Thermodynamic Degradation Science E-Book

Alec Feinberg

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Wiley Series in Quality and Reliability Engineering
• Sprache: Englisch

Seitenzahl: 408

Veröffentlichungsjahr: 2016

Beschreibung

Thermodynamic degradation science is a new and exciting discipline. This book merges the science of physics of failure with thermodynamics and shows how degradation modeling is improved and enhanced when using thermodynamic principles.

The author also goes beyond the traditional physics of failure methods and highlights the importance of having new tools such as “Mesoscopic” noise degradation measurements for prognostics of complex systems, and a conjugate work approach to solving physics of failure problems with accelerated testing applications.

Key features:

• Demonstrates how the thermodynamics energy approach uncovers key degradation models and their application to accelerated testing.

• Demonstrates how thermodynamic degradation models accounts for cumulative stress environments, effect statistical reliability distributions, and are key for reliability test planning.

• Provides coverage of the four types of Physics of Failure processes describing aging: Thermal Activation Processes, Forced Aging, Diffusion, and complex combinations of these.

• Coverage of numerous key topics including: aging laws; Cumulative Accelerated Stress Test (CAST) Plans; cumulative entropy fatigue damage; reliability statistics and environmental degradation and pollution.

Thermodynamic Degradation Science: Physics of Failure, Accelerated Testing, Fatigue and Reliability Applications is essential reading for reliability, cumulative fatigue, and physics of failure engineers as well as students on courses which include thermodynamic engineering and/or physics of failure coverage.

Leseprobe

Wiley Series in Quality & Reliability Engineering

Dr Andre KleynerSeries Editor

The Wiley series in Quality & Reliability Engineering aims to provide a solid educational foundation for both practitioners and researchers in Q&R field and to expand the reader’s knowledge base to include the latest developments in this field. The series will provide a lasting and positive contribution to the teaching and practice of engineering.

The series coverage will contain, but is not exclusive to,

statistical methods;

physics of failure;

reliability modeling;

functional safety;

six-sigma methods;

lead-free electronics;

warranty analysis/management; and

risk and safety analysis.

Wiley Series in Quality & Reliability Engineering

Next Generation HALT and HASS: Robust Design of Electronics and Systemsby Kirk A. Gray, John J. PaschkewitzMay 2016

Reliability and Risk Models: Setting Reliability Requirements, 2nd Editionby Michael TodinovSeptember 2015

Applied Reliability Engineering and Risk Analysis: Probabilistic Models and Statistical Inferenceby Ilia B. Frenkel, Alex Karagrigoriou, Anatoly Lisnianski, Andre V. KleynerSeptember 2013

Design for Reliabilityby Dev G. Raheja (Editor), Louis J. Gullo (Editor)July 2012

Effective FMEAs: Achieving Safe, Reliable, and Economical Products and Processes using Failure Mode and Effects Analysisby Carl CarlsonApril 2012

Failure Analysis: A Practical Guide for Manufacturers of Electronic Components and Systemsby Marius Bazu, Titu BajenescuApril 2011

Reliability Technology: Principles and Practice of Failure Prevention in Electronic Systemsby Norman PascoeApril 2011

Improving Product Reliability: Strategies and Implementationby Mark A. Levin, Ted T. KalalMarch 2003

Test Engineering: A Concise Guide to Cost-effective Design, Development and Manufactureby Patrick O’ConnorApril 2001

Integrated Circuit Failure Analysis: A Guide to Preparation Techniquesby Friedrich BeckJanuary 1998

Measurement and Calibration Requirements for Quality Assurance to ISO 9000by Alan S. MorrisOctober 1997

Electronic Component Reliability: Fundamentals, Modelling, Evaluation, and Assuranceby Finn JensenNovember 1995

THERMODYNAMIC DEGRADATION SCIENCE

PHYSICS OF FAILURE, ACCELERATED TESTING, FATIGUE, AND RELIABILITY APPLICATIONS

Alec Feinberg, Ph.D.

