High-Fidelity Modeling &amp; Co-simulation with $$\pi \textsc {HyFlow}$$

Barros, Fernando J.

doi:10.1007/978-3-031-26236-4_23

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…There exist other methods commonly used for combining continuous and discrete models. 36,37,38 Some of these methods are further extended to support other kinds of modeling methods. 39,40,41 There also exists a large body of work for integrating simulation models using middleware software technologies supporting distributed simulation.…”

Section: Related Workmentioning

confidence: 99%

A knowledge interchange broker composition modeling framework for simulating water, energy, and water-energy nexus systems

Fard,

Sarjoughian

2024

SIMULATION

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Understanding the dynamics of complex systems requires developing and combining different kinds of models that can be simulated separately and together. Modeling the interactions as separate models contributes to building flexible hybrid simulation frameworks. In this research, a Discrete Event System Specification–based Interaction Model (DEVS-IM) framework is developed based on the Knowledge Interchange Broker (KIB) approach. This KIB-based RESTful modeling composition framework is shown to enable systematic modeling and simulation of interactions between disparate simulatable models. It supports storing IMs developed for componentized Water Evaluation and Planning System (WEAP) and Low Emissions Analysis Platform (LEAP) tools. It generates the skeleton of DEVS-IMs stored in database for DEVS-Suite simulator. An exemplar model consisting of water, energy, and IMs demonstrates this methodology for developing nexus models of water–energy systems.

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Section: Related Workmentioning

confidence: 99%

A knowledge interchange broker composition modeling framework for simulating water, energy, and water-energy nexus systems

Fard,

Sarjoughian

2024

SIMULATION

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“…Model M RWG is defined in section, and model M ETD is described in Barros. 7 The next section provides simulation results for this model obtained using the π HyFlow ++ M&S environment.…”

Section: Rc Circuitmentioning

confidence: 99%

“…π HyFlow 7 is an extension of the original HyFlow formalism aimed to support PI while keeping modularity and the ability to modify model topology at runtime. π HyFlow defines a modular base model that hosts a dynamic set of processes.…”

Section: Introductionmentioning

confidence: 99%

Defining hybrid hierarchical models in πHYFLOW

Barros

2024

SIMULATION

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This paper presents πHyFlow, a modular approach to the process interaction worldview (PI). Traditionally, PI supports a set of interacting processes without enabling modular and hierarchical model definition. πHyFlow basic models define a dynamic set of processes while also enabling a modular interface for supporting model composition. πHyFlow allows an exact representation of continuous signals based on the concepts of dense outputs, and generalized sampling. πHyFlow ability to support accurate models of hybrid systems is presented through a DC-DC converter (DCC) based on a resistor–capacitor (RC) electrical circuit. The DCC output voltage can be modeled by a first-order differential equation that is solved using an exponential time differencing (ETD) integrator. The DCC network model uses a digital on-off controller and an ETD. Simulation results are generated by πHyFlow++, a C++ implementation of the formalism.

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High-Fidelity Modeling & Co-simulation with $$\pi \textsc {HyFlow}$$

Cited by 2 publications

References 16 publications

A knowledge interchange broker composition modeling framework for simulating water, energy, and water-energy nexus systems

A knowledge interchange broker composition modeling framework for simulating water, energy, and water-energy nexus systems

Defining hybrid hierarchical models in πHYFLOW

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