scholarly journals NUMERICAL EXPERIMENTS WITH AN ALGORITHM FOR PROCESSING EXPERIMENTAL DATA TO DETERMINE THE PARAMETERS OF A RHEOLOGICAL MODEL OF A LIQUID WITH THE EFFECT OF «SOLIDIFICATION»

2021 ◽  
pp. 206-211
Author(s):  
В.Н. Колодежнов ◽  
А.В. Колтаков ◽  
С.С. Капранчиков ◽  
А.С. Веретенников
Keyword(s):  
Experimental Data ◽  
Polyethylene Glycol ◽  
Calcium Carbonate ◽  
Relative Error ◽  
Rheological Model ◽  
Numerical Experiments ◽  
Maximum Error ◽  
Viscoplastic Fluid ◽  
Maximum Relative Error ◽  
Hardening Effect

Предложена методика обработки экспериментальных данных и алгоритм для ее реализации по определению параметров реологической модели вязкопластической жидкости, которая демонстрирует проявление эффекта «отвердевания». С целью проверки работоспособности алгоритма проведены численные эксперименты с наборами генерируемых случайным образом “псевдоэкспериментальных” данных с заранее заданной величиной максимальной относительной погрешности. Проведен анализ влияния максимальной относительной погрешности исходных “псевдоэкспериментальных” данных на величину относительной погрешности определяемых в ходе численных экспериментов параметров реологической модели. По итогам проведенных экспериментов показано, что относительная погрешность определения параметров реологической модели соизмерима с максимальной погрешностью генерируемых “псевдоэкспериментальных” данных. Рассмотрен пример обработки экспериментальных данных для суспензии частиц карбоната кальция на основе полиэтиленгликоля. A technique for processing experimental data and an algorithm for its implementation to determine the parameters of a rheological model of a viscoplastic fluid, which demonstrates the manifestation of the "hardening" effect, are proposed. In order to test the algorithm's operability, numerical experiments were carried out with sets of randomly generated "pseudo-experimental" data with a predetermined maximum relative error. The analysis of the influence of the maximum relative error of the initial “pseudo-experimental” data on the value of the relative error of the parameters of the rheological model determined during numerical experiments was carried out. Based on the results of the conducted experiments, it is shown that the relative error in determining the parameters of the rheological model is commensurate with the maximum error of the generated “pseudo-experimental” data. An example of processing experimental data for a suspension of calcium carbonate particles based on polyethylene glycol is considered.

Development of a Predictive Equation for Ventilation in a Wall-Solar Chimney System

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
David Park ◽  
Francine Battaglia
Keyword(s):  
Mathematical Model ◽  
Relative Error ◽  
Natural Ventilation ◽  
Thermal Conditions ◽  
Ambient Air ◽  
Maximum Error ◽  
Scale Model ◽  
Small Scale ◽  
Maximum Relative Error ◽  
Solar Chimney

A solar chimney is a natural ventilation technique that has potential to save energy consumption as well as to maintain the air quality in a building. However, studies of buildings are often challenging due to their large sizes. The objective of this study was to determine the relationships between small- and full-scale solar chimney system models. Computational fluid dynamics (CFD) was employed to model different building sizes with a wall-solar chimney utilizing a validated model. The window, which controls entrainment of ambient air for ventilation, was also studied to determine the effects of window position. A set of nondimensional parameters were identified to describe the important features of the chimney configuration, window configuration, temperature changes, and solar radiation. Regression analysis was employed to develop a mathematical model to predict velocity and air changes per hour, where the model agreed well with CFD results yielding a maximum relative error of 1.2% and with experiments for a maximum error of 3.1%. Additional wall-solar chimney data were tested using the mathematical model based on random conditions (e.g., geometry, solar intensity), and the overall relative error was less than 6%. The study demonstrated that the flow and thermal conditions in larger buildings can be predicted from the small-scale model, and that the newly developed mathematical equation can be used to predict ventilation conditions for a wall-solar chimney.

scholarly journals THE METHOD OF PROCESSING EXPERIMENTAL DATA AND THE ALGORITHM FOR ITS IMPLEMENTATION TO DETERMINE THE PARAMETERS OF THE RHEOLOGICAL MODEL OF A DILATANT LIQUID WITH THE EFFECT OF «SOLIDIFICATION»

2021 ◽  
pp. 101-106
Author(s):  
В.Н. Колодежнов ◽  
А.В. Колтаков ◽  
С.С. Капранчиков ◽  
А.С. Веретенников
Keyword(s):  
Experimental Data ◽  
Shear Rate ◽  
Rheological Model ◽  
Sharp Increase ◽  
Solid Phase ◽  
Threshold Value ◽  
Viscoplastic Fluid ◽  
High Concentration ◽  
Working Medium ◽  
Working Media

