DICTRA

DICTRA, a tool for simulation of diffusional transformations in alloys. In the present paper, a general survey of the diffusion-controlled transformations (DICTRA) software is given. DICTRA is an engineering tool for diffusion simulations in multicomponent alloys. The simulations are based on multicomponent diffusion and thermodynamic data, both obtained by analyzing and assessing experimental information. This allows for many different cases to be studied as soon as the underlying data are available. DICTRA is not a complete simulation tool because only geometries that can be transformed into one space variable can be treated, but many well posed problems of practical interest may be solved. The program contains several different models, which are discussed in the present paper. Each model has its own applications and several examples from recent simulations are given in order to demonstrate the usage of the particular models.


References in zbMATH (referenced in 9 articles )

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  1. Yi, Min; Xu, Bai-Xiang; Gutfleisch, Oliver: Computational study on microstructure evolution and magnetic property of laser additively manufactured magnetic materials (2019)
  2. Zhangqi Chen, Qiaofu Zhang, Ji-Cheng Zhao: pydiffusion: A Python Library for Diffusion Simulation and Data Analysis (2019) not zbMATH
  3. Andriollo, Tito; Hellström, Kristina; Sonne, Mads Rostgaard; Thorborg, Jesper; Tiedje, Niels; Hattel, Jesper: Uncovering the local inelastic interactions during manufacture of ductile cast iron: how the substructure of the graphite particles can induce residual stress concentrations in the matrix (2018)
  4. Plotkowski, A.; Krane, M. J. M.: The discrete nature of grain attachment models in simulations of equiaxed solidification (2017)
  5. Plotkowski, A.; Krane, M. J. M.: The effect of velocity based packing schemes on macrosegregation development in simulations of equiaxed solidification (2016)
  6. Smith, Jacob; Xiong, Wei; Cao, Jian; Liu, Wing Kam: Thermodynamically consistent microstructure prediction of additively manufactured materials (2016)
  7. Smith, Jacob; Xiong, Wei; Yan, Wentao; Lin, Stephen; Cheng, Puikei; Kafka, Orion L.; Wagner, Gregory J.; Cao, Jian; Liu, Wing Kam: Linking process, structure, property, and performance for metal-based additive manufacturing: computational approaches with experimental support (2016)
  8. Campisi, Laura D.: Multilayer perceptrons as function approximators for analytical solutions of the diffusion equation (2015)
  9. Illingworth, T. C.; Golosnoy, I. O.: Numerical solutions of diffusion-controlled moving boundary problems which conserve solute (2005)