SIMULATION: Transactions of The Society for Modeling and Simulation International

doi: 10.1177/00375497231156348pmid: N/A

Abdalah, Mariela

doi: 10.1177/00375497211014935pmid: N/A

This paper presents the development of ADMLib, a new high-productivity and efficient Modelica package to model and simulate anaerobic digestion systems inside the structured modeling framework. Library components were organized into subpackages to encompass growth kinetics, non-biochemical reaction kinetics, acid-base, heat transfer, and inhibition processes, as well as the characteristics of substances and gas phase. A validation of the dynamic behavior response was performed where the implemented functions were used to simulate different bibliographic models. A brief performance analysis was carried out, in order to evaluate the component-based approach of ADMLib against the traditional differential algebraic equation (DAE) systems. The implementation testing demonstrated that the developed package was reliable, usable, and performant.

Bea, EA; Mancardo Viotti, A; Carusela, MF; Monastra, AG; Soba, A

doi: 10.1177/00375497211009611pmid: N/A

In this work we compare different implementations of two interatomic potential models, one the empirical Tersoff–Brenner and the other the semi-empirical tight-binding, to be used in the thermal transport study of silicon nanosystems. The calculations are based on molecular dynamics simulations. In the case of Tersoff–Brenner potential, two free software packages were used, while for tight-binding potential, an in-house code was developed. Both approaches require an enormous amount of computing effort, so the use of acceleration tools for adequate performance is crucial. We present a detailed study of each computational tool used: efficiency, advantages and disadvantages, and the results of application to the calculation of thermal conductance of structured silicon nanocrystals subjected to a temperature gradient.

Rocchetti, Néstor; Nesmachnow, Sergio; Tancredi, Gonzalo

doi: 10.1177/0037549721998766pmid: N/A

This article describes the advances in the design, implementation, and evaluation of efficient algorithms for self-gravity simulations in astronomical agglomerates. Three algorithms are presented and evaluated: the occupied cells method, and two variations of the Barnes–Hut method using an octal and a binary tree. Two scenarios are considered in the evaluation: two agglomerates orbiting each other and a collapsing cube. The results show that the proposed octal tree Barnes–Hut method allows improving the performance of the self-gravity calculation up to 100 times with respect to the occupied cells method, while having good numerical accuracy. The proposed algorithms are efficient and accurate methods for self-gravity simulations in astronomical agglomerates.

Muraña, Jonathan; Nesmachnow, Sergio

doi: 10.1177/00375497211020083pmid: N/A

This article presents the evaluation of multicriteria planning heuristics for demand response in datacenters and supercomputing facilities. This is a relevant problem for science nowadays, when the growing application of cutting-edge technologies (numerical methods, big data processing, artificial intelligence, smart systems, etc.) has raised the energy demands in datacenters. The proposed approach involves a negotiation mechanism for colocation datacenters, where the datacenter operator agrees prices and quality of service with a group of tenants. Twelve different multicriteria heuristics are proposed for planning using both local and global information at tenants and datacenter operator levels. The proposed approach is evaluated applying simulations over realistic scenarios considering different tenant sizes and heterogeneity levels that model different business models for datacenters. Several metrics are computed and Pareto analysis is provided. The main results indicate that accurate trade-off values between the problem objectives are obtained, offering different options for decision making. The proposed approach provides a useful and applicable method for demand response planning in modern datacenters.