Random Characteristics of Hydraulic Gradient through Three-Dimensional Multilayer Embankment

The distribution characteristics of hydraulic gradient in embankment are closely related to seepage failure. Seepage failures such as flowing soil and piping will lead to serious damage and even the overall failure of embankment. The hydraulic conductivity has strong spatial variability, which changes the distribution of hydraulic gradient in embankment and increases the difficulty for predicting the embankment seepage instability. In this study, the distribution of soil hydraulic conductivity in a section of Shijiu Lake embankment was obtained by the permeability test. Based on Local Average Subdivision technique, a three-dimensional multilayer random field of embankment hydraulic conductivity was generated. Then, the mean and standard deviation of overflow point height and hydraulic gradient were calculated by the Monte Carlo method, which combined the generated three-dimensional random model and the deterministic analysis method of seepage field. Finally, the coefficient of variation (COV) of hydraulic conductivity (0.1, 0.3, 0.5, 0.7, 1.0, 2.0, and 3.0), the fluctuation scale in vertical direction (3 m) and the fluctuation scale in horizontal plane (3 m, 6 m, 12 m, 24 m, 36 m, and 48 m) were selected respectively for analyzing the random characteristics of embankment overflow point height and hydraulic gradient under the influence of different COV and fluctuation scale of embankment soil hydraulic conductivity.

A Simplified Methodology for Rapidly Analyzing the Effect of Multi-Hazard Scenario on Atmospheric Storage Tanks

Natural hazard events that trigger technical emergencies (Natech events), as a typical type of multi-hazard, have become a matter of growing concern. In particular, the occurrence of Natech events in industrial areas triggered a number of severe accidents. The present research aims at introducing a sound but simplified methodology to quickly and flexibly assess the vulnerability of atmospheric storage tanks to multiple natural disasters in Natech events. This method consists of 8 steps, relying on the simplified physical models of tank damage caused by natural disasters. The models of wind overturning tank and tank buckling caused by hail are proposed. In addition, the assessment process of tank vulnerability is demonstrated from two aspects: deterministic analysis and probabilistic analysis. The uncertain parameter set (UPS) proposed in the method and the Monte Carlo simulation method can help to purposefully analyze the impact of various parameters and this method is also a general method, which is also applicable to Natech events including other natural disasters or other types of storage tanks.

A Deterministic Analysis of the Effectiveness of Non-Clinical Approaches in the Control of Transimission of Schistosomiasis: Case Study of Mwea Irrigation Scheme, Kenya

Schistosomiasis commonly known as bilharzia is regarded by W.H.O as a neglected tropical disease. It affects the intestines and the urinary system preferentially, but can harm other systems in the body. The disease is a health concern among majority of the population in Mwea irrigation scheme in Kenya and indeed other tropical countries. This paper documents a deterministic analysis of the effectiveness of non-clinical approaches in the control of transmission of schistosomiasis in the region. A SIR based mathematical model that incorporates media campaigns as a control strategy of reducing transmission of the disease is used. The model considers behavior patterns of hosts as the main process of transmission of the disease. The dynamics of these processes is expressed in terms of ordinary differential equations deduced from the human behavior patterns that contribute to the spread of the disease. The reproduction number R0 and equilibrium points both DFE and EE are obtained. The stabilities of these equilibrium points are analyzed in reference to the reproduction number (R0). Secondary data is used in the mathematical model developed and in the prediction of the dynamics estimated in the model for a period of five years. Numerical simulation was carried out and results represented graphically. The results of the simulation show that the infection decreased from 75108 to about 35000 and the susceptible from 325142 to 50000 respectively in a period of five years. From the analysis, the DFE point is asymptotically stable when R_0<1.Sensitivity analysis of parameters was carried out using partial differentiation. The results show that the sensitivity index of most parameters are inversely proportional to R0 which will reduce schistosomiasis infection. From the results, incorporation of media campaigns as a control strategy significantly reduces transmission of the disease. The results will be useful to MOH to enhance media campaigns to prevent spread of schistosomiasis in Mwea Irrigation scheme and other endemic areas.

Probabilistic and deterministic analysis of single diode model of a solar cell: a case study

