Algorithms for Diagnostics and Nondestructive Testing

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (15 April 2020) | Viewed by 6867

Special Issue Editor

Special Issue Information

Dear colleagues,

Nondestructive testing and evaluation methods have been in the spotlight of practitioners for a long time. NDT is considered today as one of the most innovative and fastest growing technologies. We are looking for new approaches for NDT purposes. High-quality papers are solicited to address both theoretical and practical issues of algorithms applied in diagnostics and nondestructive testing. Submissions are welcome both for traditional techniques, such as algorithms in active thermography, eddy current, or magnetic methods, as well as in new applications. Potential topics include but are not limited to the following:

  • Direct and inverse problems;
  • Algorithms for the determination of residual stresses;
  • Fatigue and crack detection;
  • Materials characterization;
  • Novel signal processing algorithms;
  • Computational intelligence in diagnostics;
  • Machine learning and pattern recognition in diagnostics;
  • Optimization in diagnostics and nondestructive testing;
  • Diagnostics supported with soft computing methods;
  • Case studies.

We invite your contributions to this Special Issue, focused on "Algorithms for Diagnostics and Nondestructive Testing".

Dr. Krzysztof Chwastek
Guest Editor

Manuscript Submission Information

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Published Papers (2 papers)

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Research

12 pages, 4907 KiB  
Article
Study of Quasi-Static Magnetization with the Random-Field Ising Model
by Roman Gozdur
Algorithms 2020, 13(6), 134; https://doi.org/10.3390/a13060134 - 29 May 2020
Cited by 3 | Viewed by 3171
Abstract
The topic of this paper is modeling based on Hamiltonian spin interactions. Preliminary studies on the identification of quasi-static magnetizing field in a magnetic system were presented. The random-field Ising model was then used to simulate the simplified ferromagnetic structure. The validation of [...] Read more.
The topic of this paper is modeling based on Hamiltonian spin interactions. Preliminary studies on the identification of quasi-static magnetizing field in a magnetic system were presented. The random-field Ising model was then used to simulate the simplified ferromagnetic structure. The validation of algorithms and simulation tests were carried out for the 2D and the 3D model spaces containing at least 106 unit cells. The research showed that the response of a slowly driven magnetic system did not depend on the external field sweep rate. Changes in the spatial magnetization of the lattice were very similar below a certain rate of the external field change known as the quasi-static boundary. The observed differences in obtained magnetization curves under quasi-static conditions stemmed from the random nature of the molecular field and the avalanche-like magnetization process Full article
(This article belongs to the Special Issue Algorithms for Diagnostics and Nondestructive Testing)
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14 pages, 7508 KiB  
Article
Damage Diagnosis of Reactive Powder Concrete under Fatigue Loading Using 3D Laser Scanning Technology
by Kexin Li, Jun Wang and Dawei Qi
Algorithms 2019, 12(12), 260; https://doi.org/10.3390/a12120260 - 4 Dec 2019
Cited by 5 | Viewed by 3096
Abstract
Damage mechanisms of Reactive Powder Concrete (RPC) under fatigue loading are investigated using the 3D laser scanning technology. An independently configured 3D laser scanning system is used to monitor the damaging procedure. Texture analysis technique is also applied to enhance the understanding of [...] Read more.
Damage mechanisms of Reactive Powder Concrete (RPC) under fatigue loading are investigated using the 3D laser scanning technology. An independently configured 3D laser scanning system is used to monitor the damaging procedure. Texture analysis technique is also applied to enhance the understanding of the damage mechanisms of RPC under fatigue loading. In order to obtain the characteristic parameters of point cloud data, a point clouds projection algorithm is proposed. Damage evolution is described by the change of point cloud data of the damage in the 2D plane and 3D space during fatigue loading. The Gray Level Co-occurrence Matrix (GLCM) method is used to extract the characteristic parameters to evaluate the statue of the structural. Angular Second Moment and Cluster Shadow of typical sensitive characteristic indexes is screened by using the Digital Feature Screening. The reliability of the damage index was verified by image texture analysis and data expansion. Indexes extracted in this paper can be used as a new structural health monitoring indicator to assess health condition. Full article
(This article belongs to the Special Issue Algorithms for Diagnostics and Nondestructive Testing)
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