Minimization Principles Research Articles

Galerkin Kantorovich Method for Solving the Terzaghi’s One-Dimensional Soil Consolidation Equation

This paper presents the Galerkin-Kantorovich variational method for solving the Terzaghi’s one-dimensional consolidation equation for two-way drainage conditions. The solution was considered as an infinite series of known coordinate (shape) functions and unknown function of time which we sought such that the resulting functional is minimized. The shape functions satisfied the hydraulic boundary conditions at the boundary of the consolidating soil. Galerkin-Kantorovich variational integral equation was thus formulated for the initial boundary value problem using residual minimization principles. The solution resulted in a system of first order ordinary differential equations in which was solved for Orthogonalization principles were used to obtain the integration constants in terms of initial pore water pressure, thus yielding the general solution. Solutions for constant initial excess pore water pressure were obtained and found to be the closed-form solution. The solutions were presented in terms of global (average) degrees of consolidation and tabulated. The results obtained were exact and identical with results previously found using separation of variables techniques.

Formation Mechanism and Morphology Evolution of β-NaYF4 Single Microcrystals in Hydrothermal Process

Lanthanide-doped upconversion (Ln-doped UC) materials with predicable phase and geometry are attractive for their promising application in optics and biological. Herein, we report a facile strategy for deterministic synthesis of β-NaYF4 microcrystals by an ethylenediaminetetraacetic acid (EDTA) assisted hydrothermal process. The nucleation and growth process of the β-NaYF4 microcrystals have been experimentally revealed with different hydrothermal times. The phase and geometry of as-obtained crystals can be well manipulated by the experimental parameters such as pH values, precursors’ ratio, and reactant concentrations. The formation and morphology evolution mechanism of β-NaYF4 single microcrystals can be qualitatively analyzed using energy minimization principles under the thermodynamic and kinetic control. In addition, we presented the colour-changing up-conversion of Tm3+ and Yb3+ doped single β-NaYF4 microrod. Our work could help the understanding on crystal growth and design of rare earth fluoride mateirals at micro and nanoscale.

Minimization principle for hemivariational–variational inequality driven by uniformly monotone operators with application to problems in contact mechanics

In this paper, we consider hemivariational–variational inequalities driven by uniformly monotone or d-monotone operators in Banach spaces. We establish related minimization principles leading to the existence and uniqueness of solutions to the inequality considered as well as we suggest the Ritz type numerical approximations. The theoretical results obtained are next applied to some problems inspired by models from contact mechanics.

Revisiting the Young’s model for ferrofluid droplets: Magnetowetting or magneto-dewetting?

Magnetic field-mediated wetting of ferrofluid droplets has emerged to be of fundamental importance because of its plethora of applications ranging from chemical and biomolecular analysis to soft robotics and medical imaging. However, while extensive studies continue to be reported on the underlying experimental facets, a fundamental theoretical depiction of the observed contact angle variation with the applied magnetic field remains grossly elusive, as attributable to a complex dependence of the induced magnetization on the droplet’s intrinsic magnetic properties. Circumventing these constraints, here we put forward a first-principle analytical model that delineates the variation in the contact angle as a function of an applied magnetic field on a sessile ferrofluid droplet, by appealing to energy minimization principles. One key feature of our analysis is the consideration of the local magnetization as a function of the magnetic field itself, resulting in a new contribution to the interfacial energy by virtue of normal traction at the droplet's contact with its non-magnetic surroundings. This theory is supported by experiments identified in prior research to elucidate the fundamental physics of relevance. Our results highlight the substantial influence of the saturation magnetization and the initial susceptibility of the ferrofluid on the resulting contact angle alterations, as well as possible non-trivial routes of highly selective and precise enhancement or attenuation in the extent of wetting. These findings are likely to be of fundamental importance towards establishing the design foundations of portable magnetic resonance imaging devices, micromixers, and microreactors, magnetically-manipulated automatic control of soft fluidic matters, among others.

Experimental validation of the brachistochrone curve

We built a simple, cheap and accessible experiment to study the motion of spherical beads through three different curves, one of them being the curve of fastest descent, or brachistochrone. Despite the absence of a no-friction constraint and the rolling of the beads, our experimental findings consistently support the conclusion that the brachistochrone path remains the fastest. We perform a numerical simulation to confront with experiments and obtain that the values are in agreement, with ttheory=0.237 s, and t‾braq=0.25±0.03 s. This simple system not only serves as a practical demonstration of minimization principles but can also inspire and engage students in high schools and colleges interested in physics.

