scholarly journals INITIAL RESEARCH OF MINERAL BASED ANTI-CORROSION MULTICOMPONENT COMPOSITE MATERIAL

2019 ◽  
Vol 48 (05) ◽  
pp. 142-147
Author(s):  
Emil Asgarov
Keyword(s):  
Composite Material ◽  
Extreme Values ◽  
Extreme Value ◽  
Point Of View ◽  
Protective Film ◽  
Weak Point ◽  
Variable Function ◽  
New Material ◽  
Film Layer ◽  
Multicomponent Composite

The new approach is to create a multicomponent composite material on a basis of mineral component by defining extreme value of the multi-variable function. It is decided to carry out theoretical analyze first. For theoretical analysis, the effects of component quantity on the parameters to be determined by experiments and in all cases the results to be theorized. Thus, the mathematical formula for the relation of anti-corrosion with components has been determined. In order to evaluate anti-corrosion it is defined multi-variablefunctional relation and with this function it is achieved extreme values on optimum values of each component. The new material is compared to traditional anti –corrosion material that are common. Currently implemented anti –corrosion material doesn’t require needs of modern technological expectation. From this point of view anti-corrosion materials need to have appropriate technical parameters. Traditional anti-corrosion materials basically have one or two components and these materials has protective film layer. Disadvantage of this film layer is whole layer can easily be destructed from weak point. This is due to the fact that traditional materials form film layer in connection areas. Compare with this one the new material has discrete structure. On this basis, the combination of protective and constructive material binding based on adhesion and cohesion. The structure not allows material to be destructed from weak point. On a basis of achieved theoretical results optimal quantity of each component is clarified, anti-corrosion material is made and tested. The novelty of the approach is to achieve high quality anti-corrosion material by defining an extreme value of the multi-variable function.

scholarly journals Vibroacoustic Assessment of an Innovative Composite Material for the Roof of a Coupe Car

2021 ◽  
Vol 11 (3) ◽  
pp. 1128
Author(s):  
Nunziante Cascone ◽  
Luca Caivano ◽  
Giuseppe D’Errico ◽  
Roberto Citarella
Keyword(s):  
Composite Material ◽  
Transfer Functions ◽  
Realistic Model ◽  
Point Of View ◽  
Damping Capacity ◽  
Geometry Structure ◽  
Fiberglass Composite ◽  
New Material ◽  
Static Rigidity ◽  
Innovative Material

The objective of this paper is the vibroacoustic evaluation of an innovative material for a sports car roof, aiming at replacing fiberglass composite materials. Such evaluation was carried out using numerical and experimental analysis techniques, with cross-comparison between the corresponding results. The innovative material under analysis is a composite material, with a thermoplastic polypropylene matrix and reinforcement made of cellulose fibers. In order to validate the virtual dynamic modeling of the new material, the inertance on different points of some sheets made of the material under analysis was evaluated by an in-house made experimental activity, performed in the CRF (Fiat Research Center) test room, and cross-compared with corresponding results from a numerical analysis performed with the MSC Nastran software. Then, a realistic model of the car roof of the Alfa Romeo 4C car, made with the new material, was implemented and analyzed from the vibroacoustic point of view. The mere switch to the new material, with no changes in the geometry/structure of the car roof, did not allow preserving the original values of static rigidity, dynamic rigidity, and configuration of modal shapes. For this reason, a geometric/structural optimization of the component was performed. Once the new geometry/structure was defined, a vibroacoustic analysis was carried out, checking for a possible coupling between the fluid cavity modes and the structure car body modes. Finally, the vibroacoustic transfer functions to the driver’s ear node were assessed, considering two different excitation points on the structure. The excellent damping capacity of the proposed material led to an improvement in the vibroacoustic transfer functions and to a reduction in the weight of the pavilion.

scholarly journals Implicit max-stable extremal integrals

Extremes ◽  
2020 ◽  
Author(s):  
D. Kremer
Keyword(s):  
Loss Function ◽  
Open Problem ◽  
Stochastic Integral ◽  
Extreme Values ◽  
Stable Distributions ◽  
Extreme Value ◽  
Point Of View ◽  
Extreme Value Distributions ◽  
Application Point ◽  
Deterministic Function

