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Multi-product pipelines usually transport several products in batches to respective delivery stations. As for a multi-product pipeline with multiple pump stations, this paper develops a continuous-time mixed-integer linear programming (MILP) model based on flowrate database to optimize its detailed scheduling. In the proposed model, various unit pump cost and flowrate constraints, which strongly depend on pump operation schemes, are introduced for the economy and safety of solved scheduling plans. Moreover, this paper considers the actual field processing constraints which vary with batch interface migration and rarely considered in previous work. And a novel method of historical flowrate database preprocessing is presented to enhance solving efficiency. Finally, through comparing with three real-world cases solved by another two available models, the proposed one performs the best in scheduling optimization as well as substantial reduction of pump cost. [ABSTRACT FROM AUTHOR]

This paper presents an optimization model of inspection and replacement planning for a refinery plant under the consideration of corrosion in terms of cost. The management of corrosion is an essential task for processes that operate over several years without a shutdown. This is because corrosion can cause severe failures by thinning the wall thickness and eventually cause pipes or equipment to burst. However, required safety measures, such as the corrosion management, involve costly inspection and replacement. Therefore, a cost-effective safety-action strategy is proposed in this paper. The developed model presents an optimal combination of steel grade, design wall thickness, inspection number, and inspection timing under a given corrosion rate to minimize the cost of design, inspection, replacement, and failure. Three case studies using sensitivity analyses are applied to three major processes in a refinery plant: a crude distillation unit, visbreaker, and hydrocracker. [ABSTRACT FROM AUTHOR]

This paper considers the upstream oil and gas domain, or more precisely the daily production optimization problem in which production engineers aim to utilize the production systems as efficiently as possible by for instance maximizing the revenue stream. This is done by adjusting control inputs like choke valves, artificial lift parameters and routing of well streams. It is well known that the daily production optimization problem is well suited for mathematical optimization. The contribution of this paper is a discussion on appropriate formulations, in particular the use of static models vs. dynamic models. We argue that many important problems can indeed be solved by repetitive use of static models while some problems, in particular related to shale gas systems, require dynamic models to capture key process characteristics. The reason for this is how reservoir dynamics interacts with the dynamics of the production system. [ABSTRACT FROM AUTHOR]

This paper presents computer-based design and analysis of control systems for centrifugal compressors when the operating fluid is supercritical CO 2 . It reports a non-linear dynamic model including a main forward compression line and two different configurations for the recycle antisurge line. Disturbance scenarios are proposed for testing the configurations and performance indicators are suggested to evaluate control performance and power consumption of the compression system. The paper demonstrates that compared to the hot recycle, the process configuration including a cold gas recycle has better overall stability, but higher power consumption and lower values for the control performance indicators. Based on the previous considerations, the paper gives suggestions regarding the choice of the recycle configuration. Moreover it compares subcritical and supercritical compression during surge prevention and highlights the importance of the selection of the gas recycle configuration when full recycle is needed. [ABSTRACT FROM AUTHOR]

Highlights • An enhanced surrogate assisted framework for constrained global optimization is proposed. • Maximizing probability of improvement approach is used for selecting infill points. • Kriging meta-models of objective and constraints functions are updated in every iteration. • Meta-model of objective function is local optimized when it's sufficient mature. • Numerical results indicate that the framework is suitable for use in solving computationally expensive and constrained black-box optimization. Abstract An enhanced surrogate assisted framework, based on Probability of Improvement (PI) method, is proposed in this paper. We made some modifications to the original PI approach to enhance the performance of the modeling and optimization framework, leading to fewer rigorous simulations to find the optimal solution without loss of accuracy. We also extended the algorithm for handling general constraints using a fully probabilistic approach. The behavior of the proposed framework was investigated through a set of 9 Unconstrained Test Functions (UTF), 7 Constrained Optimization Problems (COP) and 3 Chemical Engineering Problems (CEP). The numerical results indicate that a lower number of rigorous model simulations were needed for optimizing UTF compared to the classic PI method and that the proposed framework was capable of achieving sustained near optimal solutions for COP and CEP. These results indicate that the proposed framework is suitable for solving computationally expensive constrained black-box optimization problems. [ABSTRACT FROM AUTHOR]

