A Methodology For Design And Operation Of Heap Leaching Systems

Leaching is a hydrometallurgical activity widely used in mineral processing, both for metallic and non-metallic ores, and in soil remediation. The dissolution of valuable species by heap leaching is strongly dependent on the design and operating variables, so the study of the influence of these variables on recovery and their optimization for the best performance are attractive tasks for the development of the mining industry. In this work, a methodology is developed that enables the planning and design of leaching systems. This methodology uses a proposed superstructure and a mathematical model to analyze the system behavior and determine the optimal design and operating conditions. The model was generated with a Mixed Integer Nonlinear Programming (MINLP) approach and solved by different solvers under GAMS® software (General Algebraic Modelling System). The Spatial Branch-and-Bound (SBB) solver obtained the global optimum in the shortest times. Based on a case of study for copper leaching, it is demonstrated that the procedure allows achieving optimal design and operational conditions.     

Optimal Design of a Stable Trapezoidal Channel Section Using Hybrid Optimization Techniques

A cost effective channel section for a specified flow rate, roughness coefficients, longitudinal slope, and various cost parameters can be determined using an optimization technique. However, the derived optimal channel section may not be feasible for construction because of in situ conditions. The local soil conditions may not support the optimal side slope of the channel and if constructed, the slope may fail. It is therefore necessary to also incorporate the criteria for side slope stability in designing an optimal open channel section. In this paper, a new methodology has been developed to design a stable and optimal channel section using hybrid optimization techniques. A genetic algorithm based optimization model is developed initially to determine the factor of safety of a channel slope for given soil parameters. This optimization model is then externally linked with a separate sequential quadratic programming based optimization model to evaluate the parameters of the stable and optimal channel section. Solution for various example problems incorporating different soil parameters are illustrated to demonstrate the applicability of the developed methodology.     

Optimal Layout of Sewer Systems: A Deterministic versus a Stochastic Model

The optimization of a new or partially existing urban drainage system may be modeled as a subproblems sequence of layout and optimal design within the discrete search space. The design optimization, incorporating the optimal selection of the pumping stations, intermediate manholes, pipe sections, and installation depths, for a general system fixed layout in plan, is a high level sequential decision problem which may be efficiently solved deterministically through a multilevel dynamic programming model. The optimal general layout may be selected in a deterministic way by means of a simple economical comparison of all plan solutions having optimized designs, for small to medium sized systems (if the specific restrictions of the applications are appropriately exploited) in practicable computer time. For larger dimension networks, where it is clearly impossible to achieve plan optimization with full enumeration (which is a NP complete), stochastic search models can be used. For the subproblem layout, an effective enumeration model is presented; the results of a stochastic model proposed previously, using simulated annealing for an application example, are compared and discussed in detail.     

KB-GA-Based Hybrid System for Layout Planning of Multistory Buildings

Layout planning of multistory buildings requires multidisciplinary participation in the decision-making process, which is governed by intuition, creativity, and experience of the designers, and available information. Optimization techniques are rarely applied to the layout planning stage. The present study aims at a hybrid approach by combining knowledge based system and a genetic algorithm (GA)-based optimization technique by employing them for suitable tasks, in order to take specific advantages of respective techniques, i.e., the domain dependent part is isolated and developed as a knowledge-based (KB) system, while the knowledge lean part is handled by the adaptive search techniques. The main issue to be addressed while developing an integrated system is to identify the role of individual approaches and the interactions among them. This paper outlines this concept through an integrated hybrid system GALOP for optimal layout planning of multistory office buildings. A multiobjective GA-based optimization technique produces a set of optimal solutions, from which a designer can select the final design.     

Optimum Concrete Mixture Proportion Based on a Database Considering Regional Characteristics

This paper presents an enhanced design methodology for optimal mixture proportion of concrete composition with respect to accuracy in the case of using prediction models based on a limited database. In proposed methodology, the search space is constrained as the domain defined by a limited database instead of constructing the database covering the region represented by the possible ranges of all variables in the input space. A model for defining the search space which is expressed by the effective region in this paper and evaluating whether a mix proportion is effective is added to the optimization process, yielding highly reliable results. To demonstrate the proposed methodology, a genetic algorithm, an artificial neural network, and a convex hull were adopted as an optimum technique, a prediction model for material properties, and an evaluation model for the effective region, respectively. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix proportion obtained from the proposed methodology considering the regional characteristics of the database is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.     

