- -

Characterization and assessment of composite materials via inverse finite element modeling

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Characterization and assessment of composite materials via inverse finite element modeling

Mostrar el registro completo del ítem

Llopis Albert, C.; Rubio Montoya, FJ.; Valero Chuliá, FJ. (2019). Characterization and assessment of composite materials via inverse finite element modeling. Multidisciplinary Journal for Education, Social and Technological Sciences. 6(2):1-10. https://doi.org/10.4995/muse.2019.12374

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/127675

Ficheros en el ítem

Thumbnail
Nombre: 12374-49539-1-PB.pdf
Tamaño: 1.261Mb
Formato: PDF
Abrir/Preview

Metadatos del ítem

Título: Characterization and assessment of composite materials via inverse finite element modeling
Autor: Llopis Albert, Carlos Rubio Montoya, Francisco José Valero Chuliá, Francisco José
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials
Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny
Fecha difusión:
Resumen:
[EN] Characterizing mechanical properties play a major role in several fields such as biomedical and manufacturing sectors. In this study, a stochastic inverse model is combined with a finite element (FE) approach to infer ...[+]
Palabras clave: Inverse modeling , Finite element , Mechanical properties , Heterogeneity characterization , Biomedical , Uncertainty assessment
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Multidisciplinary Journal for Education, Social and Technological Sciences. (eissn: 2341-2593 )
DOI: 10.4995/muse.2019.12374
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.4995/muse.2019.12374
Tipo: Artículo

References

Charmpis, D. C., G. I. Schueller, M. F. Pellissetti (2007). The need for linking micromechanics of materials with stochastic finite elements: A challenge for materials science. Computational Materials Science 41(1), 27-37. https://doi.org/10.1016/j.commatsci.2007.02.014

Gómez-Hernández, J.J., R.M. Srivastava, (1990). ISIM3D: an ANSI-C three-dimensional multiple indicator conditional simulation program. Computer Geoscience 16(4), 395-440. https://doi.org/10.1016/0098-3004(90)90010-Q

Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, NY, NY, 483 pp. [+]
Charmpis, D. C., G. I. Schueller, M. F. Pellissetti (2007). The need for linking micromechanics of materials with stochastic finite elements: A challenge for materials science. Computational Materials Science 41(1), 27-37. https://doi.org/10.1016/j.commatsci.2007.02.014

Gómez-Hernández, J.J., R.M. Srivastava, (1990). ISIM3D: an ANSI-C three-dimensional multiple indicator conditional simulation program. Computer Geoscience 16(4), 395-440. https://doi.org/10.1016/0098-3004(90)90010-Q

Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, NY, NY, 483 pp.

Ni, Y., M. Y.M. Chiang (2007). Prediction of elastic properties of heterogeneous materials with complex microstructures. Journal of the Mechanics and Physics of Solids 55, 517-532. https://doi.org/10.1016/j.jmps.2006.09.001

Li, G., F. Xu, G. Sun, Q. Li (2014). Identification of mechanical properties of the weld line by combining 3D digital image correlation with inverse modelling procedure. International Journal of Advanced Manufacturing Technology 74, 893-905. https://doi.org/10.1007/s00170-014-6034-x

Llopis-Albert, C., Capilla, J.E. (2009). Stochastic inverse modeling of non multiGaussian transmissivity fields conditional to flow, mass transport and secondary data. 2 Demonstration on a synthetic aquifer. Journal of Hydrology, 371, 53-65. https://doi.org/10.1016/j.jhydrol.2009.03.014

Llopis-Albert, C., Capilla, J.E. (2010). Stochastic simulation of non-Gaussian 3D conductivity fields in a fractured medium with multiple statistical populations: case study. Journal of Hydrologic Engineering, 15, 554-566. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000214

Llopis-Albert, C., Capilla, J.E. (2010a). Stochastic inverse modelling of hydraulic conductivity fields taking into account independent stochastic structures: A 3D case study. Journal of Hydrology 391, 277-288. https://doi.org/10.1016/j.jhydrol.2010.07.028

