Aug 15, 2016 - Vikash Pandey and Sverre Holm, âLinking the fractional derivative and the Lomnitz creep ..... Clearly, the Caputo fractional derivative ...... [38] M. Caputo and M. Fabrizio, âA new definition of fractional derivative without singular.
Physical and Geometrical Interpretation of Fractional Derivatives in Viscoelasticity and Transport Phenomena
Thesis submitted for the degree of Philosophiae Doctor by
Vikash Pandey Faculty of Mathematics and Natural Sciences University of Oslo Autumn 2016
© Vikash Pandey, 2016 Series of dissertations submitted to the Faculty of Mathematics and Natural Sciences, University of Oslo No. 1781 ISSN 1501-7710 All rights reserved. No part of this publication may be reproduced or transmitted, in any form or by any means, without permission.
Cover: Hanne Baadsgaard Utigard. Print production: Reprosentralen, University of Oslo.
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Preface This thesis has been submitted to the Faculty of Mathematics and Natural Sciences at the University of Oslo in partial fulfillment of the requirements for the degree Philosophiae Doctor (Ph.D.). The work was carried out at the Digital Signal Processing and Image Analysis research group in the Department of Informatics, University of Oslo. The thesis has been supervised by Professor Sverre Holm and Dr. Sven Peter Näsholm. This work was financed through a PhD grant by the University of Oslo, Norway.
Acknowledgements It is reasonable to expect that a doctoral student acknowledges his supervisor, however having Prof. Sverre Holm as a mentor makes the task quite easier. He is an extraordinary person both at professional and personal level. I am deeply indebted to him for his constant guidance and encouragement. I could not have asked for a more engaging and insightful supervisor. I am grateful for his close collaboration, thorough discussions and reviews of my work, and for pushing me forward whenever I needed it. His faith and devotion have always made me feel the need of working harder to compensate for his support. Besides his professionalism, I have also learned from his scientific thinking and writing skills, which certainly will influence me throughout my future career. His art of gently massaging the manuscript for publication is remarkable. Further, he has arranged several research stays abroad and conference participations for me. I also need to specially thank my co-supervisor Dr. Sven Peter Näsholm for regularly updating me with the latest advances related to my research. He has been actively involved in broadening my research perspective which eventually will be more useful when I explore new ideas. I was always motivated by the stimulating intellectual discussion sessions whenever I had with both of my supervisors. With their great knowledge and open attitude, they created a fertile, cross-disciplinary environment of which this thesis is the yield. My sincere regards to Prof. Fritz Albregtsen since discussing physics with him besides being joyful has always led to a deeper understanding. A pleasant and motivating work atmosphere is of utmost importance to a foreign PhD student, and so I must convey my gratitude to the head of the research group, Prof. Anne Schistad Solberg along with Assoc. Prof. Andreas Austeng for sustaining a perfect social environment to ensure my natural comfort at the work place. I am also thankful to Drift for providing the necessary technical support during my PhD studies. It is also appropriate to acknowledge all those on whose scientific work I have built on, in particular, Prof. Michael J. Buckingham of Marine Physical Laboratory, University of California, San Diego. For the past four years, I have been fortunate to be working with brilliant colleagues from a wide range of research areas. I thank them for the fruitful discussions, advice and encouragement. Also, I wish them good luck in all their future endeavors. Finally, my heartfelt thanks to my parents for supporting my decision of opting for an academic-research career. Without their blessings this thesis could not have been conceived. They have been the tower of strength and motivation for me. Their devotion for my betterment will always be reflected in every milestone I achieve in my life.
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Abstract Few could have imagined the vast developments made in the field of fractional calculus which was first merely mentioned in the year 1695 in a correspondence between the pioneers of calculus, Leibniz and L’Hôpital. However, since fractional order derivatives can easily be seen as a “natural” generalization of the integer order derivatives, their studies have mostly been limited to the mathematics community. This is evident from the fact that despite having more than three hundred years of history, the order of the fractional derivative is mostly obtained by curve-fitting the experimental data from the theoretically predicted curves. Besides, very few works have demonstrated a deductive approach to fractional derivatives from the real physical processes. The physical interpretation of the fractional order has remained an open question for the fractional community as well as for those who use them to describe anomalous, complex, and memory-driven physical phenomena. Consequently, despite its widespread applications in the field of acoustics, rheology, seismology, and medical physics, fractional calculus has been plagued as an “empirical only” mathematical methodology. This thesis mainly aims at identifying the mechanisms which give rise to power law behavior, and hence a deductive approach to the fractional derivatives. This is first achieved by mapping the grain-shearing model of wave propagation in marine sediments into the framework of fractional calculus. The time-dependent viscosity of pore-fluid in the model is identified as the non-Newtonian property of rheopecty. The wave equations from the grain-shearing model turn out to be of fractional order. In the pursuit to analyze the grain-shearing model, it is found that a linearly time-varying Maxwell model yields a similar relaxation modulus as that of a fractional dashpot, and Lomnitz’s law as its creep compliance. Further, a linearly time-varying viscosity whose varying part dominates over the constant part is established as the common physical mechanism underlying both Nutting’s law and Lomnitz’s law. The fractional order in the Nutting law, and also the terms in the creep law gain physical interpretation. This physical justification has been lacking in both Nutting’s law and Lomnitz’s law since their inception in 1921 and 1956 respectively. We have also investigated fluid dynamics in fractal media. It is shown that the fractional Navier-Stokes equation and the fractional momentum diffusion equation naturally arise in such a medium. These findings infer that fluid flow in fractal media lead to fractional derivatives in time, the order of which is related to the fractal dimension of the medium. Thus, fractional derivatives also gain a form of geometrical interpretation. In addition, spatial dispersion of elastic waves in a nonlocal elastic bar is studied using space-fractional derivatives. The nonlocal attenuation kernel is tempered in order to circumvent the strong singularity encountered at the local point of stress application. Though the dispersion behavior obtained numerically is unusual, it turns out to be physically reasonable. The overall goal of this thesis is to show that fractional calculus is not just a mathematical framework which can only be empirically introduced to curve-fit the experimental observations. Rather, it has an inherent connection to real physical processes which needs to be explored more. We hope that the results obtained here may benefit the scientific communities of fractional calculus, seismology, non-Newtonian rheology, sediment acoustics, and fluid dynamics.
Publications This thesis is based on the following publications, referred to in the text by their Roman numerals (I-IV): I. Vikash Pandey, Sven Peter Näsholm, and Sverre Holm, “Spatial dispersion of elastic waves in a bar characterized by tempered nonlocal elasticity”, Fractional Calculus and Applied Analysis, Volume 19, Number 2, Pages 498–515, April 2016. DOI: http://dx.doi.org/10.1515/fca-2016-0026 II. Vikash Pandey and Sverre Holm, “Linking the fractional derivative and the Lomnitz creep law to non-Newtonian time-varying viscosity”, Physical Review E, Volume 94, Number 3, Pages 032606-1–032606-6, September 2016. DOI: http://dx.doi.org/10.1103/PhysRevE.94.032606 III. Vikash Pandey and Sverre Holm, “Connecting the grain-shearing mechanism of wave propagation in marine sediments to fractional order wave equations”, The Journal of the Acoustical Society of America, Revised version submitted on August 15, 2016. IV. Vikash Pandey, Sverre Holm, and Sven Peter Näsholm, “Relating fractional NavierStokes equation to fractals”, Submitted for publication on September 27, 2016.
