Set Of Geometrical Parameters Research Articles

Rational ANCF Thin Plate Finite Element

In this paper, a rational absolute nodal coordinate formulation (RANCF) thin plate element is developed and its use in the analysis of curved geometry is demonstrated. RANCF finite elements are the rational counterpart of the nonrational absolute nodal coordinate formulation (ANCF) finite elements which employ rational polynomials as basis or blending functions. RANCF finite elements can be used in the accurate geometric modeling and analysis of flexible continuum bodies with complex geometrical shapes that cannot be correctly described using nonrational finite elements. In this investigation, the weights, which enter into the formulation of the RANCF finite element and form an additional set of geometric parameters, are assumed to be nonzero constants in order to accurately represent the initial geometry and at the same time preserve the desirable ANCF features, including a constant mass matrix and zero centrifugal and Coriolis generalized inertia forces. A procedure for defining the control points and weights of a Bezier surface defined in a parametric form is used in order to be able to efficiently create RANCF/ANCF FE meshes in a straightforward manner. This procedure leads to a set of linear algebraic equations whose solution defines the RANCF coordinates and weights without the need for an iterative procedure. In order to be able to correctly describe the ANCF and RANCF gradient deficient FE geometry, a square matrix of position vector gradients is formulated and used to calculate the FE elastic forces. As discussed in this paper, the proposed finite element allows for describing exactly circular and conic sections and can be effectively used in the geometry and analysis modeling of multibody system (MBS) components including tires. The proposed RANCF finite element is compared with other nonrational ANCF plate elements. Several numerical examples are presented in order to demonstrate the use of the proposed RANCF thin plate element. In particular, the FE models of a set of rational surfaces, which include conic sections and tires, are developed.

Context-sensitive spatiotemporal simulation model for movement

GIScience 2016 Short Paper Proceedings Context-sensitive spatiotemporal simulation model for movement S. Dodge Department of Geography, Environment, and Society, University of Minnesota Email: sdodge@umn.edu Abstract This paper presents a context-sensitive spatiotemporal model to simulate movement trajectories. The model incorporates both the correlated random walk and time-geography theories to generate a more realistic trajectory of an agent within its environment. 1. Introduction Movement is an essential form of temporal change that is an integral characteristic of dynamic entities (e.g. humans, animals, vehicles, diseases). It is the focus of research in a range of application domains such as transportation, movement ecology, environmental studies, and human health. Movement models help us to better understand the characteristics of movement, enable us to simulate movement and predict its patterns (Dodge 2016). Examples of existing movement models include the random walk and its variations (Codling et al. 2008, Technitis et al. 2015), time-geography (Miller 2005, Song and Miller 2014), and Brownian Bridge (Horne et al. 2007) models. These models either generate trajectories using a set of geometric movement parameters (turn angle, distance), or they identify a visitation probability surface for an agent considering its speed and time budget. Existing models often disregard the characteristics of the environment or the context within which the movement takes place. Simulation of movement in relation to its embedding context is an essential problem that is applied to generate trajectories to fill gaps in low-resolution tracking datasets, or to examine behavioral responses of moving agents to environmental changes. This paper introduces a context-sensitive spatiotemporal simulation model based on a correlated random walk with external biases and is controlled by time-geography constraints of the moving agent. The novelty of the model is that at each step the simulation is driven by behavior and the contextual factors (i.e. environment, geography) that influence the local movement of the agent. As a case study, this research uses GPS observations of a tiger to parameterize the model and to simulate the tiger’s movement between actual GPS observations. 2. Movement Simulation The overall goal is to generate a trajectory (a sequence of spatiotemporal points) from a start location and time !(# $ , & $ , ' $ ) to an end location and time )(# * , & * , ' * ). The simulation uses a correlated random walk from ! with an external bias to move towards ) (i.e. global constraints). The local movement at each step is driven by agent’s behavior and contextual factors. The model specifications are: (1) the maximum movement speed is determined by behavior (e.g. patrolling, hunting, foraging, biking), (2) the global movement path and speed are controlled by the actual time-budget to reach the end-point, and (3) the path is influenced by agent’s local choices based on context (environmental drivers and spatial constraints, -e.g. general movement direction, slope preferences, trail network). The simulation algorithm runs on regular time intervals defined by the user, named step time , to ensure the global movement occurs within the time-budget ('+ = ' * − ' $ ). The maximum speed of the agent (/ 012 ) is determined based on expert knowledge or derived