В различных технических приложениях применяются рабочие среды типа суспензий, которые при достаточно высокой концентрации частиц твердой фазы демонстрируют аномалии вязкости. Существо этих аномалий заключается в том, что при приближении скорости сдвига к некоторому пороговому значению наблюдается явление резкого возрастания вязкости жидкости. При этом в соответствующих зонах течения рабочая среда начинает вести себя подобно твердому телу. Механическое поведение такой рабочей среды может быть описано в рамках реологической модели вязкопластической жидкости, которая позволяет учитывать проявление эффекта“упрочнения” или “отвердевания”. Рассмотрена методика определения параметров такой реологической модели на основе обработки экспериментальных данных зависимости касательного напряжения от скорости сдвига. Предложен алгоритм для реализации этой методики. In various technical applications, working media such as suspensions are used, which, at a sufficiently high concentration of solid phase particles, demonstrate viscosity anomalies. The essence of these anomalies lies in the fact that when the shear rate approaches a certain threshold value, the phenomenon of a sharp increase in the viscosity of the liquid is observed. At the same time, in the corresponding flow zones, the working medium begins to behave like a solid. The mechanical behavior of such a working medium can be described within the framework of a rheological model of a viscoplastic fluid, which allows for the manifestation of the effect of “hardening” or “solidification”. The method of determining the parameters of such a rheological model based on the processing of experimental data on the dependence of the shear stress on the shear rate is considered. An algorithm for the implementation of this technique is proposed

Robustness of a Neural Network Model for Power Peak Factor Estimation in Protection Systems

2006 ◽  
Author(s):  
Rose Mary G. P. Souza ◽  
Joa˜o M. L. Moreira
Keyword(s):  
Neural Network ◽  
Relative Error ◽  
Safety Margin ◽  
Maximum Error ◽  
Maximum Relative Error ◽  
Peak Factor ◽  
Protection Systems ◽  
Power Peak ◽  
Input Variables ◽  
Factor Estimation

This work presents results of robustness verification of artificial neural network correlations that improve the real time prediction of the power peak factor for reactor protection systems. The input variables considered in the correlation are those available in the reactor protection systems, namely, the axial power differences obtained from measured ex-core detectors, and the position of control rods. The correlations, based on radial basis function (RBF) and multilayer perceptron (MLP) neural networks, estimate the power peak factor, without faulty signals, with average errors between 0.13%, 0.19% and 0.15%, and maximum relative error of 2.35%. The robustness verification was performed for three different neural network correlations. The results show that they are robust against signal degradation, producing results with faulty signals with a maximum error of 6.90%. The average error associated to faulty signals for the MLP network is about half of that of the RBF network, and the maximum error is about 1% smaller. These results demonstrate that MLP neural network correlation is more robust than the RBF neural network correlation. The results also show that the input variables present redundant information. The axial power difference signals compensate the faulty signal for the position of a given control rod, and improves the results by about 10%. The results show that the errors in the power peak factor estimation by these neural network correlations, even in faulty conditions, are smaller than the current PWR schemes which may have uncertainties as high as 8%. Considering the maximum relative error of 2.35%, these neural network correlations would allow decreasing the power peak factor safety margin by about 5%. Such a reduction could be used for operating the reactor with a higher power level or with more flexibility. The neural network correlation has to meet requirements of high integrity software that performs safety grade actions. It is shown that the correlation is a very simple algorithm that can be easily codified in software. Due to its simplicity, it facilitates the necessary process of validation and verification.

scholarly journals Test Verification and Application of a Longitudinal Temperature Force Testing Method for Long Seamless Rails Using FBG Strain Sensor

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ping Wang ◽  
Kaize Xie ◽  
Rong Chen ◽  
Liyang Shao ◽  
Lianshan Yan ◽  
...  
Keyword(s):  
Temperature Variation ◽  
Relative Error ◽  
Test Specimen ◽  
Single Point ◽  
Maximum Error ◽  
Sensitivity Coefficient ◽  
Maximum Relative Error ◽  
Longitudinal Temperature ◽  
Temperature Force ◽  
Theoretical Results

In order to evaluate the health status of continuous welded rail accurately, a deduction on the FBG sensing principle has been made with regard to the temperature variation of test specimens under different constraint conditions. A long seamless rail testing solution and its on-site application are designed based on this deduction. According to the verification experiments of sensing principle inside, the effect of the reference temperature on the FBG temperature and strain sensitivity coefficient within −30°C~30°C is not higher than 0.05%; the maximum relative error of single point between the tested and theoretical results of test specimen under constrained condition is 3.2%; and the maximum relative error of slopes of fitted straight lines based on the tested and theoretical results within the entire test temperature range is 2.3%, verifying the deduced FBG sensing principle with regard to the test specimen under constrained condition. The maximum error of the longitudinal temperature force between the on-site tested results and calculated results in long seamless rails is only 6.1 kN, the corresponding rail temperature variation is 0.3°C, and the accumulated error is controllable within 5%.

