757 research outputs found
LAMMPS code for "Simulation of Pandemics in Real-cities: Enhanced and Accurate Digital-labs"
No full textThese LAMMPS scripts were used to carry out the calculations for the manuscript
Alessio Alexiadis, Andrea Albano, Amin Rahmat, Mehmet Yildiz, Adnan Kefal, Murat Özbulut, Nadi Bakirci, Diego Alexander Garzon Alvarado, Carlos Alberto Duque-Daza, Javier Hernando Eslava Schmalbach
Simulation of Pandemics in Real-cities: Enhanced and Accurate Digital-lab
From Text to Tech notebooks
No full textSupplementary material for the manuscript 'From Text to Tech: Shaping the Future of Physics-Based Simulations with AI-Driven Generative Models' by Alessio Alexiadis and Bahman Ghiassi. It contains four notebooks used to couple large language models (Openai API) with multiphysics software (Gmesh and Elmer)
Research code supporting the publication “Designing a set of criteria for evaluating Artificial Neural Networks trained with physics-based data to replicate Molecular Dynamics and other particle methods trajectories”
No full textSupplementary material for the manuscript 'Designing a set of criteria for evaluating Artificial Neural Networks trained with physics-based data to replicate Molecular Dynamics and other particle methods trajectories.' by Alessio Alexiadis. It contains four Jupyter notebooks used to carry out the calculations in the manuscript. They require pytorch. A README file is provided in the contents of the folder with details on the code use and Creative Commons license
LAMMPS code for "Simulation of Pandemics in Real-cities: Enhanced and Accurate Digital-labs"
No full textThese LAMMPS scripts were used to carry out the calculations for the manuscript Alessio Alexiadis, Andrea Albano, Amin Rahmat, Mehmet Yildiz, Adnan Kefal, Murat Özbulut, Nadi Bakirci, Diego Alexander Garzon Alvarado, Carlos Alberto Duque-Daza, Javier Hernando Eslava Schmalbach Simulation of Pandemics in Real-cities: Enhanced and Accurate Digital-lab
From Text to Tech notebooks
No full textSupplementary material for the manuscript 'From Text to Tech: Shaping the Future of Physics-Based Simulations with AI-Driven Generative Models' by Alessio Alexiadis and Bahman Ghiassi. It contains four notebooks used to couple large language models (Openai API) with multiphysics software (Gmesh and Elmer)
Research code supporting the publication “Designing a set of criteria for evaluating Artificial Neural Networks trained with physics-based data to replicate Molecular Dynamics and other particle methods trajectories”
No full textSupplementary material for the manuscript 'Designing a set of criteria for evaluating Artificial Neural Networks trained with physics-based data to replicate Molecular Dynamics and other particle methods trajectories.' by Alessio Alexiadis. It contains four Jupyter notebooks used to carry out the calculations in the manuscript. They require pytorch. A README file is provided in the contents of the folder with details on the code use and Creative Commons license
A Laplacian-based algorithm for non-isothermal atomistic-continuum hybrid simulation of micro and nano-flows
Full text linkWe propose a new hybrid algorithm for incompressible micro and nanoflows that applies to non-isothermal steady-state flows and does not require the calculation of the Irving–Kirkwood stress tensor or heat flux vector. The method is validated by simulating the flow in a channel under the effect of a gravity-like force with bounding walls at two different temperatures and velocities. The model shows very accurate results compared to benchmark full MD simulations. In the temperature results, in particular, the contribution of viscous dissipation is correctly evaluated
Research data supporting the publication "How to modify LAMMPS from the prospective of a Particle method researcher"
No full textSource code for the manuscript "How to modify LAMMPS from the prospective of a Particle method researcher" by Andrea Albano, Eve le Guillou, Antoine Danzé, Irene Moulitsas, Iwan H. Sahputra, Amin Rahmat, Carlos Alberto Duque-Daza, Xiaocheng Shang , Khai Ching Ng, Mostapha Ariane and Alessio Alexiadi
The (atomistic-continuum) hybrid taxonomy and the hybrid-hybrid approach
No full textThe Laplacian method, initially introduced in Alexiadis et al. 2013 (1), is here extended to 2D cases. The solution algorithm on which the method is based is modified in order to tackle the issue of numerical noise in 2D domains. We also introduce the idea of the hybrid taxonomy and of hybrid-hybrid methods. The connection of the hybrid taxonomy with the notion of scale inheritance is discussed and the role of the Laplacian method within the taxonomy highlighted.</p
Geopolymers from lunar and Martian soil simulants
Full text linkThis work discusses the geopolymerization of lunar dust simulant JSC LUNAR-1A and Martian dust simulant JSC MARS-1A. The geopolymerization of JSC LUNAR-1A occurs easily and produces a hard, rock-like, material. The geopolymerization of JSC MARS-1A requires milling to reduce the particle size. Tests were carried out to measure, for both JSC LUNAR-1A and JSC MARS-1A geopolymers, the maximum compressive and flexural strengths. In the case of the lunar simulant, these are higher than those of conventional cements. In the case of the Martian simulant, they are close to those of common building bricks
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