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KAID 2012 UB BECHAR. Video created by 埃因霍温科技大学 for the course "体育和建筑空气动力学". Bertozzi和Guillermo Sapiro在2001年发表的论文“ Navier-Stokes，流体动力学以及图像和视频修补”。该算法基于流体动力学并利用了 偏微分方程。基本原理是启发式的。. The Spalart–Allmaras model is used for turbulence closure. The platform is an initiative of the Urban Energy Systems Laboratory at Empa in Switzerland, in collaboration with our research partners at ETH-Zurich, EPFL, the University of Geneva and the Lucerne University of Applied Sciences. I have around 5 years experience with c++ and game programming and trying to learn tensorflow. Figure 1: Navier-Stokes informed neural networks: A plain vanilla densely connected (physics uninformed) neural network, with 10 hidden layers and 50 neurons per hidden layer per output variable (i. Grubel: Dynamic Adaptation in HPX – A Task-Based Parallel Runtime System, Ph. PDEs and fundamental laws of physics TensorFlow, LAMMPS, i-PI;. View Pluto Chui’s profile on LinkedIn, the world's largest professional community. Mantaflow also serves as the simulation engine in Blender. URL A Parallel Matrix Scaling Algorithm. The touted AMBER Alert system is so inherently flawed it amounts to little more than "crime-control theater," according to a new report by researchers at the University of Nevada–Reno. Machine learning cfd. Last summer, I wrote about love affairs and linear differential equations. 作者: yuejian0518 (站内联系TA) 发布: 2013-05-14最近在科学网看到一论及Navier-Stokes方程的神级博文,作者为某高校力学教授. Redeem Offer. com BPainter V2. Tag: NVidia GeForce Installation and getting things to work together: Fedora 25 Workstation (not 26), gcc 6 (not 7) for CUDA 9, CUDNN 7, not Tensorflow 1. Most engineering flows of interest are turbulent. The ﬁeld of machine learning has received much interest from the scientiﬁc community. TensorFlow; tested with 1. リ（TensorFlow, Keras, …）の充実，機械学習に特化した計算 機（GPUなど）の普及，情報（Qiitaなど）により，「乱流ビッグ データ」を機械学習を用いて扱うための準備ができつつある．. In total, 27 women participated, ranging from undergraduates to full professors; in addition, five future topologists (children of the participants) attended the various social events scattered throughout the week. See full list on lorenabarba. Improvements in efficiency and reliability for Navier-Stokes computations using the LU-ADI factorization algorithm S Obayashi, K Kuwahara, K Fujii, K Matsushima 24th Aerospace Sciences Meeting, 338 , 1986. Storey; Publisher: Haynes Manuals ISBN: 9781844257867 Category: Ford Ka automobile Page: 256 View: 6856 DOWNLOAD NOW » Hatchback & Van models wth 1. FEFFERMAN The Euler and Navier–Stokes equations describe the motion of a ﬂuid in Rn (n = 2 or 3). Navier-Stokes equations in uid dynamics are derived by considering the conservation of mass, momentum, and energy for a control volume in a uid. Job Description: Imagine New Horizons. Deep learning algorithms for physical problems are a very active field of research. What are synonyms for tensorial?. For most machine learning positions, projects listed on a resume only help you get in the door to interview — they don’t help much with getting the job if you flunk the interview. The x-axis represents iterations, where each iteration is 1 million game frames (4. In this chapter we introduce Separation of Variables one of the basic solution techniques for solving partial differential equations. A SavedModel contains a complete TensorFlow program, including weights and computation. The Navier-Stokes equations are solved using the Tensorflow ML library for Python programming language via the Chorin’s projection method. CFDNet is designed to predict the primary physical properties of the fluid including velocity, pressure, and eddy viscosity using a single convolutional neural network at its core. It starts with the fluid properties velocity, pressure, temperature, density and viscosity. An ISSN is an 8-digit code used to identify newspapers, journals, magazines and periodicals of all kinds and on all media–print and electronic. JPG 642 × 121; 25 KB. Flow 3d tutorial Flow 3d tutorial. Sehen Sie sich das Profil von Matthias Pilz auf LinkedIn an, dem weltweit größten beruflichen Netzwerk. The Navier-Stokes (NS) equations are solved using Tensorflow library for Python via Chorin-s projection method. 2019 Researchers from national laboratories and universities will be demonstrating new tools and technologies for accelerating data transfer, improving application performance and increasing energy efficiency in a series of demos scheduled across three days in the DOE booth at SC19 (booth 925). Many of the topics are related tolinear and non-linear partial differential equations, including the Schr|dinger equations, the Navier-Stokes equations and quasilinear hyperbolic equations. We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. Owing to the absence of an analytical solution for this problem, the solutions based on 129^ col-location points with. The N-S equations are coupled partial differential equations that require boundary and initial conditions to be solved numerically. xphotoモジュールを使用。 ファジィフーリエ変換法. Num mundo onde toda equipe de ciência de dados é composto com um time com diversos backgrounds, conheça a trajetória da Gabriela de Queiroz, estatística, epidemiologista, developer advocate, fundadora do R-Ladies e agora machine learning manager de um time de ciência de dados na IBM. The goal of the thesis is to develop a FORTRAN code for the numerical simulation of the incompressible Navier-Stokes equations. The TFC is used to transform PDEs into unconstrained optimization problems by analytically embedding the PDE’s constraints into a “constrained expression” containing a free. The event was hosted by President Quix. Bradley October 15, 2019 (original November 16, 2010) PDE-constrained optimization and the adjoint method for solving these and re-. linalg (or. Based on your location, we recommend that you select:. Passionate about something niche?. Nov 14, 2014 - This Pin was discovered by Yaser Vatanparast. Xin, Blowup of smooth solutions to the compressible Navier-Stokes equations with compact density, 51 (1998), 229--240. Studied Navier-Stokes mesh optimisation for a complete aircraft to save time computation without affect results Performed meshes, NS3D computation and extraction of relevant aerodynamics data for several flight configuration Participated to the new chimera mesh generation. Theano and TensorFlow. A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. We prove the existence and uniqueness of local strong solutions and the existence of a global solutions for the constrained 2D Navier-Stokes equations on the torus on the whole Euclidean space. candidate I have been developing a 3D Navier Stokes simulator for volcanic eruptions on early Mars. These equations are static equations derived by coupling Maxwell's equations (electromagnetic part) and Navier-Stokes equations (fluid part). See the complete profile on LinkedIn and discover Pluto’s connections and jobs at similar companies. the modeling of ﬂuid ﬂows using the Navier-Stokes equations [1] and has many applications in engineering design (e. Find books. For example, if you want to have a look at the Navier-Stokes equations. We highlight the performance of the differentiable physics networks for a wide variety of PDEs, from non-linear advection-diffusion systems to three-dimensional Navier-Stokes flows. Bekijk het profiel van Ronald Rook op LinkedIn, de grootste professionele community ter wereld. Session 4: Algorithms and Architecture for Quantum Information: 56. This is based on joint works with Gaurav Dhariwal (York) and Mauro Mariani (Roma I). Hunt available from Rakuten Kobo. Lukas Troska: A HPX-based parallelization of a Navier-Stokes-solver, Bachelors Thesis defended at the Universität Bonn, August 2016. This is done by using Reynolds averaged Navier-Stokes (RANS) and an actuator disc (ACD) technique in the computational fluid dynamics code PHOENICS. Part of Z-Library project. Job Description: Imagine New Horizons. This book’s logical organization begins with an introductory chapter summarizing the history of fluid mechanics and then moves on to the essential mathematics and physics needed to understand and work in fluid mechanics. The second term is the convective term and the third term is the diffusive term. An ISSN is an 8-digit code used to identify newspapers, journals, magazines and periodicals of all kinds and on all media–print and electronic. Dmitry Dylov is an assistant professor and head of the Computational Life Sciences program at the Center for Data-Intensive Science and Engineering (CDISE) at SkolTech—a Russian school established in collaboration with Massachusetts Institute of Technology (MIT), USA. 0 0 0 0 Updated Jul 26, 2020. Lukas Troska: A HPX-based parallelization of a Navier-Stokes-solver, Bachelors Thesis defended at the Universität Bonn, August 2016. PDE-constrained optimization and the adjoint method1 Andrew M. These equations are static equations derived by coupling Maxwell's equations (electromagnetic part) and Navier-Stokes equations (fluid part). It only takes a minute to sign up. For CNNs, this was an insight that struck me because I wrote a lot of incompressible Navier-Stokes equations solvers for Computational Fluid Dynamics (CFD) with finite-difference methods in CUDA C/C++: stencil operations in CUDA (or numerical computation in general) are needed for the finite-difference method for computing gradients, and. Anyway, stay at home, wear mask (the droplet sizes are relatively big so masks can definitely help, and even the air-flow dynamics around a single virus particle, at that small a scale, should be almost Brownian, not of Navier-Stokes), wash your hands, and engage your mind in something else… Should be back after after a week or 10 days. However, CFD simulation is usually a computationally expensive, memory demanding and time consuming iterative process. The Navier-Stokes Equations: A Classification of Flows and Exact Solutions eBooks & eLearning Posted by DZ123 at March 4, 2019 Philip Drazin, "The Navier-Stokes Equations: A Classification of Flows and Exact Solutions". Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to. Fenics on anaconda Fenics on anaconda. In order to solve and analyse these fluid flows we require intensive simulation involving mathematical equations which governs the fluid flow, these are Navier Stokes (NS) equation. - Coded extensive program in C language to collect data using phase field energy and Navier-Stokes equation. ecell4-base: An integrated software environment for multi-algorithm, multi-timescale, multi-spatial-representation simulation of various cellular phenomena. The Reynolds number based on the chord and tip speed is Retip =0. It's very versatile, and allows coupling and import/export with deep learning frameworks (e. Abraham Union High School, Astronomy on Tap, Beebe's PCs, Schmidt Quotes, Play Dog Play Canine. 0 comments 12 Steps to Navier Stokes – CFD Python. non-turbulent) ﬂow of an incompressible. Up to now, the equations describing viscous fluid flow, the Navier-Stokes (NS) equations, have not even been proven to always have a solution. This solution is integrated with a neural network (NN). The methodology for the solution is provided, which is compared with a classical solution implemented in Fortran. The two concurrent surrogates are built incrementally starting from a moderate set of evaluations of the full order model. As illustrated in Figure 1, the “current FEA-based analysis” begins with the three requisite TAV design parameters, generates the FE mesh, and conducts two FE simulations: The 1st FE simulation is for leaflet mounting and the 2nd FE simulation for obtaining the deformed shape and stress. x and gridDim. The numerical simulations are performed with a Reynolds-averaged Navier--Stokes approach. The data was generated by DNSs of the incompressible Navier-Stokes equations (NSEs) in a triply periodic cube with size $$2 \pi$$ and $$256^3$$ collocation points. Included are partial derivations for the Heat Equation and Wave Equation. A blog about Compressive Sensing, Computational Imaging, Machine Learning. 