3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement

The compaction quality of rockfill materials plays a pivotal role in ensuring the stability and durability of runway structures. However, traditional assessment methods relying on limited random sampling may lack representativeness for the entire construction site and overlook potential areas of ins...

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Main Authors: Lu Zhao, Lili Cheng, Cheng Zhou, Lieyun Ding, Fan Wang
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Results in Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S259012302300837X
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author Lu Zhao
Lili Cheng
Cheng Zhou
Lieyun Ding
Fan Wang
author_facet Lu Zhao
Lili Cheng
Cheng Zhou
Lieyun Ding
Fan Wang
author_sort Lu Zhao
collection DOAJ
description The compaction quality of rockfill materials plays a pivotal role in ensuring the stability and durability of runway structures. However, traditional assessment methods relying on limited random sampling may lack representativeness for the entire construction site and overlook potential areas of insufficient compaction. Addressing this challenge, this paper employs the dynamic deformation modulus (EVD), a rapid and nondestructive testing method, to assess the compaction quality of runway rockfill. Subsequently, this paper propose a 3D Conditional Random Field (CRF) model based on EVD to simulate the uncertain spatial distribution of rockfill compaction quality, allowing for the estimation of the overall construction area's compaction quality with a limited number of sample points. The validity of the model is demonstrated through a case study involving a runway expansion project. Additionally, three critical construction factors--namely, measurement points, compaction passes, and compaction materials--are analyzed throughout the construction process. This analysis provides managers with valuable insights and decision-making tools to promptly evaluate the quality of compaction areas, ensuring the stability and durability of the runway.
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spelling doaj.art-6cca0b16ed7241b5b82b2dd8526af8e52024-03-24T07:00:19ZengElsevierResults in Engineering2590-12302024-03-01211017103D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurementLu Zhao0Lili Cheng1Cheng Zhou2Lieyun Ding3Fan Wang4CCCC Wuhan Zhi Xing International Engineering Consulting Company Limited, ChinaCCCC Wuhan Zhi Xing International Engineering Consulting Company Limited, ChinaNational Center of Technology Innovation for Digital Construction, Huazhong University of Science and Technology, 430074, Wuhan, China; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China; Corresponding author. National Center of Technology Innovation for Digital Construction, Huazhong University of Science and Technology, 430074, Wuhan, China.National Center of Technology Innovation for Digital Construction, Huazhong University of Science and Technology, 430074, Wuhan, China; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 430074, Wuhan, ChinaNational Center of Technology Innovation for Digital Construction, Huazhong University of Science and Technology, 430074, Wuhan, China; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 430074, Wuhan, ChinaThe compaction quality of rockfill materials plays a pivotal role in ensuring the stability and durability of runway structures. However, traditional assessment methods relying on limited random sampling may lack representativeness for the entire construction site and overlook potential areas of insufficient compaction. Addressing this challenge, this paper employs the dynamic deformation modulus (EVD), a rapid and nondestructive testing method, to assess the compaction quality of runway rockfill. Subsequently, this paper propose a 3D Conditional Random Field (CRF) model based on EVD to simulate the uncertain spatial distribution of rockfill compaction quality, allowing for the estimation of the overall construction area's compaction quality with a limited number of sample points. The validity of the model is demonstrated through a case study involving a runway expansion project. Additionally, three critical construction factors--namely, measurement points, compaction passes, and compaction materials--are analyzed throughout the construction process. This analysis provides managers with valuable insights and decision-making tools to promptly evaluate the quality of compaction areas, ensuring the stability and durability of the runway.http://www.sciencedirect.com/science/article/pii/S259012302300837XRunwayCompaction quality assessmentEVDSpatial distributionConditional random fields
spellingShingle Lu Zhao
Lili Cheng
Cheng Zhou
Lieyun Ding
Fan Wang
3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement
Results in Engineering
Runway
Compaction quality assessment
EVD
Spatial distribution
Conditional random fields
title 3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement
title_full 3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement
title_fullStr 3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement
title_full_unstemmed 3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement
title_short 3D conditional random fields simulation for rockfill compaction quality assessment with sparse EVD measurement
title_sort 3d conditional random fields simulation for rockfill compaction quality assessment with sparse evd measurement
topic Runway
Compaction quality assessment
EVD
Spatial distribution
Conditional random fields
url http://www.sciencedirect.com/science/article/pii/S259012302300837X
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AT lieyunding 3dconditionalrandomfieldssimulationforrockfillcompactionqualityassessmentwithsparseevdmeasurement
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