A Formulation of Structural Design Optimization Problems for Quantum Annealing

We present a novel formulation of structural design optimization problems specifically tailored to be solved by qa. Structural design optimization aims to find the best, i.e., material-efficient yet high-performance, configuration of a structure. To this end, computational optimization strategies can be employed, where a recently evolving strategy based on quantum mechanical effects is qa. This approach requires the optimization problem to be present, e.g., as a qubo model. Thus, we develop a novel formulation of the optimization problem. The latter typically involves an analysis model for the component. Here, we use energy minimization principles that govern the behavior of structures under applied loads. This allows us to state the optimization problem as one overall minimization problem. Next, we map this to a qubo problem that can be immediately solved by qa. We validate the proposed approach using a size optimization problem of a compound rod under self-weight loading. To this end, we develop strategies to account for the limitations of currently available hardware. Remarkably, for small-scale problems, our approach showcases functionality on today’s hardware such that this study can lay the groundwork for continued exploration of qa’s impact on engineering design optimization problems.

Rate-independent gradient-enhanced crystal plasticity theory — Robust algorithmic formulations based on incremental energy minimization

Numerically robust algorithmic formulations suitable for rate-independent crystal plasticity are presented. They cover classic local models as well as gradient-enhanced theories in which the gradients of the plastic slips are incorporated by means of the micromorphic approach. The elaborated algorithmic formulations rely on the underlying variational structure of (associative) crystal plasticity. To be more precise and in line with so-called variational constitutive updates or incremental energy minimization principles, an incrementally defined energy derived from the underlying time-continuous constitutive model represents the starting point of the novel numerically robust algorithmic formulations. This incrementally defined potential allows to compute all variables jointly as minimizers of this energy. While such discrete variational constitutive updates are not new in general, they are considered here in order to employ powerful techniques from non-linear constrained optimization theory in order to compute robustly the aforementioned minimizers. The analyzed prototype models are based on (1) nonlinear complementarity problem (NCP) functions as well as on (2) the augmented Lagrangian formulation. Numerical experiments show the numerical robustness of the resulting algorithmic formulations. Furthermore, it is shown that the novel algorithmic ideas can also be integrated into classic, non-variational, return-mapping schemes.

Effective operators and their variational principles for discrete electrical network problems

Using a Hilbert space framework inspired by the methods of orthogonal projections and Hodge decompositions, we study a general class of problems (called Z-problems) that arise in effective media theory, especially within the theory of composites, for defining the effective operator. A new and unified approach is developed, based on block operator methods, for obtaining solutions of the Z-problem, formulas for the effective operator in terms of the Schur complement, and associated variational principles (e.g., the Dirichlet and Thomson minimization principles) that lead to upper and lower bounds on the effective operator. In the case of finite-dimensional Hilbert spaces, this allows for a relaxation of the standard hypotheses on positivity and invertibility for the classes of operators usually considered in such problems by replacing inverses with the Moore–Penrose pseudoinverse. As we develop the theory, we show how it applies to the classical example from the theory of composites on the effective conductivity in the periodic conductivity problem in the continuum (2d and 3d) under the standard hypotheses. After that, we consider the following three important and diverse examples (increasing in complexity) of discrete electrical network problems in which our theory applies under the relaxed hypotheses. First, an operator-theoretic reformulation of the discrete Dirichlet-to-Neumann (DtN) map for an electrical network on a finite linear graph is given and used to relate the DtN map to the effective operator of an associated Z-problem. Second, we show how the classical effective conductivity of an electrical network on a finite linear graph is essentially the effective operator of an associated Z-problem. Finally, we consider electrical networks on periodic linear graphs and develop a discrete analog to the classical example of the periodic conductivity equation and effective conductivity in the continuum.