第一版TensorFlow第一版发布于2015年11月，它可以运行在多台服务器的GPU上，同时并在其上面进行训练。2016年2月，更新版中增加了分布式与并发处理. Sehen Sie sich das Profil von Matthias Pilz auf LinkedIn an, dem weltweit größten beruflichen Netzwerk. Schneider and Ch. Navier Stokes equations Abstract A novel hybrid deep neural network (DNN) architecture was designed to capture the spatial-temporal features of unsteady flows directly from high-dimensional numerical unsteady flow field data. Introduction to fluid dynamics, from incompressible, inviscid flow and Bernoulli’s principle, to viscid, compressible flow and Navier-Stokes equations. jl - PDE solver for economics models #opensource. Flow 3d tutorial Flow 3d tutorial. 5 words related to tensor: variable quantity, variable, muscle, musculus, tensor tympani. Tags: Fluid dynamics, Fluid simulation, GLSL, Navier-Stokes equations, NSEs, OpenCL, OpenGL, Package, Rendering December 20, 2016 by hgpu Accelerating Eulerian Fluid Simulation With Convolutional Networks. Turbulent flow was considered with the Reynolds-averaged Navier–Stokes (RANS) model because the maximum Reynolds number due to crystal rotation was approximately 3 × 10 4 in the ranges of the parameters given in Table 2. (Ljung, 2002, 1999; Johansson, 1993). To systematically train and evaluate the performance of our networks, we split the data into three parts by first randomly shuffling the entire data set and then taking the desired number of samples. Outline Introduction: Conservation Principle Derivation by Control Volume Convective Terms Forcing Terms. Computer Methods in Applied Mechanics and Engineering 364 , 112948. pptx - Free download as Powerpoint Presentation (. Consultez le profil complet sur LinkedIn et découvrez les relations de Benjamin, ainsi que des emplois dans des entreprises similaires. An accurate and efficient method for the incompressible Navier–Stokes equations using the projection method as a preconditioner, by Boyce E. Analytical treatments are based on the Navier-Stokes equations. A blog about Compressive Sensing, Computational Imaging, Machine Learning. FastR is a GraalVM based implementation of the R language that provides significant improvements in the performance of R code, the embedding of the R execution engine into Java applications, and the ability to interface with other GraalVM and JVM languages including. Aims of this module:. The equations can be written in a compact form as:. It promises advances for a wide range of applications from preventing strokes to designing better airplanes. We will send you an email that includes a link to create a new password. DataSciencePython common data analysis and machine learning tasks using python PythonDataScienceHandbook. This classi cation is typically retained even if we add more variables to the PDE. INPAINT_NS : Navier-Stokes based Inpainting. Essentially, the GS is an important family of equations in the plasma fluid theory, it is often used in laboratory plasma for instance in Reversed Field Pinch (RFP) configurations. Stack Exchange network consists of 176 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. D'Equatiounen erweideren d'Euler-Equatiounen ëm d'Viskositéit. Find books. TensorFlow Code for Google Research's BERT: Pre-Training Method for NLP Tasks more. Need variable definitions. A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. Select a Web Site. Hunt available from Rakuten Kobo. Mathematical analysis on wave and shock front. Lihat profil lengkap di LinkedIn dan terokai kenalan dan pekerjaan Mer Win di syarikat yang serupa. EQUATIONS: The Navier Stokes Equations Any study of uid ow starts with the Navier-Stokes equations: ˆv t ˆ v + ˆ(v r)v + rp =f (momentum equations) ˆ t + r(ˆv) =0 (continuity equation) We can add complications such as compressibility or heat, makes simpli cations such as time independence, or replace some terms in. 00 Bot: 1260. This solution is integrated. As a Fluids Machine Learning Intern, you will conduct research in applying machine learning techniques to improve solutions for Navier-Stokes (Finite-Volume) and Lattice Boltzmann solver technologies commonly used in Computational Fluid Dynamics. Unique Matrix Stickers designed and sold by artists. deep learning, TensorFlow, Keras, CUDA, kryptoměny, burza popis: Kryptoměny mají do značné míry spekulativní povahu a obchodování s nimi není tolik ovlivněno vnějšími faktory, jako je to na burzách akcií. This method was published in 2001 in a paper titled “Navier-Stokes, Fluid Dynamics, and Image and Video Inpainting” Sometimes I feel like the field of Computer Vision is a field of immigrants from other fields like electrical engineering, computer science, physics, and mathematics. 守恒定律的相对独立性理论物理学家力图证明各种守恒律的相互关系，尤其是等价关系。. Wall bounded flows, viscous scales, and law of the wall. However, CFD simulation is usually a computationally expensive, memory demanding and time consuming iterative process. In this study, we developed an ML approach to facilitate TAV design. Analysis, SAM Report 2016-45. I am not suggesting that humanities graduates be expected to understand and solve the equations of radioactive transfer and the Navier-Stokes equations of fluid dynamics. The Reynolds number based on the chord and tip speed is Retip =0. This classi cation is typically retained even if we add more variables to the PDE. The equations can be written in a compact form as:. Forgot Password? Enter your email address and click Submit. It starts with the fluid properties velocity, pressure, temperature, density and viscosity. Navier-Stokes Equations. The x-axis represents iterations, where each iteration is 1 million game frames (4. Tensorflow is a numerical computation library which is mostly used to conduct machine learning (ML) and deep neural networks research, but which can also be applied in various other domains. (ii) The development of a neural model of turbulence RANS (Reynolds-Averaged Navier-Stokes) for gravity currents. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. Examples include: Burger's equation, Euler equations for compressible flow, Navier-Stokes equations for incompressible flow. The N-S equations are coupled partial differential equations that require boundary and initial conditions to be solved numerically. In this paper the physics-integrated (or PDE-integrated) machine learning (ML) framework is investigated. Grubel: Dynamic Adaptation in HPX – A Task-Based Parallel Runtime System, Ph. In fact, this has been done already by Ladicky and Jeong 2015 [8]. In total, 27 women participated, ranging from undergraduates to full professors; in addition, five future topologists (children of the participants) attended the various social events scattered throughout the week. It executes on the GPU and the solver runs at interactive rates. During my doctoral studies, I developed a stabilized finite-element method with higher-order interpolation functions to solve turbulent flows via Reynolds-Averaged Navier Stokes equations in three dimensions. Return the 2d grid graph of mxn nodes, each connected to its nearest neighbors. The Holistic Urban Energy Simulation (HUES) platform is an open source platform for facilitating the design and control of renewables-based distributed energy systems. (1) Numerical experiments show that small neural networks (< 500 learnable parameters) are able to accurately learn complex solutions for systems of partial differential. 论文研究 - Navier-Stokes方程适当弱解的存在性的新证明及其他说明. AdaBound Optimizer AdaBound Optimizer combines Adam and Stochastic Gradient from CSSE 490 at Rose-Hulman Institute Of Technology. The ISSN of Clinical Orthopaedics and Related Research is 15281132, 0009921X. An accurate and efficient method for the incompressible Navier–Stokes equations using the projection method as a preconditioner, by Boyce E. The streamfunction/vorticity and temperature formulation of the Navier–Stokes and energy equations and their associated boundary conditions are written in generalized curvilinear co Patankar and D. x and gridDim. 1000, where the flow is steady. Dan Fleisch briefly explains some vector and tensor concepts from A Student's Guide to Vectors and Tensors. The system required extremely small time for its computation whereas the same computation using Navier-Stokes equations required 4 to 5 computing hours. (Matrix scaling, which could be used to build preconditioner in the iterative methods. 第二种算法基于Bertalmio，Marcelo，Andrea L. , using “ tf. Rodolfo: κατεβάστε ελεύθερα. A theoretician achieves this goal by solving the governing Navier-Stokes equations. 37 MB Numerical diffusion 01 by N. It is based on an Eulerian direct numerical simulation of the incompressible Navier-Stokes equations and a Lagrangian direct Monte-Carlo simulation of the fiber conformation. Navier-stokes, ﬂuid dynamics, and image and video inpainting 2001: SIGGRAPH 2001: Image Quilting for Texture Synthesis and Transfer 2001: SIGGRAPH 2001: Synthesizing Natural Textures 2002: EJAM 2002: Digital inpainting based on the mumford–shah–euler image model : Diffusion-based: 2003: CVPR 2003. D'Navier-Stokes-Equatioune si partiell Differentialequatiounen, déi d'Stréimung vun Newton-Fluide beschreiwen. Passionate about something niche?. training/blogs/tensorflow-pde/). The aim of this project is to provide efficient and robust tool for FEM computations as well as to offer highly modular and extensible environment for development. In this step-by-step Seaborn tutorial, you’ll learn how to use one of Python’s most convenient libraries for data visualization. In aerodynamics related design, analysis and optimization problems, flow fields are simulated using computational fluid dynamics (CFD) solvers. These equations are to be solved for an unknown velocity vector u(x,t) = (u i(x,t)) 1≤i≤n ∈ Rn and pressure p(x,t) ∈ R, deﬁned for position x ∈ Rn and time t ≥ 0. Studied Navier-Stokes mesh optimisation for a complete aircraft to save time computation without affect results Performed meshes, NS3D computation and extraction of relevant aerodynamics data for several flight configuration Participated to the new chimera mesh generation. Project: SDG for Navier-Stokes Equation • Using the new Galerkin method to simulate fluid dynamic Partial Differential Equations • MATLAB implementations • Theoretical analysis and numerical results • Optimal convergence rate for limit cases. The Navier-Stokes equations are solved using the Tensorflow ML library for Python programming language via the Chorin’s projection method. The implemented method is based on employing a Projection Method for the time discretization and the High-Order Discontinuous Galerkin Spectral Element method for the spatial discretization. In this study two wind turbine setups are investigated numerically: (a) the flow around a single model wind turbine and (b) the wake interaction between two in-line model wind turbines. Fluid mechanics embraces engineering, science, and medicine. [CFD] 비압축성 Navier-Stokes 방정식 푸는 방법, 압력 기반 방법 (Pressure based method) 5월 16, 2020 [파주 헤이리] 아다마스 253, 파스타 맛집, 통오징어 파스타. Bertozzi和Guillermo Sapiro在2001年发表的论文“ Navier-Stokes，流体动力学以及图像和视频修补”。该算法基于流体动力学并利用了 偏微分方程。基本原理是启发式的。. Search “Tensorflow tutorial” and you’ll likely end up working with MNIST data. New post "Domains separation, sending to Google Drive, FTP bulk uploader and the new language filter" in our blog. In this paper, computer vision enables recommending a reduced order model for fast stress prediction according to various possible loading environments. 