Conventional Numerical Approaches Research Articles

Modeling of Coplanar Interdigital Capacitor for Microwave Microfluidic Application

Due to its noninvasive property, the interdigital capacitor (IDC) has been applied in dielectric liquid detection and characterization. In order to integrate the IDC sensor on a lab-on-chip, it is often required to minimize and optimize the sensor for sensitive and efficient performance. However, the conventional numerical simulation approach is quite time-consuming. Therefore, an efficient analytical method is proposed herein, leading to accurate capacitance and conductance expressions of an arbitrary multilayer-structured IDC. The model is validated with practical measurements of a series of coplanar waveguide (CPW) structure-based IDCs. In addition, an accurate characterization function, which relates the IDC capacitance and conductance to the complex permittivity of a material loaded on the top of the IDC sensing area, is obtained. The characterization function shows good agreement with the finite-element method (FEM) simulation results, which demonstrates the capability of the IDC sensor in dielectric spectroscopy measurements of $\mu \text{L}$ and even nL liquids.

Fast and accurate ray-casting-based view factor estimation method for complex geometries

The concept of view factor has various applications in engineering problems, ranging from heat management to bifacial photovoltaics. Analytical solutions for view factor calculations are difficult to obtain and normally numerical methods are used. For complex geometries, when several surfaces are arbitrarily arranged in a three-dimensional environment, conventional numerical approaches such as Monte Carlo method will take a lot of simulation time. To tackle this challenge, we have developed a simple and yet accurate view factor estimation method based on ray-casting. In our method, the view factor is determined by sending out rays, evenly distributed in all directions from the target surface, and consequently counting the number of rays intercepted by each of the other surfaces present in the environment under study. Then, a simple algebraic procedure enables the estimation of a large number of view factors simultaneously. The results have been compared with exact and numerical solutions, proving that we have devised a fast and accurate view factor estimation method. This can be used to determine the view factors in environments generated via Light Detection And Ranging (LiDAR). The method has the potential to be applied in several scientific researches and engineering studies including heat transfer and solar energy.

The application of distinct lattice spring model to zonal disintegration within deep rock masses

Zonal disintegration has been frequently encountered in many tunnelling projects such as deep mining and water tunnels in hydropower stations. The mechanisms of this phenomenon cannot be explained reasonably through conventional mesh-based numerical approaches. Thus, in this study, a dual coupled Micro-Macro Continuum-Discontinuum approach named as Distinct Lattice Spring Model (DLSM) has been applied to investigate the mechanisms of zonal disintegration within deep rock masses. Firstly, the 3D numerical modes are built up, with fixed boundaries being set for far fields and displacement loading being applied along the tunnel axis. This numerical mode is then validated through comparing model simulation with laboratory model tests, where reasonable agreement has been achieved for all cases considered (normal rock mass and layered rock mass with different joint spaces). To cater for real tunnels within various rock masses, tunnels excavated in deep rock masses with different sizes, shapes and material heterogeneities are investigated. Numerical study demonstrates that, the DLSM is capable to reproduce the process of zonal disintegration explicitly, along with which the mechanical responses have been captured reasonably. It shows that, the occurrence of zonal disintegration mainly depends on the material heterogeneities and the in-suite stress level. The fracture patterns formed during zonal disintegration rely on tunnels’ shape, size and the distribution of local weakness in surrounding rock masses.

A Perspective of Conventional and Bio-inspired Optimization Techniques in Maximum Likelihood Parameter Estimation

Maximum likelihood estimation is a method of estimating the parameters of a statistical model in statistics. It has been widely used in a good many multi-disciplines such as econometrics, data modelling in nuclear and particle physics, and geographical satellite image classification, and so forth. Over the past decade, although many conventional numerical approximation approaches have been most successfully developed to solve the problems of maximum likelihood parameter estimation, bio-inspired optimization techniques have shown promising performance and gained an incredible recognition as an attractive solution to such problems. This review paper attempts to offer a comprehensive perspective of conventional and bio-inspired optimization techniques in maximum likelihood parameter estimation so as to highlight the challenges and key issues and encourage the researches for further progress.