Forecasting education expenditure with a generalized conformable fractional-order nonlinear grey system model

As an important human capital investment, education is an effective means to improve the comprehensive quality of people. Education expenditure is an important material guarantee for the development of educational undertakings. Education expenditure data is highly susceptible to numerous economic and social factors that complicate its nonlinear structure. In order to model the complex nonlinear problems of the system, this paper proposes a generalized conformable fractional-order nonlinear grey prediction model for the first time by analyzing the traditional time series-based modeling method in a nonlinear grey domain. The proposed model expands on the classical grey Bernoulli model by introducing the generalized conformable fractional accumulation as a new accumulation generator and utilizes error minimization principles in the modeling process. By altering the optimal order of the model and the cumulative generation operator, this model can adapt to various time series and reduce errors. Finally, the model is applied to education expenditure forecasting, and it is proved that the proposed model achieved good results and has higher accuracy than other models.

On variational–hemivariational inequalities in Banach spaces

This paper is devoted to a well-posedness analysis of elliptic variational–hemivariational inequalities in Banach spaces. The differential operator associated with the variational–hemivariational inequality is assumed to be strongly monotone of a general order, in contrast to that in the majority of existing references on this subject where the differential operator is assumed to be strongly monotone of order 2. Moreover, the solution existence is proved with an approach more accessible to applied mathematicians and engineers, instead of through an abstract surjectivity result for pseudomonotone operators in existing references. Equivalent minimization principles are established for certain variational–hemivariational inequalities, which are valuable for developing efficient numerical algorithms. The theoretical results are applied to the analysis of a mixed hemivariational inequality in the study of a generalized Newtonian fluid flow problem involving a nonsmooth slip boundary condition of friction type. Existence and uniqueness of both the velocity and pressure unknowns are shown for the mixed hemivariational inequalities.

Level-set topology optimization for Ductile and Brittle fracture resistance using the phase-field method

This work presents a rigorous mathematical formulation for topology optimization of a macro structure undergoing ductile failure. The prediction of ductile solid materials which exhibit dominant plastic deformation is an intriguingly challenging task and plays an extremely important role in various engineering applications. Here, we rely on the phase-field approach to fracture which is a widely adopted framework for modeling and computing the fracture failure phenomena in solids. The first objective is to optimize the topology of the structure in order to minimize its mass, while accounting for structural damage. To do so, the topological phase transition function (between solid and void phases) is introduced, thus resulting in an extension of all the governing equations. Our second objective is to additionally enhance the fracture resistance of the structure. Accordingly, two different formulations are proposed. One requires only the residual force vector of the deformation field as a constraint, while in the second formulation, the residual force vector of the deformation and phase-field fracture simultaneously have been imposed. An incremental minimization principles for a class of gradient-type dissipative materials are used to derive the governing equations. Thereafter, to obtain optimal topology to enhance the structural resistance due to fracture, the level-set-based formulation is formulated. The level-set-based topology optimization is employed to seek an optimal layout with smooth and clear boundaries. Sensitivities are derived using the analytical gradient-based adjoint method to update the level-set surface for both formulations. Here, the evolution of the level-set surface is realized by the reaction–diffusion equation to maximize the strain energy of the structure while a certain volume of design domain is prescribed. Several three-dimensional numerical examples are presented to substantiate our algorithmic developments.

The universal law of the front speed close to the disappearance of bistability

Multistable systems present rich dynamical behaviors of interfaces between the different equilibria. Close to the disappearance of bistability, i.e., transition between a bistable to a monostable region, we show that the speed of bistable fronts follows a square root law as a function of the bifurcation parameter. Analytically and numerically, we show this law for different prototype models of bistable systems. Based on a liquid crystal light valve experiment with optical feedback, we investigate the front speed close to the disappearance of bistability. Our results apply both to systems that do or do not follow energy minimization principles. Experimental findings show a quite fair agreement with the theoretical results.

Gradient damage model for ductile fracture introducing degradation of damage hardening modulus: implementation and experimental investigations

This study presents a gradient damage model for ductile fracture, in which the damage hardening modulus is degraded by the accumulation of plastic deformation and the volume expansion caused by negative hydrostatic pressure. The proposed model fulfills the thermodynamic requirements, and the governing equations are derived from energy minimization principles. Two parameter studies are carried out to confirm the basic performance of the proposed model, in which some typical ductile fracture responses are demonstrated by changing parameters for degrading the damage hardening modulus. Also, a series of numerical experiments are presented to reveal the ability of the proposed model to successfully simulate the fracture tests of advanced high strength steel sheets with different tensile strengths. It is indeed confirmed by the close agreement with experimental results that the proposed model is capable of realizing the breaking elongation, the transitional behavior from unstable to stable crack propagations, and the corresponding load–displacement curves. Also, the model successfully reproduces and predicts the crack initiation positions in notched specimens with different notch radii.