Abstract Recently, the notion of implicit extreme value distributions has been established, which is based on a given loss function f ≥ 0. From an application point of view, one is rather interested in extreme loss events that occur relative to f than in the corresponding extreme values itself. In this context, so-called f -implicit α-Fréchet max-stable distributions arise and have been used to construct independently scattered sup-measures that possess such margins. In this paper we solve an open problem in Goldbach (2016) by developing a stochastic integral of a deterministic function g ≥ 0 with respect to implicit max-stable sup-measures. The resulting theory covers the construction of max-stable extremal integrals (see Stoev and Taqqu Extremes 8, 237–266 (2005)) and, at the same time, reveals striking parallels.

scholarly journals Estimation of Extreme Values by the Average Conditional Exceedance Rate Method

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
A. Naess ◽  
O. Gaidai ◽  
O. Karpa
Keyword(s):  
Time Series ◽  
Extreme Values ◽  
Practical Interest ◽  
Extreme Value Distribution ◽  
Real Data ◽  
Extreme Value ◽  
Point Of View ◽  
Statistical Dependence ◽  
Sampled Data ◽  
Threshold Method

This paper details a method for extreme value prediction on the basis of a sampled time series. The method is specifically designed to account for statistical dependence between the sampled data points in a precise manner. In fact, if properly used, the new method will provide statistical estimates of the exact extreme value distribution provided by the data in most cases of practical interest. It avoids the problem of having to decluster the data to ensure independence, which is a requisite component in the application of, for example, the standard peaks-over-threshold method. The proposed method also targets the use of subasymptotic data to improve prediction accuracy. The method will be demonstrated by application to both synthetic and real data. From a practical point of view, it seems to perform better than the POT and block extremes methods, and, with an appropriate modification, it is directly applicable to nonstationary time series.

scholarly journals Study of synergetic effect of the complex polycarboxylate anti-corrosion additive in the model of pore concrete fluid

Vestnik MGSU ◽  
2020 ◽  
pp. 824-833
Author(s):  
Linar N. Talipov ◽  
Evgeny G. Velichko ◽  
Vyacheslav S. Semenov
Keyword(s):  
Sodium Nitrite ◽  
Electron Probe Microanalysis ◽  
Electron Probe ◽  
Structural Characteristics ◽  
Synergetic Effect ◽  
Gel Permeation Chromatography ◽  
13C Nmr Spectroscopy ◽  
Protective Film ◽  
Film Layer ◽  
Pore Liquid

Introduction. Corrosion of reinforcement in concrete structures is rather expensive for the economy of any country. Current statutory documents offer two main directions — primary and secondary protection. One of the promising areas of primary protection methods is the use of complex anti-corrosion additives in concrete due to its technological simplicity and economic efficiency. Passivators and surfactants (SAS), as components of such additives, are of particular interest. Sodium nitrite is offered as a passivator, and polycarboxylate molecules (PCE) — as a SAS. The additive of sodium nitrite together with PCE has a visual synergistic effect. Materials and methods. Identification of structural characteristics of the molecules of the obtained PCE polymers was determined by methods of exclusion gel-permeation chromatography and 13C NMR spectroscopy. To study the synergetic effect of NaNO2 + PCE additive, the samples were kept in the models of pore liquid, after which the morphology of their surface was studied by methods of scanning electron microscopy and electron probe microanalysis. Results. The texture and surface color of the presented micrographs indicate surface formations on the samples stored in the models of pore liquid with different anti-corrosion additives. Electron probe microanalysis showed increased concentrations of carbon, oxygen and sodium on the surface of samples stored in pore concrete liquid models with the addition of a complex anti-corrosion additive of sodium nitrite and PCE, which indicates increased concentrations of PCE and possible increased pH on the steel surface. Based on the data acquired, the mechanism of formation of a protective film layer using complex anti-corrosion additive NaNO2 + PCE is offered. Conclusions. Justification of synergetic effect of complex polycarboxylate anti-corrosion additive in the model of concrete pore liquid opens up prospects for research of such additives to the concrete model.

