Seyma Ordu

The conformal fractional derivative (CFD) has become a hot research topic since it has a physical interpretation and is easier to grasp and apply to problems compared with other fractional derivatives. Its application to heat transfer, diffusion, diffusion-advection, and wave propagation problems can be found in the literature. Fractional diffusion equations have received great attention recently due to their applicability in physical, chemical, and biological processes and engineering. The diffusion of the pollutants within the ground, which is an important environmental problem, can be modeled with a diffusion equation. Diffusion in some porous materials or soil can be modeled more accurately with fractional derivatives or the conformal fractional derivative. In this study, the diffusion problem of a spilled pollutant leaking into the ground modeled with the conformal fractional time derivative in spherical coordinates has been solved analytically using the Fourier series for a constant mass flow rate and complete symmetry under the assumptions of homogeneous and isotropic soil, constant soil temperature, and constant permeability. The solutions have been simulated spatially and in time. A parametric analysis of the problem has been performed for several values of the CFD order. The simulation results are interpreted. It has also been suggested how to find the parameters of the soil to see whether the CFD can be used to model the soil or not. The approach described here can also be used for modeling pollution problems involving different boundary conditions.

This study presents a novel method for predicting the undrained shear strength (c_u) using artificial intelligence technology. The c_u value is critical in geotechnical applications and difficult to directly determine without laboratory tests. The group method of data handling (GMDH)-type neural network (NN) was utilized for the prediction of c_u. The GMDH-type NN models were designed with various combinations of input parameters. In the prediction, the effective stress (σ_v’), standard penetration test result (N_SPT), liquid limit (LL), plastic limit (PL), and plasticity index (PI) were used as input parameters in the design of the prediction models. In addition, the GMDH-type NN models were compared with the most commonly used method (i.e., linear regression) and other regression models such as random forest (RF) and support vector regression (SVR) models as comparative methods. In order to evaluate each model, the correlation coefficient (R²), mean absolute error (MAE), and root mean square error (RMSE) were calculated for different input parameter combinations. The most effective model, the GMDH-type NN with input parameters (e.g., σ_v’, N_SPT, LL, PL, PI), had a higher correlation coefficient (R² = 0.83) and lower error rates (MAE = 14.64 and RMSE = 22.74) than other methods used in the prediction of c_u value. Furthermore, the impact of input variables on the model output was investigated using the SHAP (SHApley Additive ExPlanations) technique based on the extreme gradient boosting (XGBoost) ensemble learning algorithm. The results demonstrated that using the GMDH-type NN is an efficient method in obtaining a new empirical mathematical model to provide a reliable prediction of the undrained shear strength of soils.

Tr en Türk Çimento Sektörü, endüstriyel ve evsel nitelikli atıkları lisanslı tesislerinde alternatif yakıt veya hammadde olarak kullanabilmektedir. Alternatif yakıt ve hammadde kullanımının artması çevre kirliliğinin önlenmesi, doğal kaynakların ve enerjinin tasarruf edilmesi açısından oldukça önemlidir. Alternatif yakıtlar genel olarak arıtma çamuru, atık yağ, ömrünü tamamlamış lastikler, solvent ve boya grupları altında toplanabilir. Alternatif hammaddeler ise maden atıkları, ısıl işlem atıkları, inşaat atıkları grupları altında değerlendirilebilir. Bu çalışmanın amacı, alternatif hammadde ve alternatif yakıt kullanımının ve çevresel yararlarının değerlendirilmesidir. Bu amaçla, örnek olarak seçilen bir çimento tesisinde, 2013-2015 yıllarında kabul edilen atıklar, kabul öncesi yapılan analizler, kullanılan alternatif hammaddelerin ve yakıtların miktarları ve maliyete olan etkileri incelenmiştir. Çimento fabrikasında alternatif hammadde olarak demir koku, grid, döküm kumu ve fosfojips, kalite parametrelerine uyumlu bir şekilde geri kazanılmaktadır. Alternatif hammadde kullanımı maliyet olarak tesise toplamda 7.031.998 TL kazanç sağlamıştır. Alternatif yakıt olarak arıtma çamuru kullanılmaktadır. Arıtma çamuru kullanımının maliyet olarak tesise kazancı 200.514.450 TL olmuştur. Turkish Cement Sector uses industrial and domestic wastes as alternative fuels or raw materials in licensed facilities. Increasing use of alternative fuels and raw materials is very important in terms of eliminating environmental pollution, saving natural material resources and energy. Alternative fuels can generally be gathered under the groups of sewage sludge, waste oil, worn out tires, solvent and paints. As for alternative raw materials, they can be evaluated undermine waste, heat treatment waste, construction waste groups. The aim of this study is to evaluate the use of alternative raw materials and fuels and their environmental benefits. For this purpose, in a cement plant selected as a case study, wastes accepted between 2013 and 2015, pre-acceptance analyzes, quantities of alternative raw materials and fuels used, and their financial impacts are examined. Iron scent, grid, casting sand and phosphogypsum are recycled as an alternative raw material in the cement plant in accordance with quality parameters. The use of alternative raw materials resulted in savings totaling 7.031.998 TL for the plant. As alternative fuel, sewage sludge is used. The financial benefit of sewage sludge usage to the plant is 200.514.450 TL.