Electrokinetic Removal of Petroleum Hydrocarbon from Residual Clayey Soil Following a Washing Process

This study investigates total petroleum hydrocarbon (TPH) removal from residual clayey soil, after a washing procedure, using an electrokinetic process. Eight electrokinetic experiments were carried out to investigate the characteristics of TPH removal. When 0.1 M MgSO₄ or 0.1 M NaOH was used as an electrolyte, the electric current rapidly increased within the first 100 or 200 h, respectively. A negatively charged soil surface resulted in a more negative zeta potential and greater electroosmotic flow toward the cathode. Therefore, the accumulated electroosmotic flow (EOF) when using 0.1 M NaOH as the anolyte‐purging solution was higher than when using 0.1 M MgSO₄. Although the energy consumption for the two purging solutions was similar, the efficiencies of TPH removal when 0.1 M MgSO₄ and 0.1 M NaOH with surfactant were used were 0 and 39%, respectively, because the electroosmotic flow rate increased with TPH removal efficiency. When 5% isopropyl alcohol (IPA) was used as a circulation solution, the electric current increased but the TPH removal was similar to that using water. In terms of energy consumption, the use of a surfactant‐enhanced electrokinetic process with NaOH as electrolyte was effective in removing TPHs from low‐permeability soil.     

Application of bivariate frequency analysis to the derivation of rainfall–frequency curves

Bivariate distributions have been recently employed in hydrologic frequency analysis to analyze the joint probabilistic characteristics of multivariate storm events. This study aims to derive practical solutions of application for the bivariate distribution to estimate design rainfalls corresponding to the desired return periods. Using the Gumbel mixed model, this study constructed rainfall–frequency curves at sample stations in Korea which provide joint relationships between amount, duration, and frequency of storm events. Based on comparisons and analyses of the rainfall–frequency curves derived from univariate and bivariate storm frequency analyses, this study found that conditional frequency analysis provides more appropriate estimates of design rainfalls as it more accurately represents the natural relationship between storm properties than the conventional univariate storm frequency analysis.     

Analysis of ground vibrations due to underground trains by 2.5D finite/infinite element approach

The 2.5D finite/infinite element approach is adopted to study wave propagation problems caused by underground moving trains. The irregularities of the near field, including the tunnel structure and parts of the soil, are modeled by the finite elements, and the wave propagation properties of the far field extending to infinity are modeled by the infinite elements. One particular feature of the 2.5D approach is that it enables the computation of the three-dimensional response of the half-space, taking into account the load-moving effect, using only a two-dimensional profile. Although the 2.5D finite/infinite element approach shows a great advantage in studying the wave propagation caused by moving trains, attention should be given to the calculation aspects, such as the rules for mesh establishment, in order to avoid producing inaccurate or erroneous results. In this paper, some essential points for consideration in analysis are highlighted, along with techniques to enhance the speed of the calculations. All these observations should prove useful in making the 2.5D finite/infinite element approach an effective one.     

Seismic isolation analysis of FPS bearings in spatial lattice shell structures

<正>A theoretical model of a friction pendulum system(FPS) is introduced to examine its application for the seismic isolation of spatial lattice shell structures.An equation of motion of the lattice shell with FPS bearings is developed.Then, seismic isolation studies are performed for both double-layer and single-layer lattice shell structures under different seismic input and design parameters of the FPS.The influence of frictional coefficients and radius of the FPS on seismic performance are discussed.Based on the study,some suggestions for seismic isolation design of lattice shells with FPS bearings are given and conclusions are made which could be helpful in the application of FPS.     

Metal Ion Extraction with Bipyridine Derivatives as Chelating Ligands in Supercritical Carbon Dioxide

Three fluorinated bipyridine ligands have been designed and synthesized as chelating agents for the extraction of metal ions in supercritical CO₂ (sc‐CO₂). The ligand solubilities in sc‐CO₂ were investigated at different temperatures and pressures, and the measured data have been correlated using a semiempirical model. The calculated results showed satisfactory agreement with the experimental data. Based on these data, metal ion extraction with the three compounds as chelating agents in sc‐CO₂ was performed from spiked filter paper, whereby ligand 1 showed the highest extraction efficiency, especially for Ni²⁺ and Cu²⁺. The extraction constants, K_ex, of the three chelating ligands were seen to increase with increasing extraction efficiency for the same metal ion in the same extraction system.     

Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

The conventional approach to the frequency analysis of extreme precipitation is complicated by non-stationarity resulting from climate variability and change. This study utilized a non-stationary frequency analysis to better understand the time-varying behavior of short-duration (1-, 6-, 12-, and 24-h) precipitation extremes at 65 weather stations scattered across South Korea. Trends in precipitation extremes were diagnosed with respect to both annual maximum precipitation (AMP) and peaks-over-threshold (POT) extremes. Non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with model parameters made a linear function of time were applied to AMP and POT respectively. Trends detected using the Mann–Kendall test revealed that the stations showing an increasing trend in AMP extremes were concentrated in the mountainous areas (the northeast and southwest regions) of South Korea. Trend tests on POT extremes provided fairly different results, with a significantly reduced number of stations showing an increasing trend and with some stations showing a decreasing trend. For most of stations showing a statistically significant trend, non-stationary GEV and GPD models significantly outperformed their stationary counterparts, particularly for precipitation extremes with shorter durations. Due to a significant-increasing trend in the POT frequency found at a considerable number of stations (about 10 stations for each rainfall duration), the performance of modeling POT extremes was further improved with a non-homogeneous Poisson model. The large differences in design storm estimates between stationary and non-stationary models (design storm estimates from stationary models were significantly lower than the estimates of non-stationary models) demonstrated the challenges in relying on the stationary assumption when planning the design and management of water facilities. This study also highlighted the need of caution when quantifying design storms from POT and AMP extremes by showing a large discrepancy between the estimates from those two approaches.     

A TIN compression method using Delaunay triangulation

This study introduces a new Triangulated Irregular Network(TIN) compression method and a progressive visualization technique using Delaunay triangulation. The compression strategy is based on the assumption that most triangulated 2.5-dimensional terrains are very similar to their Delaunay triangulation. Therefore, the compression algorithm only needs to maintain a few edges that are not included in the Delaunay edges. An efficient encoding method is presented for the set of edges by using vertex reordering and a general bracketing method. In experiments, the compression method examined several sets of TIN data with various resolutions, which were generated by five typical terrain simplification algorithms. By exploiting the results, the connecting structures of common terrain data are compressed to 0.17 bits per vertex on average, which is superior to the results of previous methods. The results are shown by a progressive visualization method for web-based GIS.     

A new methodology for measuring coastline recession using buffering and non‐linear least squares estimation

Coastline recession is one of the best indicators of coastal erosion. Three methods for computing coastline recession – the baseline approach, the dynamic segmentation approach and the area‐based approach – have been used, each of which has one or more drawbacks. To overcome these problems, a new methodology for measuring coastline recession is proposed, using buffering and non‐linear least squares estimation. The proposed method was compared with the three existing methods with respect to two simulated cases and two real coastlines. Test results confirmed that the new method is more reliable than the three other methods, all of which are susceptible to variability of recession, scale, number of line segments, length of coastlines and direction of the baseline. The proposed method, incorporating two physically meaningful values – magnitude and variability of coastline recession according to the mean and standard deviation of coastline offsets, respectively – presents itself as an effective alternative method of assessing coastline recession.     

Discrete displacement analysis for geographic linear features and the application to glacier termini

The extent of glacier terminus displacement is instrumental in investigations of natural or artificial geographic changes. Its importance to earth science and engineering is reflected in the considerable efforts that have been devoted to the development of several boundary displacement analysis methods. Among the methods, the buffering-based approach compares favorably with other approaches in objectivity and robustness. However, it does not consider the relative positions of boundaries, because its buffering operation cannot determine features' relative directions. This limitation incurs inaccurate calculation results – underestimation of mean shifts and overestimation of shape variations, especially when the two compared boundaries intersect. Discrete displacement analysis (DDA), an alternative method that considers given geographic objects as a set of a finite number of points, is proposed here. In a series of tests carried out, including Jakobshavn glacier's calving front, DDA was found to correctly calculate mean shift and shape variation even in cases where the conventional buffering-based method failed. Moreover, this approach is independent of the dimension of space in which it is implemented, and thus is expected to be utilized for analysis of 3D geographic object displacement.     

Effect of the inter-annual variability of rainfall statistics on stochastically generated rainfall time series: part 2. Impact on watershed response variables

This study analyzes how the stochastically generated rainfall time series accounting for the inter-annual variability of rainfall statistics can improve the prediction of watershed response variables such as peak flow and runoff depth. The modified Bartlett–Lewis rectangular pulse (MBLRP) rainfall generation model was improved such that it can account for the inter-annual variability of the observed rainfall statistics. Then, the synthetic rainfall time series was generated using the MBLRP model, which was used as input rainfall data for SCS hydrologic models to produce runoff depth and peak flow in a virtual watershed. These values were compared to the ones derived from the synthetic rainfall time series that is generated from the traditional MBLRP rainfall modeling. The result of the comparison indicates that the rainfall time series reflecting the inter-annual variability of rainfall statistics reduces the biasness residing in the predicted peak flow values derived from the synthetic rainfall time series generated using the traditional MBLRP approach by 26–47 %. In addition, it was observed that the overall variability of the peak flow and run off depth distribution was better represented when the inter-annual variability of rainfall statistics are considered.