DfRSoftware Company, Raleigh, NC, USA

This edition first published 2016© 2016 by John Wiley & Sons, Ltd

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Library of Congress Cataloging-in-Publication Data

Names: Feinberg, Alec, authorTitle: Thermodynamic degradation science : physics of failure, accelerated testing, fatigue and reliability applications / Alec Feinberg, Ph.D.Description: Hoboken, NJ : John Wiley & Sons, Inc., [2016] | Series: Wiley series in quality and reliability engineering | Includes bibliographical references and index.Identifiers: LCCN 2016017320 (print) | LCCN 2016031239 (ebook) | ISBN 9781119276227 (cloth) | ISBN 9781119276241 (pdf) | ISBN 9781119276272 (epub)Subjects: LCSH: Heat-engines–Thermodynamics. | Metals–Fatigue. |Metals–Testing. | Thermodynamic equilibrium.Classification: LCC TJ265 .F45 2016 (print) | LCC TJ265 (ebook) | DDC 620.1/61–dc23LC record available at https://lccn.loc.gov/2016017320

A catalogue record for this book is available from the British Library.

Cover image: Gettyimages/AlexSava

To Linda

Failure is Not an Option

In many situations, failure is not an option. It can take immense planning to prevent failure. Thermodynamic degradation science offers new tools and measurement methods that can help.

Second Law of Thermodynamics in Terms of Aging

The spontaneous irreversible degradation processes that take place in a system interacting with its environment will do so in order to go towards thermodynamic equilibrium with its environment.

Entropy Damage

The entropy generated associated with system degradation is “entropy damage.”

List of Figures

Figure 1.1

Conceptualized aging rates for physics-of-failure mechanisms

Figure 1.2

First law energy flow to system: (a) heat-in, work-out; and (b) heat-in and work-in

Figure 1.3

Fatigue

S–N

curve of cycles to failure versus stress, illustrating a fatigue limit in steel and no apparent limit in aluminum

Figure 1.4

Elastic stress limit and yielding point 1

Figure 2.1

The entropy change of an isolated system is the sum of the entropy changes of its components, and is never less than zero

Figure 2.2

Cell fatigue dislocations and cumulating entropy

Figure 2.3

Gaussian white noise

Figure 2.4

Noise limit heart rate variability measurements of young, elderly, and CHF patients [10]

Figure 2.5

Noise limit heart rate variability chaos measurements of young and CHF patients [10]

Figure 2.6

Graphical representation of the autocorrelation function

Figure 2.7

(a) Sine waves at 10 and 15 Hz with some randomness in frequency; and (b) Fourier transform spectrum. In (b) we cannot transform back without knowledge of which sine tone occurred first

Figure 2.8

(a) White noise time series; (b) normalized autocorrelation function of white noise; and (c) PSD spectrum of white noise

Figure 2.9

(a) Flicker (pink) 1/

f

noise; (b) normalized autocorrelation function of 1/

f

noise; and (c) PSD spectrum of 1/

f

noise

Figure 2.10

(a) Brown 1/

f

2

noise; (b) normalized autocorrelation function of 1/

f

2

noise; and (c) PSD spectrum of 1/

f

2

noise

Figure 2.11

Some key types of white, pink, and brown noise that might be observed from a system

Figure 2.12

1/

f

noise simulations for resistor noise. Note the lower noise for larger resistors (power of 2) and higher noise for smaller resistors (power of 1.5)

Figure 2.13

Autocorrelation noise measurement detection system

Figure 2.14

Insulating cylinder divided into two sections by a frictionless piston

Figure 2.15

System (capacitor) and environment (battery) circuit

Figure 2.16

The system expands against the atmosphere

Figure 2.17

Mechanical work done on a system

Figure 2.18

Loss of available work due to increase in entropy damage

Figure 2.19

A simple system in contact with a heat reservoir

Figure 2.20

A system’s free energy decrease over time and the corresponding total entropy increase

