Stability and convergence of sequential methods for coupled flow and geomechanics: Drained and undrained splits

We perform a stability and convergence analysis of sequential methods for coupled flow and geomechanics, in which the mechanics sub-problem is solved first. We consider slow deformations, so that inertia is negligible and the mechanical problem is governed by an elliptic equation. We use Biot’s self-consistent theory to obtain the classical parabolic-type flow problem. We use a generalized midpoint rule (parameter α between 0 and 1) time discretization, and consider two classical sequential methods: the drained and undrained splits.The von Neumann method provides sharp stability estimates for the linear poroelasticity problem. The drained split with backward Euler time discretization (α = 1) is conditionally stable, and its stability depends only on the coupling strength, and it is independent of time step size. The drained split with the midpoint rule (α = 0.5) is unconditionally unstable. The mixed time discretization, with α = 1.0 for mechanics and α = 0.5 for flow, has the same stability properties as the backward Euler scheme. The von Neumann method indicates that the undrained split is unconditionally stable when α ? 0.5.We extend the stability analysis to the nonlinear regime (poro-elastoplasticity) via the energy method. It is well known that the drained split does not inherit the contractivity property of the continuum problem, thereby precluding unconditional stability. For the undrained split we show that it is B-stable (therefore unconditionally stable at the algorithmic level) when α ? 0.5.We also analyze convergence of the drained and undrained splits, and derive the a priori error estimates from matrix algebra and spectral analysis. We show that the drained split with a fixed number of iterations is not convergent even when it is stable. The undrained split with a fixed number of iterations is convergent for a compressible system (i.e., finite Biot modulus). For a nearly-incompressible system (i.e., very large Biot modulus), the undrained split loses first-order accuracy, and becomes non-convergent in time.We also study the rate of convergence of both splits when they are used in a fully-iterated sequential scheme. When the medium permeability is high or the time step size is large, which corresponds to a high diffusion of pressure, the error amplification of the drained split is lower and therefore converges faster than the undrained split. The situation is reversed in the case of low permeability and small time step size.We provide numerical experiments supporting all the stability and convergence estimates of the drained and undrained splits, in the linear and nonlinear regimes. We also show that our spatial discretization (finite volumes for flow and finite elements for mechanics) removes the well-documented spurious instability in consolidation problems at early times.     

Computing Local Artin Maps,and Solvability of Norm Equations

Let L = K(α) be an Abelian extension of degree n of a number field K, given by the minimal polynomial of α over K. We describe an algorithm for computing the local Artin map associated with the extension L / K at a finite or infinite prime v of K. We apply this algorithm to decide if a nonzero a ∈ K is a norm from L, assuming that L / K is cyclic.     

Finite-state dimension and real arithmetic

We use entropy rates and Schur concavity to prove that, for every integer k ⩾ 2, every nonzero rational number q, and every real number α, the base-k expansions of α, q + α, and qα all have the same finite-state dimension and the same finite-state strong dimension. This extends, and gives a new proof of, Wall’s 1949 theorem stating that the sum or product of a nonzero rational number and a Borel normal number is always Borel normal.     

A new class of massively parallel direction splitting for the incompressible Navier–Stokes equations

We introduce in this paper a new direction splitting algorithm for solving the incompressible Navier–Stokes equations. The main originality of the method consists of using the operator (I ? ?_xx)(I ? ?_yy)(I ? ?_zz) for approximating the pressure correction instead of the Poisson operator as done in all the contemporary projection methods. The complexity of the proposed algorithm is significantly lower than that of projection methods, and it is shown the have the same stability properties as the Poisson-based pressure-correction techniques, either in standard or rotational form. The first-order (in time) version of the method is proved to have the same convergence properties as the classical first-order projection techniques. Numerical tests reveal that the second-order version of the method has the same convergence rate as its second-order projection counterpart as well. The method is suitable for parallel implementation and preliminary tests show excellent parallel performance on a distributed memory cluster of up to 1024 processors. The method has been validated on the three-dimensional lid-driven cavity flow using grids composed of up to 2 × 10⁹ points.     

A finite element method with discontinuous rotations for the Mindlin–Reissner plate model

We present a continuous-discontinuous finite element method for the Mindlin–Reissner plate model based on continuous polynomials of degree k ? 2 for the transverse displacements and discontinuous polynomials of degree k ? 1 for the rotations. We prove a priori convergence estimates, uniformly in the thickness of the plate, and thus show that locking is avoided. We also derive a posteriori error estimates based on duality, together with corresponding adaptive procedures for controlling linear functionals of the error. Finally, we present some numerical results.     