scholarly journals Nonparametric Estimation of Multivariate Extreme Value Copulas with Known and Unknown Marginal Distributions

2021 ◽  
Vol 2068 (1) ◽  
pp. 012003
Author(s):  
Ayari Samia ◽  
Mohamed Boutahar
Keyword(s):  
Distribution Function ◽  
Empirical Distribution Function ◽  
Extreme Values ◽  
Empirical Distribution ◽  
Extreme Value ◽  
Dependence Function ◽  
Marginal Distributions ◽  
Nonparametric Estimators ◽  
Monte Carlo Experiments ◽  
Multivariate Extreme Values

Abstract The purpose of this paper is estimating the dependence function of multivariate extreme values copulas. Different nonparametric estimators are developed in the literature assuming that marginal distributions are known. However, this assumption is unrealistic in practice. To overcome the drawbacks of these estimators, we substituted the extreme value marginal distribution by the empirical distribution function. Monte Carlo experiments are carried out to compare the performance of the Pickands, Deheuvels, Hall-Tajvidi, Zhang and Gudendorf-Segers estimators. Empirical results showed that the empirical distribution function improved the estimators’ performance for different sample sizes.

DIAMOND-LIKE CARBON: A NEW MATERIAL BASE FOR NANO-ARCHITECTURES

COSMOS ◽  
2008 ◽  
Vol 04 (02) ◽  
pp. 203-234 ◽  
Author(s):  
XIJUN LI ◽  
DANIEL H. C. CHUA
Keyword(s):  
Carbon Film ◽  
High Hardness ◽  
Diamond Like Carbon ◽  
Protective Film ◽  
Material Base ◽  
Wear Resistant Coatings ◽  
Novel Material ◽  
New Material ◽  
High Fraction ◽  
Mechanical Devices

Diamond-like carbon (DLC) is a form of amorphous carbon which has high fraction of sp3 hybridization. Due to its nature of sp3 bonding, diamond-like carbon has been shown to have excellent properties similar to that of diamond. This includes high hardness, excellent wear-resistance, large modulus and chemically inert. Traditional applications include wear resistant coatings and protective film. This article intends to review the synthesis and material properties of diamond-like carbon as well as its potential as a novel material for applications in nano-architecture and nano-mechanical devices. An introduction into metal-dopants in diamond-like carbon film will be briefly mentioned as well as techniques on the design and fabrication of this material.

Consideration of Epistemic Uncertainty in Extreme Wave Height Estimation

2014 ◽  
Author(s):  
Ryota Wada ◽  
Takuji Waseda
Keyword(s):  
Gulf Of Mexico ◽  
Observational Data ◽  
Wave Height ◽  
Extreme Values ◽  
Epistemic Uncertainty ◽  
Extreme Value Distribution ◽  
Predictive Distribution ◽  
Extreme Value ◽  
Posterior Predictive Distribution ◽  
Value Estimation

Extreme value estimation of significant wave height is essential for designing robust and economically efficient ocean structures. But in most cases, the duration of observational wave data is not efficient to make a precise estimation of the extreme value for the desired period. When we focus on hurricane dominated oceans, the situation gets worse. The uncertainty of the extreme value estimation is the main topic of this paper. We use Likelihood-Weighted Method (LWM), a method that can quantify the uncertainty of extreme value estimation in terms of aleatory and epistemic uncertainty. We considered the extreme values of hurricane-dominated regions such as Japan and Gulf of Mexico. Though observational data is available for more than 30 years in Gulf of Mexico, the epistemic uncertainty for 100-year return period value is notably large. Extreme value estimation from 10-year duration of observational data, which is a typical case in Japan, gave a Coefficient of Variance of 43%. This may have impact on the design rules of ocean structures. Also, the consideration of epistemic uncertainty gives rational explanation for the past extreme events, which were considered as abnormal. Expected Extreme Value distribution (EEV), which is the posterior predictive distribution, defined better extreme values considering the epistemic uncertainty.

