Raymond R. Tan

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.

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.

Rule-based life cycle impact assessment using modified rough set induction methodology

Abstract Life cycle assessment (LCA) is a methodology for assessing environmental burdens of products or processes on a cradle-to-grave basis. The impact assessment phase necessitates use of decision analysis methods to account for multiple environmental criteria in the comparison of technological alternatives. Valuation or weighting of the impact criteria is usually accomplished by eliciting relative or absolute scores from an expert. This paper presents an alternative streamlined approach wherein heuristic rules are derived from a set of training data in the form of example alternatives ranked in order of preference by the expert. These decision rules are generated using an induction process based on rough set theory. The heuristic rules can subsequently be used to compare and rank new alternatives, and lead to a decision consistent with the expert preferences embodied in the training data.

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.

Fuzzy mixed-integer linear programming model for optimizing a multi-functional bioenergy system with biochar production for negative carbon emissions

A multi-functional bioenergy system is an efficient way for producing multiple energy products from biomass, which results in near-zero carbon emissions. To achieve net negative carbon emissions, biochar production as carbon sequestration can be integrated in the system. A fuzzy mixed-integer linear programming model is developed to simultaneously design and optimize a multi-functional bioenergy system given multiple product demands, carbon footprint, and economic performance constraints. Case studies are presented involving multi-functional bioenergy systems with biochar production for carbon sequestration. The results show that net negative carbon footprint can be achieved in such systems.

POLCAGE 1.0—a possibilistic life-cycle assessment model for evaluating alternative transportation fuels

Abstract A composite software model for the comparative life-cycle assessment (LCA) of 10 different fuel options for the Philippine automotive transport sector was developed. It is based on the GREET fuel-cycle inventory model developed by the Argonne National Laboratory for the United States Department of Energy. GREET 1.5a is linked to an impact assessment submodel using the Danish environmental design of industrial products (EDIP) method. This combined inventory–impact assessment model is enhanced further with possibilistic uncertainty propagation (PUP) and possibilistic compromise programming (PCP) features that allow the 10 alternatives to be ranked in the presence of multiple criteria and uncertain data. Sensitivity and scenario analysis can also be performed within the composite model. Some current and anticipated Philippine conditions, including electricity generation mix, are incorporated in the prototype’s built-in database. The software model, designated as POLCAGE 1.0 (possibilistic LCA using GREET and EDIP), is coded in Microsoft Excel and Visual Basic. The model’s capabilities and features are demonstrated using a case study based on its default scenario.

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.

Short communication: Application of symmetric fuzzy linear programming in life cycle assessment

Life cycle assessment (LCA) is known to entail multiple objective decision-making in the analysis of tradeoffs between different environmental impacts. The work of Azapagic and Clift in the late 1990s illustrates the use of multiple objective linear programming (MOLP) in the context of LCA. However, it will be noted that their approach yields a range of Pareto optimal alternatives from which the decision-maker must ultimately select the final solution. An alternative approach making use of Zimmermanns symmetric fuzzy linear programming method is proposed and illustrated with a simple case study. The procedure effectively yields a single, optimal compromise solution.

A methodology for criticality analysis in integrated energy systems

Integrated energy systems (IES) such as polygeneration plants and bioenergy-based industrial symbiosis (BBIS) networks offer the prospect of increased efficiency and reduced carbon emissions. However, these highly-integrated systems are also characterized by the strong interdependence among component units. This interdependency results in the risk of propagation of cascading failures within such networks, where disturbances in the operation of one component results in ripple effects that affect the other units in the system. In this work, a novel criticality index is proposed to quantify the effects of a component unit’s failure to run at full capacity within an IES. This index is defined as the ratio of the fractional change in the net output to the fractional change in capacity of the component causing the failure. The component units in the entire system can then be ranked based on this index. Such risk-based information can thus be used as an important input for developing risk mitigation measures and policies. Without this information, risk management based only on network topology could result to counterintuitive results. A simple polygeneration plant and two BBIS case studies are presented to demonstrate the computation of the criticality index.