scholarly journals Modeling of self-excited stress measurement system

2020 ◽  
pp. 146134842092945
Author(s):  
Ireneusz Dominik ◽  
Krzysztof Lalik ◽  
Stanisław Flaga
Keyword(s):  
Stress Measurement ◽  
Numerical Models ◽  
Piezoelectric Transducers ◽  
The Self ◽  
Model Parameters ◽  
Change Measurement ◽  
Stress Changes ◽  
Emitter System ◽  
New Type ◽  
Proper Power

In the paper two types of numerical models of the self-excited acoustical system are presented. This new type of auto-oscillating system is used for stress change measurement in constructions and rock masses. The essence of the self-excited acoustical system is to use a vibration emitter and vibration receiver placed at a distance, which are coupled with a proper power amplifier, and which are operating in a closed loop with a positive feedback. This causes the excitation of the system. The change of the velocity of wave propagation, which is associated with the change of the resonance frequency in the system is caused by the deformation of the examined material. Stress changes manifest themselves in small but detectable variations of frequency. The first of the presented models was created on the basis of estimating the model parameters by identification of the sensor–conditioner–amplifier–emitter system. The second mathematical model was delivered from the force–charge equation of the piezoelectric transducers: the sensor and the emitter. The model of the loaded beam, which determined the response of any beam point to the force applied to any other beam point is also presented.

Speed vs. comfort: Testing the efficacy of a single question for predicting transit users’ route choices

2019 ◽  
Author(s):  
Joseph John Pyne Simons ◽  
Ilya Farber
Keyword(s):  
Data Collection ◽  
Efficient Method ◽  
Choice Task ◽  
The Self ◽  
Self Report ◽  
Model Parameters ◽  
Single Item ◽  
Alternative Approach ◽  
Single Question ◽  
Insight Into

Not all transit users have the same preferences when making route decisions. Understanding the factors driving this heterogeneity enables better tailoring of policies, interventions, and messaging. However, existing methods for assessing these factors require extensive data collection. Here we present an alternative approach - an easily-administered single item measure of overall preference for speed versus comfort. Scores on the self-report item predict decisions in a choice task and account for a proportion of the differences in model parameters between people (n=298). This single item can easily be included on existing travel surveys, and provides an efficient method to both anticipate the choices of users and gain more general insight into their preferences.

Dynamic Modeling of Channel Formation During Fluid Injection Into Unconsolidated Formations

SPE Journal ◽  
2015 ◽  
Vol 20 (04) ◽  
pp. 689-700 ◽  
Author(s):  
S.. Ameen ◽  
A. Dahi Taleghani
Keyword(s):  
Preferential Flow ◽  
Volume Fraction ◽  
Injection Pressure ◽  
Internal Erosion ◽  
Fluid Injection ◽  
Critical Threshold ◽  
Model Parameters ◽  
Flow Paths ◽  
Preferential Flow Paths ◽  
Stress Changes

Summary Injectivity loss is a common problem in unconsolidated-sand formations. Injection of water into a poorly cemented granular medium may lead to internal erosion, and consequently formation of preferential flow paths within the medium because of channelization. Channelization in the porous medium might occur when fluid-induced stresses become locally larger than a critical threshold and small grains are dislodged and carried away; hence, porosity and permeability of the medium will evolve along the induced flow paths. Vice versa, flowback during shut-in might carry particles back to the well and cause sand accumulation inside the well, and subsequently loss of injectivity. In most cases, to maintain the injection rate, operators will increase injection pressure and pumping power. The increased injection pressure results in stress changes and possibly further changes in channel patterns around the wellbore. Experimental laboratory studies have confirmed the presence of the transition from uniform Darcy flow to a fingered-pattern flow. To predict these phenomena, a model is needed to fill this gap by predicting the formation of preferential flow paths and their evolution. A model based on the multiphase-volume-fraction concept is used to decompose porosity into mobile and immobile porosities where phases may change spatially, evolve over time, and lead to development of erosional channels depending on injection rates, viscosity, and rock properties. This model will account for both particle release and suspension deposition. By use of this model, a methodology is proposed to derive model parameters from routine injection tests by inverse analysis. The proposed model presents the characteristic behavior of unconsolidated formation during fluid injection and the possible effect of injection parameters on downhole-permeability evolution.

Coupled Thermo-Hydro-Geochemical Models of Engineered Barrier Systems: The Febex Project

2000 ◽  
Vol 663 ◽  
Author(s):  
J. Samper ◽  
R. Juncosa ◽  
V. Navarro ◽  
J. Delgado ◽  
L. Montenegro ◽  
...  
Keyword(s):  
Large Scale ◽  
Reference Model ◽  
Numerical Models ◽  
Full Scale ◽  
Small Scale ◽  
Model Parameters ◽  
In Situ Test ◽  
Wide Range ◽  
Engineered Barrier