Modal analysis and modified cascade neural networks in identification of geometrical parameters of circular arches

A hybrid computational system, composed of the finite element method (FEM) and cascade neural network system (CNNs), is applied to the identification of three geometrical parameters of elastic arches, i.e. span l, height f and cross-sectional thickness h. FEM is used in the direct (forward) analysis, which corresponds to the mapping α = {l, f, h} → {ω_j}, where: α – vector of control parameters, ω_j – arch eigenfrequencies. The reverse analysis is related to the identification procedure in which the reverse mapping is performed {ω_j} → {α_i}. For the identification purposes a recurrent, three level CNNs of structure (D^k-H^k-1)_s was formulated, where: k – recurrence step, s = I, II, III-levels of cascade system. The Semi-Bayesian approach is introduced for the design of CNNs applying the MML Maximum Marginal Likelihood) criterion. The computation of hyperparameters is performed by means of the Bayesian procedure evidence. The numerical analysis proves a great numerical efficiency of the proposed hybrid approach for both the perfect (noiseless) values of eigenfrequencies and noisy ones simulated by an added artificial noise.     

A Hermite cubic collocation scheme for plane strain hydraulic fractures

We describe a novel cubic Hermite collocation scheme for the solution of the coupled integro-partial differential equations governing the propagation of a hydraulic fracture in a state of plane strain. Special blended cubic Hermite-power–law basis functions, with arbitrary index 0 < α < 1, are developed to treat the singular behavior of the solution that typically occurs at the tips of a hydraulic fracture. The implementation of blended infinite elements to model semi-infinite crack problems is also described. Explicit formulae for the integrated kernels associated with the cubic Hermite and blended basis functions are provided. The cubic Hermite collocation algorithm is used to solve a number of different test problems with two distinct propagation regimes and the results are shown to converge to published similarity and asymptotic solutions. The convergence rate of the cubic Hermite scheme is determined by the order of accuracy of the tip asymptotic expansion as well as the O(h⁴) error due to the Hermite cubic interpolation. The errors due to these two approximations need to be matched in order to achieve optimal convergence. Backward Euler time-stepping yields a robust algorithm that, along with geometric increments in the time-step, can be used to explore the transition between propagation regimes over many orders of magnitude in time.     

GPU-based parallel vertex substitution algorithm for the p-median problem

We introduce a GPU-based parallel vertex substitution (pVS) algorithm for the p-median problem using the CUDA architecture by NVIDIA. pVS is developed based on the best profit search algorithm, an implementation of vertex substitution (VS), that is shown to produce reliable solutions for p-median problems. In our approach, each candidate solution in the entire search space is allocated to a separate thread, rather than dividing the search space into parallel subsets. This strategy maximizes the usage of GPU parallel architecture and results in a significant speedup and robust solution quality. Computationally, pVS reduces the worst case complexity from sequential VS’s O(p · n²) to O(p · (n ? p)) on each thread by parallelizing computational tasks on GPU implementation. We tested the performance of pVS on two sets of numerous test cases (including 40 network instances from OR-lib) and compared the results against a CPU-based sequential VS implementation. Our results show that pVS achieved a speed gain ranging from 10 to 57 times over the traditional VS in all test network instances.     

Modelling damping ratio and shear modulus of sand–mica mixtures using genetic programming

This study presents two Genetic Programming (GP) models for damping ratio and shear modulus of sand–mica mixtures based on experimental results. The experimental database used for GP modelling is based on a laboratory study of dynamic properties of saturated coarse rotund sand and mica mixtures with various mix ratios under different effective stresses. In the tests, shear modulus, and damping ratio of the geomaterials have been measured for a strain range of 0.001% up to 0.1% using a Stokoe resonant column testing apparatus. The input variables in the developed NN models are the mica content, effective stress and strain, and the outputs are damping ratio and shear modulus. The performance of accuracies of proposed NN models are quite satisfactory (R² = 0.95 for damping ratio and R² = 0.98 for shear modulus).     

