Analysis of the forces driving the oscillations in 3D fluidic oscillators

One of the main advantages of fluidic oscillators is that they do not have moving parts, which brings high reliability whenever being used in real applications. To use these devices in real applications, it is necessary to evaluate their performance, since each application requires a particular injected fluid momentum and frequency. In this paper, the performance of a given fluidic oscillator is evaluated at different Reynolds numbers via a 3D-computational fluid dynamics (CFD) analysis. The net momentum applied to the incoming jet is compared with the dynamic maximum stagnation pressure in the mixing chamber, to the dynamic output mass flow, to the dynamic feedback channels mass flow, to the pressure acting to both feedback channels outlets, and to the mixing chamber inlet jet oscillation angle. A perfect correlation between these parameters is obtained, therefore indicating the oscillation is triggered by the pressure momentum term applied to the jet at the feedback channels outlets. The paper proves that the stagnation pressure fluctuations appearing at the mixing chamber inclined walls are responsible for the pressure momentum term acting at the feedback channels outlets. Until now it was thought that the oscillations were driven by the mass flow flowing along the feedback channels, however in this paper it is proved that the oscillations are pressure driven. The peak to peak stagnation pressure fluctuations increase with increasing Reynolds number, and so does the pressure momentum term acting onto the mixing chamber inlet incoming jetPostprint (published version

Research on fluidic oscillators under incompressible and compressible flow conditions

One of the main advantages of fluidic oscillators is that they do not have moving parts, which brings high reliability whenever being used in real applications. To use these devices in real applications, it is necessary to evaluate their performance, since each application requires a particular injected fluid momentum and frequency. In this PhD., the performance of a given fluidic oscillator is evaluated at different Reynolds numbers via a 3D-computational fluid dynamics (CFD) analysis under incompressible and compressible flow conditions. In the first stage, the net momentum applied to the incoming jet is compared with the dynamic maximum stagnation pressure in the mixing chamber, to the dynamic output mass flow, to the dynamic feedback channels mass flow, to the pressure acting to both feedback channels outlets, and to the mixing chamber inlet jet oscillation angle. A perfect correlation between these parameters is obtained, therefore indicating the oscillation is triggered by the pressure momentum term applied to the jet at the feedback channels outlets. The stagnation pressure fluctuations appearing at the mixing chamber inclined walls are responsible for the pressure momentum term acting at the feedback channels outlets, thus it is proved that the oscillations are pressure-driven. In the second stage, several performance parameters were numerically evaluated as a function of different internal modifications via using 3D-CFD simulations. The evaluation is based on studying the output mass flow frequency and amplitude whenever several internal geometry parameters are modified. The geometry modifications considered were the mixing chamber inlet and outlet widths, and the mixing chamber inlet and outlet wall inclination angles. The concept behind this is, to evaluate how much the fluidic oscillator internal dimensions affect the device's main characteristics, and to analyze which parts of the oscillator produce a higher impact on the fluidic oscillator output characteristics. For the different internal modifications, evaluated, special care is taken in studying the forces required to flip the jet. The entire study is performed for three different Reynolds numbers, 8711, 16034 and 32068. Among the conclusions reached it is to be highlighted that, for a given Reynolds number, modifying the internal shape affects the oscillation frequencies and amplitudes. Any oscillator internal modification generates a much relevant effect as Reynolds number increases. Under all conditions studied, it was observed that the fluidic oscillator is pressure-driven under incompressible flow conditions as discussed in the first and second stages. In the third stage, the feedback channel effect on the oscillator output mass flow frequency and amplitude under compressible flow conditions were evaluated. In order to bring light to this point, a set of three dimensional Direct Numerical Simulations under compressible flow conditions, are introduced in the present stage, four different feedback channel lengths and two inlet fluid velocities are considered. From the results obtained, it was observed that as the inlet velocity increases, the fluidic oscillator output mass flow frequency and amplitude increase. An increase of the feedback channel length decreases the output mass flow oscillating frequency. At high feedback channel lengths, the form of the main oscillation tends to disappear, the jet inside the mixing chamber simply actuates at high frequencies, for these cases, the mass flow and pressure signals are very scattered due to the pressure waves appearing on mixing chamber converging surfaces and both feedback channels at the same time. Once the FC length exceeds a certain threshold, the oscillation stops. Under compressible conditions, the oscillations are pressure-driven as previously stated for the incompressible cases. The forces due to the pressure are much stronger than the mass flow flowing along the feedback channels.El principal avantatge dels oscil·ladors fluídics es que no te parts mòbils, i això fa que sigui més fiable en aplicacions reals. Per tal d'aplicar aquests oscil·ladors en un cas concret, es necessari avaluar el seu comportament, doncs cada cas concret necessita una freqüència i quantitat de moviment donades. En el present doctorat s'ha analitzat mitjançant 3D-CFD, una configuració de oscil·lador fluídic per diferents números de Reynolds, diferents geometries internes i considerant el fluid com incompressible i compressible. Inicialment, la quantitat de moviment aplicada al jet entrant a la cambra de barreja, es comparada amb la pressió d'estancament dinàmica a les parets convergents de la cambra de barreja, amb el cabal màssic dinàmic que surt del actuador, amb el cabal màssic dinàmic que passa per els canals de realimentació, amb la pressió dinàmica que hi ha a la sortida dels canals de realimentació i amb el angle de oscil·lació del jet a l'entrada de la cambra de barreja. Tots aquests paràmetres es va veure que estaven correlacionats i això indicava que el origen de les oscil·lacions del jet era únic i era la pressió d'estancament a les parets convergents de la cambra de barreja, provant que les oscil·lacions son dirigides per gradients de pressió. Posteriorment es va fer el mateix tipus de estudi però modificant la amplada i angle de inclinació a l'entrada de la cambra de barreja i també modificant la amplada i angle de inclinació de les parets de sortida de la cambra de barreja. Aquestes quatre modificacions de la geometria interna es van fer per tres números de Reynolds diferents, 8711, 16034 i 32068. Entre les conclusions obtingudes cal destacar que, la freqüència i amplitud de oscil·lació del jet a la sortida del actuador pot ser modificada al variar les dimensions i angles interns de la cambra de barreja. Independentment del número de Reynolds estudiat i de la modificació interna considerada, es va comprovar que les oscil·lacions estaven dirigides per els gradients de pressió existents entre les dos sortides dels conductes de realimentació. L'efecte generat per qualsevol modificació interna era sempre més rellevant a números de Reynolds alts. En la tercera fase de la tesi el fluid es va considerar com a compressible subsònic, i es va avaluar els efectes de la modificació de la longitud dels canals de realimentació, sobre la freqüència i amplitud del flux que surt del oscil·lador. Quatre diferents longituds i dos números de Mach van ser avaluats. Al augmentar la longitud del canal de realimentació, la freqüència i amplitud de la oscil·lació disminueix, la oscil·lació tendeix a ser mes caòtica, apareixen altes freqüències que fan que el jet fluctuï en lloc de oscil·lar, de fet a partir de una certa longitud les oscil·lacions desapareixen i només hi han fluctuacions. Aquestes fluctuacions apareixen abans per elevats números de Mach. Les oscil·lacions son degudes a gradients de pressió, al igual que en el cas de fluid incompressible. De fet, per fluid compressible, el cabal màssic que passa per els canals de realimentació, juga un paper menys rellevant que en el cas de fluid incompressible