Overtopping Probability Constrained Optimal Design of Composite Channels Using Swarm Intelligence Technique

In this paper swarm intelligence based methodology is proposed for optimal and reliable design of irrigation channels. The input parameters involved in channel design are prone to uncertainty and the solution of deterministic model may result in flooding risk and affect the stability of the channel. To provide reliability in the design, an overtopping probability constrained design is presented in this study. The deterministic equivalent of the probabilistic constraint is derived by following the principle of first order uncertainty analysis. In order to account for the uncertainty of design parameters in the objective function, a modified cost function is proposed. A methodology is propounded to solve it in a metaheuristic environment and solved it using elitist-mutated particle swarm optimization (EMPSO) method. The EMPSO based solutions are found to be quite successful and better than the classical optimization methods. Finally, it is concluded that the proposed methodology has a good potential for reliable design of composite channels for designer specified reliability values.     

Optimization of Watershed Control Strategies for Reservoir Eutrophication Management

A vital key to the development of a reservoir eutrophication management strategy is to link the watershed-nutrient model to the model of reservoir water quality. To develop a cost-effective optimization model, a coupled watershed-reservoir model with an optimization model has been developed to design control strategies in the watershed in a planning time horizon. This methodology can help reduce the phosphorus concentration of a reservoir to the standard level. In this study, the weather data for the next 10 years was generated using downscaled GCM data to simulate the watershed phosphorus load using the SWAT model. Then an optimal model for selection and placement of best management practices (BMP) at watershed scale is developed by linking the coupled watershed and reservoir models with a genetic algorithm. This model is able to identify the minimum present cost design (type and location) of BMP structural alternatives. The objective of water quality is obtained using a system dynamic model for reservoir phosphorus concentration to determine a permissible phosphorus load as the main agent of eutrophication in a reservoir. Structural BMPs in this study include, filter strips, parallel terraces, grade stabilization structures, and detention ponds. The optimum solution was obtained through a trade-off curve between cost and exceedance magnitude from the standard of reservoir phosphorus concentration. The case study is the Aharchai River Watershed upstream of the Satarkhan Reservoir in the northwestern part of Iran.     

Decision Support System for Manufactured Housing Facility Layout

Productivity improvement of manufactured housing (MH) production systems has been a great concern to manufacturers and production managers. Studies show that a typical manufactured housing plant fails to produce at desired capacity and production rate because of several shortcomings. The evaluation of the production system efficiency in the factory is essential for meeting the growing demand of customers with respect to design and size of the housing product. It is imperative to explore alternative layout designs that would be more efficient and productive. A decision support system (DSS) is proposed to assist the user in selecting an efficient layout design matching specified requirements and business constraints. The DSS framework covers interrelated factors of: (1) the market demand; (2) MH organization; (3) MH production process; and (4) MH production planning and facility design. Existing MH factories can utilize simulation and optimization components of the DSS in streamlining their activities and locating then solving potential bottlenecks. Additionally, the DSS can be used in selecting optimal production system layout for new plant design.     

Optimal Layout Design of a Satellite Module Using a Coevolutionary Method with Heuristic Rules

The layout design of a satellite module belongs to a three-dimensional (3D) packing problem with mutual-conflicting performance constraints. Taking the layout design of a simplified commercial communication satellite as a background, based on the cooperative coevolutionary framework, this paper presents a coevolutionary method with heuristic rules for the optimal layout design of a satellite module. First, a whole satellite module layout problem is decomposed into several sublayout problems according to the multisubphysical structure of a satellite module. Second, a relaxation model is adopted to distribute all objects among subspaces. Third, a coevolutionary genetic algorithm is adopted to solve the detailed layout design within the subspaces. Finally, a heuristic combination-rotation (CR) method is adopted to adjust the constraints to obtain the final whole layout scheme. Compared with the coevolutionary approach and the all-at-once optimization approaches, computational results show that the CR method can improve the computational accuracy of solutions and the proposed heuristic coevolutionary method can produces better solutions within short running times.     

Optimal Construction Site Layout Considering Safety and Environmental Aspects

A good site layout is vital to ensure the safety of the working environment and effective and efficient operations. Site layout planning has significant impacts on productivity, costs, and duration of construction. Construction site layout planning involves identifying, sizing, and positioning temporary and permanent facilities within the boundary of the construction site. Site layout planning can be viewed as a complex optimization problem. Although construction site layout planning is a critical process, systematical analysis of this problem is always difficult because of the existence of a vast number of trades and interrelated planning constraints. The problem has been solved using two distinct approaches: Optimization techniques and heuristics methods. Mathematical optimization procedures have been developed to produce optimal solutions, but they are only applicable for small-size problems. Artificial intelligent techniques have been used practically to handle real-life problems. On the other hand, heuristic methods have been used to produce good but not optimal solutions for large problems. In this paper, an optimization model has been developed for solving the site layout planning problem considering safety and environmental issues and actual distance between facilities. Genetic algorithms are used as an optimization bed for the developed model. In order to validate the performance of the developed model, a real-life construction project was tested. The obtained results proved that satisfactory solutions were obtained.     

