Ch4 Basics of Fluid Flow
建环专业英语
建环专业英语 Company number【1089WT-1898YT-1W8CB-9UUT-92108】建筑环境与设备工程专业英语翻译A thermodynamic system is a region in space or a quantity of matter bounded by a closed surface. The surroundings include everything external to the system, and the system is separated from the surroundings by the system boundaries. These boundaries can be movable or fixed, real or imaginary.一个热力学系统是一个在空间或有事项的数量由一个封闭的表面范围内的区域。
周围环境包括一切外部系统，系统是从周围环境隔开的系统边界。
这些边界可以是动产或固定的，真实的或想象。
The concepts that operate in any thermodynamic system are entropy and energy. Entropy measures the molecular disorder of a system. The more mixed a system, the greater its entropy; conversely, an orderly or unmixed configuration is one of low entropy. Energy has the capacity for producing an effect and can be categorized into either stored or transient forms as described in the following sections.熵和能量的概念，在任何热力学系统操作。
常微分方程的英文
常微分方程的英文Ordinary Differential EquationsIntroductionOrdinary Differential Equations (ODEs) are mathematical equations that involve derivatives of unknown functions with respect to a single independent variable. They find application in various scientific disciplines, including physics, engineering, economics, and biology. In this article, we will explore the basics of ODEs and their importance in understanding dynamic systems.ODEs and Their TypesAn ordinary differential equation is typically represented in the form:dy/dx = f(x, y)where y represents the unknown function, x is the independent variable, and f(x, y) is a given function. Depending on the nature of f(x, y), ODEs can be classified into different types.1. Linear ODEs:Linear ODEs have the form:a_n(x) * d^n(y)/dx^n + a_(n-1)(x) * d^(n-1)(y)/dx^(n-1) + ... + a_1(x) * dy/dx + a_0(x) * y = g(x)where a_i(x) and g(x) are known functions. These equations can be solved analytically using various techniques, such as integrating factors and characteristic equations.2. Nonlinear ODEs:Nonlinear ODEs do not satisfy the linearity condition. They are generally more challenging to solve analytically and often require the use of numerical methods. Examples of nonlinear ODEs include the famous Lotka-Volterra equations used to model predator-prey interactions in ecology.3. First-order ODEs:First-order ODEs involve only the first derivative of the unknown function. They can be either linear or nonlinear. Many physical phenomena, such as exponential decay or growth, can be described by first-order ODEs.4. Second-order ODEs:Second-order ODEs involve the second derivative of the unknown function. They often arise in mechanical systems, such as oscillators or pendulums. Solving second-order ODEs requires two initial conditions.Applications of ODEsODEs have wide-ranging applications in different scientific and engineering fields. Here are a few notable examples:1. Physics:ODEs are used to describe the motion of particles, fluid flow, and the behavior of physical systems. For instance, Newton's second law of motion can be formulated as a second-order ODE.2. Engineering:ODEs are crucial in engineering disciplines, such as electrical circuits, control systems, and mechanical vibrations. They allow engineers to model and analyze complex systems and predict their behavior.3. Biology:ODEs play a crucial role in the study of biological dynamics, such as population growth, biochemical reactions, and neural networks. They help understand the behavior and interaction of different components in biological systems.4. Economics:ODEs are utilized in economic models to study issues like market equilibrium, economic growth, and resource allocation. They provide valuable insights into the dynamics of economic systems.Numerical Methods for Solving ODEsAnalytical solutions to ODEs are not always possible or practical. In such cases, numerical methods come to the rescue. Some popular numerical techniques for solving ODEs include:1. Euler's method:Euler's method is a simple numerical algorithm that approximates the solution of an ODE by using forward differencing. Although it may not provide highly accurate results, it gives a reasonable approximation when the step size is sufficiently small.2. Runge-Kutta methods:Runge-Kutta methods are higher-order numerical schemes for solving ODEs. They give more accurate results by taking into account multiple intermediate steps. The most commonly used method is the fourth-order Runge-Kutta (RK4) algorithm.ConclusionOrdinary Differential Equations are a fundamental tool for modeling and analyzing dynamic systems in various scientific and engineering disciplines. They allow us to understand the behavior and predict the evolution of complex systems based on mathematical principles. With the help of analytical and numerical techniques, we can solve and interpret different types of ODEs, contributing to advancements in science and technology.。
