Dominic Chwan Yee Foo

Automated targeting technique for concentration- and property-based total resource conservation network

Resource conservation networks (RCNs) are among the most effective systems for reducing the consumption of fresh materials and the discharge of waste streams. A typical RCN involves multiple elements of resource pre-treatment, material reuse/recycle, regeneration/interception, and waste treatment for final discharge. Due to the close interactions among these individual elements, simultaneous synthesis of a total RCN is necessary. This paper presents an optimisation-based procedure known as automated targeting technique to locate the minimum resource usage or total cost of a concentration- or property-based total RCNs. This optimisation-based approach provides the same benefits as conventional pinch analysis techniques in yielding various network targets prior to detailed design. Additionally, this approach offers more advantages than the conventional pinch-based techniques through its flexibility in setting an objective function and the ability to handle different impurities/properties for reuse/recycle and waste treatment networks. Furthermore, the concentration-based RCN is treated as the special case of property integration, and solved by the same model. Literature examples are solved to illustrate the proposed approach.

Process integration for resource conservation

Introduction Motivating Examples Process Synthesis and Analysis Process Integration: A Brief Overview Strategies for Material Recovery and Types of RCNs Problem Statements Structure of the Book Data Extraction for Resource Conservation Segregation for Material Sources Extraction of Limiting Data for Material Sink for Concentration-Based RCN Data Extraction for Mass Exchange Processes Data Extraction for Hydrogen-Consuming Units in Refinery Data Extraction for Property Integration Additional Readings PART I INSIGHT-BASED PINCH ANALYSIS TECHNIQUES Graphical Targeting Techniques for Direct Reuse/Recycle Material Recovery Pinch Diagram Significance of the Pinch and Insights from MRPD Targeting for Multiple Resources Targeting for Threshold Problems Targeting for Property Integration Additional Readings Algebraic Targeting Techniques for Direct Reuse/Recycle Generic Procedure for Material Cascade Analysis Technique Targeting for Multiple Fresh Resources Targeting for Threshold Problems Targeting for Property Integration with Inferior Property Operator Level Process Changes for Resource Conservation Networks Plus-Minus Principle Algebraic Targeting Approach for Material Regeneration Networks Types of Interception Units Targeting for Single Pass Interception Unit Modeling of Mass Exchange Operation as Interception Unit Additional Readings Network Design and Evolution Techniques Procedure for Nearest Neighbor Algorithm Design for Direct Material Reuse/Recycle and the Matching Matrix Design for Material Regeneration Network Network Evolution Techniques Additional Readings Targeting for Waste Treatment and Total Material Networks Total Material Network Generic Procedure for Waste Stream Identification Waste Identification for Material Regeneration Network Targeting for Minimum Waste Treatment Flowrate Insights from the WTPD Additional Readings Synthesis of Pretreatment Network Basic Modeling of a Partitioning Interception Unit Pretreatment Pinch Diagram Insights on Design Principles from PPD Pretreatment Network Design with Nearest Neighbor Algorithm Synthesis of Inter-Plant Resource Conservation Networks Types of IPRCN Problems Generic Targeting Procedure for IPRCN Design of IPRCN IPRCN with Material Regeneration and Waste Treatment Additional Readings Synthesis of Batch Material Networks Types of Batch Resource Consumption Units Targeting Procedure for Direct Reuse/Recycle in a BMN without Mass Storage System Targeting Procedure for Direct Reuse/Recycle in a BMN with Mass Storage System Targeting for Batch Regeneration Network Design of a BMN Waste Treatment and Batch Total Network Additional Readings PART II MATHEMATICAL OPTIMIZATION TECHNIQUES Synthesis of Resource Conservation Networks: A Superstructural Approach Superstructural Model for Direct Reuse/Recycle Network Incorporation of Process Constraints Capital and Total Cost Estimations Reducing Network Complexity Superstructural Model for Material Regeneration Network Superstructural Model for Inter-Plant Resource Conservation Networks Additional Readings Automated Targeting Model for Direct Reuse/Recycle Networks Basic Framework and Mathematical Formulation of ATM Incorporation of Process Constraints into ATM ATM for Property Integration with Inferior Operator Level ATM for Bilateral Problems Automated Targeting Model for Material Regeneration and Pretreatment Networks Types of Interception Units and Their Characteristics ATM for RCN with Single Pass Interception Unit of Fixed Outlet Quality Type ATM for RCN with Single Pass Interception Unit of Removal Ratio Type Modeling for Partitioning Interception Unit(s) of Fixed Outlet Quality Type Modeling for Partitioning Interception Unit(s) of Removal Ratio Type ATM for RCN with Partitioning Interception Unit(s) ATM for Pretreatment Networks Additional Readings Automated Targeting Model for Waste Treatment and Total Material Networks ATM for Waste Treatment Network ATM for TMN without Waste Recycling ATM for TMN with Waste Recycling Additional Readings Automated Targeting Model for Inter-Plant Resource Conservation Networks ATM for Direct Integration Scheme-Direct Material Reuse/Recycle ATM for Direct Integration Scheme: RCNs with Individual Interception Unit ATM for IPRCNs with Centralized Utility Facility Insights from ATM for IPRCN Synthesis Further Reading Automated Targeting Model for Batch Material Networks Basic ATM Procedure for Batch Material Networks ATM for Direct Reuse/Recycle Network ATM for Batch Regeneration Network ATM for Batch Total Network Further Reading Appendix: Case Studies and Examples Index Problems and References appear at the end of each chapter.