Figure 3.1

Conceptual view of cyclic cumulative damage

Figure 3.2

Cyclic work plane

Figure 3.3

Carnot cycle in

P

,

V

plane

Figure 3.4

Cyclic engine damage Area 1 > Area 2

Figure 4.1

Creep strain over time for different stresses where

σ

4

 > 

σ

3

 > 

σ

2

 > 

σ

1

Figure 4.2

Example of creep of a wire due to a stress weight

Figure 4.3

Wear occurring to a sliding block having weight

P

W

Figure 4.4

Graphical example of a sine test resonance

Figure 5.1

Lead acid and alkaline MnO

2

batteries fitted data

Figure 5.2

A simple corrosion cell with iron corrosion

Figure 5.3

Uniform electrochemical corrosion depicted on the surface of a metal

Figure 6.1

Arrhenius activation free energy path having a relative minimum as a function of generalized parameter

a

Figure 6.2

Examples of ln(1 + 

B

time) aging law, with upper graph similar to primary and secondary creep stages and the lower graph similar to primary battery voltage loss

Figure 6.3

Log time compared to power law aging models

Figure 6.4

(a) Continuous function with numerous energy states. (b) Relative minimum energy states having different degradation mechanisms

Figure 6.5

Aging with critical values

t

c

prior to catastrophic failure

Figure 7.1

Types of wear dependence on sliding distance (time)

Figure 7.2

Capacitor leakage model

Figure 7.3

Beta degradation on life test data

Figure 7.4

Life test data of gate-source MESFET leakage current over time fitted to the ln(1 + 

Bt

) aging model. Junction rise was about 30°C

Figure 8.1

System with

n

particles and

n

env

environment particles

Figure 8.2

Diffusion concept

Figure 9.1

Reliability bathtub curve model

Figure 9.2

Power law fit to the wear-out portion of the bathtub curve

Figure 9.3

Log time aging with parametric threshold

t

f

Figure 9.4

PDF failure portion that drifted past the parametric threshold

Figure 9.5

Creep curve with all three stages

Figure 9.6

Creep rate power law model for each creep stage, similar to the bathtub curve in

Figure 9.1

Figure 9.7

Creep strain over time for different stresses where

σ

4

 > 

σ

3

 > 

σ

2

 > 

σ

1

Figure 9.8

Crystal frequency drift showing time-dependent standard deviation

Figure A.1

Reliability bathtub curve model

Figure A.2

Demonstrating the power law on the wear-out shape

Figure A.3

Modeling the bathtub curve with the Weibull power law

Figure A.4

Weibull hazard (failure) rate for different values of

β

[1]

Figure A.5

Weibull shapes of PDF and CDF with

β

 = 2 [1]

Figure A.6

Weibull shapes of PDF and CDF with

β

 = 0.5 [1]

Figure A.7

Normal distribution shapes of PDF and CDF;

μ

 = 5,

σ

 = 1 [1]

Figure A.8

Lognormal hazard (failure) rate for different

σ

values [1]

Figure A.9

Lognormal CDF and PDF for different σ values [1]

Figure A.10

Cpk analysis

Figure A.11

Life test: (a) Weibull analysis compared to (b) lognormal analysis test at 200°C [1]

Figure A.12

Field data (

Table A.4

) displaying inflection point as sub and main populations [1]

Figure A.13

Separating out the lower and upper distributions by the inflection point method [1]

Figure B.1

Main accelerated stresses and associated common failure issues

Figure B.2

Common accelerated qualification test plan used in industry [1]

Figure B.3

Arrhenius plot of data given in

Table B.1

Figure B.4

MTTF stress plot of data given in

Table B.2

Figure B.5

Sine vibration amplitude over time example

Figure B.6

Random vibration amplitude time series example

Figure B.7

PSD of the random vibration time series in

Figure B.6

Figure C.1

S–N

curve for human heart compared to metal

N

fatigue cycle life versus

S

stress amplitude

Figure C.2

Simplified body repair

Figure C.3

Charge and repair RC model for the human body

List of Tables

Table 1.1

Generalized conjugate mechanical work variables

Table 1.2

Some state variables

Table 1.3

Some common intensive and extensive thermodynamic variables [1, 4]

Table 1.4

Common thermodynamic processes

Table 1.5

Thermodynamic aging states [1, 2, 4]

Table 2.1

Common time series transforms

Table 2.2

Four common thermodynamic potential and energy states

Table 4.1

Typical constants for stress–time creep law

Table 4.2

Damping loss factor examples for certain materials

Table 4.3

Cumulative stress test goals: CAST equations

Table 5.1

Estimated relative corrosion resistance

Table 5.2

Predicted corrosion rates and amounts for 1 year at 5 mA of current for anodic different metals [7]