0 0 0 0 Updated Jul 26, 2020. Lukas Troska: A HPX-based parallelization of a Navier-Stokes-solver, Bachelors Thesis defended at the Universität Bonn, August 2016. The world's largest ebook library. Cesar tiene 3 empleos en su perfil. Solving pde in python. Find books. ca overlord rolls out free privacy-protecting DNS-over-HTTPS service for folks in Great White North GCC 10 gets security bug trap. General-purpose computing on graphics processing units (GPGPU, rarely GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). Addon for sending video, audio, depth and osc to a remote peer using RTP. TensorFlow based image classification of CIFAR-10 dataset of 50,000 images. 第一版TensorFlow第一版发布于2015年11月，它可以运行在多台服务器的GPU上，同时并在其上面进行训练。2016年2月，更新版中增加了分布式与并发处理. 4-Get the meeting participants' list (the people who are in the meeting when you getting the data). Wells A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations. 无痛苦N-S方程笔记 An Introduction of The Navier-Stokes Equation Without Pain 李东岳，程序员大本营，技术文章内容聚合第一站。. There are, however, many situations where derivations by rst principles are intractable or even impossible as they become too complicated or the governing physical laws are unknown. Grubel: Dynamic Adaptation in HPX – A Task-Based Parallel Runtime System , Ph. These equations are static equations derived by coupling Maxwell's equations (electromagnetic part) and Navier-Stokes equations (fluid part). The world's largest ebook library. Navier-Stokes equation, in fluid mechanics, a partial differential equation that describes the flow of incompressible fluids. (2017) accelerate the solution of incompressible Navier–Stokes equations with a CNN to solve the Poisson equation for the pressure at the forward time step. Up to now, the equations describing viscous fluid flow, the Navier-Stokes (NS) equations, have not even been proven to always have a solution. xphotoモジュールを使用。 ファジィフーリエ変換法. In fact, this has been done already by Ladicky and Jeong 2015 [8]. Two configurations are investigated: a free rotor and a shrouded rotor. The Holistic Urban Energy Simulation (HUES) platform is an open source platform for facilitating the design and control of renewables-based distributed energy systems. These equations are named after Claude-Louis Navier (1785-1836) and George Gabriel Stokes (1819-1903). The example is based on the GPU Gems article available here (PDF). URL A Parallel Matrix Scaling Algorithm. Equation 7 describes a second order non-linear partial differential equation and is except for a few special cases only numerically solvable. Please see the pySchrodinger github repository for updated code In a previous post I explored the new animation capabilities of the latest matplotlib release. A full list of changes can be found here and a long description of changes is in the manuscript here. The Navier-Stokes Equations Academic Resource Center. We propose a hybrid approach that simultaneously exploits a data-driven model and a physics-based model, in mechanics of materials. txt) or view presentation slides online. finite volume of lattice-Bolztmann methods). 00 Bot: 1260. 1 GEOSChem-on-cloudproject aims to build a cloud computing capability forGEOS-Chemthat can be easily accessed. Navier-Stokes equations describe the physics of many phenomena of scientific and engineering interest. The training runs for our 4 agents on Seaquest. I am solving the Navier Stokes equations for fluid dynamics using Tensorflow (similarly to https://data-flair. OLITÈCNICA DE. Python - 2D Array - Two dimensional array is an array within an array. Analysis, SAM Report 2016-45. Deep Learning. Navier Stokes equations Abstract A novel hybrid deep neural network (DNN) architecture was designed to capture the spatial-temporal features of unsteady flows directly from high-dimensional numerical unsteady flow field data. cloud-GC Documentation, Release 0. Although the Navier-Stokes equations are considered the appropriate conceptual model for fluid flows they contain 3 major approximations: Simplified conceptual models can be derived introducing additional assumptions: incompressible flow Conservation of mass (continuity) Conservation of momentum Difficulties: Non-linearity, coupling, role of. Update: a reader contributed some improvements to the Python code presented below. txt) or view presentation slides online. The touted AMBER Alert system is so inherently flawed it amounts to little more than "crime-control theater," according to a new report by researchers at the University of Nevada–Reno. EQUATIONS: The Navier Stokes Equations Any study of uid ow starts with the Navier-Stokes equations: ˆv t ˆ v + ˆ(v r)v + rp =f (momentum equations) ˆ t + r(ˆv) =0 (continuity equation) We can add complications such as compressibility or heat, makes simpli cations such as time independence, or replace some terms in. It’s another glamorous night in the heart of Manhattan: at a glitzy movie premiere, a gorgeous starlet, dressed to the nines and dripping in millions of dollars’ worth of jewelry on loan, makes her way past a horde of fans and paparazzi. Openfoam tensorflow. Num mundo onde toda equipe de ciência de dados é composto com um time com diversos backgrounds, conheça a trajetória da Gabriela de Queiroz, estatística, epidemiologista, developer advocate, fundadora do R-Ladies e agora machine learning manager de um time de ciência de dados na IBM. Keywords: Agricultural robot, egg picking, poultry, machine learning, TensorFlow, ROS (Free Abstract ) (Download PDF) Paper # 1700398 Detecting Maleic Anhydride in Starch using Line-Scan Hyperspectral Raman Chemical Imaging Citation: Paper number 1700398, 2017 ASABE Annual International Meeting. Solving one of. It also works with C++. Numerical validation tests show optimal convergence rates for the DG discretization indicating the correctness of the numerical scheme. The obtained correlation functions show how scale invariance is broken in a subtle way, related to intermittency corrections. 0 Bpainter V2. (Ljung, 2002, 1999; Johansson, 1993). Python by Example: Learning to Program in (3986) TensorFlow 2. I'm glad I'm not in that area. The main content is four different forms of continuity equations & Navier-Stokes equations, including the difference between integral / differential, conservation / non-harvest equations and momentum equations. NVIDIA is already…. The salient features of the proposed scheme include (1) employing the general continuum equations together with the material constitutive law rather than the derived Navier-Stokes equations, and (2) using stream function to ensure the divergence free condition of the flow in a mixed-variable setting. 我们证明，在Scheffer的意义上，补充Dirichlet边界条件的3D Navier-Stokes方程的半离散和离散半隐式Euler方案的极限是合适的。 这提供了合适的弱解存在的新证据，最早由Caffarelli，Kohn和Nirenberg提出[2]。. A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. An article in the latest edition of Science magazine, Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations, describes an emerging branch of fluid dynamics at the intersection of scientific computing and deep learning. Video created by 埃因霍温科技大学 for the course "体育和建筑空气动力学". Matlab script to solve the Navier Stokes equations applied to the moving lid cavity flow problem. Owing to the absence of an analytical solution for this problem, the solutions based on 129^ col-location points with. The team behind Google's Tensorflow, a popular open-source machine-learning framework, recently cited Julia as a "great language" that was "investing in machine-learning techniques", and that. A full list of changes can be found here and a long description of changes is in the manuscript here. What are synonyms for tensorial?. runs in Python is Google’s TensorFlow. In fact, this has been done already by Ladicky and Jeong 2015 [8]. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to quickly solving a PDE in FEniCS, such as how to define a finite variational problem. The motion of the fluid in this experiment is governed by the Navier-Stokes equations, which generally can’t be exactly solved, but in this case it can be shown that for slow speeds this is the solution and that this solution is unique and stable (to solve the equations you have to assume the cylinders are infinitely long to avoid end effects. Cesar tiene 3 empleos en su perfil. This software not only provides the most accurate simulations but allows scientists to visualize eruptions that occurred 3 billion years ago for the first time. Last summer, I wrote about love affairs and linear differential equations. Search anything related to Tensorflow, really, on Stack Exchange or any similar site, and you’ll end up reading about machine learning as related to MNIST data. Navier Stokes has a rigorous derivation based on extremely high-fidelity assumptions, such as conservation of mass, momentum, and energy. jl - PDE solver for economics models #opensource. The code solves Navier Stokes equations in a 2D lid driven cavity, with computation of the rotational as well. Tracey et al. Hi, The code must be very simple (I don't want a fancy interface, I need just a running code) I would like to have an example code for doing the following: 1- Authentication of Office account In C# 2-Create MS Teams meeting. Python by Example: Learning to Program in (3986) TensorFlow 2. See full list on maziarraissi. The aim of this project is to provide efficient and robust tool for FEM computations as well as to offer highly modular and extensible environment for development. I know it is an old question, but I hope. Anyway, stay at home, wear mask (the droplet sizes are relatively big so masks can definitely help, and even the air-flow dynamics around a single virus particle, at that small a scale, should be almost Brownian, not of Navier-Stokes), wash your hands, and engage your mind in something else… Should be back after after a week or 10 days. Python - 2D Array - Two dimensional array is an array within an array. The Navier-Stokes equations capture in a few succinct terms one of the most ubiquitous features of the physical world: the flow of fluids. Grubel: Dynamic Adaptation in HPX – A Task-Based Parallel Runtime System , Ph. The Khronos Group announces the release of the Vulkan 1. Using a hybrid ROM. Improvements in efficiency and reliability for Navier-Stokes computations using the LU-ADI factorization algorithm S Obayashi, K Kuwahara, K Fujii, K Matsushima 24th Aerospace Sciences Meeting, 338 , 1986. Read on to see performance on a 40-core Xeon and 48-core Opteron system. cloud-GC Documentation, Release 0. Equation 7 describes a second order non-linear partial differential equation and is except for a few special cases only numerically solvable. With the help of this course, you can From beginner to expert. Here we consider the laminar (i. In this module a derivation of the Navier-Stokes equations will be presented, followed by description of various techniques to simplify and solve the equation with the purpose of describing the motion of fluids at different conditions. Pluto has 5 jobs listed on their profile. Storey; Publisher: Haynes Manuals ISBN: 9781844257867 Category: Ford Ka automobile Page: 256 View: 6856 DOWNLOAD NOW » Hatchback & Van models wth 1. High quality example sentences with “open source numerical” in context from reliable sources - Ludwig is the linguistic search engine that helps you to write better in English. [1] [2] The sizes of the different terms in the equation(s) will change as the variables change, and hence, which terms are leading-order may also change. The paper by Ling et al. MPI parallelized FORTRAN 90 solver for solving molecular dynamics problems based on "parareal" algorithms. com Blenderで最も強力なペインティングプラグイン。. Readability. TensorFlow based image classification of CIFAR-10 dataset of 50,000 images. The methodology for the solution is provided, which is compared with a “classical” solution implemented in Fortran. Computational fluid dynamics (CFD) is an established method for the simulation of complex flows. svg 900 × 720; 9. (Matrix scaling, which could be used to build preconditioner in the iterative methods. We're showcasing projects here, along with helpful tools and resources, to inspire others to create new experiments. The equation is a generalization of the