Environmental decision-making under uncertainty using intuitionistic fuzzy analytic hierarchy process (IF-AHP)

Analytic hierarchy process (AHP) is a utility theory based decision-making technique, which works on a premise that the decision-making of complex problems can be handled by structuring them into simple and comprehensible hierarchical structures. However, AHP involves human subjective evaluation, which introduces vagueness that necessitates the use of decision-making under uncertainty. The vagueness is commonly handled through fuzzy sets theory, by assigning degree of membership. But, the environmental decision-making problem becomes more involved if there is an uncertainty in assigning the membership function (or degree of belief) to fuzzy pairwise comparisons, which is referred to as ambiguity (non-specificity). In this paper, the concept of intuitionistic fuzzy set is applied to AHP, called IF-AHP to handle both vagueness and ambiguity related uncertainties in the environmental decision-making process. The proposed IF-AHP methodology is demonstrated with an illustrative example to select best drilling fluid (mud) for drilling operations under multiple environmental criteria.     

Evaluation of Probe-Induced Flow Distortion of Campbell CSAT3 Sonic Anemometers by Numerical Simulation

The Campbell CSAT3 sonic anemometer is one of the most popular instruments for turbulence measurements in basic micrometeorological research and ecological applications. While measurement uncertainty has been characterized by field experiments and wind-tunnel studies in the past, there are conflicting estimates, which motivated us to conduct a numerical experiment using large-eddy simulation to evaluate the probe-induced flow distortion of the CSAT3 anemometer under controlled conditions, and with exact knowledge of the undisturbed flow. As opposed to wind-tunnel studies, we imposed oscillations in both the vertical and horizontal velocity components at the distinct frequencies and amplitudes found in typical turbulence spectra in the surface layer. The resulting flow-distortion errors for the standard deviations of the vertical velocity component range from 3 to 7%, and from 1 to 3% for the horizontal velocity component, depending on the azimuth angle. The magnitude of these errors is almost independent of the frequency of wind speed fluctuations, provided the amplitude is typical for surface-layer turbulence. A comparison of the corrections for transducer shadowing proposed by both Kaimal et al. (Proc Dyn Flow Conf, 551–565, 1978) and Horst et al. (Boundary-Layer Meteorol 155:371–395, 2015) show that both methods compensate for a larger part of the observed error, but do not sufficiently account for the azimuth dependency. Further numerical simulations could be conducted in the future to characterize the flow distortion induced by other existing types of sonic anemometers for the purposes of optimizing their geometry.     

Acute ecological risk associated with soot deposition: a Persian Gulf case study

Many studies have been carried out in the past to provide solutions to the threat of chemicals to the ecosystem. However, the basic scientific capability to predict the risk of adverse effects on the ecological system has not kept pace with society's increasing demand for uses of chemicals. As a scientific methodology for quantifying the risk to the environment associated with exposure to chemicals, ecological risk assessment is increasingly important in environmental problem solving. The purpose of this paper is to present a methodology for conducting ecological risk assessment using deterministic and probabilistic approaches. A systematic discussion on elements of ecological risk assessment is presented. A framework of ecological risk assessment is explained with the help of the Persian Gulf environmental problem as a case study. The study was based on the output of a long-range transport model of soot deposition in the Gulf. Results of the assessment using the deterministic and probabilistic approaches are discussed.     

Investigation of landslides with natural lineaments derived from integrated manual and automatic techniques applied on geospatial data

Lineament extraction has long been performed through extensive field mapping. Recent advances in the field of remote sensing have made possible the availability of imageries from earth observation satellites with different Spatio-temporal resolutions, paving way for new automatic, semi-automatic, and manual techniques for the extraction of natural lineaments. The study focuses on the extraction of lineaments representing tectonic fault zones; the lineaments are extracted automatically and semi-automatically/manually. Results show that indirect information about the tectonic lineaments can be derived through automatic techniques whereas, the semi-automatic techniques are more effective to directly identify them. Detailed analyses of lineaments and landslides revealed that areas near lineaments, in general, experienced higher frequency of landslides. Moreover, it is also observed that lineaments are not the only factor that affects landslide density; other parameters like slope and lithology were also found to be the controlling factors in determining the spatial landslide distribution. Lastly, some recommendations have been made based on observations.

