Abstract
Grouting is an essential technique for managing settlement and rectifying uneven subsidence in construction. Despite its significance, determining grouting parameters primarily relies on empirical experience, resulting in a lack of systematic and scientifically grounded methodologies. Thus, it is crucial to utilize numerical calculation methods to evaluate the effectiveness of grouting under various conditions. The calculation outcomes indicate that the formation pressure and grouting duration are critical factors that influence the expansion of the grout material. Notably, the relationship between formation pressure and the extent of grouting reinforcement displays an exponential pattern while it is inversely proportional to the reinforcement range. Building upon these analytical results, a comprehensive design framework for grouting schemes is proposed to enhance the uniformity and effectiveness of the grouting intervention. This approach optimizes the grouting process and contributes to the built environment's overall stability and structural integrity.
Key Words
building lifting; design process; formation pressure; grouting; numerical calculation
Address
Xuedong Cui: Beijing Hengxiang Hongye Foundation Reinforcement Technology Co. Ltd, Beijing 10000 China
Abstract
Abrasive water jet (AWJ) cutting technology is considered an effective method to assist shield tunnels in
crossing reinforced concrete obstacles. In this study, experiments using AWJ to cut rebars and concrete under
submerged conditions were conducted. The results showed that under submerged conditions the AWJ cutting depth
of the concrete was much greater than that of the rebars. The efficient cutting parameters were as follows: a traverse
speed of less than 2 m/min, standoff distance of less than 5 cm, and abrasive flow rate of 1100 g/min. The damage
modes at the top, middle, and bottom of the rebars were primarily deformation wear, shear wear, and a mixture of
deformation and shear wear, respectively. The order of importance of the influence of the submerged AWJ cutting
parameters on the cutting depth of the rebars was as follows: the traverse speed, standoff distance, nozzle diameter,
pump pressure, and abrasive flow rate. A prediction model for the cutting depth of the rebars was established, with an
average absolute percentage error of about 15%. On this basis, suggestions that can provide guidance for practical
engineering applications of effective AWJ-assisted cutting of reinforced concrete in shield tunneling projects are
given.
Key Words
abrasive water jet; mechanism analysis; predictive model; reinforced concrete; submerged
condition
Address
Xinjie Huang:State Key Laboratory of Tunnel Engineering, Shandong University, Jinan 250061, Shandong, China;
Institute of Geotechnical and Underground Engineering, Shandong University,
Jinan 250061, Shandong, China;
Shangrong Song, Yanzhao Feng: Sinohydro Bureau 6 Co., Ltd., Shenyang 110179, Liaoning, China
Mengmeng Hu. Biao Li, Bin Xu, Senlin Yang: State Key Laboratory of Tunnel Engineering, Shandong University, Jinan 250061, Shandong, China;
Institute of Geotechnical and Underground Engineering, Shandong University,
Jinan 250061, Shandong, China
Bo Zhang: State Key Laboratory of Tunnel Engineering, Shandong University, Jinan 250061, Shandong, China;
School of Future Technology, Shandong University, Jinan 250061, Shandong, China
Abstract
Bentonite clay is frequently utilized in combination with sand as an effective barrier material for sealing
and preventing the migration of contaminants in geo-environmental projects. This study investigates the impact of
lead and copper nitrate contamination under varying pH levels and exposure durations on the geotechnical and
mineralogical properties of bentonite, as well as the strength behavior of a sand-bentonite mixture with 20%
bentonite content. To this end, changes in the pH and Atterberg limits of bentonite contaminated with the
aforementioned pollutants were examined at initial pH values of 3, 4, and 6 over exposure periods of 0, 7, 14, and 28
days. X-ray diffraction (XRD) analysis was performed on contaminated bentonite samples to explore the correlation
between the altered geotechnical behavior of the bentonite [the primary reactive component of the soil mixture] and
its mineralogical changes. The results indicated that the presence of heavy metal contaminants lowered the soil pH,
thereby increasing its acidity. Furthermore, as the soil acidity increased, the plasticity index (PI) decreased, with lead
exerting a more pronounced effect on this reduction. Unconfined compressive strength (UCS) tests revealed that
samples exhibited lower strength in more acidic environments; however, both the type of heavy metal and the
resulting acidity levels influenced the magnitude of strength reduction. Finally, XRD analysis demonstrated that
heavy metal contamination can alter the mineralogical composition of bentonite, with lead showing a significantly
more substantial impact compared to copper.