equation devised by Swiss mathematician Leonhard Euler in the 18th century to describe the flow of incompressible and frictionless fluids. Mantaflow also serves as the simulation engine in Blender. These students seemed to experience no unusual difficulty with the material. View Pluto Chui’s profile on LinkedIn, the world's largest professional community. It’s another glamorous night in the heart of Manhattan: at a glitzy movie premiere, a gorgeous starlet, dressed to the nines and dripping in millions of dollars’ worth of jewelry on loan, makes her way past a horde of fans and paparazzi. Navier-Stokes equation, in fluid mechanics, a partial differential equation that describes the flow of incompressible fluids. This investigation has demonstrated that the probabilistic LBM, coupled with the efficient octree meshing methods, reduced the computational power required significantly compared to Navier-Stokes based solvers from 6 months to a week on a nose landing gear. To systematically train and evaluate the performance of our networks, we split the data into three parts by first randomly shuffling the entire data set and then taking the desired number of samples. The code solves Navier Stokes equations in a 2D lid driven cavity, with computation of the rotational as well. NTERNATIONAL DRYING SYMPOSIUM DITORIAL. Finding Navier-Stokes fluid flows through quantum computung: Gaitan, Frank: We present a quantum algorithm that solves an arbitrary set of coupled non-linear partial differential equations and show how it can be used to solve the governing equations for a Navier-Stokes fluid. There are, however, many situations where derivations by rst principles are intractable or even impossible as they become too complicated or the governing physical laws are unknown. Blender Marketには色々なプラグインがあります。 何かBlenderで困ったら下記サイトを見てみましょう。 Blender MarketA Unique Market for Creators that love Blenderwww. 13 Skin: -2. Although the Navier-Stokes equations are considered the appropriate conceptual model for fluid flows they contain 3 major approximations: Simplified conceptual models can be derived introducing additional assumptions: incompressible flow Conservation of mass (continuity) Conservation of momentum Difficulties: Non-linearity, coupling, role of. NVIDIA is already…. iv PREFACE seniors and graduate students. Axisymmetric Reynolds-Averaged Navier-Stokes simulations using both perfect gas and real gas, finite rate chemistry, assumptions were performed to aid in the design process and to create a comprehensive database of inlet performance. Lihat profil lengkap di LinkedIn dan terokai kenalan dan pekerjaan Mer Win di syarikat yang serupa. 中, 作者给出了可压NS的一个爆破现象. If a language+compiler can optimize more programs more effectively, we consider it better, and we want it. The created a feature vector, directly modeling individual forces and constraints from the Navier-Stokes equations, predicting reliably the positions and velocities of particles in large time step on an unseen test video. Choose a web site to get translated content where available and see local events and offers. Mer Win menyenaraikan 3 pekerjaan pada profil mereka. Here is a selection of the best 3D printable STL files for 3D printer to rise up with nice planes. Project: SDG for Navier-Stokes Equation • Using the new Galerkin method to simulate fluid dynamic Partial Differential Equations • MATLAB implementations • Theoretical analysis and numerical results • Optimal convergence rate for limit cases. finite volume of lattice-Bolztmann methods). (1) Numerical experiments show that small neural networks (< 500 learnable parameters) are able to accurately learn complex solutions for systems of partial differential. tensorflow —Latest stable release with CPU and GPU support (Ubuntu and Windows). An improved CFD model based on this framework was developed with a high-order difference method, which is a constrained interpolation profile (CIP) scheme for the base flow solver of the advection term in the Navier-Stokes equations, and preconditioned conjugate gradient (PCG) method was implemented in the model to solve the Poisson equation. 13 Skin: -2. com BPainter V2. 0A Unique Market for Creators that love Blenderblendermarket. Somewhat surprisingly, not everybody agrees with this. Rodolfo: скачать бесплатно. A wide range of Navier-Stokes solver variants are included. The two concurrent surrogates are built incrementally starting from a moderate set of evaluations of the full order model. Somewhat surprisingly, not everybody agrees with this. Already today, optimisation is used to design more efficient cars and airpla. Starting from a basic knowledge of mathematics and mechanics gained in standard foundation classes, Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave takes the reader conceptually through from the fundamental mechanics of lift to the stage of actually being able to make practical calculations and predictions of the coefficient of lift for realistic wing profile and. Most engineering flows of interest are turbulent. Owing to the absence of an analytical solution for this problem, the solutions based on 129^ col-location points with. The motion of the fluid in this experiment is governed by the Navier-Stokes equations, which generally can’t be exactly solved, but in this case it can be shown that for slow speeds this is the solution and that this solution is unique and stable (to solve the equations you have to assume the cylinders are infinitely long to avoid end effects. Also reviews all required mathematics needed for the Performance courses, including multi-variable integral calculus (line and flux integrals, Stokes’s theorem, etc. 00 Bot: 1260. Navier-Stokes Equations. Here is one solution of Poissons 2-dimensional equation, which I just recolored the scale gradient. Mathematical analysis on wave and shock front. Solving 2d pde python. Immediate Smaller Element Time Limit Exceeded "fF" letter combination seems to be typeset strangely or incorrectly How can I unambiguous. 1 Job ist im Profil von Matthias Pilz aufgelistet. Download books for free. Figure 1: Navier-Stokes informed neural networks: A plain vanilla densely connected (physics uninformed) neural network, with 10 hidden layers and 50 neurons per hidden layer per output variable (i. This article presents a new methodology called Deep Theory of Functional Connections (TFC) that estimates the solutions of partial differential equations (PDEs) by combining neural networks with the TFC. General-purpose computing on graphics processing units (GPGPU, rarely GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). This series of lectures outlines some basic aspects of fluid flow. Lukas Troska: A HPX-based parallelization of a Navier-Stokes-solver, Bachelors Thesis defended at the Universität Bonn, August 2016. Many of the topics are related tolinear and non-linear partial differential equations, including the Schr|dinger equations, the Navier-Stokes equations and quasilinear hyperbolic equations. Posts about NVidia GeForce written by ernestyalumni. iv PREFACE seniors and graduate students. 使用SciPy Stack進行科學計算和數據分析科學計算的一般主題社交數據心理學和神經科學機器學習，. - Coded extensive program in C language to collect data using phase field energy and Navier-Stokes equation. 我们证明，在Scheffer的意义上，补充Dirichlet边界条件的3D Navier-Stokes方程的半离散和离散半隐式Euler方案的极限是合适的。 这提供了合适的弱解存在的新证据，最早由Caffarelli，Kohn和Nirenberg提出[2]。. Mantaflow also serves as the simulation engine in Blender. Ve el perfil completo en LinkedIn y descubre los contactos y empleos de Cesar en empresas similares. The equations are discretized in time using a semi-implicit scheme with explicit treatment of the nonlinear term and implicit treatment of the split Stokes operators. How using computational fluid dynamics (CFD) to build a Bonneville racer has helped me understand the challenges that will be faced by Volkswagen at Pikes Peak this year. Navier Stokes equations Abstract A novel hybrid deep neural network (DNN) architecture was designed to capture the spatial-temporal features of unsteady flows directly from high-dimensional numerical unsteady flow field data. com Blenderで最も強力なペインティングプラグイン。. URL A Parallel Matrix Scaling Algorithm. The celebrated Navier-Stokes equation is an example of a system of PDEs whose theoretical understanding is incomplete: \[ \frac{\partial u}{\partial t} + (u \cdot \Delta - u) u + \frac{1}{\rho} abla p = f. Our developed system produced 64 fuzzy rules as well. By developing APIs for accessing available data from meteorological institutes. The Moonvision GmbH, Vienna. The training runs for our 4 agents on Seaquest. Implemented a tool to reproduce and compare DL trainings easily with different hyper parameters, introduced an active learning workflow by prediction uncertainty (with pending patent application), successfully managed projects with leading customers in the industry, supervisor for interns. Forgot Password? Enter your email address and click Submit. (**) You may say it isn't basic, but actually, some of it is. Zech: Shape Holomorphy of the stationary Navier-Stokes Equations, accepted (2018), SIAM J. Download Full Book in PDF, EPUB, Mobi and All Ebook Format. TensorFlow Code for Google Research's BERT: Pre-Training Method for NLP Tasks more. Tags: Fluid dynamics, Fluid simulation, GLSL, Navier-Stokes equations, NSEs, OpenCL, OpenGL, Package, Rendering December 20, 2016 by hgpu Accelerating Eulerian Fluid Simulation With Convolutional Networks. The Navier-Stokes equations are among the Clay Mathematics Institute Millennium Prize problems, seven problems judged to be among the most important open questions in mathematics. Pluto has 5 jobs listed on their profile. (2020) A low-rank solver for the stochastic unsteady Navier–Stokes problem. special/limited editions. Download Star Smashers Of The Galaxy Rangers full book in PDF, EPUB, and Mobi Format, get it for read on your Kindle device, PC, phones or tablets. Also was inspired by recent work using deep nets with fluid simulations … so this was the result, deep-nets animating Navier-Stokes fluids synced to music. Cesar tiene 3 empleos en su perfil. Using a hybrid ROM. Two configurations are investigated: a free rotor and a shrouded rotor. It’s another glamorous night in the heart of Manhattan: at a glitzy movie premiere, a gorgeous starlet, dressed to the nines and dripping in millions of dollars’ worth of jewelry on loan, makes her way past a horde of fans and paparazzi. 3 (maybe Tensorflow 1. For instance, the Navier Stokes equations can be approximated with it or reaction–diffusion systems can be simulated with it. 论文研究 - Navier-Stokes方程适当弱解的存在性的新证明及其他说明. Download pdf version. Computer Methods in Applied Mechanics and Engineering 364 , 112948. The implemented method is based on employing a Projection Method for the time discretization and the High-Order Discontinuous Galerkin Spectral Element method for the spatial discretization. (2020) Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition. This example implements a PyGPU program that solves Navier-Stokes equations for incompressible flow. ML is in a nutshell “the science of getting computers to act without being explicitly programmed” and is permeating an ever-expanding range of human activities. Curriculum Vitae Work Experience. In this paper, computer vision enables recommending a reduced order model for fast stress prediction according to various possible loading environments. Grubel: Dynamic Adaptation in HPX – A Task-Based Parallel Runtime System , Ph. Dan Fleisch briefly explains some vector and tensor concepts from A Student's Guide to Vectors and Tensors. Tag: NVidia GeForce Installation and getting things to work together: Fedora 25 Workstation (not 26), gcc 6 (not 7) for CUDA 9, CUDNN 7, not Tensorflow 1. 3 litre (1297cc) Duratec petrol engine, inc. fr/kum/ Tutorial. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to. (2020) A low-rank solver for the stochastic unsteady Navier–Stokes problem. 