We are pleased to announce that our former Ph.D. student, Dr. Kang, has accepted a position as a tenure-track Assistant Professor at National Kyungbok University in Korea

Last year, former STIL student Felix joined Jacobs Engineering Group. Congratulations on your 1-year anniversary of your career!

We would like to anounce Former Ph. D student, Dr. Wu’s new carreer. He now Bridge Designer at WSB. Curently he designed many TxDOT highway bridges.

Former Ph.D. student Dr. David has secured a position at Tower Engineering Solutions (TES) (https://www.congruex.com/tes/). Congratulations and best wishes for his successful career!”

In this study, we investigate a numerical-modeling method uniquely performing analyses of 50 different metal hydrides to find the optimized thermal effect. This paper presents a metal-hydride thermal energy conversion method, which offers an alternative approach to the traditional vapor-compression heat pump associated with conventional heating, ventilation, and air conditioning (HVAC). The authors have developed an innovative heat pump applicable to non-vapor compression-based systems, which are in compliance with low-temperature heat source requirements for operation. The new heat pump has a high-energy savings potential for both heating and cooling that featured two different metal-hydrides, that are distributed inside parallel channels filled with porous media. Thermal energy conversion is developed as a set of successive thermal waves. The numerical-modeling results present the enhanced thermal effect, which is attained in a synchronous motion of the thermal waves and the heat source (or sink) inside paired porous media channels, which accompanies the phase transition in the succession of unit metal-hydride heat pumps. The results present in a form convenient for the prediction of thermal energy efficiency based on the proposed thermal-conversion method in real devices that were experimentally verified in previous work. The non-vapor technologies will be operational with low energy input, which makes it possible to utilize waste heat or low-level heat often found in the environment such as solar radiation, exhaust gas from a heat engine, or high-temperature fuel cell system. View Full-TextKeywords: metal-hydride; heat pump; porous media; thermal wave; temperature; HVAC; non-vapor compression

This journal paper has been published. (June 2020)

This study presents a comparative assessment of image enhancement and segmentation techniques to automatically identify the flash flooding from the low-resolution images taken by traffic-monitoring cameras. Due to inaccurate equipment in severe weather conditions (e.g., raindrops or light refraction on camera lenses), low-resolution images are subject to noises that degrade the quality of information. De-noising procedures are carried out for the enhancement of images by removing different types of noises. For the comparative assessment of de-noising techniques, the Bayes shrink and three conventional methods are compared. After the de-noising, image segmentation is implemented to detect the inundation from the images automatically. For the comparative assessment of image segmentation techniques, k-means segmentation, Otsu segmentation, and Bayesian segmentation are compared. In addition, the detection of the inundation using the image segmentation with and without de-noising techniques are compared. The results indicate that among de-noising methods, the Bayes shrink with the thresholding discrete wavelet transform shows the most reliable result. For the image segmentation, the Bayesian segmentation is superior to the others. The results demonstrate that the proposed image enhancement and segmentation methods can be effectively used to identify the inundation from low-resolution images taken in severe weather conditions. By using the principle of the image processing presented in this paper, we can estimate the inundation from images and assess flooding risks in the vicinity of local flooding locations. Such information will allow traffic engineers to take preventive or proactive actions to improve the safety of drivers and protect and preserve the transportation infrastructure. This new observation with improved accuracy will enhance our understanding of dynamic urban flooding by filling an information gap in the locations where conventional observations have limitations.

This journal paper has been published. (June 2020)

This journal paper has been published. (April 2020)

This journal paper has been published. (Dec 2019)

Abstract

In this study, an automated acoustic scanning system was developed for rapid delamination detection on concrete bridge decks. A new ball-chain impact source was designed by combining the advantages of chain-drag (rapid testing speed) and impact-echo tests (analysis in the frequency domain). Conventional steel link chains and the new ball chains were investigated as acoustic excitation sources. Acoustic signals were processed by short-time Fourier transform (STFT) in the frequency range 0.5–5 kHz. Compared with the conventional chain-drag test, the ball-chain results show better signal-to-noise ratio (S/N), higher sensitivity, and repeatability to delamination identification. The automated scanning system includes excitation sources (ball chains), acoustic sensors (microphones), a geographic positioning system (GPS), data acquisition (oscilloscope), and a signal-processing algorithm. Acoustic scanning results are integrated with positioning data to generate an image of the scanned area in a map view. The system was validated in the field on a concrete bridge deck and was found to show satisfactory accuracy, efficiency, and repeatability.

This journal paper has been published. (Feb 2018)

Chain drag testing is commonly used in current practice for bridge deck evaluation due to its low cost and ease of use. However, this method is subjective, and highly depends on the experience of the operators. Ambient noise caused by traffic affects the test speed and accuracy of results. This paper describes a recent research to develop an automated chain drag acoustic scanning system to detect delaminations in concrete structures, including bridge decks. The system consists of an array of chains, a noncontact MEMS microphone sensor array, multi-channel data acquisition device, positioning system, and signal processing schemes. The multi-channel design improves the spatial coverage and resolution of testing. An algorithm for interpreting acoustic signals from the automated chain drag test is developed. This automated system will enable real time visualization of tested areas. Compared to the conventional manual chain drag test, the automated system provides improved accuracy, spatial resolution, repeatability, and practicality.

This journal paper has been published. (Nov 2017)