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Related publications The following publications written in the context of the PhD study are related to the included papers, but are not included in full text in this thesis. I. Vikash Pandey and Sverre Holm, “A fractional calculus approach to the propagation of waves in an unconsolidated granular medium”, Abstract presented at the 170th ASA meeting, Jacksonville, Florida. Published in The Journal of the Acoustical Society of America, Volume 138, Number 3, Pages 1766–1766, September 2015. DOI: http://dx.doi.org/10.1121/1.4933584 II. Sverre Holm and Vikash Pandey, “Wave propagation in marine sediments expressed by fractional wave and diffusion equations”, IEEE/OES China Ocean Acoustics (COA), Pages 1–5, IEEE Xplore, January 2016. DOI: http://dx.doi.org/10.1109/COA.2016.7535803 III. Vikash Pandey and Sverre Holm, “Linking the viscous grain-shearing mechanism of wave propagation in marine sediments to fractional calculus”, Abstract presented at the 171st ASA meeting, Salt Lake City, Utah. Published in The Journal of the Acoustical Society of America, Volume 139, Number 4, Pages 2010–2010, April 2016. DOI: http://dx.doi.org/10.1121/1.4949910 IV. Vikash Pandey and Sverre Holm, “Connecting the viscous grain-shearing mechanism of wave propagation in marine sediments to fractional calculus”, A four page abstract presented at the 78th EAGE Conference and Exhibition, May 2016. DOI: 10.3997/2214-4609.201600862
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Contents 1
Introduction 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Fractional Calculus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Challenges to fractional calculus . . . . . . . . . . . . . . . . . . . . . . . . .
2
Applications of fractional calculus 2.1 Some examples on interpretation of fractional derivatives 2.2 Applications studied in this thesis . . . . . . . . . . . . 2.2.1 Nonlocal elasticity . . . . . . . . . . . . . . . . 2.2.2 Fractional viscoelasticity . . . . . . . . . . . . . 2.2.3 Time-dependent non-Newtonian rheology . . . . 2.2.4 Fluid dynamics in fractal media . . . . . . . . .
3
4
1 1 3 6
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7 8 9 9 11 14 19
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21 21 21 22 22
Discussions and future work 4.1 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23 23 26
Summary of publications 3.1 Paper I . . . . . . . . 3.2 Paper II . . . . . . . 3.3 Paper III . . . . . . . 3.4 Paper IV . . . . . . .
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Bibliography
27
Paper I Spatial dispersion of elastic waves in a bar characterized by tempered . . . . nonlocal elasticity
31
Paper II Linking the fractional derivative and the Lomnitz creep law to non. . . . Newtonian time-varying viscosity Paper III Connecting the grain-shearing mechanism of wave propagation in marine . . . . sediments to fractional order wave equations xi
31 47 47 61 61
Paper IV Relating fractional Navier-Stokes equation to fractals
xii
. . . .
89 89
Chapter 1 Introduction The thesis is organized into four chapters; an introduction, applications of fractional calculus, summary of publications, as well as discussions and future work. The bibliography, and the published/submitted papers referred to by their respective Roman numbers follow thereafter. This chapter gives an overview of the mathematical framework of fractional calculus along with its key historical developments. The applications discussed in Chapter 2 have eventually blossomed into the four papers which constitute the main body of the thesis. A deductive approach is adopted to describe applications in sediment acoustics, rheology, seismology and transport phenomena. On the one hand, Papers II and III are closely linked because a timevarying Maxwell model is studied in both. In Paper II, the physical mechanism underlying Nutting’s law and Lomnitz’s law is identified by investigating the stress-strain transient behavior of the time-varying Maxwell model. The frequency dependent dynamic behavior of this model is used in Paper III to describe the grain-shearing mechanism of wave propagation in marine sediments. On the other hand, Paper IV investigates fluid dynamics in fractal media. The Papers II-IV reflect the title of the thesis giving physical interpretation to the fractional differential equations arising in the study of different physical phenomena. However, in Paper I, spatial dispersion of elastic waves in the Eringen nonlocal elastic bar is investigated. The bar is characterized by a tempered attenuation kernel which then leads to interesting results.
1.1
Background
A couple of the mathematical expressions introduced to middle school students are, (i) xn = x · x · x ·x · x · · · x, n
(ii) n! = 1 · 2 · 3 · · · (n − 1) · n, where x is a real number, and n is a positive integer. This concept of exponentiation and factorial is quite easy to grasp and straight forward. But, the interpretation could become tricky, and confusion is bound to arise when n is not necessarily a positive integer. However, even in that case, one can still obtain the values of xn and n! from the following expressions:
1
(i) xn = en ln x , (ii) n! = Γ (n + 1), where n is a real number, and Γ (·) is the Euler gamma function. Although the results are verifiable using a scientific calculator, the expressions are difficult to comprehend for non-integer values of n. The problem further deepens if x is declared to be a regular physical quantity such as length or time. Since quantities raised to non-integer exponents require non-integral dimensions, they seem counterintuitive to our accepted notion of physical dimensions. A similar situation but of an even higher complexity and impact arises when the order of a derivative is raised to a non-integer order, i.e., a fractional order. Fractional Calculus as the name implies, is a field of mathematics that deals with derivatives and integrals of arbitrary orders, including complex orders. In the literature, it is also referred by several other names such as Generalized Integral and Differential Calculus, and Calculus of Arbitrary Order [1]. The name “Fractional Calculus” is a holdover, and accepted simply for historical reasons [2] as explained in the subsequent paragraph. Fractional calculus has applications in the field of material science, rheology, seismology, transport phenomena, nuclear physics, medical physics and finance, just to name a few [3–9]. It is interesting to note that using the principle of mathematical induction, it is quite possible to deduce and verify asymptotic behavior of fractional derivative at least for simple functions, such as power function, exponential function and trigonometric functions. However, the birth of fractional calculus is often accredited to an exchange of letter dated September 30th, 1695, between the mathematical geniuses Leibniz and L’Hôpital. L’Hôpital referring to a particular notation he had used in his publications for the nth-derivative of the linear function, f (x) = y,
dn y, dxn
(1.1)
posed a question to√Leibniz, “What if n be 1/2?”. Leibniz replied: “Thus it follows that d1/2 x will be equal to x dx : x. This is an apparent paradox from which, one day, useful consequences will be drawn.” [10]. Here, “:” implies division, “/”. In this way, the seeds of fractional derivatives were sown over 300 years ago. In the beginning, fractional calculus was primarily reserved for the best minds in mathematics many of whom directly or indirectly contributed to its development. Some of them who dabbled with it in chronological order are L. Euler, P. -S. Laplace, S. F. Lacroix, J. -B. J. Fourier, N. H. Abel, J. Liouville, G. F. B. Riemann, A. K. Grünwald, O. Heaviside, G. H. Hardy, and G. W. Scott Blair [3–5, 10]. Although treating it purely as a mathematical exercise, Lacroix was probably the first one to publish an article in 1819 which had fractional derivatives [11] mentioned as, m! dn m x = xm−n , n dx (m − n)!
m ≥ n.