0 0 0 0 Updated Jul 26, 2020. II version 9. A derivation of the Navier-Stokes equations can be found in [2]. ML is in a nutshell “the science of getting computers to act without being explicitly programmed” and is permeating an ever-expanding range of human activities. The Holistic Urban Energy Simulation (HUES) platform is an open source platform for facilitating the design and control of renewables-based distributed energy systems. 86 × 10[5], which corresponds to a challenging flow where leading-edge separations are commonly observed. Here is a selection of the best 3D printable STL files for 3D printer to rise up with nice planes. A two-dimensional (2D) numerical model, termed as UPC-CHD, is developed using the conservative forms of the Navier-Stokes (NS) continuity, momentum and energy equations for viscous, incompressible. 37 MB Numerical diffusion 01 by N. The goal of the thesis is to develop a FORTRAN code for the numerical simulation of the incompressible Navier-Stokes equations. The Navier-Stokes equations capture in a few succinct terms one of the most ubiquitous features of the physical world: the flow of fluids. They may be used to model the weather, ocean currents, water flow in a pipe and air flow around a wing. Studied Navier-Stokes mesh optimisation for a complete aircraft to save time computation without affect results Performed meshes, NS3D computation and extraction of relevant aerodynamics data for several flight configuration Participated to the new chimera mesh generation. In this step-by-step Seaborn tutorial, you’ll learn how to use one of Python’s most convenient libraries for data visualization. The momentum equations (1) and (2) describe the time evolution of the velocity ﬁeld (u,v) under inertial and viscous forces. The answer is the Navier-Stokes equations. x and gridDim. Essentially, the GS is an important family of equations in the plasma fluid theory, it is often used in laboratory plasma for instance in Reversed Field Pinch (RFP) configurations. It solves the Navier-Stokes equations (momentum, mass, and energy conservation) with numerical methods (e. Blender Marketには色々なプラグインがあります。 何かBlenderで困ったら下記サイトを見てみましょう。 Blender MarketA Unique Market for Creators that love Blenderwww. Mathematical analysis on wave and shock front. In fluid dynamics, the Navier-Stokes equations are equations, that describe the three-dimensional motion of viscous fluid substances. Sehen Sie sich auf LinkedIn das vollständige Profil an. This solution is integrated. In my scheme there are. 0 was released today. 译文 | 与TensorFlow的第一次接触 第六章：并发. Initial samples are selected for two levels of fidelity via LHS (Latin Hypercube Sampling). Owing to the absence of an analytical solution for this problem, the solutions based on 129^ col-location points with. At very small scales or under extreme conditions, real fluids made out of discrete molecules will produce results different from the. It is very much similar to Keras' Dense layer. If a language+compiler can optimize more programs more effectively, we consider it better, and we want it. js, TensorFlow Serving, or TensorFlow Hub). Flow 3d tutorial Flow 3d tutorial. Introduction and Outline The in uence of machine learning has exploded in the last few years, fueled by a steep rise in computational power. Therefore, it is of interest to develop models that can predict weather conditions faster than traditional meteorological models. Navier-Stokes equations describe the physics of many phenomena of scientific and engineering interest. di LinkedIn, komuniti profesional yang terbesar di dunia. - Tensorflow - Machine Learning (Regression, Classification, Neural Network, SVM and Kernels, Clustering, PCA) Navier-Stokes Solver in 12 Lines of Code. x and gridDim. The first Women in Computational Topology WinCompTop workshop was held in August at the Institute for Mathematics and its Applications (IMA) in Minneapolis, MN. The Spalart–Allmaras model is used for turbulence closure. In order to solve and analyse these fluid flows we require intensive simulation involving mathematical equations which governs the fluid flow, these are Navier Stokes (NS) equation. It solves the Navier-Stokes equations (momentum, mass, and energy conservation) with numerical methods (e. 2019-04-16 Tags: deep learning, neural network, differential equations, pde, navier-stokes, github, l-bfgs by klotz espressif/esp-who: Face detection and recognition framework 2019-04-01 Tags: esp33 , deep learning , face recognition , github by klotz. I have around 5 years experience with c++ and game programming and trying to learn tensorflow. The Moonvision GmbH, Vienna. Abraham Athletics & Activities, Mt. The goals of this post are to write about my experiences with using TensorFlow for : training an SVD based unsupervised learning ML model using TensorFlow; deploy the trained model with TensorFlow serving. I've also seen references to a form for compressible flow as well as one for incompressible flow. The TFC is used to transform PDEs into unconstrained optimization problems by analytically embedding the PDE’s constraints into a “constrained expression” containing a free. The motion of the fluid in this experiment is governed by the Navier-Stokes equations, which generally can’t be exactly solved, but in this case it can be shown that for slow speeds this is the solution and that this solution is unique and stable (to solve the equations you have to assume the cylinders are infinitely long to avoid end effects. Features Variety of built-in fully-differentiable simulations, ranging from Burgers and Navier-Stokes to the Schrödinger equation. 19 Demo Station 1 10 a. Therefore, a reduced order model (ROM) is generated. 4?), not theano 1. The Navier-Stokes equations are solved using the Tensorflow ML library for Python programming language via the Chorins projection method. See full list on github. Pluto has 5 jobs listed on their profile. Bradley October 15, 2019 (original November 16, 2010) PDE-constrained optimization and the adjoint method for solving these and re-. I've also seen references to a form for compressible flow as well as one for incompressible flow. The Navier-Stokes (NS) equations are solved using Tensorflow library for Python via Chorin-s projection method. If you are a mechanical engineer working on the design of a blade for a propeller or maybe perfecting the profile of an airplane wing, you’ll almost certainly always refer to some Computational Fluid Dynamics (CFD) simulations as a cheaper proxy to solving the Navier Stokes equations. Ebooks library. Mantaflow also serves as the simulation engine in Blender. Fluid simulation is a computer graphic used to develop realistic animation of liquids in modern games. Download books for free. Section 9-1 : The Heat Equation. I know it is an old question, but I hope. NVIDIA is already…. In order to compute the residuals of the Navier-Stokes equations e V P 1 to e V P 4, the partial differential operators are computed by using automatic differentiation (AD), which can be directly formulated in the deep learning framework, e. They are quite difficult enough for highly-trained physicists. Requirements. Rodolfo: κατεβάστε ελεύθερα. Professor of Tokyo University of Science, also Visiting Professor of Institute of Space and - Cited by 12,599 - fluid dynamics - aerodynamics - aeroacoustics - computational mechanics - optimization. The system required extremely small time for its computation whereas the same computation using Navier-Stokes equations required 4 to 5 computing hours. Buy Fourier Analysis and Nonlinear Partial Differential Equations (Grundlehren der mathematischen Wissenschaften) 2011 by Bahouri, Hajer, Chemin, Jean-Yves, Danchin, Raphaël (ISBN: 9783642168291) from Amazon's Book Store. Our developed system produced 64 fuzzy rules as well. In this chapter we introduce Separation of Variables one of the basic solution techniques for solving partial differential equations. , tensorflow via numpy) or standalone compilation as matlab plugin. (1) Numerical experiments show that small neural networks (< 500 learnable parameters) are able to accurately learn complex solutions for systems of partial differential. Fluid mechanics embraces engineering, science, and medicine. Choose a web site to get translated content where available and see local events and offers. We will send you an email that includes a link to create a new password. which involved solving Navier-Stokes. The equations, which date to the 1820s, are today used to model everything from ocean currents to turbulence in the wake of an airplane to the flow of blood in the heart. Advances in Water Resources, Vol. This article presents a new methodology called Deep Theory of Functional Connections (TFC) that estimates the solutions of partial differential equations (PDEs) by combining neural networks with the TFC. Discover (and save!) your own Pins on Pinterest. Addon for sending video, audio, depth and osc to a remote peer using RTP. Ebooks library. This is done by using Reynolds averaged Navier-Stokes (RANS) and an actuator disc (ACD) technique in the computational fluid dynamics code PHOENICS. 3 litre (1297cc) Duratec petrol engine, inc. by the Navier-Stokes equations, ˆ @v @t + ˆ(v r)v = r p+ r2v; (7) where pdenotes the pressure and the viscosity coef-ﬁcient. This article presents a new methodology called Deep Theory of Functional Connections (TFC) that estimates the solutions of partial differential equations (PDEs) by combining neural networks with the TFC. (2020) A low-rank solver for the stochastic unsteady Navier–Stokes problem. com provides all kinds of CUDA Freelancer in Comoros the with proper authentic profile and are available to be hired on Truelancer. 0 0 0 0 Updated Jul 26, 2020. It does not require the original model building code to run, which makes it useful for sharing or deploying (with TFLite, TensorFlow. The trained model uses the Softmax function as the loss function, and the data is equal to 180 learning data for normal and abnormal cells to improve the performance indicators of low precision, F‐1, and score generated in the first experiment. Partial differential equations (PDEs) are among the most ubiquitous tools used in modeling problems in nature. Up to now, the equations describing viscous fluid flow, the Navier-Stokes (NS) equations, have not even been proven to always have a solution. A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. The Moonvision GmbH, Vienna. Introduction to fluid dynamics, from incompressible, inviscid flow and Bernoulli’s principle, to viscid, compressible flow and Navier-Stokes equations. Flow 3d tutorial Flow 3d tutorial. Stack Exchange network consists of 177 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. As illustrated in Figure 1, the “current FEA-based analysis” begins with the three requisite TAV design parameters, generates the FE mesh, and conducts two FE simulations: The 1st FE simulation is for leaflet mounting and the 2nd FE simulation for obtaining the deformed shape and stress. Benjamin indique 5 postes sur son profil. Curriculum Vitae Work Experience. The celebrated Navier-Stokes equation is an example of a system of PDEs whose theoretical understanding is incomplete: \[ \frac{\partial u}{\partial t} + (u \cdot \Delta - u) u + \frac{1}{\rho} abla p = f. The equations, which date to the 1820s, are today used to model everything from ocean currents to turbulence in the wake of an airplane to the flow of blood in the heart. Num mundo onde toda equipe de ciência de dados é composto com um time com diversos backgrounds, conheça a trajetória da Gabriela de Queiroz, estatística, epidemiologista, developer advocate, fundadora do R-Ladies e agora machine learning manager de um time de ciência de dados na IBM.
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text:
Next: Demonstration 18: The equatorial quasi-biennial oscillation
Previous: Demonstration 16: The ellipsoid vortex

