chapter 11 response surface methods and other approaches to

鲁子问英语教学论英文版考研课后习题和答案鲁子问《英语教学论》（英文版）课后习题详解目录Chapter 1 Concepts for English Teaching in SchoolsChapter 2 ELT Methods and Approaches in and outside China Chapter 3 Elements of English Teaching in SchoolsChapter 4 Principles of English Teaching in SchoolsChapter 5 Strategies of English Teaching in SchoolsChapter 6 Instructional Design for English TeachingChapter 7 Process of English Teaching in SchoolsChapter 8 Activities of Teaching English in SchoolsChapter 9 Teaching English Language Knowledge in Schools Chapter 10 Teaching English Listening and Speaking in Schools Chapter 11 Teaching English Reading and Writing in Schools Chapter 12 Teaching English Learning Strategies in Schools Chapter 13 Teaching English Culture and Affection in Schools Chapter 14 Educational Technology and Resources for English Teac hing in SchoolsChapter 15 Assessment and Testing for English in SchoolsChapter 16 Evaluation on Teaching English in SchoolsChapter 17 Research on English Teaching in SchoolsChapter 18 Professional Development of English Teachers in School s•试看部分内容Chapter 1 Concepts for English Teaching in Schools Section 11. Based on the theories in this unit, what are the main educationalfactors that cause teacher L’s wholehearted enthusiasm to meet w ith cold indifference from his students?Key: In the first place, teaching is an interactive activity in which bo th teachers and students become more developed. Teacher L condu cts a completely exam-oriented teaching, which is boring and mund ane. He is ignorant of students’learning needs and there is no int eraction between them. Secondly, in language teaching, the more i mportant factor is students’positive and active approach to learni ng. Teacher L obviously doesn’t care about students’motivation a nd incentive; he crams learning materials and exam content in the students, regardless of students’emotional response. Lastly, teaching should be teacher-led but students-centered activity. Here teacher L takes teaching as teacher-led and exam-centered. He is putting th e cart before the horse. Only by focusing on students’learning ne eds and motivation can they perform well in exams and achieve lea rning goals.2. In your opinion, what kind of classroom teaching activity conform s to the essence of education?Key: The essence of teaching is to lead students to develop and th e teacher’s job is to help students to find answers by themselves a nd to explore language learning methods by themselves. Therefore, the teaching activity that conforms to the essence of education is a series of questions thrown to students to help deduce proper ans wers.Section 21. What do you think are the main causes for the misunderstanding in the argument “English teaching in elementary and middle schoo ls in China cannot be communicative competence oriented”? Key: It ignores the fact that language is the tool for communication and communication is the function of language. It is through inter personal communication that language remains active and vigorous. Therefore, one of the teaching goals of elementary and middle school English should be to develop student’s communicative compet ence. If communication is removed from the goals of English teachi ng, then language learning becomes a boring process of memorizat ion. There’s no fun in it. Besides, without focusing on communicati on, language learning will be far from effective, since communicatio n is the best way to learn all languages.2. After reflection on your own English study, identify what your ma in learning problems are.Key: The main learning problems may include: 1) fear of speaking E nglish, especially in public; 2) lack of motivation; 3) imbalance of fu n and homework.Section 31. What do you think is the major mistake in the viewpoint “one’s vocabulary size is the indicator of whether one’s English learning i s successful”?Key: This statement overemphasizes the role of vocabulary. It shoul d be noted that vocabulary constitutes only a part of language; the re is also grammar. Even if one has a good mastery of vocabulary and grammar, there are still culture and style to bear in mind. A su ccessful English learner should have certain awareness of culture wit h a good command of vocabulary and grammar. S/he should be ab le to adjust his or her style on different occasions; his or her knowledge of English should be able to satisfy his or her needs successfu lly.2. What do you think the essential difference between an English la nguage curriculum and an English literacy curriculum is? How do yo u understand the instrumental nature of English curriculum and the humanist nature of English curriculum in the National Curriculum S tandards for English in Schools in China (MOE, 2001)?Key: 1) The essential difference is that an English language curriculu m is to develop students’overall competence in English. Its teachi ng and learning process is to cultivate students’proficiency in the basic four skills: listening, speaking, reading and writing. By the end of the learning, students should be able to communicate effectivel y in English, have certain knowledge of English culture and develop some value and abilities. However, an English literacy curriculum is to focus on students’reading ability. The main job involved is to teach students to read and perhaps to write. The teaching objective and learning purpose is narrowed down to master a set of words; communication is absent in this curriculum.2) It’s instrumental in that it views English as a tool for communic ation. To achieve effective communication, not only vocabulary and grammar but culture is embodied in the teaching goals. Besides, it i s instrumental in that it sets English as a tool help understand oneself and the world. The job is not only to learn language but to dev elop and better oneself. It is humanist in that it concerns not only the learning of language but the development of children. Chapter 2 ELT Methods and Approaches in and outside China Section 11. Based on what you just learned, give suggestions to Miss M to help solve her problem of having nothing to teach after the second week of the term.Key: Miss M should follow certain theories in teaching. She should work out the teaching plan at the beginning of the term and adjust her teaching to the usual pace. Most importantly, she should take into consideration of students’learning realities, including questions like: how do students like her teaching method? Have students ach ieved the supposed goals after the teaching? Does her teaching me et students’present language level? Has the teaching covered less than expected or something unnecessary? She should first conduct a needs analysis of students, then works out the teaching plan base d on the needs and finally assess teaching and learning after a cert ain period.2. What do you think is the best language teaching approach or m ethod?Key: The Communicative Approach is the best language approach in that it covers the most important aspect of language learning: lan guage is learned to communicate, to exchange meaning and inform ation and to share feelings. It is the language in use that injects lif e and vitality into language and that makes it a more real existence of life. Language teaching and learning should be centered on co mmunication, which should be regarded as a proper method and th e final goal.Section 21. What is the problem with Mr. N’s complaints that the course bo ok does not explain much about grammar, does not have enough grammar exercises, and has too many activities?Key: The problem is the contradiction between the design of textbo ok and the actual assessment of teaching and learning. The design of the textbook is based on the task-based approach: students are supposed to achieve learning goals through the completion of a ser ies of tasks. The main activity involved is communication. However, Mr. N has to find lots of grammar materials outside the textbook f or students because little is mentioned in the book and what is me ntioned cannot meet the requirements of exams, which includes lots of grammar and little completion of tasks. There is certainly a gap between the textbook design and the assessment and this causesmuch challenge for both teachers and students. To bridge up the g ap, either should be adjusted to adapt to the other.2. Consider the style of a teacher you know. Do you think his/her t eaching is in line with the National Curriculum Standards? Please gi ve reasons and examples.Key: My high school English teacher’s teaching is not consistent wi th the National Curriculum Standards. In the first place, the focus of his teaching is on vocabulary and grammar. English lessons are fill ed with mechanical and meaningless drills instead of meaningful tas ks. Besides, his teaching does not allow too much communication. T hroughout the class, he spent much time explaining grammatical po ints and little time is devoted to communication. Finally, his teachin g doesn’t encourage holistic development for he was always haste ning for exams and ignoring students’learning needs. There was n o time for value-imparting or affection-influencing. All these contrad ict with the National Curriculum Standards.。

