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Devotta, Ashwin MorisORCID iD iconorcid.org/0000-0003-3877-9067
Publications (7 of 7) Show all publications
Devotta, A. M., Sivaprasad, P. V., Beno, T., Eynian, M., Hurtig, K., Magnevall, M. & Lundblad, M. (2019). A modified Johnson-Cook model for ferritic-pearlitic steel in dynamic strain aging regime. Metals, 9(5)
Open this publication in new window or tab >>A modified Johnson-Cook model for ferritic-pearlitic steel in dynamic strain aging regime
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2019 (English)In: Metals, ISSN 2075-4701, Vol. 9, no 5Article in journal (Refereed) Published
Abstract [en]

In this study, the flow stress behavior of ferritic-pearlitic steel (C45E steel) is investigated through isothermal compression testing at different strain rates (1 s-1, 5 s-1, and 60 s-1) and temperatures ranging from 200 to 700 °C. The stress-strain curves obtained from experimental testing were post-processed to obtain true stress-true plastic strain curves. To fit the experimental data to well-known material models, Johnson-Cook (J-C) model was investigated and found to have a poor fit. Analysis of the flow stress as a function of temperature and strain rate showed that among other deformation mechanisms dynamic strain aging mechanism was active between the temperature range 200 and 400 °C for varying strain rates and J-C model is unable to capture this phenomenon. This lead to the need to modify the J-C model for the material under investigation. Therefore, the original J-C model parameters A, B and n are modified using the polynomial equation to capture its dependence on temperature and strain rate. The results show the ability of the modified J-C model to describe the flow behavior satisfactorily while dynamic strain aging was operative. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Place, publisher, year, edition, pages
MDPI AG, 2019
Keywords
flow stress; modified Johnson-Cook model; dynamic strain aging
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-13989 (URN)10.3390/met9050528 (DOI)2-s2.0-85066741813 (Scopus ID)
Funder
Swedish Research Council, 20110263, 20140130
Available from: 2019-06-20 Created: 2019-06-20 Last updated: 2019-07-25Bibliographically approved
Devotta, A. M., Beno, T., Siriki, R., Löf, R. & Eynian, M. (2017). Finite Element Modeling and Validation of Chip Segmentation in Machining of AISI 1045 Steel. Paper presented at Conference of 16th CIRP Conference on Modelling of Machining Operations, CIRP CMMO 2017 ; Conference Date: 15 June 2017 Through 16 June 2017. Procedia CIRP, 58, 499-504
Open this publication in new window or tab >>Finite Element Modeling and Validation of Chip Segmentation in Machining of AISI 1045 Steel
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2017 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 58, p. 499-504Article in journal (Refereed) Published
Abstract [en]

The finite element (FE) method based modeling of chip formation in machining provides the ability to predict output parameters like cutting forces and chip geometry. One of the important characteristics of chip morphology is chip segmentation. Majority of the literature within chip segmentation show cutting speed (vc) and feed rate (f) as the most influencing input parameters. The role of tool rake angle (α) on chip segmentation is limited and hence, the present study is aimed at understanding it. In addition, stress triaxiality’s importance in damage model employed in FE method in capturing the influence of α on chip morphology transformation is also studied. Furthermore, microstructure characterization of chips was carried out using a scanning electron microscope (SEM) to understand the chip formation process for certain cutting conditions. The results show that the tool α influences chip segmentation phenomena and that the incorporation of a stress triaxiality factor in damage models is required to be able to predict the influence of the α. The variation of chip segmentation frequency with f is predicted qualitatively but the accuracy of prediction needs improvement. © 2017 The Authors.