Narrow-band topology optimization on a sparsely populated grid

A variety of structures in nature exhibit sparse, thin, and intricate features. It is challenging to investigate these structural characteristics using conventional numerical approaches since such features require highly refined spatial resolution to capture and therefore they incur a prohibitively high computational cost. We present a novel computational framework for high-resolution topology optimization that delivers leaps in simulation capabilities, by two orders of magnitude, from the state-of-the-art approaches. Our technique accommodates computational domains with over one billion grid voxels on a single shared-memory multiprocessor platform, allowing automated emergence of structures with both rich geometric features and exceptional mechanical performance. To achieve this, we track the evolution of thin structures and simulate its elastic deformation in a dynamic narrow-band region around high-density sites to avoid wasted computational effort on large void regions. We have also designed a mixed-precision multigrid-preconditioned iterative solver that keeps the memory footprint of the simulation to a compact size while maintaining double-precision accuracy. We have demonstrated the efficacy of the algorithm through optimizing a variety of complex structures from both natural and engineering systems.

A Perspective of Conventional and Bio-inspired Optimization Techniques in Maximum Likelihood Parameter Estimation

Maximum likelihood estimation is a method of estimating the parameters of a statistical model in statistics. It has been widely used in a good many multi-disciplines such as econometrics, data modelling in nuclear and particle physics, and geographical satellite image classification, and so forth. Over the past decade, although many conventional numerical approximation approaches have been most successfully developed to solve the problems of maximum likelihood parameter estimation, bio-inspired optimization techniques have shown promising performance and gained an incredible recognition as an attractive solution to such problems. This review paper attempts to offer a comprehensive perspective of conventional and bio-inspired optimization techniques in maximum likelihood parameter estimation so as to highlight the challenges and key issues and encourage the researches for further progress.

A Novel Fractional Tikhonov Regularization Coupled with an Improved Super-Memory Gradient Method and Application to Dynamic Force Identification Problems

This paper presents a novel inverse technique to provide a stable optimal solution for the ill-posed dynamic force identification problems. Due to ill-posedness of the inverse problems, conventional numerical approach for solutions results in arbitrarily large errors in solution. However, in the field of engineering mathematics, there are famous mathematical algorithms to tackle the ill-posed problem, which are known as regularization techniques. In the current study, a novel fractional Tikhonov regularization (NFTR) method is proposed to perform an effective inverse identification, then the smoothing functional of the ill-posed problem processed by the proposed method is regarded as an optimization problem, and finally a stable optimal solution is obtained by using an improved super-memory gradient (ISMG) method. The result of the present method is compared with that of the standard TR method and FTR method; new findings can be obtained; that is, the present method can improve accuracy and stability of the inverse identification problem, robustness is stronger, and the rate of convergence is faster. The applicability and efficiency of the present method in this paper are demonstrated through a mathematical example and an engineering example.

Low-cost multiband compact branch-line coupler design using response features and automated EM model fidelity adjustment

Design closure of compact microwave components is a challenging problem because of significant electromagnetic (EM) cross-couplings in densely arranged layouts. A separate issue is a large number of designable parameters resulting from replacement of conventional transmission line sections by compact microstrip resonant cells. This increases complexity of the design optimization problem and requires employment of expensive high-fidelity EM analysis for reliable performance evaluation of the structure at hand. Consequently, neither conventional numerical optimization algorithms nor interactive approaches (e.g., experience-driven parameters sweeps) are capable of identifying optimum designs in reasonable timeframes. Here, we discuss application of feature-based optimization for fast design optimization of dual- and multiband compact couplers. On one hand, design of such components is difficult because of multiple objectives (achieving equal power split and good matching and port isolation for all frequency bands of interest). On the other hand, because of well-defined shapes of the S-parameter responses for this class of components, feature-based optimization seems to be well suited to control multiple figures of interest as demonstrated in this work. Two-level EM modeling is used for further design cost reduction. More importantly, we develop a procedure for automated determination of the low-fidelity EM model coarseness that allows us to find the fastest possible model that still ensures sufficient correlation with its high-fidelity counterpart, which is critical for robustness of the optimization process. Our approach is illustrated using two dual-band compact couplers. Experimental validation is also provided.

