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http://repository.umy.ac.id/handle/123456789/24858
Wed, 19 Feb 2020 19:53:10 GMT2020-02-19T19:53:10ZEFFECT OF INPUT SOURCE ENERGY AND MEASUREMENT OF FLEXIBLE PAVEMENT DEFLECTION USING THE SASW METHOD
http://repository.umy.ac.id/handle/123456789/31734
EFFECT OF INPUT SOURCE ENERGY AND MEASUREMENT OF FLEXIBLE PAVEMENT DEFLECTION USING THE SASW METHOD
ISMAIL, NORFARAH NADIA; YUSOFF, NUR IZZI MD; NAYAN, KHAIRUL ANUAR M; RAHMAN, NORINAH ABD; ROSYIDI, SRI ATMAJA P; ISMAIL, AMIRUDIN
This paper presents the effect of input source energy on the results of spectral analysis of surface wave (SASW) evaluation of flexible pavements in terms of maximum and minimum wavelength. A series of surface wave tests, namely the SASW test, were done on asphalt pavement using four steel balls with different masses as sources. These sources were dropped from two different heights, 0.25 and 0.50 m. This test was also conducted with two different configurations, i.e. with the receivers positioned 0.15 and 0.30 m apart. This paper also presents the feasibility of using accelerometers to measure flexible pavement deflection. For this purpose, the process of integrating accelerometer time history is described. It is proved that a change in input source energy has some effect on the value of maximum and minimum wavelength. The result for numerical double integration is satisfactory and is congruent with the displacement obtained through finite element analysis.
Thu, 17 Oct 2019 00:00:00 GMThttp://repository.umy.ac.id/handle/123456789/317342019-10-17T00:00:00ZENGINEERING CHARACTERISTICS OF NANOSILICA/ POLYMER-MODIFIED BITUMEN AND PREDICTING THEIR RHEOLOGICAL PROPERTIES USING MULTILAYER PERCEPTRON NEURAL NETWORK MODEL
http://repository.umy.ac.id/handle/123456789/31732
ENGINEERING CHARACTERISTICS OF NANOSILICA/ POLYMER-MODIFIED BITUMEN AND PREDICTING THEIR RHEOLOGICAL PROPERTIES USING MULTILAYER PERCEPTRON NEURAL NETWORK MODEL
YUSOFF, NUR IZZI MD; ALMAHALI, DHAWO IBRAHIN; IBRAHIM, AHMAD NAZRUL H; ROSYIDI, SRI ATMAJA P; HASSAN, NORHIDAYAH ABDUL
This study examines the effect of mixing varying percentages of nano-silica (NS), i.e. 2, 4 and 6% (by weight of polymer-modified bitumen, PMB) with PMB, in unaged and aged conditions. The Fourier transform infrared spectroscopy, x-ray diffraction, scanning electron microscopy and dynamic shear rheometer were used to determine chemical, microstructure and rheological properties of the binders, respectively. An artificial neural network (ANN) model, known as the multilayer perceptron neural networks model with three different algorithms namely; Levenberg-Marquardt (LM), scaled conjugate gradient (SCG), and gradient descent with adaptive back propagation (GDA) were used to predict the rheological properties of binders. The results indicate that adding NS to PMB may weaken the binders and delay their ageing. The amorphous structures of NS-PMBs remain unchanged and no new crystalline phase was formed when varying percentages of NS was added to PMB. Extreme heat caused a marked increase in the complex modulus of NS-PMB6 while low temperatures reduced its complex modulus. This resulted in enhanced resistance to the rutting and fatigue parameters. Adding higher amounts of NS particles to PMB also improved the viscoelastic properties and resistance to the ageing conditions of NS-PMB6. In terms of modeling, it was found that the most suitable algorithms and neurons number in the hidden layer for the ANN-Unaged model is LM algorithm and 11 neurons. For ANN-RTFOT and ANN-PAV models, the optimum algorithms and neurons number in hidden layer is SGC algorithm with 11 neurons and LM with 9 neurons respectively. The R-value (>0.95) for all models show a good agreement between measured and predicted data. It was concluded that the ANNs could be used as an accurate, fast and practical method for researchers and engineers to predict the phase angle and complex modulus of NS-PMBs.