Chapter 11 Regression with a Binary Dependent Variable1) The binary dependent variable model is an example of aA) regression model, which has as a regressor, among others, a binary variable.B) model that cannot be estimated by OLS.C) limited dependent variable model.D) model where the left-hand variable is measured in base 2.Answer: C2) (Requires Appendix material) The following are examples of limited dependent variables, with the exception ofA) binary dependent variable.B) log-log specification.C) truncated regression model.D) discrete choice model.Answer: B3) In the binary dependent variable model, a predicted value of 0.6 means thatA) the most likely value the dependent variable will take on is 60 percent.B) given the values for the explanatory variables, there is a 60 percent probability that the dependent variable will equal one.C) the model makes little sense, since the dependent variable can only be 0 or 1.D) given the values for the explanatory variables, there is a 40 percent probability that the dependent variable will equal one.Answer: B4) E(Y X1, ..., X k) = Pr(Y= 1 X1,..., X k) means thatA) for a binary variable model, the predicted value from the population regression is the probability that Y=1, given X.B) dividing Y by the X's is the same as the probability of Y being the inverse of the sum of the X's.C) the exponential of Y is the same as the probability of Y happening.D) you are pretty certain that Y takes on a value of 1 given the X's.Answer: A5) The linear probability model isA) the application of the multiple regression model with a continuous left-hand side variable and a binary variable as at least one of the regressors.B) an example of probit estimation.C) another word for logit estimation.D) the application of the linear multiple regression model to a binary dependent variable.Answer: D6) In the linear probability model, the interpretation of the slope coefficient isA) the change in odds associated with a unit change in X, holding other regressors constant.B) not all that meaningful since the dependent variable is either 0 or 1.C) the change in probability that Y=1 associated with a unit change in X, holding others regressors constant.D) the response in the dependent variable to a percentage change in the regressor.Answer: C7) The following tools from multiple regression analysis carry over in a meaningful manner to the linear probability model, with the exception of theA) F-statistic.B) significance test using the t-statistic.C) 95% confidence interval using ± 1.96 times the standard error.D) regression R2.Answer: D8) (Requires material from Section 11.3 – possibly skipped) For the measure of fit in your regression model with a binary dependent variable, you can meaningfully use theA) regression R2.B) size of the regression coefficients.C) pseudo R2.D) standard error of the regression.Answer: C9) The major flaw of the linear probability model is thatA) the actuals can only be 0 and 1, but the predicted are almost always different from that.B) the regression R2 cannot be used as a measure of fit.C) people do not always make clear-cut decisions.D) the predicted values can lie above 1 and below 0.Answer: D10) The probit modelA) is the same as the logit model.B) always gives the same fit for the predicted values as the linear probability model for values between0.1 and 0.9.C) forces the predicted values to lie between 0 and 1.D) should not be used since it is too complicated.Answer: C11) The logit model derives its name fromA) the logarithmic model.B) the probit model.C) the logistic function.D) the tobit model.Answer: C12) In the probit model Pr(Y= 1=Φ(β0+β1X), ΦA) is not defined for Φ(0).B) is the standard normal cumulative distribution function.C) is set to 1.96.D) can be computed from the standard normal density function.Answer: B13) In the expression Pr(Y= 1=Φ(β0+β1X),A) (β0+β1X) plays the role of z in the cumulative standard normal distribution function.B) β1 cannot be negative since probabilities have to lie between 0 and 1.C) β0 cannot be negative since probabilities have to lie between 0 and 1.D) min (β0+β1X)> 0 since probabilities have to lie between 0 and 1.Answer: A14) In the probit model Pr(Y= 1X1, X2,..., X k) =Φ(β0+β1X1+βx X2+ ... +βk X k),A) the β's do not have a simple interpretation.B) the slopes tell you the effect of a unit increase in X on the probability of Y.C) β0 cannot be negative since probabilities have to lie between 0 and 1.D) β0 is the probability of observing Y when all X's are 0Answer: A15) In the expression Pr(deny= 1 P/I Ratio, black) =Φ(–2.26 + 2.74P/I ratio+ 0.71black), the effect ofincreasing the P/I ratio from 0.3 to 0.4 for a white personA) is 0.274 percentage points.B) is 6.1 percentage points.C) should not be interpreted without knowledge of the regression R2.D) is 2.74 percentage points.Answer: B16) The maximum likelihood estimation method produces, in general, all of the following desirable properties with the exception ofA) efficiency.B) consistency.C) normally distributed estimators in large samples.D) unbiasedness in small samples.Answer: D17) The logit model can be estimated and yields consistent estimates if you are usingA) OLS estimation.B) maximum likelihood estimation.C) differences in means between those individuals with a dependent variable equal to one and those with a dependent variable equal to zero.D) the linear probability model.Answer: B18) When having a choice of which estimator to use with a binary dependent variable, useA) probit or logit depending on which method is easiest to use in the software package at hand.B) probit for extreme values of X and the linear probability model for values in between.C) OLS (linear probability model) since it is easier to interpret.D) the estimation method which results in estimates closest to your prior expectations.Answer: A19) Nonlinear least squaresA) solves the minimization of the sum of squared predictive mistakes through sophisticated mathematical routines, essentially by trial and error methods.B) should always be used when you have nonlinear equations.C) gives you the same results as maximum likelihood estimation.D) is another name for sophisticated least squares.Answer: A20) (Requires Advanced material) Only one of the following models can be estimated by OLS:A) Y=AKαLβ+u.B) Pr(Y= 1 X) =Φ(β0+β1X)C) Pr(Y= 1 X) =F(β0+β1X) =.D) Y=AKα Lβu.Answer: D21) (Requires Advanced material) Nonlinear least squares estimators in general are notA) consistent.B) normally distributed in large samples.C) efficient.D) used in econometrics.Answer: C22) (Requires Advanced material) Maximum likelihood estimation yields the values of the coefficients thatA) minimize the sum of squared prediction errors.B) maximize the likelihood function.C) come from a probability distribution and hence have to be positive.D) are typically larger than those from OLS estimation.Answer: B23) To measure the fit of the probit model, you should:A) use the regression R2.B) plot the predicted values and see how closely they match the actuals.C) use the log of the likelihood function and compare it to the value of the likelihood function.D) use the fraction correctly predicted or the pseudo R2.Answer: D24) When estimating probit and logit models,A) the t-statistic should still be used for testing a single restriction.B) you cannot have binary variables as explanatory variables as well.C) F-statistics should not be used, since the models are nonlinear.D) it is no longer true that the 2<R2.Answer: A25) The following problems could be analyzed using probit and logit estimation with the exception of whether or notA) a college student decides to study abroad for one semester.B) being a female has an effect on earnings.C) a college student will attend a certain college after being accepted.D) applicants will default on a loan.Answer: B26) In the probit regression, the coefficient β1 indicatesA) the change in the probability of Y= 1 given a unit change in XB) the change in the probability of Y= 1 given a percent change in XC) the change in the z- value associated with a unit change in XD) none of the aboveAnswer: C27) Your textbook plots the estimated regression function produced by the probit regression of deny onP/I ratio. The estimated probit regression function has a stretched "S" shape given that the coefficient on the P/I ratio is positive. Consider a probit regression function with a negative coefficient. The shape wouldA) resemble an inverted "S" shape (for low values of X, the predicted probability of Y would approach1)B) not exist since probabilities cannot be negativeC) remain the "S" shape as with a positive slope coefficientD) would have to be estimated with a logit functionAnswer: A28) Probit coefficients are typically estimated usingA) the OLS methodB) the method of maximum likelihoodC) non-linear least squares (NLLS)D) by transforming the estimates from the linear probability modelAnswer: B29) F-statistics computed using maximum likelihood estimatorsA) cannot be used to test joint hypothesisB) are not meaningful since the entire regression R2 concept is hard to apply in this situationC) do not follow the standard F distributionD) can be used to test joint hypothesisAnswer: D30) When testing joint hypothesis, you can useA) the F- statisticB) the chi-squared statisticC) either the F-statistic or the chi-square statisticD) none of the aboveAnswer: C。

