This paper aims to develop a finite element (FE) model precisely simulating the multi-particle impact in the radial mode abrasive waterjet turning (AWJT). An explicit dynamic analysis was carried out to predict the cr...
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This paper aims to develop a finite element (FE) model precisely simulating the multi-particle impact in the radial mode abrasive waterjet turning (AWJT). An explicit dynamic analysis was carried out to predict the crater profile resulting from the impact of the abrasive particles along a limited segment of the jet pass over the workpiece surface. The effect of both momentum transfer loss and abrasive load ratio was taken into consideration while calculating the impact velocity of the abrasive particles. To build a user-friendly model, the scripting feature of ABAQUS was involved to automatically perform all the repetitive modeling procedures. The presented FE model considers four variable turning parameters tested at five levels each, including impact velocity, abrasive mass flow rate, traverse rate, and workpiece speed. The obtained crater profile from the simulation process was utilized to calculate the depth of cut (DOC) at different parameter combinations. A comparison between the numerical and experimental results shows a good agreement with an average absolute relative error of 9.74%.
This study investigates the application of quantum mechanical (QM) and multiscale computational methods in understanding the reaction mechanisms and kinetics of S(N)2 reactions involving methyl iodide with NH2OH and N...
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This study investigates the application of quantum mechanical (QM) and multiscale computational methods in understanding the reaction mechanisms and kinetics of S(N)2 reactions involving methyl iodide with NH2OH and NH2O-, as well as the Claisen rearrangement of 8-(vinyloxy)dec-9-enoate. Our aim is to evaluate the accuracy and effectiveness of these methods in predicting experimental outcomes for these organic reactions. We achieve this by employing QM-only calculations and several hybrids of QM and molecular mechanics (MM) methods, namely QM/MM, QM1/QM2, and QM1/QM2/MM methodologies. For the S(N)2 reactions, our results demonstrate the importance of explicitly including solvent effects in the calculations to accurately reproduce the transition state geometry and energetics. The multiscale methods, particularly QM/MM and QM1/QM2, show promising performance in predicting activation energies. Moreover, we observe that the size of the MM active region significantly affects the accuracy of calculated activation energies, highlighting the need for careful consideration during the setup of multiscale calculations. In the case of the Claisen rearrangement, both QM-only and multiscale methods successfully reproduce the proposed reaction mechanism. However, the activation free energies calculated using a continuum solvation model, based on single-point calculations of QM-only structures, fail to account for solvent effects. On the other hand, multiscale methods more accurately capture the impact of solvents on activation free energies, with systematic error correction enhancing the accuracy of the results. Furthermore, we introduce a python code for setting up multiscale calculations with ORCA, which is available on GitHub at https://***/iranimehdi/pdbtoORCA.
Investigating the earliest stages of crystallization requires the transmission electron microscope (TEM) and is particularly challenging for materials which can be affected by the electron beam. Typically, when imagin...
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Investigating the earliest stages of crystallization requires the transmission electron microscope (TEM) and is particularly challenging for materials which can be affected by the electron beam. Typically, when imaging at magnifications high enough to observe local crystallinity, the electron beam's current density must be high to produce adequate image contrast. Yet, minimizing the electron dose is necessary to reduce the changes caused by the beam. With the advent of a sensitive, high-speed, direct-detection camera for a TEM that is corrected for spherical aberration, it is possible to probe the early stages of crystallization at the atomic scale. High-quality images with low contrast can now be analyzed using new computing methods. In the present paper, this approach is illustrated for crystallization in a Ge2Sb2Te5 (GST-225) phase-change material which can undergo particularly rapid phase transformations and is sensitive to the electron beam. A thin (20 nm) film of GST-225 has been directly imaged in the TEM and the low-dose images processed using python scripting to extract details of the nanoscale nuclei. Quantitative analysis of the processed images in a video sequence also allows the growth of such nuclei to be followed.