(1.2)
Surprisingly, Eq. (1.2) which Lacroix had derived using the technique of mathematical induction is in accordance to the modern day definition of fractional derivatives [4, 5]. Finally, by letting m = 1 and n = 1/2, he obtained, d1/2 x x=2 . (1.3) 1/2 dx π 2
1.2
Fractional Calculus
The correspondence between Leibniz and L’Hôpital motivated many mathematicians and physicists to give a definition to the fractional derivatives. The most famous of these definitions that has been popularized are due to Riemann and Liouville. Unfortunately Riemann’s work which he had accomplished in his student days [10] was published only posthumously in 1876. He had used a generalization of the Taylor series to derive a formula for integration of arbitrary order [5]. Riemann further utilized the analytic continuation of Cauchy’s n-fold integral [3, 5], 1 (I f ) (t) = (n − 1)!
t (t − τ )n−1 f (τ ) dτ,
n
(1.4)
0
by replacing its factorial with the Gamma function to yield the fractional integral as, 1 (I f ) (t) = Γ (m)
t (t − τ )m−1 f (τ ) dτ.
m
(1.5)
0
Here, n is a positive integer, and m is a real-valued number. And, the function f (τ ) is expected to be a continuous, causal, and well-defined in the given limits. Also, Γ (·) is the Euler Gamma function defined for a complex variable z as: ∞ Γ (z) =
xz−1 e−x dx,
(z) > 0,
(1.6)
0
where (·) denotes the real part of a complex number. It is understood that Euler’s invention of the gamma function for the non-integer values of the factorial was eventually a result of his investigation of fractional integrals of monomials of arbitrary order [12]. On replacing the order m by (n − m) and introducing a nth order derivative before the integral in Eq. (1.5), Riemann-Liouville definition of fractional derivative [4, 5] is obtained as, 1 dn (D f ) (t) = Γ (n − m) dtn
t (t − τ )n−m−1 f (τ ) dτ,
m
m ∈ (n − 1, n) ,
(1.7)
0
where, n ∈ N, is the set of positive integers. As observed, having an integral in its expression, fractional differentiation is non-unique and non-local, just as is the regular integration. On the contrary, integer order derivatives are both unique and local. The fact that the choice of limits of integration affects the result of fractional derivative explains why Leibniz considered the subject to be paradoxical. Leibniz must have been aware that the result of integrating a function depends on how the function behaves over the range for which the integral is calculated. However, such a generalization has a merit too because it essentially unifies integrals and derivatives into a single operator. Thus, in order for the fractional generalizations to converge to the regular calculus where both uniqueness and locality is guaranteed, it is expected that the theory involves some sort of boundary conditions, involving information about the behavior of the function in the 3
given limits. While the sheer number of actual definitions is quite numerous and are often variations of the Riemann-Liouville definition, we have followed the Caputo definition [4,5] which is defined as the convolution of the power law kernel Φm (t) with the ordinary derivative: n dm d m f (t) ≡ 0 Dt f (t) Φm (t) ∗ f (τ ) , (1.8) dtm dτ n where, Φm (t) =
tn−m−1 . Γ (n − m)
(1.9)
Using Eq. (1.9) in (1.8), we have dm 1 f (t) = m dt Γ (n − m)
t 0
1 (t − τ )m+1−n
dn f (τ ) dτ. dτ n
(1.10)
From Eqs. (1.5)–(1.10) it can be seen that the power law kernel is built into the fabric of fractional calculus. The power law kernel which is also referred to as the “memory kernel” is the key to the modeling of materials which remember their past deformations. Some examples of such materials from daily life are cheese, clay, silly putty, rubber, and plastic. This application aspect of fractional derivatives had initially led to the development of the theory of “hereditary” solid mechanics. In the last 50 years, the theory has blossomed as the field of fractional viscoelasticity which is discussed in more detail in Chapter 2. As noticed, the Riemann-Liouville definition differs from the Caputo definition by the order of convolution and differentiation. In the former, convolution is carried out first, in contrast, differentiation is followed by the convolution in the latter. The fact that the Caputo fractional derivative satisfies the relevant property of being zero when applied to a constant, but RiemannLiouville definition does not, often favors the use of the Caputo definition [4,5]. This allows for the standard inclusion of traditional initial and boundary conditions in the Caputo formulation. But, modeling of physical systems based on other definitions of fractional derivative may require the values of the fractional derivative terms at the initial time, which may be impractical. This startling fact could be one of the reasons why fractional calculus historically had a difficult time getting embraced by the scientific communities. Clearly, the Caputo fractional derivative represents a sort of regularization in the time origin for the Riemann-Liouville fractional derivative. Therefore, we have followed Caputo’s definition in this thesis due to its better suitability to the modeling and analysis of physical phenomena. It may be even easier to see the extension to fractional derivatives from the Fourier transform property for integer order derivatives. The Fourier transform of the power law, Φm (t) in Eq. (1.9) is also a power law [4,5]. Since a convolution in time domain is a product in frequency domain, we see from Eq. (1.8) that,
m d f (t) = (iω)m F (ω) . (1.11) F m dt 4
The spatio-temporal Fourier transform is defined as ∞ ∞ f (x, t) ei(kx−ωt) dx dt,
F [f (x, t)] = F (ω)
(1.12)
−∞ −∞
where ω is the temporal angular frequency, and k is the corresponding spatial frequency. A simple example of fractional derivatives of a quadratic function, f (t) = t2 , is plotted for different values of the fractional order in Figure 1.1. The values are obtained using the expression, Γ(p + 1) p−m dm p t = , where p is a real number. (1.13) t m dt Γ(p − m + 1)
16
dm dtm f
(t)
14
Fractional derivative,
12
f(t) = t2 m = 0.25 m = 0.50 m = 0.75 m = 1.00
10 8 6 4 2 0 0
1
2
3
4
t m
Fig. 1.1: Fractional derivatives dtd m f (t), of a quadratic function, f (t) = t2 (blue, solid line). The fractional order, m has values 0.25 (magenta, dotted line), 0.50 (black, dashed line), 0.75 (green, dash-dot line), and 1 (red, thicker solid line). It is reasonable to acknowledge that fractional calculus can be considered as a branch of mathematical physics which deals with integro-differential equations, where integrals are of convolution type and exhibit weakly singular kernels of power law type. Thus, the current name of “Fractional calculus” is actually a misnomer, and the designation of “Calculus of arbitrary order” would be more appropriate. To summarize, the “integral” nature of the fractional derivatives broadens the landscape which then requires some peripheral vision to cover the view. 5
1.3
Challenges to fractional calculus
Although almost as old as the classical Newtonian calculus, fractional calculus fell into an oblivion for many years. The underlying reasons can be stated into four points. First, several of the definitions proposed for fractional derivatives were inconsistent, implying they worked in some cases but not in others. Oftentimes, the various definitions were not equivalent to each other and led to a paradox [13]. Second, the mathematics appeared complex and also very different compared to the well established integer order calculus. Third, since there were almost no practical applications of this field yet, it was considered by many as merely an abstract area for mathematical adventures with little or no use. Even at present there are very few examples which directly relate fractional derivatives to real physical processes. And, the fourth reason which upscaled the previous three challenges was the lack of an acceptable physical and geometric interpretation of fractional derivatives. On the contrary, the integer order derivatives have a clear physical and geometric interpretation, so their applications are easily understood. However, a quite dedicated work to solve this problem was made by Podlubny [14] in 2002. He tried giving a geometric interpretation of the Riemann-Liouville fractional integral based on the projection of a very fascinating shadow of a fence on a wall. It may be concluded that a convincing interpretation of fractional derivative has not been achieved yet, which is also ascertained by a recent paper written by eminent researchers working in the field [15]. How this limitation affects some of the present day applications of fractional calculus is explained in more detail in Papers II and III. Another possible drawback is the nonlocal nature of fractional derivatives which is connected to the fact that the fractional operators are convolution integrals. Compared with the numerical implementation of an integer order derivative, which only needs a few evaluations, the numerical evaluation of a fractional derivative needs substantially more floating point operations and data flow [13]. However, this aspect of fractional derivatives is not treated in this thesis, besides there are ways to circumvent them partially, if not completely. Thus, it is not surprising that most scientists and engineers have remained unaware of this broader