Table 6.1

Failure mechanisms and associated thermal activation energies

Table A.1

Constant failure rate conversion table

Table A.2

Relationship between Cpk index and yield [1]

Table A.3

Life test data arranged for plotting

Table A.4

Field data and the renormalized groups

Table A.5

Multiple stress accelerated test to demonstrate 1 FMH [1]

Table B.1

MTTF observed

Table B.2

Machine stress MTTF observed

Table B.3

Gaussian probabilities (%)

Table B.4

Multiple stress accelerated test to demonstrate 0.6 FMH

Table B.5

Optimized multiple stress accelerated test for 0.6 FMH

Table B.6

Profile of a product’s temperature exposure per year

Table C.1

Human cyclic engine and possible stresses that shorten cycle life

About the Author

Dr Alec Feinberg received his Ph.D. in physics from Northeastern University in 1981. He is the founder of DfRSoft, a software and consulting company where he now works. He is the principal author of the book Design for Reliability. Alec has 30 years of experience in the area of reliability physics working in diverse industries including AT&T Bell Labs, TASC, M/A-COM, and Advanced Energy. He has provided reliability engineering services in all areas that include solar, thin film, power electronics, defense, microelectronics, aerospace, wireless electronics, and automotive electrical systems. He has provided training classes in Design for Reliability, Shock and Vibration, HALT, Reliability Growth, Electrostatic Discharge, Dielectric Breakdown, DFMEA, and Thermodynamic Reliability Engineering. Alec has presented numerous technical papers and won the 2003 RAMS Alan O. Plait best tutorial award for the topic Thermodynamic Reliability Engineering. Alec is also a contributing author to the book The Physics of Degradation in Engineered Materials and Devices. Alec is available to provide consulting and to give training classes in Thermodynamic Degradation Science, Design for Reliability, and Shock and Vibration through the author's website at www.dfrsoft.com.

Preface

Thermodynamic degradation science is a new and exciting discipline. It contributes to both physics of failure and as a new area in thermodynamics. There are many different ways to approach the science of degradation. Since thermodynamics uses an energy perspective, it is a great way to analyze such problems. There is something in this book for everyone who is concerned with degradation issues. Even if you are just interested in reliability or accelerated testing, there is a lot of new and highly informative material. We also go beyond traditional physics of failure methods and develop conjugate work models and methods. It is important to have new tools such as “mesoscopic” noise degradation measurements for complex systems and a conjugate work approach to solving physics of failure problems. We cover a number of original key topics in this book, including:

thermodynamic principles of degradation;

conjugate work, entropy damage, and free energy degradation analysis;

physics of failure using conjugate work approach;

complex systems degradation analysis using noise analysis;

mesoscopic

noise entropy measurement for disorder in operating systems;

human heart degradation noise measurements;

cumulative entropy damage, cyclic work, and fatigue analysis;

Miner’s rule derivation for fatigue and Miner’s rule for batteries;

engines and efficiency degradation;

aging laws, cumulative accelerated stress test (CAST) plans, and acceleration factors for: creep; wear; fatigue; thermal cycle; vibration (sine and random); temperature; humidity and temperature;

transistor aging laws (bipolar and FET models);

new accelerated test environmental profiling CAST planning method;

vibration cumulative damage (sine and random);

FDS (fatigue damage spectrum) analysis (sine and random);

chemical corrosion and activations aging laws;

diffusion aging laws;

reliability statistics;

how aging laws affect reliability distributions;

human engine degradation;

human heart versus metal cyclic fatigue;

human growth and repair model;

negative entropy and spontaneous negative entropy; and

environmental degradation and pollution.

When we think of thermodynamic degradation, whether it be for complex systems, devices, or even human aging, we begin to realize that it is all about “order” being converted to “disorder” due to the natural spontaneous tendencies described by the second law of thermodynamics to come to equilibrium with the neighboring environment. Although most people who study thermodynamics are familiar with its second law, not many think of it as a good explanation of why a product degrades over time. However, we can manipulate and rephrase it as follows.

The second law in terms of system thermodynamic degradation: the spontaneous irreversible degradation processes that take place in a system interacting with its environment will do so in order to go towards thermodynamic equilibrium with its environment.

