Traditional Analytical Models Research Articles

ИНФОРМАЦИОННАЯ РЕВОЛЮЦИЯ: СРЕДСТВА АНАЛИЗА И ПРОГНОЗИРОВАНИЯ.ИНСТРУМЕНТЫ ПРИКЛАДНОГО АНАЛИЗА ИНФОРМАЦИОННОЙ РЕВОЛЮЦИИ И НЕКОТОРЫЕ РЕЗУЛЬТАТЫ ИХ ИСПОЛЬЗОВАНИЯ

В статье рассматривается применение традиционных инструментов анализа технологических революций: технологии общего назначения, 4-круговой модели инноваций, S-образной кривой к анализу информационной революции, разворачивающейся в настоящее время. Демонстрируется объясняющая и прогностическая сила этих аналитических инструментов для исследования данной проблемы. В частности, демонстрируются требования к промышленной политике, положительно влияющие на информационную революцию. The paper describes application of traditional analytical models of technology change – General Purpose Tecnhology, Saarbrücken model of technology transfer, S-shaped curve for current information revolution analysis. Analytical and prognostical power of the above mentioned instruments is demonstrated. In particular the paper is focused on the industrial policy features, which can speed up progress in implementation of the new wave of technologies.

Reducing dissipation in piezoelectric flexural microplate resonators in liquid environments

While piezoelectric microplates are emerging as a promising MEMS liquid-based sensing platform, often acoustic radiation losses limit device performance. This paper presents a new analysis of microplate acoustic radiation losses through the use of traditional analytical models for the fundamental mode and a new finite element model that is used to analyze trends affecting Q for both the fundamental and higher order flexural modes. Results from these models are compared with experimental measurements of frequency and Q measured using both electrical characterization and the laser Doppler vibrometer for multiple modes of the microplate in water as compared to air and vacuum. Finally, a microplate mode with a high initial Q of around 150 in air and that demonstrates an increase in Q going from air to water is presented as a strong candidate for use in droplet based sensing applications.

A continuum model for tension-compression asymmetry in skeletal muscle.

Experiments on passive skeletal muscle on different species show a strong asymmetry in the observed tension-compression mechanical behavior. This asymmetry shows that the tension modulus is two orders of magnitude higher than the compression modulus. Until now, traditional analytical constitutive models have been unable to capture that strong asymmetry in anisotropic solids using the same material parameters. In this work we present a model which is able to accurately capture five experimental tests in chicken pectoralis muscle, including the observed tension-compression asymmetry. However, aspects of the anisotropy of the tissue are not captured by the model.

Full-field modal analysis during base motion excitation using high-speed 3D digital image correlation

In recent years, many efforts have been made to exploit full-field measurement optical techniques for modal identification. Three-dimensional digital image correlation using high-speed cameras has been extensively employed for this purpose. Modal identification algorithms are applied to process the frequency response functions (FRF), which relate the displacement response of the structure to the excitation force. However, one of the most common tests for modal analysis involves the base motion excitation of a structural element instead of force excitation. In this case, the relationship between response and excitation is typically based on displacements, which are known as transmissibility functions. In this study, a methodology for experimental modal analysis using high-speed 3D digital image correlation and base motion excitation tests is proposed. In particular, a cantilever beam was excited from its base with a random signal, using a clamped edge join. Full-field transmissibility functions were obtained through the beam and converted into FRF for proper identification, considering a single degree-of-freedom theoretical conversion. Subsequently, modal identification was performed using a circle-fit approach. The proposed methodology facilitates the management of the typically large amounts of data points involved in the DIC measurement during modal identification. Moreover, it was possible to determine the natural frequencies, damping ratios and full-field mode shapes without requiring any additional tests. Finally, the results were experimentally validated by comparing them with those obtained by employing traditional accelerometers, analytical models and finite element method analyses. The comparison was performed by using the quantitative indicator modal assurance criterion. The results showed a high level of correspondence, consolidating the proposed experimental methodology.

An Intelligent Design Model for the Thin-Walled Steel Perforated Member

The analysis of perforated steel members is a 3D problem in nature, there still exist many difficulties for the traditional analytical expressions to be used in the perforated steel member design. The proliferation of industrial “Big-Data” has created many new opportunities for those working in science, engineering and business. Computational intelligence technology from industrial big data can provide a more effective help for decision-making of enterprises’ innovative design. This paper describes work that aims to use neural network technology to establish an intelligent design model for prediction of the ultimate load of thin-walled steel perforated sections. Compared with those of the traditional analytical model, the intelligent design model for the solving the hard problem of complex steel perforated sections is very promising.