Flowrate Targeting Algorithm for Interplant Resource Conservation Network. Part 2: Assisted Integration Scheme

Part 1 of the series (Chew, I. M. L.; Foo, D. C. Y.; Ng, D. K. S.; Tan, R. R. Flowrate Targeting Algorithm for Interplant Resource Conservation Network. Part 1: Unassisted Integration Scheme. Ind. Eng. Chem. Res. DOI: 10.1021/ie901802m.) proposes a systematic three-step targeting algorithm for unassisted integration scheme for interplant resource conserVation network (IPRCN), where cross-plant streams within the pinch region can be used to achieve minimum resource flow rate targets. However, the unassisted scheme does not hold true for all cases. Part 2 of the series explores additional material recovery to be realized by sending cross-plant streams outside the pinch region. This is known as the assisted integration scheme. Appropriate identification of waste streams as the cross-plant streams is an important step in locating the minimum flow rate targets for these cases. The effect of pinch shifting and the generation of new waste streams are also investigated.

A hierarchical approach for the synthesis of batch water network

This work addresses the problem of synthesising cost-effective batch water networks where a number of process sources along with fresh water are mixed, stored, and assigned to process sinks. In order to address the complexity of the problem, a three-stage hierarchical approach is proposed. In the first stage, global targets are identified by formulating and solving a linear transportation problem for minimum water usage, maximum water recycle, and minimum wastewater discharge. These targets are determined a priori and without commitment to the network configuration. Next, a network with minimum number of tanks is synthesised by solving a mixed-integer non-linear program. The bilinear constraints are relaxed to transform the program into a mixed-integer linear program that is globally solvable. The third stage is aimed at simplifying the network configuration by minimising the number of network inter-connections. Insights gained from the water pinch analysis are also incorporated into the approach to further reduce the water flows via the placement of water regeneration unit. A case study is solved to illustrate the effectiveness of the proposed procedure.

An algebraic approach to identifying bottlenecks in linear process models of multifunctional energy systems

This paper presents an algebraic approach for identifying bottlenecks in continuous process systems where each process unit is characterized by fixed mass and energy balance relationships. In industrial applications, such a system is designed to produce a particular product portfolio. This is determined from the anticipated products market and is taken as a baseline state. A process plant is designed with the individual process units at the required size to meet the baseline portfolio, and typically additional margin for safety reason is considered. A simple approach to identify the bottlenecks is proposed and the product portfolio is changed by a given fraction relative to the baseline state. A bottleneck occurs when the available excess capacity of a process unit is insufficient to meet the incremental requirement. Two illustrative case studies demonstrate the proposed methodology.