In this paper, a plug-in - FibrePlug - developed within the ABAQUSTM Simple GUI (RSG) and Fox GUI development environments is introduced. In contrast to traditional meso-scale modeling, FibrePlug provides an advanced ...
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In this paper, a plug-in - FibrePlug - developed within the ABAQUSTM Simple GUI (RSG) and Fox GUI development environments is introduced. In contrast to traditional meso-scale modeling, FibrePlug provides an advanced user-friendly environment for simultaneously modeling fibers at micro- and meso-scales. With FibrePlug, the yarn level fabrics may be replaced by a specific user-defined number of representative bundles also known as virtual fibers. Further customizations, including the modification of the number of virtual fibers, are available within the GUI. In addition to the FibrePlug's microscale modeling capabilities, readers are also introduced with the beam and solid element discretization features within the plug-in and their implications to computational efficiencies. The feature of the plug-in's hybrid multi-scale model generation is also demonstrated. Furthermore, the accuracy of a uniform beam-element model generated with FibrePlug is validated by simple tensile tests performed with the 3D DIC equipment. Despite noticeable deviations in mechanical properties with respect to traverse direction, these properties are satisfactorily predicted along the loading direction.
We present TopoStats, a python toolkit for automated editing and analysis of Atomic Force Microscopy images. The program automates identification and tracing of individual molecules in circular and linear conformation...
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We present TopoStats, a python toolkit for automated editing and analysis of Atomic Force Microscopy images. The program automates identification and tracing of individual molecules in circular and linear conformations without user input. TopoStats was able to identify and trace a range of molecules within AFM images, finding, on average, similar to 90% of all individual molecules and molecular assemblies within a wide field of view, and without the need for prior processing. DNA minicircles of varying size, DNA origami rings and pore forming proteins were identified and accurately traced with contour lengths of traces typically within 10 nm of the predicted contour length. TopoStats was also able to reliably identify and trace linear and enclosed circular molecules within a mixed population. The program is freely available via GitHub (https://***/afm-spm/topostates) and is intended to be modified and adapted for use if required.
Recent research has shown that 95% of network tasks are monitored manually. This has consumed a lot of money and time. Many workers need to be employed for the same tasks in network deployment. This analysis aims to i...
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ISBN:
(纸本)9781665403382
Recent research has shown that 95% of network tasks are monitored manually. This has consumed a lot of money and time. Many workers need to be employed for the same tasks in network deployment. This analysis aims to identify the best method that can improve the efficiency of scripting in configuring network devices and to find the differences in performance in the time needed to configure network devices between manual method and automation. Network topology was designed that contains 36 Cisco devices with different IOS versions. The topology was designed precisely to implement automation in a practical way that can reduce the time needed for configuration with no errors. Based on data analysis from the emulator that mimics a realistic network environment, it is identified that automation is a superior method in configuring Cisco devices because automation can save up to 99% of the time needed. The performance presents the automation method required only 120 seconds to configure all Cisco devices compared to the manual method that required 5797 seconds. Besides, zero errors were reported in automation, while 2 errors were identified in the manual method. This research is significant and practical in helping the network administrators to handle network configurations and automation in deployments of the network systems in an organization.
This paper presents the development of a lattice structure design (LSD) tool for building and analyzing different configurations of 3D-printed lattice structure (LS). This tool was developed via ABAQUS graphical user ...
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This paper presents the development of a lattice structure design (LSD) tool for building and analyzing different configurations of 3D-printed lattice structure (LS). This tool was developed via ABAQUS graphical user interface (GUI) based on python code. Due to the extensive research activities in the field of lattice design using experimental and computational methods, there is a high demand for finding new techniques to reduce the computational time and human effort. Also, several challenges were revealed while creating finite element models for lattices of complicated geometries. These models showed the capability for capturing the elastic and inelastic mechanical responses of LSs during the compression test. Consequently, the LSD tool was designed not only to build lattice structures in a short time and simple way, but also to analyze the associated compressive mechanical behavior that goes beyond initial yielding to cover the entire crushing behavior. This paper examined many challenges involved in generating and decomposing the lattice geometry, creating hexahedron elements and optimizing the mesh density, assigning and inserting the material type, activating the face recognition to define the boundary and loading conditions, and conducting linear and polar patterns. Finally, to demonstrate the effectiveness of the new approach in designing and analyzing LSs, finite element results were validated with the previous experimental findings.
