A.K. Pandey

Bio: A.K. Pandey is an academic researcher from Duke University. The author has contributed to research in topics: Biology & Botany. The author has an hindex of 4, co-authored 4 publications receiving 2738 citations.

Modal Technology for Damage Detection of Bridges

Abstract: Technologies of analytical and experimental modal analysis have been investigated for their application in damage detection of bridges. In the context of experiments performed on a typical highway bridge in North Carolina, various signals and signal-processed data that can be used for interrogation are presented. By introducing simulated failures in a highway bridge in Pennsylvania and in a number of laboratory bridge models and analytical models, experimental results are examined for their ability to detect faults.

Thermal analysis of hybrid photovoltaic-thermal water collector modified with latent heat thermal energy storage and two side serpentine absorber design

Abstract: The most popular renewable energy source is solar energy, which characterises as free, clean, and environmentally friendly. Photovoltaics (PV) generate electricity from daylight, becoming increasingly popular in residential and other applications. The potential energy delivery from a photovoltaic module is a function of solar radiation falling on the front surface and module operating temperature. However, these systems are modified to improve energy generation by placing an absorber on the bottom side of the module termed a Photovoltaic Thermal (PVT) system to reduce module temperature. The current study aims to investigate the experimental heat transfer efficiency for the fabricated PVT system employing two-sided serpentine flow thermal absorber and phase change material (PCM). PCM discharge the latent heat during off-sunshine hours to provide additional hot water. The experiment setup was tested with water as a working fluid in the flow rate range of 0.0085–0.067 kg/s. The optimal flow rate at which maximum heat gain of 757 W was obtained 0.033 kg/s with an average energy-saving efficiency of 69 %. The results confirm enhanced energy delivery of 3–5 % by PVT-PCM system compared to reference PV module for the same ambient operating conditions. Furthermore, the study reveals that overall efficiency of the PVT setup augment with the use of a thermal absorber and PCM, while the thermal efficiency is a factor that depends on the working fluid properties. • Fabrication of a two-side serpentine flow absorber for cooling photovoltaic thermal-phase change material collector system. • Results from heat transfer analysis lead to higher heat removal at 0.033 kg/s fluid flow rate of water. • Overall and energy-saving efficiency enhance by 23% and 28% for water flow rate of 0.033 kg/s as compared to other flow rates. • As the water flow rate increases from 0.0085 kg/s to 0.033 kg/s, the panel maximum average power output gains by 3%.

Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

Abstract: This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.

A summary review of vibration-based damage identification methods

Abstract: This paper provides an overview of methods to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration response. Research in vibration-based damage identification has been rapidly expanding over the last few years. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. The motivation for the development of this technology is presented. The methods are categorized according to various criteria such as the level of damage detection provided, model-based versus non-model-based methods, and linear versus nonlinear methods. The methods are also described in general terms including difficulties associated with their implementation and their fidelity. Past, current, and future-planned applications of this technology to actual engineering systems are summarized. The paper concludes with a discussion of critical issues for future research in the area of vibration-based damage identification.

Vibration-based Damage Identification Methods: A Review and Comparative Study:

Abstract: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented, and the damage identification algorithms in terms of signal processing...

Structural Health Monitoring: A Machine Learning Perspective

Abstract: This book focuses on structural health monitoring in the context of machine learning. The authors review the technical literature and include case studies. Chapters include: operational evaluation, sensing and data acquisition, introduction to probability and statistics, machine learning and statistical pattern recognition, and data prognosis.