We see that the science presents us with a gift, for its second law actually explains the aging processes. When I first realized this, I started to combine the science of degradation with thermodynamics. I presented these concepts in a number of papers and conferences, and in the book called Design for Reliability first published in 2000. The initial work was done with Professor Alan Widom at Northeastern University (1995). Recently I was invited to write a chapter in a book edited with Professor Swingler at Heriot-Watt University, Edinburgh, entitled The Physics of Degradation in Engineered Materials and Device. That gave me the chance to start to work on applications and new ways of performing degradation analysis. We see that this science is starting to catch on. This book presents the fundamentals and goes beyond including new ways to make measurements, and provides many examples so the reader will learn the value of how this science can be used. I believe this science will significantly expand soon and it is my hope that this book will provide the spark to inspire others. I believe there are a lot of new opportunities to enhance and use thermodynamic degradation methods. We should find that prognostics, using a thermodynamic energy approach, should advance our capabilities immensely. I have included such a measurement system in the book.

The fact is that, in many situations, failure is simply not an option and it can take immense planning to prevent failure. We need all the tools available to assist us. Thermodynamic degradation science offers new tools, new ways to solve physics of failure problems, and new ways to do prognostics and prevent failure.

1Equilibrium Thermodynamic Degradation Science

1.1 Introduction to a New Science

Thermodynamic degradation science is a new and exciting discipline. Reviewing the literature, one might note that thermodynamics is underutilized for this area. You may wonder why we need another approach. The answer is: in many cases you do not. However, the depth and pace of understanding physics of failure phenomenon, and the simplified methods it offers for such problems, is greatly improved because thermodynamics offers an energy approach. Further, systems are sometimes complex and made up of many components. How do we describe the aging of a complex system? Here is another possibility where thermodynamics, an energy approach, can be invaluable. We will also see that assessing thermodynamic degradation can be very helpful in quantifying the life of different devices, their aging laws, understanding of their failure mechanisms and help in reliability accelerated test planning [1–4]. One can envision that degradation is associated with some sort of device damage that has occurred. In terms of thermodynamics, degradation is about order versus disorder in the system of interest. Therefore, often we will use the term thermodynamic damage which is associated with disorder and degradation. One clear advantage to this method is that:

thermodynamics is an energy approach, often making it easier to track damage due to disorder and the physics of failure of aging processes.

More importantly, thermodynamics is a natural candidate to use for understanding system aging.

Here the term “system” can be a device, a complex assembly, a component, or an area of interest set apart for study.

Although most people who study thermodynamics are familiar with its second law, not many think of it as a good explanation of why a system degrades over time. We can manipulate a phrasing of the second law of thermodynamics to clarify our point [1, 4].

Second law in terms of system thermodynamic damage: the spontaneous irreversible damage processes that take place in a system interacting with its environment will do so in order to go towards thermodynamic equilibrium with its environment.

There are many phrasings of the second law. This phrasing describes aging, and we use it in this chapter as the second law in terms of thermodynamics damage occurring in systems as they age. We provide some examples in Chapter 2 (see Sections 2.10 and 2.11) of this statement in regards to aging to help clarify this.

When we state that degradation is irreversible, we mean either non-repairable damage or that we cannot reverse the degradation without at the same time employing some new energetic process to do so. We see there is a strong parallel consequence of the second law of thermodynamics associated with spontaneous degradation processes.

The science presents us with a gift, for its second law actually explains the aging processes[1, 4].

We are therefore compelled to look towards this science to help us in our study of system degradation. Currently the field of physics of failure includes a lot of thermodynamic-type explanations. Currently however, the application of thermodynamics to the field of device degradation is not fully mature. Its first and second laws can be difficult to apply to complex aging problems. However, we anticipate that a thermodynamic approach to aging will be invaluable and provide new and useful tools.

1.2 Categorizing Physics of Failure Mechanisms

When we talk about system damage, we should not lose sight of the fact that that we are using it as an applicable science for physics of failure. To this end, we would like to keep our sights on this goal. Thermodynamic reliability is a term that can apply to thermodynamic degradation physics of a device after it is taken out of the box and subjected to its use under stressful environmental conditions. We can categorize degradation into categories [1, 2] as follows.

