Utilization of Geotextile Tube for Sandy and Muddy Coastal Management: A Review

Threats to beaches have accelerated the coastal destruction. In recent decades, geotextile tubes were used around the world to prevent coastal erosion, to encourage beach nourishment, and to assist mangrove rehabilitation. However, the applications of geotextile tube in sandy and muddy coasts have different concerns as the geological settings are different. Applications of geotextile tubes in sandy beaches were mainly to prevent coastline from further erosion and to nourish the beach. However, for the muddy coasts, mangrove rehabilitation and conservation were additional concerns in coastal management schemes. The mangrove forests are natural barriers which can be found on the muddy coasts of many tropical countries. In this paper, the viability of geotextile tubes in sandy and muddy beaches was analysed. The advantages and disadvantages of the utilization of geotextile tubes in coastal management were discussed based on the experiences from the tropical countries such as Mexico, Malaysia, and Thailand. From the case studies, impressive improvements in coastal restoration after installation of geotextile tubes were shown. Based on the discussion, several recommendations to improve the application of geotextile tubes were suggested in this paper

Performance-Based Evaluation of a Double-Deck Tunnel and Design Optimization

The double-deck tunnel is well known as smart infrastructure because multiple sections can be used for various purposes. Although the stability of a double-deck tunnel is mainly governed by the intermediate slab, the effect of various governing factors on tunnel structural stability has not been fully investigated. In this study, performance-based evaluation method for a double-deck tunnel is suggested as a three-dimensional matrix considering the life cycle of a double-deck tunnel. Moreover, a customized software for design and maintenance of a double-deck tunnel is developed. A structural analysis solver based on a beam–spring model for a double-deck tunnel was embedded in this code. The effects of connection type as well as depth of tunnel, ground stiffness and traffic load on structural behavior of tunnel were investigated. From the analysis, it was found that the connection type between segment lining and intermediate slab significantly affects the behavior of segment lining: simply connected condition causes lesser stress and moment than fully fixed condition. The deeper the tunnel depth, the greater the member force of segment lining. In addition, as both the tunnel depth and the ground stiffness increase, the influence of connection type on the structural stability of the double-deck tunnel becomes insignificant

Chemical composition and antibacterial activity of some herbal essential oils against Streptococcus mutans

Background and aims: One of the most common chronic diseases in the world is tooth decay. A variety of bacteria are involved in this disorder of which Streptococcus mutants is the most common. Essential oils are considered as new natural compounds for use in combating drug-resistant bacteria. This study was aimed to evaluate the antibacterial activity of some essential oils prepared from Eucalyptus caesia Benth, Cuminum cyminum L. and Satureja hortensis L. on S. mutants. Methods: In this study, essential oils were extracted by hydrodistillation method. E. caesia Benth, C. cyminum L. and S. hortensis L. were characterized by using gas chromatography‒mass spectrophotometry (GC‒MS). Antibacterial activity indices including minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC) and zone of inhibition for the above essential oils against Streptococcus mutans were determined using broth macro-dilution and disk diffusion methods. Data analysis was performed using one-way ANOVA and Tukey test. Results:Results showed that all three extracts had antibacterial activity against S. mutants. S. hortensis L. essential oil with the lowest MIC and MBC value (13.2 and 18.4 µg/ml, respectively) and the biggest inhibition zone showed the strongest antibacterial effect against S. mutants in all exposure times and at all concentrations, compared with two other essential oils. Furthermore, C. cyminum L. essential oil had higher anti-bacterial activity against S. mutant than E. caesia Benth essential oil. Conclusions:The essential oils used in the present study with different components showed antibacterial activity (especially S. hortensis L essential oil), and therefore they can be used as a new antibacterial substance. Keywords: Dental caries, Streptococcus mutans, Essential oils, Antimicrobial

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering

This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. &nbsp

Bearing capacity prediction of shallow foundation on sandy soils:a comparative study of analytical, FEM, and machine learning approaches

In this study, we compared the Ultimate Bearing Capacity (UBC) of shallow foundations on sandy soils that were predicted using Analytical, Finite Element Modeling (FEM), and Machine Learning (ML) approaches for predicting the Ultimate Bearing Capacity (UBC) of shallow foundations on sandy soils. For the first of its type, we presented a novel Python-based pipeline that enables rapid and precise estimation of the UBC for shallow foundations, surpassing traditional methods by providing superior speed and accuracy. The proposed models consider the foundations’ geometry and soil properties as input parameters. We created, trained, and tested nineteen ML models using the Pycaret library in the Google Colab environment. Furthermore, we conducted a comparative analysis of twelve new datasets derived from the training process. Our objective was to estimate the UBC values using three established techniques: (a) the widely recognized Terzaghi method, (b) the advanced three-dimensional FEM software (using OptumG3 software), and the ML-based method. Based on the ML results, we found that Gradient Boosting Regression (gbr), AdaBoost Regression (ada), Random Forest Regression (rf), and Extra Tree Regression (et) were the most effective models for estimating UBC. The gbr model exhibited the highest UBC prediction performance, attaining an R2 value of 1 on the training set, an R2 value of 0.937 on the test set, and an RMSE of 1.171 kPa. Using sensitivity analysis results, we demonstrated that the internal friction angle of the soil is the most significant input variable for estimating UBC, closely followed by the depth of the footing. The comparative results revealed that the well-known Terzaghi method and FEM modeling underestimate the UBC. The proposed user-friendly pipeline would be a valuable tool for geotechnical engineers to predict UBC values, providing a larger dataset in future research that can be trained and tested for the model to enhance reliability further

FEM-based modelling of stabilized fibrous peat by end-bearing cement deep mixing columns

This study aims to simulate the stabilization process of fibrous peat samples using end-bearing Cement Deep Mixing (CDM) columns by three area improvement ratios of 13.1% (TS-2), 19.6% (TS-3) and 26.2% (TS-3). It also focuses on the determination of approximate stress distribution between CDM columns and untreated fibrous peat soil. First, fibrous peat samples were mechanically stabilized using CDM columns of different area improvement ratio. Further, the ultimate bearing capacity of a rectangular foundation rested on the stabilized peat was calculated in stress-controlled condition. Then, this process was simulated via a FEM-based model using Plaxis 3-D foundation and the numerical modelling results were compared with experimental findings. In the numerical modelling stage, the behaviour of fibrous peat was simulated based on hardening soil (HS) model and Mohr-Coulomb (MC) model, while embedded pile element was utilized for CDM columns. The results indicated that in case of untreated peat HS model could predict the behaviour of fibrous peat better than MC model. The comparison between experimental and numerical investigations showed that the stress distribution between soil (S) and CDM columns (C) were 81%C-19%S (TS-2), 83%C-17%S (TS-3) and 89%C-11%S (TS-4), respectively. This implies that when the area improvement ratio is increased, the share of the CDM columns from final load was increased. Finally, the calculated bearing capacity factors were compared with results on the account of empirical design methods