Strength predictions of clear wood at multiple scales using numerical limit analysis approaches

This work aims at a new approach for understanding failure mechanisms and predicting wood strengths, which are strongly influenced by the complex hierarchical material system of wood. Thus, a mechanical concept, where different microstructural characteristics are incorporated, appears to be necessary, based on the division of wood into meaningful scales of observation. At each scale, effective strength properties are to be determined and a multiscale approach needs to be applied, for which conventional numerical methods appear to be inefficient. In this work, numerical limit analysis approaches are further developed and applied for the first time to wood, complementing conventional methods successfully at certain scales of observation in a multiscale ‘damage’ approach.Limit analysis belongs to the group of direct plastic analysis methods, focusing exclusively on the time instant of structural collapse, and delivering the ultimate strength. Compared with conventional numerical approaches that have previously been applied to wood, limit analysis approaches are much more stable and efficient.In this work, orthotropic failure criteria and periodic boundary conditions are implemented into both lower bound and upper bound numerical limit analysis formulations. As numerical results, effective failure surfaces are obtained at both annual ring scale and clear wood scale. A validation at clear wood scale indicates that this new approach is very promising.

Closed-Form Solution of Large Deflected Cantilever Beam a gainst Follower Loading Using Complex Analysis

The literature reveals that the non-conservative deflection of an elastic cantilever beam caused by applying follower tip loading was investigated and solved by various numerical methods like: Runge Kutta, iterative shooting, finite element, finite difference, direct iterative and non-iterative numerical methods. This is due to the fact that the Euler–Bernoulli nonlinear differential equation governing the problem contains the “slope at the free end”, this slope however needs special numerical treatment. On the other hand, some of these methods fail to find numerical solutions for extremely large loading conditions. Hence, this paper is aimed to obtain a closed-form solution for solving the large deflection of a cantilever beam opposed to a concentrated point follower load at its free end. This closed-form solution when compared with other conventional numerical approaches is characterized by simplicity, stability and straightforwardness in getting the beam deflection and slopes even for extremely large loading conditions. The closed-form solution is obtained by applying complex analysis along with elliptic-integral approach. Very good results were obtained when the elastica of the beam compared with that of various numerical methods which are used in analyzing similar problem.

Robust numerical phase stabilization for long-range swept-source optical coherence tomography.

A novel phase stabilization technique is demonstrated with significant improvement in the phase stability of a micro-electromechanical (MEMS) vertical cavity surface-emitting laser (VCSEL) based swept-source optical coherence tomography (SS-OCT) system. Without any requirements of hardware modifications, the new fully numerical phase stabilization technique features high tolerance to acquisition jitter, and significantly reduced budget in computational effort. We demonstrate that when measured with biological tissue, this technique enables a phase sensitivity of 89 mrad in highly scattering tissue, with image ranging distance of up to 12.5 mm at A-line scan rate of 100.3 kHz. We further compare the performances delivered by the phase-stabilization approach with conventional numerical approach for accuracy and computational efficiency. Imaging result of complex signal-based optical coherence tomography angiography (OCTA) and Doppler OCTA indicate that the proposed phase stabilization technique is robust, and efficient in improving the image contrast-to-noise ratio and extending OCTA depth range. The proposed technique can be universally applied to improve phase-stability in generic SS-OCT with different scale of scan rates without a need for special treatment.