电路原理专业词汇表Glossary of “Principles of Electric Circuits”Chapter 1 Elements and Laws of Electrical Circuits 电路electrical circuit电流current电荷electric charge电压voltage电位potential电位差potential difference电动势electromotive force功率power能量energy电阻resistor / resistance电导conductor / conductance电感inductor / inductance电容capacitor / capacitance欧姆定律Ohm’s Law广义欧姆定律generalized Ohm’s Law参考方向reference direction电压极性voltage polarity正极positive polarity负极negative polarity理想独立电压源ideal independent voltage source理想独立电流源ideal independent current source理想受控源ideal dependent / controlled source压控电压源voltage controlled voltage source(VCVS)压控电流源voltage controlled current source(VCCS)流控电压源current controlled voltage source(CCVS)流控电流源current controlled current source(CCCS)节点node支路branch回路loop基尔霍夫定律Kirchhoff’s Law基尔霍夫电流定律Kirchhoff’s Current Law(KCL)基尔霍夫电压定律Kirchhoff’s Voltage Law(KVL)闭合面closed boundary集总参数lumped parameter集总参数电路lumped circuit集总参数元件lumped element分布参数distributed parameter分布参数电路distributed circuit直流direct current(DC)交流alternating current(AC)有源器件active element无源器件passive element无损电路lossless circuitChapter 2 Analysis methods to simple resistorcircuits串联series connection分压voltage division并联parallel connection分流current division等效电阻equivalent resistanceY-Δ变换Wye-Delta transformation入端电阻input resistanceChapter 3 Methods of Analysis支路电流法method of branch current节点法Nodal Analysis回路电流法loop current method网孔电流法mesh current method外网孔outer mesh自导纳self-admittance互导纳mutual-admittance矩阵matrix行row列column参考节点reference node平面电路planar circuit方程equation消去法elimination technique克莱姆法则Cr amer’s rule代入法substitution method运算放大器operational amplifier(op amp)同向输入端noninverting input反向输入端inverting input输出端output等效电路模型equivalent circuit model开环放大倍数open-loop gain闭环放大倍数closed-loop gain入端电阻input resistance输出电阻output resistance线性工作区linear region正向饱和区positive saturation反向饱和区negative saturation同向放大noninverting amplifier反向放大inverting amplifier加法器summing amplifier积分器integrator微分器differentiator自激振荡self-sustained oscillationChapter 4 Circuit Theorems叠加原理superposition principle输入/激励input / excitation输出/响应output / response线性电路linear circuit代数和algebraic sum替代定理substitution principle戴维南定理Thevenin’s Theorem诺顿定理Norton’s Theorem二端网络two-terminal circuit开路电压open-circuit voltage短路电流short-circuit current特勒根定理Tellegen Theorem功率平衡定理Power-balancing Theorem互易定理reciprocal theorem对偶原理principle of duality对偶元件dual element对偶图dual graphChapter 5 Nonlinear Circuit非线性电路nonlinear circuit非线性元件nonlinear element压控电阻voltage-controlled resistor流控电阻current-controlled resistor静态电阻static resistance动态电阻dynamic resistance小信号分析small-signal analysis小信号模型small-signal modal分段线性化法piece-wise linear mthod数值解法numerical analysisChapter 6 First-order Circuit一阶电路first-order circuit一阶微分方程first-order differential equation 过渡过程transient process线性时不变电路linear time-invariable circuit 单位阶跃函数unit step function单位脉冲函数unit pulse function单位斜坡函数unit ramp function起始条件initial condition起始值initial value零输入响应zero-input response零状态响应zero-state response稳态响应steady-state response暂态响应transient response时间常数time constant指数函数exponential function阶跃响应step response冲激响应impulse response自由响应natural response强迫响应forced response全响应complete response稳态值final value卷积积分convolution integration时域延迟time delay换路switching跳变现象jump phenomenon脉冲持续时间pulse duration脉冲重复周期repeating period of pulseChapter 7 Second-order Circuit二阶电路second-order circuit齐次微分方程homogeneous differential equation常系数微分方程constant coefficients equation特征方程characteristic equation特征根characteristic root特征值eigenvalue特征向量eigenvector特解particular solution通解general solution自然频率natural frequency衰减系数damping factor谐振角频率resonant frequency / undamped natural frequency 过阻尼情况overdamped case欠阻尼情况underdamped case临界情况critically damped case固有振荡角频率damping frequency / damped natural frequency 衰减振荡damped oscillation无损lossless正弦响应sinusoidal response波形waveform实数real复数complex衰减attenuationChapter 8 Sinusoidal Steady-State Analysis幅值amplitude / magnitude相位phase相位差phase difference角频率angular frequency周期period频率cyclic frequency正弦sinusoidal余弦cosine初相角initial phase angle瞬时值instantaneous value最大值maximum有效值effective valueroot-mean-square valueu 领先i φu leads i by φu 落后i φu lags i by φ同相in phase反相opposite in phase实部real part虚部imaginary part直角坐标形式rectangular form极坐标形式polar form指数形式exponential form相量phasor参考相量reference phasor电压三角形voltage triangle瞬时功率instantaneous power平均功率average power阻抗impedance导纳admittance电抗reactance电纳susceptance感性inductive容性capacitive正弦稳态响应sinusoidal steady-state response时域time-domain相量域phasor-domain视在功率apparent power功率因数power factor (pf)复功率complex power功率三角形power triangle复共轭complex conjugate有功功率active power无功功率reactive power最大功率传输定理Maximum Power Transfer Theorem功率守恒定理Theorem of conservation of power阻抗匹配impedance matching共轭匹配conjugate matchingChapter 9 Magnetically Coupled Circuits 耦合couple互感mutual inductance自感self-inductance磁通magnetic flux互感电压mutual / induced voltage线圈coil铁心线圈coil with iron core匝数turn耦合系数coupling coefficient变压器transformer空心变压器air-core transformer原边primary coils / windings副边secondary coils / windings引入阻抗reflected impendence理想变压器ideal transformer全耦合变压器unity-coupled transformer 变比turns ratio / transformation ratio自耦合变压器auto-transformer多绕组变压器multiple-winding transformer 右螺旋定则right-handed screw rule同名端dotted terminalterminals of same magnetic polarity 漏感leakage inductanceChapter 10 Resonance串联谐振series resonance并联谐振parallel resonance谐振频率resonant frequency特性阻抗characteristic impedance品质因数quality factor频率响应frequency response选择性selectivity选频特性frequency-selection characteristic Chapter 11 Frequency Response复频率complex frequency网络函数network function转移函数transfer function多项式polynomial极点pole零点zero波特图Bode plot分贝decibel增益gain对数logarithm半对数semilog转折频率corner / break frequency截止频率cut-off frequency带宽bandwidth无源滤波器passive filter有源滤波器active filter低通滤波器low-pass filter高通滤波器high-pass filter带通滤波器band-pass filter带阻滤波器band-stop / band-reject / notch filter Chapter 12 Three-phase Circuits对称三相电源balanced three-phase sources 对称三相电路symmetrical three-phase circuit中线neutral line中性点neutral point三相四线制three-phase four-wire system相电压phase voltage线电压line voltage相序phase sequence正序positive / abc sequence负序negative / acb sequence相电流phase current线电流line currentChapter 13 Steady-State Response of PeriodicExcitation周期性非正弦激励nonsinusoidal periodic excitation三角形式的付里叶级数trigonometric Fourier series指数形式的付里叶级数exponential Fourier series付里叶系数Fourier coefficient基波fundamental harmonic基波频率fundamental frequency谐波harmonic wave高次谐波higher harmonic频谱frequency spectrum谱线spectrum line线状频谱line spectrum奇次odd偶次even奇对称odd symmetry偶对称even symmetry半波对称half-wave symmetry帕斯瓦尔定理Parseval’s theoremChapter 14 Fourier Transformation andLaplace Transformation付里叶变换Fourier transformation拉普拉斯变换Laplace transformation原函数original function象函数transform function积分变换integral transformation频域frequency domain幅度谱amplitude spectrum相位谱phase spectrum矩形脉冲rectangular pulse线性性质linearity时域微分time differentiation时域积分time integration时域平移time shift频域平移frequency shift拉普拉斯反变换inverse Laplace transformation 拉普拉斯变换对Laplace pairsChapter 15 Two-port Networks端口port二端口网络two-port network四端网络four-terminal network / quadripole Z参数impedance parametersY参数admittance parametersH参数Hybrid parametersT参数Transmission parameters策动点driving point(二端口)级联cascade connection传播常数transmission constantChapter 16 Basis of Network Graph Theory 图graph拓扑图topological graph子图subgraph连通图connected graph有向图oriented graph树tree树支tree branch连支link割集cut set降阶关联矩阵reduced incidence matrix增广矩阵augmented matrix秩rank基本回路矩阵fundamental loop matrix基本割集矩阵fundamental cut set matrix单位阵unit matrix转置阵transposed matrix正定矩阵positive definite matrix非奇异矩阵nonsingular matrix逆矩阵inverse matrix方阵square matrix零矩阵zero matrix行列式determinantChapter 17 State Variables Approach状态变量state variable状态方程state equation状态空间state space列向量column vector特征值characteristic value特征向量characteristic vector特征方程characteristic equation相似矩阵similar matrixChapter 18 Nonlinear Dynamic Circuits非线性时变电路nonlinear time-varying circuit自治电路非自治电路前向欧拉法forward Eular’s method后向欧拉法backward Eular’s method相平面状态平面state planar相轨线中心点焦点节点鞍点平衡点稳定性stability渐近稳定asymptotic stabilityChapter 19 Distributed Circuits分布参数电路distributed circuit传输线transmission line均匀传输线uniform transmission line 反射reflection透射transmission波长wave length波速wave speed行波traveling wave驻波standing wave正向行波direct wave反向行波returning wave波阻抗wave impedance波前wave front传播常数propagation constant Appendix Magnetic Circuit磁路magnetic circuit铁磁物质ferromagnetic substance磁导率magnetic permeability磁感应强度magnetic induction磁通magnetic flux磁链magnetic linkage磁通势magnetomotive force磁通密度magnetic flux density磁通连续性定理principle of continuity of magnetic flux 磁场强度magnetic flux intensity磁阻reluctance磁导permeance安培环路定理principle of Ampere loop circuit磁化曲线magnetization curve磁滞回线hysteresis loop磁滞hysteresis涡流eddy current涡流损失eddy current loss集肤效应skin effect漏磁通leakage flux磁饱和magnetic saturation电磁感应定律law of electromagnetic induction励磁电流exciting current《电工学上》中英名词对照表一阶电路first-order circuitV形曲线V curve三相电路three-phase circuit三相功率three-phase power三相三线制three-phase three-wire system三相四线制three-phase four-wire system三相变压器three-phase transformer三角形联接trianular connection三角波triangular wave三相异步电动机three-phase induction motor 支路branch支路电流法branch current method中性点neutral point中性线neutral conductor中央处理器centre processing unit〔CPU〕互感mutual inductance介电常数permittivity of the dielectric瓦特Watt功率表powermeter无功功率reactive power韦伯Weber反电动势counter emf反相opposite in phase反馈控制feedback control方框图block diagram开路open circuit开关switch水轮发电机water-wheel generator功work功率power功率因数power factor功率三角形power triangle功率角power angle电能electric energy 电荷electric charge电场electric field电场强度electric field