Article
Geochemistry & Geophysics
Hai Liu, Hantao Lu, Jianying Lin, Feng Han, Chao Liu, Jie Cui, Billie F. Spencer
Summary: Ground-penetrating radar (GPR) is widely used for the nondestructive inspection of concrete structures reinforced by steel bars. This study examines the scattering and penetration characteristics of EM waves passing through rebar nets, finding that rebar perpendicular to the polarization direction is transparent to GPR waves, while rebar parallel to the polarization direction causes a shielding effect, creating a blind band in the low-frequency range.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2021)
Article
Chemistry, Analytical
Dafnik Saril Kumar David, Yeongseok Jeong, Yin Chao Wu, Suyun Ham
Summary: This paper discusses the characterization challenges of electromagnetic waves in inhomogeneous media. Understanding the electromagnetic properties of materials is crucial for analyzing wave behavior. The paper develops a numerical model for electromagnetic antennas using the finite difference time domain method and verifies its accuracy with experimental data. Inhomogeneous models considering different materials and random aggregates and voids are also analyzed and verified experimentally.
Article
Engineering, Electrical & Electronic
Sigurd Eide, Svein-Erik Hamran, Henning Dypvik, Hans E. F. Amundsen
Summary: This article assesses how the ground-penetrating radar RIMFAX will image the crater floor at the Mars 2020 landing site, with a focus on understanding lithological compositions and stratigraphic relationships. Through synthetic modeling and simulations, the study aims to gain scientific insights on the deposition chronology and volcanic history in the region, by examining the potential mafic unit and its relevance to radar sounding.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Computer Science, Information Systems
Peiyu Wu, Han Yu, Yongjun Xie, Haolin Jiang, Toshiaki Natsuki
Summary: By combining higher order formulation with PML implementation, a computationally efficient LOD algorithm with improved absorption is proposed for simulating ground penetrating radar in open regions in the FDTD algorithm. The implementation shows advantages in accuracy, efficiency, and absorption enhancement.
Article
Geochemistry & Geophysics
Iraklis Giannakis, Antonios Giannopoulos, Craig Warren, Anastasia Sofroniou
Summary: Full-waveform inversion is a promising interpretation tool for hydrogeological applications, but has been limited in practical uptake due to computational requirements, inability to reconstruct loss mechanisms, and need for a good initial model. This study introduces a novel FWI approach that addresses these issues using a fractally correlated water distribution, reducing computational requirements and improving performance.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geosciences, Multidisciplinary
Bowen Ma, Weiqiang Zhu, Qinghua Huang
Summary: Ground penetrating radar (GPR) is an effective technology for investigating shallow underground structures, and migration is necessary for interpreting GPR data. The finite-difference time-domain algorithm can provide higher-resolution and more reliable results in three-dimensional RTM approach.
JOURNAL OF APPLIED GEOPHYSICS
(2021)
Article
Geochemistry & Geophysics
Tonghua Ling, Wenchao He, Xianjun Liu, Sheng Zhang, Fu Huang, Fei Hua
Summary: This study proposes a method of using the Fisher-Yates random shuffling algorithm combined with the finite-difference time-domain method to construct a fine grid model for simulating ground-penetrating radar in mixed media. The experimental results showed that this method can effectively simulate ground-penetrating radar in mixed media and interpret the corresponding images.
GEOPHYSICAL PROSPECTING
(2022)
Article
Construction & Building Technology
M. Miskiewicz, K. Daszkiewicz, J. Lachowicz, P. Tysiac, P. Jaskula, K. Wilde
Summary: Nondestructive methods of road pavement diagnostics, such as groundpenetrating radar (GPR) and laser scanning technology, are effective in assessing factors contributing to pavement failure and detecting nonhomogeneous compaction zones. Comparing radar images can help identify reflections and anomalies caused by defects, while laser scanning technology can be used to evaluate geometric changes on the surface.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Chemistry, Analytical
Qingqing Cao, Imad L. Al-Qadi
Summary: Ground-penetrating radar (GPR) has been used for predicting asphalt concrete (AC) pavement density and quality control. A three-phase numerical model was developed to estimate asphalt pavement specific gravity, with the reflection amplitude method shown to be more sensitive to thin surface layers. The study focused on the impact of air-void content, asphalt content, aggregate gradation, and aggregate dielectric constants on GPR measurements.
Article
Environmental Sciences
Sheng Zhang, Liang Zhang, Tonghua Ling, Guihai Fu, Youlin Guo
Summary: In this study, ground penetrating radar (GPR) was used to detect and evaluate changes in soil water content, with a new wavelet packet-based energy analysis method proposed for assessing soil water content. The research showed a highly correlated linear relationship between the wavelet packet-based energy indexes (WPEI) and soil water contents, indicating the feasibility and accuracy of the method. The large-area, continuous scanning measurement method of GPR was found to be suitable for evaluating soil water contents in various contexts.