Tue, 21 Aug 2018 00:00:00 GMThttp://repository.umy.ac.id/handle/123456789/317322018-08-21T00:00:00ZWAVELET-SPECTOGRAM ANALYSIS OF SURFACE WAVE TECHNIQUE FOR IN SITU PAVEMENT STIFFNESS MEAUREMENT
http://repository.umy.ac.id/handle/123456789/31731
WAVELET-SPECTOGRAM ANALYSIS OF SURFACE WAVE TECHNIQUE FOR IN SITU PAVEMENT STIFFNESS MEAUREMENT
ROSYIDI, SRI ATMAJA P; YUSOFF, NUR IZZI MD
Accurate, quick, and nondestructive in situ tests for measuring pavement stiffness, or elastic modulus, are an increasingly important element in pavement management systems. This is due to the increasing number of aged road networks and the limited budget allocated by the government for pavement monitoring and maintenance. This paper aims to propose a new wavelet-spectrogram analysis of surface wave (WSSW) technique for nondestructive testing and in situ measurement of pavement surface layers. The proposed technique was developed on the basis of the spectral analysis of surface wave (SASW) and modified data analysis of the ultrasonic surface wave (USW) methods. This technique uses two receivers to detect and record the signals of the surface wave propagating on a pavement surface. In wavelet analysis, the received signals are transformed into a time-frequency domain and displayed in a spectrogram. The spectrogram was generated on the basis of the mother wavelet of the Gaussian derivative (GoD). A wavelet filtration technique was also used in the time-frequency spectrogram to diminish the effect of the noise signal recorded during field measurement. The unwrapped phase of a different spectrum was generated from a selected wave energy in the spectrogram to obtain a phase velocity; this was performed through a linear regression analysis for calculating the value of the slope of a phase velocity. The elastic modulus of the pavement surface layer can be obtained via a linear relationship of assumed density, measured phase velocity, and assumed Poisson’s ratio of pavement materials. The results can be used to show that the proposed technique can be of practical use for in situ elastic modulus measurement on flexible and rigid pavements. It can also be used to determine any changes that might occur in the stiffness of the pavement surface layer.
Mon, 21 May 2018 00:00:00 GMThttp://repository.umy.ac.id/handle/123456789/317312018-05-21T00:00:00ZCOMPARATIVE STUDY ON USING STATIC AND DYNAMIC FINITE ELEMENT MODELS TO DEVELOP FWD MEASUREMENT ON FLEXIBLE PAVEMENT STRUCTURES
http://repository.umy.ac.id/handle/123456789/31730
COMPARATIVE STUDY ON USING STATIC AND DYNAMIC FINITE ELEMENT MODELS TO DEVELOP FWD MEASUREMENT ON FLEXIBLE PAVEMENT STRUCTURES
HAMIM, ASMAH; YUSOFF, NUR IZZI MD; CEYLAN, HALIL; ROSYIDI, SRI ATMAJA P; EL-SHAFIE, AHMED
The deflection basin obtained through backcalculation analysis is compared with the measured deflection basin to determine the moduli of each pavement layer. Most computer programs use multi-layered elastic theory (MET) to perform backcalculation for determining deflection basin. Other structural analysis techniques, such as finite element method (FEM) and finite difference method (FDM), can be used to model flexible pavement structures when conducting FWD tests. Unlike FEM, MET analysis does not take into account nonlinear materials and dynamic loading. This study aims to develop a better finite element (FE) model by using the static and dynamic analyses in the ANSYS computer program. A comparative study was conducted by using varying sizes of model geometry and different types of elements and sizes to determine how they affect the developed FE model. The results of the analyses show that transient dynamic analysis is the best method for simulating FWD test. The percentage of errors between FE deflection basin and measured deflection basin range between 0.94 and 5.01%. Model geometry of 5000 × 5000 mm is sufficient to produce a good deflection basin which approximates the measured deflection. To ensure the accuracy of the developed model, the information on material properties must be valid. Additionally, finer and higher order elements should be used close to the loading region, for instance four or eight-node quadrilateral element (CAX4 or CAX8) with quadratic interpolation function.
Tue, 10 Jul 2018 00:00:00 GMThttp://repository.umy.ac.id/handle/123456789/317302018-07-10T00:00:00Z