intensity电位electric potential电位差electric potential difference 电位升potential rise电位降potential drop电位计potentiometer电压voltage电压三角形voltage triangle电动势electromotive force〔emf〕电源source电压源voltage source电流源current source电路circuit电路分析circuit analysis电路元件circuit element电路模型circuit model电流current电流密度current density电流互感器current transformer电阻resistance电阻器resistor电阻性电路resistive circuit电阻率resistivity电导conductance电导率conductivity电容capacitance电容器capacitor电容性电路capacitive circuit电感inductance电感器inductor电感性电路inductive circuit电桥bridge电机electric machine电磁转矩electromagnetic torque电角度electrical degree电枢armature电枢反应armature reaction电工测量electrical measurement电磁式仪表electromagnetic instrument电动式仪表electrodynamic instrument平均值average value平均功率average power正极positive pole正方向positive direction正弦量sinusoid正弦电流sinusoidal current结点node结点电压法node voltage method对称三相电路symmetrical three-phase circuit 主磁通main flux外特性external characteristic发送机transmitter他励发电机separately excited generator可编程控制器programmable controller〔PLC〕安培Ampere电流表currenter安匝ampere-turns伏特V olt电压表valeage伏安特性曲线volt-ampere characteristic有效值effective value有功功率active power交流电路alternating current circuit (a-ccircuit) 交流电机alternating-current machine自感self-inductance自感电动势self-induced emf自耦变压器autotransformer自励发电机self-excited generator自整角机selsyns 自动控制automatic control自动调节automatic regulation自锁self-locking负极negative pole负载load负载线load line负反馈negative feedback动态电阻dynamic resistance并联parallel connection并联谐振parallel resonance并励发电机shunt d-c generator并励电动机shunt d-c motor并励绕组shunt field vending同步发电机synchronous generator同步电动机synchronous motor同步转速synchronous speed同相in phase机械特性torque-speed characteristic过励overexcitation执行元件servo-unit传递函数transfer function传感器transducer闭环控制closed loop control回路loop网络network导体conductor导纳admittance阶跃电压step voltage全电流定律law of total current全响应complete response麦克斯韦Maxwell基尔霍失电流定律Kirchhof f’s current law 〔KCL〕基尔霍失电压定律Kirchhof’s voltage law〔KVL〕库仑Coulomb亨利Henry角频率angular frequency串联series connection串联谐振series resonance串励绕组series field winding阻抗impedance阻抗三角形impedance triangle阻转矩counter torque初相位initial phase时间常数time constant时域分析time domain analysis时间继电器time-delay relay励磁电流exciting current励磁机exciter励磁绕组field winding励磁电流exciting current励磁变阻器field rheostat两相异步电动机two-phase induction motor 两功率表法two-powermeter method伺服电动机servomotor步进电动机stepping motor步距角stepangle汽轮发电机turboalternator直流电路direct current circuit (d-c cir-cuit) 直流电机direct-current machine法拉Farad空载no-load空载特性open-circuit characteristic空气隙air gap非线性电阻nonlinear resistance非正弦周期电流nonsinusoidal periodic受控电源controlled source变压器transformer变比ration of transformation变阻器rheostat线电压line voltage线电流line current线圈coil线性电阻linear resistance 周期period参考电位reference potential参数parameter视在功率apparent power定子stator转子rotor转子电流rotor current转差率slip转速speed转矩torque组合开关switchgroup制动braking单相异步电动机single-phase induction motor 相phase相电压phase voltage相电流phase current相位差phase difference相位角phase angle相序phase sequence相量phasor相量图phasor diagram响应response星形联接star connection复数complex number阻抗impedance导纳admittance复励发电机compound d-c generator欧姆Ohm欧姆定律Ohm's law等效电路equivalent circuit品质因数quality factor绝缘insulation绝缘体insulator显极转子salient poles rotor测速发电机tachometer generator绕组winding绕线式转子wound rotor起动starting起动电流starting current起动转矩starting torque起动按钮start button容抗capacitive reactance容纳capacitive susceptance诺顿定理Norton's theorem高斯Gauss原动机prime mover原绕组primary winding铁心core铁损core loss矩形波rectangular wave特征方程characteristic equation积分电路integrating circuit效率efficiency振荡放电oscill tory discharge继电器relay热继电器thermal overload relay〔OLR〕换向器commutator调节特性regulating characteristic调速speed regulation继电接触器控制relay-contactor control 副绕组secondary winding铜损copper loss基波fundamental harmonic谐波harmonic谐振频率resonant frequency通频带bandwidth理想电压源ideal voltage source理想电流源ideal current source减幅振荡attenuated oscillation常开触点normally open contact常闭触点normally closed contact停止stopping停止按钮stop button接收机receiver 接触器contactor控制电动机control motor控制电路control circuit旋转磁场rotating magnetic field隐极转子nonsalient poles rotor涡流eddy current涡流损耗eddy-current loss焦耳Joule奥斯特Oersted短路short circuit锯齿波sawtooth wave幅值amplitude最大值maximum value最大转矩maximum〔breakdown〕torque 滞后lag超前lead傅里叶级数Fourier series暂态transient state暂态分量transient component等幅振荡unattenuated oscillation联锁interlocking感抗inductive reactance感纳inductive susceptance感应电动势induced emf楞次定则Lenz's law频率frequency频域分析frequency domain analysis频谱spectrum输入input输出output微法microfarad微分电路differentiating circuit叠加原理superposition theorem零状态响应zero-state response零输入响应zero-input response罩极式电动机shaded-pole motor滑环slip ring鼠笼式转子squirrel-cage rotor截止角频率cutoff angular frequency 滤波器filters磁场magnetic field磁场强度magnetizing farce磁路magnetic circuit磁通flux磁感应强度flux density磁通势magnetomotive force〔mmf〕磁阻reluctance磁导率permeability磁化magnetization磁化曲线magnetization curve磁滞hysteresis磁滞回线hysteresis loop磁滞损耗hysteresis loss磁极pol磁电式仪表magnetoelectric instrument 漏磁通leakage flux漏磁电感leakage inductance漏磁电动势leakage emf赫兹Hertz稳态steady state稳态分量steady state component静态电阻static resistance碳刷carbon brush额定值rated value额定rated voltage额定功率rated power额定转矩tated torque瞬时值instantaneous value戴维宁定理Thevenin's theorem激励excitation满载full load槽fuse熔断器fuse《电工学下》中英名词对照表二画PN结PN junctionP型半导体P-type semiconductorJK触发器JK flip-flopD触发器 D flip-flop二极管diode二进制binary system二进制计数器binary counter十进制decimal system十进制计数器decimal counter二—十进制binary coded decimal system〔BCD〕三画RC选频网络RC selection frequency networkRS触发器RS flip-flopN型半导体N-type semiconductorN沟道N-channel门电路gate circuit三态逻辑门tri-state logic gate三相整流器three-phase rectifier工作点operating point干扰interference上升沿rise edge下降沿fall edge四画方框图block diagram双稳态触发器bistable flip-flop无稳态触发器astable flip-flop无输出变压器功率放大器output transformerless〔OTL〕power amplifier 无输出电容器功率放大器output capacitorless〔OCL〕power amplifier反向电阻backward resistance反向偏置backward bias反向击穿reverse breakdown反相器inverter反馈feedback反馈系数feedback coefficient互补对称功率放大器complementary symmetry power amplifier少数载流子minority carrier 分立电路discrete circuit分贝decibel〔DB〕分频frequency division分辨率resolution开启电压threshold voltage开关型直流电源switching mode direct power supply计数器counter与门AND gate与非门NAND gate与或非门and-or-invert〔AOI〕gate卡诺图Karnaugh map五画电感滤波器inductance filter电容滤波器capacitor filter电流放大系数current amplification coefficient电压放大器voltage amplifier电压放大倍数voltage gain电压比较器voltage comparator主从型触发器master-slave flip-flop失真distortion只读存储器read only memory〔ROM〕可编程逻辑器件programmable logic device〔PLD〕可关断晶闸管gate turn-off thyristor 〔GTO〕功率放大器power amplifier功率晶体管giant transistor〔GTR〕正向电阻forward resistance正向偏置forward bias正反馈positive feedback正弦波振荡器sinusoidal oscillator正逻辑positive logic击穿breakdown占空比duty ratio加法器adder发射极emitter发光二极管light- emitting diode〔LED〕布尔代数Boolean algebra半波可控整流half -wave controlled rectifier半波整流器half -wave rectifier半加器half-adder半导体semiconductor本征半导体intrinsic semiconductor失调电压offset voltage失调电流offset current平均延迟时间average delay time六画共模信号common-mode signal共模输入common-mode input共模抑制比common-mode rejection ratio 〔CMRR〕共发射极接法common-emitter configuration共价键covalent bond动态dynamics杂质impurity伏安特性volt-ampere characteristics扩散diffusion全波整流器biphase〔full –wave〕rectifier 全波可控整流biphase controlled rectifier 全加器full adder全局布线区global routing pool〔GRP〕负反馈negative feedback负载电阻load resistance负载线load line负电阻negative resistance负逻辑negative logic夹断电压pinch-off voltage多级放大器multistage amplifier多数载流子majority carrier多谐振荡器astable multivibrator自由电子free electron自激振荡器self-excited oscillator自偏压self-bias导通on导电沟道conductive在系统可编程in system programmable 〔ISP〕异或门exclusive-OR gate异步二进制计数器asynchronous binary counter同步二进制计数器synchronous binary counter同或门exclusive-NOR gate发光二极管light- emitting diode〔LED〕场效晶体管field-effect transistor〔FET〕光敏电阻photo-sensitive resistor光电二极管photodiode光电晶体管phototransistor 光电藕合器photocoupler传输门transmission gate〔TG〕传输特性transfer characteristics七画运算放大器operational amplifier低频放大器low-frequency amplifier时钟脉冲clock pulse时序逻辑电路sequential logic circuit谷点valley point译码器decipherer阻容—耦合放大器resistance-capacitance coupled amplifier阻断interception阻挡层barrier采样保持sample and hold串联型稳压电源series voltage rgulator八画空穴hole空间电荷区space-charge layer固定偏置fixed-bias直接耦合放大器direct- coupled amplifier 单稳态触发器monostable flip-flop单结晶体管unijuction transistor〔UJT〕金属—氧化物—半导体metal-oxide-semiconductor〔MOS〕非门NOT gate非线性失真nonlinear diatortion或门OR gate或非门NOR gate饱和saturation转移特性transfer characteristic定时器timer参数parameter参考电压reference voltage组合逻辑电路combinational logic circuit九画穿透电流penetration current复合recombination复合晶体管Darlington复位reset差放放大器differential amplifier差模信号differential-mode signal差模输人differential-mode input绝缘栅双极型晶体管insulated gate bipolar transistor〔IGBT〕绝缘栅场效晶体管isolated-gatefield-effect transistor〔IGFET〕栅极gate，grid恒流源constant current source通用逻辑块generic logic block〔GLB〕通用阵列逻辑generic array logic〔GAL〕脉冲pulse脉冲宽度pulse width脉冲幅度pulse amplitude脉冲周期pulse period脉冲前沿pulse leading edge脉冲后沿pulse trailing edge十画桥式整流器bridge rectifier旁路电容bypass capacitor射极输出器emitter follower振荡器oscillator振荡频率oscillation frequency耗尽层depletion layer耗尽型MOS场效晶体管depletion mode MOSFET载流子carrier硅silicon硅稳压二极管Zener diode峰点peak point热敏电阻thermistor十一画逻辑门1ogic gates逻辑电路1ogic circuit基极base控制极control grid偏流current bias偏置电路biasing circuit接地ground，grounding；earth，earthing 虚地imaginary ground维持电流holding current基本RS触发器basic RS flip-flop随机存取存储器random access memory 〔RAM〕寄存器register移位寄存器shift register清零clear掺杂半导体doped semiconductor十二画晶体crstal晶体管transistor晶体管—晶体管逻辑电路transistor- transistor logic 〔TTL〕circuit编码coding晶闸管thyristor集成电路integrated circuit〔IC〕集电极collector幅频特性amplitude frequency-response characteristic编码器encoder最小项miniterm十三画源极sourse滤波器filter数字电路digital circuit数字集成电路digital integrated circuit数码显示digital display数—模转换器digital-analog converter 〔DAC〕数据选择器multiplexer数据分配器demultiplexer锗germanium输入输出单元input output cell〔IOC〕输入电阻input resistance输出电阻output resistance输出布线区output routing pool〔ORP〕输出逻辑宏单元output logic macro cell 〔OLMC〕零点漂移zero drift跨导transconductance触发器flip-flop十四画截止cut-off漂移drift静态statics静态工作点quiescent point漏极drain模—数转换器analog - digital converter 〔ADC〕模拟电路analog circuit稳压二极管Zener diode十五画整流电路rectifier circuit增强型MOS场效晶体管enhancement mode MOSFET。

