P. Klinkhachorn

Detection of subsurface defects in fiber reinforced polymer composite bridge decks using digital infrared thermography

Fiber reinforced polymer (FRP) bridge decks are rapidly emerging as potential alternatives to conventional reinforced concrete (RC) bridge decks. The FRP decks offer higher strength-to-weight ratios compared to RC decks. However, presence of subsurface defects such as debonds and delaminations formed during initial construction and in service can adversely affect the structural integrity and service performance of the FRP bridge decks. Hence, a field monitoring technique such as infrared thermography is required to evaluate the in situ condition of these FRP decks. This paper investigates the use of digital infrared thermography for subsurface defect detection in FRP bridge decks. Air-filled and water-filled debonds were inserted between the wearing surface and the underlying FRP deck in the laboratory. Simulated subsurface delaminations (of various sizes and thickness) were also created at the flange-to-flange junction between two FRP deck modules. The infrared technique was used to detect these embedded subsurface defects. Surface temperature–time curves were established for different sizes of delaminations and debonds. In addition, field study was conducted on a FRP bridge deck to detect debonds between the wearing surface and the underlying deck. The laboratory and field testing results show that infrared thermography is a potentially useful tool for defect detection in FRP composite bridge decks. The technique can possibly be used for several applications such as quality control during pultrusion of new decks (in factories), during field construction, and for field inspection of in-service decks.

Non-baseline detection of small damages from changes in strain energy mode shapes

Several methods for damage detection based on identifying changes in strain energy mode shapes (SEMS) have been recently described in the literature. Most of these methods require knowing strain energy distribution for the undamaged structure (baseline SEMS). This is especially true for detection of small damages, where changes in the SEMS cannot be observed otherwise. Usually, the mode shapes from the structure under test should be compared to the baseline mode shapes to provide sufficient data for damage detection. However, these methods do not cover damage detection on structures where baseline mode shapes cannot be readily obtained, for example, structures with preexisting damage. Conventional methods, like building a finite element (FE) model of a structure to be used as a baseline might be an expensive and time-consuming task that can be impossible for complex structures. This paper suggests a method for extraction of localized changes (damage peaks) from SEMS based on Fourier analysis of the strain energy distribution. A detailed analytical proof is given for the case of a pinned–pinned beam and a numerical proof for the free–free beam. The analytical predictions have been confirmed both by the FE model and impact testing experiments on a free–free aluminum beam, including single and multiple damage scenarios.

Developing professionalism in the electrical engineering classroom

The authors share their experience in teaching electrical engineering students the ethical, social, safety, and economic considerations in engineering practice. The exercises take the form of a trial where the students have to defend their judgments. The approach is found to be successful in helping students to understand the true meaning of being an engineering professional. Professional ethics and hypothetical accident scenarios are presented. >

Hybrid LQG-neural controller for inverted pendulum system

The paper presents a hybrid system controller, incorporating a neural and an LQG controller. The neural controller has been optimized by genetic algorithms directly on the inverted pendulum system. The failure-free optimization process stipulated a relatively small region of the asymptotic stability of the neural controller, which is concentrated around the regulation point. The presented hybrid controller combines benefits of a genetically optimized neural controller and an LQG controller in a single system controller. High quality of the regulation process is achieved through utilization of the neural controller, while stability of the system during transient processes and a wide range of operation are assured through application of the LQG controller. The hybrid controller has been validated by applying it to a simulation model of an inherently unstable system - the inverted pendulum.

Design of a microprocessor-controlled personal static VAr compensator (PSVC)

A prototype personal static VAr compensator (PSVC) has been designed for load power factor correction for both residential and commercial applications. The PSVC demonstrates the two key benefits of power factor correction, which include decreased power costs and increased system capacity. The PSVC also demonstrates conventional static VAr compensator (SVC) principles that are routinely applied by power utilities. The PSVC prototype consists of two main branches-a TSC (thyristor switched capacitor) branch and a TCR (thyristor controlled reactor) branch. A microprocessor is responsible for calculating the displacement power factor and for executing the fuzzy logic control scheme for the two branches. The PSVC is currently being evaluated using an inductive load and an AC motor. Test results are presented.

Genetic algorithms-based parameter optimization of a non-destructive damage detection method

The method of strain energy mode shapes allows the determination of changes in structural integrity from changes in the vibrational response of a structure. The modified method presented does not require knowledge of the undamaged state of the structure. Genetic algorithms (GA) are applied to produce a sufficiently optimized amplitude characteristic of a filter used to extract damage information from strain energy mode shapes. Finite element modeling has been used to produce a training data set with the known location of damages. The amplitude characteristic of the filter has been encoded as a genetic string where the pass coefficient for each harmonic of its discrete Fourier transform representation is a number between zero and one in 8-bit Gray code. The genetic optimization has been performed based on the minimization of the signal-to-distortion ratio. The amplitude characteristic of the filter was not limited to any specific configuration, i.e. either low-or high-pass or specific cut-off frequencies. The results obtained from the GA confirmed the theoretical predictions and allowed improvement in the methods sensitivity to damages of lower magnitude.

Subsurface Defect Detection in FRP Composites Using Infrared Thermography

This paper demonstrates the use of digital infrared thermography to detect subsurface defects such as debonds and delaminations in Fiber Reinforced Polymer (FRP) bridge decks. Simulated sub‐surface debonds and delaminations were inserted between the wearing surface and the underlying FRP deck specimens. The infrared thermography technique was used to detect these embedded subsurface defects. The use of various cooling and heating methods, including solar radiation, was explored. Surface temperature‐time curves were established for different types and sizes of subsurface defects.

An automated damage detection system for armored vehicle launched bridge

This paper presents an overview of an automated damage detection system for the Armored Vehicle Launched Bridge (AVLB). The system utilizes a non-contact laser vibrometer mounted on a computer-controlled robotic gantry as the measurement sensor. Acquired data is automatically processed to obtain strain energy mode shapes, which are used as the damage indicator. The analysis of the strain energy mode shapes is performed by a fuzzy expert system. This system was successfully tested on a full-scale AVLB with different damage scenarios.

Ultrasonic instrumentation for measuring applied stress on bridges

The measurement of applied stress on bridges can provide valuable information on the condition of the structure. The conventional technique for measuring applied stress is with a strain gage. However, strain gages can be time consuming to install because first the surface must usually be prepared. On a bridge, paint removal will most likely be necessary as part of this surface preparation. When dealing with lead-based paints, which are considered hazardous waste, many time consuming removal procedures are required. Because of these factors, a device that measures applied stress without requiring paint removal could be useful. While a “clamp-on” strain gage can also be used to measure applied stress without requiring paint removal, this type of strain gage can not be used on some bridge details, such as webs of I-beams and tops of box girders. An ultrasonic technique using non-contact electromagnetic transducers provides a possible method for applied stress measurement which is not limited by the same factors as those with conventional strain gages. The transducers operate through nonconductive and conductive (lead-based) paint and work on rusted, pitted surfaces. Our previous research developed a technique for measuring applied stresses on bridges with EMATs and included many laboratory tests. This paper describes field applications of the technique on actual bridge structures, as well as additional system testing and instrument calibration in the laboratory.

Packing of convex polygons in a rectangularly bounded, non-homogeneous space

A two-dimensional heuristic packing strategy, capable of achieving a dense packing of convex polygonal shapes, is presented. A method for extending the placement strategy to nonconvex n-gons is also presented. The algorithm was developed as part of a system to automate the various aspects of the hardwood manufacturing industry. The techniques developed, however, are applicable to the packing problem in general.<<ETX>>