《液压与气压传动》课程教学大纲
液压与气压传动一、课程介绍《液压与气压传动》是材料成型及控制工程专业本科学生的一门学科基础选修课。
液压装置广泛的使用在工业与农业生产的各个领域，它们是使用压力油为传递能量的载体来实现传动与控制的，随着自动化技术的开展，应用越来越广泛。
课程的任务是使学生掌握液压与气压传动的基础知识，掌握各种液压、气动元件的工作原理、特点、应用和选用方法，熟悉各类液压与气动基本问路的功用、组成和应用场合，了解国内外先进技术成果在机械设备中的应用。
本课程教学内容分液压传动和气压传动两局部。
液压传动局部主要介绍液压流体力学基础知识，液压动力元件、执行元件、控制元件和辅助元件，液压传动基本回路、典型液压传动系统和液压系统的设计计算。
气压传动局部介绍气压传动基础知识、气源装置及气动元件和气动基本回路与常用回路，气动逻辑系统设计和气动传动系统实例。
本课程所讲述的内容有：液压流体力学基础、液压泵、液压马达与液压缸、液压控制阀、液压辅件、液压基本回路、典型液压系统、液压系统的设计计算、气压传动基础知识、气源装置及气动元件、气动基本回路与常用回路、气动逻辑系统设计、气动传动系统实例等共11章，教学局部共包含理论24学时,末考试形式为开卷笔试。
Introduction“Hydraulic and pneumatic transmission^ is a mechanical professional students a compulsory technical courses. Hydraulic device widely used in various fields of industrial and agricultural production, which is the use of pressurized oi1 to pass energy carriers to realize transmission and control, along with the development of automation technology, more and more widely.Task course is to enable students to master the basics of hydraulic and pneumatictransmission, master a variety of hydraulic, pneumatic components working principle, characteristics, application and selection methods familiar basic functions of various types of hydraulic and pneumatic circuits, composition and applications, understanding advanced technical achievements in mechanical devices.This course content hydraulic and pneumatic transmission of two parts. Hydraulic transmission section introduces the basics of hydraulic fluid mechanics, hydraulics components, actuators, control components , auxiliary components, the basic hydraulic transmission circuit, a typical hydraulic system and hydraulic system design calculations. Pneumatic transmission section describes the basics of pneumatic transmission, gas source device, pneumatic components, basic and common pneumatic circuits , logic system design and examples of pneumatic transmission.The contents of this course are: hydraul ic fluid mechanics, hydraul ic pump, hydraulic motor and hydraulic cylinder, hydraulic control valve, hydraulic accessories, hydraulic basic circuit, typical hydraulic system, hydraulic system design calculation, pneumatic transmission basic knowledge, gas Source device and pneumatic components, pneumatic basic circuit and common circuit, pneumatic logic system design, pneumatic transmission system examples, etc., a total of 11 chapters, the teaching part contains a total of 24 hours of theory.课程基本信息1、教学目的“液压与气压传动”是非机械专业本科生的一门专业基础课程。
流式英文PPT
To introduce and focus the cells for interrogation
Optics
To generate and collect the light signals
Electronics
To convert the optical signals to proportional electronic signals and digitize them for computer analysis
•Cells in suspension
Fluidics •flow in single-file through
•an illuminated volume where they
Optics •scatter light and emit fluorescence
•that is collected, filtered and •converted to digital values
DNA
PI
Fluorescein (FITC)
300 nm
Excitation Emisson
400 nm
500 nm
Wavelength
600 nm
700 nm
400 nm
500 nm
600 nm
700 nm
Relat iv e I nt ens it y
Protein
Phycoerytherin (PE)
Routed the generated light signals to the specific detectors by the collection optics
Laser
FALS Sensor
建筑环境与设备工程专业英语翻译
A thermodynamic system is a region in space or a quantity of matter bounded by a closed surface. The surroundings include everything external to the system, and the system is separated from the surroundings by the system boundaries. These boundaries can be movable or fixed, real or imaginary.一个热力学系统是一个在空间或有事项的数量由一个封闭的表面范围内的区域。
周围环境包括一切外部系统，系统是从周围环境隔开的系统边界。
这些边界可以是动产或固定的，真实的或想象。
The concepts that operate in any thermodynamic system are entropy and energy. Entropy measures the molecular disorder of a system. The more mixed a system, the greater its entropy; conversely, an orderly or unmixed configuration is one of low entropy. Energy has the capacity for producing an effect and can be categorized into either stored or transient forms as described in the following sections.熵和能量的概念，在任何热力学系统操作。
熵措施分子系统紊乱。
更为复杂的系统，其熵值越大，反之，有序或纯配置是低熵之一。
长安大学水力学第三章水动力学基本定律
若给定a，b，c，即 可以得到某一质点 的轨迹方程。-迹线
某一液体质点M，在t0时刻占有空间坐
标为(a、b、c)，在任意t时刻所占有 的空间坐标为(x、y、z)，则(x、y、 z)可表示为时间t与(a、b、c)起始坐 标的函数，即
z t
ux
x t
x(a,b, c,t) t
uy
y t
y(a,b, c,t) t
迹线——是指某个液体质点不同时刻所流经的空
间点所连成的线。流动的轨迹线
流线——是指某一时刻，在流场中，由许多质点
组成的一条光滑曲线，其上所有点的速度方向 都与该曲线相切。
流线能反映瞬时的流动方向 流线图
流线的基本特性
1．恒定流时，流线的形状和位置不随时间而改变。
因为整个流场内各点流速向量均不随
2．恒定流时液体质点运动的迹线与流线相重时合间。而改变，不同时刻的流线的形状