Highlights • A novel piecewise state feedback controller is introduced. • The chemical process optimal control problem is formulated as an optimal control problem of switched dynamical systems. • A gradient-based parallel optimization algorithm is developed for solving the optimal control. • Convergence results indicate that the gradient-based parallel optimization algorithm is global convergent. • Three chemical process optimal control problems are given to illustrate the effectiveness of the proposed algorithm. Abstract This paper considers an optimal control problem of chemical processes with a novel piecewise state-feedback controller. Firstly, the chemical process optimal control problem is formulated as a switched dynamical system optimal control problem, which can be transformed into a parameter optimization problem. Next, to achieve rapid convergence from remote starting points, we propose a novel gradient-based optimization algorithm, which is suitable to a parallel implementation because the step is improved by updating its direction as well as its length simultaneously before moving to the next iteration, and the step computation involves only the inner products of vectors. Then, the convergent properties of the parameter optimization problem to the original optimal control problem are discussed. Finally, the numerical simulation results show that the gradient-based parallel optimization algorithm is an effective alternative method for solving the chemical process optimal control problems. [ABSTRACT FROM AUTHOR]

Graphical abstract Image, graphical abstract Highlights • A two-dimensional, two-phase, isothermal model is presented for PEMFCs. • The modeling results agree well with the different experimental data. • Effects of cell voltage on the species distribution are explored. • Effects of cell voltage on the saturation level distribution are studied. Abstract In this paper, a two-dimensional, two-phase, isothermal model is presented to investigate the water transport characteristic and water distribution in a proton exchange membrane fuel cell (PEMFC) with emphasis on exploring the water distribution in the layers of PEMFC. The governing equations have been solved over a single computational domain, which consists of all the layers. The result of polarization curve has been validated against the experimental data in an extensive range of operating conditions. A parametric study has also been performed to examine the effects of the diffusion layer (DL) permeability, contact angle, and cell output voltage on water distribution in the various layers of PEMFC. Numerical results elucidate that water distribution level in the cathode side is decreased with the increment in the cell voltage. Furthermore, the permeability of the cathode DL and contact angle significantly influence the water saturation level in the cathode side. [ABSTRACT FROM AUTHOR]

Using sequence information can improve performances in fault detection for serial (temporal) correlated process data. Classical methods firstly construct extended vectors through concatenating current process data and a certain number of previous process data, and then take dimension reduction methods. However, the simple extension of process data may distort the correlation between variables and largely increase the dimensionality. This paper proposes a novel algorithm, called Dynamic Graph Embedding (DGE), for fault detection. DGE adopts augmented matrices instead of extended vectors to encode sequence information. Furthermore, DGE incorporates both time information and neighborhood information to form similarities of different process data. And then DGE is designed to obtain embedding matrices with Markov chain analysis of the similarities. Extensive experimental results on the Tennessee Eastman (TE) benchmark process show the superiority of DGE in terms of missed detection rate (MDR) and false alarm rate (FAR). [ABSTRACT FROM AUTHOR]

In this paper, an integrated coal gasification combined cycle system for the production of hydrogen and electricity is optimized in terms of energy and exergy efficiencies, and the amount and cost of the produced hydrogen and electricity. The integrated system is optimized by focusing on the conversion process of coal to syngas. A novel optimization process is developed which integrates an artificial neural network with a genetic algorithm. The gasification system is modeled and simulated with Aspen Plus for large ranges of operating conditions, where the artificial neural network method is used to represent the simulation results mathematically. The mathematical model is then optimized using a genetic algorithm method. The optimization demonstrates that the lower is the grade of coal of the three considered coals, the less expensive is the hydrogen and electricity that can be produced by the considered integrated gasification combined cycle (IGCC) system. [ABSTRACT FROM AUTHOR]