Keywords
Cutting; Forecasting; Machining centers; Scanning electron microscopy; Shear stress, Chip morphologies; Chip segmentation; Cutting conditions; Damage model; Microstructure characterization; Output parameters; Stress triaxiality; Stress triaxiality factor, Finite element method
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-11909 (URN)10.1016/j.procir.2017.03.259 (DOI)2-s2.0-85029738278 (Scopus ID)
Conference
Conference of 16th CIRP Conference on Modelling of Machining Operations, CIRP CMMO 2017 ; Conference Date: 15 June 2017 Through 16 June 2017
Funder
Knowledge Foundation, 20110263, 20140130.
Note

Funders: Sandvik Coromant

Available from: 2017-12-13 Created: 2017-12-13 Last updated: 2019-05-21Bibliographically approved
Devotta, A. M., Beno, T. & Löf, R. (2017). Finite element modelling and characterisation of chip curl in nose turning process. International Journal of Machining and Machinability of Materials, 19(3), 277-295
Open this publication in new window or tab >>Finite element modelling and characterisation of chip curl in nose turning process
2017 (English)In: International Journal of Machining and Machinability of Materials, E-ISSN 1748-572X, Vol. 19, no 3, p. 277-295Article in journal (Refereed) Published
Abstract [en]

Finite element (FE) modelling of machining provide valuable insights into its deformation mechanics. Evaluating an FE model predicted chip morphology requires characterisation of chip shape, chip curl and chip flow angles. In this study, a chip morphology characterisation methodology is developed using computed tomography (CT), high-speed imaging and Kharkevich model equations enabling evaluation of FE model’s chip morphology prediction accuracy. Chip formation process in nose turning of AISI 1045 steel is simulated using a 3D FE model for varying feed rate and depth of cut and evaluated against experimental investigations using the employed methodology. The study shows that the methodology is able to characterise chip morphology in nose turning process accurately and enables evaluation of FE model’s chip morphology prediction accuracy. This can enable the finite element model to be deployed in cutting tool design for chip breaker geometry design.

Place, publisher, year, edition, pages
InderScience Publishers, 2017
Keywords
machining, chip-up-curl, chip-side-curl, chip shape, computed tomography, CT, finite element model, chip side flow angle, Johnson cook model, coulomb friction model, advantedge, high speed videography
National Category
Manufacturing, Surface and Joining Technology
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
urn:nbn:se:hv:diva-11575 (URN)10.1504/IJMMM.2017.084009 (DOI)2-s2.0-85019137109 (Scopus ID)
Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2019-05-23Bibliographically approved
Devotta, A. M. & Beno, T. (2016). Characterization of Chip Morphology in Oblique Nose Turning employing High Speed Videography and Computed Tomography Technique. In: Proceedings International Conference on Competitive manufacturing: January 27, 2016 – January 29, 2016 Stellenbosch, South Africa. Paper presented at International Conference on Competitive manufacturing – COMA ‘16”in Stellenbosch, South Africa 2016 (pp. 249-254). Conference on Assembly Technologies & Systems (CIRP)
Open this publication in new window or tab >>Characterization of Chip Morphology in Oblique Nose Turning employing High Speed Videography and Computed Tomography Technique
2016 (English)In: Proceedings International Conference on Competitive manufacturing: January 27, 2016 – January 29, 2016 Stellenbosch, South Africa, Conference on Assembly Technologies & Systems (CIRP), 2016, p. 249-254Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Conference on Assembly Technologies & Systems (CIRP), 2016
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-8669 (URN)978-0-7972-1602-0 (ISBN)
Conference
International Conference on Competitive manufacturing – COMA ‘16”in Stellenbosch, South Africa 2016
Note

Ingår i licentiatuppsats

Available from: 2015-11-14 Created: 2015-11-14 Last updated: 2019-03-13Bibliographically approved
Devotta, A. M., Beno, T. & Löf, R. (2016). Modeling of Chip curl in Orthogonal Turning using Spiral Galaxy describing Function. In: : . Paper presented at “6th International Conference on Competitive Manufacturing – COMA ‘16”in Stellenbosch, South Africa 2016.
Open this publication in new window or tab >>Modeling of Chip curl in Orthogonal Turning using Spiral Galaxy describing Function
2016 (English)Conference paper, Published paper (Refereed)
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-8668 (URN)
Conference
“6th International Conference on Competitive Manufacturing – COMA ‘16”in Stellenbosch, South Africa 2016
Note