A Hybrid Method for Calculating the Coupling to PCB Inside a Nested Shielding Enclosure Based on Electromagnetic Topology

Conventional analytical and numerical approaches are inefficient for the analysis of electromagnetic (EM) coupling effect on a printed circuit board (PCB) in complicated electric systems. This paper develops a hybrid method based on the combination of electromagnetic topology and analytical method or full-wave simulation. A coupling mechanism of PCB in a nested shielding enclosure is established, and the EM interactions from exterior fields to interior PCB are determined by the way of conductive and radiation coupling interference. The total load disturbance voltage of PCB trace is obtained by solving the BLT equation of the two interference paths. In this paper, the full-wave simulation method is adopted to calculate the electric field and numerical integration method is applied to solve the BLT equation. The results of the proposed method are in good agreement with the result of a commercial full-wave tool, which confirms its validity. Compared to numerical simulation, the proposed method simplifies the modeling process significantly and possesses better efficiency.

Particle swarm optimization for numerical bifurcation analysis in computational inelasticity

SummaryAn efficient and robust algorithm to numerically detect material instability or bifurcation is of great importance to the understanding and simulation of material failure in computational and applied mechanics. In this work, an intelligence optimizer, termed the particle swarm optimization, is introduced to the numerical solution of material bifurcation problem consisting of finding the bifurcation time as well as the corresponding bifurcation directions. The detection of material bifurcation is approached as a constrained minimization problem where the determinant of the acoustic tensor is minimized. The performance of the particle swarm optimization method is tested through numerical bifurcation analysis on both small and finite deformation material models in computational inelasticity with increasing complexity. Compared with conventional numerical approaches to detect material bifurcation, the proposed method demonstrates superior performance in terms of both computational efficiency and robustness. Copyright © 2016 John Wiley & Sons, Ltd.

Efficient Estimation of the Probability of Small-Disturbance Instability of Large Uncertain Power Systems

This paper proposes a methodology to efficiently estimate the probability of small-disturbance rotor angle instability of uncertain power systems. Traditional Monte Carlo (MC) approaches are computationally intensive and inefficient, particularly when used to study low probability conditions which result in small disturbance instabilities and develop into serious outage events high impact. The proposed methodology uses importance sampling to focus on conditions which contain the high information content required to make relevant decisions about low probability events. Latin hypercube sampling (LHS) is used to efficiently bound the search space and identify operating conditions leading to a marginally stable or unstable system response. The proposed approach is demonstrated on a model of a multi-area transmission network with a significant capacity of intermittent generation connected through a multi-terminal voltage source converter-based high voltage direct current (VSC-HVDC) grid. It is demonstrated that the methodology yields accurate results with just a small fraction of the sample points required using a conventional numerical MC approach.

The Interaction of the Plane Stress Mode I Crack with an Inhomogeneity Undergoing a Stress-Free Transformation Strain

Thin composite films containing inclusions are commonly being developed as corrosion resistant, wear resistant coatings and so forth. For systems where the composite film is under residual stresses properly designed, a controlled debonding process of the inclusions can be used to reduce the stress levels in the film lowering the risk of through cracks in the film as well as the risk for the film's delamination from the substrate. In this paper, on the basis of the Eshelby equivalent inclusion theory, a general solution is derived by treating an inhomogeneous inclusion as a homogeneous one with transformation strain for the configuration force (CF) and stress intensity factor (SIF) between mode I crack and an inhomogeneous inclusion of arbitrary shape which undergoes some degree of stress-free transformation strain under plane stress loading conditions. Then the CF associated with the transformation is calculated from the work done during the transformation, from which some simplified approximate formulae are also presented for common inclusion shapes in order to provide a quick estimate for the effects of inclusion shape, location and size on the CF of plane stress model I crack. In comparison to conventional numerical approaches, the present solution provides a novel approach to explain the behavior of crack deflection/penetration and can be used for the optimization design of the composite films.