uz
z t
z(a,b, c,t) t
液体质点在任意时刻 的速度。 返回
（x，y，z）
t0
O M （a，b，c） x
y
欧拉法
ux ux (x, y, z,t) uy uy (x, y, z,t) uz uz (x, y, z,t)
ax
dux (x, y, z,t) dt
ay
duy (x, y, z,t) dt
本课程只研究恒定流。
如果流场中任何空间点上有任何一个运动要素是随时间而变化的，这种 水流称为非恒定流。
2.基本概念 Basics of Liquid Flow
• 迹线与流线 • 流管、元流（微小流束）、总流和过水断面 • 流量和断面平均流速 • 水流的分类 • 均匀流、渐变流过水断面的重要特性
stablediffusion模型路径
stablediffusion模型路径Stable Diffusion Model: A Path to Understanding Diffusion ProcessesIntroductionDiffusion is a fundamental process that plays a crucial role in various fields, including physics, chemistry, biology, and social sciences. Understanding the mechanisms behind diffusion is essential for predicting and analyzing a wide range of phenomena. One popular model used to describe diffusion is the Stable Diffusion Model. In this article, we will explore the concept of the Stable Diffusion Model, its key features, and its applications.The Basics of DiffusionBefore delving into the Stable Diffusion Model, let's briefly review the basics of diffusion. Diffusion refers to the spontaneous movement of particles from an area of high concentration to an area of low concentration, driven by random molecular motion. This process continues until a state of equilibrium is reached, where the concentration of particles is uniform throughout the system.The Stable Diffusion ModelThe Stable Diffusion Model provides a mathematical framework to describe and analyze diffusion processes. It is based on the assumption that the displacement of diffusing particles follows a probability distribution known as the stable distribution. This distribution is characterized by its stability index, which determines the shape of the distribution.Unlike other diffusion models that assume a Gaussian distribution, the Stable Diffusion Model allows for heavy-tailed distributions, capturing the presence of outliers and extreme events. This makes it particularly useful in situations where the diffusion process exhibits non-Gaussian behavior, such as in financial markets or turbulent fluid flow.Key Features of the Stable Diffusion Model1. Stable Distribution: The Stable Diffusion Model uses the stable distribution to describe the displacement of diffusing particles. This distribution is characterized by its four parameters: stability index, skewness, scale, andlocation.2. Heavy-Tailed Behavior: The Stable Diffusion Model allows for heavy-tailed distributions, which means that extreme events or outliers are more likely to occur compared to a Gaussian distribution. This feature makes the model suitable for describing processes with occasional large fluctuations.3. Non-Markovian Dynamics: Unlike the standard Brownian motion, which assumes a Markovian process, the Stable Diffusion Model incorporates non-Markovian dynamics. This means that the future behavior of the diffusion process depends not only on its current state but also on its past history.Applications of the Stable Diffusion ModelThe Stable Diffusion Model finds applications in various fields, including:1. Financial Markets: The stock market is known to exhibit heavy-tailed behavior, with occasional extreme price movements. The Stable Diffusion Model provides a more accurate description of these dynamics and is used inoption pricing, risk management, and portfolio optimization.2. Turbulent Fluid Flow: Turbulent flow is characterized by its chaotic and unpredictable nature. The Stable Diffusion Model helps in understanding the statistical properties of turbulent flow, leading to improved modeling and prediction of fluid dynamics.3. Biological Systems: Diffusion plays a vital role in biological systems, such as the movement of molecules across cell membranes or the spread of diseases. The Stable Diffusion Model allows for non-Gaussian behavior, making it suitable for studying complex biological processes. ConclusionThe Stable Diffusion Model offers a valuable framework for understanding and analyzing diffusion processes. Its ability to capture heavy-tailed distributions and non-Markovian dynamics makes it applicable in various fields, ranging from finance to biology. By incorporating the stable distribution, this model provides a more accurate representation of real-world phenomena and enables researchers to gain deeper insights into diffusionprocesses.。
化学反应工程英文课件Chapter 11
化学反应工程
停留时间分布函数 — F(t) 函数
对于同时进入反应器入口的 N 个流体粒子，若在出口 处进行检测，则其中停留时间介于 0 ～ t 之间的流体粒 子所占的分率为 F(t) —— 我们定义 F(t) 为停留时间分 布函数。 如：在某时刻进入反应器入口的 100 个流体粒子，到 达出口时停留时间为 0 ~ 5 min 的粒子有 20 个，若取 t = 5 min，则此时 F(t) = 20 /100 = 0.2。 F(t) 是一个累积（如 t = 0～5 min ）的分率。
化学反应工程
Figure 11.3Ex来自mples of macro- and microfluid behavior.