Reliability-Based Optimization Considering Manufacturing and Operational Uncertainties

This paper presents approaches for integrating multidisciplinary optimization and probabilistic methods to perform reliability-based multidisciplinary optimization. The approaches are built into a framework that allows solution of optimization problems, wherein system parameters including dimensional tolerances, material properties, boundary conditions, loads, and model predictions are uncertain or variable. This approach directly supports quality engineering because it allows engineers to specify manufacturing tolerances required to achieve the desired product reliability, and it results in robust designs that are optimal over the range of variable conditions because it considers uncertainties during the optimization process. The basic reliability-based multidisciplinary optimization methodology has been demonstrated to design engine components, aircraft lap joints, and transport aircraft wings. Herein this methodology is reviewed and then the focus is on demonstrating a new framework that makes it possible to use these methods with commercial CAD∕CAE tools and support commercial shape parameterization to enable shape optimization and consideration of manufacturing uncertainties.     

Layout Design of Irrigation Networks in Highly Parcelled Territories Using Geographical Information System

Traditional irrigation zones in the east of Spain have been denoted by the high level of parcellation. The layout of the irrigation network design in highly parcelled territories presents an important degree of difficulty, the previous experience of the designer in this task being crucial in the final result. In this work, a new heuristic algorithm for layout of the irrigation network design is presented. We start from a classical graph theory algorithm (Dijkstra’s algorithm) used for solving the shortest path spanning tree problem. This algorithm is modified to assign weights to the arcs and plot limits are used as if they were the arcs of a graph. The algorithm is implemented on a geographical information system, thus creating an application that automatically generates the layout of the irrigation network design. The only necessary initial data are the origin of the network (supply point) and the hydrants (delivery points). The advantage of this heuristic is that the subjectivity introduced for the designer is removed. Moreover, it allows for solving complex problems, and therefore it is applicable to highly parcelled zones, where the number of vertices and edges is so high that it would inhibit calculating capacity of any optimization process. A practical example is presented, in which the layout design obtained by applying the heuristic is compared with the original existing layout.     

Experimental Validation of Lagrange-Rayleigh-Ritz Modeling Technique for Mass Loaded Actively Controlled Panels

This paper describes the validation of a Lagrange-Rayleigh-Ritz technique for the mathematical modeling of mass loaded panels for active control studies. The validation has been carried out by comparing the results produced by a Lagrange-Rayleigh-Ritz model with the results produced by a finite-element model and experimental data. Attention was focussed on a simply supported panel with a lumped mass constrained to its surface to simulate the presence of equipment mounted on the panel and twin piezoelectric patches bonded to the panel, working as sensors and actuators. The design of the experimental rig is described in detail, and a test campaign was carried out to obtain a set of transfer functions characteristic of this plant. The experimental data are then used to validate the predictions of the mathematical model. In particular, it was demonstrated that the Lagrange-Rayleigh-Ritz model was able to reproduce accurately the dynamics of the plant requiring a relatively small number of degrees of freedom.     

Optimal Design of Pressurized Irrigation Subunit

A linear programming (LP) model is presented for optimal design of the pressurized irrigation system subunit. The objective function of the LP is to minimize the equivalent annual fixed cost of pipe network of the irrigation system and its annual operating energy cost. The hydraulic characteristics in the irrigation subunit are ensured by using the length, energy conservation, and pressure head constraints. The input data are the system layout, segment-wise cost and hydraulic gradients in all the alternative pipe diameters, and energy cost per unit head of pumping water through the pipeline network. The output data are: segment-wise lengths of different diameters, operating inlet pressure head, and equivalent annual cost of the pipeline network. The explicit optimal design is demonstrated with design examples on lateral and submain or manifold of pressurized irrigation systems. The effect of the equations for friction head loss calculation on optimization procedure is investigated through the design example for microirrigation manifold. The performance evaluation of the proposed model in comparison with the analytical methods, graphical methods, numerical solutions, and dynamic programming optimization model reveals the good performance of the proposed model. The verification of operating inlet pressure head obtained by the proposed model with accurate numerical step-by-step method suggested that it is mostly accurate.     