In this paper, a new methodology has been developed to deal with the front-end crude scheduling (FECS) problems with the consideration of inherent upset minimization (IUM). Specifically, the primary and secondary inherent upsets (IUs) have been defined and modeled to, respectively, address flowrate fluctuations of feeding crude distillation units and the long-distance pipeline (LDPL). Based on such IU characterizations, a new MINLP model with the unit-based continuous time representation is developed to determine the optimal FECS solution by minimizing the overall operating cost and instability along the entire scheduling time horizon. In addition to the IUM, another two merits are also included in this study: (i) the trans-mixing (TM) issue along with crude transportation inside the LDPL has been modeled; (ii) multiple types of crudes with multiple key properties have been simultaneously considered. The developed FECS MINLP model is solved by the ANTIGONE solver to obtain the global optima. The efficacy of the proposed methodology and the FECS model, and the effect of IUM have been investigated through various case studies. [ABSTRACT FROM AUTHOR]

This paper proposes a locality preserving discriminative canonical variate analysis (LP-DCVA) scheme for fault diagnosis. The LP-DCVA method provides a set of optimal projection vectors that simultaneously maximizes the within-class mutual canonical correlations, minimizes the between-class mutual canonical correlations, and preserves the local structures present in the data. This method inherits the strength of canonical variate analysis (CVA) in handling high-dimensional data with serial correlations and the advantages of Fisher discriminant analysis (FDA) in pattern classification. Moreover, the incorporation of locality preserving projection (LPP) in this method makes it suitable for dealing with nonlinearities in the form of local manifolds in the data. The solution to the proposed approach is formulated as a generalized eigenvalue problem. The effectiveness of the proposed approach for fault classification is verified by the Tennessee Eastman process. Simulation results show that the LP-DCVA method outperforms the FDA, dynamic FDA (DFDA), CVA-FDA, and localized DFDA (L-DFDA) approaches in fault diagnosis. [ABSTRACT FROM AUTHOR]

In this paper, we consider near-optimal operation for a class of unconstrained batch processes using the self-optimizing control (SOC) methodology. The existing static SOC approach is extended to the dynamic case by means of a static reformulation of the dynamic optimization problem. However, the dynamic SOC problem is posed as a structure-constrained controlled variable (CV) selection problem, which is different from the static cases. A lower-block triangular structure is specified for the combination matrix, H , to allow for optimal operation whilst respecting causality. A new result is that the structure-constrained SOC problem still results in a convex formulation, which has an analytic solution where the optimal CVs associated with discrete time instants are solved separately. In addition, the inputs are directly determined based on current CV functions for on-line utilization. A fed-batch reactor and a batch distillation column are used to demonstrate the usefulness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, we examine the mathematical structure of chemical reaction networks with the goals of identifying reaction invariant states and determining their physical significance. A combined species-reaction graph/convex analysis approach is developed to find semi-positive invariant states associated with a reaction network. Application of this graphical/algebraic reaction network analysis approach to four different chemical processes reveals that reaction invariants can represent conserved quantities other than elemental balances. [ABSTRACT FROM AUTHOR]

Artificial gas-lift (AGL) technique is commonly used to enhance oil production when the reservoir pressure in wells is not enough to sustain acceptable oil flow rate. However, the gas-lift wells are prone to instability, characterized by regular oscillations of pressure and flow. This phenomenon is known as casing-heading instability. It results in production loss and negative impact on downstream equipment, and has been a challenging problem to both industry and academia. In this paper, a novel concept of optimal tracking control is proposed for stabilization and operating mode transition in gas-lift wells when casing-heading phenomenon occurs. The stability of artificial gas-lift process is ensured by manipulating both gas lift choke and oil production choke, where the openings of both choke valves can vary from fully closed to fully open. Through the simulation of the open-loop system, a stability map of AGL process is produced. Then a trajectory optimization algorithm is developed based on this stability map, which is synthesized with a tracking controller to achieve trajectory optimization control. Also, a nonlinear state observer is designed to ensure estimation of unmeasurable variables. Through simulation studies, the effectiveness of proposed trajectory optimization control is demonstrated. [ABSTRACT FROM AUTHOR]

