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This paper considers the design of an input signal for minimizing the time and energy required to detect and isolate faults in the outputs of a system. Faults are represented by discrete switches between affine models with bounded disturbances and bounded measurement errors. Within this framework, previous work has demonstrated that a minimally harmful input guaranteeing fault diagnosis can be obtained by solving a Mixed Integer Quadratic Program (MIQP). A closed-loop approach allows to reduce the length and/or norm of this input by solving an MIQP at each time instant with the newly available measurements. However, solving such programs online can be computationally demanding. In this paper, we employ multi-parametric (mp) programming to move most of the computation offline, thus allowing the application of the closed-loop approach to fast processes. Still, the mp-MIQP complexity becomes quickly prohibitive as the number of faulty models increases. In order to overcome this problem, we propose a strategy based on mp-optimization and graph theory that takes into account only two models at a time. While this approach is suboptimal compared to the case in which all the models are considered simultaneously, simulations show that, in practice, the performance is comparable. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents new definitions for process intensification identifying two main categories called unit intensification and plant intensification. This paper also proposes general mathematical programming formulations for the different categories of intensification through a disjunctive formulation to consider the use of existing units or to include additional units. The ideas of process integration (energy, mass and property integration) are very useful for process intensification helping in maximizing throughput for a given process, minimizing process inventory for a given throughput or in minimizing utilities and feedstock for a given throughput (this means that process intensification is broader than process integration). This paper identifies that process intensification is a wider approach than single unit intensification as it was considered by most of the previous works. A case study is presented to show the applicability of the proposed models and definitions. [Copyright &y& Elsevier]

Abstract Inter-plant hydrogen network with reuse/recycle optimization is important for saving hydrogen resource. Thus, it's necessary to optimize the inter-plant hydrogen network. In this paper, a novel two-step method that combines the pinch insight with mathematical programming is developed to optimize the inter-plant hydrogen network with purification reuse/recycle. A new transhipment model for targeting inter-plant hydrogen network is built to target the hydrogen utility consumption for each refinery. After the hydrogen consumption is determined, individual plant hydrogen networks are designed separately. The mathematical model is linear to guarantee global optimal solution. Furthermore, the model can also optimize the number of inter-plant connections of the hydrogen network. Case study indicates the effectiveness of model. Highlights • A two-step method to target and design inter-plant hydrogen network with purification reuse/recycle is proposed. • The hydrogen utilities for inter-plant network can be reduced further by inter-plant streams. • The number of inter-plant connections can be optimized. [ABSTRACT FROM AUTHOR]

Safety and performance are important factors in the design and operation of chemical plants. This paper describes the formulation of a mixed integer nonlinear programming model for the optimization of plant layout with safety considerations. The model considers a quantitative risk analysis to take safety into account, and a bowtie analysis is used to identify possible catastrophic outcomes. These effects are quantified through consequence analyses and probit models. The model allows the location of facilities at any available point, an advantage over grid-based models. Two case studies are solved to show the applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

Abstract: The optimal placement of turbines in a wind farm is critical to the maximization of power production. In this paper, we develop a new mathematical programming approach for wind farm layout optimization. We use Jensen's wake decay model to represent multi-turbine wake effects. We develop mixed integer linear and quadratic optimization formulations and apply them to several example layout cases in the literature. Compared to previous approaches, our models produce layouts that tend to be more symmetric and that generate slightly more power. Our formulations solve quickly, allowing a decision maker to efficiently explore the impact of different turbine densities in a wind farm. [Copyright &y& Elsevier]

Abstract: This paper presents a disjunctive mathematical model for the optimal design of air cooled heat exchangers. The model involves seven discrete decisions which are related to the selection of the type of the finned tube, number of tube rows, number of tube per row, number of passes, fins per unit length, mean fin thickness and the type of the flow regime. Each discrete decision is modeled using disjunctions, boolean variables and logical propositions. The main continuous decisions are: fan diameter, bundle width, tube length, pressure drops and velocities in both sides of the ACHE, heat transfer area, fan power consumption. Then, the resulting generalized disjunctive programming model is reformulated as a mixed integer non-linear programming, implemented in GAMS (general algebraic modeling system) and solved using a branch-and-bound method. The proposed model was successfully verified by comparing the obtained output results with different designs taken from the literature. Then, the model is solved to obtain the optimal designs corresponding to the following optimization criteria: a) minimization the total annual cost which includes investment (heat transfer area) and operating cost (fan power consumption), b) minimization the heat transfer area and c) minimization the fan power consumption. Obtained optimal and sub-optimal designs are compared in detail. [Copyright &y& Elsevier]

