Active thermography for the investigation of corrosion in steel surfaces

The present work aims at developing an experimental methodology for the analysis of corrosion phenomena of steel surfaces by means of Active Thermography (AT), in reflexion configuration (RC). The peculiarity of this AT approach consists in exciting by means of a laser source the sound surface of the specimens and acquiring the thermal signal on the same surface, instead of the corroded one: the thermal signal is then composed by the reflection of the thermal wave reflected by the corroded surface. This procedure aims at investigating internal corroded surfaces like in vessels, piping, carters etc. Thermal tests were performed in Step Heating and Lock-In conditions, by varying excitation parameters (power, time, number of pulse, ….) to improve the experimental set up. Surface thermal profiles were acquired by an IR thermocamera and means of salt spray testing; at set time intervals the specimens were investigated by means of AT. Each duration corresponded to a surface damage entity and to a variation in the thermal response. Thermal responses of corroded specimens were related to the corresponding corrosion level, referring to a reference specimen without corrosion. The entity of corrosion was also verified by a metallographic optical microscope to measure the thickness variation of the specimens

Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

NASA Tech Briefs Index, 1977, volume 2, numbers 1-4

Announcements of new technology derived from the research and development activities of NASA are presented. Abstracts, and indexes for subject, personal author, originating center, and Tech Brief number are presented for 1977

Synthesis Study: Overview of Readily Available Culvert Inspection Technologies

Culverts, conduits that facilitate passage of water beneath roadways and other structures, represent important components of infrastructure systems, helping to drain, direct or divert surface water and prevent the disruption of roadways. Their efficient inspection and maintenance is thus critical to safe operation of Indiana’s transportation infrastructure. Although approximately 25% of culverts associated with INDOT managed roadways are inspected each year, inspectors face many challenges determining the actual condition of culverts, which can vary substantially in material type, form, length, depth of cover, accessibility, and age. This study was therefore performed to understand and synthesize technical culvert inspection alternatives with a focus on identifying and prioritizing readily available solutions. Research revealed that no standard inspection guidelines exist for small culverts, and that inspection practices vary significantly across states. DOT survey results indicate that DOTs primarily rely on visual examination conducted by field personnel, often from the open ends of the culvert, limiting the range of flaws and failure modes that can be identified, and the desired early warning benefits of inspection. While a range of technologies exist to facilitate inspection, most methods apply to only a limited set of culvert materials and operating conditions. This study thus provides a ranked recommendation of readily available culvert inspection solutions, segmented according to their applicability to varying culvert conditions and inspection needs. Techniques involving mobile visual camera systems and multi-sensing modes stand out for their potential to provide insight into the condition of a variety of culvert types at moderate cost

Index to 1981 NASA Tech Briefs, volume 6, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1981 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Predicting deterioration rate of culvert structures utilizing a Markov model

A culvert is typically a hydraulic passage, normally placed perpendicular to the road alignment, which connects the upstream and downstream sections underneath an embankment, while also providing structural support for earth and traffic loads. The structural condition of culverts continues to deteriorate due to aging, limited maintenance budgets, and increased traffic loads. Maintaining the performance of culverts at acceptable levels is a priority for the U.S. Department of Transportation (DOT), and an effective maintenance of culvert structures can be greatly improved by introducing asset management practices. A priority list generated by traditional condition assessment might not provide optimum solutions, and benefits of culvert asset management practices can be maximized by incorporating prediction of deterioration trends. This dissertation includes the development of a decision making chart for culvert inspection, the development of a culvert rating methodology using the Analytic Hierarchy Process (AFIP) based on an expert opinion survey and the development of a Markovian model to predict the deterioration rate of culvert structures at the network level. The literature review is presented in three parts: culvert asset management systems in the U.S.; Non-destructive Technologies (NDT) for culvert inspection (concrete, metal, and thermoplastic culvert structures); and statistical approaches for estimating the deterioration rate for infrastructure. A review of available NDT methods was performed to identify methods applicable for culvert inspection. To identify practices currently used for culvert asset management, culvert inventory data requests were sent to 34 DOTs. The responses revealed that a relatively small number of DOTs manage their culvert assets using formal asset management systems and, while a number of DOTs have inventory databases, many do not have a methodology in place to convert them to priority lists. In addition, when making decisions, DOTs do not incorporate future deterioration rate information into the decision making process. The objective of this work was to narrow the gap between research and application. The culvert inventory database provides basic information support for culvert asset management. Preliminary data analysis of datasets provided by selected DOTs was performed to demonstrate the differences among them. An expert opinion survey using AHP was performed to confirm the weight of 23 factors, which was believed to contribute to the hydraulic & structural performance of culvert structures, so as to establish the culvert rating methodology. A homogenous Markov model, which was calibrated using the Metropolis-Hastings Algorithm, was utilized in the computation of the deterioration rate of culverts at the network level. A real world case study consisting of datasets of three highways inspected regularly by Oregon DOT is also presented. The performance of the model was validated using Pearson\u27s chi-square test

Robust techniques and applications in fuzzy clustering

This dissertation addresses issues central to frizzy classification. The issue of sensitivity to noise and outliers of least squares minimization based clustering techniques, such as Fuzzy c-Means (FCM) and its variants is addressed. In this work, two novel and robust clustering schemes are presented and analyzed in detail. They approach the problem of robustness from different perspectives. The first scheme scales down the FCM memberships of data points based on the distance of the points from the cluster centers. Scaling done on outliers reduces their membership in true clusters. This scheme, known as the Mega-clustering, defines a conceptual mega-cluster which is a collective cluster of all data points but views outliers and good points differently (as opposed to the concept of Dave\u27s Noise cluster). The scheme is presented and validated with experiments and similarities with Noise Clustering (NC) are also presented. The other scheme is based on the feasible solution algorithm that implements the Least Trimmed Squares (LTS) estimator. The LTS estimator is known to be resistant to noise and has a high breakdown point. The feasible solution approach also guarantees convergence of the solution set to a global optima. Experiments show the practicability of the proposed schemes in terms of computational requirements and in the attractiveness of their simplistic frameworks. The issue of validation of clustering results has often received less attention than clustering itself. Fuzzy and non-fuzzy cluster validation schemes are reviewed and a novel methodology for cluster validity using a test for random position hypothesis is developed. The random position hypothesis is tested against an alternative clustered hypothesis on every cluster produced by the partitioning algorithm. The Hopkins statistic is used as a basis to accept or reject the random position hypothesis, which is also the null hypothesis in this case. The Hopkins statistic is known to be a fair estimator of randomness in a data set. The concept is borrowed from the clustering tendency domain and its applicability to validating clusters is shown here. A unique feature selection procedure for use with large molecular conformational datasets with high dimensionality is also developed. The intelligent feature extraction scheme not only helps in reducing dimensionality of the feature space but also helps in eliminating contentious issues such as the ones associated with labeling of symmetric atoms in the molecule. The feature vector is converted to a proximity matrix, and is used as an input to the relational fuzzy clustering (FRC) algorithm with very promising results. Results are also validated using several cluster validity measures from literature. Another application of fuzzy clustering considered here is image segmentation. Image analysis on extremely noisy images is carried out as a precursor to the development of an automated real time condition state monitoring system for underground pipelines. A two-stage FCM with intelligent feature selection is implemented as the segmentation procedure and results on a test image are presented. A conceptual framework for automated condition state assessment is also developed