The U.S. power grid is undergoing a transformation. Operational focus is shifting away from utilities with large centralized generators at the transmission level and moving toward individual customers who contribute g...
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ISBN:
(纸本)9781728131085
The U.S. power grid is undergoing a transformation. Operational focus is shifting away from utilities with large centralized generators at the transmission level and moving toward individual customers who contribute generation from distributed energy resources (DERs) at the distribution level Utility-scale renewable generation, meanwhile, continues to span across both transmission and distribution networks. The current interconnection process for small- to grid-scale DERs is well-defined, time-consuming and complex. It involves studying every DER application within a network model to identify its impacts on the network, both locally and systemwide. New technologies and applications are expanding the use cases for the capacity analysis approach. which is radically changing how interconnections are evaluated. Rather than focusing on individual DER connections, capacity analysis can allow you to study nearly every possible interconnection scenario. By identifying and understanding the ideal locations and usage times for DERs - and optimizing operating conditions - capacity analysis is making faster approvals and interconnections. as well as higher DER penetration, possible. This presentation will cover recent implementations of capacity analysis performed for Southern California Edison.
Heart is one of the most important organs in Human's body. In life, some changes may happen that may bring various diseases like, blood pressure, sugar, etc. Similarly, heart failure is also a dreadful disease. He...
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Heart is one of the most important organs in Human's body. In life, some changes may happen that may bring various diseases like, blood pressure, sugar, etc. Similarly, heart failure is also a dreadful disease. Heart failure is a serious condition and there is no cure for this disease. It is a situation in which the patient's heart is not pumping the blood well as the normal heart pumps. Heart Failure prediction is a complex task in the medical field. The rates of heart failure have been increasing day by day as the rate of population is also increasing day by day. This paper aims at analyzing the machine learning algorithms based on the percentage of various performance metrics (such as, Accuracy, Precision and Recall). The machine learning methodology is proposed. The most suitable algorithm for each metrics is predicted. It is analyzed using the specific variables in the dataset by using the python programming as well as different supervised machine learning algorithms which include, Decision Tree, Logistic Regression, KNN and Random Forest. Anaconda jupyter notebook is used for implementing python scripting.
Triaxial testing serves as a fundamental method for evaluating the elastic and strength properties of rocks,crucial for developing accurate 3D geomechanical *** paper presents a novel method for determining strength p...
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Triaxial testing serves as a fundamental method for evaluating the elastic and strength properties of rocks,crucial for developing accurate 3D geomechanical *** paper presents a novel method for determining strength parameters by incorporating the dependence of uniaxial compressive strength(UCS)on P-wave velocity into the Hoek-Brown ***,a new approach is introduced to process triaxial test data efficiently using python libraries such as SciPy,NumPy,Matplotlib,and ***,the paper addresses challenges in determining elastic parameters through triaxial testing.A python script is developed to automate the calculation of elastic modulus and Poisson's ratio,over-coming subjectivity in selecting the linear portion of stress-strain *** script optimally identifies the linear region by minimizing the fit error with appropriate constraints,ensuring a more objective and standardized *** proposed methodologies are demonstrated using limestone specimens from Central Asian gas *** innovations offer faster,more reliable results,reducing error and enhancing the comparability of analyses in geomechanics,with potential applications across various geological settings.
Micromechanics is a technique for the analysis of composites or heterogeneous materials which focuses on the components of the intended structure. Each one of the components can exhibit isotropic behavior, but the mic...
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Micromechanics is a technique for the analysis of composites or heterogeneous materials which focuses on the components of the intended structure. Each one of the components can exhibit isotropic behavior, but the microstructure characteristics of the heterogeneous material result in the anisotropic behavior of the structure. In this research, the general mechanical properties of a 3D anisotropic and heterogeneous Representative Volume Element (RVE), have been determined by applying periodic boundary conditions (PBCs), using the Asymptotic Homogenization Theory (AHT) and strain energy. In order to use the homogenization theory and apply the periodic boundary conditions, the ABAQUS scripting interface (ASI) has been used along with the python programming language. The results have been compared with those of the Homogeneous Boundary Conditions method, which leads to an overestimation of the effective mechanical properties. According to the results, applying homogenous boundary conditions results in a 33% and 13% increase in the shear moduli G(23) and G(12), respectively. In polymeric composites, the fibers have linear and brittle behavior, while the resin exhibits a non-linear behavior. Therefore, the nonlinear effects of resin on the mechanical properties of the composite material is studied using a user-defined subroutine in Fortran (USDFLD). The non-linear shear stress-strain behavior of unidirectional composite laminates has been obtained. Results indicate that at arbitrary constant stress as 80 MPa in-plane shear modulus, G12, experienced a 47%, 41% and 31% reduction at the fiber volume fraction of 30%, 50% and 70%, compared to the linear assumption. The results of this study are in good agreement with the analytical and experimental results available in the literature
In this paper, the impact of maximum flow uncertainty on flood hazard zone is analyzed. Two factors are taken into account: (1) the method for determination of maximum flows and (2) the limited length of the data seri...