Abstract: This research deals with the utilization of analytic programming for a synthesis of control law for three selected discrete chaotic systems. The novelty of the approach is that a tool for symbolic regression–analytic programming–is used for such kinds of difficult problems. The paper consists of the descriptions of analytic programming as well as chaotic systems and used cost functions. For simulations, evolutionary algorithm SOMA (Self-Organizing Migrating Algorithm) and analytic programming were used. For each case study, repeated simulations were conducted to outline the effectiveness and robustness of used methods. All repeated simulations have given satisfactory results. [Copyright &y& Elsevier]

Abstract: Optimal allocation of emergency resources is a crucial content of emergency management. It is a key step in emergency rescue and assistance. Multiple resources and potential secondary disasters are often neglected in the existing methods, which desperately need to be improved. In this paper, we formulate the emergency resource allocation problem with constraints of multiple resources and possible secondary disasters, and model the multiple resources and multiple emergency response depots problem considering multiple secondary disasters by an integer mathematical programming. For the complexity, a heuristic algorithm is designed to efficiently solve it based on linear programming and network optimization. The algorithm modifies the solutions of the linear programming by setting a priority of preference for each location where the secondary disasters will take place with certain possibilities. The numerical simulation provides evidence for its effectiveness and efficiency. Our method and algorithm can also be implemented in the practical applications with large-scale scenario. [Copyright &y& Elsevier]

Abstract: Optimization of industrial water networks made up of several water-using processes can reduce freshwater usage and wastewater production. A common feature of previous water network studies is that each water-using operation is assumed to have a single outlet stream. In this paper, a superstructure and a mathematical programing model are proposed for optimization of a water network with both single and two outflow water-using processes. A two outflow water-using process has two outlet streams with different impurity concentrations, in which one has a lower concentration and the other a higher concentration. Outlet stream with a high concentration can be reused in other water-using processes, regenerated in a regeneration system or discharged, while the outlet stream with a low concentration can only be reused in other water-using processes. These intricacies are accounted for in the mathematical model. For a two outflow water-using process, the main parameters are the allocation rates of flowrate and mass load which may be determined through consideration of the process’s performance characteristics. The optimization methodology is demonstrated through a case study of a water network consisting of four single outflow water-using units, one two outflow water-using unit and a regeneration unit. [Copyright &y& Elsevier]

Abstract: This paper presents a new mathematical programming model for the optimal synthesis of recycle and reuse networks considering simultaneously the integration of the water network system and the surrounding watershed to satisfy process and environmental constraints. The model considers the optimal location of the new industrial facility to integrate its wastewater discharge to the environment with the surrounding watershed through a disjunctive formulation. The pollutants discharged for the new plant are tracked simultaneously with the other discharges to the watershed (i.e., residential, sanitary, industrial and extractions), and the natural phenomena that affect the composition of the watershed (i.e., evaporation, filtration, etc.), in addition to the chemical reactions that are carried out in the rivers. The objective function consists in minimizing the total annual cost that is constituted by the installation of the new plant cost (including the transportation for raw materials, products and services, as well as the land cost), the wastewater treatment costs (including the piping cost) and the fresh sources cost. Two example problems were used to show the applicability of the proposed methodology. [Copyright &y& Elsevier]

Abstract: In this paper a systematic methodology is presented for the simultaneous optimal selection of raw materials, fossil fuels and alternative fuels in cement production. The aim is to offer a generic mathematical formulation that can be used as the basis for developing case specific mathematical formulations that can assist the strategic decision-making process. The mathematical model presented takes into consideration the essential elements of a cement plant operation. The final formulation is a mixed integer linear programming problem that aims at minimizing the overall operating cost. A realistic case study is presented which demonstrates the usefulness of the proposed mathematical programming methodology. [Copyright &y& Elsevier]

Abstract: This paper presents a mathematical programming model for the optimal design of mass and property integration networks that include property interceptors within the structure of the network, as opposed to the end-of-pipe use of such interceptors. The model is based on a recycle and reuse scheme that simultaneously satisfies process and environmental constraints. The properties considered in this work are composition, toxicity, theoretical oxygen demand, pH, density and viscosity. The property mixing rules included in the model give rise to bilinear terms for the property operators, and a global optimization algorithm is used for the solution of the model. The model minimizes the total annual cost of the network, which includes the fresh sources cost and the annualized property treatment system and the piping costs. Three examples are included to show the applicability and advantages of the proposed model. [Copyright &y& Elsevier]

Abstract: In this paper, the optimization techniques for solving a class of non-differentiable optimization problems are investigated. The non-differentiable programming is transformed into an equivalent or approximating differentiable programming. Based on Karush–Kuhn–Tucker optimality conditions and projection method, a neural network model is constructed. The proposed neural network is proved to be globally stable in the sense of Lyapunov and can obtain an exact or approximating optimal solution of the original optimization problem. An example shows the effectiveness of the proposed optimization techniques. [Copyright &y& Elsevier]