The vertical and horizontal structure of steady forced Rossby waves depends on the velocity and stratification profiles in the basic state. This demonstration allows you to explore this dependence.

1: The model

We consider the linearised quasi-geostrophic equations in a -plane. and are horizontal coordinates representing longitude and latitude respectively and represents height. The channel is assumed to have rigid walls at , where the boundary condition of no normal flow is applied. The basic state is one of flow with speed in the -direction and the backgound stratification is represented by the buoyancy frequency . The flow is disturbed by topographic forcing at the lower boundary, with topographic height of the form

The disturbances to the basic flow are represented by a quasi-geostrophic streamfunction , assumed to have the form . The equation for may be derived from the linearised form of the quasi-geostrophic potential vorticity equation, and takes the form

where . The constant represents the effect of constant damping on both temperature or density and momentum and is the Coriolis parameter. The boundary condition

is applied at corresponding to flow over topography. At the upper boundary the condition that waves decay with (for ) is applied.

2: Running the demonstration

On entering this demonstration you must:

(i) specify either a topographic shape and basic state distributions of and , by selecting Specify formulae.

(ii) select Calculate to determine the steady state wave field. This is depicted in terms of the distribution of , i.e. of the streamfunction along the centre of the channel, in the plane.

(iii) Other menu options control some of the internal parameters of the calculation and are described in detail in §4 below.

3: Notes

The method of solution is to take the Fourier transform of (17.1) with respect to . A set of ordinary differential equations in for each Fourier component results, and each may be solved using a simple numerical scheme. An inverse transform may then be applied to the resulting expressions to give the solution for as a function of and .

The method of solution implicitly assumes that the -domain is periodic. You must therefore remember that when you specify an initial distribution, or a forcing distribution, that distribution is actually replicated periodically an infinite number of times to the left and to the right of your field of view. If you want to use this demonstration to study the response to an isolated topographic forcing, you must therefore choose the damping constant to be sufficiently large that the waves have decayed to a small factor of their original amplitude in the time it takes the waves to propagate through the length of the domain.

Otherwise, the method of solution is extremely robust.

Note that most of the parameters for this demonstration are not displayed on the screen initially. To inspect the model parameters, functions or grid size, choose the appropriate menu option and the information will be displayed in a window. Hitting escape in these windows leaves the data unchanged and returns to the menu.

Note that this demonstration works in SI units. Sensible default values are given for the various parameters.

Calculate: Evaluates and draws a contour plot of psi.

Model: Allows you to specify the parameters , , and .

Specify formulae: allows you to change the formulae used for , and .

Domain: allows you to specify the ranges of and values you are interested in.

Accuracy: allows you to set the number of grid points used in the and directions. The number of points in the direction must be a power of 2. The maximum number of points in either direction is 64.

Exit: returns to the GEFD main menu.

5: Suggested experiments

(i) Taking sinusoidal topography and independent of height, you might verify the basic predictions of the Charney-Drazin model, viz. vertical propagation when the basic velocity is positive and not too strong, vertical trapping otherwise. Does the critical positive velocity, above which there is no vertical propagation, have the expected dependence on horizontal wavelength?

(ii) Keeping sinusoidal topography, now let increase with height, starting below the critical velocity and increasing to above it. What is the vertical structure of the waves? Now change the topography to an isolated hump. Can you explain the pattern that results? You should find that some waves excited by the topography are trapped in the vertical, whilst others propagate.

(iii) Now try varying the stratification, e.g. let increase with height as it does from troposphere to stratosphere, in the real atmosphere. Could the increase in from troposphere to stratosphere alone account for the observed structure of the waves with height?

References

Charney, J.G. and Eliassen, A., 1949: A numerical model for prediciting the perturbations of the middle latitude westerlies. Tellus, 1, 38-54.

White, A.A., 1982: Zonal translation properties of two quasi-geostrophic systems of equations. J. Atmos. Sci., 39, 2107-2118.

Next: Demonstration 18: The equatorial quasi-biennial oscillation
Previous: Demonstration 16: The ellipsoid vortex
Emily 2002-10-09

format: plain


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# Japan Earthquake: nuclear plants part 2

#### etudiant

Gold Member
Very impressive performance by TEPCO. They are eating the elephant, one spoonful at a time, as laid out in their longer term plans..
Presumably a similar approach will be implemented later on units 1 and 2. Once that is done, the actual site fuel removal and cleanup can begin.

#### Astronuc

Staff Emeritus
I posted about some open-access reports in the thread on Fukushima discussions.

However, there are two important technical books on the accident progression and report by AESJ. They are not open-access, but must be purchased, but are probably worth the money for serious technical analysis.

A Study of the Fukushima Daiichi Nuclear Accident Process
https://www.springer.com/us/book/9784431555421 e-book $89.00 The Fukushima Daiichi Nuclear Accident Final Report of the AESJ Investigation Committee https://www.springer.com/us/book/9784431551591 e-book$129.00

"Japan Earthquake: nuclear plants part 2"

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# What happened with the file?

What happened with this file?

infile = "\\test data.txt";

outstr = OpenWrite[infile];
Close[instr];

All content of "test data.txt" was lost.

• You should have used OpenAppend. – Mr.Wizard Mar 22 '13 at 16:52

From the help

OpenWrite["file"] open an output stream to a file, wiping out the previous contents of the file

... it's gone, you deleted it :


text:
IsAntiArborescence - Maple Help

GraphTheory

 IsArborescence
 test if a graph is an arborescence
 IsAntiArborescence
 test if a graph is an anti-arborescence

 Calling Sequence IsArborescence(G,opts) IsAntiArborescence(G,opts)

Parameters

 G - a directed graph opts - : (optional) root=true or root=false

Options

 • root : keyword option of the form root=true or root=false. This specifies whether the root vertex should be returned when the check is positive. The default is false.

Description

 • The IsArborescence function returns true if the input graph is an arborescence, and false otherwise.
 • The IsAntiArborescence function returns true if the input graph is an anti-arborescence, and false otherwise.

Details

 • A directed graph G is an arborescence if there is a single vertex u called the root such that for any other vertex v, there is exactly one path from u to v.
 • A directed graph G is an anti-arborescence if there is a single vertex v called the root such that for any other vertex u, there is exactly one path from u to v. An anti-arborescence is a graph whose reverse is an arborescence.

Examples

Confirm that a directed path is both an arborescence and an anti-arborescence.

