Summary Geophysics and Geotechnical Engineering commonly use one-dimensional (1D) wave propagation analysis, simplifying complex scenarios by assuming flat and homogeneous soil layers, vertical ...seismic wave propagation, and negligible pore water pressure effects (total stress analysis). These assumptions are commonly used in practice, providing the basis for applications like analyzing site responses to earthquakes and characterizing soil properties through inversion processes. These processes involve various in-situ tests to estimate the subsurface soil’s material profile, providing insights into its behavior during seismic events. This study seeks to address the limitations inherent to 1D analyses by using three-dimensional (3D) physics-based simulations to replicate in-situ tests performed in the Argostoli basin, Greece. Active and passive source surveys are simulated, and their results are used to determine material properties at specific locations, employing standard geophysical methods. Our findings underscore the potential of 3D simulations to explore different scenarios, considering different survey configurations, source types, and array sets.
In the Cigéo project for deep geological of radioactive waste, the project manager has to follow the convergence of tunnel (cells) cross-section built at 490 m depth. This convergence is due to the ...mechanical pressure in the rock layer. Vibrating Wire Extensometers (VWE) are ised to measure the strain at their locations. Our objective is to optimize the location of sensors to estimate the horizontal stress due to strain observations. This issue is solved using an inverse problem, which first requires the creation of a direct model that represents the bahviour of a cross-section. From rock data measured on site, thanks to an underground demonstrator, a numerical model is developed to generate s strain database for different VWE locations with different rock stresses and rigidities. The theoritical orientation of the sensors is orthoradial, but they can have angle and intrinsic errors. Considering various types of uncertainties, an inverse model based on Bayesian approach is developped to calculate the probability distribution of stresses. The last step is to use a genetic algorithm to determine the optimal sensor distribution. The best sensor placements is found to be near the kidneys, i.e. at more or less 45° around 0° and 180°.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any ...defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear wave velocity and frequency. The collected data, including compressive and shear wave velocity, frequency and derived material properties as well as modulus of elasticity, were used for subsequent analyses. To determine the type of defect, artificial intelligence and machine learning methods were utilized. Data collected from the impact echo method were analyzed using RStudio and the MATLAB toolbox for statistical analysis. Linear regression was employed to establish relationships between inputs (wave velocity and frequency) and outputs as shear and compressive modulus. The accuracy of these relationships was assessed through correlation coefficients, p-values and adjusted R-squared error. Additionally, an Imperial Competitive Algorithm (ICA) as part of the artificial neural network method was implemented to predict the variables. The results demonstrated high correlation coefficients and low mean square errors, indicating accurate predictions. Frequency domain defect detection was performed by analyzing frequency-amplitude data. The MATLAB toolbox was used to identify peaks and determine defects based on a 20% boundary condition. The comparison of peaks confirmed the presence of defects in beams with voids, corrosion and debonding. Subsequently, support vector machines were employed to classify defects in reinforced concrete structures, including voids, corrosion and debonding. This study utilized key features of reinforced concrete and assessed SVM performance using precision, recall and F1-score metrics. Overall, this study illustrates the effectiveness of machine learning techniques complied with impact echo tests in assessing and predicting the quality of reinforced concrete beams with various internal defects.
This paper takes place in improving the energy performance assessment of cob buildings, by evaluating thevariability of its hygrothermal properties at the material scale, related to the traditional ...construction process. Forso, we proposed and analysed data to handle the variability of the hygrothermal properties. The specimens weremanufactured using a moulding method representative of on-site cob wall manufacturing process, for three plants species (hemp shiv, flax yarn and hay stalk) and three fibre content (0, 1% and 3%). Using non-destructivetests and statistical analysis, the random variability of cob composites hygrothermal properties (density, thermalconductivity, specific heat capacity, water-vapor permeability, moisture buffering value and sorption isotherms)was found as well as the variability distribution. It has been shown that the variability of properties is sensitive tothe nature of plant fibres specie and the fibre content. Using the variability indicators, it has been found on thermal conductivity, a low coefficient of variation of 2.88% for 1%-flax fibred mixture (lower than unfibred material) and a high one for 3%-hemp composites of 10.88%. The variability of sorption isotherms was usually found to be high at lower humidity loads. It has been shown that increase fibre content stabilizes the variability of properties. Moreover, some evolution trends of the variability according to mixes was proposed; two parameters were found: the first, either FCmax highlighting the fibre content for which the maximum of variability was achieved or FCmin for the opposite; the second is FCres highlighting the residual variability, for high fibre content. The distribution of properties were found to be generally centered.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This book is a compilation of selected papers from the 10th PIANC Smart Rivers Conference (Smart Rivers 2022). The work focuses on novel techniques for inland waterways and navigation structures. The ...contents make valuable contributions to academic researchers, engineers in the industry, and regulators of aviation authorities. As well, readers will encounter new ideas for realizing Green Waterways and Sustainable Navigations. This is an open access book.
Stringent measures by water authorities worldwide on water clarification has resulted in the use of chemical-based coagulants to be a formidable challenge. This has driven the need to find ...alternative sustainable coagulants such as plant-based bio coagulants which are readily available, abundant and cost effective in developing countries such as Zimbabwe. In this regard, the effectiveness of treating effluent from a brewery malting processing plant using bio-coagulants (
Aloe vera, Cactus opuntia and Okra seeds
) was investigated compared to that of a chemical coagulant (Alum). The water pollution parameters that were investigated include turbidity, total dissolved solids, electrical conductivity, temperature and pH. The results showed that Alum was the most effective coagulant as it reduced the turbidity from 734 NTU to 68.3 NTU and Total Dissolved Solids (TDS) from 19,800 ppm to 880 ppm at a dosage of 40 mg/L.
Okra seeds
had an optimum dosage of 35 mg/L with a turbidity and TDS removal of 88.83% and 95.25% respectively. Aloe Vera had an optimum dosage of 40 mg/L with a turbidity and TDS removal of 74.25% and 95.40% respectively. For
Cactus opuntia
it was 50 mg/L obtaining turbidity and TDS removal of 74.66% and 95% respectively. The best blend of the bio coagulants had a ratio of (0.17, 0.17, and 0.67) for
Aloe vera, Cactus opuntia and Okra seeds
respectively. At a dosage of 40 mg/L the turbidity removal was 83.92% and TDS removal was 95.12%. The results indicated that blending the plant-based coagulants had a positive synergistic effect.
Graphical Abstract
Highlights
Aluminium sulphate (Alum) is more effective in reduction of suspended solids and dissoved solids compared to
Aloe vera, Cactus and Okra seeds.
The effectiveness of
Aloe vera, Cactus and Okra seeds as plant-based coagulants
indicates that they have active compounds effective as coagulation agents.
There were positive synergistic effects upon blending
Aloe vera, Cactus and Okra seeds
this was observed in the reduction of turbidity this was higher than when
Aloe vera and Cactus
were used individually as coagulants.
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