Identification of plastic properties of metallic structures by artificial neural networks based on plane strain small punch test

Author(s):  
Mohammad Ehsan Hassani ◽  
Wenke Pan
Smart Cities ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 118-134 ◽  
Author(s):  
Zaheer Allam

Through the Internet of things (IoT), as promoted by smart cities, there is an emergence of big data accentuating the use of artificial intelligence through various components of urban planning, management, and design. One such system is that of artificial neural networks (ANNs), a component of machine learning that boasts similitude with brain neurological networks and its functioning. However, the development of ANN was done in singular fashion, whereby processes are rendered in sequence in a unidimensional perspective, contrasting with the functions of the brain to which ANN boasts similitude, and in particular to the concept of neuroplasticity which encourages unique complex interactions in self-learning fashion, thereby encouraging more inclusive urban processes and render urban coherence. This paper takes inspiration from Christopher Alexander’s Nature of Order and dwells in the concept of complexity theory; it also proposes a theoretical model of how ANN can be rendered with the same plastic properties as brain neurological networks with multidimensional interactivity in the context of smart cities through the use of big data and its emerging complex networks. By doing so, this model caters to the creation of stronger, richer, and more complex patterns that support Alexander’s concept of “wholeness” through the connection of overlapping networks. This paper is aimed toward engineers with interdisciplinary interest looking at creating more complex and intricate ANN models, and toward urban planners and urban theorists working on the emerging contemporary concept of smart cities.


2017 ◽  
Vol 734 ◽  
pp. 212-236 ◽  
Author(s):  
Ying Zhi Li ◽  
Paul Stevens ◽  
Jin Feng Geng ◽  
Dong Fang Ma ◽  
Liang Xu

In the early 1980’s, the small punch technique was developed in USA and Japan. This technique has been applied to nuclear reactors, electric power plants for safety assessments. European researchers have carried out the pioneer work on SP creep testing in the 1990’s. European Code of Practice (CoP) documents have become available in 2006, which provides a guide line to perform small punch tests for metallic materials, and introduces methods for estimation of tensile properties, fracture toughness and creep properties. Since then several conferences and symposiums have been held to exchange ideas and experiences, and several efforts have been made to improve the approaches for interpreting the material properties from test results. However, due to the complexity of the small punch test itself and lack of systematic test data for verification, especially in the creep region, up to now there is no common acceptable method to interpret creep properties. This paper discusses some of the problems commonly encountered in the small punch creep test (SPCT) analysis, such as the uniqueness in reverse creep analysis for identification of material parameters, how to consider effects of large deformation and strain hardening, how to separate deflection into a part caused by loading and a part caused by creep, and how to estimate the elastic-plastic properties of a material in the creep temperature region. Based on these considerations, several existing approaches for interpreting creep properties have been re-evaluated. In addition, a software package, based on the optimization toolbox of Matlab has been developed for identification of material parameters automatically. Verifications are performed by checking the agreement between properties derived by small punch test and uni-axial tests. Discussions on problems of existing approaches and how to improve them further, are described in the paper. Experimental data are provided by JRC Petten, Netherlands, and Henan Electric Power Research Institute, China. Recently a working group led by JRC Petten is engaged in upgrading the CoP to a European standard. It is expected that in the future more data will become available for further verification.


Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  

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