The component interaction network approach for modeling of complex thermal systems

Khoury, Khalil El; Mouawad, Grace; Hitti, Georges El; Nemer, Maroun

doi:10.1016/j.advengsoft.2013.06.009

Cited by 13 publications

(3 citation statements)

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“…Two important methods for obtaining large models are coupling and assembling. In coupling, the system of equations, which is obtained from the models of each element, is solved iteratively (Clarke, et al, 2007;El Khoury, et al, 2013;Ma & Le, 1992). For example, building energy software tools use iterative methods to solve the coupled equations: EnergyPlus uses Gauss-Seidel successive substitution or Newton-Raphson method (Ficher, et al, 1999;, TRNSYS uses successive substitutions and Powell's method (TRNSYS 17, 2009), ESP-r solves independently the domain equations and then the coupling (Clarke, et al, 2007), IDA ICE uses a modular approach (Sahlin, 1996).…”

Section: Heat Capacitiesmentioning

confidence: 99%

Dynamic Models for Energy Control of Smart Homes

Ghiaus

2021

Towards Energy Smart Homes

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Section: Heat Capacitiesmentioning

confidence: 99%

Dynamic Models for Energy Control of Smart Homes

Ghiaus

2021

Towards Energy Smart Homes

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“…The overall system of components interconnected by their respective heat and mass fluxes forms the component interaction network (CIN). The method has been used in many thermal problems [10]- [16]. An example of CIN application is shown in Fig In the CIN method, all of the heat transfer modes are expressed in the form of:…”

Section: -2mentioning

confidence: 99%

Parallel Finite Element Approach for large Thermal Problems Applied to Glass Bending Furnace

Baydoun¹

2020

Proceedings of the 7th International Conference on Fluid Flow, Heat and Mass Transfer (FFHMT'20)

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“…In contrast to the monolithic approach, the partitioned approach avoids software development challenges by maintaining the modularity of all the component models. [12][13][14][15][16][17][18][19] This also allows component source codes that are developed and validated independently from one another by experts to be integrated and coupled. As a result, legacy models, in-house research models, and commercial modeling and simulation packages can potentially be utilized within the system.…”

Section: Introductionmentioning

confidence: 99%

A Purposed Model Coupling Framework for the Rapid Assembly of Complex System Simulations within an Integrated Computational Environment

McNunn

Bryden

2014

52nd Aerospace Sciences Meeting

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Often the emergent behavior of large-scale complex engineered and natural systems is a consequence of the interaction and interconnectivity between a large numbers of component subsystems. Consequently, modeling and simulating these large-scale systems requires methods that enable large numbers of heterogeneous, distributed models and databases to be assembled into a federated architecture that supports their interoperability and information sharing. However, to accurately propagate information through a federated system of models and databases a workflow is needed that identifies any data-related interdependencies that require an implicit solution and schedule the sequence of data exchanges, model runtimes, and database queries that is needed to evaluate the overall system. Although the local data exchanges that are needed to simulate the connectivity between any two components are often well understood, identifying the necessary workflow to solve a large-scale system of component models and databases is challenging and generally not practical using a hands-on or brute-force approach. As a result, a novel method is needed that identifies the computational workflow needed to accurately propagate data through a large-scale federated system of models and databases to ensure each component receives the necessary input data from the other components in the system prior to it being solved or queried. This paper develops a methodology that utilizes Tarjan's algorithm for finding the strongly connected components of a directed graph as a mechanism for organizing and scheduling the computational workflow needed to solve federated systems of models and databases based on the local input and output data associated with each component. The methodology is applied to identify the computational workflow needed to solve a system of models and databases representing the heat transfer and thermal stress in a one-dimensional gas turbine blade wall with a thermal barrier coating, and a system of models and databases representing a hybrid gas turbine, solid oxide fuel cell energy system.

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The component interaction network approach for modeling of complex thermal systems

Cited by 13 publications

References 13 publications

Dynamic Models for Energy Control of Smart Homes

Dynamic Models for Energy Control of Smart Homes

Parallel Finite Element Approach for large Thermal Problems Applied to Glass Bending Furnace

A Purposed Model Coupling Framework for the Rapid Assembly of Complex System Simulations within an Integrated Computational Environment

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