The FLUENT User's Guide tells you what you need to know to use FLUENT. At the end of the User's Guide, you will find a Reference Guide, a nomenclature list, a bibliography, and an index.!! Under U.S. and international copyright law, Fluent is unable to distribute copies of the papers listed in the bibliography, other than those published internally by Fluent. Please use your library or a document delivery service to obtain copies of copyrighted papers.A brief description of what's in each chapter follows:•Chapter 1, Getting Started, describes the capabilities of FLUENT and the way in which it interacts with other Fluent Inc. and third-party programs. It also advises you on how to choose the appropriate solverformulation for your application, gives an overview of the problem setup steps, and presents a samplesession that you can work through at your own pace. Finally, this chapter provides information aboutaccessing the FLUENT manuals on CD-ROM or in the installation area.•Chapter 2, User Interface, describes the mechanics of using the graphical user interface, the text interface, and the on-line help. It also provides instructions for remote and batch execution. (See the separate Text Command List for information about specific text interface commands.)•Chapter 3, Reading and Writing Files, contains information about the files that FLUENT can read and write, including hardcopy files.•Chapter 4, Unit Systems, describes how to use the standard and custom unit systems available in FLUENT.•Chapter 5, Reading and Manipulating Grids, describes the various sources of computational grids and explains how to obtain diagnostic information about the grid and how to modify it by scaling, translating, and other methods. This chapter also contains information about the use of non-conformal grids.•Chapter 6, Boundary Conditions, explains the different types of boundary conditions available in FLUENT, when to use them, how to define them, and how to define boundary profiles and volumetric sources and fix the value of a variable in a particular region. It also contains information about porousmedia and lumped parameter models.•Chapter 7, Physical Properties, explains how to define the physical properties of materials and the equations that FLUENT uses to compute the properties from the information that you input.•Chapter 8, Modeling Basic Fluid Flow, describes the governing equations and physical models used by FLUENT to compute fluid flow (including periodic flow, swirling and rotating flows, compressibleflows, and inviscid flows), as well as the inputs you need to provide to use these models.•Chapter 9, Modeling Flows in Moving Zones, describes the use of single rotating reference frames, multiple moving reference frames, mixing planes, and sliding meshes in FLUENT.•Chapter 10, Modeling Turbulence, describes FLUENT's models for turbulent flow and when and how to use them.•Chapter 11, Modeling Heat Transfer, describes the physical models used by FLUENT to compute heat transfer (including convective and conductive heat transfer, natural convection, radiative heat transfer,and periodic heat transfer), as well as the inputs you need to provide to use these models.•Chapter 12, Introduction to Modeling Species Transport and Reacting Flows, provides an overview of the models available in FLUENT for species transport and reactions, as well as guidelines for selectingan appropriate model for your application.•Chapter 13, Modeling Species Transport and Finite-Rate Chemistry, describes the finite-rate chemistry models in FLUENT and how to use them. This chapter also provides information about modeling species transport in non-reacting flows.•Chapter 14, Modeling Non-Premixed Combustion, describes the non-premixed combustion model and how to use it. This chapter includes details about using prePDF.•Chapter 15, Modeling Premixed Combustion, describes the premixed combustion model and how to use it.•Chapter 16, Modeling Partially Premixed Combustion, describes the partially premixed combustion model and how to use it.•Chapter 17, Modeling Pollutant Formation, describes the models for the formation of NOx and soot and how to use them.•Chapter 18, Introduction to Modeling Multiphase Flows, provides an overview of the models for multiphase flow (including the discrete phase, VOF, mixture, and Eulerian models), as well as guidelines for selecting an appropriate model for your application.•Chapter 19, Discrete Phase Models, describes the discrete phase models available in FLUENT and how to use them.•Chapter 20, General Multiphase Models, describes the general multiphase models available in FLUENT (VOF, mixture, and Eulerian) and how to use them.•Chapter 21, Modeling Solidification and Melting, describes FLUENT's model for solidification and melting and how to use it.•Chapter 22, Using the Solver, describes the FLUENT solvers and how to use them.•Chapter 23, Grid Adaption, explains the solution-adaptive mesh refinement feature in FLUENT and how to use it.•Chapter 24, Creating Surfaces for Displaying and Reporting Data, explains how to create surfaces in the domain on which you can examine FLUENT solution data.•Chapter 25, Graphics and Visualization, describes the graphics tools that you can use to examine your FLUENT solution.•Chapter 26, Alphanumeric Reporting, describes how to obtain reports of fluxes, forces, surface integrals, and other solution data.•Chapter 27, Field Function Definitions, defines the flow variables that appear in the variable selection drop-down lists in FLUENT panels, and tells you how to create your own custom field functions. •Chapter 28, Parallel Processing, explains the parallel processing features in FLUENT and how to use them. This chapter also provides information about partitioning your grid for parallel processing.18. Introduction to Modeling Multiphase FlowsA large number of flows encountered in nature and technology are a mixture of phases. Physical phases of matter are gas, liquid, and solid, but the concept of phase in a multiphase flow system is applied in a broader sense. In multiphase flow, a phase can be defined as an identifiable class of material that has a particular inertial response to and interaction with the flow and the potential field in which it is immersed. For example, different-sized solid particles of the same material can be treated as different phases because each collection of particles with the same size will have a similar dynamical response to the flow field.This chapter provides an overview of multiphase modeling in FLUENT, and Chapters 19 and 20 provide details about the multiphase models mentioned here. Chapter 21 provides information about melting and solidification.18.1 Multiphase Flow RegimesMultiphase flow can be classified by the following regimes, grouped into four categories:gas-liquid or liquid-liquid flowsbubbly flow: discrete gaseous or fluid bubbles in a continuous fluiddroplet flow: discrete fluid droplets in a continuous gasslug flow: large bubbles in a continuous fluidstratified/free-surface flow: immiscible fluids separated by a clearly-defined interfacegas-solid flowsparticle-laden flow: discrete solid particles in a continuous gaspneumatic transport: flow pattern depends on factors such as solid loading, Reynolds numbers, and particle properties. Typical patterns are dune flow, slug flow, packed beds, and homogeneous flow.fluidized beds: consist of a vertical cylinder containing particles where gas is introduced through a distributor. The gas rising through the bed suspends the particles. Depending on the gas flow rate, bubbles appear and rise through the bed, intensifying the mixing within the bed.liquid-solid flowsslurry flow: transport of particles in liquids. The fundamental behavior of liquid-solid flows varies with the properties of the solid particles relative to those of the liquid. In slurry flows, the Stokes number (seeEquation 18.4-4) is normally less than 1. When the Stokes number is larger than 1, the characteristic of the flow is liquid-solid fluidization.hydrotransport: densely-distributed solid particles in a continuous liquidsedimentation: a tall column initially containing a uniform dispersed mixture of particles. At the bottom, the particles will slow down and form a sludge layer. At the top, a clear interface will appear, and in the middle a constant settling zone will exist.three-phase flows (combinations of the others listed above)Each of these flow regimes is illustrated in Figure 18.1.1.Figure 18.1.1: Multiphase Flow Regimes18.2 Examples of Multiphase SystemsSpecific examples of each regime described in Section 18.1 are listed below:Bubbly flow examples: absorbers, aeration, air lift pumps, cavitation, evaporators, flotation, scrubbersDroplet flow examples: absorbers, atomizers, combustors, cryogenic pumping, dryers, evaporation, gas cooling, scrubbersSlug