LIQUIDUS THERMO-BAROMETER FOR THE MODELING OF MAGNETITE — MELT EQUILIBRIUM

2018 ◽  
pp. 71-80
Author(s):  
N. S. Aryaeva ◽  
E. V. Koptev-Dvornikov ◽  
D. A. Bychkov
Keyword(s):  
Experimental Data ◽  
Liquidus Temperature ◽  
Vertical Structure ◽  
Maximum Error ◽  
Silicate Melt ◽  
System Of Equations ◽  
Wide Range ◽  
Basaltic Melts ◽  
Multidimensional Statistics

A system of equations of thermobarometer for magnetite-silicate melt equilibrium was obtained by method of multidimensional statistics of 93 experimental data of a magnetite solubility in basaltic melts. Equations reproduce experimental data in a wide range of basalt compositions, temperatures and pressures with small errors. Verification of thermobarometers showed the maximum error in liquidus temperature reproducing does not exceed ±7 °C. The level of cumulative magnetite appearance in the vertical structure of Tsypringa, Kivakka, Burakovsky intrusions predicted with errors from ±10 to ±50 m.

Error-aware Design Procedure to Implement Energy-efficient Approximate Squaring Hardware

2020 ◽  
Vol 10 (4) ◽  
pp. 471-477
Author(s):  
Merin Loukrakpam ◽  
Ch. Lison Singh ◽  
Madhuchhanda Choudhury
Keyword(s):  
Energy Saving ◽  
Relative Error ◽  
Energy Efficient ◽  
Piecewise Linear ◽  
Arithmetic Operation ◽  
Design Procedure ◽  
Digital Signal ◽  
Maximum Relative Error ◽  
Square Function ◽  
Efficient Design

Background:: In recent years, there has been a high demand for executing digital signal processing and machine learning applications on energy-constrained devices. Squaring is a vital arithmetic operation used in such applications. Hence, improving the energy efficiency of squaring is crucial. Objective:: In this paper, a novel approximation method based on piecewise linear segmentation of the square function is proposed. Methods: Two-segment, four-segment and eight-segment accurate and energy-efficient 32-bit approximate designs for squaring were implemented using this method. The proposed 2-segment approximate squaring hardware showed 12.5% maximum relative error and delivered up to 55.6% energy saving when compared with state-of-the-art approximate multipliers used for squaring. Results: The proposed 4-segment hardware achieved a maximum relative error of 3.13% with up to 46.5% energy saving. Conclusion:: The proposed 8-segment design emerged as the most accurate squaring hardware with a maximum relative error of 0.78%. The comparison also revealed that the 8-segment design is the most efficient design in terms of error-area-delay-power product.

A Meshless Local Petrov-Garlerkin Method for Solving the Biharmonic Equation

2014 ◽  
Vol 931-932 ◽  
pp. 1488-1494
Author(s):  
Supanut Kaewumpai ◽  
Suwon Tangmanee ◽  
Anirut Luadsong
Keyword(s):  
Relative Error ◽  
Biharmonic Equation ◽  
Interpolation Method ◽  
Step Function ◽  
Special Treatment ◽  
Maximum Relative Error ◽  
Heaviside Step Function ◽  
Treatment Techniques ◽  
Point Interpolation Method ◽  
Point Interpolation

A meshless local Petrov-Galerkin method (MLPG) using Heaviside step function as a test function for solving the biharmonic equation with subjected to boundary of the second kind is presented in this paper. Nodal shape function is constructed by the radial point interpolation method (RPIM) which holds the Kroneckers delta property. Two-field variables local weak forms are used in order to decompose the biharmonic equation into a couple of Poisson equations as well as impose straightforward boundary of the second kind, and no special treatment techniques are required. Selected engineering numerical examples using conventional nodal arrangement as well as polynomial basis choices are considered to demonstrate the applicability, the easiness, and the accuracy of the proposed method. This robust method gives quite accurate numerical results, implementing by maximum relative error and root mean square relative error.

scholarly journals Evaluation of the Undrained Shear Strength of Organic Soils from a Dilatometer Test Using Artificial Neural Networks