The irreversible mechanisms of interest that cause aging are categorized into four main categories of:

forced processes;

activation;

diffusion; and

combinations of these processes yielding complex aging.

These are the key aging mechanisms typically of interest and discussed in this book. Aging depends often on the rate-controlling process. Any one of these three processes may dominate depending on the failure mode. Alternately, the aging rate of each process may be on the same time scale, making all such mechanisms equally important. Figure 1.1 is a conceptualized overview of these processes and related physics of failure mechanisms.

Figure 1.1 Conceptualized aging rates for physics-of-failure mechanisms

In this chapter, we will start by introducing some of the parallels of thermodynamics that can help in our understanding of physics of degradation problems. Here fundamental concepts will be introduced to build a basic framework to aid the reader in understanding the science of thermodynamic damage in physics of failure applications.

1.3 Entropy Damage Concept

When building a semiconductor component, manufacturing a steel beam, or simply inflating a bicycle tire, a system is created which interacts with its environment. Left to itself, the interaction between the system and environment degrade the system of interest in accordance with our second law phrasing of device degradation. Degradation is driven by this tendency of the system/device to come into thermodynamic equilibrium with its environment. The total order of the system plus its environment tends to decrease. Here “order” refers to how matter is organized, for example disorder starts to occur when: the air in the bicycle tire starts to diffuse through the rubber wall; impurities from the environment diffuse into otherwise pure semiconductors; internal manufacturing stresses cause dislocations to move into the semiconductor material; or iron alloy steel beams start to corrode as oxygen atoms from the atmospheric environment diffuse into the steel. In all of these cases, the spontaneous processes creating disorder are irreversible. For example, the air is not expected to go back into the bicycle tire; the semiconductor will not spontaneously purify; and the steel beam will only build up more and more rust. The original order created in a manufactured product diminishes in a random manner, and becomes measurable in our macroscopic world.

Associated with the increase in total disorder or entropy is a loss of ability to perform useful work. The total energy has not been lost but degraded. The total energy of the system plus the environment is conserved during the process when total thermodynamic equilibrium is approached. The entropy of the aging process is associated with that portion of matter that has become disorganized and is affecting the ability of our device to do useful work. For the bicycle tire example, prior to aging the system energy was in a highly organized state. After aging, the energy of the gas molecules (which were inside the bicycle tire) is now randomly distributed in the environment. These molecules cannot easily perform organized work; the steel beam, when corroded into rust, has lost its strength. These typical second-law examples describe the irreversible processes that cause aging.

More precisely:

if entropy damage has not increased, then the system has not aged.

Sometimes it will be helpful to separately talk about entropy in two separate categories.

Entropy damage causes system damage, as compared to an entropy term we refer to as non-damage entropy flow.

For example, the bicycle tire that degraded due to energy loss did not experience damage and can be re-used. Adding heat to a device increased entropy but did not necessarily cause damage. However, the corrosion of the steel beam is permanent damage. In some cases, it will be obvious; in other cases however, we may need to keep tabs on entropy damage. In most cases, we will mainly be looking at entropy change due to device aging as compared to absolute values of entropy since entropy change is easier to measure. Entropy in general is not an easy term to understand. It is like energy: the more we learn how to measure it, the easier it becomes to understand.

1.3.1 The System (Device) and its Environment

In thermodynamics, we see that it is important to define both the device and its neighboring environment. Traditionally, this is done quite a bit in thermodynamics. Note that most books use the term “system” [5, 6]. Here this term applies to some sort of device, complex subsystem, or even a full system comprising many devices. The actual term system or controlled mass is often used in many thermodynamic text books. In terms of the aging framework, we define the following in the most general sense.

The system is some sort of volume set apart for study. From an engineering point of view, of concern is the possible aging of the system that can occur

.

The environment is the neighboring matter, which interacts with the system in such a way as to drive it towards its thermodynamic equilibrium aging state

.

This interaction between a system and its environment drives the system towards a thermodynamic equilibrium lowest-energy aging state

.

It is important to realize that there is no set rule on how the system or the environment is selected. The key is that the final results be consistent.