The paper presents a probabilistic and deterministic analysis for parameterization of solar cells to study the electrical behavior based on single diode model. Estimation of electrical parameters is important in design, control, and delivery of solar power through a solar cell. Due to non-linearity and non-convexity of the parameterization problem, the single objective function is transformed into set of sub-problems through Pascoletti–Serafini Scalarization using ε -constraint method. Thus, each sub-problem is minimized to obtain a unique set of points on Pareto front. The results are compared with multi-variable Newton Raphson (NR), Particle Swarm Optimization (PSO), and Black Widow Optimization (BWO) based on convergence accuracy, precision and ability to trace non-convex region. Solarex MSX83 (36 cells) is considered as the test case for the validation of deterministic optimization models under Standard test Conditions (STCs). Electrical characteristics are plotted under STC (1000 W/m2, 1.5 A.M. spectrum, 25 °C) which shows fair agreement with the actual experimental curves present in the datasheet. The results obtained from the proposed bi-objective minimization algorithm shows a better convergence response with an additional benefit of tracing the convexity of the problem. Moreover, the proposed technique also ensures a good fit as suggested by the statistical means. Finally, a probabilistic model is proposed for single diode model of a solar cell in the presence of parametric uncertainty. Random samples of uncertain electrical parameters are obtained using Latin hypercube and Monte Carlo sampling methods to estimate the probability of the output response. It can be concluded that the objective function shows a bi-modal distribution under parametric variations which may arise due to measurement error, shading losses, surface defects, and manufacturing issues.

Genetic load and extinction in peripheral populations: the roles of migration, drift and demographic stochasticity

We analyse how migration from a large mainland influences genetic load and population numbers on an island, in a scenario where fitness-affecting variants are unconditionally deleterious, and where numbers declines with increasing load. Our analysis shows that migration can have qualitatively different effects, depending on the total mutation target and fitness effects of deleterious variants. In particular, we find that populations exhibit a genetic Allee effect across a wide range of parameter combinations, when variants are partially recessive, cycling between low-load (large-population) and high-load (sink) states. Migration further reduces load in the sink state (by increasing heterozygosity) but increases load in the large-population state (by hindering purging). We identify various critical parameter thresholds at which one or other stable state collapses, and discuss how these thresholds are influenced by the genetic vs. demographic effects of migration. Our analysis is based on a 'semi-deterministic' analysis, which accounts for genetic drift but neglects demographic stochasticity. We also compare against simulations which account for both demographic stochasticity and drift. Our results clarify the importance of gene flow as a key determinant of extinction risk in peripheral populations, even in the absence of ecological gradients.

ANN-MATOPT hybrid algorithm: determination of kinetic and non-kinetic parameters in different reaction mechanisms

In this work we have applied the computational methodology based on Artificial Neural Networks (ANN) to the kinetic study of distinct reaction mechanisms to determine different types of parameters. Moreover, the problems of ambiguity or equivalence are analyzed in the set of parameters to determine in different kinetic systems when these parameters are from different natures. The ambiguity in the set of parameters show the possibility of existence of two possible set of parameter values that fit the experimental data. The deterministic analysis is applied to know beforehand if this problem occurs when rate constants of the different stages of the mechanism and the molar absorption coefficients of the species participating in the reaction are obtained together. Through the deterministic analysis we will analyze if a system is identifiable (unique solution or finite number of solutions) or if it is non-identifiable if it possesses infinite solutions. The determination of parameters of different nature can also present problems due to the different magnitude order, so we must analyze in each case the necessity to apply a second method to improve the values obtained through ANN. If necessary, an optimization mathematical method for improving the values of the parameters obtained with ANN will be used. The complete process, ANN and mathematical optimizations constitutes a hybrid algorithm ANN-MATOPT. The procedure will be applied first for the treatment of synthetic data with the purpose of checking the applicability of the method and after, it will be used in the case of experimental kinetic data.

Oil recovery enhancement by reservoir hydraulic compression technique employment

Industrial experiment works (IEW) were carried out to study the mechanism of filtration and reservoir properties changes (FRP) in the process of wells swabbing. Based on the hydrodynamic studies, the results of the works are analyzed. A method for oil production enhancing by reservoirs hydraulic compression has been worked out. In the process of well swabbing the barograms were recorded, pressure recovery curves were taken with the determination of hydraulic conductivity and piezoconductivity values, potential productivity coefficients, well flow rate, reservoir pressure before and after exposure. The interpretation of hydrodynamic studies was carried out by the deterministic analysis with subsequent modeling of the situation. The reservoir, opened by the perforation interval, is of complex structure, as a result of which the liquid was absorbed by the interlayer located above the area with newly formed microcracks. Keywords: hard-to-recover reserves; swabbing; carbonate reservoirs; filtration reservoir properties; pressure recovery curve.

Application of the wavelet transform in filtering the noise of real earthquake accelerograms

In the deterministic analysis of building structures, real accelerograms are used as input data. Very often, only instrumental recordings of accelerograms that are not cleared of noise are publicly available. Such accelerograms cannot be used directly in the analysis of building structures. Various broadband filters are used to adjust the instrumental recordings of accelerographs. This article discusses the possibility of applying filters based on the wavelet transform. The technique of the algorithm of filtering from the noise of the source data is considered. As an efficiency of this filtering algorithm, a comparative analysis of the dynamic coefficient and the energy criteria of the pulse and Arias for the corrected and instrumental accelerograms is carried out.