Modeling of single-lap composite adhesive joints under mechanical and thermal loads

Two-dimensional (plane-stress and plane-strain) theoretical models are presented for stress analysis of adhesively bonded single-lap composite joints subjected to either thermal or mechanical loading or a combination thereof. The joints consist of similar/dissimilar orthotropic or isotropic adherends and an isotropic adhesive interlayer. The governing differential equation of the problem is obtained using a variational method which minimizes the complementary strain energy in the bonded assembly. In this formulation, through-thickness variation of shear and peel stresses in the interlayer is considered. Both shear and normal traction-free boundary conditions are exactly satisfied. Peel and shear stresses obtained from plane-strain analytical models considering a homogeneous adhesive interlayer are in close agreement with those of the finite element predictions. A systematic parametric study is also conducted to identify an ideal set of geometric and material parameters for the optimal design of single-lap composite joints.

Fatigue tests and design of diamond bird-beak SHS T-joints under axial loading in brace

A diamond bird-beak square hollow section (SHS) T-joint is different from a conventional SHS T-joint as the brace and chord members both rotate 45°. This paper deals with fatigue behavior of such joints through fatigue tests and proposed fatigue design curves (Sr,hs–N curves). Diamond bird-beak SHS T-joints (DBB T-joints) with a unique set of geometric non-dimensional key parameters (β, 2γ and τ) were used for fatigue tests. Cracking patterns were observed during the fatigue tests. Based on the fatigue data and stress concentration factors (SCFs) derived by the authors of this paper, new fatigue design curves (Sr,hs–N curves) using hot spot stress concept were discussed by means of deterministic method and least-square method, respectively. Finally, fatigue strength was compared between DBB T-joints and conventional SHS T-joints. The results indicated that DBB T-joints have better fatigue behavior when β is not greater than 0.7.

Uncertainty propagation analysis in laminated structures with viscoelastic core

This paper investigates how uncertainties affect the modal parameters of a sandwich structure with a viscoelastic core, which is commonly used in both passive and hybrid control strategies. The viscoelastic sandwich structural component is modelled using (1) the classical model proposed by Mead and Markus and (2) a more complex model that has recently been proposed in the literature. The mechanical behaviour of the viscoelastic core is described by fractional derivative operators. The uncertainties are assumed to come from two sources. The first source of uncertainty is associated with the physical parameters of the constitutive model used to describe the dynamic behaviour of the viscoelastic core, which should be characterised when solving the inverse problem for model calibration. The second source is associated with a set of geometrical parameters and is considered to be linked to both manufacturing processes and assembling–disassembling structural set-ups. A set of examples is performed using the Monte Carlo Simulation analysis, allowing the measurement of the impact of typical sources of uncertainties in modal predictions as well as providing means to make a comparative analysis between two viscoelastic sandwich models. Among other conclusions, it was found that the mean values of the modal parameters do not change much for the different analyses performed, and the thickness of the viscoelastic layer is the most critical variable because it affects both the modal frequency and the damping ratio.

