Please wait, while we are loading the content...
| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | James, V. Henrickson Kirkpatrick, Kenton Valasek, John |
| Copyright Year | 2013 |
| Abstract | Shape memory alloys are capable of delivering advantageous solutions to a wide range of engineering-based problems. Implementation of these solutions, however, is often complicated by the hysteretic, non-linear, thermo-mechanical behavior of the material. Although existing shape memory alloy constitutive models are largely accurate in describing this unique behavior, they require prior characterization of the material parameters. Consequently, before thorough modeling and simulation can occur for a shape memory alloy-based project, one must first go through the process of identifying several material parameters unique to shape memory alloys. Current characterization procedures necessitate extensive experimentation, data collection, and data processing. As a result, these methods simultaneously create a high barrier of entry for engineers new to active materials and impede the advanced study of shape memory alloy material parameter evolution. This paper develops a novel method in which computational intelligence methods are used to rapidly identify shape memory alloy material parameters. Specifically, an artificial neural network is trained to identify transformation temperatures and stress influence coefficients of given shape memory alloy specimens using strain-temperature coordinates as inputs. After generating training data through the use of a constitutive model, the resulting trained artificial neural network was used to identify parameters for a number of randomly generated theoretical shape memory alloys. Results presented in the paper show that the artificial neural network was able to rapidly identify both transformation temperatures and stress influence coefficients with satisfactory accuracy. The generation of training data was then repeated using Taguchi methods. Further results presented in the paper show that the artificial neural network trained with the Taguchi-based training data yielded improved characterization accuracy while using less training data. |
| Sponsorship | Aerospace Division |
| File Format | |
| ISBN | 9780791856031 |
| DOI | 10.1115/SMASIS2013-3016 |
| Volume Number | Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation |
| Conference Proceedings | ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems |
| Language | English |
| Publisher Date | 2013-09-16 |
| Publisher Place | Snowbird, Utah, USA |
| Access Restriction | Subscribed |
| Subject Keyword | Temperature Shape memory alloys Artificial neural networks Alloys Modeling Stress Thermomechanics Simulation Active materials Data collection Taguchi methods Engineers Shapes Constitutive equations |
| Content Type | Text |
| Resource Type | Article |
National Digital Library of India (NDLI) is a virtual repository of learning resources which is not just a repository with search/browse facilities but provides a host of services for the learner community. It is sponsored and mentored by Ministry of Education, Government of India, through its National Mission on Education through Information and Communication Technology (NMEICT). Filtered and federated searching is employed to facilitate focused searching so that learners can find the right resource with least effort and in minimum time. NDLI provides user group-specific services such as Examination Preparatory for School and College students and job aspirants. Services for Researchers and general learners are also provided. NDLI is designed to hold content of any language and provides interface support for 10 most widely used Indian languages. It is built to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is designed to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is developed, operated and maintained from Indian Institute of Technology Kharagpur.
Learn more about this project from here.
NDLI is a conglomeration of freely available or institutionally contributed or donated or publisher managed contents. Almost all these contents are hosted and accessed from respective sources. The responsibility for authenticity, relevance, completeness, accuracy, reliability and suitability of these contents rests with the respective organization and NDLI has no responsibility or liability for these. Every effort is made to keep the NDLI portal up and running smoothly unless there are some unavoidable technical issues.
Ministry of Education, through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.
| Sl. | Authority | Responsibilities | Communication Details |
|---|---|---|---|
| 1 | Ministry of Education (GoI), Department of Higher Education |
Sanctioning Authority | https://www.education.gov.in/ict-initiatives |
| 2 | Indian Institute of Technology Kharagpur | Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project | https://www.iitkgp.ac.in |
| 3 | National Digital Library of India Office, Indian Institute of Technology Kharagpur | The administrative and infrastructural headquarters of the project | Dr. B. Sutradhar bsutra@ndl.gov.in |
| 4 | Project PI / Joint PI | Principal Investigator and Joint Principal Investigators of the project |
Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon |
| 5 | Website/Portal (Helpdesk) | Queries regarding NDLI and its services | support@ndl.gov.in |
| 6 | Contents and Copyright Issues | Queries related to content curation and copyright issues | content@ndl.gov.in |
| 7 | National Digital Library of India Club (NDLI Club) | Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach | clubsupport@ndl.gov.in |
| 8 | Digital Preservation Centre (DPC) | Assistance with digitizing and archiving copyright-free printed books | dpc@ndl.gov.in |
| 9 | IDR Setup or Support | Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops | idr@ndl.gov.in |
|
Loading...
|