The platform pitching motion of floating offshore wind turbine: A preliminary unsteady aerodynamic analysis

The flow-field around the rotor blades of an FOWT may be significantly influenced by the six rigid-body motions of the floating platform via the blade–wake interaction. Therefore, the accurate prediction of unsteady aerodynamic load which is calculated by many conventional numerical approaches is still questionable for an FOWT. In this study, the periodic pitching motion of the rotating turbine blades due to the floating platform motion is considered to investigate the effects of vortex–wake–blade interaction for the aerodynamic performance of an FOWT. The unsteady computational fluid dynamics (CFD) simulations based on the dynamic mesh technique were applied for analyzing the pitching motion of wind turbine due to the platform motion. The in-house unsteady blade element momentum code using the direct local relative velocity approach was also applied to simulate the unsteady aerodynamic performance. The equivalent average velocity approach which simplifies the relative velocity contribution due to the platform motion was proposed and incorporated to the in-house code. It is shown that the unsteady aerodynamic loads of the floating offshore wind turbine become sensitively changed due to the variation of frequency and amplitude of the platform motion. Additionally, there are strong flow interaction phenomena between the rotating blades with oscillating motions and generated blade-tip vortices.

FSI 해석법을 이용한 고속 주축계의 열특성 해석

FSI (Fluid Structure Interaction) method, in this study, has been applied to analyzing thermal characteristics of a high speed machine tool spindle system. The spindle is composed of angular contact ceramic ball bearings, a high speed built-in motor, a cooling jacket, and so on. The cooling jacket has three inlets and outlets. Using the FSI method, temperature distributions and thermal displacements of the spindle system were computed considering the heating of the front and rear bearings and the built-in motor. The results computed using the FSI method were compared with those determined by experiment and using the conventional numerical approach. The results determined using the FSI method were similar to those from the conventional numerical approach but showed better agreement with the experimental results. Therefore, it is concluded that the FSI method is useful for analyzing the thermal characteristics of high speed spindles and can be applied to the design of high speed spindles.

Measurement of properties of graphene sheets subjected to drilling operation using computer simulation

Drilling being one of the primary machining processes find wide spread applications in manufacturing of functional components. Optimization of drilling process performance requires critical understanding of process parameters which govern the mechanism of drilling process. Machining process at nanoscale level has been studied extensively using numerical modeling approaches owing to complexity in conducting experiments at nanoscale level. In this paper, we propose a new evolutionary approach based on multi-gene genetic programming (MGGP) to numerically model the drilling process of graphene sheet, a two dimensional nanoscale material. The performance of our proposed MGGP model is compared with that of the artificial neural network (ANN) and we observe that our predictions are well in agreement with the data obtained using conventional numerical approach for modeling machining process of nanoscale materials. We anticipate that our proposed MGGP model can find applications in optimizing the machining processes of nanoscale materials.

Buoyancy-driven fluid flow and heat transfer in a square cavity with a wavy baffle—Meshless numerical analysis

Abstract The meshless local Petrov–Galerkin method is implemented to simulate the buoyancy-driven flow and heat transfer in a differentially-heated enclosure having a baffle attached to its higher temperature side wall. To execute the proposed numerical treatment, the stream function–vorticity formulation is employed and a unity weighting function is applied for the weak form of the governing equations. In this meshless numerical approach, the field variables are approximated using the MLS interpolation technique. Being attested through comparing the results of two test case simulations with the results of either an analytical or a conventional numerical approach, the MLPG method is applied to investigate the buoyancy-driven flow and heat transfer in the baffled cavity. The present analyses involve a parametric study to implicate the effects of the baffle undulation number, amplitude, location on the wall, and the system Rayleigh number. The investigation reveals the eminent participation of the baffle in transferring heat from the hot wall. The analyses disclose an increase of the hot wall average Nusselt number by elevating the location of the baffle on the hot wall. This average Nusselt number descends with increasing the baffle amplitude. The cold wall average Nusselt number increases as the baffle number of undulation augments.

PMO-241 Conveying medication benefits to ulcerative colitis patients: what thresholds for adherence are applied?

IntroductionNon-adherence to maintenance 5-ASA occurs in at least 30% of ulcerative colitis (UC) patients and is associated with adverse health outcomes and increased healthcare expenditure. Targeted strategies to convey information...