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In this chapter, we selectively present global methods for efficiently solving FPDEs, employing the basis functions introduced in Chapters 2 and 3. Here, we adopt the term global often in the context of space-time, considering time as another (space-like) spectral direction. We examine a number of typical FPDEs, which we introduced and probabilistically interpreted in Chapter 1, including: the subdiffusion equation, tempered fractional diffusion on the half/whole line, in addition to the generalized and unified (1+d)-dimensional sub-to-superdiffusion FPDE model for d≥1, where a single FPDE form can model a range of physical processes by just varying the corresponding temporal/spatial fractional derivatives in the model, hence, rendering the FPDE elliptic, parabolic, and/or hyperbolic on the (1+d)-dimensional space-time hypercube. In this chapter, we employ one-sided, two-sided, constant/variable-order, and fully distributed order fractional operators, introduced in Chapters 1 and 2.
As highlighted in Chapter 1, anomalous transport phenomena can be observed in a wide variety of complex, multi-scale, and multi-physics systems such as: sub-/super-diffusion in subsurface transport, kinetic plasma turbulence, aging polymers, glassy materials, in addition to amorphous semiconductors, biological cells, heterogeneous tissues, and fractal disordered media. In this chapter, we focus on some selective applications of FPDEs and the methods presented in earlier chapters, reporting the scientific evidence of how and why fractional modeling naturally emerges in each case, along with a review of selected nonlocal mathematical models that have been proposed. The applications of interest are: (i) concentration transport in surface/subsurface dynamics, (ii) complex rheology and material damage, and (iii) fluid turbulence and geostrophic transport.
We initially introduce the standard diffusion model solving the PDF of the Brownian motion/process, satisfying the normal scaling property. This happens through a new definition of the process increments, where they are no longer drawn from a normal distribution, leading to α-stable Lévy flights at the microscopic level and correspondingly an anomalous diffusion model with a fractional Laplacian at the macroscopic scale. Next, we show how the Riemann–Liouville fractional derivatives emerge in another anomalous diffusion model corresponding to the asymmetric α-stable Lévy flights at small scales. Subsequently, we introduce the notion of subdiffusion stochastic processes, in which the Caputo time-fractional derivative appears in the anomalous subdiffusion fractional model. We combine the previous two cases, and construct continuous-time random walks, where a space-time fractional diffusion model will solve the evolution of the probability density function of the stochastic process. Next, we motivate and introduce many other types of fractional derivatives that will code more complexity and variability at micro-to-macroscopic scales, including fractional material derivatives, time-variable diffusivity for the fractional Brownian motion, tempered/variable-order/distributed-order/vector fractional calculus, etc.
This chapter provides a comprehensive presentation of global numerical methods for solving FODEs employing the polynomial and non-polynomial bases, introduced in Chapter 2. The FODEs of interest will be initial-/boundary-value problems, posed using a variety of fractional derivatives (e.g., Caputo, Riemann–Liouville, Riesz, one-sided, two-sided, variable-order, distributed order, etc.), introduced in Chapters 1 and 2. We devote Sections 3.1 and 3.2 to introducing a series of variational and non-variational spectral methods in single domains, where the solution singularities can occur at the initial or boundary points. In a variational formulation of an FODE, one first obtains the weak (variational) form of the given equation, where the highest derivative order is reduced using integration-by-parts, and then solves the variational formulation by constructing the corresponding (finite-dimensional) solution and test subspaces. In non-variational problems, one rather directly solves the strong (original) FODE, hence assuming a higher regularity in the solution. Moreover, we introduce spectral element methods (SEM) for FODEs in multiple domains for the main purpose of capturing possible interior/boundary singularities.
We present the need for new fractional spectral theories, explicitly yielding rather non-polynomial, yet orthogonal, eigensolutions to effectively represent the singularities in solutions to FODEs/FPDEs. To this end, we present the regular/singular theories of fractional Sturm–Liouville eigen-problems. We call the corresponding explicit eigenfunctions of these problems Jacobi poly-fractonomials. We demonstrate their attractive properties including their analytic fractional derivatives/integrals, three-term recursions, special values, function approximability, etc. Subsequently, we introduce the notion of generalized Jacobi poly-fractonomials (GJPFs), expanding the range of admissible parameters also allowing function singularities of negative indices at both ends. Next, we present a rigorous approximation theory for GJPFs with numerical examples. We further generalize our fractional Sturm–Liouville theories to regular/singular tempered fractional Sturm–Liouville eigen-problems, where a new exponentially tempered family of fractional orthogonal basis functions emerges. We finally introduce a variant of orthogonal basis functions suitable for anomalous transport that occurs over significantly longer time-periods.
Fractional diffusion equations are naturally derived on unbounded domains, and their solutions usually decay very slowly at infinity. A usual approach to dealing with unbounded domains is to use a domain truncation with exact or approximate transparent boundary conditions. But since accurate transparent boundary conditions at truncated boundaries are not easily available, we develop in this chapter efficient spectral methods for FPDEs on unbounded domains so as to avoid errors introduced by domain truncation. Formulation of Laplacians in bounded domains will be presented in Chapter 6.
The fractional Laplacian has multiple equivalent characterizations. Moreover, in bounded domains, boundary conditions must be incorporated in these characterizations in mathematically distinct ways, and there is currently no consensus in the literature as to which definition of the fractional Laplacian in bounded domains is most appropriate for a given application. Although the study of the fractional Laplacian is far from complete, this chapter can serve as a proper educational/research starting point for students/researchers in order to employ these operators to model complex anomalous systems. The Riesz (or integral) definition, for example, admits a nonlocal boundary condition, where the value of a function must be prescribed on the entire exterior of the domain in order to compute its fractional Laplacian. By contrast, the spectral definition requires only the standard local boundary condition. We compare several commonly used definitions of the fractional Laplacian theoretically, through their stochastic interpretations as well as their analytical properties. Then, we present quantitative comparisons using a sample of state-of-the-art methods. We finally discuss recent advances on nonzero boundary conditions and present new methods to discretize such boundary value problems.
We present efficient time-stepping schemes for accurate and long-time integration of time-fractional models. We direct our attention to introducing local multi-step finite-difference methods for time-fractional models. We introduce the fractional Adams family of schemes, which seamlessly generalize the classical explicit Adams–Bashforth and implicit Adams–Moulton schemes. Next, we combine the fractional Adams implicit-explicit (IMEX) schemes for stable and long-time integrations along with employing new correction terms, which enrich the underlying approximation space, especially in the context of nonlinear FODEs. We also investigate the linear stability of the fractional IMEX methods along their fast implementations. To this end, we present a fast approximate inversion scheme and fast computation of hypergeometric functions, which makes the IMEX algorithms amenable for accurate long-time integration of FODEs. To reduce the number of correction terms, we formulate a self-singularity-capturing scheme, which automatically captures the singular structure of the unknown solution (with even several random singularities without any prior knowledge), employing a two-stage time-integration algorithm. We will test the ease and efficiency of the method in the context of challenging cases, e.g., long-integration of singular-oscillatory solutions and nonlinear FODEs.
This comprehensive introduction to global spectral methods for fractional differential equations from leaders of this emerging field is designed to be accessible to graduate students and researchers across math, science, and engineering. The book begins by covering the foundational fractional calculus concepts needed to understand and model anomalous transport phenomena. The authors proceed to introduce a series of new spectral theories and new families of orthogonal and log orthogonal functions, then present corresponding spectral and spectral element methods for fractional differential equations. The book also covers the fractional Laplacian in unbounded and bounded domains and major developments in time-integration of fractional models. It ends by sampling the wide variety of real-world applications of fractional modeling, including concentration transport in surface/subsurface dynamics, complex rheology and material damage, and fluid turbulence and geostrophic transport.
Bathymetry is an important factor affecting wave propagation in coastal environments but is often challenging to measure in practice. We propose a method for inferring coastal bathymetry from spatial variations in surface waves by combining a high-order spectral method for wave simulation and an adjoint-based variational data assimilation method. Recursion-formed adjoint equations are derived to obtain the sensitivity of the wave surface elevation to the underlying bottom topography to any desired order of nonlinear perturbation. We also develop a multiscale optimisation method to eliminate spurious high-wavenumber fluctuations in the reconstructed bathymetry data caused by sensitivity variations over the different length scales of surface waves. The proposed bottom detection method is validated with a realistic coastal wave environment involving complex two-dimensional bathymetry features, non-periodic incident waves and nonlinear broadband multidirectional waves. In numerical experiments at both laboratory and field scales, the bathymetry reconstructed from our method agrees well with the ground truth. We also show that our method is robust against imperfect surface wave data in the presence of limited sampling frequency and noise.
We propose an improved adjoint-based method for the reconstruction and prediction of the nonlinear wave field from coarse-resolution measurement data. We adopt the data assimilation framework using an adjoint equation to search for the optimal initial wave field to match the wave field simulation result at later times with the given measurement data. Compared with the conventional approach where the optimised initial surface elevation and velocity potential are independent of each other, our method features an additional constraint to dynamically connect these two control variables based on the dispersion relation of waves. The performance of our new method and the conventional method is assessed with the nonlinear wave data generated from phase-resolved nonlinear wave simulations using the high-order spectral method. We consider a variety of wave steepness and noise levels for the nonlinear irregular waves. It is found that the conventional method tends to overestimate the surface elevation in the high-frequency region and underestimate the velocity potential. In comparison, our new method shows significantly improved performance in the reconstruction and prediction of instantaneous surface elevation, surface velocity potential and high-order wave statistics, including the skewness and kurtosis.
To improve the stability of Cs2SnCl6 under aqueous/moisture environments, we applied a concept of artificial passivation by depositing a protective TiO2 coating of 10 nm on the surface of Cs2SnCl6. Static leaching experiments results indicate that the initial release rates of Cs+ and Cl− are decreased by 20–30 times with TiO2 coating, suggesting its possibility to improve the short-term water/environmental stability of Cs2SnCl6. An amorphous-to-crystalline phase transition in TiO2 film was observed, possibly resulting in degradation of Cs2SnCl6. However, the crystalline TiO2 film still remains after 21 days water exposure and can still act as an effective passivation layer to reduce the release rates of Cs+ and Cl- by as much as about 17 and 7 times, respectively, relative to static leaching without artificial coatings. Therefore, the water/environmental stability of metal halide perovskite Cs2SnCl6, which is a highly soluble molecular salt, can be enhanced by the nanoscale TiO2 coating as an artificial passivation film.
Underground Nuclear Astrophysics in China (JUNA) will take the advantage of the ultra-low background in Jinping underground lab. High current accelerator with an ECR source and detectors were commissioned. JUNA plans to study directly a number of nuclear reactions important to hydrostatic stellar evolution at their relevant stellar energies. At the first period, JUNA aims at the direct measurements of 25Mg(p,γ)26 Al, 19F(p,α) 16 O, 13C(α, n) 16O and 12C(α,γ) 16O near the Gamow window. The current progress of JUNA will be given.