Flame simulations with an open-source code
| Main Author: | Ballantyne, John |
|---|---|
| Other Authors: | Dasgupta, Adhiraj, Gonzalez-Juez, Esteban, Haworth, Daniel C. |
| Format: | Dataset |
| Terbitan: |
Mendeley
, 2018
|
| Subjects: | |
| Online Access: |
https:/data.mendeley.com/datasets/h8hch3hs9p |
| ctrlnum |
0.17632-h8hch3hs9p.1 |
|---|---|
| fullrecord |
<?xml version="1.0"?>
<dc><creator>Ballantyne, John</creator><title>Flame simulations with an open-source code</title><publisher>Mendeley</publisher><description>Flame simulations are used to gain insight into combustion physics and to design combustion systems such as piston engines, gas–turbine engines, and process heaters. In these simulations, the balance between reaction and molecular mixing plays a key role. To model molecular mixing, using a full multicomponent approach leads to high accuracy at the expense of a hefty computational cost. Thus, the use of a mixture-averaged model is usually preferred. Hence, this paper presents and tests a new OpenFOAM®-based code that incorporates a detailed, mixture-averaged approach for calculating transport properties in reacting flows, and provides a capability to solve either fully-compressible or low-Mach-number governing equations. The code is made readily available on GitHub and is written completely in OpenFOAM®’s native code framework, making it highly portable and easy to maintain, enhance, and extend. It is tested by modeling two laminar flames, and two turbulent flames undergoing extinction and reignition. Overall, predictions with the present code are seen to be in good agreement with experimental and direct-numerical-simulation data.</description><subject>Computational Physics</subject><contributor>Dasgupta, Adhiraj</contributor><contributor>Gonzalez-Juez, Esteban</contributor><contributor>Haworth, Daniel C.</contributor><type>Other:Dataset</type><identifier>10.17632/h8hch3hs9p.1</identifier><rights>GNU Public License Version 3</rights><rights>http://www.gnu.org/licenses/gpl-3.0.en.html</rights><relation>https:/data.mendeley.com/datasets/h8hch3hs9p</relation><date>2018-12-13T16:03:45Z</date><recordID>0.17632-h8hch3hs9p.1</recordID></dc>
|
| format |
Other:Dataset Other |
| author |
Ballantyne, John |
| author2 |
Dasgupta, Adhiraj Gonzalez-Juez, Esteban Haworth, Daniel C. |
| title |
Flame simulations with an open-source code |
| publisher |
Mendeley |
| publishDate |
2018 |
| topic |
Computational Physics |
| url |
https:/data.mendeley.com/datasets/h8hch3hs9p |
| contents |
Flame simulations are used to gain insight into combustion physics and to design combustion systems such as piston engines, gas–turbine engines, and process heaters. In these simulations, the balance between reaction and molecular mixing plays a key role. To model molecular mixing, using a full multicomponent approach leads to high accuracy at the expense of a hefty computational cost. Thus, the use of a mixture-averaged model is usually preferred. Hence, this paper presents and tests a new OpenFOAM®-based code that incorporates a detailed, mixture-averaged approach for calculating transport properties in reacting flows, and provides a capability to solve either fully-compressible or low-Mach-number governing equations. The code is made readily available on GitHub and is written completely in OpenFOAM®’s native code framework, making it highly portable and easy to maintain, enhance, and extend. It is tested by modeling two laminar flames, and two turbulent flames undergoing extinction and reignition. Overall, predictions with the present code are seen to be in good agreement with experimental and direct-numerical-simulation data. |
| id |
IOS7969.0.17632-h8hch3hs9p.1 |
| institution |
Universitas Islam Indragiri |
| affiliation |
onesearch.perpusnas.go.id |
| institution_id |
804 |
| institution_type |
library:university library |
| library |
Teknologi Pangan UNISI |
| library_id |
2816 |
| collection |
Artikel mulono |
| repository_id |
7969 |
| city |
INDRAGIRI HILIR |
| province |
RIAU |
| shared_to_ipusnas_str |
1 |
| repoId |
IOS7969 |
| first_indexed |
2020-04-08T08:30:09Z |
| last_indexed |
2020-04-08T08:30:09Z |
| recordtype |
dc |
| _version_ |
1686587755120820224 |
| score |
17.538404 |