Particle Swarm Optimization for Construction Site Unequal-Area Layout

Layout of temporary facilities on a construction site is essential to enhancing productivity and safety, and is a complex issue due to the unique nature of construction. This paper proposes a particle swarm optimization (PSO)-based methodology to solve the construction site unequal-area facility layout problem. A priority-based particle representation of the candidate solutions to the layout problem is proposed. The particle-represented solution in terms of priorities should be transformed to the specific layout plan with consideration of nonoverlap and geometric constraints. In addition, a modified solution space boundary handling approach is proposed for controlling particle updating with regard to the priority value range. Computational experiments are carried out to justify the efficiency of the proposed method and investigate its underlying performances. This study aims at providing an alternative and effective means for solving the construction site unequal-area layout problem by utilizing the PSO algorithm.     

Methodology to Assess Building Designs for Protection against Internal Chemical and Biological Threats

Recent world events involving chemical and biological (CB) attacks within critical infrastructure have highlighted a potential threat to buildings and their occupants. As a result, protecting buildings from CB attacks has become an important design consideration. A methodology has been developed to provide decision makers with the ability to assess multiple building designs for protection against an internal CB release. This methodology includes modeling and simulation of CB contaminant dispersion, a quantitative means to calculate a building’s protection level, and a weighted sum, multiple objective optimization for design selection. This paper outlines the phases in the methodology, and focuses on the application of multizone modeling and optimization techniques to compare design alternatives. The assessment of design options for CB protection in a hospital emergency room is used as an illustrative example. Optimal design options are determined based on the weighted combination functions for the building’s protection level, initial capital costs, and ongoing operations and maintenance costs.     

New Mathematical Optimization Model for Construction Site Layout

Layout of temporary construction facilities (objects) is an important activity during the planning process of construction projects. The construction area layout is a complex problem whose solution requires the use of analytical models. Existing popular models employ genetic algorithms that have proven to be useful tools in generating near optimal site layouts. This paper presents an alternative approach based on mathematical optimization that offers several important features and generates a global optimal solution. The construction area consists of an unavailable area that includes existing facilities (sites) and available area in which the objects can be located. The available area is divided into regions that are formulated using binary variables. The locations of the objects are determined by optimizing an objective function subject to a variety of physical and functional constraints. The objective function minimizes the total weighted distance between the objects and the sites as well as among the objects (if desired). The distance can be expressed as Euclidean or Manhattan distance. Constraints that ensure objects do not overlap are developed. The new approach, which considers a continuous space in locating the objects simultaneously, offers such capabilities as accommodating object adjacency constraints, facility proximity constraints, object–region constraints, flexible orientation of objects, visibility constraints, and nonrectangular objects, regions, and construction areas. Application of the model is illustrated using two examples involving single and multiple objects. The proposed model is efficient and easy to apply, and as such should be of interest to construction engineers and practitioners.     

Particle Swarm Optimization-Supported Simulation for Construction Operations

This study proposes an integration of particle swarm optimization (PSO) and a construction simulation so as to determine efficiently the optimal resource combination for a construction operation. The particle-flying mechanism is utilized to guide the search process for the PSO-supported simulation optimization. A statistics method, i.e., multiple-comparison procedure, is adopted to compare the random output performances resulting from the stochastic simulation model so as to rank the alternatives (i.e., particle-represented resource combinations) during the search process. The indifference zone and confidence interval facilitate consideration of the secondary performance measure (e.g., productivity) when the main performance measures (e.g., cost) of the competing alternatives are close. The experimental analyses demonstrate the effectiveness and efficiency of the proposed simulation optimization. The study aims to providing an alternative combination of optimization methodology and general construction simulation by utilizing PSO and a statistics method so as to improve the efficiency of simulation in planning construction operations.     

Decarburization of stainless steel: Part II. A mathematical model and a process optimization for industrial scale systems

A mathematical model is presented for describing the bath temperature and composition trajectories for the decarburization of stainless steel for processes operating on an indus-trial scale. The model is based on a set of component balances, written with the aid of driving force expressions, the appropriate equilibrium relationships and the heat balance. The resultant set of ordinary differential equations were solved numerically. The predic-tions based on the model were compared with experimentally measured bath composition and temperature paths obtained for the operation of a 40 ton electric furnace. The predic-tions and measurements showed very good agreement. The mathematical model was then combined with a trajectory optimization technique to compute the optimal blowing programi .e., oxygen-argon content of the gas supplied) such that the total cost of the operation is minimized. This calculation was repeated for a series of cost factors. On leave from Department of Iron and Steel Engineering, Nagoya University, Nagoya, Japan