff, of the ground derived by following the traditional linear source model shows large deviation as compared to the thermal conductivity of the geological materials. In order to determine λ_eff properly, the linear source model is modified and an equivalent radius, r_eq, of energy piles is considered. The λ_eff estimated by the modified model shows a good agreement with thermal conductivity of the in situ geological materials. In addition, there has been no obvious correlation between borehole thermal resistances and thermal efficiency due to heat transport of energy piles that depends not only by borehole thermal resistance but also by the pile’s diameter and ground conditions. The findings drawn from this study indicate that the modified model is reasonable and useful in determining thermal properties of energy piles.     

Experimental and numerical investigations on CO2 injection and enhanced gas recovery effects in Altmark gas field (Central Germany)

The feasibility of CO₂ storage and enhanced gas recovery (EGR) effects in the mature Altmark natural gas field in Central Germany has been studied in this paper. The investigations were comprehensive and comprise the characterization of the litho- and diagenetic facies, mineral content, geochemical composition, the petrophysical properties of the reservoir rocks with respect to their potential reactivity to CO₂ as well as reservoir simulation studies to evaluate the CO₂ wellbore injectivity and displacement efficiency of the residual gas by the injected CO₂. The Rotliegend sediments of the Altmark pilot injection area exhibit distinct mineralogical, geochemical, and petrophysical features related to litho- and diagenetic facies types. The reservoir rock reactivity to CO₂ has been studied in autoclave experiments and associated effects on two-phase transport properties have been examined by means of routine and special core analysis before and after the laboratory runs. Dissolution of calcite and anhydrite during the short-term treatments leading to the enhancements of permeability and porosity as well as stabilization of the water saturation relevant for CO₂ injection have been observed. Numerical simulation of the injection process and EGR effects in a sector of the Altmark field coupled with a wellbore model revealed the possibility of injecting the CO₂ gas at temperatures as low as 10 °C and pressures around 40 bar achieving effective inflow in the reservoir without phase transition in the wellbore. The small ratio of injected CO₂ volume versus reservoir volume indicated no significant EGR effects. However, the retention and storage capacity of CO₂ will be maximized. The migration/extension of CO₂ varies as a function of heterogeneity both in the layers and in the reservoir. The investigation of CO₂ extension and pressure propagation suggested no breakthrough of CO₂ at the prospective production well during the 3-year injection period studied.     

Landslide susceptibility analysis based on ArcGIS and Artificial Neural Network for a large catchment in Three Gorges region,China

A landslide susceptibility map is very important and necessary to efficiently prevent and mitigate the losses brought by natural hazard for a large area. For the purpose of landslide susceptibility analysis for the whole Xiangxi catchment (3,209 km²), Artificial Neural Network (ANN) analysis was applied as the main method. The whole catchment was divided into two parts: the training area and the implementation area. The backwater area (559 km²) of Xiangxi catchment was used as the training area for the ANN method. In the training area the correlations between the landslide distribution and its causative factors, which includes lithology, slope angle, slope curvature and river network, have been analyzed based on the geological map and digital elevation model (DEM). The back-propagation training algorithm in ANN was selected to train the sample data from the training area, which were composed of input data (causative factors) and target output data (landslide occurrence), in order to find the correlations between them. Based on these correlations and input data in the implementation area (causative factors), the network output data were obtained for the implementation area. In the end, a map of landslide susceptibility, which was established by network output data, was presented for Xiangxi catchment. ArcGIS was applied to extract and quantify input information from a DEM for susceptibility analysis and also to present the result visually. As a result, a landslide susceptibility map, in which 70 % of all landslides are rightly classified in the training area (backwater area), was created for Xiangxi catchment.     

Interannual variability of air temperature inversions in ice-free area of northern James Ross Island,Antarctica

Theoretical and Applied Climatology - Air temperature inversions are common features in Antarctica, especially in the interior where they are observed nearly year-round. Large temporal variability...     

Impact of climate variability of the Western Tropical Pacific on maximum salinity water in the South China Sea

Ocean Dynamics - Salinity observations in the Vietnamese upwelling area in June 2016 indicated a significant increase in the salinity of the maximum salinity water (MSW). The source of MSW inflow...     

Farside explorer: unique science from a mission to the farside of the moon

Farside Explorer is a proposed Cosmic Vision medium-size mission to the farside of the Moon consisting of two landers and an instrumented relay satellite. The farside of the Moon is a unique scientific platform in that it is shielded from terrestrial radio-frequency interference, it recorded the primary differentiation and evolution of the Moon, it can be continuously monitored from the Earth–Moon L2 Lagrange point, and there is a complete lack of reflected solar illumination from the Earth. Farside Explorer will exploit these properties and make the first radio-astronomy measurements from the most radio-quiet region of near-Earth space, determine the internal structure and thermal evolution of the Moon, from crust to core, and quantify impact hazards in near-Earth space by the measurement of flashes generated by impact events. The Farside Explorer flight system includes two identical solar-powered landers and a science/telecommunications relay satellite to be placed in a halo orbit about the Earth–Moon L2 Lagrange point. One lander would explore the largest and oldest recognized impact basin in the Solar System— the South Pole–Aitken basin—and the other would investigate the primordial highlands crust. Radio astronomy, geophysical, and geochemical instruments would be deployed on the surface, and the relay satellite would continuously monitor the surface for impact events.     

Estimating the spatial pattern of human-caused forest fires using a generalized linear mixed model with spatial autocorrelation in South Korea

Most forest fires in Korea are spatially concentrated in certain areas and are highly related to human activities. These site-specific characteristics of forest fires are analyzed by spatial regression analysis using the R-module generalized linear mixed model (GLMM), which can consider spatial autocorrelation. We examined the quantitative effect of topology, human accessibility, and forest cover without and with spatial autocorrelation. Under the assumption that slope, elevation, aspect, population density, distance from road, and forest cover are related to forest fire occurrence, the explanatory variables of each of these factors were prepared using a Geographic Information System-based process. First, we tried to test the influence of fixed effects on the occurrence of forest fires using a generalized linear model (GLM) with Poisson distribution. In addition, the overdispersion of the response data was also detected, and variogram analysis was performed using the standardized residuals of GLM. Second, GLMM was applied to consider the obvious residual autocorrelation structure. The fitted models were validated and compared using the multiple correlation and root mean square error (RMSE). Results showed that slope, elevation, aspect index, population density, and distance from road were significant factors capable of explaining the forest fire occurrence. Positive spatial autocorrelation was estimated up to a distance of 32 km. The kriging predictions based on GLMM were smoother than those of the GLM. Finally, a forest fire occurrence map was prepared using the results from both models. The fire risk decreases with increasing distance to areas with high population densities, and increasing elevation showed a suppressing effect on fire occurrence. Both variables are in accordance with the significance tests.     

A general reduction scheme for reactive transport in porous media

We present a method to transform the governing equations of multispecies reactive transport in porous media. The reformulation leads to a smaller problem size by decoupling of equations and by elimination of unknowns, which increases the efficiency of numerical simulations. The reformulation presented here is a generalization of earlier works. In fact, a whole class of transformations is now presented. This class is parametrized by the choice of certain transformation matrices. For specific choices, some known formulations of reactive transport can be retrieved. Hence, the software based on the presented transformation can be used to obtain efficiency comparisons of different solution approaches. For our efficiency tests, we use the MoMaS benchmark problem on reactive transport.