Article
Engineering, Civil
Lilong Cui, Tianqing Ling, Jingzhou Xin, Rukai Li
Summary: Ground penetrating radar (GPR) has the potential to estimate asphalt pavement thickness and density during compaction, but the accuracy of data collection is significantly affected by surface moisture. This study proposed an approach based on the extended common midpoint (XCMP) method to minimize the effect of surface moisture, and verified its effectiveness through numerical simulation and laboratory experiments. The proposed method can accurately predict thickness and density under complicated compaction conditions, demonstrating its potential for real-time compaction monitoring.
KSCE JOURNAL OF CIVIL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Chuan Li, Yue Zhang, Lulu Wang, Weiping Zhang, Xi Yang, Xiumei Yang
Summary: Ground-penetrating radar (GPR) is used to detect tunnels by analyzing the attenuation and reflection coefficients of electromagnetic waves. The rebar is recognized by reconstructing its hyperbolic feature using the negative peak points in the A-scan. This method was successfully applied in the Husa Tunnel in Yunnan Province, China, and showed evident hyperbolic features of the reconstructed rebar in the B-scan.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Qingqing Cao, Imad L. Al-Qadi
Summary: This paper presents a simulated approach using ground-penetrating radar (GPR) to quantify the effect of internal moisture content on the dielectric properties of asphalt concrete (AC) pavement. The proposed model was validated through GPR surveys and demonstrated the ability of GPR to monitor moisture variation in AC pavements.
Article
Chemistry, Analytical
Jiaming Tang, Chunhua Chen, Zhiyong Huang, Xiaoning Zhang, Weixiong Li, Min Huang, Linghui Deng
Summary: An improved Crack Unet model based on the Unet semantic segmentation model is proposed for 3D ground-penetrating radar crack image processing. The experiment showed that the model displayed better capacity in the radar image crack segmentation task than current mainstream algorithms do, and it has excellent engineering application value.
Article
Engineering, Multidisciplinary
Zhengfang Wang, Ming Lei, Jing Wang, Bo Li, Jing Xu, Yuchen Jiang, Qingmei Sui, Yao Li
Summary: This paper proposes an unsupervised deep learning method for translating real ground penetrating radar (GPR) images to simulated ones. The method introduces geometry-consistency constraints to prevent semantic distortion in translation. It was validated using GPR data collected in various scenarios, and the findings demonstrate accurate identification of internal defects in translated GPR images.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Construction & Building Technology
Mojtaba Ziyadi, Hasan Ozer, Maryam Shakiba, Imad L. Al-Qadi
Summary: The study investigated the impact of pavement structural rolling resistance on vehicles' excess fuel consumption and proposed a practical approach to assess the influence of pavement deflection on fuel consumption. The proposed model was validated through sensitivity analysis and provided estimated fuel consumption for heavy trucks under different loading, temperature, and speed scenarios.
ROAD MATERIALS AND PAVEMENT DESIGN
(2023)
Article
Construction & Building Technology
Jose Rivera-Perez, John Huang, Imad L. Al-Qadi
Summary: This study investigates the sources of pay disincentives in the two HMA pay specifications developed by the Illinois Department of Transportation, and finds that production and construction issues are the main causes of pay disincentives to contractors.