field of fractional calculus since it is not taught in schools and colleges. Despite the fact that fractional derivatives have the potential to describe natural phenomena of higher complexity, the difficulty to introduce them even at a college level of education has contributed to the skepticism prevalent in scientific communities. Furthermore, relating them directly to physical processes has remained an open problem. The challenges to fractional framework is self-evident from the fact that despite of being an invention of the 17th century, the first major scientific conference on fractional calculus and its applications was organized much later in June 1974 by Ross at the University of New Haven, Connecticut [15]. Since then, a more intensive development of the field has taken place with more focus towards its potential applications [3]. Consequently, a specialized international journal for fractional calculus, Fractional Calculus and Applied Analysis, was established in 1998. An international conference series, Fractional Differentiation and its Applications, devoted to bring the researchers on a common platform is being held every second year since 2004. At present, fractional calculus is one of the most intensively developing areas of the mathematical physics as a result of its intriguing leaps in engineering and scientific applications. This can also be witnessed by the vast number of publications made in the last five decades [15, 16]. 6
Chapter 2 Applications of fractional calculus After the apparent dispute regarding the various definitions of fractional derivatives settled, a paradigm shift in the last 50 years has taken place, and since then there has been more focus towards its physical applications. The credit of this goes to Caputo, Mainardi, Podlubny, Kilbas and Hilfer, among others. Probably, it were Caputo and Mainardi who popularized fractional derivatives in the 20th century by first using it to describe the dissipative mechanism in earth materials [17–19]. Surprisingly, the empirical use of the fractional calculus can be traced back to almost 100 years ago when it was used for describing the power law behavior of complex viscoelastic materials. Some of the key early contributions came from Gemant [20], Scott Blair [21] and Gerasimov [5,22]. Gemant was possibly the first to suggest its use by introducing a half-order derivative in the Maxwell element to explain the transient behavior of flour dough like viscoelastic media [20]. While Scott Blair was primarily motivated by the experimental results [21] on cheese and clay, Gerasimov’s treatment was mainly a mathematical exercise as he had considered a power law kernel for the relaxation function in Boltzmann’s integral equation for viscoelasticity [4]. Some valuable contributions were made by Rabotnov and Cole-Cole; the former developed the theory of hereditary solid mechanics [4] using fractional derivatives, and the latter connected the fractional derivatives to the relaxation phenomena in dielectrics [23,24]. Such applications were inspired by two distinct features of fractional derivatives. First, contrary to the exponential decaying laws obtained from the integer order differential equations, fractional derivatives could give power law behavior which was observed in many complex media. Second, it could also capture power law jumps which sometimes were exhibited by the same material at different time scales. This was difficult to encompass using the integer order derivatives. Even though, Gerasimov’s and Rabotnov’s work date back to 1948, the two scientists from the former Soviet Union are apparently little known in the field because their work were published in Russian. Further, Scott Blair may be the first one to establish a fractional framework underlying Nutting’s power law [21]: σ ∝ t−m ,
0 < m < 1,
(2.1)
where σ is the stress, t is the time. He had intuitively referred to the order m as the “coefficient of dissipation”, and considered it to give a measure of the firmness of the material in his earlier work [25]. The Nutting law essentially describes material which exhibit memory. The study of these materials fall into the category of fractional viscoelasticity discussed in Subsection 2.2.2. 7
2.1
Some examples on interpretation of fractional derivatives
The suitability of the fractional derivatives in describing biological and viscoelastic media has been sufficiently demonstrated [3, 26]. They could describe both the transient stress-strain behavior as a function of time as well as the dynamic wave dispersion and attenuation as a function of frequency [4]. Interestingly, the use of half-order derivatives has also lead to a formulation of certain electro-chemical and heat-mass transfer problems which are found more suitable than the classical Fick’s law of diffusion [27]. But, fractional derivatives have mostly been “inductively” employed in these applications. The number of works which have “deduced” fractional derivatives from physical processes are very few. The honor of the first application [1] of fractional derivative belongs to Niels Henrik Abel in 1826. He demonstrated a deductive approach when he posed the solution of an integral equation that arises in the formulation of the mechanical problem of the tautochrone. This problem, sometimes also called the isochrone problem, is that of finding the shape of a frictionless wire lying in a vertical plane such that the time required by a bead to slide down the wire under the influence of gravity is independent of its initial position on the wire. It turns out that Abel’s solution motivated by the use of Laplace transform comprises of fractional derivative of order half, which corresponds to a cycloid as the isochrone, as well as the brachistochrone curve [28]. The brachistochrone problem which deals with the shortest time of slide had also been an exciting problem of the calculus of variations. It was probably Abel’s elegant solution which attracted and encouraged Liouville who made the first major attempt to give a more acceptable definition of a fractional derivative. Another contribution bearing a deductive approach came from the study of Bagley and Torvik on the Rouse model of polymer dynamics [29, 30] in 1980’s. They established a direct connection to the fractional derivatives by deriving a fractional stress-strain relationship of order half underlying the macroscopic mechanical properties of polymers. This finding was further developed [31] by generalizing the Rouse relaxation time which then extended the order of the fractional derivative to 0 and 1. It should be noted that there could be more such studies which may have demonstrated a direct connection between fractional derivatives and physical processes. However, the two examples of the isochrone and polymer dynamics have solely been included for their importance, and to resonate with the goal of the thesis. Further, the present scenario in most of the applications is that the value of the fractional order is usually obtained by curve-fitting the experimental data. This ambiguity has led to a lacking in the confidence of the use of fractional derivatives. However, fractional derivatives naturally emerge in complex processes and the order is found to be related to the physical parameters of the model as illustrated in this thesis through the Papers II and III. Besides, as shown in Paper IV, fluid transport in fractal media lead to fractional order differential equations, where the order is linked to the fractal dimension of the media. 8
2.2
Applications studied in this thesis
2.2.1
Nonlocal elasticity
An interesting fact is that, the power law memory inherent in a material is not limited to the time domain, but rather it could also exhibit in the space domain [32–34]. The study of such materials falls into the realm of nonlocal elasticity which goes back to the works of Kröner and Eringen [33, 35]. The study of nonlocal elasticity which is one of the branches of Nonlocal continuum field theories, is built upon two assumptions. First, the molecular interactions in a material are inherently nonlocal. Second, the theory assumes the energy balance law to be valid globally for the entire body. The applications of nonlocal elasticity have already been established in describing complex properties of liquid crystals, fluids, suspensions, and dielectrics [34]. Some latest applications are in nanomechanics which integrates the study of mechanical (elastic, thermal and kinetic) properties of physical systems at the nanometer scale, e.g., combining solid mechanics with atomistic simulations to analyze the strength and dispersive properties of carbon nanotubes. It is well established that, under the action of an applied stress, the constituent points of a nonlocal elastic material display range-dependent nonlocal interaction between themselves. Physically, it implies that the effect at a given point in space at a given time is dependent on the causes at the same point for all preceding times. Consequently, the applied stress is not confined to a local point, but rather distributed to all the interacting points of the material. An illustration comparing the local and nonlocal elasticity is shown in Figure 2.1, where constituent elements in a nonlocal material are shown connected to each other by means of springs of varying stiffnesses.
