|
|
|
|
| LEADER |
04459nma a2201081 u 4500 |
| 001 |
EB002186127 |
| 003 |
EBX01000000000000001323614 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
231103 ||| eng |
| 020 |
|
|
|a 9783036584485
|
| 020 |
|
|
|a books978-3-0365-8449-2
|
| 020 |
|
|
|a 9783036584492
|
| 100 |
1 |
|
|a Xin, Jingzhou
|
| 245 |
0 |
0 |
|a Intelligent Building Health Monitoring and Assessment
|h Elektronische Ressource
|
| 260 |
|
|
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
|
| 300 |
|
|
|a 1 electronic resource (236 p.)
|
| 653 |
|
|
|a machine learning
|
| 653 |
|
|
|a 3D FEM modelling
|
| 653 |
|
|
|a shield tunnelling
|
| 653 |
|
|
|a fiber-reinforced polymer
|
| 653 |
|
|
|a arch rib inclination angle
|
| 653 |
|
|
|a magnetoelastic effect
|
| 653 |
|
|
|a spatial diffusion model
|
| 653 |
|
|
|a moving loads identification
|
| 653 |
|
|
|a vehicle-bridge interaction
|
| 653 |
|
|
|a n/a
|
| 653 |
|
|
|a finite element method
|
| 653 |
|
|
|a steel box girder
|
| 653 |
|
|
|a loading system
|
| 653 |
|
|
|a MobileNetV2
|
| 653 |
|
|
|a CFST arch bridge
|
| 653 |
|
|
|a rebar
|
| 653 |
|
|
|a cantilever anti-slide pile
|
| 653 |
|
|
|a steel-concrete composite beam
|
| 653 |
|
|
|a long-span bridge
|
| 653 |
|
|
|a dung beetle optimizer (DBO)
|
| 653 |
|
|
|a evolution law of internal force and deformation
|
| 653 |
|
|
|a monitoring
|
| 653 |
|
|
|a magnetic resonance
|
| 653 |
|
|
|a field verification
|
| 653 |
|
|
|a weight calculation method
|
| 653 |
|
|
|a neural networks
|
| 653 |
|
|
|a Monte Carlo
|
| 653 |
|
|
|a History of engineering & technology / bicssc
|
| 653 |
|
|
|a Tikhonov regularisation
|
| 653 |
|
|
|a longitudinal temperature distribution
|
| 653 |
|
|
|a Technology: general issues / bicssc
|
| 653 |
|
|
|a rigid-frame arch bridge
|
| 653 |
|
|
|a plate end debonding
|
| 653 |
|
|
|a stayed-buckle cable
|
| 653 |
|
|
|a bridge engineering
|
| 653 |
|
|
|a steel tube concrete truss arch
|
| 653 |
|
|
|a highway basket-handle arch bridge
|
| 653 |
|
|
|a lateral stability
|
| 653 |
|
|
|a intermediate crack debonding
|
| 653 |
|
|
|a transfer learning
|
| 653 |
|
|
|a alignment prediction
|
| 653 |
|
|
|a trapezoidal thrust load
|
| 653 |
|
|
|a large-span track bridge
|
| 653 |
|
|
|a working stress
|
| 653 |
|
|
|a bearing characteristics
|
| 653 |
|
|
|a bridge temperature
|
| 653 |
|
|
|a non-uniform temperature field
|
| 653 |
|
|
|a cable-stayed bridge
|
| 653 |
|
|
|a corrosion factors
|
| 653 |
|
|
|a response surface method
|
| 653 |
|
|
|a Newmark-β method
|
| 653 |
|
|
|a scale model test
|
| 653 |
|
|
|a bridge substructure
|
| 653 |
|
|
|a active underpinning
|
| 653 |
|
|
|a moving force identification
|
| 653 |
|
|
|a optimized calculation method of internal force
|
| 653 |
|
|
|a friction-pendulum bearing
|
| 653 |
|
|
|a stay cable
|
| 653 |
|
|
|a super-long span
|
| 653 |
|
|
|a seismic-performance improvement
|
| 653 |
|
|
|a test design
|
| 700 |
1 |
|
|a Jiang, Yan
|
| 700 |
1 |
|
|a Wu, Bo
|
| 700 |
1 |
|
|a Yang, Simon X.
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b DOAB
|a Directory of Open Access Books
|
| 500 |
|
|
|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
|
| 028 |
5 |
0 |
|a 10.3390/books978-3-0365-8449-2
|
| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/113901
|z DOAB: description of the publication
|
| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/7742
|7 0
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 900
|
| 082 |
0 |
|
|a 576
|
| 082 |
0 |
|
|a 600
|
| 082 |
0 |
|
|a 620
|
| 082 |
0 |
|
|a 340
|
| 520 |
|
|
|a Buildings play an indispensable role in urban development. As typical structures of transportation buildings, bridges serve as crucial nodes in connecting different regions, promoting economic growth, and ensuring social security. However, with the extension of their service life, the performance of bridges will inevitably decline. Performance monitoring and evaluation are crucial during the life cycle of bridges. The accelerating convergence of civil engineering, materials science, and artificial intelligence has sparked the interest of researchers from different disciplines in the emerging field of bridge state perception. This reprint covers topics on condition monitoring and assessment of engineering structures, featuring 13 papers. These studies provide some novel methods, models, and technological applications for bridge condition perception, which are of great significance for the design, construction, and assessment of bridges.
|