2018 ◽  
Vol 8 (8) ◽  
pp. 1395 ◽  
Author(s):  
Zbigniew Lechowicz ◽  
Masaharu Fukue ◽  
Simon Rabarijoely ◽  
Maria Sulewska
Keyword(s):  
Neural Networks ◽  
Shear Strength ◽  
Artificial Neural Networks ◽  
Relative Error ◽  
Undrained Shear Strength ◽  
Organic Soils ◽  
Maximum Relative Error ◽  
Empirical Methods ◽  
Pressure Reading ◽  
Undrained Shear

The undrained shear strength of organic soils can be evaluated based on measurements obtained from the dilatometer test using single- and multi-factor empirical correlations presented in the literature. However, the empirical methods may sometimes show relatively high values of maximum relative error. Therefore, a method for evaluating the undrained shear strength of organic soils using artificial neural networks based on data obtained from a dilatometer test and organic soil properties is presented in this study. The presented neural network, with an architecture of 5-4-1, predicts the normalized undrained shear strength based on five independent variables: the normalized net value of a corrected first pressure reading (po − uo)/σ′v, the normalized net value of a corrected second pressure reading (p1 − uo)/σ′v, the organic content Iom, the void ratio e, and the stress history indictor (oc or nc). The neural model presented in this study provided a more reliable prediction of the undrained shear strength in comparison to the empirical methods, with a maximum relative error of ±10%.

Impact Simulation of a Crashworthy Composite Fuselage Section with Energy-Absorbing Floor

2014 ◽  
Vol 529 ◽  
pp. 102-107
Author(s):  
Hai Bo Luo ◽  
Ying Yan ◽  
Xiang Ji Meng ◽  
Tao Tao Zhang ◽  
Zu Dian Liang
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Dynamic Response ◽  
Relative Error ◽  
High Strength ◽  
Computer Code ◽  
Impact Simulation ◽  
Average Acceleration ◽  
Simulation Results ◽  
Energy Absorbing

A 7.8m/s vertical drop simulate of a full composite fuselage section was conducted with energy-absorbing floor to evaluate the crashworthiness features of the fuselage section and to predict its dynamic response to dummies in future. The 1.52m diameter fuselage section consists of a high strength upper fuselage frame, one stiff structural floor and an energy-absorbing subfloor constructed of Rohacell foam blocks. The experimental data from literature [6] were analyzed and correlated with predictions from an impact simulation developed using the nonlinear explicit transient dynamic computer code MSC.Dytran. The simulated average acceleration did not exceed 13g, by contrast with experimental results, whose relative error is less than 11%. The numerical simulation results agree with experiments well.

Development and Validation of a Dynamic Growth Model for Listeria monocytogenes in Fluid Whole Milk

1999 ◽  
Vol 62 (2) ◽  
pp. 170-176 ◽  
Author(s):  
S. H. ALAVI ◽  
V. M. PURI ◽  
S. J. KNABEL ◽  
R. H. MOHTAR ◽  
R. C. WHITING
Keyword(s):  
Experimental Data ◽  
Listeria Monocytogenes ◽  
Growth Model ◽  
Extreme Values ◽  
Exponential Growth Phase ◽  
Lag Phase ◽  
Maximum Relative Error ◽  
Whole Milk ◽  
Dynamic Growth ◽  
Fluid Milk

Listeria monocytogenes, a psychrotrophic microorganism, has been the cause of several food-borne illness outbreaks, including those traced back to pasteurized fluid milk and milk products. This microorganism is especially important because it can grow at storage temperatures recommended for milk (≤7°C). Growth of L. monocytogenes in fluid milk depends to a large extent on the varying temperatures it is exposed to in the postpasteurization phase, i.e., during in-plant storage, transportation, and storage at retail stores. Growth data for L. monocytogenes in sterilized whole milk were collected at 4, 6, 8, 10, 15, 20, 25, 30, and 35°C. Specific growth rate and maximum population density were calculated at each temperature using these data. The data for growth rates versus temperature were fitted to the Zwietering square root model. This equation was used to develop a dynamic growth model (i.e., the Baranyi dynamic growth model or BDGM) for L. monocytogenes based on a system of equations which had an intrinsic parameter for simulating the lag phase. Results from validation of the BDGM for a rapidly fluctuating temperature profile showed that although the exponential growth phase of the culture under dynamic temperature conditions was modeled accurately, the lag phase duration was overestimated. For an α0 (initial physiological state parameter) value of 0.137, which corresponded to the mean temperature of 15°C, the population densities were under-predicted, although the experimental data fell within the narrow band calculated for extreme values of α0. The maximum relative error between the experimental data and the curve based on an average α0 value was 10.42%, and the root mean square error was 0.28 log CFU/ml.

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