Fig. 2.1: A schematic comparison of local and nonlocal elasticity.
The nonlocal strain is expressed by the convolution integral of the strain in the neighborhood ε (y) with the attenuation kernel g (x − y), where y is the Euclidean distance from the local point x. For an infinitely long, one-dimensional, isotropic, linear nonlocal elastic bar, the 9
constitutive equation [36, 37] has the form, ⎡
⎤
⎢ ⎥ ∞ ⎢ ⎥ ⎢ ⎥ ε (y) g (x − y) dy ⎥ , σ (x) = E0 ⎢ ε (x) + κ ⎢ ⎥ ⎣Local strain ⎦ −∞
(2.2)
Nonlocal strain
where E0 is the elastic modulus at zero frequency, and κ is a material constant which gives a measure of the strength of nonlocality. In contrast, stress in a local elastic medium is limited to the point of impact, x. From Eq. (2.2), it may seem that, in the dynamic case of wave propagation in a nonlocal medium, the change in strain at the local position x, will instantaneously alter the stress at the nonlocal position y. Therefore, the communication between the points x and y may appear to be occurring at an infinite speed, and hence be non-causal and physically invalid. However, it should be noted that, one of the axioms on which the nonlocal continuum field theory is built upon, incorporates the axiom of causality [36]. Causality which is one of the basic principles of physics, dictates that the cause has to precede its effect. This imposes restrictions on both the time-domain and frequency-domain responses of a system. In the case of wave dispersion, which connects the oscillations in space with the oscillations in time, the causality principle enforces that the speed of a propagating wave cannot keep on increasing indefinitely. In order to satisfy the causality principle, the real and imaginary parts of the wave propagation vector, which are frequency dependent, must obey the Kramers-Kronig relations [7]. Since the Kramers-Kronig relations are essentially a Hilbert transform pair, it further implies that the wave attenuation is always coupled with its velocity. On the one hand, the causality principle is very well taken care of, when models are formulated in the time domain and the resulting dispersion is “temporal” in nature. On the other hand, a mechanical wave propagating in a nonlocal elastic medium exhibits “spatial” dispersion, such that the phase velocity and the wave attenuation are primarily dependent on the spatial wavenumber. Further, similar to the case of the temporal dispersion, it is reasonable to expect the validity of the causality principle in the spatial dispersion too. This aspect, in the case of a nonlocal elastic medium, is governed by the choice of the attenuation kernel g (x − y), which determines the extent of nonlocality present in the medium. This is investigated in Paper I, where the attenuation kernel adopted is a power law in space and has a singularity [38] at the local point. The kernel is therefore tempered [39, 40] to obtain the phase velocity dispersion and wave attenuation. It is shown that the elastic waves in such a nonlocal bar become non-dispersive in high frequency regimes. The dispersion plots in Fig. 2 of Paper I show that the phase velocity never exceeds the upper limit of lossless speed. Further, the attenuation in the corresponding frequency regime is negligible. Thus, the causality principle is not violated if an elastic wave undergoes spatial dispersion in such a nonlocal medium.
10
2.2.2
Fractional viscoelasticity
The characterization of media has been a long withstanding problem since the classical notion of solids, liquids and gases is not sufficient to match the properties of the medium we encounter in our daily life. This is better reflected by the viscoelastic bodies, which when deformed, exhibit both viscous and elastic behavior through simultaneous dissipation and storage of mechanical energy [4, 41]. Consequently, stress-strain constitutive equations for the viscoelastic behavior embody elastic deformation and viscous flow as special cases, and at the same time also allow response patterns that characterize behavioral blends of the two. Accordingly, multiple viscoelastic models have been proposed to describe the mechanical as well as the wave dispersive properties of biological materials and earth materials. The models traditionally include ideal springs and dashpots which are arranged in series and (or) parallel combinations to depict the interplay between the elastic and viscous properties of a material [41, 42]. The viscoelastic models; the Maxwell model and the Kelvin-Voigt model central to the theme of the Papers II and III are illustrated in Figure 2.2 a) and b) respectively.
Fig. 2.2: A mechanical equivalent sketch of the classical viscoelastic models; a) the Maxwell model, and b) the Kelvin-Voigt model. c) The fractional derivative element; a fractional dashpot. Figure adapted from Mainardi [4]. The constitutive relation for the spring and the viscous dashpot follow from Hooke and Newton [4, 42] respectively as, (2.3) σ (t) = E0 ε (t) , and
dε (t) , (2.4) dt where ε is the strain, and η is the viscosity of a Newtonian fluid. The fact that stresses add up in the parallel branches, and strains in series combinations, is used to obtain the stress-strain relation of the models as desired. Linear viscoelasticity embodying the above two equations has been a subject of intensive research mainly because it has the Boltzmann superposition principle inherent in it [4]. The underlying assumption of the principle is that the creep in a specimen σ (t) = η
11
is a function of the entire loading history, or simply the “memory”. And, each increment of load makes an independent as well as an additive contribution to the total deformation. Further, it should be emphasized that all these mechanical viscoelastic models are only “models”, and are not explanations, however they are found quite useful when analyzing complex material behavior. There are also many complex media such as biological tissues, polymers and earth sediments which do not obey the Newtonian fluid property expressed by Eq. (2.4), and therefore could not be satisfactorily described by the classical viscoelastic models. However, their fractional order counterparts which are essentially obtained by replacing the Newtonian dashpot in them by the fractional dashpot illustrated in Figure 2.2 c), have been found comparatively more useful [4,7–9,43–45]. The fractional dashpot is also referred to as the Scott Blair element due to historical reasons as mentioned in the first paragraph of this Chapter. The constitutive relation of the fractional dashpot [4] is given as, σ (t) = E0 τ
md
ε (t) , dtm
m
(2.5)
where the characteristic retardation time τ gives a measure of the time taken for the creep strain to accumulate. From Eq. (2.5), it can be seen that as m goes from 0 to 1, the fractional dashpot interpolates from a spring to a Newtonian dashpot, hence it is also termed a springpot. The fractional dashpot has attracted a lot of interest which eventually led to the development of the field of fractional viscoelasticity. This also brings into light the key difference between the framework of viscoelasticity and fractional viscoelasticity [4, 26]. In viscoelastic studies, the material is simply regarded as a combination of an elastic and a viscous element. On the contrary, in fractional viscoelasticity, material properties can be represented by various states between an elastic solid and a viscous fluid. Also, a noticeable advantage of fractional viscoelasticity is that it uses fewer viscoelastic elements which makes the parameter identification procedure robust and easier. Besides, such anomalous behavior of the fractional dashpot has been found to be thermodynamically consistent [46]. Moreover, the fractional viscoelastic models should not be seen as an entirely different class of models, but rather an extension of their classical counterparts. This is evident from the findings of Schiessel and Blumen [47] as they showed that the viscoelastic models with fractional attributes can be realized through hierarchical arrangements of springs and Newtonian dashpots in the form of trees, ladders and fractal networks [3]. As illustrated in Figure 2.3, a ladder network of an infinite number of Maxwell models is equivalent to a fractional dashpot. Another way of realizing a fractional dashpot is through the Maxwell–Wiechert model illustrated in Figure 2.4. The model is motivated from the study of Cole-Cole on dielectrics [23]. Also, it is more intuitive than the ladder network, as it takes into account the fact that the relaxation does not occur with a single time constant but with a distribution of time constants. These models may also explain why fractional models are being increasingly used in the investigation of biological tissues [8] in which the number of constituents is supposedly very large. On the one hand, the linear, time invariant systems exhibit exponential decay in time, implying no memory. On the other hand, power law decay inherent in the fractional derivatives can be obtained when several simultaneously decaying processes have closely spaced exponential decay rates. This hints about the statistical origins of fractional viscoelasticity [49]. 12
Fig. 2.3: Ladder arrangement of the classical Maxwell models. Figure adapted from Hilfer [3], and Schiessel and Blumen [47].