Fuzzy optimization of topologically constrained eco-industrial resource conservation networks with incomplete information

It is possible to minimize industrial resource consumption by establishing eco-industrial resource conservation networks (RCN) between different plants. The establishment of these networks requires the satisfaction of quality criteria for material properties deemed significant by an industry. It also necessitates cooperation among the different firms based on the satisfaction of individual cost or resource consumption goals. Furthermore, there may be varying degrees of incomplete information regarding the process data of the participating plants. Eco-industrial RCNs may also be topologically constrained with respect to the number of links connecting different plants. These design aspects are incorporated in the optimization model through fuzzy mixed integer linear programming (FMILP) or fuzzy mixed integer non-linear programming (FMINLP). Case studies from literature involving water integration and hydrogen recovery are used to illustrate the methodology. The model is able to identify the topologically constrained network that achieves the highest level of overall satisfaction among participating plants.

Assessing the sensitivity of water networks to noisy mass loads using Monte Carlo simulation

For many water-intensive processes, water reuse can reduce water consumption as well as effluent generation. Process integration approach based on graphical pinch methodology for targeting and water network synthesis is often employed. The integrity of water network design to achieve the minimum water targets is highly sensitive to the availability of reliable process data. Existing network design process, however, assume that process data are fixed and well-defined, whereas the actual operating conditions such as water flowrate and the corresponding mass loads may fluctuate over time. These fluctuations in processing conditions can lead to process disruptions and product quality problems. This work demonstrates the use of Monte Carlo simulation in assessing the vulnerability of water networks to noisy mass loads. A case study illustrates the procedure of selecting the most robust network configuration from three alternative designs that achieve comparable water savings.

Ionic liquid design for enhanced carbon dioxide capture by computer-aided molecular design approach

Carbon capture and storage is an emerging technology to mitigate carbon dioxide (CO2) emissions from industrial sources such as power plants. Post-combustion capture based on aqueous amine scrubbing is one of the most promising technologies for CO2 capture currently. This technology, however, possesses a number of shortcomings, including high regeneration energy requirement, high solvent loss, degradation of solvent, etc. To overcome these limitations, researchers suggested different solvents and alternative technologies to replace the current amine scrubbing technique. Ionic liquids (ILs) are the most potential substitute among all. This is mainly because they have negligible vapour pressure and high thermal stability, which reduce solvent loss. However, there are up to a million possible combinations of cation and anion that may make up the ILs, which makes experimental works very time consuming and costly. In this work, optimal IL solvents specifically for carbon capture purpose are designed using computer-aided molecular design approach. This approach utilises group contribution method to estimate the thermophysical properties of ILs, and UNIFAC model to predict CO2 solubility in the ILs. Structural constraints are included to ensure that the synthesised ILs structure will satisfy the bonding requirement. This work focuses on design of ILs based on a physical absorption mechanism, and hence no chemical reaction is involved. The results show that the designed ILs are capable of capturing CO2 and their predicted properties are in good agreement with properties as determined through experimental works.

A heuristic-based algebraic targeting technique for aggregate planning in supply chains

Process integration techniques have seen its establishment in many non-conventional applications in the last decade. One of the newest applications of process integration technique is in the area of supply chain management. The well-established pinch analysis tools of composite curves and grand composite curves have been demonstrated their adaptability in this new area. Although the graphical tools provide many important insights for production planners, the common limitations of these graphical tools such as inaccuracy and being cumbersome need to be overcome. This calls for an algebraic targeting approach presented in this paper, known as the supply chain cascade analysis to supplement the various graphical tools. The cascade analysis technique sets targets for a supply chain. Besides, other new insights such as minimum and maximum inventory as well as the scheduling of process shut down are being introduced in this paper. Two industrial case studies are presented to illustrate the proposed method.

P-graph and Monte Carlo simulation approach to planning carbon management networks

Abstract A P-graph and Monte Carlo simulation approach to planning carbon management networks is proposed. These networks are generalized systems for minimizing emissions of CO 2 . Application of the P-graph framework to such problems has the added advantage of being able to rigorously identify both optimal and near-optimal solutions, which is a feature that is useful for practical decision-making; Monte Carlo simulation can then be used to evaluate the robustness of a network to variations in system parameters. Two literature case studies are used to demonstrate this methodology. The first example is a carbon-constrained energy sector planning problem, while the second example is a CO 2 capture and storage planning problem. In both cases, it is demonstrated that multiple solutions generated using P-graph methodology allow identification of robust, near-optimal carbon management networks.