Reaction network model is central to ethylene cracking process simulation. Studying an ethylene cracking reaction (ECR) network, which involves hundreds of components and thousands of reactions, becomes a difficult task. To facilitate a rapid and comprehensive reaction network analysis and improve ECR network, this paper introduced a ranking algorithm called network flow analysis algorithm (NFAA) to a reaction network analysis procedure. NFAA analyses the reaction network with comprehensive information such as network topological structure, reaction mechanism, and process model data. Following NFAA, reactions and species are ranked based on their significances. According to the ranking of reactions, unimportant reactions (lower ranking) in ECR network are removed to reduce ECR network complexity and decrease computational scale without loss of prediction accuracy. On the other hand, rankings provide guidance on adjusting parameters of ECR network. The application of NFAA makes a progress in improvement of ECR reaction network in an industrial case. [ABSTRACT FROM AUTHOR]

For many industrial sites, a production scheduling solution – be it manual or optimized – is in many ways still a complex and “exotic” application that seldomly finds its way into the daily practice of the plant floor. As it lies within the interface between business and control systems, scheduling is too often seen as something decoupled and theoretical that requires high-level experts for configuring, using and maintaining it. In this paper, we discuss some of the challenges and hurdles for deploying scheduling solutions. A relevant ongoing technological transition towards stronger integration is also addressed. Some potential for improvements are identified both in academia and industry. By addressing the main pain points it can be seen that with a common mind-set the complexity of deploying a scheduling solution can be lowered significantly. [ABSTRACT FROM AUTHOR]

Although modern chemical processes are highly automatic, abnormal situation management (ASM) still heavily relies on human operators. Process fault detection and diagnosis (FDD) are one of the most important issues of ASM but few FDD systems have been satisfactorily applied in real chemical processes since the concept of FDD was proposed about 40 years ago. In this paper, developments of chemical process FDD are briefly reviewed. The reason why FDD has not been widely implemented in the chemical process industry is discussed. One of the insights gained is that some basic problems in FDD such as how to define faults and how many faults to diagnose have not even been addressed well while researchers tirelessly try to invent new methods to diagnose fault. A new framework is proposed based on the big data in a cloud computing environment of a big chemical corporation for addressing the challenging issues in ASM. [ABSTRACT FROM AUTHOR]

This paper deals with time-optimal operation of batch diafiltration processes in the presence of membrane fouling. Fouling causes a decrease in the effective membrane area and, hence, an increase in processing time. In this work we study a time-optimal operation with several fouling models available in literature. Pontryagin's minimum principle is applied to characterize the structure of the optimal operation which voids any further on-line optimization. Due to the specific structure of the problem, it is possible, in several problem setups, to derive and verify an explicit analytic solution. Obtained results are applied in case studies where we provide a comparison between traditional operation and the proposed time-optimal operation. In cases, where the optimal operation cannot be identified analytically, we analyze the performance of sub-optimal control derived from neighboring analytical solution and compare it to optimal operation found via numerical optimization techniques. [ABSTRACT FROM AUTHOR]

Opportunities and challenges in the petrochemical industry and the emergence of massive disruptive technologies have triggered a new revolution that has the power to fundamentally change industrial processes including manufacturing, engineering, materials, supply chains, lifecycle management. Recently, the newly arisen smart factory adopted a disruptive manufacturing methodology and has become a key part of the petrochemical industry. The smart factory, which is different from the original production systems used in the petrochemical industry, needs to assess and position its future research agenda including its definition, intension, framework, and technology. Systems thinking and systems problem solving for the smart factory must be prioritized. Based on an analysis of the driving force for smart factory development, this paper proposes a lifecycle blueprint and consensus-based operating and technology roadmap. The definition and features of a smart factory in the petrochemical industry are presented. Furthermore, a summary of the technical systems and future-proof research field of the smart petrochemical factory from an academic and industrial viewpoint is presented. [ABSTRACT FROM AUTHOR]