Characterization of High-Pressure-Die-Cast Magnesium Alloy AM60

The primary goal of this study is the characterization of high pressure die cast magnesium alloys AM60 so that the failure model which is proposed by J.Weiler can be validated for two new castings. The input variables of failure model can be determined by characterization of different regions within the castings. Based on the location of gate system, the desired regions are identified across both castings and tensile specimens are extracted from various regions. Therefore the local mechanical properties are determined, and fracture strain of samples ranges from 1.2 to 9.5%. The area fraction of porosities and skin fraction of each region are obtained from microscopic studies, and skin fraction ranges from 0.27 to 5.5% for the samples which are removed from the knit line region. The area fraction of porosities ranges from 0.4 to 2.85% within the knit line region, while high fraction of shrinkage porosities are observed within the fracture surface of samples removed from last-to-fill regions. By introduction of skin fraction as ligament factor of failure model, the fracture strain can be estimated with high accuracy. The deviation between predicted and experimental values was less than 90% for most locations. The premature failure happens to the samples containing porosities within the skin region, and actual positions of pores are considered for prediction of fracture strain. The microscopic studies of sections along the flow path also indicate that the thick defect bands are formed within the flange gates, and higher fraction of the gas pores are detected within the region closer to the overflows, and average area fraction of porosities reaches 2.8%. To evaluate the yielding behavior of samples, the elasto-plastic transition point of the samples containing different fractions of large dendrites are determined by analysis of strain hardening rate. The fully plastic behavior begins at 107MPa for the samples containing accumulated large dendrites within the core region, while it ranges from 121 to 132MPa for the samples with fine microstructure

Multiscale Machine Learning and Numerical Investigation of Ageing in Infrastructures

Infrastructure is a critical component of a country’s economic growth. Interaction with extreme service environments can adversely affect the long-term performance of infrastructure and accelerate ageing. This research focuses on using machine learning to improve the efficiency of analysing the multiscale ageing impact on infrastructure. First, a data-driven campaign is developed to analyse the condition of an ageing infrastructure. A machine learning-based framework is proposed to predict the state of various assets across a railway system. The ageing of the bond in fibre-reinforced polymer (FRP)-strengthened concrete elements is investigated using machine learning. Different machine learning models are developed to characterise the long-term performance of the bond. The environmental ageing of composite materials is investigated by a micromechanics-based machine learning model. A mathematical framework is developed to automatically generate microstructures. The microstructures are analysed by the finite element (FE) method. The generated data is used to develop a machine learning model to study the degradation of the transverse performance of composites under humid conditions. Finally, a multiscale FE and machine learning framework is developed to expand the understanding of composite material ageing. A moisture diffusion analysis is performed to simulate the water uptake of composites under water immersion conditions. The results are downscaled to obtain micromodel stress fields. Numerical homogenisation is used to obtain the composite transverse behaviour. A machine learning model is developed based on the multiscale simulation results to model the ageing process of composites under water immersion. The frameworks developed in this thesis demonstrate how machine learning improves the analysis of ageing across multiple scales of infrastructure. The resulting understanding can help develop more efficient strategies for the rehabilitation of ageing infrastructure