Simplified Approach to the Prediction and Analysis of Temperature Inhomogeneity in Rapid Compression Machines

Substantial progress has been made in understanding and reducing temperature inhomogeneity in rapid compression machines (RCMs) with the help of computational modeling. To date, however, it has not been possible to investigate and map the full range of possible RCM designs, working gases, and operating conditions. In this work, we present a framework which simplifies the task of comprehensive and general RCM performance prediction. A set of thermophysical and geometrical parameters has been defined to characterize the design and operating conditions of a general RCM. Dimensional analysis was applied to reduce the number of variables, and a sensitivity analysis, based on computational simulations, was used to rank the dimensionless parameters and eliminate unimportant ones. The results of this analysis show that Reynolds number, Prandtl number, aspect ratio, and crevice volume ratio are the most important parameters determining temperature inhomogeneity. A further set of computational simulations was conducted to predict postcompression temperature inhomogeneity over the full range of RCM design and operating parameters. These results are well-represented by a simple power-law equation that correlates a dimensionless temperature inhomogeneity parameter (mass-averaged over the main chamber) as a function of postcompression time with just three parameters—Peclet number (the product of Reynolds and Prandtl numbers), aspect ratio, and crevice volume ratio. This equation can serve as a simple and general tool for RCM designers and users who wish to determine optimal configurations that minimize temperature inhomogeneity for combustion experiments.

Computational modeling of structure formation during dielectrophoresis in particulate composites

In this paper a novel numerical model is proposed for qualitative simulation of the structure formation during dielectrophoresis in a medium of dielectric particles suspended in a liquid between parallel-plate electrodes. Upon application of an electric field particles reorient with respect to the imposed electric field, followed by rotational and axial displacement of particles interaction until chains are formed. The performance of the model is illustrated in a number of fundamental cases. The influence of parameters such as size, aspect ratio and heterogeneity of the particles is studied for the purpose of obtaining insight in the ideal conditions required to obtain the desired structure. In a multi-particle system, the relative particle size is shown to be a key parameter in chain evolution process. The quality of the structure evolution is investigated using a set of geometric parameters. A new topological parameter, chain perfection degree, relating the microstructure to the overall performance of the piezoelectric composite, is proposed and calculated for the fundamental case-studies.

On the plastic zone correction of a Zener–Stroh crack interacting with a nearby inhomogeneity and an edge dislocation

The investigation on the interaction among a Zener–Stroh crack, a nearby inhomogeneity/inclusion and an extra edge dislocation has been carried out. A Zener–Stroh crack is formed by pileup of net dislocations. With the existence of a nearby inclusion, an extra dislocation near the crack may be either absorbed into the crack (so the crack grows bigger) or repelled away by the crack and the inclusion. The result depends on the force on the dislocation from the crack and inclusion. In our current study, the plastic zone correction at the crack tips is adopted, where the plastic zone size (PZS) is determined by our newly developed generalized Irwin approach since the stress fields around the crack tips are mixed modes. With the distributed dislocation method, the expressions for the stress intensity factor, PZS and crack tip opening displacement (CTOD) are obtained for different sets of geometric and material parameters. Numerical examples show that when the extra single edge dislocation is located near the sharp tip of the Zener–Stroh crack, the normalized PZS and normalized CTOD become very sensitive to the position of the edge dislocation. It is also observed that the mixed mode problem usually has larger PZS and CTOD comparing to the pure mode I loading problem.

Morphometric structural diversity of a natural armor assembly investigated by 2D continuum strain analysis.

Many armored fish scale assemblies use geometric heterogeneity of subunits as a design parameter to provide tailored biomechanical flexibility while maintaining protection from external penetrative threats. This study analyzes the spatially varying shape of individual ganoid scales as a structural element in a biological system, the exoskeleton of the armored fish Polypterus senegalus (bichir). X-ray microcomputed tomography is used to generate digital 3D reconstructions of the mineralized scales. Landmark-based geometric morphometrics is used to measure the geometric variation among scales and to define a set of geometric parameters to describe shape variation. A formalism using continuum mechanical strain analysis is developed to quantify the spatial geometry change of the scales and illustrate the mechanisms of shape morphing between scales. Five scale geometry variants are defined (average, anterior, tail, ventral, and pectoral fin) and their functional implications are discussed in terms of the interscale mobility mechanisms that enable flexibility within the exoskeleton. The results suggest that shape variation in materials design, inspired by structural biological materials, can allow for tunable behavior in flexible composites made of segmented scale assemblies to achieve enhanced user mobility, custom fit, and flexibility around joints for a variety of protective applications.

