Indian geotechnical journal, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 28, 2024
Language: Английский
Indian geotechnical journal, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 28, 2024
Language: Английский
SSRN Electronic Journal, Journal Year: 2024, Volume and Issue: unknown
Published: Jan. 1, 2024
Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI
Language: Английский
Citations
3Transportation Geotechnics, Journal Year: 2024, Volume and Issue: unknown, P. 101387 - 101387
Published: Oct. 1, 2024
Language: Английский
Citations
3Construction and Building Materials, Journal Year: 2024, Volume and Issue: 445, P. 137794 - 137794
Published: Aug. 22, 2024
Language: Английский
Citations
2Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2023, Volume and Issue: 7(3), P. 2147 - 2161
Published: Dec. 27, 2023
Language: Английский
Citations
6Published: Dec. 11, 2023
Premature failure and degradation of layers are the main problems for transportation infrastruc-ture. Addressing these issues necessitates implementing structural health monitoring (SHM) layers. This strategic approach is instrumental in mitigating maintenance expenses, prolonging operational lifespan, preventing accidents resulting from abrupt layer col-lapse. To this end, research investigated stress/strain damage detection capabilities a self-sensing cementitious composite developed potential utilization construction an intelligent subgrade layer. The prepared consisted 10% cement hybrid conductive fillers, including multiwalled carbon nanotubes (MWCNTs) graphene nanoplatelets (GNPs) sand. Initial findings reveal that electrical resistivity significantly affected by concentration MWCNTs/GNPs, with minimum more than 0.5% needed to achieve responsive composite. More-over, piezoresistive analysis indicates increase MWCNTs/GNPs stress levels leads improvement sensing perfor-mance. When subjected equivalent levels, variations FCR exhibit increasing trend decreasing resilient modulus, stemming decrease stiffness due increased MWCNTs/GNPs. Additionally, EIS demonstrates contraction Nyquist curves under compressive ramp loading prior failure, followed expansion postfailure. Scanning electron microscopy (SEM) images visually showcase bridging effects MWCNTs filling ef-fects GNPs within structure.
Language: Английский
Citations
1Journal of Engineering Sciences, Journal Year: 2024, Volume and Issue: 11(1), P. H1 - H8
Published: Jan. 1, 2024
Large quantities of polyethylene terephthalate (PET) plastic are discarded into the environment during production, application, and disposal. Although current clean-up strategies aim to mitigate adverse impacts PET pollution, efforts struggle keep up with escalating amount waste. This accumulation waste poses significant threats ecosystems worldwide. One recycling method for involves its utilization in soil reinforcement applications within civil engineering. By incorporating reinforce poor-quality sands, sustainable construction practices can be promoted engineering infrastructures, addressing multiple aspects sustainability, including engineering, economic, social, environmental considerations. The experimental work conducted this research involved sieve analysis, proctor compaction test, California Bearing Ratio (CBR) direct shear box test. sand was reinforced varying percentages flakes, namely 5, 10, 15 %, respect weight sample taken laboratory tests were performed on samples. Including flakes enhanced various properties, such as strength friction angle. It also improved CBR value composite, making it suitable pavement construction. reduction dry density further supports application composite lightweight structures. In conclusion, geotechnical material obtained from soil-PET utilized projects, landfills slope stabilization.
Language: Английский
Citations
0International Journal of Advanced Computer Science and Applications, Journal Year: 2024, Volume and Issue: 15(6)
Published: Jan. 1, 2024
Artificial intelligence algorithms have become much more sophisticated, so the most complex and challenging problems can be solved with them. California Bearing Ratio (CBR) is a time-consuming testing parameter, univariate multivariate regression methods are used to address this challenge. Therefore, CBR value an essential parameter in indexing resistance provided by structure's subterranean formation or foundation soil. crucial factor pavement design. However, its determination laboratory conditions process. This makes it necessary look for alternative method estimate soil subgrade, especially developed layers of study has one machine learning (ML) models, including Random Forest (RF), predict CBR. Additionally, some meta-heuristic been improving accuracy optimizing output prediction, consisting Gold Rush optimizer (GRO), Stochastic Paint (SPO), Electrostatic Discharge algorithm (EDA). The results hybrid models were compared via criteria choose desired model. SPO had desirable performance when coupled RF other optimizers, exhibiting high R2 low RMSE.
Language: Английский
Citations
0Environmental Challenges, Journal Year: 2024, Volume and Issue: 16, P. 100998 - 100998
Published: Aug. 1, 2024
Language: Английский
Citations
0Indian geotechnical journal, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 28, 2024
Language: Английский
Citations
0