Ercan Özgan

Artificial neural network based modelling of the Marshall Stability of asphalt concrete

Research highlight? Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modelled by using artificial neural network. In order to investigate the MS based on physical properties, exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6 h and temperatures of 30oC, 40oC and 50oC were selected. At the environment temperature of 17oC the stability of the asphalt core samples decreased by 40.16 % at 30oC after 1.5 h and 62.39% after 6h. At 40oC, the decrease was 74.31% after 1.5h and 78.10 % after 6h. At 50oC the stability of the asphalt decreased by 83.22 % after 1.5h, and 88.66 % after 6h. Experiment results and ANN model exhibited good correlation, ANN method could be used to model the MS. In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modeled by using artificial neural network. In order to investigate the MS based on physical properties, exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6h and temperatures of 30?C, 40?C and 50?C were selected. The results showed that at the environment temperature of 17?C the stability of the asphalt core samples decreased by 40.16% at 30?C after 1.5h and 62.39% after 6h. At 40?C, the decrease was 74.31% after 1.5 and 78.10% after 6h. At 50?C the stability of the asphalt decreased by 83.22% after 1.5h, and 88.66% after 6h. Experiment results and ANN model exhibited good correlation for this reason the ANN method could be used to model the MS.

Fuzzy logic and statistical-based modelling of the Marshall Stability of asphalt concrete under varying temperatures and exposure times

In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modelled by using fuzzy logic and statistical method. This is an experimental study conducted using statistics and fuzzy logic methods. In order to investigate the Marshall Stability of asphalt concrete based on exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6h and temperatures of 30, 40 and 50^oC were selected. The MS of the asphalt concrete at 17^oC (in laboratory environment temperature) was used as reference. The results showed that the MS of the asphalt core samples decreased 40.16% at 30^oC after 1.5h and 62.39% after 6h. At 40^oC the decrease was 74.31% after 1.5h, and 78.10% after 6h. At 50^oC the stability of the asphalt decreased 83.22% after 1.5h, 88.66% after 6h. The relationships between experimental results, fuzzy logic model and statistical results exhibited good correlation. The correlation coefficient was R=0.99 for fuzzy logic model and R^2=0.9 for statistical method. Based on the results of the study, it could be said that both the fuzzy logic method and statistical methods could be used for modelling of the stability of asphalt concrete under varying temperature and exposure time.

Adaptive neuro-fuzzy inference approach for prediction the stiffness modulus on asphalt concrete

In this study, stiffness modulus parameters of asphalt concrete were determined experimentally for different temperature and exposure times. The stiffness modules were calculated according to Nijboer stiffness module. Basic physical properties and the quantity of bitumen of asphalt core samples were designated for determining the stiffness modules. The samples were exposed to 17^oC (reference temperature), 30, 40 and 50^oC temperatures for 1.5, 3, 4.5 and 6h respectively and then Marhall Stability tests were done for each samples. By using the test results a prediction model with Sugeno type based on the adaptive neuron-fuzzy inference system (ANFIS) was alternatively developed to predict the stiffness modules of asphalt core samples. As a result, it was seen that the developed prediction model could be used as a prediction model for unperformed situations which are not suitable for experiments.

Effects of Freezing and Thawing Cycles on the Engineering Properties of Soils

In this study, particular engineering characteristics of soil exposed to freezing and thawing cycles were investigated. Low plasticity clay (CL) soil samples (classified according to the USCS soil classification system) were sampled in situ, and some basic properties of these soil samples were investigated by performing sieve analyses, hydrometer tests, specific gravity tests, and liquid, plastic, and shrinkage limits tests. The same tests were also conducted after freezing and thawing cycles. Additionally, scanning electron microscope (SEM) tests to determine the microstructures of the soil samples and energy dispersive X-ray-EDX tests to determine the chemical compositions of the samples were performed. Finally, triaxial compression tests were conducted before and after the freezing and thawing cycles to determine the strength parameters of the soil samples. The experimental results show that the physical and mechanical properties of the soil changed significantly after the freezing and thawing cycles.

Short Communication: Modeling of asphalt concrete via simulated annealing

In this study, 65 asphalt core specimens taken from D100/11 state highway section in Turkey were examined for their physical properties in the laboratory. Analysis of data was conducted to determine the effects of the varying environment temperature and varying length of exposure to these temperatures on the stability of the asphalt core samples using destructive, Marshall, method. The asphalt core samples were determined using SPSS statistical program for modeling. Simulated annealing was implemented to determine a set of unknown parameters which best matched the asphalt concrete model predictions with experimental data. This modeling procedure can be used as a guideline for experiments to improve the stability of the asphalt concrete. The stability of the asphalt concrete is taken as the main objective function with respect to voids of volume, saturated unit volume weight, air dry unit volume weight, environment temperature, and exposure time.

Effects of Freezing and Thawing on the Consolidation Settlement of Soils

The effects of freezing and thawing on consolidation parameters and other properties of soil were investigated experimentally. Samples of soils were collected in-situ and characterized in the laboratory. Index properties of soil samples were determined by conducting sieve analyses, hydrometer tests, specific gravity tests, and liquid limit, plastic limit, and shrinkage limit tests before and after 30 freezing-thawing cycles. Microstructure and elemental composition of the soil samples were determined by scanning electron microscope (SEM) and energy dispersive X-ray (EDX) analysis, respectively. To determine the effects of freezing thawing onto the consolidation parameters of soil, consolidation tests were conducted on the samples before and after the freezing-thawing cycles. After 30 freezing-thawing cycles, consolidation settlements increased by about 23%.

The Investigation into the Effect of Hydrostatic Pressure on the Engineering Properties of Hardened Concrete

The aim of this study is to investigate the effect of hydrostatic pressure on the engineering properties of hardened concrete. To this end, a concrete column with dimensions of 100 cm width, 25 cm depth and 250 cm height was produced using C20 class concrete. While pouring the concrete, 15 cm reference cube samples were taken from the fresh concrete. After 28 days, 8 from the cube samples and 128 from different hydrostatic heights, in total 136 pieces of core samples with Ø100 mm diameter were taken and their compressive strength was determined. The average compressive strength of the reference core samples was 36.95 N/mm2 and the compressive strength of other samples changed between 37.3 N/mm2 and 43.0 N/mm2 according to the hydrostatic pressure. It was concluded that compressive strength changed between 0.95% and 16.37% according to the reference sample. Statistical analysis was conducted based on the experimental results. The compressive strength of the core samples related to its hydrostatic height and physical properties were predicted with a high reliability. A model equation was formed to convert the compressive strength of the core samples into reference compressive strength according to hydrostatic height and the convertibility coefficients were ascertained.

Prediction of concrete compressive strength in buildings that would be reinforced by fuzzy logic

In this study, core samples were taken from column or reinforced wall in order to make reinforcement or restoration. The effect of the element height and volume of voids of these samples to the compressive strength were investigated. C25 type ready to use concrete was used and a column without steel was produced. During the production process, 15 cm reference cube samples were taken from the fresh concrete. After 28 days, 8 cores from reference cubes and 128 samples from column were taken and their compressive strengths were determined. As a result, the average compressive strength of the reference core samples was 36.95 Mpa and according to the height compressive strengths of other samples was ranging between 37.3 and 43.0 Mpa. The ratio of the increasing of the compressive strength changes between 0.95 and 16.37% according to the reference sample. Based on the experimental results, fuzzy Logic method was used for modelling of the experimental results. The paper demonstrates that fuzzy logic can be successfully used in modelling the compressive strength of concrete for different height and volume of voids. This model enables us to easily and reliably estimate the compressive strength of concrete.