Discontinuous Galerkin deterministic solvers for a Boltzmann–Poisson model of hot electron transport by averaged empirical pseudopotential band structures

The purpose of this work is to incorporate numerically, in a discontinuous Galerkin (DG) solver of a Boltzmann–Poisson model for hot electron transport, an electronic conduction band whose values are obtained by the spherical averaging of the full band structure given by a local empirical pseudopotential method (EPM) around a local minimum of the conduction band for silicon, as a midpoint between a radial band model and an anisotropic full band, in order to provide a more accurate physical description of the electron group velocity and conduction energy band structure in a semiconductor. This gives a better quantitative description of the transport and collision phenomena that fundamentally define the behavior of the Boltzmann–Poisson model for electron transport used in this work. The numerical values of the derivatives of this conduction energy band, needed for the description of the electron group velocity, are obtained by means of a cubic spline interpolation. The EPM-Boltzmann–Poisson transport with this spherically averaged EPM calculated energy surface is numerically simulated and compared to the output of traditional analytic band models such as the parabolic and Kane bands, numerically implemented too, for the case of 1D n+−n−n+ silicon diodes with 400 and 50 nm channels. Quantitative differences are observed in the kinetic moments related to the conduction energy band used, such as mean velocity, average energy, and electric current (momentum), as well as the IV-curves.

Parameters controlling pressure and fracture behaviors in field injectivity tests: A numerical investigation using coupled flow and geomechanics model

Field injectivity tests are widely used in the oil and gas industry to obtain key formation characteristics. The prevailing approaches for injectivity test interpretation rely on traditional analytical models. A number of parameters may affect the test results and lead to interpretation difficulties. Understanding their impacts on pressure response and fracture geometry of the test is essential for accurate test interpretation. In this work, a coupled flow and geomechanics model is developed for numerical simulation of field injectivity tests. The coupled model combines a cohesive zone model for simulating fluid-driven fracture and a poro-elastic/plastic model for simulating formation behavior. The model can capture fracture propagation, fluid flow within the fracture and formation, deformation of the formation, and evolution of pore pressure and stress around the wellbore and fracture during the tests. Numerical simulations are carried out to investigate the impacts of a multitude of parameters on test behaviors. The parameters include rock permeability, the leak-off coefficient of the fracture, rock stiffness, rock toughness, rock strength, plasticity deformation, and injection rate. The sensitivity of pressure response and fracture geometry on each parameter is reported and discussed. The coupled flow and geomechanics model provides additional advantages in the understanding of the fundamental mechanisms of field injectivity tests.

A fast semi-analytical model for the slotted structure of induction motors

A fast, semi-analytical model for induction motors (IMs) is presented. In comparison to traditional analytical models for IMs, such as lumped parameter, magnetic equivalent circuit and anisotropic layer models, the presented model calculates a continuous distribution of the magnetic flux density in the air gap and both the stator and rotor slots of the IM. Due to its semi-analytical nature, the computation time of the model is short in comparison to finite element analysis (FEA) simulations. However, the curved shapes of typical IM slots require a suitable representation of each slot in polar coordinates. Two different polar slot representations are investigated and it is shown that a double region representation is favorable to a single region representation. Finally, the model is implemented for four different benchmark motors. The calculation results are shown to be in good agreement with linear 2D FEA simulation results. This makes the model a suitable candidate for fast design tools.

A coupled dynamics, multiple degree of freedom process damping model, Part 1: Turning

Self-excited vibration, or chatter, is an important consideration in machining operations due to its direct influence on part quality, tool life, and machining cost. At low machining speeds, a phenomenon referred to as process damping enables stable cutting at higher depths of cut than predicted with traditional analytical models. This paper describes an analytical stability model which includes a process damping force that is dependent on the surface normal velocity, chip width, cutting speed, and an empirical process damping coefficient. Model validation is completed using time domain simulation and turning experiments. The results indicate that the multiple degree of freedom model is able to predict the stability boundary using a single process damping coefficient.

A coupled dynamics, multiple degree of freedom process damping model, Part 2: Milling

Self-excited vibration, or chatter, is an important consideration in machining operations due to its direct influence on part quality, tool life, and machining cost. At low machining speeds, a phenomenon referred to as process damping enables stable cutting at higher depths of cut than predicted with traditional analytical models. This paper describes an analytical stability model for milling operations which includes a process damping force that depends on the surface normal velocity, depth of cut, cutting speed, and an empirical process damping coefficient. Model validation is completed using time domain simulation and milling experiments. The results indicate that the multiple degree of freedom model is able to predict the stability boundary using a single process damping coefficient.