The structure of the O2-N2O complex.

We have investigated the lowest energy structures and interaction energies of the oxygen nitrous oxide complex (O2-N2O) using explicitly correlated coupled cluster theory. We find that the intermolecular potential energy surface of O2-N2O is very flat, with two minima of comparable energy separated by a low energy first order saddle point. Our results are able to conclusively distinguish between the two sets of experimental geometric parameters for O2-N2O that were previously determined from rotationally resolved infrared spectra. The global minimum structure of O2-N2O is therefore found to be planar with a distorted slipped parallel structure. Finally, we show that the very flat potential energy surface of O2-N2O is problematic when evaluating vibrational frequencies with a numerical Hessian and that consideration should be given as to whether results might change if the step-size is varied.

Finite element model updating of a space vehicle first stage motor based on experimental test results

This paper discusses about a procedure to minimize the differences between analytical and experimental results of a space vehicle model by applying the finite element model updating procedure, in order to optimize the structures and processes before hardware is acquired. The material and geometric parameter set is formed for modal updating based on sensitivity analysis. Optimal values of experimental model parameters are determined using orthogonal array method. The updated finite element model produces more reliable results with the measured values. The method avoids irregularity and mismatch between the experimental and analytical model data sets, allowing flexible but automated model updating using neural network predicted parameters. The numerical results are compared with the experimental measurements and the divergences are measured by natural frequency difference and modal assurance condition. By training the neural network model based on the results and simultaneously adjusting the structural parameters, it is possible to reduce the difference between the measured and the predicted frequency values.

A quantum mechanics-based halogen bonding scoring function for protein-ligand interactions.

A quantum mechanics-based scoring function for halogen bonding interaction, namely XBScore(QM), is developed based on 18,135 sets of geometrical and energetical parameters optimized at M06-2X/aug-cc-pVDZ level. Applying the function on typical halogen bonding systems from Protein Data Bank demonstrates its strong ability of predicting halogen bonding as attractive interaction with strength up to -4kcal mol(-1). With a diverse set of proteins complexed with halogenated ligands, a systematic evaluation demonstrates the integrative advantage of XBScore(QM) over 12 other scoring functions on halogen bonding in four aspects, viz. pseudo docking power, ranking power, scoring power, and genuine docking power. Thus, this study not only provides a practicable scoring function of halogen bonding for high throughput virtual screening, but also serves as a benchmark for evaluating the performance of current scoring functions on characterizing halogen bonding.

3D analysis of paper microstructures at the scale of fibres and bonds

The evolution of paper microstructure parameters, such as porosity and fibre orientation, as a function of papermaking conditions is most often studied at a macroscopic scale. However, modelling the physical and mechanical properties of papers using upscaling approaches requires understanding the deformation micro-mechanisms that are induced by papermaking operations within the structure of paper fibrous networks for individual fibres and fibre-to-fibre bonds. We addressed this issue by analysing three-dimensional images of model papers. These images were obtained using X-ray microtomography. The model papers were fabricated by varying forming, pressing, and drying conditions. For each image, this analysis enabled an unprecedented large set of geometrical parameters to be measured for individual fibres (centreline, shape and inclination of the fibre cross sections) and fibre-to-fibre bonds (inter-bond distance, number of bonds per unit length of fibre, bond surface area) within the fibrous networks. The evolution of the as-obtained microstructure parameters was analysed as a function of papermaking conditions. All results were in accordance with the data available in the literature. A key result was obtained for the evolution of the number of fibre-to-fibre contacts per fibre as a function of the network density. A representative number of contacts was obtained using relatively small imaged volumes. These volumes must only contain enough fibre segments the cumulated length of which is of the same order as the mean fibre length. These results were also used to validate microstructure models for the prediction of the number of fibre-to-fibre contacts within fibrous networks.

