Investigation and modeling of unsaturated flow through swelling soils

Although the theory of water movement through an unsaturated, swelling soil has been developing for a number of years, the efficiency of the results has been limited, and the developed models have suffered from a lack of a mechanism to reliably define water flow and experimental techniques for measuring the unsaturated soil hydraulic properties. The intent of the present research is to elucidate and to investigate the theory of flow through unsaturated, swelling soil, to develop a three dimensional theoretical model based on a reliable soil swelling and unsaturated flow mechanism and, furthermore, to characterize the relationships between different soil hydraulic and swelling properties. In the first part, based on the water adsorption mechanism by the soil particles and the use of continuum theory principles, a theoretical model of unsaturated flow through swelling soil has been developed. Some new techniques were established to measure the different soil swelling and hydraulic properties and to analyze the effect of the soil's initial conditions. The reliability of the different existing empirical models, to be applied to the results obtained from hydraulics, shrinkage and swelling experiments, were investigated and modified where necessary. A static neural network model was developed to mathematically characterize the experimental results being used in the proposed numerical solution of the mathematical model. The neural network model works based on the back-propagation error method with adaptive learning rules by means of the neural network tool box of MATLAB software. A finite difference numerical model, based on a fully implicit method, was proposed to numerically solve the one dimensional governing equation (simplified form of 3D governing equation). For this part of the study, a computer program in C++ language was developed. Finally, the results of the numerical method were verified using the results obtained from infiltration tests. The tests were conducted for the semi-infinite soil columns having three different confinement conditions: completely confined, semi-confined and free swelling. The results show a clear agreement between the output of the developed numerical model and the experimental data. As one of the conclusions, the results of the numerical analysis of the developed mathematical model agreed reasonably well with those of the experiments. The study also indicated that the static neural network model, as one of the most promising models, can precisely characterize any experimental function related to the soil properties and cooperates with other numerical approaches such as finite difference method to solve a highly nonlinear partial differential equation such as unsaturated flow equatio

Development a Conceptual Framework for Industrial and Hazardous Wastes Rating Systems

Production of a large volume of industrial and hazardous waste with various compositions makes the need for comprehensive management and consequently the concept of waste rating more tangible. Despite numerous waste rating systems presented so far, analyzing the makeup of such systems play a significant role in meeting human health. In this study, the structure of 34 rating systems of industrial and hazardous waste have been analyzed based on both quantitative and qualitative standpoints and the results are presented as a formational-conceptual framework. Results showed that every rating system is formed of two parts of formational fundamentals and functional indices, which the first part has a longitudinal relation with the second. While lowly considered, this study is focusing on the formational fundamental part in the rating systems of industrial and hazardous waste, as intellectual prerequisites in suggesting a new system. Some of the factors in the first level are: dependence of the organization which determines the policy and general goals of a rating system, time of presenting the method during which remarkable changes take place in computing methods of the rating systems, infrastructures and facilities which are efficient in the accuracy and scope of the system and finally references and standards causing variations in definitions and final results of the rating system. Furthermore, factors such as: aspects of the study and style of use are identified in second level of formational fundamentals. Finally, the fundamentals are presented in a formational-conceptual framework for better perceiving and more effective use

Industrial Wastes Risk Ranking with TOPSIS, Multi Criteria Decision Making Method

Today, various types of industrial waste are produced in different industries to meet human demands. Growth in quantity as well as complication in quality of these wastes are followed by the advance of technology. Management of such wastes need a proper identification and comprehensive understanding of the risk, emerging after the harmful characteristics of the wastes and negatively affect the human and environment health. Wastes risk ranking systems, in this regard, links between the industrial wastes indices and mathematical method/algorithm, being able at estimation of the risk level as well as comparison between the wastes of an industrial unit based on the risk level. Complexity of the method, high computational costs and lack of proper description of waste using selected indices in former studies has led to the proposal of an applicable and flexible method. In this study, the “TOPSIS Multi-Criteria Decision-Making (MCDM) method” was developed in order for ranking the risk of various industrial wastes. Totally, a number of 9 subsidiary indices on the human health and 11 subsidiary indices on the environment health was identified and employed. Finally, the proposed waste risk ranking system was used for ranking 9 types of identified industrial waste in three industrial section. Results show that the “TOPSIS MCDM”, due to the lack of complexities in method and limited computational costs, is an efficient and appropriate method for ranking industrial wastes