Hybrid real-coded genetic algorithm for data partitioning in multi-round load distribution and scheduling in heterogeneous systems

Data partitioning and scheduling is one the important issues in minimizing the processing time for parallel and distributed computing system. We consider a single-level tree architecture of the system and the case of affine communication model, for a general m processor system with n rounds of load distribution. For this case, there exists an optimal activation order, optimal number of processors m* (m * ≤ m), and optimal rounds of load distribution n* (n * ≤ n), such that the processing time of the entire processing load is a minimum. This is a difficult optimization problem because for a given activation order, we have to first identify the processors that are participating (in the computation process) in every round of load distribution and then obtain the load fractions assigned to them, and the processing time. Hence, in this paper, we propose a real-coded genetic algorithm (RCGA) to solve the optimal activation order, optimal number of processors m* (m * ≤ m), and optimal rounds of load distribution n* (n * ≤ n), such that the processing time of the entire processing load is a minimum. RCGA employs a modified crossover and mutation operators such that the operators always produce a valid solution. Also, we propose different population initialization schemes to improve the convergence. Finally, we present a comparative study with simple real-coded genetic algorithm and particle swarm optimization to highlight the advantage of the proposed algorithm. The results clearly indicate the effectiveness of the proposed real-coded genetic algorithm.     

Coarse-Grained Parallel Geometric Search

We present a parallel algorithm for solving thenext element search problemon a set of line segments, using a BSP-like model referred to as thecoarse grained multicomputer(CGM). The algorithm requiresO(1) communication rounds (h-relations withh=O(n/p)),O((n/p) log n) local computation, andO((n/p) log p) memory per processor, assumingn/p⩾p. Our result implies solutions to the point location, trapezoidal decomposition, and polygon triangulation problems. A simplified version for axis-parallel segments requires onlyO(n/p) memory per processor, and we discuss an implementation of this version. As in a previous paper by Develliers and Fabri (Int. J. Comput. Geom. Appl.6(1996), 487–506), our algorithm is based on a distributed implementation of segment trees which are of sizeO(n log n). This paper improves onop. cit.in several ways: (1) It studies the more general next element search problem which also solves, e.g., planar point location. (2) The algorithms require onlyO((n/p) log n) local computation instead ofO(log p*(n/p) log n). (3) The algorithms require onlyO((n/p) log p) local memory instead ofO((n/p) log n).     

Generalized Strong Pseudoprime Tests and Applications

We describe probabilistic primality tests applicable to integers whose prime factors are all congruent to 1 mod r where r is a positive integer;r =  2 is the Miller–Rabin test. We show that if ν rounds of our test do not find n ≠  =  (r +  1)²composite, then n is prime with probability of error less than (2 r) ^− ν. Applications are given, first to provide a probabilistic primality test applicable to all integers, and second, to give a test for values of cyclotomic polynomials.     

Computational assessment of several hydrogen-free high energy compounds

Tetrazino-tetrazine-tetraoxide (TTTO) is an attractive high energy compound, but unfortunately, it is not yet experimentally synthesized so far. Isomerization of TTTO leads to its five isomers, bond-separation energies were empolyed to compare the global stability of six compounds, it is found that isomer 1 has the highest bond-separation energy (1204.6 kJ/mol), compared with TTTO (1151.2 kJ/mol); thermodynamic properties of six compounds were theoretically calculated, including standard formation enthalpies (solid and gaseous), standard fusion enthalpies, standard vaporation enthalpies, standard sublimation enthalpies, lattice energies and normal melting points, normal boiling points; their detonation performances were also computed, including detonation heat (Q, cal/g), detonation velocity (D, km/s), detonation pressure (P, GPa) and impact sensitivity (h₅₀, cm), compared with TTTO (Q = 1311.01 J/g, D = 9.228 km/s, P = 40.556 GPa, h₅₀ = 12.7 cm), isomer 5 exhibites better detonation performances (Q = 1523.74 J/g, D = 9.389 km/s, P = 41.329 GPa, h₅₀ =  28.4 cm).     

Bounds for the Roots of Lacunary Polynomials

A polynomial P(X)  = X^d + a_d − 1X^d − 1 + ⋯ is called lacunary when a_d − 1 =  0. We give bounds for the roots of such polynomials with complex coefficients. These bounds are much smaller than for general polynomials.     

