# 物理代写|热力学代写thermodynamics代考|Why Statistical Thermodynamics?

#### Doug I. Jones

Lorem ipsum dolor sit amet, cons the all tetur adiscing elit

couryes™为您提供可以保分的包课服务

couryes-lab™ 为您的留学生涯保驾护航 在代写热力学thermodynamics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写热力学thermodynamics代写方面经验极为丰富，各种代写热力学thermodynamics相关的作业也就用不着说。

## 物理代写|热力学代写thermodynamics代考|Why Statistical Thermodynamics?

While the above classification scheme might please the engineering mind, it does little to acquaint you with the drama and excitement of both learning and applying statistical thermodynamics. Yes, you will eventually be able to calculate from atomic and molecular properties the thermodynamic properties of ideal gases, real gases, and metals. Examples might include equations of state, measurable properties such as specific heats and the internal energy, and also ephemeral properties such as the entropy and free energies. And yes, you will learn how to calculate various transport properties, such as the thermal conductivity and the diffusion coefficient. Furthermore, with respect to chemical reactions, you will eventually be able to determine equilibrium constants and estimate elementary rate coefficients.

While these pragmatic aspects of statistical thermodynamics are important, the real drama of the subject lies instead in its revelations about our natural world. As you work through this book, you will slowly appreciate the limitations of classical thermodynamics. In particular, the first, second, and third laws of thermodynamics should take on a whole new meaning for you. You will understand that volumetric work occurs because of microscopic energy transfers and that heat flow occurs because of redistributions in molecular population. You will realize that entropy rises in isolated systems because of a fundamental enhancement in molecular probabilities. You will also appreciate in a new way the important underlying link between absolute property values and crystalline behavior near absolute zero.

Perhaps more importantly, you will come to understand in a whole new light the real meaning of thermodynamic equilibrium and the crucial role that temperature plays in defining both thermal and chemical equilibrium. This new understanding of equilibrium will pave the path for laser-based applications of statistical thermodynamics to measurements of both temperature and species concentrations, as discussed in Chapter 11. Such optical measurements are extremely important to current research in all of the thermal sciences, including fluid mechanics, heat transfer, combustion, plasmas, and various aspects of nanotechnology and manufacturing.

## 物理代写|热力学代写thermodynamics代考|Probability: Definitions and Basic Concepts

Probability theory is concerned with predicting statistical outcomes. Simple examples of such outcomes include observing a head or tail when tossing a coin, or obtaining the numbers $1,2,3,4,5$, or 6 when throwing a die. For a fairly-weighted coin, we would, of course, expect to see a head for $1 / 2$ of a large number of tosses; similarly, using a fairlyweighted die, we would expect to get a four for $1 / 6$ of all throws. We can then say that the probability of observing a head on one toss of a fairly-weighted coin is $1 / 2$ and that for obtaining a four on one throw of a fairly-weighted die is $1 / 6$. This heuristic notion of probability can be given mathematical formality via the following definition:
Given $N_s$ mutually exclusive, equally likely points in sample space, with $N_e$ of these points corresponding to the random event $A$, then the probability $P(A)=N_e / N_s$.
Here, sample space designates the available $N_s$ occurrences while random event $A$ denotes the subset of sample space given by $N_e \leq N_s$. The phrase mutually exclusive indicates that no two outcomes can occur simultaneously in a single sample space; this criterion is obviously required if we are to convert our heuristic understanding of chance to a welldefined mathematical probability.

As a further example, for a standard deck of playing cards, we have 52 points in sample space, of which four represent aces. Hence, the probability of drawing a single ace from a well-mixed deck is $P(A)=4 / 52=1 / 13$, where the event $A$ designates the random drawing of an ace. Visually, the relation between event $A$ and sample space can be described by a so-called Venn diagram, as shown in Fig. 2.1. Here, sample points resulting in event $A$ fall within the area $A$, while those not resulting in event $A$ fall elsewhere in the surrounding box, whose total area represents the entire sample space. Hence, assuming a uniform point density, we find that the ratio of the cross-hatched area to the total area in Fig. 2.1 provides a visual representation of $P(A)$. Similarly, from the viewpoint of set theory, we observe that for a fairly-weighted die the random event of obtaining an even number $E={2,4,6}$ from within the entire sample space $S={1,2,3,4,5,6}$ clearly occurs with probability $P(A)=1 / 2$.

Our notion of probability becomes more complicated if we consider two different random events, $A$ and $B$, which can both occur within a given sample space. On this basis, we may define the compound probability, $P(A B)$, which represents events $A$ and $B$, and also the total probability, $P(A+B)$, which represents events $A$ or $B$ (including both). From the viewpoint of set theory, $P(A B)$ is called the intersection of $A$ and $B(A \cap B)$, while $P(A+B)$ is labeled the union of $A$ and $B(A \cup B)$. Pictorial displays of the (a) intersection and (b) union of $A$ and $B$ are given by the two Venn diagrams shown in Fig. 2.2.

If the events $A$ and $B$ are mutually exclusive, a single trial by definition permits no overlap in sample space. Therefore, $P(A B)=0$ so that
$$P(A+B)=P(A)+P(B),$$
as displayed by the Venn diagram of Fig. 2.3(a). As an example, the probability of picking a king $(K)$ or a queen $(Q)$ from a single deck of playing cards is given by the total probability $P(K+Q)=P(K)+P(Q)=2 / 13$. In comparison, the probability of picking a king from one deck and a queen from a different deck is $P(K Q)=(1 / 13)^2$. In the latter case, we have two different sample spaces, as indicated by the Venn diagram of Fig. 2.3(b), so that the events are now mutually independent. Hence, in general, the compound probability becomes
$$P(A B)=P(A) \cdot P(B) .$$

# 热力学代写

## 物理代写|热力学代写thermodynamics代考|Probability: Definitions and Basic Concepts

$$P(A+B)=P(A)+P(B),$$

$$P(A B)=P(A) \cdot P(B) .$$

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

Days
Hours
Minutes
Seconds

# 15% OFF

## On All Tickets

Don’t hesitate and buy tickets today – All tickets are at a special price until 15.08.2021. Hope to see you there :)