AMPP Store - Products tagged with 'ndt'

Available for download

08004 Non-Destructive Determination of Rust Creep

Product Number: 51300-08004-SG

ISBN: 08004 2008 CP

Author: Claus E. Weinell and Soeren Nyborg Rasmussen

Publication Date: 2008

$20.00

Modern high performance paint systems are so durable that when exposed to natural weathering they may show only slight signs of deterioration. This means that new coatings being marketed have limited track records. Which creates an increased reliance on accelerated laboratory testing to evaluate performance.

Available for download

51318-10509-Recent Applications of Evaluation Equipment in HTHA Service

Product Number: 51318-10509-SG

Author: M. Nugent / T. Silfies / P. Kowalski / N. Sutton

Publication Date: 2018

$20.00

This paper will highlight some of the ongoing advances of the HTHA Joint Industry Project (JIP) to date and provide a preview into upcoming developments in the NDE and FFS codes.

Available for download

Machine learning based NDT data fusion to detect corrosion in reinforced concrete structures by robot-assisted inspection

Product Number: 51321-16392-SG

Author: Patrick Pfändler/Ueli Angst

Publication Date: 2021

$20.00

Available for download

Pitting Corrosion Detection by Ultrasound Monitoring

Product Number: 51324-20810-SG

Author: Magnus Wangensteen; Ali Fatemi; Tonni Franke Johansen; Erlend Magnus Viggen

Publication Date: 2024

$40.00

Early diagnosis is essential for successful mitigation of pitting corrosion, a localized form of corrosion that causes cavities and structural failure in metallic materials. Although ultrasonic inspection techniques are effective in detecting uniform wall thinning, they have challenges in accurately identifying pitting corrosion. The present work proposes a technique for early-stage pitting detection utilizing time-lapse pulse-echo signals. The generation of two-dimensional time-lapse images of ultrasonic reflectivity may be achieved by capturing several ultrasonic traces over a period of time. These images can then serve as input for a neural network trained specifically for the purpose of pitting diagnostics. To obtain a substantial training dataset required for training the machine learning model, a drilling experiment was conducted, and random time-ordered combinations of the pulse-echo measurements produced the time-lapse images. A classification neural network was trained to detect the presence of pits, while a separate regression network was trained to estimate the pit depth. Test data from a previously unseen transducer indicates that the pit depth estimations exhibit a mean absolute error of less than 0.2 mm. All pits are reliably identified when they exceed the defined pitting threshold of 0.5 mm by a depth of 0.1 mm.

Technology for Chemical Cleaning of Industrial Equipment, 2nd Edition

Product Number: 37634-POD

ISBN: 978-1-57590-367-5

Author: Wayne Frenier

$148.00

This is a print-on-demand (POD) book that will be produced just for you in 2-5 days after your order. It should arrive at your door in about one to two weeks. However, due to supply chain and logistic challenges currently affecting the industry, it may take longer. Allow three weeks for international orders.

This book presents new developments that have affected the commercial use of chemicals and devices to clean industrial equipment.

This second edition emphasizes the mechanisms of important cleaning processes and solvents and gives an overview of the science and technology of the formation and removal of fouling deposits in the industrial equipment environment.

It is directed to a general technically trained audience, with emphasis placed on the basic chemical and mechanical principles of industrial cleaning. All of the chapters have been updated and significant new information on the dissolution of inorganic solids is included.

2018 NACE, color, 8.5 x 11" trim size, perfect bound, 392 pages.

Products tagged with 'ndt'

08004 Non-Destructive Determination of Rust Creep

51318-10509-Recent Applications of Evaluation Equipment in HTHA Service

Machine learning based NDT data fusion to detect corrosion in reinforced concrete structures by robot-assisted inspection

Pitting Corrosion Detection by Ultrasound Monitoring

Technology for Chemical Cleaning of Industrial Equipment, 2nd Edition

Association for Materials Protection and Performance