As a system ages, work is performed by the system on the environment or vice versa. The non-equilibrium process involves an energy exchange between these two.

Equilibrium thermodynamics provides methods for describing the initial and final equilibrium system states without describing the details of how the system evolves to a final equilibrium state. Such final states are those of maximum total entropy (for the system plus environment) or minimum free energy (for the system)

.

Non-equilibrium thermodynamics describes in more detail what happens during the evolution towards the final equilibrium state, for example the precise rate of entropy increase or free energy decrease. Those parts of the energy exchange broken up into heat and work by the first law are also tracked during the evolution to an equilibrium final state. This is a point where the irreversible process virtually slows to a halt

.

1.3.2 Irreversible Thermodynamic Processes Cause Damage

We can elaborate on reversible or irreversible thermodynamic processes. Sanding a piece of wood is an irreversible process that causes damage. We create heat from friction which raises the internal energy of the surface; some of the wood is removed creating highly disordered wood particles so that the entropy has increased. The disordered wood particles can be thought of as entropy damage; the wood block has undergone an increase in its internal energy from heating, which also increases its entropy as well as some of the wood at the surface is loose. Thus, not all the entropy production goes into damage (removal of wood). Since we cannot perform a reversible cycle of sanding that collects the wood particles and puts them back to their original state, the process is irreversible and damage has occurred. Although this is an exaggerated example:

in a sense there are no reversible real processes; this is because work is always associated with energy loss.

The degree of this loss can be minimized in many cases for a quasistatic process (slow varying in time). We are then closer to a reversible process or less irreversible. For example, current flowing through a transistor will cause the component to heat up and emit electromagnetic radiation which cannot be recovered. As well, commonly associated with the energy loss is degradation to the transistor. This is a consequence of the environment performing work on the transistor. In some cases, we could have a device doing work on the environment such as a battery. There are a number of ways to improve the irreversibility of the aging transistor: improve the reliability of the design so that less heat is generated; or lower the environmental stress such as the power applied to the transistor. In the limit of reducing the stress to zero, we approach a reversible process.

A reversible process must be quasistatic. However, this does not imply that all quasistatic processes are reversible.

In addition, the system may be repairable to its original state from a reliability point of view.

A quasistatic process ensures that the system will go through a gentle sequence of states such that a number of important thermodynamic parameters are well-defined functions of time; if infinitesimally close to equilibrium (so the system remains in quasistatic equilibrium), the process is typically reversible.

A repairable system is in a sense “repairable-reversible” or less irreversible from an aging point of view. However, we cannot change the fact that the entropy of the universe has permanently increased from the original failure and that a new part had to be manufactured for the replaceable part. Such entropy increase has in some sense caused damage to the environment that we live in.

1.4 Thermodynamic Work

As a system ages, work is performed by the system on the environment or vice versa. The non-equilibrium process involves an energy exchange between these two. Measuring the work isothermally (constant temperature) performed by the system on the environment, and if the effect on the system can be quantified, then a measure of the change in the system’s free energy can be obtained. If the process is quasistatic, then generally the energy in the system ΔU can be decomposed into the work δW done by the environment on the system and the heat δQ flow.

The bending of a paper clip back and forth illustrates cyclic work done by the environment on the system that often causes dislocations to form in the material. The dislocations cause metal fatigue, and thereby the eventual fracture in the paper clip; the diffusion of contaminants from the environment into the system may represent chemical work done by the environment on the system. We can quantify such changes using the first and second law of thermodynamics. The first law is a statement that energy is conserved if one regards heat as a form of energy.

The first law of thermodynamics: the energy change of the system dU is partly due to the heat δQ added to the system which flows from the environment to the system and the work δW performed by the system on the environment (Figure 1.2a):

(1.1)

In the case where heat and work are added to the system, then either one or both can cause damage (Figure 1.2b). If we could track this, we could measure the portion of entropy related to the damage causing the loss in the free energy of the system (which is discussed in Chapter 2).

Figure 1.2 First law energy flow to system: (a) heat-in, work-out; and (b) heat-in and work-in

If heat flows from the system to the environment, then our sign convention is that . Similarly, if the work is done by the system on the environment then our sign convention is that