Multistream heat exchanger modeling and design

Watson, H. A.; Khan, Kamil A.; Barton, Paul I.

doi:10.1002/aic.14965

Cited by 50 publications

(54 citation statements)

References 17 publications

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“…To that end, it is necessary to calculate for each 'kink' point in the hot and cold balanced composite curves (all the inlet and outlet temperatures) the triples (Hm, Tm, tm) and order those triples by non-decreasing enthalpy values. The first part (calculate the triples) can be efficiently performed using the approach presented by Watson et al (2015) and Watson and Barton (2016) that relies also on the 'max' operator, and therefore can be efficiently reformulated as a disjunction following the procedure presented by Quirante et al (2017). The advantage of this approach, in particular, the part related to the interpolation, is that for constant heat flow values it preserves the linearity and it has shown to be numerically efficient.…”

Section: Discussionmentioning

confidence: 99%

“…To that end, let us define the new index sets: According to Watson and Barton (2016) and Watson et al (2015), if we denote as Hm the enthalpy value in each one of the points in the set M, we can create a set of triples (Hm, Tm, tm) ordered by non-decreasing enthalpy values. Tm makes reference to the hot composite curve temperature and tm to the cold composite curve temperature, both at Hm.…”

Section: Area Estimationmentioning

confidence: 99%

“…The difficulty is to calculate all the triples from an arbitrarily ordered set of hot and cold streams in which inlet and outlet temperatures are also unknown. Watson et al (2015) and Watson and Barton (2016) showed that the enthalpy values for each of the 'kink' points can be calculated by the following expressions:…”

Section: Area Estimationmentioning

confidence: 99%

See 2 more Smart Citations

Disjunctive model for the simultaneous optimization and heat integration with unclassified streams and area estimation

Quirante

Grossmann

2018

Computers & Chemical Engineering

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Section: Discussionmentioning

confidence: 99%

Section: Area Estimationmentioning

confidence: 99%

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Disjunctive model for the simultaneous optimization and heat integration with unclassified streams and area estimation

Quirante

Grossmann

2018

Computers & Chemical Engineering

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“…Local sensitivity information for non-smooth models is obtained by calculating generalized derivatives automatically as explained in [187]. This approach has been applied to develop compact models for multi-stream heat exchangers [188], which have been incorporated into flowsheets of natural gas liquefaction [26] such as the simple mixed refrigerant [189,190] and dual mixed refrigerant processes [191,192].…”

Section: Categorization According To Modeling Approachmentioning

confidence: 99%

Modeling and Simulation of Energy Systems: A Review

2018

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Energy is a key driver of the modern economy, therefore modeling and simulation of energy systems has received significant research attention. We review the major developments in this area and propose two ways to categorize the diverse contributions. The first categorization is according to the modeling approach, namely into computational, mathematical, and physical models. With this categorization, we highlight certain novel hybrid approaches that combine aspects of the different groups proposed. The second categorization is according to field namely Process Systems Engineering (PSE) and Energy Economics (EE). We use the following criteria to illustrate the differences: the nature of variables, theoretical underpinnings, level of technological aggregation, spatial and temporal scales, and model purposes. Traditionally, the Process Systems Engineering approach models the technological characteristics of the energy system endogenously. However, the energy system is situated in a broader economic context that includes several stakeholders both within the energy sector and in other economic sectors. Complex relationships and feedback effects exist between these stakeholders, which may have a significant impact on strategic, tactical, and operational decision-making. Leveraging the expertise built in the Energy Economics field on modeling these complexities may be valuable to process systems engineers. With this categorization, we present the interactions between the two fields, and make the case for combining the two approaches. We point out three application areas: (1) optimal design and operation of flexible processes using demand and price forecasts, (2) sustainability analysis and process design using hybrid methods, and (3) accounting for the feedback effects of breakthrough technologies. These three examples highlight the value of combining Process Systems Engineering and Energy Economics models to get a holistic picture of the energy system in a wider economic and policy context.

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“…Saving on capital cost and volume is provided by using multi-stream heat exchanger [14]. Watson et al [15] presented model formulation and solution strategy for design and simulation of processes involving multi-stream heat exchangers in which they combined an extension of pinch analysis with an explicit dependence on the heat exchange area in a non-smooth equation system. During design of multi-stream plate fin heat exchanger, it is important to consider the optimal combination of fin categories and detailed geometries of fin types [16].…”

Section: Introductionmentioning

confidence: 99%

Energy analysis of heat exchanger in a heat exchanger network

Rauch

Galović

2018

THERM SCI

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Original scientific paper https://doi.org/10.2298/TSCI171231216R For many years now, heat exchanger optimization has been a field of research for a lot of scientists. Aims of optimization are different, having in mind heat exchanger networks with different temperatures of certain streams. In this paper mathematical model in dimensionless form is developed, describing operation of one heat exchanger in a heat exchanger network, with given overall area, based on the maximum heat-flow rate criterion. Under the presumption of heat exchanger being a part of the heat exchanger network, solution for the given task is resting in a possibility of connecting an additional fluid stream with certain temperature on a certain point of observed heat exchanger area. The connection point of additional fluid stream determines the exchanging areas of both heat exchangers and it needs to allow the maximum exchanged heat-flow rate. This needed heat-flow rate achieves higher value than the heat-flow rate acquired by either of streams. In other words, a criterion for the existence of the maximum heat-flow rate, as a local extremum, is obtained within this mathematical model. Results of the research are presented by the adequate diagrams and are interpreted, with emphasis on the cases which fulfill and those which do not fulfill the given condition for achieving the maximum heat-flow rate.

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Multistream heat exchanger modeling and design

Cited by 50 publications

References 17 publications

Disjunctive model for the simultaneous optimization and heat integration with unclassified streams and area estimation

Disjunctive model for the simultaneous optimization and heat integration with unclassified streams and area estimation

Modeling and Simulation of Energy Systems: A Review

Energy analysis of heat exchanger in a heat exchanger network

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