Extreme Values of Waves and Ship Responses Subject to the Markov Chain Condition

1979 ◽  
Vol 23 (03) ◽  
pp. 188-197
Author(s):  
Michel K. Ochi
Keyword(s):  
Distribution Function ◽  
Markov Chain ◽  
Probability Distribution ◽  
Random Process ◽  
Probability Distribution Function ◽  
Extreme Values ◽  
Random Processes ◽  
Chain Condition ◽  
Extreme Value ◽  
Spectral Bandwidth

This paper discusses the effect of statistical dependence of the maxima (peak values) of a stationary random process on the magnitude of the extreme values. A theoretical analysis of the extreme values of a stationary normal random process is made, assuming the maxima are subject to the Markov chain condition. For this, the probability distribution function of maxima as well as the joint probability distribution function of two successive maxima of a normal process having an arbitrary spectral bandwidth are applied to Epstein's theorem for evaluating the extreme values in a given sample under the Markov chain condition. A numerical evaluation of the extreme values is then carried out for a total of 14 random processes, including nine ocean wave records, with various spectral bandwidth parameters ranging from 0.11 to 0.78. From the results of the computations, it is concluded that the Markov concept is applicable to the maxima of random processes whose spectral bandwidth parameter, ɛ, is less than 0.5, and that the extreme values with and without the Markov concept are constant irrespective of the e-value, and the former is approximately 10 percent greater than the latter. It is also found that the sample size for which the extreme value reaches a certain level with the Markov concept is much less than that without the Markov concept. For example, the extreme value will reach a level of 4.0 (nondimensional value) in 1100 observations of the maxima with the Markov concept, while the extreme value will reach the same level in 3200 observations of the maxima without the Markov concept.

Examination of Microstructure of Cement Composite Material for Renovation of Horizontal Structures

2019 ◽  
Vol 808 ◽  
pp. 103-108
Author(s):  
Lenka Mészárosová ◽  
Vít Černý ◽  
Rostislav Drochytka ◽  
Winfried Malorny
Keyword(s):  
Thermal Conductivity ◽  
Composite Material ◽  
High Temperature ◽  
Surface Temperature ◽  
Cement Composite ◽  
Volume Weight ◽  
Coefficient Of Thermal Conductivity ◽  
New Material ◽  
Properties Of Materials ◽  
Low Volume

Development of new material is focused on modification of properties of materials with silicate binder so that these could be used for renovation of horizontal structures of high-temperature devices and at the same time contribute to reduction of heat transportation of constructions with higher surface temperature (in this case 200 and 500 °C). Main requirements for this material is low volume weight and low coefficient of thermal conductivity. This paper assesses influence of exposition to higher temperatures on microstructure.

Covariate Extreme Value Analysis Using Wave Spectral Partitioning

2020 ◽  
Vol 37 (5) ◽  
pp. 873-888 ◽  
Author(s):  
Jesús Portilla-Yandún ◽  
Edwin Jácome
Keyword(s):  
Extreme Values ◽  
Wind Waves ◽  
Spectral Energy Distribution ◽  
Wave Spectrum ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Spectral Energy ◽  
Value Analysis ◽  
Spectral Partitioning

AbstractAn important requirement in extreme value analysis (EVA) is for the working variable to be identically distributed. However, this is typically not the case in wind waves, because energy components with different origins belong to separate data populations, with different statistical properties. Although this information is available in the wave spectrum, the working variable in EVA is typically the total significant wave height Hs, a parameter that does not contain information of the spectral energy distribution, and therefore does not fulfill this requirement. To gain insight in this aspect, we develop here a covariate EVA application based on spectral partitioning. We observe that in general the total Hs is inappropriate for EVA, leading to potential over- or underestimation of the projected extremes. This is illustrated with three representative cases under significantly different wave climate conditions. It is shown that the covariate analysis provides a meaningful understanding of the individual behavior of the wave components, in regard to the consequences for projecting extreme values.

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