rcndeinfo@ndevr.org.uk
  • LinkedIn

RCNDE

  • Contact usrcndeinfo@ndevr.org.uk
  • For membersLogin & Members News
MENU
  • HOME
  • ABOUT
    • NDE
    • RCNDE
    • NDEvR
    • RCNDE governance
    • Our team
  • OUR WORK
    • Research
    • Technology transfer
    • Strategic activities
    • Case studies
  • WHY JOIN
    • How to join
    • FAQs
  • THE COMMUNITY
    • Academic expertise
    • Tier 1 members
    • Tier 2 members
    • Associate members
    • Collaborators
    • Doctoral training
  • NEWS & EVENTS
  • CONTACT

Filip Szlaszynski

EngD student 2017 intake

University: Imperial College London

Industrial partner: EDF Energy

Background: Undergraduate BEng in Mechanical Engineering with Oil and Gas Studies at University of Aberdeen, graduating in June 2017. Previously worked on the use of elastic waves for damage detection and structural health monitoring in composite wind turbine blades.

Guided Wave Testing of feature-rich structures

Guided Wave Testing (GWT) is well established in industry for the routine inspection of pipelines. The established inspections are almost always on pipeline structures with low density of features, so that reflections of the guided waves from defects are usually adequately separable from the signals arising from other benign features of the pipelines.

This EngD project will investigate deployment of guided waves for relatively short range inspections to detect and characterise specific candidate defects in pipes and other tubular structures in which the geometry is complex and there is a higher density of features than is usually encountered in GWT. A typical example would be to detect and size a crack at a weld at a location just 2-5 metres from the transducer, when there are structural features nearby and access for direct inspection at the defect location is not possible. Furthermore, access for placing the transducer may also be incomplete, such as access to only part of the circumference of the pipe/tube.

The aim, and central deliverable, of the project is to develop capability to detect and characterise defects in such structures. The proposed approach is to establish a means to anticipate the expected (background) signals in the absence of a defect, and then identify and interpret any superposed signal that is associated with a candidate defect. This will be done using numerical model simulations, using the so-called full wave inversion methodology.

  • LinkedIn

RCNDE – an internationally renowned membership-based industrial-academic collaboration that coordinates research into NDE technologies, ensuring research topics are relevant to the medium to longer-term needs of industry.

Activities

Our research Strategic activities Technology transfer

Latest news

  • RCNDE Spring 2025 Annual Meetings
  • RCNDE 2025 Spring Event
  • Publication of report on “Civil Structures workshop”

Further information

  • About us
  • FAQs
  • Why join?
  • How to join
  • Contact us
  • Accessibility
  • Privacy policy
© Copyright 2022 | All Rights Reserved RCNDE - Local SEO & Web Design Essex.

We are using cookies to give you the best experience on our website.

You can find out more about which cookies we are using or switch them off in .

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Strictly Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Cookie Policy

More information about our Cookie Policy