Fig. 2.4: The Maxwell–Wiechert model. Figure adapted from Näsholm and Holm [48]. 13
2.2.3
Time-dependent non-Newtonian rheology
Apart from the viscoelasticity described earlier, fluids departing from the Newtonian behavior could also be classified into another two categories; time independent and time dependent. The time-independent fluids can be further classified into three types; Bingham plasticity, dilatancy and pseudoplasticity [50, 51]. Since the inherent physical mechanism underlying such complex behavior is difficult to understand at the level of molecular dynamics, many empirical relations have been put forward for their investigation. One of such mathematical relations which has been employed extensively to describe various types of time-independent fluids stems from the Herschel-Bulkley fluid model as, ˙ q, (2.6) σ = σth + K(ε) where σth is the threshold stress required for a Bingham plastic like fluid-flow, e.g., tomatoketchup and toothpaste, and the constant K is the consistency index. However, some fluids do not require a threshold stress to flow. Then, letting σth = 0, reduces Eq. (2.6) to the Ostwald power law equation [50] which describes the remaining two types of time independent nonNewtonian fluids. The flow index q > 1 corresponds to the shear-thickening dilatant fluids, e.g. a mixture of cornstarch and water. And, q < 1 corresponds to the shear-thinning pseudoplastic fluids such as blood and ice. The Newtonian fluid property is maintained, if q = 1. The various time-independent behavior of the non-Newtonian fluids and their dependence on the shear rate is illustrated in Figure 2.5.
Fig. 2.5: Various types of time-independent non-Newtonian fluids; Bingham plastic (orange, fine dash-dot line), Bingham pseudoplastic (magenta, fine-dashed line), Dilatant (red, dash-dot line), and Pseudoplastic (blue, dotted line). The Newtonian (black, solid line) is included as a reference. Figure adapted from Deshpande [50]. Contrary to the time-independent non-Newtonian fluids, their time-dependent counterparts have not received significant interest owing to their complexity. The two types of the time dependent fluid behavior are called thixotropy and rheopecty [51]. On the one hand, thixotropic 14
fluids are very common such as yogurt, coal-water slurries and paints, and they display decreasing viscosity with respect to time. On the other hand, rheopectic fluids are comparatively rare and they display the opposite, i.e., increasing viscosity with respect to time, when agitated. A simple example of rheopectic behavior is a whipped cream; the longer one whips, the thicker it gets. The apparent changes in the viscosity is attributed to the structural build-up and breakdown of the internal components of a fluid which is determined by its kinematic shearing history [50, 51]. It should also be noted that time-dependent properties rheopecty and thixotropy lead to similar shear thickening and shear thinning behavior as those from the time-independent properties of dilatancy and pseudoplasticity, respectively. This is evident from the “nature” of the curves illustrated in Figure 2.6 a) and b), and therefore may lead to a confusion. However, on noting the abscissa of the plots, the key difference underlying the two categories of non-Newtonian fluids becomes clear. Moreover, the time-independent non-Newtonian fluids are dependent on strain rate as mentioned earlier, in contrast, the time-dependent properties exhibit at a constant stress or strain. Further, the experimental investigation of such non-Newtonian properties is rather difficult since oftentimes material exhibit a blend of the time-independent and time-dependent properties. Thus, even though the two contrasting properties may coexist in a material, timedependent behavior is rarely incorporated in the constitutive equation. The transient behavior of rheopectic materials under a constant shear stress and a constant shear strain is investigated in Paper II. There it is shown that if a linearly time-varying viscosity as illustrated in Figure 2.7, and mathematically expressed as, η (t) = η0 + θ · t,
(2.7)
when replaces the Newtonian dashpot in Figure 2.2 a), yields a time-varying Maxwell model whose relaxation modulus is, G(t) =
t 1+ τ
−m ,
τ=
η0 , θ
m=
E0 , θ
t ≥ 0,
(2.8)
which on a further approximation, θ · t η0 , is similar to that of a fractional dashpot illustrated in Figure 2.2 c). Here, η0 is the constant part of the viscosity, θ > 0 is the rheopectic coefficient, and τ is the time constant of the material. The creep compliance of the time-varying Maxwell model yields the famous logarithmic creep law of Lomnitz [52] which he had experimentally induced in 1956 during his PhD studies, t J(t) = 1 + m ln 1 + . (2.9) τ We may be the first to obtain a derivation of this law. The creep law although motivated by experimental observations on the igneous rocks, has widespread applications in fault dynamics, plate tectonics, rock physics, and in the understanding of damping of Chandler wobble [53]. 15
!
Fig. 2.6: Comparison of the two types of non-Newtonian fluids: a) time-independent; dilatant (red, dash-dot line) and pseudoplastic (blue, dotted line), and b) time-dependent; rheopectic (red, dash-dot line) and thixotropic (blue, dotted line). Newtonian (black, solid line) behavior is included in both subplots as a reference. Figure adapted from Deshpande [50] and Sochi [51].
16
Fig. 2.7: A mechanical equivalent sketch of the time-varying viscosity.
The dynamic behavior of the time-varying Maxwell is used to connect to Buckingham’s grain-shearing model in Paper III. The motivation behind the study is the rheopectic property of the pore-fluid manifesting from the shearing of the sediment grains in a marine environment (see, Figure 1 in Paper III.). The interesting derivation of the Kelvin-Voigt fractional derivative wave equation and diffusion-wave equation and their dispersion analysis for compression wave and shear wave propagation in marine sediments can be found in the paper. This discovery has only been possible after realizing that what Buckingham had referred to as “strain hardening” behavior of the intergranular sliding [54], is actually due to the the rheopectic behavior of the pore-fluid. In order to complete this argument, it should also be noted that the term strain hardening or work hardening is more commonly used in the the field of material science to explain the increase in material strength when strained beyond the linear elastic region [55], i.e., the non-Hookean behavior (see, Figure 2.8). As expected, the non-Hookean behavior of strain-hardening leads to nonlinear elasticity which is also evident from the mathematical expression used to describe it, σ = Sεp
(2.10)
where S is the strength coefficient of the material, and p is the strain hardening exponent, often less than unity for metals and alloys. On the contrary, the framework of fractional viscoelasticity is inherently linear. It can be seen that, Papers II and III intend to bridge the time-dependent behavior with the fractional viscoelasticity. Interestingly, as illustrated in Figure 2.9, the relaxation response G(t) of a viscoelastic material to a unit step in strain, owing to its partly elastic behavior, will differ from that of a medium characterized by time-dependent properties alone. 17
Fig. 2.8: Strain hardening (blue, dotted line) of a material when stretched beyond its Hookean region (black, solid line). On further stretching, the material undergoes necking, and even further strain leads to a fracture. Figure adapted from Callister [55].