化学反应工程 Earliness of Mixing
The fluid elements of a single flowing stream can mix with each other either early or late in their flow through the vessel. For example, see Fig. 11.4. Usually this factor has little effect on overall behavior for a single flowing fluid. However, for a system with two entering reactant streams it can be very important. For example, see Fig. 11.5.
化学反应工程
11.1 E, THE AGE DISTRIBUTION OF FLUID, THE RTD
It is evident that elements of fluid taking different routes through the reactor may take different lengths of time to pass through the vessel. The distribution of these times for the stream of fluid leaving the vessel is called the exit age distribution E, or the residence time distribution RTD of fluid. E has the units of time-1.
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Objectives
• Identify the basic categories of fluid flow. • Understand the definition of pathline, streamline and streakline. • Understand how flow rates are defined and how to relate volume, mass, and weight based flow rates. • Understand the Equation of Continuity and know how to apply it to various types of flow.
must be the same for all cross sections of the streamtube.
Pathlines
Streaklines (脉线 ) 脉线
•
A Streakline is the locus of fluid particles that have passed sequentially through a prescribed point in the flow. Easy to generate in experiments: dye in a water flow, or smoke in an airflow. same as pathline and streamline for steady flow
• •
相继通过某空间点的质点连线
Comparisons
For steady flows: streamlines, pathlines and streaklines are identical. For unsteady flows: they can be very different. Streamlines are an instantaneous picture of the flow field Pathlines and Streaklines are flow patterns that have a time history associated with them. Streakline: instantaneous snapshot of a timeintegrated flow pattern. Pathline: time-exposed flow path of an individual particle.
Outline
• • • • • • • •
4.1 Two ways to describe fluid motion 4.2 Types of flows 4.3 Steady Flow and Uniform Flow 4.4 Pathline, Streamline And Streak line 4.5 Flow Rate and Mean Velocity 4.6 Fluid System and Control Volume 4.7 Equation of Continuity 4.8 One-, Two-, and Three-Dimensional Flow
4.3 Steady flow and Uniform flow
Steady - unsteady
Changing in timespace
4.3 Steady flow and Uniform flow
Steady flow is constant with time, while unsteady flow changes with time. Uniform flow is constant with space, while nonuniform flow changes over space.
Example
• • •
Valve at C is opened slowly Classify the flow at B while valve is opened Classify the flow at A
4.4 Pathline, Streamline
The flow velocity is the basic description of how a fluid moves in time and space, but in order to visualize the flow pattern it is useful to define some other properties of the flow. These definitions correspond to various experimental methods of visualizing fluid flow.
Streamlines
•
A Streamline is a curve that is everywhere tangent to the instantaneous local velocity vector. Geometric arguments results in the equation for a streamline
4.1 Two ways to describe fluid motion
Two ways to describe motion are Lagrangian and Eulerian description.
Lagrangian Description
• • •
•
Lagrangian description of fluid flow tracks the position and velocity of individual particles. (eg. Track the location of a migrating bird.) Motion is described based upon Newton's laws. Difficult to use for practical flow analysis. • Fluids are composed of billions of molecules. • Interaction between molecules hard to describe/model. Named after Italian mathematician Joseph Louis Lagrange (1736-1813).
Example
CAR surface pressure contours and streamlines
Streamtube
• Streamtube
is an imaginary tube whose boundary consists of streamlines.
• The volume flow rate
•
dr dx dy dz = = = V u v w
Streamlines
V2, b2
V1, b1
Ideal flow
Character of Streamline
1 Streamlines can not cross each other. (otherwise, the cross point will have two tangential lines.) 2 Streamline can't be a folding line, but a smooth curve. 3 Streamline cluster density reflects the magnitude of velocity. （Dense streamlines mean large velocity; while sparse streamlines mean small velocity.） ）
non-uniform velocity profile
4.2 Types of flow
Incompressible flow: liquids Compressible : gases mainly
Pressure flow-----liquids /gases in pipes Gravity flow ------free surface flow in open channels
4.3 Steady flow and Uniform flow
1. Steady uniform flow. Conditions do not change with position in the stream or with time. An example is the flow of water in a pipe of constant diameter at constant velocity. 2. Steady non-uniform flow. Conditions change from point to point in the stream but do not change with time. An example is flow in a tapering pipe with constant velocity at the inlet - velocity will change as you move along the length of the pipe toward the exit. 3. Unsteady uniform flow. At a given instant in time the conditions at every point are the same, but will change with time. 4. Unsteady non-uniform flow. Every condition of the flow may change from point to point and with time at every point.