Investigation of Accelerated Degradation Methods to Cause Blisters for Non-Defective Vinyl Ester Resin Glass Flake Organic Coatings

Organic coatings are applied as a corrosion prevention measure, but their effectiveness may degrade over time. In this study, the acceleration effects of typical degradation methods in non-defective vinyl ester resin organic coatings containing glass flakes such as high-temperature immersion and immersion in chemical accelerators are clarified using physiochemical techniques. Immersion in an acetic acid (AcOH) aqueous solution causes resin swelling, and the behaviors are quantitatively evaluated through gravimetric, thickness, and electrochemical impedance spectroscopy (EIS) measurements. Furthermore, a combined process of immersion in hydrofluoric acid and an AcOH aqueous solution reduces the electrical properties and eventually blisters the thick coating surface. This result suggests that an appropriate combination of the resin swelling and the glass degradation (glass dissolution and/or formation of the gap between glass and resin) decrease mechanical properties of the glass flake coating and causes blisters. In order to help the health diagnosis of the visually non-defective aged glass flake coating, the relationship between the electrical characteristic values and the invisible degradation by accelerated tests is finally indicated.

Towards a new ground snow-load map for structural design in Germany

<p>The current European standard for snow loads on structures relies on characteristic values (i.e., snow loads with an annual probability of exceedance of 0.02 and referred to as the 50-year mean return levels) derived for Germany in 2005 using about 350 snow water-equivalent (SWE) time series from ground stations operated by the German National Weather Service (DWD) [<em>DIN EN 1991-1-3/NA:2019-04</em>, 2019]. Here we present a methodology for generating a new ground snow-loads map for Germany, which aims at improving the relative coarse spatial resolution and reducing uncertainties and inconsistencies at national borders of the actual standard. Our methodology is based on (1) high-quality and homogeneous snow-cover time series, including both daily snow-depth (from about 6000 stations in Germany and in neighbouring countries) and three-weekly water-equivalent observation (from about 10<sup>3</sup> German stations) over the period from 1950 to 2020, (2) an integrated model combining an empirical regression model for snow bulk density and the semi-empirical multi-level ΔSNOW model for generating accurate daily SWE values from 6000 snow-depth time series [<em>Castino et al.</em>, 2022], (3) the spatial interpolation of both daily snow-depth and modelled-SWE time series using a universal-kriging method to generate high spatial-resolution (~1km<sup>2</sup>) rasterised daily snow loads over the period from 1950 to 2020, and (4) the extreme value analysis of the rasterized daily snow loads for estimating the characteristic values at high spatial resolution for the entire German territory. The uncertainties of the obtained characteristic snow-load values will be estimated using a leave-one-out cross validation based on a selection of observed-SWE time series representative of the diversity of the regional snow climatology in Germany. Finally, the characteristic values of the snow-load map generated with this methodology will be compared with the current German standard.   </p> <p> </p> <p><strong>References</strong></p> <p>Castino, F., H. Schellander, B. Wichura, and M. Winkler (2022), SWE modelling: comparison between different approaches applied to Germany, abstract submitted to D-A-CH MeteorologieTagung - 21-25.03.2022, Leipzig.</p> <p>DIN EN 1991-1-3/NA:2019-04 (2019), Nationaler Anhang - National festgelegte Parameter - Eurocode 1: Einwirkungen auf Tragwerke - Teil 1-3: Allgemeine Einwirkungen - Schneelasten, edited, p. 22, Deutsches Institut für Normung e.V., Beuth-Verlag, Berlin.</p>

CALCULATION OF CLIMATE LOADS DESIGN VALUES ACCORDING TO THE PROBABILITY MODEL OF ANNUAL MAXIMUM SERIES

The aim of this work is to improve a method for determining the characteristic values of climatic loads according to a probabilistic model of the annual maxima sequence, by choosing a rational type of generalized extreme value distribution law. An analysis is provided regarding the suitability of using four types of distributions for describing a data collection of maximum values of climatic loads. Using example data from the meteorological stations of Ukraine, it is found that for coefficients of variation smaller than 0.85–1.0, it is advisable to use the double exponential Gumbel distribution (generalized extreme value distribution type-I), and at higher values of the coefficient of variation, it is advisable to use the Weibull distribution (generalized extreme value distribution type-III). Recommendations are provided for considering the accuracy in the estimations of the characteristic values of loads according to the probabilistic model for the annual maximum value series.

Polarization-Singular Approach to Imaging Mueller-Matrix Polarimetry in the Differential Diagnosis of Histological Sections of Biopsy of Tumors of the Uterus and Prostate

The possibilities of the diagnostic use of the singular approach of the distributions of the number of characteristic values of the MMI is effective for differentiating the polarization properties of histological biopsy sections of benign and malignant tumours of the uterus and prostate. Within the framework of evidence-based medicine, the sensitivity, specificity and accuracy of the azimuthal-invariant express (∼15 min) method of Mueller-matrix mapping of polarization-singular states in the differential diagnosis of uterine myoma and adenocarcinoma, as well as adenocarcinoma of the prostate with varying degrees of differentiation have been determined.