ABSTRACTFEBEX (Full-scale Engineered Barrier EXperiment) is a demonstration and research project dealing with the bentonite engineered barrier designed for sealing and containment of waste in a high level radioactive waste repository (HLWR). It includes two main experiments: an situ full-scale test performed at Grimsel (GTS) and a mock-up test operating since February 1997 at CIEMAT facilities in Madrid (Spain) [1,2,3]. One of the objectives of FEBEX is the development and testing of conceptual and numerical models for the thermal, hydrodynamic, and geochemical (THG) processes expected to take place in engineered clay barriers. A significant improvement in coupled THG modeling of the clay barrier has been achieved both in terms of a better understanding of THG processes and more sophisticated THG computer codes. The ability of these models to reproduce the observed THG patterns in a wide range of THG conditions enhances the confidence in their prediction capabilities. Numerical THG models of heating and hydration experiments performed on small-scale lab cells provide excellent results for temperatures, water inflow and final water content in the cells [3]. Calculated concentrations at the end of the experiments reproduce most of the patterns of measured data. In general, the fit of concentrations of dissolved species is better than that of exchanged cations. These models were later used to simulate the evolution of the large-scale experiments (in situ and mock-up). Some thermo-hydrodynamic hypotheses and bentonite parameters were slightly revised during TH calibration of the mock-up test. The results of the reference model reproduce simultaneously the observed water inflows and bentonite temperatures and relative humidities. Although the model is highly sensitive to one-at-a-time variations in model parameters, the possibility of parameter combinations leading to similar fits cannot be precluded. The TH model of the “in situ” test is based on the same bentonite TH parameters and assumptions as for the “mock-up” test. Granite parameters were slightly modified during the calibration process in order to reproduce the observed thermal and hydrodynamic evolution. The reference model captures properly relative humidities and temperatures in the bentonite [3]. It also reproduces the observed spatial distribution of water pressures and temperatures in the granite. Once calibrated the TH aspects of the model, predictions of the THG evolution of both tests were performed. Data from the dismantling of the in situ test, which is planned for the summer of 2001, will provide a unique opportunity to test and validate current THG models of the EBS.

Small Holes Fabrication on Soda Glass by Self-Elastic Polycrystalline Diamond Tool

2012 ◽  
Vol 516 ◽  
pp. 516-521
Author(s):  
Chung Chieh Cheng ◽  
Dong Yea Sheu
Keyword(s):  
Surface Roughness ◽  
Diamond Tool ◽  
Polycrystalline Diamond ◽  
The Self ◽  
High Quality ◽  
Drilling Tool ◽  
Drilling Tools ◽  
Absorbing Materials ◽  
New Type ◽  
Small Holes

This study describes a novel process to drill small holes in brittle materials such as glass, silicon and ceramic using a self-elastic polycrystalline diamond (PCD) drilling tool. In order to improve the surface roughness and reduce crack of the small holes, a new type of self-elastic PCD drilling tool equipped with vibration absorbing materials inside the housing was developed to fabricate small holes in glass in this study. The self-elastic PCD drilling tools could absorb the mechanical force by the vibration absorbing materials while the PCD tool penetrates into the small holes. Compared to conventional PCD drilling tools, the experimental results show that high-quality small holes drilled in glass can be achieved with cracking as small as 0.02mm on the outlet surface using the self-elastic PCD drilling tool.

PRELIMINARY STUDY ON NOVEL BEAM-TO-COLUMN CONNECTION BASED ON SMA PLATE

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Michael CH Yam ◽  
Ke Ke ◽  
Ping Zhang ◽  
Qingyang Zhao
Keyword(s):  
Friction Coefficient ◽  
Energy Dissipation ◽  
Numerical Study ◽  
Numerical Models ◽  
Numerical Technique ◽  
The Self ◽  
Hysteretic Behavior ◽  
The Novel ◽  
Energy Dissipation Capacity ◽  
Preliminary Study

A novel beam-to-column connection equipped with shape memory alloy (SMA) plates has been proposed to realize resilient performance under low-to-medium seismic actions. In this conference paper, the detailed 3D numerical technique calibrated by the previous paper is adopted to examine the hysteretic behavior of the novel connection. A parametric study covering a reasonable range of parameters including the thickness of the SMA plate, friction coefficient between SMA plate and beam flange and pre-load of the bolt was carried out and the influence of the parameters was characterized. In addition, the effect of the SMA Belleville washer on the connection performance was also studied. The results of the numerical study showed that the initial connection stiffness and the energy-dissipation capacity of the novel connection can be enhanced with the increase of the thickness of the SMA plate. In addition, the initial connection stiffness and energy-dissipation behavior of the novel connection can be improved by increasing the friction coefficient or pre-load of bolts, whereas the increased friction level could compromise the self-centering behavior of the connection. The hysteretic curves of the numerical models of the connection also implied that the SMA washers may contribute to optimizing the connection behavior by increasing the connection stiffness and energy-dissipation capacity without sacrificing the self-centering behavior.