The Effect of Addition Parsnip Herb and its Extract on Momtaze Hamburger Shelf Life

The antioxidant effects of different forms of parsnip in beef burgers during storage for 9 days at 4°C were studied. Beef burgers were treated with 0.3% parsnip powder, 0.4% parsnip powders, 0.25 and 0.35% ethanol extracts of parsnip and 0.25 and 0.35% aqueous extracts of parsnip as well as the results were compared to beef burgers without any additive (control). Oxidation tests such as the determination of TBA value, peroxide index, pH, anisidine value, and conjugated diens and TOTOX value were determined at a gap of 3 days interval for a period of 9 days. Experiments were performed in a factorial form in a completely randomized design with the software of SPSS version 16.0. Incorporation of different forms of parsnip decreased (P<0.05) the pH value of the products. In the end of storage, the TBA value of treatments was lower than control. The results show that powder, ethanol extracts and aqueous extracts of parsnip are very effective against lipid oxidation and have potential as natural antioxidants in beef burgers. Among the different forms of parsnip, powder (0.3 and 0.4%) and aqueous extracts of parsnip (0.25 and 0.35%) were more efficient than other treatments

Exchange Rate and Trade Balance: Iran and its major Trading partners

The main objective of this paper isto evaluate the short and long run effects of exchange rate depreciation inIran on the trade balance of each 5 major trading partners, including: Germany,United Arabic Emirates, Turkey, China and South Korea during 1980-2011. Theequations are estimated by using ARDL approach and ECM, and the stability oftrade balance in long term is evaluated by CUSUM and CUSUMSQ tests. The resultsof the short-term effects on trade balance indicate that J-Curve exists onlyfor UAE and South Korea. Furthermore, a long run impact on trade balance ofIran with Germany, UAE and South Korea is recognized

Partial Least Squares Structural Equation Modeling with R

Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and restrictions (e.g. normality and relatively large sample sizes) that could discourage practitioners from applying the model. Partial least squares SEM (PLS-SEM) is a nonparametric technique which makes no distributional assumptions and can be estimated with small sample sizes. In this paper a general introduction to PLS-SEM is given and is compared with conventional SEM. Next, step by step procedures, along with R functions, are presented to estimate the model. A data set is analyzed and the outputs are interpreted Accessed 5,694 times on https://pareonline.net from September 16, 2016 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Kernel Smoothing Item Response Theory in R: A Didactic

Item response theory (IRT) refers to a family of mathematical models which describe the relationship between latent continuous variables (unobserved attribute or characteristic) and their manifestations (dichotomous/polytomous observed outcomes or responses) with regard to a set of item characteristics. Researchers typically use parametric IRT (PIRT) models to measure educational and psychological latent variables. However, PIRT models are based on a set of strong assumptions that often are not satisfied. For this reason, non-parametric IRT (NIRT) models can be more desirable. An exploratory NIRT approach is kernel smoothing IRT (KS-IRT; Ramsay, 1991) which estimates option characteristic curves by non-parametric kernel smoothing technique. This approach only gives graphical representations of item characteristics in a measure and provides preliminary feedback about the performance of items and measures. Although KS-IRT is not a new approach, its application is far from widespread, and it has limited applications in psychological and educational testing. The purpose of the present paper is to give a reader-friendly introduction to the KS-IRT, and then use the KernSmoothIRT package (Mazza et al., 2014, 2022) in R to straightforwardly demonstrate the application of the approach using data of Children’s Test Anxiety scale

Fitting the Mixed Rasch Model to a Reading Comprehension Test: Identifying Reader Types

Standard unidimensional Rasch models assume that persons with the same ability parameters are comparable. That is, the same interpretation applies to persons with identical ability estimates as regards the underlying mental processes triggered by the test. However, research in cognitive psychology shows that persons at the same trait level may employ different strategies to arrive at the solutions. This is a major threat to the construct validity of a test since the construct representation of the test changes for different classes of respondents. In this study a reading comprehension test composed of 20 multiple-choice items is analysed with mixed Rasch model. Findings show that a two-class model fits the data best. After investigating class specific item profiles the implications of the study for test validation along with the contribution of the research to our understanding of reading processes are discussed. Accessed 7,812 times on https://pareonline.net from March 05, 2013 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Linear Logistic Test Modeling with R

The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The applications of the model in test validation, hypothesis testing, cross-cultural studies of test bias, rule-based item generation, and investigating construct irrelevant factors which contribute to item difficulty are explained. The model is applied to an English as a foreign language reading comprehension test and the results are discussed. Accessed 7,390 times on https://pareonline.net from January 01, 2014 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right