PyMOL is often used to generate images of biomolecular structures. Hundreds of parameters in PyMOL provide precise control over the appearance of structures. We developed 241 python functions-called "shortcuts&qu...
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PyMOL is often used to generate images of biomolecular structures. Hundreds of parameters in PyMOL provide precise control over the appearance of structures. We developed 241 python functions-called "shortcuts"-that extend and ease the use of PyMOL. A user runs a shortcut by entering its name at the PyMOL prompt. We clustered the shortcuts by functionality into 25 groups for faster look-up. One set of shortcuts generates new styles of molecular representation. Another group saves files with time stamps in the file names;the unique filenames avoid overwriting files that have already been developed. A third group submits search terms in the user's web browser. The help function prints the function's documentation to the command history window. This documentation includes the PyMOL commands that the user can reuse by copying and pasting onto the command line or into a script file. The shortcuts should save the average PyMOL user many hours per year searching for code fragments in their computer or on-line. Statement for Lay Public Computer-generated images of protein structures are vital to the interpretation of and communication about the molecular structure of proteins. PyMOL is a popular computer program for generating such images. We made a large collection of macros or shortcuts that save time by executing complex operations with a few keystrokes.
A methodology for quantification of the impact of sediment transport on flood hazard is proposed. The applied algorithm consists of several python scripts for automation of sediment routing, hydrodynamic simulations, ...
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A methodology for quantification of the impact of sediment transport on flood hazard is proposed. The applied algorithm consists of several python scripts for automation of sediment routing, hydrodynamic simulations, and geoprocessing of results. Flood hazard maps are uniquely linked with particular simulations of morphological changes in a river. Finally, the maps are stochastically processed. The proposed procedure was applied for a selected reach of the Warta river, located in Poland. Simulations were run for 6- and 12-year flow series composed randomly on the basis of historical data. The 30 flow series for each period and four functions describing the transport of sediment were treated as uncertain variables. It was assumed that the features characterising the mean sample may properly represent the sediment content in the river reach studied. The final results are presented as maps showing the probabilities of inundation. The comparison of results with literature data confirmed the significance of the impact related to sediment transport processes on the quantification of flood hazard uncertainty. The main advantages of the presented algorithm are effective management of simulations and processing of results obtained in 240 runs of the sediment routing model.
In this study, landslide susceptibility maps (LSM) of the Akincilar region were produced with the methods of frequency ratio (FR), information value (IV), logistic regression (LR), random forest (RF), and multi-layer ...
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In this study, landslide susceptibility maps (LSM) of the Akincilar region were produced with the methods of frequency ratio (FR), information value (IV), logistic regression (LR), random forest (RF), and multi-layer perceptron (MLP) by using a new GIS-based toolbox (LSAT, Landslide Susceptibility Assessment Tool). LSAT was used to assess the landslide susceptibility of the Akincilar region located 150 km northwest of Sivas city (Turkey). LSM was successfully constructed using five different methods for the study area. Area under the curve (AUC) values were calculated as 70.95%, 71.85%, 72.57%, 72.67%, 73.93% for prediction rate of FR, IV, LR, MLP and RF methods, respectively. Time-consuming processes are one of the significant problems of constructing LSM. LSAT can be used easily in this type of study and minimizes such problems. Data preparation processes, visualization of modeling results, and accuracy assessment of LSM could very quickly and automatically be done thanks to this tool.
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