ROAD MATERIALS AND PAVEMENT DESIGN
(2023)
Article
Construction & Building Technology
Lama Abufares, Qingqing Cao, Imad L. Al-Qadi
Summary: Ground-penetrating radar (GPR) is used to assess civil structures like pavements by predicting asphalt concrete (AC) layer thicknesses and dry densities. Moisture content quantification in AC improves density prediction, while in cold recycled pavements, it helps monitor the curing process. The Al-Qadi-Cao-Abufares (ACA) model predicts AC density and moisture content accurately.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Construction & Building Technology
Zehui Zhu, Imad L. Al-Qadi
Summary: This article proposes a deep neural network, CrackPropNet, for measuring crack propagation on asphalt concrete (AC) specimens. It offers an accurate, flexible, efficient, and low-cost solution using images collected during cracking tests. CrackPropNet differs from traditional deep learning networks by learning to locate displacement field discontinuities through feature matching in reference and deformed images. It achieved high F-1 scores on the testing dataset and showed promising generalization on different images. The CrackPropNet can accurately and efficiently detect complex crack patterns in AC cracking tests, making it useful for characterizing cracking phenomena and validating theoretical models.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Engineering, Civil
Jose Rivera-Perez, Imad L. Al-Qadi
Summary: Asphalt concrete (AC) balanced mix design (BMD) is used to control pavement cracking and rutting potential by selecting aggregate gradation, component volumetrics, and binder content. This study proposes an autoencoder deep neural network (ADNN) to develop optimized AC mix design alternatives that can meet a prescribed flexibility index (FI) and rut depth (RD). The autoencoder learns the patterns in the input data and creates a compressed representation of the AC mix design. Models were trained using a database of 5,357 data sets to predict binder content and aggregate gradation based on target mix type, FI, and RD.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Civil
Ester Tseng, Imad L. Al-Qadi, Erol Tutumluer, Issam I. A. Qamhia, Hasan Ozer
Summary: This paper presents case studies to demonstrate that appropriately designed and constructed flexible pavements can withstand climatic changes. Techniques such as mechanically or chemically stabilized subgrade, proper drainage, and minimizing plastic fines in unbound layers can effectively control moisture damage.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Civil
Imad L. Al-Qadi, Angeli Jayme, Egemen Okte
Summary: The Georgia Department of Transportation (GDOT) has successfully used a combination of open-graded friction course (OGFC) and stone-matrix asphalt (SMA) layers on its Interstate highways for over two decades. Through life-cycle assessment and cost analysis, GDOT compared the environmental and economic impacts of different resurfacing cycles on a section of Interstate 95. The evaluation showed that the SMA and micro-milling combination had positive outcomes in terms of field performance, environmental impacts, and long-term economic benefits.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Civil
Izak M. Said, Imad Al-Qadi
Summary: A framework for incorporating dynamic loading in pavement design is introduced, consisting of five main steps. Input parameters are determined, and a database of critical pavement responses is built using finite element models. AASHTOWare's transfer function is used to predict pavement damage and calculate the international roughness index. The load spectrum is adjusted to include roughness-induced dynamic loading. A simple analytical dynamic-loading model is developed, and multiple case studies were performed, validating the outcome.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Civil
Xiuyu Liu, Imad L. Al-Qadi
Summary: This paper presents an integrated vehicle-pavement approach and investigates the excess fuel consumption of a seven-DOF full-car model on rough pavements. The study concluded that overlooking local roughness variance may underestimate excess fuel consumption by 30%. Compared with a 2D half-car model, a 3D full-car model reduces computation error of excess fuel consumption by approximately 11%.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2023)
Article
Engineering, Civil
Watheq Sayeh, Imad L. Al-Qadi
Summary: Pay for Performance (PFP) is a statistical-based quality assurance specification used to evaluate asphalt concrete construction. The study analyzed data from highway construction seasons in Illinois to determine variability trends. The results showed that reducing density standard deviation led to an increase in pay factor. If density standard deviation had been reduced, the average increase in pay per project would be $38,000.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2023)
Article
Construction & Building Technology
Jose Rivera-Perez, Alireza Talebpour, Imad L. Al-Qadi
Summary: This study developed two deep learning models to predict the flexibility index and rut depth in the asphalt concrete mix design. The models were trained based on a large database and Monte Carlo Dropout simulations were used to compute the distribution of predicted results. The developed models provide more accurate predictions for AC mix design.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Engineering, Civil
Zehui Zhu, Imad L. Al-Qadi
Summary: This study proposes a framework for detecting surface cracks in asphalt concrete specimens using two-dimensional digital image correlation (DIC). The framework addresses the decorrelation issue caused by deformation and discontinuities, and detects cracks based on displacement fields. The framework can accurately measure strains and determine crack development. It can be used to study cracking phenomena, evaluate fracture properties, assess testing protocols, and develop theoretical models.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2023)
Article
Engineering, Civil
Aravind Ramakrishnan, Imad L. Al-Qadi
Summary: The axle load limits for single and tandem axles were assessed using an advanced finite element model. It was found that the distresses caused by tandem axles were greater than those caused by single axles. The load equivalency was found to be dependent on various parameters such as tire type, pavement material, and structure.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2023)
Article
Construction & Building Technology
Babak Asadi, Ramez Hajj, Imad L. Al-Qadi
Summary: This paper presents a probabilistic model for predicting the dynamic modulus of asphalt concrete using a Bayesian Neural Network. The model successfully predicted unseen testing datasets and enhanced interpretability through SHAP analysis.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Engineering, Civil
Jose J. Rivera-Perez, Imad L. Al-Qadi
Summary: This study evaluated the impact of asphalt concrete properties on flexibility index and rut depth by collecting extensive I-FIT and HWTT test results and conducting data analysis and feature ranking. The results identified the critical properties that significantly influenced flexibility index and rut depth, providing guidance for AC mix designers to achieve the required cracking and rutting performance by controlling mix design parameters.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2023)