flow examples: large bubble motion in pipes or tanksStratified/free-surface flow examples: sloshing in offshore separator devices, boiling and condensation in nuclear reactorsParticle-laden flow examples: cyclone separators, air classifiers, dust collectors, and dust-laden environmental flowsPneumatic transport examples: transport of cement, grains, and metal powdersFluidized bed examples: fluidized bed reactors, circulating fluidized bedsSlurry flow examples: slurry transport, mineral processingHydrotransport examples: mineral processing, biomedical and physiochemical fluid systemsSedimentation examples: mineral processing18.3 Approaches to Multiphase ModelingAdvances in computational fluid mechanics have provided the basis for further insight into the dynamics of multiphase flows. Currently there are two approaches for the numerical calculation of multiphase flows: the Euler-Lagrange approach and the Euler-Euler approach.18.3.1 The Euler-Lagrange ApproachThe Lagrangian discrete phase model in FLUENT (described in Chapter 19) follows the Euler-Lagrange approach. The fluid phase is treated as a continuum by solving the time-averaged Navier-Stokes equations, while the dispersed phase is solved by tracking a large number of particles, bubbles, or droplets through the calculated flow field. The dispersed phase can exchange momentum, mass, and energy with the fluid phase.A fundamental assumption made in this model is that the dispersed second phase occupies a low volume fraction, even though high mass loading ( ) is acceptable. The particle or droplet trajectories are computed individually at specified intervals during the fluid phase calculation. This makes the model appropriate for the modeling of spray dryers, coal and liquid fuel combustion, and some particle-laden flows, but inappropriate for the modeling of liquid-liquid mixtures, fluidized beds, or any application where the volume fraction of the second phase is not negligible.18.3.2 The Euler-Euler ApproachIn the Euler-Euler approach, the different phases are treated mathematically as interpenetrating continua. Since the volume of a phase cannot be occupied by the other phases, the concept of phasic volume fraction is introduced. These volume fractions are assumed to be continuous functions of space and time and their sum is equal to one. Conservation equations for each phase are derived to obtain a set of equations, which have similar structure for all phases. These equations are closed by providing constitutive relations that are obtained from empirical information, or, in the case of granular flows , by application of kinetic theory.In FLUENT, three different Euler-Euler multiphase models are available: the volume of fluid (VOF) model, the mixture model, and the Eulerian model.The VOF ModelThe VOF model (described in Section 20.2) is a surface-tracking technique applied to a fixed Eulerian mesh. It is designed for two or more immiscible fluids where the position of the interface between the fluids is of interest. In the VOF model, a single set of momentum equations is shared by the fluids, and the volume fraction of each of the fluids in each computational cell is tracked throughout the domain. Applications of the VOF model include stratified flows , free-surface flows, filling, sloshing , the motion of large bubbles in a liquid, the motion of liquid after a dam break, the prediction of jet breakup (surface tension), and the steady or transient tracking of any liquid-gas interface.The Mixture ModelThe mixture model (described in Section 20.3) is designed for two or more phases (fluid or particulate). As in the Eulerian model, the phases are treated as interpenetrating continua. The mixture model solves for the mixture momentum equation and prescribes relative velocities to describe the dispersed phases. Applications of the mixture model include particle-laden flows with low loading, bubbly flows, sedimentation , and cyclone separators. The mixture model can also be used without relative velocities for the dispersed phases to model homogeneous multiphase flow.The Eulerian ModelThe Eulerian model (described in Section 20.4) is the most complex of the multiphase models in FLUENT. It solves a set of n momentum and continuity equations for each phase. Coupling is achieved through the pressure and interphase exchange coefficients. The manner in which this coupling is handled depends upon the type of phases involved; granular (fluid-solid) flows are handled differently than non-granular (fluid-fluid) flows. For granular flows , the properties are obtained from application of kinetic theory. Momentum exchange between the phases is also dependent upon the type of mixture being modeled. FLUENT's user-defined functions allow you tocustomize the calculation of the momentum exchange. Applications of the Eulerian multiphase model include bubble columns , risers , particle suspension, and fluidized beds .18.4 Choosing a Multiphase ModelThe first step in solving any multiphase problem is to determine which of the regimes described inSection 18.1 best represents your flow. Section 18.4.1 provides some broad guidelines for determining appropriate models for each regime, and Section 18.4.2 provides details about how to determine the degree of interphase coupling for flows involving bubbles, droplets, or particles, and the appropriate model for different amounts of coupling.18.4.1 General GuidelinesIn general, once you have determined the flow regime that best represents your multiphase system, you can select the appropriate model based on the following guidelines. Additional details and guidelines for selecting the appropriate model for flows involving bubbles, droplets, or particles can be found in Section 18.4.2.For bubbly, droplet, and particle-laden flows in which the dispersed-phase volume fractions are less than or equal to 10%, use the discrete phase model. See Chapter 19 for more information about the discrete phase model.For bubbly, droplet, and particle-laden flows in which the phases mix and/or dispersed-phase volume fractions exceed 10%, use either the mixture model (described in Section 20.3) or the Eulerian model (described in Section 20.4). See Sections 18.4.2 and 20.1 for details about how to determine which is more appropriate for your case.For slug flows, use the VOF model. See Section 20.2 for more information about the VOF model.For stratified/free-surface flows, use the VOF model. See Section 20.2 for more information about the VOF model.For pneumatic transport, use the mixture model for homogeneous flow (described in Section 20.3) or the Eulerian model for granular flow (described in Section 20.4). See Sections 18.4.2 and 20.1 for details about how to determine which is more appropriate for your case.For fluidized beds, use the Eulerian model for granular flow. See Section 20.4 for more information about the Eulerian model.For slurry flows and hydrotransport , use the mixture or Eulerian model (described, respectively, inSections 20.3 and 20.4). See Sections 18.4.2 and 20.1 for details about how to determine which is more appropriate for your case.For sedimentation, use the Eulerian model. See Section 20.4 for more information about the Eulerian model.For general, complex multiphase flows that involve multiple flow regimes, select the aspect of the flow that is of most interest, and choose the model that is most appropriate for that aspect of the flow. Note that the accuracy of results will not be as good as for flows that involve just one flow regime, since the model you use will be valid for only part of the flow you are modeling.18.4.2 Detailed GuidelinesFor stratified and slug flows, the choice of the VOF model, as indicated in Section 18.4.1, is straightforward. Choosing a model for the other types of flows is less straightforward. As a general guide, there are some parameters that help to identify the appropriate multiphase model for these other flows: the particulate loading, , and the Stokes number, St. (Note that the word ``particle'' is used in this discussion to refer to a particle, droplet, or bubble.)The Effect of Particulate LoadingParticulate loading has a major impact on phase interactions. The particulate loading is defined as the mass density ratio of the dispersed phase ( d) to that of the carrier phase ( c):The material density ratiois greater than 1000 for gas-solid flows, about 1 for liquid-solid flows, and less than 0.001 for gas-liquid flows. Using these parameters it is possible to estimate the average distance between the individual particles of the particulate phase. An estimate of this distance has been given by Crowe et al. [ 42]:where . Information about these parameters is important for determining how the dispersed phase shouldbe treated. For example, for a gas-particle flow with aparticulate loading of 1, the interparticle space is about 8; the particle can therefore be treated as isolated (i.e., very low particulate loading).Depending on the particulate loading, the degree of interaction between the phases can be divided into three categories:For very low loading, the coupling between the phases is one-way; i.e., the fluid carrier influences the particles via drag and turbulence, but the particles have no influence on the fluid carrier. The discrete phase, mixture, and Eulerian models can all handle this type of problem correctly. Since the