tailieunhanh - STATISTICAL THERMODYNAMICS: FUNDAMENTALS AND APPLICATIONS

My intention in this textbook is to provide a self-contained exposition of the fundamentals and applications of statistical thermodynamics for beginning graduate students in the engineering sciences. Especially within engineering, most students enter a course in statistical thermodynamics with limited exposure to statistics, quantum mechanics, and spectroscopy. Hence, I have found it necessary over the years to “start from the beginning,” not leaving out intermediary steps and presuming little knowledge in the discrete, as compared to the continuum, domain of physics. Once these things are done carefully, I find that good graduate students can follow the ideas, and that they leave the course excited and satisfied with their. | Statistical THERMODYNAMICS FUNDAMENTALS AND APPLICATIONS NORMAND M. LAUREN DEAU Cambridge g 9780521846356 This page intentionally left blank STATISTICAL THERMODYNAMICS FUNDAMENTALS AND APPLICATIONS Statistical Thermodynamics Fundamentals and Applications discusses the fundamentals and applications of statistical thermodynamics for beginning graduate students in the engineering sciences. Building on the prototypical Maxwell-Boltzmann method and maintaining a step-by-step development of the subject this book makes few presumptions concerning students previous exposure to statistics quantum mechanics or spectroscopy. The book begins with the essentials of statistical thermodynamics pauses to recover needed knowledge from quantum mechanics and spectroscopy and then moves on to applications involving ideal gases the solid state and radiation. A full introduction to kinetic theory is provided including its applications to transport phenomena and chemical kinetics. A highlight of the textbook is its discussion of modern applications such as laser-based diagnostics. The book concludes with a thorough presentation of the ensemble method featuring its use for real gases. Each chapter is carefully written to address student difficulties in learning this challenging subject which is fundamental to combustion propulsion transport phenomena spectroscopic measurements and nanotechnology. Students are made comfortable with their new knowledge by the inclusion of both example and prompted homework problems. Normand M. Laurendeau is the Ralph and Bettye Bailey Professor of Combustion at Purdue University. He teaches at both the undergraduate and graduate levels in the areas of thermodynamics combustion and engineering ethics. He conducts research in the combustion sciences with particular emphasis on laser diagnostics pollutant formation and flame structure. Dr. Laurendeau is well known for his pioneering research on the development and application of both .

• Năng lượng
• Gaussian Distribution
• Poisson Distribution
• Binomial Distribution
• Probability Distributions
• Statistical Mathemati
• Quantum Mechanics
• Positive distribution law
• The truncated Gaussian
• The fitted Gaussian
• The lognormal distribution
• Nuclear data evaluation files
• Face detection
• Based adaboost algorithm
• Haar like pattern
• Weak classifier
• Generalized hyperbolic skew t distribution
• EM algorithm
• Goodness of fit
• Normal inverse gaussian distribution
• Stock exchange
• Vuong type test
• Communications in Physics
• Simple model for market returns distribution
• Market returns distribution
• Boltzmann distribution to Gaussian asymptotic one
• Estimate the stability of the market
• Scripts and Functions
• Empirical Distributions
• Uniform Distribution
• Logarithmic Normal
• Gaussian mixture model
• Brain hemispheres
• Weight distribution
• Euclidean distance
• Brain DTGaussian mixture model
• Monte Carlo
• integral estimation
• congruential generators
• increasing dimension
• standard distributions
• Risk Management
• Asymptotic Behavior
• Cross Moment
• Conditional Correlation
• asymptotic dependence
• Analysis chemistry
• Confidence Intervals
• Standard deviations
• The Method of Least Squares
• Standard deviation
• Stylized facts
• Normal inverse Gaussian
• GARCH model
• Hyperbolic distribution
• Leptokurtic returns
• BMC Bioinformatics
• Dirichlet process
• Genetic architecture
• Meta analysis
• QTL effects