Gene expression models for prediction of longitudinal dispersion coefficient in streams

Summary Longitudinal dispersion is the key hydrologic process that governs transport of pollutants in natural streams. It is critical for spill action centers to be able to predict the pollutant travel time and break-through curves accurately following accidental spills in urban streams. This study presents a novel gene expression model for longitudinal dispersion developed using 150 published data sets of geometric and hydraulic parameters in natural streams in the United States, Canada, Europe, and New Zealand. The training and testing of the model were accomplished using randomly-selected 67% (100 data sets) and 33% (50 data sets) of the data sets, respectively. Gene expression programming (GEP) is used to develop empirical relations between the longitudinal dispersion coefficient and various control variables, including the Froude number which reflects the effect of reach slope, aspect ratio, and the bed material roughness on the dispersion coefficient. Two GEP models have been developed, and the prediction uncertainties of the developed GEP models are quantified and compared with those of existing models, showing improved prediction accuracy in favor of GEP models. Finally, a parametric analysis is performed for further verification of the developed GEP models. The main reason for the higher accuracy of the GEP models compared to the existing regression models is that exponents of the key variables (aspect ratio and bed material roughness) are not constants but a function of the Froude number. The proposed relations are both simple and accurate and can be effectively used to predict the longitudinal dispersion coefficients in natural streams.

Comparing the Mixing Performance of Common Types of Chaotic Micromixers: A Numerical Study

High-efficiency micromixers are of critical importance in several industrial applications. Implementing chaotic advection to passively enhance fluid mixing is a well-established technique. The purpose of the present study is to compare different configurations of passive mixers. Six different microchannel designs, commonly used in the majority of mixing applications, were numerically evaluated in the present study. Both two-dimensional and three-dimensional serpentine-type microchannel designs were investigated. For each design, the effect of geometrical parameters was studied using a commercial computational fluid dynamics code. Results are presented in terms of mixing efficiency and pressure drop. It is revealed that increasing the flow path by providing compact fluid passages is not the only way to achieve better mixing; inducing a helical flow along the flow length has an additional benefit in improving the mixing performance. The results of this study can be used as a basis for further improving the design of micromixers, while they can also provide the engineers with guiding principles, not for selecting the optimum set of geometrical parameters for a specific microchannel design but for screening out the least efficient micromixer configurations.

2D photonic-crystal optomechanical nanoresonator.

We present the optical optimization of an optomechanical device based on a suspended InP membrane patterned with a 2D near-wavelength grating (NWG) based on a 2D photonic-crystal geometry. We first identify by numerical simulation a set of geometrical parameters providing a reflectivity higher than 99.8% over a 50-nm span. We then study the limitations induced by the finite value of the optical waist and lateral size of the NWG pattern using different numerical approaches. The NWG grating, pierced in a suspended InP 265-nm thick membrane, is used to form a compact microcavity involving the suspended nanomembrane as an end mirror. The resulting cavity has a waist size smaller than 10μm and a finesse in the 200 range. It is used to probe the Brownian motion of the mechanical modes of the nanomembrane.

Design and characterization of an assembly to obtain a linkage pivot by crimping process

The purpose of this research is to design and test a linkage pivot assembled by metal forming process. The assembly is obtained by crimping a tubular component onto a cylindrical grooved component using an experimental instrumented device. The quality of the linkage pivot is evaluated by a pullout test which measures the force required to break or dismantle the assembly. The study is focused on analysing the effect of the main process parameter (i.e. the crimping depth) and geometrical parameters (i.e. the tubular component thickness and the groove radius). For one set of geometrical parameters, an appropriate crimping depth leading to the maximum assembly strength and assembly stiffness is determined. The study of the geometrical parameters shows that the tubular component thickness and the groove radius do not affect much the assembly strength. However, the tubular component thickness affects considerably the forming load, the assembly stiffness and the failure mode. According to the obtained results, one set of parameters that meets industrial requirements is selected to design the linkage pivot.