Eulerian model is the most expensive, the discrete phase or mixture model is recommended.For intermediate loading, the coupling is two-way; i.e., the fluid carrier influences the particulate phase via drag and turbulence, but the particles in turn influence the carrier fluid via reduction in mean momentum and turbulence. The discrete phase, mixture, and Eulerian models are all applicable in this case, but you need to take into account other factors in order to decide which model is more appropriate. See below for information about using the Stokes number as a guide.For high loading, there is two-way coupling plus particle pressure and viscous stresses due to particles (four-way coupling). Only the Eulerian model will handle this type of problem correctly.The Significance of the Stokes NumberFor systems with intermediate particulate loading, estimating the value of the Stokes number can help you select the most appropriate model. The Stokes number can be defined as the relation between the particle response time and the system response time:where and t s is based on the characteristic length ( L s) and the characteristic velocity ( V s) of the system under investigation: .For , the particle will follow the flow closely and any of the three models (discrete phase, mixture, or Eulerian) is applicable; you can therefore choose the least expensive (the mixture model, in most cases), or themost appropriate considering other factors. For , the particles will move independently of the flowand either the discrete phase model or the Eulerian model is applicable. For , again any of the three models is applicable; you can choose the least expensive or the most appropriate considering other factors. ExamplesFor a coal classifier with a characteristic length of 1 m and a characteristic velocity of 10 m/s, the Stokes number is 0.04 for particles with a diameter of 30 microns, but 4.0 for particles with a diameter of 300 microns. Clearly the mixture model will not be applicable to the latter case.For the case of mineral processing, in a system with a characteristic length of 0.2 m and a characteristic velocity of 2 m/s, the Stokes number is 0.005 for particles with a diameter of 300 microns. In this case, you can choose between the mixture and Eulerian models. (The volume fractions are too high for the discrete phase model, as noted below.)Other ConsiderationsKeep in mind that the use of the discrete phase model is limited to low volume fractions. Also, the discrete phase model is the only multiphase model that allows you to specify the particle distribution or include combustion modeling in your simulation.。

GLOBAL SENSITIVITY ANALYSISGlobal sensitivity analysis is the study of how the uncertainty in the output of a model (numerical or otherwise) can be apportioned to different sources of uncertainty in the model input”. Global could be an unnecessary specification here, were it not for the fact that most analysis met in the literature are local or one-factor-at-a-time.All models have use for global sensitivity analysis. Applications worked out by the Joint Research Centre group for Applied Statistics include: Atmospheric chemistry, transport emission modelling, fish population dynamics, composite indicators, hydrocarbon exploration models, macroeconomic modelling, radioactive waste management.Prescriptions have been issued for global sensitivity analysis of models when these used for policy analysis. In Europe, the European Commission recommends sensitivity analysis in the context of the extended impact assessment guidelines and handbook (2002). Similar recommendation in the United States EPA’s White Paper o n model use acceptability (1999).The EC handbook for extended impact assessment, a working document by the European Commission, 2002, states: “A good sensitivity analysis should conduct analyses over the full range of plausible values of key parameters and their interactions, to assess how impacts change in response to changes in key parameters”.The EPA paper (1999) is less prescriptive, but insists on the need for uncertainty and sensitivity analysis.We list below what are the desirable properties of an ideal global sensitivity analysis method.1. Cope with the influence of scale and shape. The influence of the input should incorporate theeffect of the range of input variation and the form of its probability density function (pdf). It matters whether the pdf of an input factor is uniform or normal, and what are the distribution parameters.2. Include multidimensional averaging. In a local approach to SA one computes partialderivatives, as discussed above. This is the effect of the variation of a factor when all othersare kept constant at the central (nominal) value. A global method should instead evaluate the effect of a factor while all others are varying as well.3. Be model independent. The method should work regardless of the additivity or linearity ofthe model. A global sensitivity measure must be able to appreciate the so-called interaction effect, especially important for non-linear, non-additive models. These arise when the effect of changing two factors is different from the sum of their individual effects.4. Be able to treat grouped factors as if they were single factors. This property of synthesis isessential for the agility of the interpretation of the results. One would not want to beconfronted with a SA made of dense tables of sensitivity measures.A few words about the output Y of interest. In our experience, the target of interest should not be the model output per se, but the question that the model has been called to answer. To make an example, if a model predicts contaminant distribution over space and time, it is the total areawhere a given threshold is exceeded at a given time which would play as output of interest, or the total health effects per time unit.One should seek from the analyses conclusions of relevance to the question put to the model,as opposed to relevant to the model, e.g.Uncertainty in emission inventories [in transport] are driven by variability in driving habits morethan from uncertainty in engine emission data.In transport with chemical reaction problems, uncertainty in the chemistry dominates over uncertainty in the inventories.Engineered barrier count less than geological barriers in radioactive waste migration.This remark on the output of interest clearly applies to model use, not to model building, where the analyst might have interest in studying a variety of intermediate outputs.Suggested ReferencesCampolongo, F., Saltelli A,. Jensen, N.R., Wilson, J., and Hjorth, J., 1999a, The role of multiphase chemistry in the oxidation of dimethylsulphide (DMS). A latitude dependent analysis, Journal of Atmospheric Chemistry, 32, 327-356.Campolongo, F., Tarantola, S., and Saltelli, A., 1999b, Tackling quantitatively large dimensionality problems, Computer Physics Communications, 117, 75-85.Crosetto, M. and Tarantola, S., 2001 Uncertainty and Sensitivity Analysis: Tools for GIS-based Model Implementation, International Journal of Geographic Information Science, 154, 415-437.EC, 2000, European Commission’s Communication on Extended Impact Assessment Brussels, 05/06/2002 COM(2002) 276 final. Guidelines for implementing the directive are available at the Governance page of the EC, http://europa.eu.int/comm/governance/docs/index_en.htm.EPA, 1999, The US Environmental Protection Agency Science Policy Council, White Paper on the Nature and Scope of Issues on Adoption of Model Use Acceptability Guidance,/osp/crem/library/whitepaper_1999.pdf.Ratto, M., Tarantola, S. and A. Saltelli 2001, Sensitivity analysis in model calibration:GSA-GLUE approach, Computer Physics Communications, 136, 212-224.Saltelli, A., S. Tarantola, K. Chan, 1999, A quantitative, model independent method for global sensitivity analysis of model output, Technometrics, 41 (1), 39-56.Saltelli, A., K. Chan and M. Scott, Eds., 2000, Handbook of sensitivity analysis, John Wiley & Sons publishers, Probability and Statistics series.Saltelli, A., 1999, Sensitivity analysis. Could better methods be used?, Journal of Geophysical Research, 104(D3), 3789-3793. N.B. see also Errata Corrige for a table’s error on the same journal, 1999, 104(D19), 24,013.Saltelli, A. (2002). Making best use of model valuations to compute sensitivity indices. Computer Physics Communications, 145, 280-297.Saltelli, A., Tarantola, S. Campolongo, F., 2000, Sensitivity analysis as an ingredient of modelling, Statistical Science, 15(4), 377-395.Saltelli A. Tarantola S., 2002, On the relative importance of input factors in mathematical models: safety assessment for nuclear waste disposal, Journal of American Statistical Association, 97 (459), 702-709.Saltelli A. Tarantola S., 2004, Campolongo, F. and Ratto, M., Sensitivity Analysis in Practice. A Guide to Assessing Scientific Models, John Wiley & Sons publishers, Probability and Statistics series, 2003 (to appear).Tarantola, S., J. Jesinghaus, M. Puolamaa, 2000, Global sensitivity analysis: a quality assurance tool in environmental policy modelling, in Saltelli, et al. (Eds) 2000, 385-397.Tarantola S., Saisana M., Saltelli A., Schmiedel F. and N. Leapman (2002) Statistical techniques and participatory approaches for the composition of the European Internal Market Index1992-2001, European Commission, EUR 20547 EN.MONTE CARLO (OR SAMPLE_BASED) ANALYSISMonte