 > $\mathrm{with}\left(\mathrm{GraphTheory}\right):$
 > $T≔\mathrm{Graph}\left(\left\{\left[1,2\right],\left[2,3\right]\right\}\right)$
 ${T}{≔}{\mathrm{Graph 1: a directed unweighted graph with 3 vertices and 2 arc\left(s\right)}}$ (1)
 > $\mathrm{IsArborescence}\left(T\right)$
 ${\mathrm{true}}$ (2)
 > $\mathrm{IsAntiArborescence}\left(T\right)$
 ${\mathrm{true}}$ (3)

Confirm that a directed cycle is neither an arborescence nor an anti-arborescence.

 > $C≔\mathrm{Graph}\left(\left\{\left[1,2\right],\left[2,3\right],\left[3,1\right]\right\}\right)$
 ${C}{≔}{\mathrm{Graph 2: a directed unweighted graph with 3 vertices and 3 arc\left(s\right)}}$ (4)
 > $\mathrm{IsArborescence}\left(C\right)$
 ${\mathrm{false}}$ (5)
 > $\mathrm{IsAntiArborescence}\left(C\right)$
 ${\mathrm{false}}$ (6)

Check whether a graph is an arborescence and display its root vertex.

 > $G≔\mathrm{Graph}\left(\left\{\left[1,2\right],\left[1,5\right],\left[2,3\right],\left[2,4\right]\right\}\right)$
 ${G}{≔}{\mathrm{Graph 3: a directed unweighted graph with 5 vertices and 4 arc\left(s\right)}}$ (7)
 > $\mathrm{IsArborescence}\left(G\right)$
 ${\mathrm{true}}$ (8)
 > $\mathrm{IsArborescence}\left(G,\mathrm{root}\right)$
 ${\mathrm{true}}{,}{1}$ (9)
 > $\mathrm{IsAntiArborescence}\left(G\right)$
 ${\mathrm{false}}$ (10)

Check whether a graph is an anti-arborescence and display its root vertex.

 > $A≔\mathrm{Graph}\left(\left\{\left[1,3\right],\left[2,3\right]\right\}\right)$
 ${A}{≔}{\mathrm{Graph 4: a directed unweighted graph with 3 vertices and 2 arc\left(s\right)}}$ (11)
 > $\mathrm{IsArborescence}\left(A\right)$
 ${\mathrm{false}}$ (12)
 > $\mathrm{IsAntiArborescence}\left(A,\mathrm{root}\right)$
 ${\mathrm{true}}{,}{3}$ (13)
 > $\mathrm{IsAntiArborescence}\left(A\right)$
 ${\mathrm{true}}$ (14)

Compatibility

 • The GraphTheory[IsArborescence] and GraphTheory[IsAntiArborescence] commands were introduced in Maple 2016.


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NN Backpropagation

The case we are handling: a 2 layers network

The above diagram shows the network to be used. From the last blog we get the loss function:

In order to use the gradient descent algorithm to train $\scriptsize W_1$ and $\scriptsize W_2$, we need to compute the derivative of $\scriptsize\mathscr{L}$ to $\scriptsize W_1$ and $\scriptsize W_2$, which are:

If we have $\scriptsize \frac{d\mathscr{L}}{dW_2}$ by hand, then $\scriptsize W_2$ can be trained using gradient descent:

Compute $\frac{d\mathscr{L}}{dW_2}$

How to compute $\scriptsize \frac{d\mathscr{L}}{dW_2}$? We use the chain rule to “propagate back” the gradient, for $\scriptsize W_2$:

As the last blog described, $\scriptsize \frac{d\mathscr{L}}{df}$ of the $\scriptsize ith$ sample can be expressed as:

considering $\scriptsize f=W_2\cdot X_2+b_2$:

then:

Compute $\frac{d\mathscr{L}}{dW_1}$

Now we will compute $\scriptsize \frac{d\mathscr{L}}{dW_1}$ to train $\scriptsize W_1$. The gradient will be propagated back to $\scriptsize W_1$ like this:

the same as before, we know that $\scriptsize Y_1 = W_1\cdot X_1 + b_1$, the above equation results in:

$\scriptsize \frac{d\mathscr{L}}{df}$ is already known, $\scriptsize \frac{dX_2}{dY_1}$ depends on the activation function of the hidden layer.

Using this method, we can easily propagate the gradient back to the input layer through the whole network and update all the layers, no matter how many layers are there in between.

-->

Wangxin

I am algorithm engineer focused in computer vision, I know it will be more elegant to shut up and show my code, but I simply can't stop myself learning and explaining new things ...

SVD, PCA and Least Square Problem

SVD PCA Continue reading

NN Softmax loss function

Published on March 09, 2017

NN Dropout

Published on January 08, 2017


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# Sun related calculations

Thank you!

## Code to calculate Equation of Time and Solar Declination

The Equation of Time is the difference between the time that is shown by a sundial and the time that is shown by a clock that is set to local mean time. Essentially, the Equation of Time shows the longitude of the sun in the sky, relative to its mean position. The Solar Declination is the sun's latitude. Both of these quantities must be known for many purposes related to solar energy.

### Computer program

The following subroutine, here written in QBasic but easily translatable to other languages, calculates the Equation of Time and the Solar Declination on any day of the year. It is quite accurate. Its Root-Mean-Square error for the Equation of Time is only 3.7 seconds. The Declination is calculated with errors that are always small compared with the angular radius of the sun as seen from the earth (about 0.25 degrees).

Anyone who wants further information should follow the following link: [Link] The program that includes the routine is ETIMSDEC. There are instructions how to run it. The article titled "The Latitude and Longitude of the Sun", which I wrote several years ago, describes the astronomical logic behind the routine.

DOwenWilliams 10:19, 18 May 2011 (PDT) David Williams

FUNCTION ET.Dec (D, F%) STATIC
' Calculates equation of time, in minutes, or solar declination,
' in degrees, on day number D of year. (D = 0 on January 1.)
' F% selects function: True (non-zero) for Equation of Time,
' False (zero) for Declination.
' STATIC means variables are preserved between calls of function

IF PI = 0 THEN ' first call, initialize constants

PI = 4 * ATN(1)
W = 2 * PI / 365 ' earth's mean orbital angular speed in radians/day
DR = 180 / PI ' degree/radian factor
C = -23.45 / DR ' reverse angle of earth's axial tilt in radians
ST = SIN(C) ' sine of reverse tilt
CT = COS(C) ' cosine of reverse tilt
E2 = 2 * .0167 ' twice earth's orbital eccentricity
SP = 12 * W ' 12 days from December solstice to perihelion
D1 = -1 ' holds last D. Saves time if D repeated for both functions

END IF

IF D <> D1 THEN ' new value of D
A = W * (D + 10) ' Solstice 10 days before Jan 1
B = A + E2 * SIN(A - SP)
D1 = D
END IF

IF F% THEN ' equation of time calculation
C = (A - ATN(TAN(B) / CT)) / PI
ET.Dec = 720 * (C - INT(C + .5)) ' this is value of equation of time
' in 720 minutes, earth rotates PI radians relative to sun

ELSE ' declination calculation
C = ST * COS(B)
ET.Dec = ATN(C / SQR(1 - C * C)) * DR ' this is value of declination
' arcsine of C in degrees. ASN not directly available in QBasic

END IF

END FUNCTION

### Alternative calculation

The following calculation is essentially the same as the one above, with minor changes. Angles are in degrees instead of radians. Some explanation follows each line. And, although it can be written as a computer program, the calculation can be done with a pocket calculator or similar tool.

Angles are in degrees. Asterisks mean multiplication. Slashes mean division. The conventional order of operations applies.

$W=360/365.24$

W is the Earth's mean angular orbital velocity in degrees per day.

$A=W*(D+10)$

D is the date, in days starting at zero on January 1 (i.e. the days part of the ordinal date -1). 10 is the approximate number of days from the December solstice to January 1. "A" is the angle the earth would move on its orbit at its average speed from the December solstice to date D.

$B=A+(360/\pi)*0.0167*sin(W*(D-2))$

B is the angle the Earth moves from the solstice to date D, including a first-order correction for the Earth's orbital eccentricity, 0.0167. The number 2 is the number of days from January 1 to the date of the Earth's perihelion. This expression for B can be simplified by combining constants to: $B=A+1.914*sin(W*(D-2))$.

$C=(A-arctan(tan(B)/cos(23.44)))/180$

C is the difference between the angles moved at mean speed, and at the corrected speed projected onto the equatorial plane, and divided by 180 to get the difference in "half turns". The number 23.44 is the obliquity (tilt) of the Earth's axis in degrees. The subtraction gives the conventional sign to the equation of time. For any given value of x, arctan(x) (sometimes written as tan−1x) has multiple values, differing from each other by integer numbers of half turns. The value generated by a calculator or computer may not be the appropriate one for this calculation. This may cause C to be wrong by an integer number of half turns. The excess half turns are removed in the next step of the calculation:

$EoT=720*(C-nint(C))$

EoT is the equation of time in minutes. The expression nint(C) means the nearest integer to C. On a computer, it can be programmed, for example, as INT(C+0.5). It is 0, 1, or 2 at different times of the year. Subtracting it leaves a small positive or negative fractional number of half turns, which is multiplied by 720, the number of minutes (12 hours) that the Earth takes to rotate one half turn relative to the Sun, to get the equation of time.

Compared with published values, this calculation has a Root Mean Square error of only 3.7 seconds of time. The greatest error is 6.0 seconds.

The value of B in the above calculation is an accurate value for the Sun's ecliptic longitude (shifted by 90 degrees), so the solar declination becomes readily available:

$Declination = - arcsin(sin(23.44)*cos(B))$

which is accurate to within a fraction of a degree.

## Formulae about paraboloidal dishes

### Dimensions of a dish

The dimensions of a symmetrical paraboloidal dish are related by the equation: $\scriptstyle 4FD = R^2$, where $F$ is the focal length, $D$ is the depth of the dish (measured along the axis of symmetry from the vertex to the plane of the rim), and R is the radius of the rim. Of course, they must all be in the same units. If two of these three quantities are known, this equation can be used to calculate the third.

