Confidence bounds on risk assessments for underground nuclear waste repositories

The estimation of risk confidence bounds is an important element of a comprehensive probabilistic risk assessment for a radioactive waste repository. Normal distribution bounds may be used in the asymptotic limit of a very large number of Monte Carlo simulations, but sharp skewness of the risk distribution may severely retard the convergence process. The Tchebycheff bounds are parameter-free and may be applied regardless of distribution, save for the finiteness of variance. These bounds may be generally applicable, but they are invariably very broad. Better parameter-free bounds for mean risk are presented here, based on an inequality originally derived by Guttman.     

Probabilistic analysis of rock slope stability and random properties of discontinuity parameters, Interstate Highway 40, Western North Carolina, USA

Probabilistic analysis has been used as an effective tool to evaluate uncertainty so prevalent in variables governing rock slope stability. In this study a probabilistic analysis procedure and related algorithms were developed by extending the Monte Carlo simulation. The approach was used to analyze rock slope stability for Interstate Highway 40 (I-40), North Carolina, USA. This probabilistic approach consists of two parts: analysis of available geotechnical data to obtain random properties of discontinuity parameters; and probabilistic analysis of slope stability based on parameters with random properties. Random geometric and strength parameters for discontinuities were derived from field measurements and analysis using the statistical inference method or obtained from experience and engineering judgment of parameters. Specifically, this study shows that a certain amount of experience and engineering judgment can be utilized to determine random properties of discontinuity parameters. Probabilistic stability analysis is accomplished using statistical parameters and probability density functions for each discontinuity parameter. Then, the two requisite conditions, kinematic and kinetic instability for evaluating rock slope stability, are determined and evaluated separately, and subsequently the two probabilities are combined to provide an overall stability measure. Following the probabilistic analysis to account for variation in parameters, results of the probabilistic analyses were compared to those of a deterministic analysis, illustrating deficiencies in the latter procedure. Two geometries for the cut slopes on I-40 were evaluated, the original 75° slope and the 50° slope which has developed over the past 40 years of weathering.     

Photospheric Network as the Energy Source for the quiet-Sun corona

We propose a mechanism for the formation of a magnetic energy avalanche based on highly dynamic phenomena within the ubiquitous small-scale network magnetic elements in the quiet photosphere. We suggest that this mechanism may provide constant mass and energy supply for the corona and fast wind. Constantly emerging from sub-surface layers, flux tubes collide and reconnect generating magneto-hydrodynamic shocks that experience strong gradient acceleration in the sharply stratified photosphere/chromosphere region. Acoustic and fast magnetosonic branches of these waves lead to heating and/or jet formation due to cumulative effects (Tarbell et al., 1999). The Alfvén waves generated by post-reconnection processes have quite a restricted range of parameters for shock formation, but their frequency, determined by the reconnection rate, may be high enough (0.1–2.5 s^–1) to carry the energy into the corona. We also suggest that the primary energy source for the fast wind lies far below the coronal heights, and that the chromosphere and transition region flows and also radiative transient form the base of the fast wind. The continuous supply of emerging magnetic flux tubes provides a permanent energy production process capable of explaining the steady character of the fast wind and its energetics.     

Parameter estimations of a storm surge model using a genetic algorithm

A genetic algorithm was used to optimize the parameters of the two-dimensional Storm Surge/Tide Operational Model (STORM) to improve sea level predictions of storm surges. The model was then tested using data from Typhoon Maemi, which landed on the Korean Peninsula in 2003. The following model parameters were used: the coefficients for bottom drag, background horizontal diffusivity, Smagorinsky’s horizontal viscosity, and sea level pressure scaling. The simulation results using the optimized parameters improved sea level predictions. This study demonstrates that parameter optimizations and their adequate applications are essential for improving model performance.     

Contamination of water and soil by the Erdenet copper–molybdenum mine in Mongolia

As one of the largest copper–molybdenum (Cu–Mo) mines in the world, the Erdenet Mine in Mongolia has been active since 1978 and is expected to continue operations for at least another 30 years. In this study, the potential impacts of mining activities on the soil and water environments have been evaluated. Water samples showed high concentrations of sulfate, calcium, magnesium, Mo, and arsenic, and high pH values in the order of high to low as follows: tailing water > Khangal River > groundwater. Statistical analysis and the δ²H and δ¹⁸O values of water samples indicate that the tailing water directly affects the stream water and indirectly affects groundwater through recharge processes. Soil and stream sediments are highly contaminated with Cu and Mo, which are major elements of ore minerals. Based on the contamination factor (CF), the pollution load index (PLI), and the degree of contamination (C_d), soil appears to be less contaminated than stream sediments. The soil particle size is similar to that of tailing materials, but stream sediments have much coarser particles, implying that the materials have different origins. Contamination levels in stream sediments display a tendency to decrease with distance from the mine, but no such changes are found in soil. Consequently, soil contamination by metals is attributable to wind-blown dusts from the tailing materials, and stream sediment contamination is caused by discharges from uncontained subgrade ore stock materials. Considering the evident impact on the soil and water environment, and the human health risk from the Erdenet Mine, measures to mitigate its environmental impact should be taken immediately including source control, the establishment of a systematic and continuous monitoring system, and a comprehensive risk assessment.     

Arsenic and metal contamination of water resources from mining wastes in Korea

 Water resources near a gold-mine waste site were studied for the distribution and contents of contaminants, and their behavior in the surface and groundwater systems. Arsenic, cadmium, and manganese were identified with levels exceeding the drinking water guidelines of WHO (World Health Organization), and their distribution depended upon the differences in source materials and in spatial pH variations. Originating from arsenopyrite, concentrations of dissolved arsenic were controlled by sorption with amorphous iron (Fe(OH)₃) and carbonate minerals. Cadmium and manganese were derived from the mineral phase including sphalerite (ZnS), otavite (CdCO₃), and rhodochrosite (MnCO₃); their concentrations in water resources were limited by the solubility of mineral phases. All of these processes are significantly pH-dependent, implying that a small decline in pH could result in a drastic increase in contaminant concentrations and become a pollution threat to the water resources of the Gubong area. Received: 13 December 1999 · Accepted: 21 March 2000