Carlo (MC) analysis is based on performing multiple evaluations with randomly selected model input, and then using the results of these evaluations to determine both uncertainty in model predictions and apportioning to the input factors their contribution to this uncertainty. A MC analysis involves the selection of ranges and distributions for each input factor; generation of a sample from the ranges and distributions specified in the first step; evaluation of the model for each element of the sample; uncertainty analysis and sensitivity analysis.Various sampling procedures are used in MC studies. Among those are: random sampling, stratified sampling (including latin hypercube sampling), and quasi-random sampling.Sensitivity measures based on the MC approach include regression-based measures (Standardised Regression Coefficients (SRC), Partial Correlation Coefficients (PCC), Standardised Rank Regression Coefficients (SRRC), Partial Rank Correlation Coefficients (PRCC)).Suggested references:Helton JC, FJ Davis (2000) Sampling Based Methods. Chapter 6 in Mathematical and Statistical Methods for Sensitivity Analysis of Model Output. Edited by A. Saltelli, K. Chan, and M. Scott, John Wiley and Sons.Helton JC (1993) Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal. Reliability Engineering and System Safety, 42,327-367.RESPONSE SURFACE METHODOLOGYThis procedure is based on the development of a response surface approximation to the model under consideration. This approximation is then used as a surrogate for the original model in uncertainty and sensitivity analysis.The analysis involves the selection of ranges and distributions for each input factor, the development of an experimental design defining the combinations of factor values on which evaluate the model, evaluations of the model, construction of a response surface approximation to the original model, uncertainty analysis and sensitivity analysis.Different types of experimental designs are available to select the points at which evaluate the model. The choice of the design points depend on a several factors: the number of independent variables under consideration, the computational effort needed for each model evaluation, the presence of quadratic or higher order effects, the importance of variable interactions.Sensitivity measures for the input factors are derived from the constructed response surface. This surface plays the same role in a response surface methodology as the Taylor series in a differential analysis.SCREENING DESIGNSFactors screening may be useful as a first step when dealing with a model containing a large number of input factors (hundreds). By input factor we mean any quantity that can be changed in the model prior to its execution. This can be a model parameter, or an input variable, or a model scenario. Often, only a few of the input factors and groupings of factors, have a significant effect on the model output.Screening experiments are used to identify the subset of factors that controls most of the output variability with a relatively low computational effort. As a drawback, these economical methods tend to provide qualitative sensitivity measures, i.e. they rank the input factors in order of importance, but do not quantify how much a given factor is more important than another.Typical screening designs are one-at-a-time (OAT) experiments, in which the impact of changing the values of each of the chosen factors is evaluated in turn. Although simple, easy to implement, and computationally cheap, the OAT methods have a limitation in that they do not enable estimation of interactions among factors and usually provide a sensitivity measure that is local (around a given point of the input space).An OAT design that is not dependent on the choice of the specific point in the input space is that proposed by Morris.Alternative approaches to the problem of screening include the design of Cotter, the Iterated Fractional Factorial Designs (IFFDs) introduced by Andres and Hajas, the sequential bifurcation method proposed by Bettonvil; and the method proposed by Morris, that still being an OAT experiment covers the whole input factor space.Suggested references:F. Campolongo, J. Kleijnen, and T. Andres, 2000, Screening methods in Sensitivity Analysis. Chapter 4 in Sensitivity Analysis, A. Saltelli, K. Chan, and M. Scott, Eds. John Wiley and Sons Publishers.Handbook of Simulation, Jerry Banks Editor, Wiley, New York, 1998.W. J.Welch, R. J.Buck, J. Sacks, H. P. Wynn, T. J. Mitchell , and M. D. Morris, 1992. Screening, predicting, and computer experiments. Technometrics, 34(1), 15-47.Campolongo, F., Saltelli A,. Jensen, N.R., Wilson, J., and Hjorth, J., 1999a, The role of multiphase chemistry in the oxidation of dimethylsulphide (DMS). A latitude dependent analysis, Journal of Atmospheric Chemistry, 32, 327-356.Campolongo, F., Tarantola, S., and Saltelli, A., 1999b, Tackling quantitatively large dimensionality problems, Computer Physics Communications, 117, 75-85.LOCAL - DIFFERENTIAL ANALYSISLocal SA investigates the impact of the input factors on the model locally, i.e. at some fixed point in the space of the input factors. Local SA is usually carried out by computing partial derivatives of the output functions with respect to the input variables (differential analysis). In order to compute the derivative numerically, the input parameters are varied within a small interval around a nominal value. The interval is not related to our degree of knowledge of the variables and is usually the same for all of the variables.One shortcoming of the linear sensitivity approach is that it is not possible to assess effectively the impact of possible differences in the scale of variation of the input variables, unless the model itself is linear. When significant uncertainty exists in the input parameters, the linear sensitivities alone are not likely to provide a reliable estimator of the output uncertainty in the model. When the model is non-linear and various input variables are affected by uncertainties of different orders of magnitude a global sensitivity method should be used.Differential analysis techniques are based on the use of a Taylor series to approximate the model under consideration. Once constructed, this series can be used as a surrogate for the original model in analytical uncertainty and sensitivity studies.A differential analysis involves four steps:（1）base values and ranges are selected for each input factor;（2）a Taylor series approximation to the output is developed around the base values for the inputs;（3）variance propagation techniques are used to estimate the uncertainty in the output in terms of its expected value and its variance;（4）the Taylor series approximation is used to estimate the importance of individual input factors.In the fourth step, there are different ways of measuring the importance of the input factors. For example normalised partial derivatives, in the first order Taylor series approximation, can measurethe effect on the solution that results from perturbing an input factor by a fixed fraction of its base value.One problem arising in a differential analysis is the determination of an appropriate order for the Taylor series approximation. Estimates for expected value and variance, in the third step, vary according to the order of approximation.Differential analysis methods have been used extensively in chemistry in a variety of applications, such as the solution of inverse problems, where they have proven their worth. Nevertheless, the use of global methods, possibly quantitative, should be preferred to derivative-based SA for all problem settings where finite parameter variations are involved, unless the model is known to be linear or the range of variation is small.Suggested references:T. Turanyi, and H. Rabitz. Local methods and their applications. Chapter 5 in Mathematical and Statistical Methods for Sensitivity Analysis of Model Output. Edited by A. Saltelli, K. Chan, and M. Scott, to be published by John Wiley and Sons.T. Turanyi, 1990. Reduction of large reaction mechanisms. New J. Chem. 14, 795-803.FORM-SORMFORM and SORM are useful methods when the analyst is not interested in the magnitude of Y (and hence its potential variation) but in the probability of Y exceeding some critical value. The constraint (Y-Y crit < 0) determines a hyper-surface in the space of the input factors, X. The minimum distance between some design point for X and the hyper-surface is the quantity of interest.Let B denote such a minimum distance for some assigned joint distribution of the input X. In these settings one can chose as sensitivity measure the derivative of B with respect to the input factors. Such a quantity should not be confused with the local derivative of Y with respect to the inputs, as the action of taking the minimum of B over the hyper-space of X introduces an element ofprobabilistic weighting. The First Order Reliability Method (FORM) offers such a probabilistic measure. It gives an estimate of how much a given input factor may drive the risk (probability of failure) of the system.Suggested references:J. Cawlfield. Reliability Algorithms (FORM and SORM). Chapter 7 in Mathematical and Statistical Methods for Sensitivity Analysis of Model Output. Edited by A. Saltelli, K. Chan, and M. Scott, to be published by John Wiley and Sons.。