Accurate models of H2O and CO2 solubility in silicate melts are vital for understanding volcanic plumbing systems. These models are used to estimate the depths of magma storage regions from melt inclusion volatile con...
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Accurate models of H2O and CO2 solubility in silicate melts are vital for understanding volcanic plumbing systems. These models are used to estimate the depths of magma storage regions from melt inclusion volatile contents, investigate the role of volatile exsolution as a driver of volcanic eruptions, and track the degassing path followed by a magma ascending to the surface. However, despite the large increase in the number of experimental constraints over the last two decades, many recent studies still utilize an earlier generation of models which were calibrated on experimental datasets with restricted compositional ranges. This may be because many of the available tools for more recent models require large numbers of input parameters to be hand-typed (e.g., temperature, concentrations of H2O, CO2, and 8-14 oxides), making them difficult to implement on large datasets. Here, we use a new open-source python3 tool, VESIcal, to critically evaluate the behaviors and sensitivities of different solubility models for a range of melt compositions. Using literature datasets of andesitic-dacitic experimental products and melt inclusions as case studies, we illustrate the importance of evaluating the calibration dataset of each model. Finally, we highlight the limitations of particular data presentation methods, such as isobar diagrams, and provide suggestions for alternatives, and best practices regarding the presentation and archiving of data. This review will aid the selection of the most applicable solubility model for different melt compositions, and identifies areas where additional experimental constraints on volatile solubility are required. Plain Language Summary Being able to accurately model the solubility of H2O and CO2 in magmas is very important for understanding a wide variety of volcanic processes, such as the depths at which magma is stored in the crust, the driving force behind volcanic eruptions, and the release of volatile elements into the atmosphere. Ho
In this scientific paper is presented a software implementation of two side-channel radio attacks: CRA Correlation Radio Attack and TRA Template Radio Attack. The main goal is to recover the AES-128 key from an unknow...
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ISBN:
(纸本)9781728171432
In this scientific paper is presented a software implementation of two side-channel radio attacks: CRA Correlation Radio Attack and TRA Template Radio Attack. The main goal is to recover the AES-128 key from an unknown system. Both attacks are developed in python3 using a Linux-based computer. The algorithm uses Probability Density Functions and the Hamming-weight model. The results are calculated by the Partial Guessing Entropy. The software is run on the CPU.
Genetic algorithms (GAs) are meta-heuristic algorithms that are used for solving constrained and unconstrained optimization problems, mimicking the process of natural selection in biological evolution. Due to the fact...
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Genetic algorithms (GAs) are meta-heuristic algorithms that are used for solving constrained and unconstrained optimization problems, mimicking the process of natural selection in biological evolution. Due to the fact that GAs do not require the optimization function to be differentiable, they are suitable for application in cases where the derivative of the objective function is either unavailable or impractical to obtain numerically. This paper proposes a general purpose genetic algorithm toolkit, implemented in python3 programming language, having only minimum dependencies in NumPy and Joblib, that handle some of the numerical and parallel execution details.
Today39;s demand for precisely predicting chemical reactions from first principles requires research to go beyond Gibbs39; free energy diagrams and consider other effects such as concentrations and quantum tunneli...
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Today's demand for precisely predicting chemical reactions from first principles requires research to go beyond Gibbs' free energy diagrams and consider other effects such as concentrations and quantum tunneling. The present work introduces overreact, a novel python package for propagating chemical reactions over time using data from computational chemistry only. The overreact code infers all differential equations and parameters from a simple input that consists of a set of chemical equations and quantum chemistry package outputs for each chemical species. We evaluate some applications from the literature: gas-phase eclipsed-staggered isomerization of ethane, gas-phase umbrella inversion of ammonia, gas-phase degradation of methane by chlorine radical, and three solvation-phase reactions. Furthermore, we comment on a simple solvation-phase acid-base equilibrium. We show how it is possible to achieve reaction profiles and information matching experiments.
The graphical user interface is a key element in facilitating the use of complex simulation software. This project describes the development of a graphical user interface called "ERSN-OpenMC-Py" for an exist...
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The graphical user interface is a key element in facilitating the use of complex simulation software. This project describes the development of a graphical user interface called "ERSN-OpenMC-Py" for an existing neutron simulation code, OpenMC. The main goal is to make simulation more accessible to a wider audience by providing a user-friendly and intuitive user interface. The process of developing the graphical user interface is described in detail, including the different stages of development such as user interface design, user interface implementation, and user interface integration with the OpenMC simulation code. The development tools used, such as python3 and PyQt5, are also explained. The user interface allows the user to control the simulation parameters and interact with the simulation results. Key features of the user interface include visualization of simulation results, modification of simulation parameters, saving and loading simulation configurations, as well as managing output files. The end result is a functional user interface that allows users to easily visualize simulation results and control simulation parameters in an intuitive manner. This user interface also provides a better user experience for non -programming experts who wish to use the simulation code for their own projects. Program summary Program Title: ERSN-OpenMC-Py, version 1.0 CPC Library link to program files: https://doi .org /10 .17632 /83xrdht7mz .1 Developer's repository link: https://github .com /mohamedlahdour /ERSN -OpenMC -Py Licensing provisions: GPLv2 Programming language: python3 External routines/libraries: NumPy, Matplotlib, PyQt5 Nature of problem: The program is designed to be utilized in the everyday workflow for tasks such as preparing input files for the OpenMC code and analyzing the resulting calculations. Solution method: The graphical user interface of the OpenMC is created using PyQt5. Figures are plotted by means of matplotlib library.
The study of growth of woody species is a challenging issue, primarily due to the complexity of the involved processes, which span broad spatial and temporal scales. Very often, this latter aspect almost precludes com...
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The study of growth of woody species is a challenging issue, primarily due to the complexity of the involved processes, which span broad spatial and temporal scales. Very often, this latter aspect almost precludes complete experimentation, thereby hindering the comparison between theoretical predictions and real-world observations. Computer simulations offer an alternative approach, allowing for data collection based on theoretical assumptions, and has been applied to the analysis of different features in plant development, as the production of secondary vascular tissues, xylem and phloem, in woody plants. However, the simulation of bark development faces added difficulties, due to the scarcity of experimental observations to base the model on. In this article, we introduce a computer model designed to simulate bark formation based on mechanical stimuli acting on the various types of cells comprising this tissue. Our model can be conceptualized as a cellular automaton of variable size with non-local updating rules. By adjusting the parameters defining the model, we investigate the most influential factors in bark development, obtaining the most common bark types observed in trees. Furthermore, we provide an intuitive interface, making it suitable for educational purposes as well.
The behavior of the nuclear reactor in response to any sudden change in reactivity is very important for reactor control. Positive reactivity insertions causes power excursion and could have a destructive impact on th...
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The behavior of the nuclear reactor in response to any sudden change in reactivity is very important for reactor control. Positive reactivity insertions causes power excursion and could have a destructive impact on the reactor core. The aim of the study is to investigate the safety features of a material test reactor (MTR) during reactivity transient with emphasis on the capability of the mathematical modeling using programming language. Therefore a mathematical model using python3.6;high-level programming language is developed to solve the point kinetic equations taking into account Doppler and moderator feedback effects. The model is validated with AIREKMOD_RR;point kinetic computer code for reactivity transient analysis in nuclear research reactors. The results of the python model demonstrate the inherent safety features of the MTR reactor. Also, there is good agreement between the results of the python model and AIREKMOD_RR code, illustrating the efficiency of the python model in simulating the behavior of the reactor core under reactivity transient.
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