Inclusion complexation of pinostrobin with various cyclodextrin derivatives

Pinostrobin (PNS) is one of the important flavonoids and can be abundantly found in the rhizomes of fingerroot (Boesenbergia rotrunda) and galangal (Alpinia galangal and Alpinia officinarum), the herbal basis of Southeast Asian cooking. Similar to other flavonoids, PNS exhibits anti-oxidative, anti-inflammatory and anti-cancer properties. However, this compound has an extremely low water solubility that limits its use in pharmaceutical applications. Beta-cyclodextrin (βCD) and its derivatives, 2,6-dimethyl-βCD (2,6-DMβCD) and the three hydroxypropyl-βCDs (2-HPβCD, 6-HPβCD and 2,6-DHPβCD), have unique properties that enhance the stability and solubility of such low-soluble guest molecules. In the present study, molecular dynamics simulations were applied to investigate the dynamics and stability of PNS inclusion complexes with βCD and its derivatives (2,6-DMβCD, 2,6-DHPβCD, 2-HPβCD and 6-HPβCD). PNS was able to form complexes with βCD and all four of its derivatives by either the chromone (C-PNS) or phenyl (P-PNS) ring dipping toward the cavity. According to the molecular mechanics-generalized Born surface area binding free energy values, the stability of the different PNS/βCD complexes was ranked as 2,6-DHPβCD > 2,6-DMβCD > 2-HPβCD > 6-HPβCD > βCD. These theoretical results were in good agreement with the stability constants that had been determined by the solubility method.     

Fuzzy logic and statistical-based modelling of the Marshall Stability of asphalt concrete under varying temperatures and exposure times

In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modelled by using fuzzy logic and statistical method. This is an experimental study conducted using statistics and fuzzy logic methods. In order to investigate the Marshall Stability of asphalt concrete based on exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6 h and temperatures of 30, 40 and 50 °C were selected. The MS of the asphalt concrete at 17 °C (in laboratory environment temperature) was used as reference. The results showed that the MS of the asphalt core samples decreased 40.16% at 30 °C after 1.5 h and 62.39% after 6 h. At 40 °C the decrease was 74.31% after 1.5 h, and 78.10% after 6 h. At 50 °C the stability of the asphalt decreased 83.22% after 1.5 h, 88.66% after 6 h. The relationships between experimental results, fuzzy logic model and statistical results exhibited good correlation. The correlation coefficient was R = 0.99 for fuzzy logic model and R² = 0.9 for statistical method. Based on the results of the study, it could be said that both the fuzzy logic method and statistical methods could be used for modelling of the stability of asphalt concrete under varying temperature and exposure time.     

On reliability of the folded hypercubes

In this paper, we explore the 2-extra connectivity and 2-extra-edge-connectivity of the folded hypercube FQ_n. We show that κ₂(FQ_n) = 3n − 2 for n ⩾ 8; and λ₂(FQ_n) = 3n − 1 for n ⩾ 5. That is, for n ⩾ 8 (resp. n ⩾ 5), at least 3n − 2 vertices (resp. 3n − 1 edges) of FQ_n are removed to get a disconnected graph that contains no isolated vertices (resp. edges). When the folded hypercube is used to model the topological structure of a large-scale parallel processing system, these results can provide more accurate measurements for reliability and fault tolerance of the system.     

Guaranteed-quality all-quadrilateral mesh generation with feature preservation

In this paper, a quadtree-based mesh generation method is described to create guaranteed-quality, geometry-adapted all-quadrilateral (all-quad) meshes with feature preservation for arbitrary planar domains. Given point cloud, our method generates all-quad meshes with these points as vertices and all the angles are within [45°, 135°]. For given planar curves, quadtree-based spatial decomposition is governed by the curvature of the boundaries and narrow regions. 2-refinement templates are chosen for local mesh refinement without creating any hanging nodes. A buffer zone is created by removing elements around the boundary. To guarantee the mesh quality, the angles facing the boundary are improved via template implementation, and two buffer layers are inserted in the buffer zone. It is proved that all the elements of the final mesh are quads with angles between 45° ± ε and 135° ± ε (ε ≤ 5°) with the exception of badly shaped elements that may be required by the sharp angles in the input geometry. We also prove that the scaled Jacobians defined by two edge vectors are in the range of [sin(45° ? ε), sin90°], or [0.64, 1.0]. Furthermore, sharp features and narrow regions are detected and preserved automatically. Boundary layer meshes are generated by splitting elements of the second buffer layer. We have applied our algorithm to a set of complicated geometries, including the Lake Superior map and the air foil with multiple components.     

Some Applications of Magma in Designs and Codes: Oval Designs,Hermitian Unitals and Generalized Reed–Muller Codes

We describe three applications of Magma to problems in the area of designs and the associated codes:  •  Steiner systems, Hadamard designs and symmetric designs arising from an oval in an even-order plane, leading in the classical case to bent functions and difference-set designs;  •  the Hermitian unital as a 2-(q³ +  1, q +  1, 1) design, and the code overF_p where p divides q +  1;  •  a basis of minimum-weight vectors for the code over F_pof the design of points and hyperplanes of the affine geometry AG_d(F_p), where p is a prime.