Quantifying the Effects of Climate Change on Pavement Performance Prediction using AASHTOWare Pavement ME Design

Climate change is one of the most concerning global issues and has the potential to influence every aspect of human life. Like different components of society, it can impose significant adverse impacts on pavement infrastructure. Although several research efforts have focused on studying the effects of climate change on natural and built systems, its impact on pavement performance has not been studied as extensively. The primary objectives of this thesis research was to quantify the effect of temperature changes on flexible pavement response and performance prediction using the AASHTOWare Pavement ME Design (PMED), and quantify the effects of Local Calibration Factors (LCFs) used by different state highway agencies in the United States on predicted pavement performance. Particular emphasis was given to LCF values used by the Idaho Transportation Department. The climatic data, as well as LCFs corresponding to several different states, were used to identify how different LCF values affect pavement performance prediction. The effects of atmospheric temperature changes on pavement temperature and Asphalt Concrete (AC) layer modulus were studied by analyzing the intermediate files generated by PMED. Finally, the impact of temperature change on AC dynamic modulus (E*) was also analyzed to link the PMED-predicted distresses with asphalt mix properties. Historical climatic data was obtained from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) database. Projected data considered to simulate the temperature changes in the future were generated by adopting two different approaches: (1) Manual alteration of historical temperature distribution data to represent scenarios with increased mean and standard deviation values; and (2) Use of temperature data projected by established Global Climate Models (GCM). All different climatic scenarios were used in PMED along with a standard pavement section, and the distresses predicted over the design life of the pavement were compared. Simulation results showed consistent increase in Total Pavement rutting and AC rutting with increasing air temperatures. The effect of temperature increase on AC thermal cracking predicted by PMED demonstrated inconsistent trends. In contrast, the projected temperature increase had no significant effect on bottom-up fatigue cracking for the chosen study locations. It was found that the impact of changed air temperatures can be different for pavement sections constructed in different geographic locations. Moreover, the analysis confirmed that the Local Calibration Factors (LCFs) established by different state highway agencies played a major role in governing the effect of future temperature increase on predicted pavement performance. Through an extensive study of the LCFs used in the states of Idaho, Colorado, and Michigan, it was observed that the LCFs in Idaho did not adequately reflect the effects of future temperature changes on predicted pavement performance. Findings from this study emphasize the importance of considering non-stationary climate conditions likely to occur in the future during the process of pavement design. Moreover, this study also highlighted different aspects of the LCFs that play a significant role in capturing the effects of climatic factors on pavement performance predicted by PMED. Based on the findings, it is believed that further fine-tuning of the LCFs used in Idaho may be needed

Implementing AASHTO TP 110 for Alkali-Silica Reaction Potential Evaluation of Idaho Aggregates

The reaction between the active silica constituents of aggregates and alkalis in cement in the presence of moisture is called Alkali-Silica Reaction (ASR). ASR forms a swelling gel which can expand and cause internal stresses in cementitious materials leading to cracking, loss of strength, and eventually failure. The primary objective of this research study is to evaluate the advantages associated with implementing the new test method AASHTO TP-110 to better characterize the ASR potential of Idaho aggregates. Total of 8 identified aggregate types will be tested. The sources of those aggregate types are across Idaho with different degrees of ASR potential

An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System

Optical camera communication (OCC) exhibits considerable importance nowadays in various indoor camera based services such as smart home and robot-based automation. An android smart phone camera that is mounted on a mobile robot (MR) offers a uniform communication distance when the camera remains at the same level that can reduce the communication error rate. Indoor mobile robot navigation (MRN) is considered to be a promising OCC application in which the white light emitting diodes (LEDs) and an MR camera are used as transmitters and receiver respectively. Positioning is a key issue in MRN systems in terms of accuracy, data rate, and distance. We propose an indoor navigation and positioning combined algorithm and further evaluate its performance. An android application is developed to support data acquisition from multiple simultaneous transmitter links. Experimentally, we received data from four links which are required to ensure a higher positioning accuracy

A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry

The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories: host vehicles (HVs) are the ones used to estimate other vehicles' positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme

Comparative study of resin sealant and resin modified glass ionomer as pit and fissure sealant

