Preliminary Study on Reconstruction of Building Thermal Field Based on Iterative Algorithm Acoustic CT Article Swipe
Hengjie Qin
,
Jiangqi Wen
,
Zihe Gao
,
Lingling Chai
,
Haowei Yao
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/fire6050199
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/fire6050199
Real-time acquisition and visualization of temperature anomalies in building spaces and 3D temperature field data during fires are of vital importance for fire danger warnings, early rescue operations, evacuation commands, and subsequent fire accident investigations. Taking into account the non-contact, global (planar and spatial), and high efficiency advantages of acoustic CT temperature measurement technology, this study involved the conducting of exploratory preliminary research in order to provide new ideas for the real-time global perception of information on building fires. The detailed research objective was as follows: obtain the temperature data at any time of a fire based on Fire Dynamics Simulator (FDS) and fit them to form the base temperature distribution diagram at that time. The large ill-conditioned matrix equation of acoustic flight under the scheme of multi-grid division was then constructed. The discrete temperature data of each grid in the building space was obtained by solving the matrix equation based on algebraic reconstruction algorithm (ART) and joint algebraic reconstruction algorithm (SART). The three-dimensional temperature field reconstruction of building space was realized by the interpolation of discrete temperature data. The reconstruction effect of each scheme was evaluated through the error analysis between the reconstruction data and the basic data. The results show that the real-time reconstruction of a 3D temperature field of a building thermal field can be realized based on acoustic CT temperature measurement technology, and the reconstruction algorithm and grid division scheme have a significant control effect on the reconstruction effect.
Related Topics
Concepts
Interpolation (computer graphics)
Algorithm
Algebraic Reconstruction Technique
Computer science
Field (mathematics)
Grid
Matrix (chemical analysis)
Reconstruction algorithm
Simulation
Computer vision
Mathematics
Iterative reconstruction
Geometry
Composite material
Motion (physics)
Materials science
Pure mathematics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/fire6050199
- https://www.mdpi.com/2571-6255/6/5/199/pdf?version=1683875021
- OA Status
- gold
- Cited By
- 5
- References
- 10
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4376273298
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4376273298Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/fire6050199Digital Object Identifier
- Title
-
Preliminary Study on Reconstruction of Building Thermal Field Based on Iterative Algorithm Acoustic CTWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-12Full publication date if available
- Authors
-
Hengjie Qin, Jiangqi Wen, Zihe Gao, Lingling Chai, Haowei YaoList of authors in order
- Landing page
-
https://doi.org/10.3390/fire6050199Publisher landing page
- PDF URL
-
https://www.mdpi.com/2571-6255/6/5/199/pdf?version=1683875021Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2571-6255/6/5/199/pdf?version=1683875021Direct OA link when available
- Concepts
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Interpolation (computer graphics), Algorithm, Algebraic Reconstruction Technique, Computer science, Field (mathematics), Grid, Matrix (chemical analysis), Reconstruction algorithm, Simulation, Computer vision, Mathematics, Iterative reconstruction, Geometry, Composite material, Motion (physics), Materials science, Pure mathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 1, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
10Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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