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In this paper, the impact of maximum flow uncertainty on flood hazard zone is analyzed. Two factors are taken into account: (1) the method for determination of maximum flows and (2) the limited length of the data series available for calculations. The importance of this problem is a consequence of the implementation of the EU Flood Directive in all EU member states. The factors mentioned seem to be among the most important elements responsible for potential uncertainty and inaccuracy of the developed flood hazard maps. Two methods are analyzed, namely the quantiles method and the maximum likelihood method. The maximum flows are estimated for the Wronki gauge station located in the reach of the Warta river. This simple river system is located in the central part of Poland. The length of the available data is 44years. Hence, the series of the lengths 40, 30 and 20years are tested and compared with reference calculations for 44years. The hydrodynamic model HEC-RAS is used to calculate water surface profilesin steady state flow. The python scripting language is applied for automation of HEC-RAS calculations and processing of final results in the form of inundation maps. The number of trials for each factor is not huge to keep the presented methodology useful in practice. The chosen measure of uncertainty is the range of variability for maximum flow values as well as inundation areas. The estimated values stressed the great importance of the factors analyzed for the uncertainty of the maximum flows as well as inundation areas. The impact of the data series length on the maximum flows is straightforward;a shorter data series gives a wider range of variability. However, the dependencies between other factors are more complex. Hence, the application of methodology based on the simulation and GIS data processing for assessment of this problem seems to be quite a good approach.
The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic mode...
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The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous.
Scripts are used in PyMOL to exert precise control over the appearance of the output and to ease remaking similar images at a later time. We developed horizontal scripts to ease script development. A horizontal script...
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Scripts are used in PyMOL to exert precise control over the appearance of the output and to ease remaking similar images at a later time. We developed horizontal scripts to ease script development. A horizontal script makes a complete scene in PyMOL like a traditional vertical script. The commands in a horizontal script are separated by semicolons. These scripts are edited interactively on the command line with no need for an external text editor. This simpler workflow accelerates script development. In using PyMOL, the illustration of a molecular scene requires an 18-element matrix of view port settings. The default format spans several lines and is laborious to manually reformat for one line. This default format prevents the fast assembly of horizontal scripts that can reproduce a molecular scene. We solved this problem by writing a function that displays the settings on one line in a compact format suitable for horizontal scripts. We also demonstrate the mapping of aliases to horizontal scripts. Many aliases can be defined in a single script file, which can be useful for applying costume molecular representations to any structure. We also redefined horizontal scripts as python functions to enable the use of the help function to print documentation about an alias to the command history window. We discuss how these methods of using horizontal scripts both simplify and enhance the use of PyMOL in research and education.
The minimization of weight and maximization of payload is an ever challenging design procedure for air vehicles. The present study has been carried out with an objective to redesign control surface of an advanced allm...
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The minimization of weight and maximization of payload is an ever challenging design procedure for air vehicles. The present study has been carried out with an objective to redesign control surface of an advanced allmetallic fighter aircraft. In this study, the structure made up of high strength aluminum, titanium and ferrous alloys has been attempted to replace by carbon fiber composite (CFC) skin, ribs and stiffeners. This study presents an approach towards development of a methodology for optimization of first-ply failure index (FI) in unidirectional fibrous laminates using Genetic-Algorithms (GA) under quasi-static loading. The GAs, by the application of its operators like reproduction, cross-over, mutation and elitist strategy, optimize the ply-orientations in laminates so as to have minimum FI of Tsai-Wu first-ply failure criterion. The GA optimization procedure has been implemented in MATLAB and interfaced with commercial software ABAQUS using python scripting. FI calculations have been carried out in ABAQUS with user material subroutine (UMAT). The GA's application gave reasonably welloptimized ply-orientations combination at a faster convergence rate. However, the final optimized sequence of ply-orientations is obtained by tweaking the sequences given by GA's based on industrial practices and experience, whenever needed. The present study of conversion of an all metallic structure to partial CFC structure has led to 12% of weight reduction. Therefore, the approach proposed here motivates designer to use CFC with a confidence.
To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on re...
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To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on recent advances in Bruker BioSpin NMR spectrometer hardware and software. Given the daunting challenge for non-NMR experts to collect quality spectra, our goal was to increase user accessibility, provide customized functionality, and improve the consistency and reliability of resultant data. This methodology, NMRbot, is encoded in a set of scripts written in the python programming language accessible within the Bruker BioSpin TopSpin (TM) software. NMRbot improves automated data acquisition and offers novel tools for use in optimizing experimental parameters on the fly. This automated procedure has been successfully implemented for investigations in metabolomics, small-molecule library profiling, and protein-ligand titrations on four Bruker BioSpin NMR spectrometers at the National Magnetic Resonance Facility at Madison. The investigators reported benefits from ease of setup, improved spectral quality, convenient customizations, and overall time savings.
Coastal vulnerability assessments to climate change impacts have been conducted in the past. However, few if any account for the highly variable risk associated with tidal stage in macro-tidal environments. The purpos...
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Coastal vulnerability assessments to climate change impacts have been conducted in the past. However, few if any account for the highly variable risk associated with tidal stage in macro-tidal environments. The purpose of this research was to develop a geomatics tool which interactively determines the biophysical vulnerability of a macro-tidal estuary in the Bay of Fundy to varying levels of storm surge and tide state. A conceptual framework was designed to illustrate the relative interrelationships between exposure conditions (surge height, tidal stage), biophysical state (freeboard, exposure, width of foreshore, intertidal slope, observed erodibility, shore protection) and morphological resilience condition. This conceptual framework was then used to develop a dynamic, custom python programming script within ArcGIS 9.3 to calculate coastal vulnerability for user determined combinations of surge height and tide state. The analysis was conducted for four coastlines, backshore, upper foreshore, middle foreshore and lower foreshore, to reflect varying biophysical states with varying tide levels. The results of the tool were compared with known areas of concern (high erosion, dyke overtopping), as determined by historical records, local expert knowledge and GIS analysis of aerial photography. The number of known locations of concern is lower than that of the results produced by the tool. This is most likely due to the results being analyzed at extreme water levels, greater than higher high water large tide. However, this estimation of vulnerability may limit negative impacts of climate change by highlighting vulnerable areas prior to an event, allowing coastal managers and planners to install measures to reduce the vulnerability and enhance the adaptive capacity of local communities.
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