A more complex calculation is needed to find the diameter of the dish measured along its surface. This is sometimes called the "linear diameter". It is the diameter of a flat, circular sheet of material, usually metal, which is the right size to be cut and bent to make the dish. Two intermediate results are useful in the calculation: $\scriptstyle P=2F$ and $\scriptstyle Q=\sqrt {P^2+R^2}$, where F and R are defined as above. The linear diameter is then given by: $\scriptstyle S= \frac {RQ} {P} + P \ln \left ( \frac {R+Q} {P} \right )$, where $\scriptstyle \ln(x)$ means the natural logarithm of $\scriptstyle x$, i.e. its logarithm to base "e".

The volume of the dish, i.e. the amount of liquid it could hold if the rim were horizontal and the vertex at the bottom, is given by $\scriptstyle V= \frac {\pi R^4} {8 F}$, or equivalently $\scriptstyle V= \frac {1} {2} \pi R^2 D$, where the symbols are defined as above. This can be compared with the well-known formulae for the volumes of a cylinder and a cone. Of course, $\scriptstyle \pi R^2$ is the aperture area of the dish, the area enclosed by the rim, which is proportional to the amount of sunlight the reflector dish can intercept.

### Paraboloids made by rotating liquids

Paraboloids can be made quite simply by rotating open-topped containers which hold liquids. The top surface of a liquid which is being rotated at constant speed around a vertical axis naturally takes the form of a paraboloid.

The focal length of the paraboloid is related to the angular speed at which the liquid is rotated by the equation: 2f$\omega^2$=g, where f is the focal length, $\omega$ is the rotation speed, and g is the acceleration due to gravity. They must be in compatible units so, for example, f can be in metres, $\omega$ in radians per second, and g in metres per second-squared. The angle unit in $\omega$ must be radians. 1 radian per second is about 9.55 rotations per minute (RPM). On the Earth's surface, g is about 9.81 metres per second-squared. Putting these numbers into the equation produces the approximation: $\scriptstyle fs^2 \approx 447$, where $f$ is the focal length in metres, and s is the rotation speed in RPM.

### Focus-balanced reflectors

Paraboloidal reflectors that have their centres of mass coincident with their focal points are useful. If the paraboloidal reflector is axially symmetrical and is made of material of uniform thickness, its centre of mass coincides with its focus if the depth of the reflector, measured along its axis of symmetry from the vertex to the plane of the rim, is 1.8478 times its focal length. The radius of the rim of the reflector is 2.7187 times the focal length. The angular radius of the rim, as seen from the focal point, is 72.68 degrees.

## Iterative calculations

There are situations in which a calculation is impracticably difficult or impossible to do, even by a professional mathematician. Often, in these situations, a numerical answer can be obtained by using a computer program that performs a large number of iterations around a loop. Using these techniques requires the availability of a computer programming language (it makes little difference which one), and some proficiency in using it. Obtaining these is very useful.

### Numerical integration

Integration is an operation that can be extremely difficult or impossible. However, integration is really just summation of an infinite number of infinitessimal terms. By making the terms larger than infinitessimal, but still very small, a computer program can make the machine add a huge number of terms to come up with an acceptably accurate value for the definite integral. An example is shown in Focus-balanced paraboloid. The integration was impossibly difficult, at least for the writer. Writing the computer program was quite easy, and the answer was accurate to at least ten significant digits.

### Binary searches to invert functions

In "Dimensions of a dish", above, an expression is given that allows the "linear diameter" of a paraboloidal dish, which is represented by S, to be calculated from its focal length, F, and the radius of its rim, R. Doing the calculation in that direction is easy, using a pocket calculator. However, inverting it to calculate F from S and R, for example, is extremely difficult. One approach is to program a computer to perform a binary search for the correct value of F. Using the given R and a trial value of F which is at the middle of an assumed range of possibility, the machine calculates a value for S. Depending on whether the calculated S is too high or too low, compared with the given one, the trial F is assigned as either the upper or the lower limit of a new range of possibility, half as large as the previous one. A new trial F is then calculated, in the middle of the new range, and the cycle is repeated. Within ten iterations, the range of possibility is reduced by a factor of a thousand. (210=1024) The true value of F is known to be within this small range. A few more iterations allow F to be found to any desired level of accuracy. This technique is frequently useful.


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# What is the positive integer n? (1) For every integer m,

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What is the positive integer n? (1) For every integer m, [#permalink]

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18 Aug 2008, 07:32
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What is the positive integer n?

(1) For every integer m, $$(m+n)!/(m-1)!$$ is divisible by 16

(2) $$m^2-9n+20=0$$

Thanks

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 07:51
tarek99 wrote:
What is the positive integer n?

(1) For every integer m, $$(m+n)!/(m-1)!$$ is divisible by 16

(2) $$m^2-9n+20=0$$

Thanks

B
back solving

n= (m^2+20) / 9

for n to be a positive integer m^2+20 should be multiple of 9

Try values 9, 18,27 , 36 for m^2+20
m^2+20 = 36 suits best
=> m=+4 or -4

and also n=4;

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 07:59
Can you please explain why A is insufficient?

chan4312 wrote:
tarek99 wrote:
What is the positive integer n?

(1) For every integer m, $$(m+n)!/(m-1)!$$ is divisible by 16

(2) $$m^2-9n+20=0$$

Thanks

B
back solving

n= (m^2+20) / 9

for n to be a positive integer m^2+20 should be multiple of 9

Try values 9, 18,27 , 36 for m^2+20
m^2+20 = 36 suits best
=> m=+4 or -4

and also n=4;

_________________

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 08:08
I think the answer is (E).

Because there is upper limit for n. If we insert an super high value for n, the term can surely be divided by 16.

Most likely, I am wrong. I am now in the valley for Quan. Have been too focus on prastising Verb.

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 08:29
jallenmorris wrote:
Can you please explain why A is insufficient?

chan4312 wrote:
tarek99 wrote:
What is the positive integer n?

(1) For every integer m, $$(m+n)!/(m-1)!$$ is divisible by 16

(2) $$m^2-9n+20=0$$

Thanks

B
back solving

n= (m^2+20) / 9

for n to be a positive integer m^2+20 should be multiple of 9

Try values 9, 18,27 , 36 for m^2+20
m^2+20 = 36 suits best
=> m=+4 or -4

and also n=4;

put n=1
==> (m+1)! / (m-1)! = (m+1)m

put m=15 ...divisible by 16

put n=2
==> (m+2)! / (m-1)! =(m+2)(m+1)m
put m=14 divisible by 16

put n=3
==> (m+3)! / (m-1)! = (m+3)(m+2)(m+1)m
put m=13

put n=4
==> (m+4)! / (m-1)! = (m+4)(m+3)(m+2)(m+1)m

n can be anything..

So i could not deduce anything from A.

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 13:26
Well guys, the OA is C. Here is the OE, which I never understood clearly. Maybe someone could use that to come up with a better explanation:

(1) Note that (m+n)!/(n-1)! = m(m+1)(m+2).....(m+n), the product of the n+1 integers from m to m+n, inclusive. The product is a multiple of 16 for every integer n if and only if three of the terms are even, i.e. if the product consists of at least 6 terms. Thus n+1 is greater than or equal to 6, and n is at least 5. NOT SUFF.

(2) n is either 4 or 5 NOT SUFF.

(1&2) n=5 SUFF.

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 13:43
tarek99 wrote:
Well guys, the OA is C. Here is the OE, which I never understood clearly. Maybe someone could use that to come up with a better explanation:

(1) Note that (m+n)!/(n-1)! = m(m+1)(m+2).....(m+n), the product of the n+1 integers from m to m+n, inclusive. The product is a multiple of 16 for every integer n if and only if three of the terms are even, i.e. if the product consists of at least 6 terms. Thus n+1 is greater than or equal to 6, and n is at least 5. NOT SUFF.

(2) n is either 4 or 5 NOT SUFF.

(1&2) n=5 SUFF.

We can do that!
Let us extend our earlier analysis

n= (m^2+20) / 9

for n to be a positive integer m^2+20 should be multiple of 9

Try values 9, 18,27 , 36, 45 for m^2+20
m^2+20 = 36 => m=+4 or -4
m^2+20 = 45 => m=+5 or -5

substitute m value to get n
==> n can be 4 or 5
let us see which value suits best.

(m+n)!/(n-1)! = m(m+1)(m+2).....(m+n)
for n=4 => it becomes m(m+1)(m+2)(m+3)(m+4)

for a product of consecutive numbers series to have 16 as a factor , there should be atleast three even numbers in the series.
let us see 2*3*4*5*6 = 720 ,divisible by 16

so above n=4 does not suffice.

try n=5 ==> it contains 6 terms..
m can be either even or odd it does not matter..it is divisible by 16.
truly tough one..

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 15:59
What is the positive integer n?

(1) For every integer m, is divisible by 16

(2)

Explanation:

From choice 1, we can deduce that n should atleast be 5 because, the numeration will only yield a product of 16, it (m+n) is 6!. This is because, 6! = 6*5*4*3*2*1 and this is the smallest number that has 4 multiples of 2s, which will give 16. So, n>=5. However, this is insufficient.

Choice 2: Here the equation should be n^2-9n+20 = 0 ; The question cannot relate choice 1 and choice 2. There is nowhere else about "m" except in choice 1. Hence, when we solve for the above equation, we get, (n-5)*(n-4)=0, which will give n = 5 or n = 4; So, this is insufficient.

Combining both the choices, we get n = 5 and hence the correct answer is C.

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Re: DS: What is n? [#permalink]

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18 Aug 2008, 19:53
for a product of consecutive numbers series to have 16 as a factor , there should be atleast three even numbers in the series.
let us see 2*3*4*5*6 = 720 ,divisible by 16

.........a very simple question ...........u got the core right

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Re: DS: What is n?   [#permalink] 18 Aug 2008, 19:53
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