On generalizing trace minimization principles

Various trace minimization principles have interplayed with numerical computations for the standard eigenvalue and generalized eigenvalue problems in general, as well as important applied eigenvalue problems including the linear response eigenvalue problem from electronic structure calculation and the symplectic eigenvalue problem of positive definite matrices that play important roles in classical Hamiltonian dynamics, quantum mechanics, and quantum information, among others. In this paper, Ky Fan's trace minimization principle is extended along the line of the Brockett cost function tr(DXHAX) in X on the Stiefel manifold, where D of an apt size is positive definite. Specifically, we investigate infX⁡tr(DXHAX) subject to XHBX=Ik (the k×k identity matrix) or XHBX=Jk, where Jk=diag(±1). We establish conditions under which the infimum is finite and when it is finite, analytic solutions are obtained in terms of the eigenvalues and eigenvectors of the matrix pencil A−λB, where B is possibly indefinite and possibly singular, and D is also possibly indefinite.

Probabilistic failure mechanisms via Monte Carlo simulations of complex microstructures

A probabilistic approach to phase-field brittle and ductile fracture with random material and geometric properties is proposed within this work. In the macroscopic failure mechanics, materials properties and spatial quantities (of different phases in the geometrical domain) are assumed to be homogeneous and deterministic. This is unlike the lower scale with strong fluctuation in the material and geometrical properties. Such a response is approximated through some uncertainty in the model problem. The presented contribution is devoted to providing a mathematical framework for modeling uncertainty through stochastic analysis of a microstructure undergoing brittle/ductile failure. Hereby, the proposed model employs various representative volume elements with random distribution of stiff inclusions and voids within the composite structure. We develop an allocating strategy to allocate the heterogeneities and generate the corresponding meshes in two- and three-dimensional cases. Then the Monte Carlo Finite Element Method (MC-FEM) is employed for solving the stochastic PDE-based model and approximate the expectation and the variance of the solution field of brittle/ductile failure by evaluating a large number of samples. For the prediction of failure mechanisms, we rely on the phase-field approach which is a widely adopted framework for modeling and computing the fracture phenomena in solids. Incremental perturbed minimization principles for a class of gradient-type dissipative materials are used to derive the perturbed governing equations. This analysis enables us to study the highly heterogeneous microstructure and monitor the uncertainty in failure mechanics. Several numerical examples are given to examine the efficiency of the proposed method.

Random Interference Signal Decomposition and the Normalized Filtering Method of an Optical Fiber Current Transducer

Focusing on the problem of characteristic decomposition and filtering of random interference information measured by an optical fiber current transducer (OFCT), a signal filtering algorithm by combing complete ensemble empirical mode decomposition (CEEMD) with normalized autocorrelation function, is proposed. The CEEMD feature decomposition model of the OFCT signal is established and multiple eigenmode functions of the measured signal are extracted. The normalized autocorrelation function models of different types of intrinsic mode function (IMF) are established. By extracting the characteristics of the autocorrelation function, high-weight IMFs are selected. After the mean filtering process is performed on other IMFs, the signal reconstruction is performed together with the effective modal components. With the premise of signal statistical learning and structural risk minimization principles, a support vector regression model is established to classify the data by linear fitting. The more reliable current information after filtered is obtained. Experiment results demonstrate that the proposed signal filtering algorithm by combining the advantages of CEEMD and normalized autocorrelation function decomposes the signal according to the time-scale characteristics of OFCT data itself, without pre-setting any basis functions. The root mean square error of optimized data is reduced by 39.3%, and the signal quality is greatly improved.