Strength check of a three-row roller slewing bearing based on a mixed finite element model

For the two failure modes of a three-row roller slewing bearing, ring fracture and raceway spalling, a method for checking the strength of a slewing bearing through finite element analysis is proposed. This method calculates the internal stress distribution of the bearing rings by using the mixed finite element model with both solid elements and spring elements of the slewing bearing assembly and checks the bearing structural strength by using the maximum internal stress of the bearing rings. The method also calculates the contact stress between the roller and raceways by using the entity contact model between the roller and the raceways; the obtained maximum contact stress is used to check the contact strength of the slewing bearing. The proposed mixed finite element model considers the structural deformation of the bearing rings, and the calculated results can reflect the real situation more accurately than the traditional analytical model with the hypothesis of rigid ring. The proposed method also avoids the solution problem, which has large-scale calculation and difficulty of convergence of the entity finite element model of a slewing bearing, and the calculation efficiency is improved effectively. The calculated results by mixed finite element model are consistent with the failure mode of this type of slewing bearing in engineering practice.

Comprehensive methodology for detecting fracture aperture in naturally fractured formations using mud loss data

Abstract When encountered with naturally fractured formations, the knowledge of the location and the aperture of the fractures intersecting the wellbore has a strong technical and economical impacts on drilling engineering, oil production and reservoir management strategies. So far no method has been well-developed for predicting fracture aperture to optimize particle size of lost circulation materials (LCMs) based on mud loss data, which is the primary source of information retrieved from the drilling process. The typical curve in traditional analytical model, which has been the predominant tool in the assessment of fracture aperture in the past several decades, has two major deficiencies: (1) no consideration of the mechanical properties of fracture and (2) incapable of providing accurate fracture aperture in the case of fracture networks. Based on the mathematic model previously published in JPSE (Xia et al., 2015. J. Pet. Sci. Eng. 129, 254–267), this paper develops a methodology that optimizes the fracture characteristics based on recording mud loss data. The methodology poses the prediction problem as history matching, where the outer optimization shell involves the length and the aperture of the fractures intersecting the wellbore. The proposed methodology systematically integrates a Fracture Generation Module, a Mud Loss Simulator, and a Global Optimization Module. The suggested methodology is automated and accurate for field development. We end this paper with some case studies to illustrate the applicability of this methodology.

Toward Closing the Loop between Infrastructure Investments and Societal and Economic Impacts

The long-term value proposition of transportation infrastructure investments can be significantly distorted if the short-term effects of spatial externalities on land use patterns, economic expansions, and migration patterns are not properly included in the analysis. Some of these effects occur over a short period of time and soon after the investment materializes, whereas others take longer and follow more steady patterns. In this article, we develop a novel dynamical model of a primal society with constructs that are specifically geared toward transportation infrastructure expansions and investments. The model quantifies the impact of these expansions on some key performance indicators and on the overall utility and production capacity of the society. We argue that traditional analytical models that work on the premises of stationary behavior and a static response of society to changes in infrastructure do not correctly capture these effects. The land use patterns and spatial expansion computed from the model are validated against existing theory on land use. Preliminary results on how to use the model for value proposition analysis are also presented using simple case studies.

The Temporal Characteristic of Human Mobility: Modeling and Analysis of Social Worm Propagation

A common view of modeling social worm propagation is topology construction for social networking layer and human behavior modeling for message checking activity. However, due to the existence of human mobility behavior, traditional analytical models have not been suitable for the propagation dynamics of social worms nowadays, which results in underestimating the scale of infected network and lacking a comprehensive and accurate abstraction for human behaviors. This letter proposes a novel model to understand the propagation dynamics of social worms in hierarchical networks based on the temporal characteristic of human mobility. We characterize the infection scale and the spread speed for social worms adopting discrete model and difference-equation method. Our simulations and analysis show our model to approximate the complicated propagation behaviors of social worms more accurately, and we give two quantitative conclusions on the range of final infection scale and the fastest spread speed. In addition, the results indicate the rationality and validity of our conclusions.

Improved time-varying mesh stiffness model of cracked spur gears

Based on our previous work (Ma et al., 2014, Engineering Failure Analysis, 44, 179–194), this paper presents an improved analytical model (IAM) for the time-varying mesh stiffness (TVMS) calculation of cracked spur gears. In the improved analytical model, the calculation error of TVMS under double-tooth engagement due to repeatedly considering the stiffness of the fillet-foundation is revised, and the effects of reduction of fillet-foundation stiffness of cracked gears and extended tooth contact (ETC) are also considered, which have a great influence on TVMS, especially under the condition of large torques and crack levels. Moreover, the comparisons among the IAM, traditional analytical model (TAM) and finite element (FE) model are also carried out under different torques and crack depths. IAM is also verified by comparing TVMS and vibration responses obtained by FE model, which can be considered as a gauge to evaluate the calculation error. The results show that the maximum error of IAM is about 12.04%, however, that of TAM can be up to 32.73%.