Fig. 2.9: Comparison of relaxation moduli, G(t) of viscoelastic material (black, solid line), and time-dependent non-Newtonian rheopectic material (red, dash-dot line) and thixotropic material (blue, dotted line). Figure adapted from Sochi [51]. Further, it should be noted that the classifications of media stated earlier are by no means distinct or sharply defined. However, we also have the opinion that the framework of fractional viscoelasticity may bring all fluid properties under one umbrella. 18
2.2.4
Fluid dynamics in fractal media
The regular geometrical structures taught in schools such as a sphere, cube, cone etc, are less encountered in nature. Most of the structure we observe in our daily life are actually complex and apparently irregular [56]. Fractal geometry has been applied to study such structures followed by recent attempts to connect them to the fractional derivatives [57–61]. The impetus for this is from the fact that self-similarity in the form of spatial power laws inherent in the fractal objects could also be incorporated in the fractional framework. Most media through which fluids flow in nature are often characterized by fractal networks, such as plasma flow during lightening, underground water networks, blood vessels in human body, and branching in trees and its root network [56]. A simplified example of such a network relevant to the theme of the Paper IV is illustrated in Figure 2.10.
Fig. 2.10: A schematic representation of a fractal network observed in blood vessels and tree roots. Figure adapted from Mandelbrot [56]. Further, just as fractional derivatives can have an arbitrary order, fractal geometrical structures can have an intermediate dimension, i.e., non-integral dimension. This idea can better be understood from the definition of fractal dimension D given by Mandelbrot [56] as, D=
log N , log
(2.11)
where N is the number of self similar pieces, also called as the branching factor, and is the inverse of the scaling factor. For example, the square and triangular Sierpinski carpets illustrated in Figure 2.11 a) and b) respectively, have the fractal dimension of, Dsqr = log 8/ log 3 ≈ 1.892, and Dtri = log 3/ log 2 ≈ 1.585. Although unusual, the values of the fractal dimensions 19
make sense, since the carpets are definitely more than a one-dimensional object, but then they do not completely fill up the two-dimensional space either.
Fig. 2.11: a) Square Sierpinski carpet, and b) Triangular Sierpinski carpet. Figure adapted from Mandelbrot [56]. The fractal nature of the flow network naturally favors the fractional framework since power law is inherent in both. On the one hand, some studies have fractionalized one of the main equations of the fluid flow, the Navier-Stokes equation, and proposed solutions to it [62]. However the motivation is sheer mathematical. On the other hand, there are also works which have tried to obtain closed-form expressions from the physics of the fluid flow in fractal media [57–59]. A recent work by Butera and Di Paola [60] falls in that category, where they have elegantly tried to model fluid flow in a medium whose cross-sections are given by the Sierpinski carpets. But, despite an elegant approach, a closed-form expression of a governing fractional differential equation was not obtained. Their intermediate result relating velocity of fluid flow to temporal power law is extended in Paper IV to naturally arrive at the fractional Navier-Stokes equation. Further, a minor mathematical manipulation of this derivation leads to the fractional momentum diffusion equation which to the best of our knowledge may be its first derivation. Moreover, the order of the obtained transport equations is found to be related to the fractal dimension of the medium, giving fractional derivatives also a geometrical interpretation.
20
Chapter 3 Summary of publications 3.1
Paper I
“Spatial dispersion of elastic waves in a bar characterized by tempered nonlocal elasticity” Fractional Calculus and Applied Analysis, Volume 19, Number 2, Pages 498–515, April 2016. In this paper, wave propagation in an infinitely long, one-dimensional, nonlocal elastic bar is investigated. The measure of the nonlocality given by the attenuation kernel is considered to be a power law, which has a singularity, and therefore tempered. The resulting stress-strain constitutive relation is characterized by an integration implying strong nonlocal elasticity. The spatial dispersion relation is obtained from which it is difficult to extract the expression of the spatial frequency. Consequently, Müller’s method of root extraction is employed to obtain a numerical set of solutions relating spatial frequency to the temporal frequency. It is found that for low frequencies, elastic waves in such a medium exhibit strong phase velocity dispersion, but become non-dispersive in the high frequency regime. Further, the unusual wave attenuation in the nonlocal bar is explained to be physically valid. A bonus from this work is that we have shown how tempering can be employed in a fractional framework when a singularity is encountered.
3.2
Paper II
“Linking the fractional derivative and the Lomnitz creep law to non-Newtonian timevarying viscosity” Physical Review E, Volume 94, Number 3, Pages 032606-1–032606-6, September 2016. We have modified the classical Maxwell model by substituting its Newtonian dashpot by another dashpot which is characterized by a linearly increasing viscosity. The new dashpot then corresponds to a rare property of time-dependent non-Newtonian fluids, called rheopecty. The transient behavior of the time-varying Maxwell model is investigated, and its relaxation modulus and creep compliance are derived. It is found that its relaxation modulus is actually an asymptotic Nutting’s law which is similar to that from a fractional dashpot. This then bridges the two disparate fields of time-dependent non-Newtonian rheology and fractional viscoelasticity. 21
An offshoot of this work is witnessed by obtaining Lomnitz’s logarithmic creep law as the creep compliance of the time-varying Maxwell model. In this way, both Nutting’s law and Lomnitz’s law gain physical interpretation by identifying the common rheopecty mechanism underlying them. An even more interesting outcome is that, both laws are found to share the same assumption which is, the linearly time-varying part of the viscosity dominates over its constant part. Further, the order of the fractional derivative gains a physical interpretation. It is shown to give a measure of the interplay between the elastic and viscous properties of the material, which also is in accordance to the intuitive observation of Scott Blair.
3.3
Paper III
“Connecting the grain-shearing mechanism of wave propagation in marine sediments to fractional order wave equations” The Journal of the Acoustical Society of America, Revised version submitted on August 15, 2016. The findings of the Paper II are extended in this paper to investigate the grain-shearing (GS) mechanism of wave propagation in marine sediment. This has been possible because the behavior of the pore-fluid mediating the sliding grains turns out to be rheopectic. This simple observation then links time-dependent non-Newtonian rheology to sediment acoustics. Consequently, fractional derivatives are shown to naturally arise in this study. It is shown that the compressional wave propagation obtained in the original grain-shearing model turn out to be the Kelvin-Voigt fractional derivative wave equation. And, the shear wave equation takes the form of a diffusion-wave equation. Besides, in the fractional framework, the equations are much easier to analyze and interpret. The dispersion relations obtained using fractional calculus are shown to be exactly the same as those from the original GS model [54], which then establishes the equivalence of the wave equations obtained in the two different frameworks. Further, asymptotic behavior of the dispersion curves are easily extracted in the fractional framework.