Ekeland variational principle and its equivalents in T 1-quasi-uniform spaces

The present paper is concerned with the Ekeland Variational Principle (EkVP) and its equivalents (Caristi–Kirk fixed point theorem, Takahashi minimization principle, Oettli-Théra equilibrium version of EkVP) in quasi-uniform spaces. These extend some results proved by Hamel and Löhne [A minimal point theorem in uniform spaces. In: Nonlinear analysis and applications: to V. Lakshmikantham on his 80th birthday. Vols 1, 2. Dordrecht: Kluwer Academic Publishers; 2003. p. 577–593] and Hamel [Equivalents to Ekeland's variational principle in uniform spaces. Nonlinear Anal. 2005;62:913–924] in uniform spaces, as well as those proved in quasi-metric spaces by various authors. The case of F-quasi-gauge spaces, a non-symmetric version of F-gauge spaces introduced by Fang [The variational principle and fixed point theorems in certain topological spaces. J Math Anal Appl. 1996;202:398–412], is also considered. The paper ends with the quasi-uniform versions of some minimization principles proved by Arutyunov and Gel'man [The minimum of a functional in a metric space, and fixed points. Zh Vychisl Mat Mat Fiz. 2009;49:1167–1174] and Arutyunov [Caristi's condition and existence of a minimum of a lower bounded function in a metric space. Applications to the theory of coincidence points. Proc Steklov Inst Math. 2015;291(1):24–37] in complete metric spaces.

Well-posedness analysis of a stationary Navier\u2013Stokes hemivariational inequality

This paper provides a well-posedness analysis for a hemivariational inequality of the stationary Navier-Stokes equations by arguments of convex minimization and the Banach fixed point. The hemivariational inequality describes a stationary incompressible fluid flow subject to a nonslip boundary condition and a Clarke subdifferential relation between the total pressure and the normal component of the velocity. Auxiliary Stokes hemivariational inequalities that are useful in proving the solution existence and uniqueness of the Navier–Stokes hemivariational inequality are introduced and analyzed. This treatment naturally leads to a convergent iteration method for solving the Navier–Stokes hemivariational inequality through a sequence of Stokes hemivariational inequalities. Equivalent minimization principles are presented for the auxiliary Stokes hemivariational inequalities which will be useful in developing numerical algorithms.

Minimization arguments in analysis of variational–hemivariational inequalities

In this paper, an alternative approach is provided in the well-posedness analysis of elliptic variational–hemivariational inequalities in real Hilbert spaces. This includes the unique solvability and continuous dependence of the solution on the data. In most of the existing literature on elliptic variational–hemivariational inequalities, well-posedness results are obtained by using arguments of surjectivity for pseudomonotone multivalued operators, combined with additional compactness and pseudomonotonicity properties. In contrast, following (Han in Nonlinear Anal B Real World Appl 54:103114, 2020; Han in Numer Funct Anal Optim 42:371–395, 2021), the approach adopted in this paper is based on the fixed point structure of the problems, combined with minimization principles for elliptic variational–hemivariational inequalities. Consequently, only elementary results of functional analysis are needed in the approach, which makes the theory of elliptic variational–hemivariational inequalities more accessible to applied mathematicians and engineers. The theoretical results are illustrated on a representative example from contact mechanics.

The mixed Deep Energy Method for resolving concentration features in finite strain hyperelasticity

The introduction of Physics-informed Neural Networks (PINNs) has led to an increased interest in deep neural networks as universal approximators of PDEs in the solid mechanics community. Recently, the Deep Energy Method (DEM) has been proposed. DEM is based on energy minimization principles, contrary to PINN which is based on the residual of the PDEs. A significant advantage of DEM, is that it requires the approximation of lower order derivatives compared to formulations that are based on strong form residuals. However both DEM and classical PINN formulations struggle to resolve fine features of the stress and displacement fields, for example concentration features in solid mechanics applications. We propose an extension to the Deep Energy Method (DEM) to resolve these features for finite strain hyperelasticity. The developed framework termed mixed Deep Energy Method (mDEM) introduces stress measures as an additional output of the NN to the recently introduced pure displacement formulation. Using this approach, Neumann boundary conditions are approximated more accurately and the accuracy around spatial features which are typically responsible for high concentrations is increased. In order to make the proposed approach more versatile, we introduce a numerical integration scheme based on Delaunay integration, which enables the mDEM framework to be used for random training point position sets commonly needed for computational domains with stress concentrations, i.e. domains with holes, notches, etc. We highlight the advantages of the proposed approach while showing the shortcomings of classical PINN and DEM formulations. The method is offering comparable results to Finite-Element Method (FEM) on the forward calculation of challenging computational experiments involving domains with fine geometric features and concentrated loads, but additionally offers unique capabilities for the solution of inverse problems and parameter estimation in the context of hyperelasticity.