     

Exact anisotropic polytropic cylindrical solutions

In this paper, we study anisotropic compact stars with static cylindrically symmetric anisotropic matter distribution satisfying polytropic equation of state. We formulate the field equations as well as the corresponding mass function for the particular form of gravitational potential \(z(x)=(1+bx)^{\eta }~(\eta =1,~2,~3)\) and explore exact solutions of the field equations for different values of the polytropic index. The values of arbitrary constants are determined by taking mass and radius of compact star (Her X-1). We find that resulting solutions show viable behavior of physical parameters (density, radial as well as tangential pressure, anisotropy) and satisfy the stability condition. It is concluded that physically acceptable solutions exist only for \(\eta =1,~2\).     

Communicating human health risks associated with disinfection by-products in drinking water supplies: a fuzzy-based approach

Chlorine used for the disinfection of water supplies can react with naturally occurring organic compounds and form potentially harmful disinfection by-products (DBPs). A risk index for two regulated groups of chlorinated DBPs—trihalomethanes (THMs) and haloacetic acids (HAAs), using fuzzy C-means (FCM) clustering algorithm and fuzzy rule-based modeling is proposed for risk communication. The proposed index evaluates the cancer and non-cancer risks individually for THMs and HAAs using the FCM algorithm. Subsequently, two different fuzzy rule-bases were used to evaluate the overall risk-index based on cancer and non-cancer risks. The overall risk-index will provide drinking water utilities with an effective communication tool for communicating aggregated water quality compliance. Simulated DBP occurrence data obtained from the City of Quebec, Canada, is used to demonstrate the application of this methodology.     

Use of neural networks for the prediction of frictional drag and transmission of axial load in horizontal wellbores

The use of mud motors and other tools to accomplish forward motion of the bit in extended reach and horizontal wells allows avoiding large amounts of torque caused by rotation of the whole drill string. The forward motion of the drill string, however, is resisted by excessive amount of friction. In the presence of large compressive axial loads, the drill pipe or coiled tubing tends to buckle into a helix in horizontal boreholes. This causes additional frictional drag resisting the transmission of axial load (resulting from surface slack‐off force) to the bit. As the magnitude of the frictional drag increases, a buckled pipe may become ‘locked‐up’ making it almost impossible to drill further. In case of packers, the frictional drag may inhibit the transmission of set‐up load to the packer. A prior knowledge of the magnitude of frictional drag for a given axial load and radial clearance can help avoid lock‐up conditions and costly failure of the tubular. In this study a neural network model, for the prediction of frictional drag and axial load transmission in horizontal wellbores, is presented. Several neural network architectures were designed and tested to obtain the most accurate prediction. After cross‐validation of the Back Propagation Neural Network (BPNN) algorithm, a two‐hidden layer model was chosen for simultaneous prediction of frictional drag and axial load transmission. A comparison of results obtained from BPNN and General Regression Neural Network (GRNN) algorithms is also presented. Copyright © 2002 John Wiley & Sons, Ltd.     

Error minimization of polynomial approximation of Delta T

The difference between Universal time (UT) and Dynamical time (TD), known as Delta T (ΔT) is tabulated for the first day of each year in the Astronomical Almanac. During the last four centuries it is found that there are large differences between its values for two consecutive years. Polynomial approximations have been developed to obtain the values of ΔT for any time of a year for the period AD 1620 to AD 2000 (Meeu 2000) as no dynamical theories describe the variations in ΔT. In this work, a new set of polynomials for ΔT is obtained for the period AD 1620 to AD 2007 that is found to produce better results compared to previous attempts.