Conditioning Model Ensembles to Various Observed Data (Field and Regional Level) by Applying Machine-Learning-Augmented Workflows to a Mature Field with 70 Years of Production History

2021 ◽  
pp. 1-18
Author(s):  
Gisela Vanegas ◽  
John Nejedlik ◽  
Pascale Neff ◽  
Torsten Clemens
Keyword(s):  
Machine Learning ◽  
Oil Recovery ◽  
Numerical Models ◽  
Operating Conditions ◽  
Model Parameters ◽  
Large Set ◽  
Model Parameter ◽  
Production History ◽  
Hydrocarbon Fields ◽  
Parameter Distributions

Summary Forecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the production forecast from hydrocarbon fields. Changing operating conditions [e.g., implementation of improved oil recovery or enhanced oil recovery (EOR)] results in model parameters becoming sensitive in the forecast that were not sensitive during the production history. Hence, simulation approaches need to be able to address uncertainty in model parameters as well as conditioning numerical models to a multitude of different observed data. Sampling from distributions of various geological and dynamic parameters allows for the generation of an ensemble of numerical models that could be falsified using principal-component analysis (PCA) for different observed data. If the numerical models are not falsified, machine-learning (ML) approaches can be used to generate a large set of parameter combinations that can be conditioned to the different observed data. The data conditioning is followed by a final step ensuring that parameter interactions are covered. The methodology was applied to a sandstone oil reservoir with more than 70 years of production history containing dozens of wells. The resulting ensemble of numerical models is conditioned to all observed data. Furthermore, the resulting posterior-model parameter distributions are only modified from the prior-model parameter distributions if the observed data are informative for the model parameters. Hence, changes in operating conditions can be forecast under uncertainty, which is essential if nonsensitive parameters in the history are sensitive in the forecast.

A new ensemble-based statistical methodology to verify changes in weather and climate models

2021 ◽  
Author(s):  
Christian Zeman ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Hypothesis Test ◽  
Model Development ◽  
Atmospheric Model ◽  
Statistical Hypothesis ◽  
Model Parameters ◽  
Rounding Errors ◽  
Weather And Climate

<p>Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.</p><p>Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.</p><p>We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.</p>

scholarly journals A Study on A New Type 1 Half-Logistic Family of Distributions and Its Applications

2020 ◽  
Vol 8 (4) ◽  
pp. 934-949
Author(s):  
Morad Alizadeh ◽  
Alireza Nematollahi ◽  
Emrah Altun ◽  
Mahdi Rasekhi
Keyword(s):  
Residual Life ◽  
Moment Generating Function ◽  
Likelihood Method ◽  
Mean Deviation ◽  
Model Parameters ◽  
Type I ◽  
Monte Carlo Simulation Study ◽  
New Type ◽  
Application Fields ◽  
Family Of Distributions

In this paper, we propose a new class of continuous distributions with two extra shape parameters called the a new type I half logistic-G family of distributions. Some of important properties including ordinary moments, quantiles, moment generating function, mean deviation, moment of residual life, moment of reversed residual life, order statistics and extreme value are obtained. To estimate the model parameters, the maximum likelihood method is also applied by means of Monte Carlo simulation study. A new location-scale regression model based on the new type I half logistic-Weibull distribution is then introduced. Applications of the proposed family is demonstrated in many fields such as survival analysis and univariate data fitting. Empirical results show that the proposed models provide better fits than other well-known classes of distributions in many application fields.

scholarly journals Analytical and Numerical Connections between Fractional Fickian and Intravoxel Incoherent Motion Models of Diffusion MRI

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1963
Author(s):  
Jingting Yao ◽  
Muhammad Ali Raza Anjum ◽  
Anshuman Swain ◽  
David A. Reiter
Keyword(s):  
Skeletal Muscle ◽  
Goodness Of Fit ◽  
Numerical Models ◽  
Tissue Perfusion ◽  
Parametric Models ◽  
Intravoxel Incoherent Motion ◽  
Fickian Diffusion ◽  
Model Parameters ◽  
Mathematical Framework ◽  
Stretched Exponential

Impaired tissue perfusion underlies many chronic disease states and aging. Diffusion-weighted imaging (DWI) is a noninvasive MRI technique that has been widely used to characterize tissue perfusion. Parametric models based on DWI measurements can characterize microvascular perfusion modulated by functional and microstructural alterations in the skeletal muscle. The intravoxel incoherent motion (IVIM) model uses a biexponential form to quantify the incoherent motion of water molecules in the microvasculature at low b-values of DWI measurements. The fractional Fickian diffusion (FFD) model is a parsimonious representation of anomalous superdiffusion that uses the stretched exponential form and can be used to quantify the microvascular volume of skeletal muscle. Both models are established measures of perfusion based on DWI, and the prognostic value of model parameters for identifying pathophysiological processes has been studied. Although the mathematical properties of individual models have been previously reported, quantitative connections between IVIM and FFD models have not been examined. This work provides a mathematical framework for obtaining a direct, one-way transformation of the parameters of the stretched exponential model to those of the biexponential model. Numerical simulations are implemented, and the results corroborate analytical results. Additionally, analysis of in vivo DWI measurements in skeletal muscle using both biexponential and stretched exponential models is shown and compared with analytical and numerical models. These results demonstrate the difficulty of model selection based on goodness of fit to experimental data. This analysis provides a framework for better interpreting and harmonizing perfusion parameters from experimental results using these two different models.

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