JabRef references

de Luca Xavier Augusto L, Ross-Jones J, Cantarelli Lopes G, Tronville P, Silveira Gonçalves J, Rädle M and Krause M (2018), "Microfiber Filter Performance Prediction using a Lattice-Boltzmann Method", Communications in Computational Physics., April, 2018. Vol. 23(4), pp. 910-931.

[BibTeX] [DOI]

BibTeX:

@article{augusto:17,
  author = {de Luca Xavier Augusto, L. and Ross-Jones, J. and Cantarelli Lopes, G. and Tronville, P. and Silveira Gonçalves, J.A. and Rädle, M. and Krause, M.J.},
  title = {Microfiber Filter Performance Prediction using a Lattice-Boltzmann Method},
  journal = {Communications in Computational Physics},
  year = {2018},
  volume = {23},
  number = {4},
  pages = {910--931},
  doi = {10.4208/cicp.OA-2016-0180}
}

de Lima Corrêa L, Borguesan B, Krause M and Dorn M (2018), "Three-Dimensional Protein Structure Prediction Based on Memetic Algorithms", Computers & Operations Research. Vol. 91, pp. 160 - 177.

[Abstract] [BibTeX] [DOI] [URL]

Abstract: Abstract Tertiary protein structure prediction is a challenging problem in Structural Bioinformatics and is classified according to the computational complexity theory as a NP-hard problem. In this paper, we proposed a first-principle method that makes use of a priori information about known protein structures to tackle the three-dimensional protein structure prediction problem. We do so by designing a multimodal memetic algorithm that uses an evolutionary approach with a ternary tree-structured population allied to a local search strategy. The method has been developed based on an incremental approach using the combination of promising evolutionary components to address the concerned multimodal problem. Three memetic algorithms focused on the problem are proposed. The first one modifies a basic version of a memetic algorithm by introducing modified global search operators. The second uses a different population structure for the memetic algorithm. And finally, the last algorithm consists of the integration of global operators and multimodal strategies to deal with the inherent multimodality of the protein structure prediction problem. The implementations take advantage of structural knowledge stored in the Protein Data Bank to guide the exploiting and restrict the protein conformational search space. Predicted three-dimensional protein structures were analyzed regarding root mean square deviation and the global distance total score test. Obtained results for the three versions outperformed the basic version of the memetic algorithm. The third algorithm overcomes the results of the previous two, demonstrating the importance of adapting the method to deal with the complexities of the problem. In addition, the achieved results are topologically compatible with the experimental correspondent, confirming the promising performance of our approach.

BibTeX:

@article{correa:17,
  author = {de Lima Corrêa, L. and Borguesan, B. and Krause, M.J. and Dorn, M.},
  title = {Three-Dimensional Protein Structure Prediction Based on Memetic Algorithms},
  journal = {Computers & Operations Research},
  year = {2018},
  volume = {91},
  pages = {160 -- 177},
  url = {https://www.sciencedirect.com/science/article/pii/S0305054817302897},
  doi = {10.1016/j.cor.2017.11.015}
}

Dapelo D, Trunk R, Krause M and Bridgeman J (2019), "Towards Lattice-Boltzmann Modelling of Unconfined Gas Mixing in Anaerobic Digestion", Computers & Fluids. Vol. 180, pp. 11-21.

[Abstract] [BibTeX] [DOI] [URL]

Abstract: A novel Lattice-Boltzmann model to simulate gas mixing in anaerobic digestion is developed and described. For the first time, Euler-Lagrange multiphase, non-Newtonian and turbulence modelling are applied jontly with a novel hybrid boundary condition. The model is validated in a laboratory-scale framework and flow patterns are assessed through Particle Imaging Velocimetry (PIV) and innovative Positron-Emission Particle Tracking (PEPT). The model is shown to reproduce the experimental flow patterns with fidelity in both qualitative and quantitative terms. The model opens up a new approach to computational modelling of the complex multiphase flow in anaerobic digesters and offers specific advantages, such as computational efficiency, over an analogous Euler-Lagrange finite-volume computational fluid dynamics approach.

BibTeX:

@article{dapelo:19,
  author = {Dapelo, D. and Trunk, R. and Krause, M.J. and Bridgeman, J.},
  title = {Towards Lattice-Boltzmann Modelling of Unconfined Gas Mixing in Anaerobic Digestion},
  journal = {Computers & Fluids},
  year = {2019},
  volume = {180},
  pages = {11--21},
  url = {http://www.sciencedirect.com/science/article/pii/S0045793018306728},
  doi = {10.1016/j.compfluid.2018.12.008}
}

Dapelo D, Trunk R, Krause MJ, Cassidy N and Bridgeman J (2020), "The application of Buckingham pi theorem to Lattice--Boltzmann modelling of sewage sludge digestion", Computers & Fluids. Vol. 209, pp. 104632.