Llopis-Albert, C., Palacios-Marqués, D., Merigó, J.M. (2014). A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty. Journal of Hydrology 511, 10-16. https://doi.org/10.1016/j.jhydrol.2014.01.021

Llopis-Albert, C., Rubio, F., Valero, F. (2015). Improving productivity using a multi-objective optimization of robotic trajectory planning. Journal of Business Research 68, 1429-1431. https://doi.org/10.1016/j.jbusres.2015.01.027

Llopis-Albert, C., Pulido-Velazquez, D. (2015). Using MODFLOW code to approach transient hydraulic head with a sharp-interface solution. Hydrological processes 29(8), 2052-2064. https://doi.org/10.1002/hyp.10354

Llopis-Albert, C., Merigó, J.M., Xu, Y.J. (2016). A coupled stochastic inverse/sharp interface seawater intrusion approach for coastal aquifers under groundwater parameter uncertainty. Journal of Hydrology 540, 774-783. https://doi.org/10.1016/j.jhydrol.2016.06.065

Llopis-Albert, C. Rubio, F., Valero, F. (2018). Optimization approaches for robot trajectory planning. Multidisciplinary Journal for Education, Social and Technological Sciences 5(1), 1-16. https://doi.org/10.4995/muse.2018.9867

Llopis-Albert, C. Rubio, F., Valero, F. (2018a). Designing Efficient Material Handling Systems Via Automated Guided Vehicles (AGVs). Multidisciplinary Journal for Education, Social and Technological Sciences, 5(2), 97-105.https://doi.org/10.4995/muse.2018.10722

Mortazavi, F., E. Ghossein, M. Lévesque, I. Villemure (2014). High resolution measurement of internal full-field displacements and strains using global spectral digital volume correlation. Optics and Lasers in Engineering 55, 44-52. https://doi.org/10.1016/j.optlaseng.2013.10.007

Rubio, F., Llopis-Albert, C., Valero, F., Suñer, J.L. (2015). Assembly line productivity assessment by comparing optimization-simulation algorithms of trajectory planning for industrial robots. Mathematical Problems in Engineering, vol. 2015, Article ID 931048, 10 pages, 2015. https://doi.org/10.1155/2015/931048

Rubio, F., Llopis-Albert, C., Valero, F., Suñer, J.L. (2016). Industrial robot efficient trajectory generation without collision through the evolution of the optimal trajectory. Robotics and Autonomous Systems 86, 106-112. https://doi.org/10.1016/j.robot.2016.09.008

Rubio, F., Valero, F., Llopis-Albert, C. (2019). A review of mobile robots: Concepts, methods, theoretical framework, and applications. International Journal of Advanced Robotic Systems, 16(2). https://doi.org/10.1177/1729881419839596

Sriramula, S., M. K. Chryssanthopoulos (2009). Quantification of uncertainty modelling in stochastic analysis of FRP composites. Composites Part A: Applied Science and Manufacturing 40(11), 1673-1684. https://doi.org/10.1016/j.compositesa.2009.08.020

Wu, X., Y. Zhu (2017). Heterogeneous materials: a new class of materials with unprecedented mechanical properties. Materials Research Letters 5:8, 527-532. https://doi.org/10.1080/21663831.2017.1343208

Zhang, Z., C. Zhan, K. Shankar, E.V. Morozov, H. Kumar, T. Ray (2017). Sensitivity analysis of inverse algorithms for damage detection in composites. Composite Structures 176, 844-859. https://doi.org/10.1016/j.compstruct.2017.06.019

Zottis, J., Theis, C.A., da Silva, A (2018). Evaluation of experimentally observed asymmetric distributions of hardness, strain and residual stress in cold drawn bars by FEM-simulation. Journal of Materials Research and Technology. https://doi.org/10.1016/j.jmrt.2018.01.004

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem