Nonlinear Diffusion Model Research Articles

Economic dynamics and technology diffusion in indian power sector

There is a growing concern among policy makers about how electricity is generated and consumed in the context of energy security and global climate change. In such a scenario, renewable energy sources, especially solar and wind energy, are likely to play a significant role in providing reliable and sustainable electricity to consumers as they are locally available and their carbon foot print is small. The future share of power by renewables will greatly depend on the expected generation cost and the government's support to investments in the sector. Using levelised cost approach, capital cost, operating and fuel costs of major electricity generation technologies are compared. Then, a forecast is made for electricity generation in India, using non-linear Bass diffusion model over 15-year horizon, until 2030, for all major energy technologies, viz., coal, natural gas, hydro, solar, wind, and biomass. The results show how present trends and future forecasts of electricity-generating technologies change the electricity generation mix, and how solar and wind power may increase their share in the total generation. However, fossil fuels will continue to remain competitive relative to renewables due to their cost advantage. The main issue considered here is whether each energy technology has reached its maximum penetration level. This helps set out a path for renewable energy technology diffusion in the Indian power sector

Analysis of subdiffusion in disordered and fractured media using a Grünwald-Letnikov fractional calculus model

The increasing applications of fractional calculus in simulating the anomalous transport behavior in disordered and fractured heterogeneous porous media has grown rapidly over the past decade. In the present study, a temporal fractional flux relationship is employed as a constitutive equation to relate the volumetric flow rate to the gradient of the pore pressure. The novelty of this paper entails interpreting the time fractional derivative operator in the flux relationship by the Grunwald-Letnikov (G-L) definition as opposed to the Caputo interpretation which has been widely considered. Subsequently, a numerical scheme based on the block-centered finite-difference discretization is formulated to handle the resulting non-linear fractional diffusion model. In addition, a linear stability analysis is successfully performed to establish the stability criterion of the developed numerical scheme. An expression for the modified incremental material balance index was derived to assess the effectiveness of the numerical discretization process. Finally, numerical experiments were performed to provide qualitative insights into the nature of pressure evolution in a hydrocarbon reservoir under the influence subdiffusion. In summary, the results establish that subdiffusion regime results in the development of higher pressure drop in the reservoir. This paper will provide a strong foundation for researchers interested in investigating anomalous diffusion phenomena in porous media.

On the Foundation of Equipartition in Supernova Remnants

Abstract A widely accepted paradigm is that equipartition (eqp) between the energy density of cosmic rays (CRs) and the energy density of the magnetic field cannot be sustained in supernova remnants (SNRs). However, our 3D hydrodynamic supercomputer simulations, coupled with a nonlinear diffusive shock acceleration model, provide evidence that eqp may be established at the end of the Sedov phase of evolution in which most SNRs spend the longest portions of their lives. We introduce the term “constant partition” for any constant ratio between the CR energy density and the energy density of the magnetic field in an SNR, while the term “equipartition” should be reserved for the case of approximately the same values of the energy density (also, it is constant partition in the order of magnitude) of ultra-relativistic electrons only (or CRs in total) and the energy density of the magnetic field. Our simulations suggest that this approximate constant partition exists in all but the youngest SNRs. We speculate that since evolved SNRs at the end of the Sedov phase of evolution can reach eqp between CRs and magnetic fields, they may be responsible for initializing this type of eqp in the interstellar medium. Additionally, we show that eqp between the electron component of CRs and the magnetic field may be used for calculating the magnetic field strength directly from observations of synchrotron emission from SNRs. The values of magnetic field strengths in SNRs given here are approximately 2.5 times lower than values calculated by Arbutina et al.

Time fractional super-diffusion model and its application in peak-preserving smoothing

The super-diffusion model is suggested for peak-preserving smoothing. In this model, the time derivative on the left of the classical diffusion model is replaced with the time fractional derivative. Because of the weight property of the fractional derivative, the super-diffusion model can further improve the smooth performance of the classical nonlinear diffusion model. An explicit difference scheme and an implicit difference scheme are given. Then some comparisons between the proposed model and the classical nonlinear diffusion model are done. The results indicate the proposed model outperforms the classic nonlinear diffusion model. In the end, the proposed method is used to smooth a nuclear magnetic resonance spectroscopy and a mass spectrometry.

Delay Induced Hopf Bifurcation in a Nonlinear Innovation Diffusion Model: External Influences Effect

Delay Induced Hopf Bifurcation in a Nonlinear Innovation Diffusion Model: External Influences Effect

Analysis of the fractional diffusion equations with fractional derivative of non-singular kernel

In this paper we study linear and nonlinear fractional diffusion equations with the Caputo fractional derivative of non-singular kernel that has been launched recently (Caputo and Fabrizio in Prog. Fract. Differ. Appl. 1(2):73-85, 2015). We first derive simple and strong maximum principles for the linear fractional equation. We then implement these principles to establish uniqueness and stability results for the linear and nonlinear fractional diffusion problems and to obtain a norm estimate of the solution. In contrast with the previous results of the fractional diffusion equations, the obtained maximum principles are analogous to the ones with the Caputo fractional derivative; however, extra necessary conditions for the existence of a solution of the linear and nonlinear fractional diffusion models are imposed. These conditions affect the norm estimate of the solution as well.

Optimal investment and premium control in a nonlinear diffusion model

This paper considers the optimal investment and premium control problem in a diffusion approximation to a non-homogeneous compound Poisson process. In the nonlinear diffusion model, it is assumed that there is an unspecified monotone function describing the relationship between the safety loading of premium and the time-varying claim arrival rate. Hence, in addition to the investment control, the premium rate can be served as a control variable in the optimization problem. Specifically, the problem is investigated in two cases: (i) maximizing the expected utility of terminal wealth, and (ii) minimizing the probability of ruin respectively. In both cases, some properties of the value functions are derived, and closed-form expressions for the optimal policies and the value functions are obtained. The results show that the optimal investment policy and the optimal premium control policy are dependent on each other. Most interestingly, as an example, we show that the nonlinear diffusion model reduces to a diffusion model with a quadratic drift coefficient when the function associated with the premium rate and the claim arrival rate takes a special form. This example shows that the model of study represents a class of nonlinear stochastic control risk model.

Numerical simulation of a porous medium-type atherosclerosis initiation model

Atherosclerosis is an inflammatory disease due to the accumulation of low-density lipoproteins (LDLs) in the arteries wall, with the consequence that plaque is built up inside the arteries. Different mathematical models have been proposed to represent the first stages of atherosclerosis development. In this work we propose a mathematical model based on [1,2] but including a nonlinear diffusion porous medium-type in the 1D system of PDEs. The numerical solution is obtained by means of an ADER-WENO approach in the finite volume framework. First results theoretically obtained and numerically proved has been reported in [1], for the linear diffusion model. In this work we extend those results to the nonlinear diffusion model.

Modeling nonlinear moisture diffusion in inhomogeneous media

While moisture diffusion in microelectronic device and packaging has been studied for decades, the problems involving complex nonlinear moisture diffusion in multi-material assembly have not been fully studied. This paper has developed a general nonlinear diffusion model by adopting water activity, a continuous state variable, as the field variable. The generalized solubility is introduced, which is temperature- and water activity-dependent. The effective diffusivity is defined and derived in terms of generalized solubility and water activity. By comparing the water activity-based model with the existing various normalized models, the present theory can unify and generalize the current approaches. More importantly, the present model can solve both linear and nonlinear moisture diffusion in inhomogeneous material system without normalization. The commercial finite element software has been applied to solve the nonlinear generalized moisture diffusion problem using the analogy of water activity and temperature. A source code of user-defined subroutines in ABAQUS has been provided in the Appendix of the paper. The mathematical formulation and the numerical implementation method presented in this paper can be applied to any nonlinear sorption or diffusion problems in inhomogeneous material system.

Linearized finite-element method solution of the ion-exchange nonlinear diffusion model

Ion-exchange process is one of the most common techniques used in glass waveguide fabrication. This has many advantages, such as low cost, ease of implementation, and simple equipment requirements. The technology is based on the substitution of some of the host ions in the glass (typically Na + ) with other ions that possess different characteristics in terms of size and polarizability. The newly diffused ions produce a region with a relatively higher refractive index in which the light could be guided. A critical issue arises when it comes to designing such waveguides, which is carefully and precisely determining the resultant index profile. This task has been proven to be hideous as the process is generally governed by a nonlinear diffusion model with no direct general analytical solution. Furthermore, numerical solutions become unreliable—in terms of stability and mean squared error—in some cases, especially the K + − Na + ion-exchanged waveguide, which is the best candidate to produce waveguides with refractive index differences compatible with those of the commercially available optical fibers. Linearized finite-element method formulations were used to provide a reliable tool that could solve the nonlinear diffusion model of the ion-exchange in both one- and two-dimensional spaces. Additionally, the annealed channel waveguide case has been studied. In all cases, unprecedented stability and minimum mean squared error could be achieved.

Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion.

The degradation of the acquired signal by Poisson noise is a common problem for various imaging applications, such as medical imaging, night vision, and microscopy. Up to now, many state-of-the-art Poisson denoising techniques mainly concentrate on achieving utmost performance, with little consideration for the computation efficiency. Therefore, in this paper we aim to propose an efficient Poisson denoising model with both high computational efficiency and recovery quality. To this end, we exploit the newly developed trainable nonlinear reaction diffusion (TNRD) model which has proven an extremely fast image restoration approach with performance surpassing recent state-of-the-arts. However, the straightforward direct gradient descent employed in the original TNRD-based denoising task is not applicable in this paper. To solve this problem, we resort to the proximal gradient descent method. We retrain the model parameters, including the linear filters and influence functions by taking into account the Poisson noise statistics, and end up with a well-trained nonlinear diffusion model specialized for Poisson denoising. The trained model provides strongly competitive results against state-of-the-art approaches, meanwhile bearing the properties of simple structure and high efficiency. Furthermore, our proposed model comes along with an additional advantage, that the diffusion process is well-suited for parallel computation on graphics processing units (GPUs). For images of size , our GPU implementation takes less than 0.1 s to produce state-of-the-art Poisson denoising performance.

Stochastic lattice model of synaptic membrane protein domains.

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

Evaluation of Classical Models for Thermal and Moisture Transport in Stone Walls of Historical Buildings

This paper concerns the evaluation and the validation of a heat and moisture transfer models in stone walls using in situ measurements on an instrumented wall. Firstly, a pure thermal (respectively moisture) diffusion problems are considerate, then this problem was combined with convection on the external edge of model. It is found that, despite of an uncoupled approach, the nonlinear thermal diffusive model performs quite well and reproduces perfectly the measured temperatures. It is the same for the convective-diffusive thermal problem, where the temperature on the surface wall is also reproduced quite well. An improvement of this second type problem results could be expected by taking into account the radiation. Otherwise, the both cases of moisture transfer problem (purely diffusive or diffusive-convective problem) are ill-simulated by the Kunzel’s model.

Submodels of model of nonlinear diffusion with non-stationary absorption

We study the model, describing a nonlinear diffusion process (or a heat propagation process) in an inhomogeneous medium with non-stationary absorption (or source). We found tree submodels of the original model of the nonlinear diffusion process (or the heat propagation process), having different symmetry properties. We found all invariant submodels. All essentially distinct invariant solutions describing these invariant submodels are found either explicitly, or their search is reduced to the solution of the nonlinear integral equations. For example, we obtained the invariant solution describing the nonlinear diffusion process (or the heat distribution process) with two fixed "black holes", and the invariant solution describing the nonlinear diffusion process (or the heat distribution process) with the fixed "black hole" and the moving "black hole". The presence of the arbitrary constants in the integral equations, that determine these solutions provides a new opportunities for analytical and numerical study of the boundary value problems for the received submodels, and, thus, for the original model of the nonlinear diffusion process (or the heat distribution process). For the received invariant submodels we are studied diffusion processes (or heat distribution process) for which at the initial moment of the time at a fixed point are specified or a concentration (a temperature) and its gradient, or a concentration (a temperature) and its rate of change. Solving of boundary value problems describing these processes are reduced to the solving of nonlinear integral equations. We are established the existence and uniqueness of solutions of these boundary value problems under some additional conditions. The obtained results can be used to study the diffusion of substances, diffusion of conduction electrons and other particles, diffusion of physical fields, propagation of heat in inhomogeneous medium.

A novel investigation of a micropolar fluid characterized by nonlinear constitutive diffusion model in boundary layer flow and heat transfer.

The rheological and heat-conduction constitutive models of micropolar fluids (MFs), which are important non-Newtonian fluids, have been, until now, characterized by simple linear expressions, and as a consequence, the non-Newtonian performance of such fluids could not be effectively captured. Here, we establish the novel nonlinear constitutive models of a micropolar fluid and apply them to boundary layer flow and heat transfer problems. The nonlinear power law function of angular velocity is represented in the new models by employing generalized "n-diffusion theory," which has successfully described the characteristics of non-Newtonian fluids, such as shear-thinning and shear-thickening fluids. These novel models may offer a new approach to the theoretical understanding of shear-thinning behavior and anomalous heat transfer caused by the collective micro-rotation effects in a MF with shear flow according to recent experiments. The nonlinear similarity equations with a power law form are derived and the approximate analytical solutions are obtained by the homotopy analysis method, which is in good agreement with the numerical solutions. The results indicate that non-Newtonian behaviors involving a MF depend substantially on the power exponent n and the modified material parameter [Formula: see text] introduced by us. Furthermore, the relations of the engineering interest parameters, including local boundary layer thickness, local skin friction, and Nusselt number are found to be fitted by a quadratic polynomial to n with high precision, which enables the extraction of the rapid predictions from a complex nonlinear boundary-layer transport system.

A nonlinear diffusion model for electricity prices and derivatives

In this paper, we first develop a one-factor diffusion model for electricity prices, which is based on a power transformation of CIR process. We show that the new model is tractable and we are able to derive the analytical solutions for future and future option prices. To enhance the model's ability to capture the prices spikes, we extend it to a time-changed model where the price is modelled by a nonlinear CIR process time changed by Levy subordinators. We employ the eigenfunction expansion methods to obtain the closed-form solutions for the derivatives. Our empirical study indicates the new models have the potential to capture the main features of electricity data better than the competing models.

A nonlinear diffusion model for electricity prices and derivatives

In this paper, we first develop a one-factor diffusion model for electricity prices, which is based on a power transformation of CIR process. We show that the new model is tractable and we are able to derive the analytical solutions for future and future option prices. To enhance the model's ability to capture the prices spikes, we extend it to a time-changed model where the price is modelled by a nonlinear CIR process time changed by Lévy subordinators. We employ the eigenfunction expansion methods to obtain the closed-form solutions for the derivatives. Our empirical study indicates the new models have the potential to capture the main features of electricity data better than the competing models.

Modeling liquidation risk with occupation times

In this paper, we develop a new structural model that allows for a distinction between default and liquidation to be made. Default occurs when firm’s asset value process crosses a bankruptcy barrier. Here, we do not assume that default immediately triggers liquidation. Instead, the firm is allowed to continue operating even if it is in default. Liquidation is triggered as soon as the firm’s asset value has cumulatively spent a prespecified amount of time below the default barrier or has dropped below the liquidation barrier. The proposed model includes the Black–Cox model as a limiting case. A semi-analytical formula of the liquidation probability is derived for the case where firm’s asset value follows a geometric Brownian motion. Nonlinear volatility diffusion models are discussed as well.

Diffusion-Controlled and Creep-Mitigated ASR Damage via Microplane Model. I: Mass Concrete

AbstractA diffusion-based and creep-based chemo-mechanical model for calculating the evolution of damage caused in concrete and concrete structures by the alkali-silica reaction (ASR) is developed. First the model of Bažant and Steffens for the diffusion controlled kinetics of ASR is reviewed and used to calculate the rate of production of the ASR gel within the aggregate. The next step is the formulation of a nonlinear diffusion model for the penetration of gel into the micropores and nanopores in a mineral aggregate grain, into the interface transition zone (ITZ) and into the nearby microcracks created in the cement paste of mortar. The gel that penetrates the pores and cracks in cement paste is considered to calcify promptly and stop expanding. A novel point, crucial for unconditional numerical stability of time step algorithm, is that the diffusion analysis is converted to calculating the pressure relaxation at constant gel mass during each time step, with sudden jumps between the steps. The gel expan...

Nonlinear diffusion model for annealed proton-exchanged waveguides in zirconium-doped lithium niobate.

Photorefractive-damage- (PRD) resistant zirconium-oxide-doped lithium niobate is investigated as a substrate for the realization of annealed proton-exchanged (APE) waveguides. Its advantages are a favorable distribution coefficient, PRD resistance comparable to magnesium-oxide-doped lithium niobate, and a proton-diffusion behavior resembling congruent lithium niobate. A 1D model for APE waveguides was developed based on a previous model for congruently melting lithium niobate. Evidence for a nonlinear index dependence on concentration was found.