Extracting Modal Parameters of a Layered Stone Pagoda Using TDD Technique

This work introduces a modal testing and analysis results of the mock-up for a layered stone pagoda. The pagoda has been horizontally excited by an impact hammer. As to the measured acceleration time responses, the first five lower mode shapes and natural frequency are extracted by the TDD technique. It is observed that the time delay of a shear wave occurs through friction surfaces. Such phenomena cannot be described by using the traditional analytical models such as a continuum cantilever beam model or a discrete shear building model. However, the time delay typically affects only the phases of the pagoda system. The frequencies of the pagoda system are not affected by such time delay. It is found in the first time that the layered stone pagoda system has a set of closely placed modes in near of natural frequency. It is believed that such modes are due to the friction characteristics in friction surfaces. Based on the stick-slip friction model, it seems that the one of the closely placed mode can be a self-excited one.

Mechanics of thick-shell microcapsules made by microfluidics

Double emulsion templates made by microfluidics allow for the production of tailored and monodisperse microcapsules. However, their mechanical properties cannot be predicted by traditional analytical models because of their relatively thick shells. In this work, we produce thick-shelled microcapsules with varying sizes and shell thicknesses and mechanically characterize them in single-capsule compression tests using Weibull statistics. We simulate their compression with finite element modeling and find a good agreement with the experimental results under linear elastic conditions, which enables the prediction of elastic properties based on bulk material parameters. Analysis of the simulated stresses show that capsules with a thickness-to-radius ratio above 20% consistently fail at a constant maximum principal stress in accordance with the brittle nature of their bulk material, enabling the extrapolation of their failure loads as well. Combining this structure-property correlation with processing-structure relationships found in previous studies provides a general predictive framework for the assembly of monodisperse microcapsules with tunable mechanics for protection and/or controlled release of encapsulants.

The Application of Fluid Analogy Method for Estimating Transit Route ODs Using IC Card On-Off Passenger Data

Transit route ODs are important reference data for transit network planning and operation management. However, it has the difficulties in data collection, and is of high expense and survey error by means of manual investigation method. It is easy to collect the passenger boarding-alighting counts. The method of fluid analogy method (FAM) is presented for transit passenger OD estimation. It uses the concept of pipe flow, transit route and passengers are regarded as the pipe and fluid, generate bus route OD matrix based upon passenger boarding and alighting counts. The accuracy of route OD estimates generated from boarding-alighting data is tested against actual transit integrated circuit cards (IC cards) OD based on Beijing transit route. It is shown that error index for OD at AM peak hours, PM peak hours and all day is 0.79, 0.80 and 0.83, the result shows that it has a good performance. While the correlation coefficient for actual traveled stops and estimated at AM peak hours, PM peak hours and all day is 0.98, 0.98 and 0.99, which further validate the accuracy and reliability of FAM method in estimating transit route ODs. Compared with traditional equalization algorithms and other analytical model, the method is simple, efficient and able to get a unique solution OD. It has a high practical value in real-time scheduling of intelligent public transport.

Effect of pores and He bubbles on the thermal transport properties of UO2 by molecular dynamics simulation

The thermal conductivities of UO2 single crystals containing nanoscale size pores and He gas bubbles are calculated using non-equilibrium molecular dynamics as a function of pore size and gas density in the bubble. As expected, the thermal conductivity decreases as pore size increases, while the decrease in thermal conductivity is determined to be more substantial than the predictions of traditional analytical models by Loeb and Maxwell-Eucken. However, the recent model of Alvarez, which is applicable when the phonon mean-free path is comparable to the pore size, is able to quantitatively reproduce the simulation results. The thermal conductivity of UO2 of the small pores considered here is reduced further when the pore is filled with He gas. This surprising result is due to the penetration of the helium atoms into the lattice where they act as phonon scattering centers.

Discrete event simulation case study: Diagnostic path for stroke patients in a stroke unit

Hospitals aim at delivering efficient and effective healthcare. This requires high quality medical care, provided by highly trained and motivated professionals. Also the way operations are organized can contribute to a smoother healthcare delivery. An important point here is patient flow and waiting times during the patient trajectory diagnosis-therapy-care. Due to the large variability that exist between patients care needs, even for patients with a similar pathology, predicting the waiting times is very challenging. Traditional analytical optimization models like queuing theory cannot cope with the complexity of the pathways followed by patients and the interrelationships between the resources they need. Discrete event simulation can help to provide insight into the impact of operational changes, e.g. concerning available scanner capacity, on the timing of the patient’s trajectory in a hospital unit.This paper focuses on the diagnostic part of the stay of stroke patients in a stroke unit of a university hospital. With the help of discrete event simulation this patient flow is analyzed and the impact of potential changes in the capacity profile of test resources is investigated. The paper describes the steps taken in the study and the challenges met. The structure of the simulation program is explained and the results of the scenario analysis are discussed. The paper starts with a brief exploration of the use of discrete event simulation in healthcare and ends with general observations on the subject.