RETRACTED: Shear Strength Behavior of Crude Oil Contaminated Sand-Concrete Interface

This article has been retracted: please see Civil Engineering Journal policies: (https://www.civilejournal.org/index.php/cej/about/editorialPolicies).This article has been retracted at the request of the Editor-in-Chief. It has come to our attention that there is significant duplication of text and content between this Civil Engineering Journal article and other paper by the same authors, "Shear Strength Behavior of Crude Oil Contaminated Sand-Concrete Interface" by Amir Hossein Mohammadi, Taghi Ebadi, Abolfazl Eslami, Geomechanics and Engineering (Techno Press) (Volume 12, Number 2, February 2017, pages 211-221) www.techno-press.org/content/?page=article&journal=gae&volume=12&num=2&ordernum=3. One of the conditions of submission of a paper for publication is that authors declare explicitly that the paper is not under consideration for publication elsewhere. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process

Analysis of Most Important Indices in Environmental Impacts Assessment of Ports

Ports are the main centers of economic activities and producers of environmental pollutions on the shores and urban areas. Regarding the growth of world trade, transportation of goods through the ports has been undergoing prompt development, possibly experiencing further progress in the upcoming years. In the recent years, the destructive impacts of ports on the environment has been increasing. The type of activities and interactions carried out in the ports have speeded up such destructions. The major sources of pollutions are usually air, noise, water, soil and garbage. The objective of this study is to identify the main and sub-indices in the assessment of environmental impacts of ports (EIAP). To this end, a number of 28 case studies over the world have been analyzed. The indices of the environmental impacts of ports are categorized and evaluated according to four scales: the application and study aspects, the time, the location, as well as the quantity of occurrence of the criteria. Totally 200 main and sub-indices have been identified, within which, the first 10 have been allocated to the pollution of air, noise, water, transportation, traffic, greenhouse gases, garbage, soil, climate change and dredging, since 2000 to 2016. Finally, to better understand the subject, the conceptual framework for EIAP is presented. This study provides with port managers guidance toward identifying significant environmental aspects of ports; it is, at the same time, applicable in order for awareness and prioritization in the environmental management

Effect of Bentonite Addition on Geotechnical Properties of Oil-Contaminated Sandy Soil

Oil and its derivatives not only change the chemical and biological properties of the soils, but also affect their geotechnical properties. Effects of oil contamination on a sandy soil which mixed with bentonite was assessed in terms of compaction, shear strength, and consolidation behavior. The experiments were carried out by polluting dry sandy soil with 2.5, 5, 7.5, 10% w/w crude oil at different bentonite contents (0, 5, 10, 15, 20% w/w). Results of compaction tests indicated that at a fixed bentonite content, with increasing crude oil content, the maximum dry density increases, while the optimum water content decreases. Similarly, at a fixed contaminant content, increasing the bentonite content in the soil leads to increase in soil maximum dry density and the optimum moisture content. Moreover, direct shear tests revealed that at a specific bentonite content, higher contamination concentration causes lower internal friction angle. The effect of oil content on the coefficient of consolidation (Cv) and void ratio of soils with 0, 5, 10, 15, and 20 percent bentonite contents was studied. The results of consolidation tests indicated that at a fixed bentonite content Cv has an overall increasing pattern which is in its maximum amount at 5% oil content

Multi-objective Optimal Model for Surface and Ground-water Conjunctive Use Management Using SGAs and NSGA-II