Key Words
bentonite mineralogy; copper nitrate; Heavy metal contaminant; lead nitrate; unconfined
compressive strength
Address
Azam Kouhpeyma, Mahmoud Hassanlourad, Fouad Kilanehei: Department of Civil Engineering, Faculty of Engineering, Imam Khomeini International University (IKIU),
Qazvin, Iran
Abstract
The presence of fine particles can change the microstructure of sandy silts and thus affect their
mechanical properties. In this study, a series of undrained triaxial tests was conducted to investigate the monotonic
and cyclic behavior of sandy silts with fines content (FC) of 60%, 76%, and 92%. The different effective confining
pressures (o3' = 40, 60, 80, 100, 120, and 140 kPa) and cyclic stress ratios (CSR, od/2o'od/2o3' = 0.12, 0.18, 0.24, and 0.36)
were considered in the experiment study. The research results showed that the undrained shear strength of sandy silts
increased significantly with the increase of o
3', but decreased with the increase of FC. A larger amplitude and rate of
double amplitude axial strain and excess pore water pressure ratio were observed as the CSR increased. The
liquefaction resistance of the sandy silts initially decreased and then increased with the increasing o
3'. The lowest
liquefaction resistance was found in the cases of o
3' = 100 kPa. An increase in FC can delay the generation of excess
pore water pressure and enhance the liquefaction resistance of sandy silts under the cyclic loading. Two quantitative
relationships between the number of loading cycles to failure and the FC were established through nonlinear surface
fitting, respectively, considering the different cyclic stress ratios and effective confining pressures. The research
results can provide a reference for the liquefaction treatment of sandy silt foundations.
Key Words
axial strain; excess pore water pressure; fines content; liquefaction resistance; sandy silts
Address
Meng-Hui Huang, Zhen-Dong Cui, Li Yuan, Soomro Mukhtiar Ali: State Key Laboratory of Intelligent Construction and Healthy Operation & Maintenance of Deep Underground
Engineering, School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou,
Jiangsu 221116, P. R. China
Abstract
Dynamic Compaction (DC) is a widely adopted ground improvement technique, particularly effective
for granular soils. This study presents a hybrid approach combining fuzzy logic implemented via a Sugeno Inference
System and Particle Swarm Optimization (PSO) to estimate and enhance the effective depth of DC. A fuzzy model
was developed to evaluate the influence of key operational parameters, including tamper weight, drop height, radius,
number of drops, grid spacing, and soil resistance. A symbolic regression-based correlation was proposed to estimate
the improvement depth and was validated against the fuzzy model results. Parametric analysis revealed that the
interaction between tamper weight and drop height is the most influential factor. Optimization using PSO resulted in
a 33% increase in the maximum improvement depth without additional energy input. In addition, optimal design
parameters were identified, including a tamper radius of 1.5–2.0 m, 25 drops per point, and a grid spacing of 6–7 m.
This hybrid AI-based framework offers a practical alternative to conventional empirical DC design and demonstrates
promising capability for improving design efficiency and parameter selection.
Address
Hamid Koohsari, Hamid Alielahi: Department of Civil Engineering, Za.C., Islamic Azad University, Zanjan, Iran
Amir Najafi: Department of Industrial Engineering, NT.C, Islamic Azad University, Tehran, Iran
Mohammad Adampira: Department of Civil Engineering, SR.C., Islamic Azad University, Tehran, Iran
Abstract
This study presents a system reliability analysis of a gravity retaining wall (R-Wall) subjected to varying
seismic conditions using a sequential compounding method integrated with deterministic and artificial intelligence
approaches. Three primary failure modes, sliding (SL), overturning (OT), and bearing capacity (BC), were evaluated
under five horizontal seismic coefficients (KH = 0.10 to 0.18) through deterministic analysis and validated using
Artificial Neural Network (ANN) models. The reliability index (B), calculated using the First-Order Second Moment
(FOSM) method, revealed that overturning is the most critical failure mode, with B declining sharply beyond KH =
0.12. In contrast, SL and BC retained relatively higher B values (9.38–4.46 and 13.45–6.87, respectively). The
overall Bsystem decreased drastically from 5.99 to 0.13, indicating increasing structural vulnerability under stronger
seismic loads. ANN models with architectures 4-15-1 (SL and OT) and 7-15-1 (BC) showed excellent predictive
performance (R2 > 0.999, RMSE < 0.005), closely replicating deterministic and system reliability outcomes.
Monotonicity analysis further quantified the influence of input parameters on wall stability, highlighting kH and ob
as dominant contributors, while rb had minimal effect. Across all cases, the ANN model effectively captured
complex nonlinear relationships, offering valuable insights for optimized and safer design of retaining structures
under seismic loading.
Key Words
ANN; bearing capacity; overturning; sequential compounding method; sliding; system
reliability
Address
Md Shayan Sabri, Amit Kumar Verma, Nitish Kumar, T. N Singh: Department of Civil and Environmental Engineering, Indian Institute of Technology Patna,
Bihar, 801106, India