Space Thermoacoustic Radioisotopic Power System, SpaceTRIPS: The Magnetohydrodynamic Generator

Electricity production is a major problem for deep space exploration. The possibility of using radioisotope elements with a very long life as an energy source was investigated in the framework of an EU project “SpaceTRIPS”. For this, a two-stage system was tested, the first in which thermal energy is converted into mechanical energy by means of a thermoacoustic process, and the second where mechanical energy is converted into electrical energy by means of a magnetohydrodynamic generator (MHD). The aim of the present study is to develop an analytical model of the MHD generator. A one-dimensional model is developed and presented that allows us to evaluate the behavior of the device as regards both electromagnetic and fluid-dynamic aspects, and consequently to determine the characteristic values of efficiency and power.

Quantitative analysis of combustion process of marine dual fuel engine under the framework of iconology

The methane (CH4) burning interruption factor and the characteristic values characterizing the flame combustion state in the engine cylinder were defined. The logical mapping relationship between image feature values and combustion conditions in the framework of iconology was proposed. Results show that there are two periods of combustion instability and combustion stability during the combustion of dual fuel. The high temperature region with a cylinder temperature greater than 1800K is the largest at 17°CA after top dead center (TDC), accounting for 73.25% of the combustion chamber area. During the flame propagation, the radial flame velocity and the axial flame velocity are “unimodal” and “wavy,” respectively. During the combustion process, the CH4 burning interruption factor first increased and then decreased. The combustion duration in dual fuel mode is 21.25°CA, which is 15.5°CA shorter than the combustion duration in pure diesel mode.

Evaluation of the mechanical properties of fluvial coarsegrained soils from dynamic penetration test

Soil and rock properties are essential inputs for the design of geotechnical structures. But unlike man-made materials, the determination of the characteristic value is not simple, mostly because of the large space variability of the soils and rocks. In many cases, the large spatial variability makes it difficult to collect sufficient ground samples for further laboratory testing so that many tests are performed directly in the field. In Slovakia, the dynamic penetration test (DP) is, among others, a quite popular field test for soil investigation. From the measured data, it is possible to derive relative density (ID) shear (φ ef) and deformation (E def) parameters of coarse-grained soils. There are many available correlations between the DP results and geotechnical parameters. Therefore, it is necessary to choose the most appropriate one as it considerably affects the final evaluation. This paper shows the assessment of geotechnical parameters of coarse-grained fluvial soil from the DP results and presents the statistical determination of its characteristic values, which are furthermore compared with the nominal values used in Slovakia.

Annotation and Classification of Graphs of Property Values Reported in Material Science Literature

Building a system for extracting information from the scientific literature is an important research topic in the field of inorganic materials science. However, conventional extraction systems have a limitation in that they do not extract characteristic values from nontextual components, such as charts, diagrams, and tables, which provide key information in many scientific documents. Although there have been several studies on identifying the characteristic values of graphs in the literature, there is no general method that classifies graphs according to the property conditions of the values in the field of materials science. Therefore, in this study, we focus on graphs that are figures representing graphically numerical data, such as a bar graph and line graph, as the first step toward developing a framework for extracting material property information from such noncontextual components. We propose deep-learning-based classification models for identifying the types of graph properties, such as temperature and time, by combining graph images, text in graphs, and captions in neural networks. To train and evaluate the models, we construct a material graph dataset with different types of material properties from a large collection of data from journals in the field of materials science. By using cloud sourcing, we annotate 16,668 images. Our experimental results demonstrate that the best model can achieve high performance with a microaveraged F-score of 0.961.

The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects

The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final shape of the EEG signal and thus its characteristic values, latency and amplitude. There are several types of filters to eliminate noise early in the processing of EEG data. However, there is no gold standard for their use. This article aims to verify and compare the influence of four various filters (FIR, IIR, FFT, NOTCH) on the latency and amplitude of the EEG signal. By presenting a comparison of selected filters, the authors intend to raise awareness among researchers as regards the effects of known filters on latency and amplitude in a selected area—the sensorimotor area.

The Optimal Performance of the Energy Efficiency of a Pulse Dust Collection System towards Sustainability

A growing number of manufacturers are realizing cost and environmental benefits through the sustainability of innovation and optimization processes. Based on polluting less and creating less, the study is pursuing sustainability on increasing operational efficiency by reducing costs and waste. Pulse dust collection systems are commonly used filtration equipment in industries and have lots of energy consumption due to running all day. This study is focused on the optimal parameters for energy saving and cost reduction, and the model is represented by the pressure drop of the filter and the residual powder. The characteristic values of the cleaning efficiency and the air permeability reduction are used for MATLAB to analyze the optimization state. This study found that the material of filter elements, the type of dust, the conditions of pulse-jet, and the filtering speed are the factors that affect the operational efficiency. In terms of cost, the pulse interval time in 10 s is the best parameter, and the pulse time does not affect the overall cost of the filter. Considering energy saving, 0.1 s of the pulse time is the best parameter. In addition, a lower dust concentration is a way to improve efficiency for increasing the filter life and reducing cost.