3.4
Paper IV
“Relating fractional Navier-Stokes equation to fractals” Submitted for publication on September 27, 2016. Lately, some studies have proposed solutions to the fractional Navier-Stokes equation which is one of the fundamental equations of fluid dynamics having applications in various areas. However, the motivation behind that is purely mathematical. In this paper, we have derived the fractional Navier-Stokes equation without modifying either the law of conservation of mass, or the conservation of momentum. This has been possible by extending the findings of a recent work by Butera and Di Paola [60]. A natural consequence of this derivation is that the fractional momentum diffusion equation follows from the fractional Navier-Stokes equation. This connects the fluid dynamics in fractal space to diffusion in momentum space. Further, fractional derivatives also gain a geometrical interpretation because the order of the obtained transport equations is found to be related to the fractal dimension of the medium. 22
Chapter 4 Discussions and future work 4.1
Discussions
The results presented in this thesis can be summarized into five points. First, it is demonstrated that fractional derivatives naturally arise in materials which are characterized by linearly timevarying viscosity. The order of the fractional derivative is found to be a ratio of the physical parameters of elasticity modulus and the rheopectic coefficient. Second, one of the problems in the modeling of the time-dependent non-Newtonian fluids has been an ambiguity in the estimation of its relaxation time constant. We found the time constant to be a ratio of the constant, and the time-varying part of the viscosity. These two achievements have been possible after a similarity between the relaxation modulus of a fractional dashpot and a time-varying Maxwell model is established. A bonus of the linking is that the fractional viscoelasticity underlying Nutting’s law gets a physical interpretation. The application of these findings has also been demonstrated by formulating grain-shearing mechanism of wave propagation in marine sediments using fractional calculus. The obtained wave equations which are comparatively easier to analyze and manipulate on a fractional framework, are shown to be equivalent to Buckingham’s “convolved” wave equations. Thus, a connection between time-dependent non-Newtonian rheology, sediment acoustics and fractional viscoelasticity is found. Moreover, dual properties such as, both wave and diffusion like behavior, are easily identified in the fractional framework. Third, the creep compliance of the time-varying Maxwell model is found to be the same as the Lomnitz creep law which imparts a physical interpretation to the creep law just as in the case of Nutting’s law. Surprisingly, Nutting’s law and Lomnitz’s law share the same underlying physical mechanism of rheopecty; viscosity linearly increasing with time. An important observation which can be made here is that the connection between rheopecty and Lomnitz’s creep law is not an independent one, but rather it also connects to the fractional dashpot. As shown in Figure 4.1, the creep compliances of the time-varying Maxwell model (or, equivalently the Lomnitz law expressed by Eq. (2.9)) and that of the fractional dashpot (see, Eq. (3.1) in Mainardi [4]), m t 1 JF D (t) = , (4.1) Γ(1 + m) τ despite being mathematically dissimilar, are actually numerically equivalent for very low values of the order. 23
1.05
Creep compliance, J(t)
Time-varying Maxwell model Fractional dashpot
1.04
1.03
1.02
1.01
1 10-3 10-2 10-1 100 101 102 103 104 105 106
Time, t (seconds) Fig. 4.1: Numerical equivalence of the creep compliances of the fractional dashpot (red, dotted line) and the time-varying Maxwell model (blue, solid line). The values of the plotting parameters are taken from Lomnitz’s study [52] on igneous rocks, m = 0.002, and τ = 10−3 seconds. Further, the convergence exists over a wide range, from milliseconds to weeks. Fourth, the time-fractional Navier-Stokes equation and the fractional momentum diffusion equation are found to be naturally governing the fluid transport mechanism in a fractal medium. An interesting observation is that even without including the classical losses of any kind, the fractality of the medium alone gives rise to a fluid flow with a power law form of velocity field. The order of the derived transport equations is found to be related to the fractal dimension of the medium, thus yielding a form of a geometrical interpretation to the fractional derivatives. We believe this contributes to filling the gap between fractal geometry and fractional calculus. Fifth, the wave dispersive properties of a nonlocal elastic bar is studied, the result of which are anomalous, yet physically valid. In addition, we have also demonstrated how a strong singularity, which is sometimes encountered in the physical modeling using fractional derivatives, can be countered by tempering the attenuation kernel. The results from this work may benefit the material science industry where materials with unusual properties are artificially engineered. Until now the disparate fields of fractional viscoelasticity and rheology have not shared any significant connection with each other which is also evident from the lack of cross-referencing between the two fields. We encourage the respective scientific communities to come together for a symbiotic relationship, and experimentally test the findings reported in this thesis. The blend of the two fields then besides increasing the confidence in the use of fractional derivatives 24
will have even better applications in the field of elastodynamics, rheology, seismology, transport phenomena, biomedical acoustics, and sediment acoustics. As illustrated through the problems investigated in this thesis it is evident that the study of fractional calculus could lead to new possibilities by filling the voids of the classical calculus. We have the opinion that results obtained in this thesis may lead a step closer in establishing fractional calculus as a natural outgrowth of the integer order classical calculus, in much the same way as the gamma function has outgrown from the factorials. Perhaps, fractional calculus may serve as an efficient language to describe the natural phenomena. In that case, the interpretation of the physical phenomena in the framework of fractional derivatives must be as robust as in the framework of “classical” integer order derivatives. This would then necessitate a bridging of the two frameworks of mathematical physics as illustrated in Figure 4.2. Moreover, a broader fractional framework could possibly meet the demands of the physical reality without losing the classical calculus, since the latter is an inherent subset of the former. This is evident, as in the limiting conditions, results from the fractional calculus asymptotically converge to those from the classical calculus.
Fig. 4.2: An illustration of building a bridge between the two isolated “islands” of fractional calculus and classical calculus. Such a bridging may help in a better exploration of the vast ocean of physics. 25
4.2
Future work
A general notion accepted within the scientific community is that a problem when supposedly solved often leads to the discovery of new problems, to which this thesis is no exception. An obvious goal would be to analyze the viscous grain-shearing mechanism of wave propagation is marine sediments. However, in that case, a direct test of the fractional framework would be intended by fitting it to the experimental sediment data. Another interesting study could be to add a fractional dashpot element to the established models of time-independent non-Newtonian fluids, and then analyze their transient as well as their dynamic response. Further, an investigation could be made to model the thixotropic properties of fluids. The observation that the creep compliance of the time-varying Maxwell model numerically converges to that from a fractional dashpot for very low values of the order leaves room for further investigation. This could be to find the underlying physical mechanism which could encompass the entire spectrum of creep compliance exhibited by the fractional dashpot. Regarding fluid dynamics of fluids in fractal networks, an investigation could be made to obtain a closed-form governing equation which could include both the apparent losses from the fractality of the media as well as the classical Darcy losses. Further, analyzing the flow of time-dependent non-Newtonian fluids in fractal networks could have direct implications to the oil and gas industry. The problem can further be extended to find the dynamic response of a porous fractal frame containing time-dependent non-Newtonian fluids. These studies may help in a better understanding of the transport phenomena occurring in the fractal space. I wish to also extend the application of fractional calculus to the fields of quantum mechanics [63], and nonlinear dynamics and chaos [64], where not much work has been done. The latter may also be verifiable in an electronics laboratory. An another potential application of fractional derivatives could be much awaited in the field of Cosmology. The spectrum of cosmic microwave background radiation is influenced by the integrated Sachs-Wolfe effect which essentially describes gravitational potentials that vary with time while the photons are moving through them [65, 66]. The importance of the effect can be understood as, if the depth of the potential had remained constant, the energy gained by the photon while falling into the potential would have exactly canceled its losses while coming out of the potential. In simple words, the blue shift would then exactly cancel the red shift which could have led to a uniform background radiation on large scales. The observation of enhanced anisotropies on large angular scales is due to this integrated Sachs-Wolfe Effect, and therefore a holistic approach is required to investigate it, which might be possible in the larger framework of fractional calculus. In order to justify the plan of future studies mentioned here, I would like to mention an incident. In 1831, somebody asked Michael Faraday to talk about the usefulness of his discovery: the electromagnetic induction phenomenon. Faraday simply answered: What is the usefulness of a child? He grows into a man! In 2016, I would like to conclude this thesis thinking of fractional calculus as a young cricket player full of energy, who has just entered the field and can bat, bowl, and field equally well, and therefore demonstrates promising qualities of becoming an “all rounder” of the game in future.
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