A Mathematical Method for Eliminating Spin Losses in Toroidal Traction Drives

The efficiency of the original Toroidal continuously variable transmission (CVT) is limited due to the spin losses caused by the different speed distribution in the contact area. To overcome this drawback, this paper replaces the original working surface with a new surface derived from a differential equation and proposes a novel Logarithmic CVT. Equations and ranges of the transmission ratio range, half-cone-angle, and conformity ratio, which are essential geometrical parameters of the Logarithmic CVT, are derived. A set of geometrical parameters is further recommended. With such geometrical parameters, the transmission ratio range of the Logarithmic CVT is as wide as that of the Half-Toroidal CVT. The two types of CVTs are compared with each other in terms of efficiency based on a widely accepted computational model. The results show that efficiency of the Logarithmic CVT is higher than that of Half-Toroidal CVT except for some particular situations because of the thrust bearing losses.

Development of methods of carrying out experimental research of measurement errors for sets of geometrical parameters on NC equipment as in the case of a turbine disk

The technique of experimental studies of measurement error groups of geometrical parameters on CNC equipment on example radial-angular positions of turbine disk is developed. This technique consists of a series of successive stages: analysis of parts and groups of geometric parameters; calibration of the measurement system; binding to the details; selection of the measurement cycle; development of the control program to be measured; measurements on CNC equipment and KIM; comparison of measurement results; error analysis, the establishment of their causes and the proposal to reduce them. For the analysis of obtained results is used a statistical method for determining the total error. The random component was evaluated by multiple repetition of the process of measuring the centering holes on CNC equipment and statistical processing of the results. The systematic error was estimated by comparing the data obtained as a result of control on CNC equipment with reference values. As reference data taken measurements on coordinate-measuring machine Global Performance 07.10.07. Control radial-angular arrangement centering holes turbine disk is possible using standard measuring cycle equipment. It is worth noting the dependence of the accuracy of measurement of the nominal angle of the dowel holes. With the increase in the angle measurement error increases. This technique is universally applicable to the measurement of many geometric parameters of the different parts.

Prediction of minimum factor of safety against slope failure in clayey soils using artificial neural network

This paper presents prediction of minimum factor of safety (FS) against slope failure in clayey soils using artificial neural network (ANN). Two multilayer perceptron ANN models were used to predict the minimum factor of safety using different data sets of geometric and shear strength parameters and based on the four well-known methods of Fellenius (Ordinary), Bishop, Janbu, and Spencer, respectively. The input parameters used to train and test the two ANN models include the reciprocal of slope tangent β, angle of internal friction of soil φ (o), height of the slope H (m), cohesion of the soil c (kN/m2), unit weight of the soil γ (kN/m3) and the stability number m (c/γH). The output parameter for both ANN is the FS of the slope. The number of hidden layers and the number of neurons in each hidden layer were determined by trial and error to achieve the best results. It is observed that both ANN predictions are very close to the FS calculated by each of the corresponding four methods, separately. However, the ANN model with the scaled down number of input parameters showed better performance and the best one has a normalized mean square error of 0.0073, mean absolute percent error (MAPE) of 1.52 % and correlation coefficient (r) of 0.9966. It is concluded that such ANN models are reliable, simple and valid computational tools for predicting the FS and for assessing the stability of slopes of clayey soil. Six known case studies that are based on different methods were used to further test and validate the accuracy of the ANN model. It was observed that the ANN model predictions of FS of the case studies were very accurate with MAPE of 3.72 % for all methods combined. Based on the developed ANN model, a parametric study was then carried out to investigate the influence of the slope angle (β), stability number (m) and angle of internal friction (φ) on the factor of safety and slope stability of clayey soil.