The widespread activities in water resources exploitation and use require sound research programs on planning and management of conjunctive use of surface and ground-water. Conjunctive management is a suitable approach for the imbalanced water resources distribution and related constraints in using surface water. In this paper, a multi-objective model is developed to maximize the minimum reliability of the system and to minimize the costs due to failure to supply water, aquifer storage, failure to cope with reservoir capacity, and prioritizing water allocations. The non-dominated sorting genetic algorithm (NSGA-II) is used to present the optimal trade-off between the objectives. The sequential genetic algorithm (SGA) is also applied in order to be compared with the NSGA-II model. The results show that the NSGA-II model can considerably reduce the computational cost of the conjunctive use models in comparison with the SGA optimization model. The obtained trade-off curve shows that a slight increase in reliability leads to much higher system costs. The weighted single objective SGA model results verify the optimal trade-off obtained from NSGA-II model and show the optimality of the allocated discharges

Development Structure for Optimal Long-Term Planning in Conjunctive Use

In the most of arid and semi-arid countries, the quality and quantity of available water resources play a significantly limiting role in development. In these regions, the conjunctive management is a suitable alternative that can lead to the optimal operation of available water resources. In this study, a conjunctive use model is developed in order to maximize water supply demands in 30-year period historical records. Discharge from resources, consumption priority in sectors and zones, inter-basin water conveyance plans and water demands are considered as the optimization model’s constraints. The ultimate goal of the study is to present short-term, medium-term and long-term operating policy. The sequential genetic algorithm is used to speed up the convergence to near global solution. The operating rules of surface and groundwater resources are separately developed for agriculture as well as domestic demands in the annual and monthly manner, respectively in the three above-mentioned periods. Finally, these rules are verified based on previously unused historical records. The results showed that the proposed model can effectively improve water resources potential, sustainable groundwater resources and undesirable use in agriculture sector

Development of a Smart Model for Groundwater Level Prediction Based on Aquifer Dynamic Conditions

In recent years, drought and demand growth in most parts of the county have caused a dramatic increase in using groundwater for water supply purposes. Besides, unplanned excessive discharges from aquifers have led to aquifer degradation. In most integrated water resources management models, groundwater simulation is used for taking into account discharge constrains, however, the most cases the optimal solution is not achievable.Hence, artificial neural network models may be replaced by groundwater numerical simulation models. In this paper, a methodology based on dynamic artificial neural networks (DANN) is developed for simulating groundwater table.Karajaquifer is used as the case study and its groundwater numerical model (PMWIN) is calibrated using such measured groundwater characteristics as hydraulic conductivity and specific storage. The results of the numerical model are presented to DANN for training. In the proposed procedure, the total recharge, discharge, and groundwater level in previous time intervals are used as the inputs to the DANN model. The model output is the groundwater level at the end of the time interval. In this study, the development of the model is accomplished in four steps that consist of developing the aquifer simulation model and its calibration, producing the input-output data set for DANN training, training the DANN model for various structures, and selecting the best structure for use in the optimization model. The result shows that the proposed DANN model is more efficient in simulating groundwater level fluctuations than the static artificial neural network (SANN) models

Conjunctive use Management under Uncertainty in Aquifer Parameters

Conjunctive use operation policies play a vital role in the sustainability of water resources and their optimal allocation. To be realistic conditions of real water resource system should be considered in simulation and derivation of operating rules of real-world water resource system. In this research, the combined fuzzy logic and direct search optimization technique is used to account for the uncertainty associated with parameters affecting groundwater table level fluctuations. These parameters include specific yields and inflow recharge and outflow discharge from the aquifer, which are typically uncertain. A membership function is determined for each parameter using hydrogeologic and piezometric data. For each membership value ( level cut), the corresponding intervals are determined. These intervals are considered as constraints on the membership value of the groundwater table level fluctuations in the optimization model. The process is repeated for other  level cuts to obtain the fuzzy number. For the uncertainty influencing the water demands, a conjunctive use model with water resources constraints is developed. Using this model, the priorities for the different zones and their optimal allocations are determined. The results show that the better the real conditions are reflected in the conjunctive use model, the better will the system be reliably capable of handling the water demands. The results of the proposed model also indicate that it present reliable allocations compared to the static conventional models and that it performs more desirably and practically in allocating supplies to water demands as it duly includes the opinions of the decision-makers involved