Simulating Pitting Corrosion in AM 316L Microstructures Through Phase Field Methods and Computational Modeling

This work investigates how the crystallographic features of additive manufactured (AM) microstructures impact the pitting corrosion process through computational simulations of phase field models. Crystallographic influence is explored by introducing orientation dependencies into the corrosion potentials and elastic constants of the model through microstructural data provided from AM 316L samples. Comparisons of evolved pit morphologies and stress responses are made to a standard homogeneous, semi-circular model to better highlight how the complexity of AM microstructures affects pit evolution and stress concentrations. The results illustrate that AM-informed modeling cases produce larger, deeper pits with numerous locations of elevated stress concentrations along the pit front.

A case study on using the FDS tool for on-site fire investigation

When investigating a fire type event, one has to have in mind that maybe the most important aspect is the identification of the source of ignition. Nowadays, commercial and open-source software are available and can be used during such investigations. The fire field model - Fire Dynamics Simulator (FDS) is one of the most popular numerical model used for fire investigation. The purpose of this paper is to demonstrate the importance of computer simulations when two hypotheses, Arson effect with multiple fireplaces and electric short circuit are taken into consideration as the cause of the fire. To virtually simulate the findings at the fire site, the FDS tool (Computational Fluid Dynamics) was used. Computational simulations for the two scenarios revealed that the multiple fireplaces scenario, the initial ignition at both the warehouse and the roof of the annex, illustrates the effects of the fire in a similar way to those found at the site, while the scenario with the initial source on the wall of the room with the electrical panel produces a fire located at the level of the construction and is not transmitted to the annex. Consequently, the results obtained validate the multiple outbreak (Arson effect) scenario.

Minimizing IL-6 and IL-10 signalling pathway elements using lumping species and parameters

There are many cell signalling pathways that include a higher set of elements. Understanding the dynamics of such systems becomes a difficult issue in systems biology. Mathematical approaches with computational simulations provide a wide range to simplify such complex models and to predicate their dynamics. A powerful technique for reducing the complexity of cell signalling pathways is lumping variables and parameters. In this work, we suggest this technique to reduce the number of elements of IL-6 and IL-10 signalling pathways. The reduced model given in this work provides one a better understanding and predicting some model dynamics, and gives accurate approximate solutions. Computational results show that there is a good agreement between the model dynamics for the original and the simplified models.

A Model for Traffic Forwarding through Service Function Chaining using Deep Reinforcement Learning Techniques

The development of new communication networks to offer innovative services has increased the volume of data. With the introduction of Deep Reinforcement Learning and Service Function Chaining architecture, new research opportunities have emerged to propose solutions to the new challenges. This work proposes a model through computational simulations how these techniques can be applied. The model was evaluated using two variations of the Deep Q-Network algorithm over the CIC-Darknet dataset. Results showed that both variations are a promising mechanism to make the networks more autonomous and intelligent. to demonstrate

Lipids in the Piezo1 channel pore: gating mechanism, or simulation artifact?

Opening and closure of certain mechanosensitive ion channels have recently been linked with the presence of lipids in or near their pores. Although non-conducting structures of mechanosensitive Piezo channels do not show the presence of lipids in the pore, computational simulations suggest whole phospholipids enter the Piezo1 pore in the closed state. Here, to probe this phenomenon, we conduct coarse-grained (CG) and all-atom (AA) simulations of Piezo1 with different solvation algorithms and equilibrium protocols, including CG-to-AA reverse mapping from Martini CG force field to CHARMM AA force field. Our results show that the lack of initial hydration of the upper pore region, enabled by common CG but not AA solvation algorithms, allows entry of whole lipids through gaps between pore helices during subsequent equilibrium simulations. Absolute binding free energy calculations show that these lipids are thermodynamically unfavorable, indicating they are likely kinetically trapped in the pore during microsecond-long AA simulations. An alternative equilibrium protocol is proposed to avoid such simulation artifact for channels whose pores are walled with transmembrane gaps. This work underscores the notion that, as simulated systems become increasingly complex, interpretation of simulated data in physiological contexts requires extra precautions. When no experimental data is available, free energy approaches such as those implemented here appear as trustworthy validations of results observed from MD trajectories.

LIFE AS WE DO NOT KNOW IT

Information plays a critical role in complex biologicalsystems. This article proposes a role for information processing in questions around the origin of life and suggests how computational simulations may yield insights into questions related to the origin of life. Such a computational model of the origin of life would unify thermodynamics with information processing and we would gain an appreciation of why proteins and nucleotides evolved as the substrate of computation andinformation processing in living systems that we see on Earth. Answers to questions like these may give us insights into noncarbon based forms of life that we could search for outside Earth. I hypothesize that carbon-based life forms are only one amongst a continuum of life-like systems in the universe.Investigations into the role of computational substrates that allow information processing is important and could yield insights into:1) novel non-carbon based computational substrates thatmay have “life-like” properties, and2) how life may have actually originated from non-life onEarth. Life may exist as a continuum between non-life and life and we may have to revise our notion of life and how common it is in the universe.Looking at life or life-like phenomena through the lens ofinformation theory may yield a broader view of life.

A NEW SCALING STRATEGY OF BUBBLING FLUIDIZED BED REACTORS BASED ON POPULATION-BALANCE MODEL

This work proposes a new strategy for the scaling of bubbling fluidized bed reactors. This strategy is based on the bubble size distribution, bubble coalescence phenomenon, and the chemical reactivity, allowing to deduct the dimensionless number Chejne-Macias-Maya that must remain constant at different scales to guarantee the fluidization regime. The proposed strategy is validated from computational simulations carried out at different operating conditions. Additionally, limits for the validity of this scaling strategy were determined, which agrees with those reported in the literature.