Ingår i Licentiatuppsats

Available from: 2015-11-14 Created: 2015-11-14 Last updated: 2019-03-13Bibliographically approved
Devotta, A. M. (2015). Characterization & modeling of chip flow angle & morphology in 2D & 3D turning process. (Licentiate dissertation). Trollhättan: University West
Open this publication in new window or tab >>Characterization & modeling of chip flow angle & morphology in 2D & 3D turning process
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Within manufacturing of metallic components, machining plays an important role and is of vital significance to ensure process reliability. From a cutting tool design perspective,  tool macro geometry  design  based on physics based  numerical modelling  is highly needed  that can predict chip morphology.  The chip morphology describes the chip shape geometry and the chip curl geometry. The prediction of chip flow and chip shape is vital in predicting chip breakage, ensuring good chip evacuation and lower surface roughness.  To this end, a platform where such a  numerical model’s chip morphology prediction  can be compared with experimental investigation is needed and is the focus of this work. The studied cutting processes are orthogonal cutting process and nose turning process. Numerical models that simulate the chip formation process are employed to predict the chip morphology and are accompanied by machining experiments. Computed tomography is used  to scan the chips obtained from machining experiments and its ability to capture the variation in  chip morphology  is evaluated.  For nose turning process,  chip  curl parameters during the cutting process are to be calculated. Kharkevich model is utilized in this regard to calculate the  ‘chip in process’ chip curl parameters. High speed videography is used to measure the chip side flow angle during the cutting process experiments and are directly compared to physics based model predictions. The results show that the methodology developed provides  the framework where advances in numerical models can be evaluated reliably from a chip morphology prediction capability view point for nose turning process. The numerical modeling results show that the chip morphology variation for varying cutting conditions is predicted qualitatively. The results of quantitative evaluation of chip morphology prediction shows that the error in prediction is too large to be used for predictive modelling purposes.

Place, publisher, year, edition, pages
Trollhättan: University West, 2015. p. 67
Series
Licentiate Thesis: University West ; 5
Keywords
Chip curl, Chip flow, Computed tomography, Chip formation, Machining
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-8671 (URN)978-91-87531-20-0 (ISBN)978-91-87531-21-7 (ISBN)
Presentation
2016-03-31, 11:00 (English)
Supervisors
Available from: 2016-04-01 Created: 2015-11-14 Last updated: 2016-04-01Bibliographically approved
Devotta, A. M., Beno, T., Löf, R. & Espes, E. (2015). Quantitative Characterization of Chip Morphology Using Computed Tomography in Orthogonal Turning Process. Paper presented at 9th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME ’14. Procedia CIRP, 33, 299-304
Open this publication in new window or tab >>Quantitative Characterization of Chip Morphology Using Computed Tomography in Orthogonal Turning Process
2015 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 33, p. 299-304Article in journal (Refereed) Published
Abstract [en]

Abstract The simulation of machining process has been an area of active research for over two decades. To fully incorporate finite element (FE) simulations as a state of art tool design aid, there is a need for higher accuracy methodology. An area of improvement is the prediction of chip shape in FE simulations. Characterization of chip shape is therefore a necessity to validate the FE simulations with experimental investigations. The aim of this paper is to present an investigation where computed tomography (CT) is used for the characterization of the chip shape obtained from 2D orthogonal turning experiments. In this work, the CT method has been used for obtaining the full 3D representation of a machined chip. The CT method is highly advantageous for the complex curled chip shapes besides its ability to capture microscopic features on the chip like lamellae structure and surface roughness. This new methodology aids in the validation of several key parameters representing chip shape. The chip morphology’s 3D representation is obtained with the necessary accuracy which provides the ability to use chip curl as a practical validation tool for FE simulation of chip formation in practical machining operations. The study clearly states the ability of the new CT methodology to be used as a tool for the characterization of chip morphology in chip formation studies and industrial applications.

Keywords
validation, Finite lement method, Computed Tomography
National Category
Materials Engineering
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-7888 (URN)10.1016/j.procir.2015.06.053 (DOI)2-s2.0-84939796397 (Scopus ID)
Conference
9th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME ’14
Available from: 2015-08-13 Created: 2015-08-13 Last updated: 2019-03-13Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-3877-9067

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