The purpose of the present study was to compare the marginal integrity of resin modified glass ionomer cement with that of resin sealant, in vitro. Forty artificial pit and fissure cavities were prepared in occlusal surface of extracted premolar teeth by using ¼ round carbide bur. Cavities were condensed with artificial organic debris followed by cleaning with prophylaxis pumice brush and paste and then separated into two treatment groups. In Group A, 15 fissure cavities were sealed by resin sealant and in Group B, 15 fissure cavities were sealed by resin modified glass ionomer sealant. These specimens were subjected to thermo-cycling followed by dye penetration test. The remaining 5 cavities from each group were analyzed for debris score by the SEM. The results of the microleakage test showed that the efficacy of preventing microleakage of samples sealed by resin modified glass ionomer sealant was higher than the samples sealed by resin sealant. However, no significant differences were found. It can be concluded that use of resin modified glass ionomer sealant is a good alternative for sealing pits and fissures

An analysis of the thermal interaction between components in power converter applications

Accurately predicting the temperature of semiconductor devices is very important in the initial design of power electronics converter. RC thermal models derived from well-known methods have some ability to predict the temperature. However, the accuracy is boundary condition specific, hence, these methods cannot be used in the reliability analysis. To make the thermal model more accurate and robust the factors contributing to discrepancies need to be analyzed carefully. These are power-module-materials’ non-linear properties, thermal grease layer and the cooling system (i.e., liquid-cooled cold plate). In this work, estimation of accurate RC parameters from FEA thermal model is demonstrated in COMSOL. The electrical model having temperature dependent power loss model is coupled to refined thermal model and solved in a circuit simulator, PLECS. The proposed method is applied in two applications: assessing thermal interaction between IGBTs and anti-parallel diodes in a half-bridge power module, and assessing thermal interaction among the discrete switches in an interleaved bidirectional DC-DC converter. Results show that the impact of material non-linearity, thermal grease layer and cooling boundary conditions are significant for accurate prediction of IGBT and diode temperatures. The proposed model is consistent to FEA results and differs by 2-6.5% comparing to the experimental results

Filtration and Synthesis of Different types of Human Voice Signals: An application of digital signal processing

An observation of the effect in audio signal by using digital filter plays an important role in the field of digital signal processing (DSP). Day by day the digital form of signal is becoming more preferable than the analog one which is increasing the need of DSP in the rapidly changing world. Yet, there are many attractive schemes for designing a digital filter; we adopt windowing technique for design a FIR low pass filter in the frequency domain for the short period. However, the main task of our work is to perform filtration of the different types of practical human voice signals by using digital filter and synthesis of those signals to reduce the memory size (kB) by remaining the same quality of the signal. We used MATLAB for the design of digital filter and synthesis of those audio signals. MATLAB provides different options for signal synthesis. Finally, this paper gives an idea about reconstructed signals and filtrated signals. Keywords: Digital filter, Cutoff frequency, Fourier transform, Inverse Fourier transforms, normalized frequency

Hand Sign to Bangla Speech: A Deep Learning in Vision based system for Recognizing Hand Sign Digits and Generating Bangla Speech

Recent advancements in the field of computer vision with the help of deep neural networks have led us to explore and develop many existing challenges that were once unattended due to the lack of necessary technologies. Hand Sign/Gesture Recognition is one of the significant areas where the deep neural network is making a substantial impact. In the last few years, a large number of researches has been conducted to recognize hand signs and hand gestures, which we aim to extend to our mother-tongue, Bangla (also known as Bengali). The primary goal of our work is to make an automated tool to aid the people who are unable to speak. We developed a system that automatically detects hand sign based digits and speaks out the result in Bangla language. According to the report of the World Health Organization (WHO), 15% of people in the world live with some kind of disabilities. Among them, individuals with communication impairment such as speech disabilities experience substantial barrier in social interaction. The proposed system can be invaluable to mitigate such a barrier. The core of the system is built with a deep learning model which is based on convolutional neural networks (CNN). The model classifies hand sign based digits with 92% accuracy over validation data which ensures it a highly trustworthy system. Upon classification of the digits, the resulting output is fed to the text to speech engine and the translator unit eventually which generates audio output in Bangla language. A web application to demonstrate our tool is available at http://bit.ly/signdigits2banglaspeech