In model-based real-time optimization, plant-model mismatch can be handled by applying bias- and gradient-corrections to the cost and constraint functions in an iterative optimization procedure. One of the major challenges in practice is the estimation of the plant gradients from noisy measurement data, in particular for several optimization variables. In this paper we propose a new real-time optimization scheme that explores the inherent smoothness of the plant mapping to enable a reliable optimization. The idea here is to combine the quadratic approximation approach used in derivative-free optimization techniques with the iterative gradient-modification optimization scheme. The convergence of the scheme is analyzed. Simulation studies for the optimization of a ten-variable synthetic example and a reactor benchmark problem with considerable plant-model mismatch show its promising performance. [ABSTRACT FROM AUTHOR]

In this paper Multistage flash (MSF), Reverse Osmosis (RO) and hybrid MSF/RO desalination systems are optimized. A superstructure is set up for analyzing various process configurations in a single flowsheet. Detailed steady state models for MSF and RO sections of the superstructure are developed incorporating comprehensive physio-chemical properties and design characteristics. The model for the hybrid system combines individual models of MSF and RO systems and additional separators and mixers. The optimization variables consist of the operating and design variables, and the objective function is developed on the basis of economic and technical performance indicators. Primary results show that the hybridization of MSF and RO systems sharing common intake-outfall facilities presents lower cost with the additional benefits of higher overall recovery than MSF system and higher product quality than RO system. The sensitivity analysis of the cost parameters is performed to realize their effects on the selection of process configuration. [ABSTRACT FROM AUTHOR]

In this first of a series of two papers, the effect of varying steam levels on the total steam flowrate within steam systems is analysed mathematically for the traditional parallel configuration as well as for the case of hot liquid reuse. It is demonstrated that in the case of parallel heat exchangers utilising only latent heat, a minimum total steam flowrate is obtained by optimally selecting steam levels, but that in the case of hot liquid reuse, introducing multiple steam levels increases the minimum total steam flowrate attainable under those conditions. The flowrate attained utilising hot liquid reuse, however, remains lower than when only utilising latent heat. It is concluded that the lowest steam flowrate is attained using hot liquid reuse and only a single level of steam, but that the presence of additional steam levels resulting from turbines requires a more holistic approach to the synthesis of steam networks. [ABSTRACT FROM AUTHOR]

Presented in this paper is a mathematical technique for simultaneous heat integration and process scheduling in multipurpose batch plants. Taking advantage of the intermittent continuous behavior of process streams during transfer from one processing unit to another, as determined by the recipe, the presented formulation aims to maximize the coincidence of availability of hot and cold stream pairs with feasible temperature driving forces, while taking into consideration process scheduling constraints. Contrary to similar contributions in published literature, time is treated as one of the key optimization variables instead of a parameter fixed a priori. Heat integration during stream transfer has the added benefit of shortened processing time, which invariably improves throughput, as more batches are likely to be processed within a given time horizon, compared to conventional heating and cooling in situ. Application of the proposed model to a case study shows improvements of more than 30% in energy savings and up to 15% in product output. [ABSTRACT FROM AUTHOR]

This paper provides a historical perspective and an overview of the pioneering work that Manfred Morari developed in the area of resiliency for chemical processes. Motivated by unique counter-intuitive examples, we present a review of the early mathematical formulations and solution methods developed by Grossmann and co-workers for quantifying Static Resiliency (Flexibility). We also give a brief overview of some of the seminal ideas by Manfred Morari and co-workers in the area of Dynamic Resiliency. Finally, we provide a review of some of the recent developments that have taken place since that early work. [ABSTRACT FROM AUTHOR]