The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles Collected During High Atmospheric Loading for PM_2.5

Although it is well known that rain plays an important role in capturing air pollutants, its quantitative evaluation has not been done enough. In this study, the pollutant scavenging effect by size of raindrops was investigated by clarifying the chemical nature of individual size-resolved raindrops and their residual particles. Raindrops as a function of their size were collected using the raindrop collector devised by ourselves during high atmospheric loading for PM2.5. The raindrop number concentration (m−2 h−1) tended to drastically decrease as the drop size goes up. Particle scavenging rate, Rsca.(%), based on the actual measurement values were 38.7, 69.5, and 80.8% for the particles with 0.3–0.5, 0.5–1.0, and 1.0–2.0 μm diameter, respectively. S, Ca, Si, and Al ranked relatively high concentration in raindrops, especially small ones. Most of the element showed a continuous decrease in concentration with increasing raindrop diameter. The source profile by factor analysis for the components of residual particles indicated that the rainfall plays a valuable role in scavenging natural as well as artificial particles from the dirty atmosphere

A Study on Thermal Modeling and Heat Load Mitigation for Satellite Electronic Components

Since most of the satellite components are using various EEE (Electrical, Electronic and Electromechanical) parts, the reliability of EEE parts acts very important in the satellite system. There are many factors that influence the reliability of EEE parts in the satellite system. Excessively dissipated heat can cause the failure of EEE parts and consequently, leading to a failure of total satellite system. In this paper, the thermal modeling using nodal network was compared with that using plate modeling to find out which one is the most suitable methodology. For a comparison, KOMPSAT- 1 SAR was modeled by two different modeling and the result was discussed. There was almost no difference in the numerical results between the two modeling methods. However, while it took much more time to perform thermal analysis using the nodal network modeling method, and the debugging was more difficult in the plate modeling method when the error is occurred. The computation time was considerably reduced by developing and implementing the input file format transfer code when using nodal network modeling method. It was found that the nodal network modeling method is suitable for the complicated components, such as SAR or transponder, because of its simple debugging ability. Excessive heat load was expected on some EEE parts of SAR such as high heat-dissipated diodes, transistors, and inductors due to increased power requirements of KOMPSAT-2 satellite system. The methods for the mitigation of heat load were studied through the design change of housing or the layout change of high power parts

Temperature-dependent evolutions of excitonic superfluid plasma frequency in a srong excitonic insulator candidate, Ta2_2NiSe5_5

We investigate an interesting anisotropic van der Waals material, Ta$_{2}$NiSe$_{5}$, using optical spectroscopy. Ta$_{2}$NiSe$_{5}$ has been known as one of the few excitonic insulators proposed over 50 years ago. Ta$_{2}$NiSe$_{5}$ has quasi-one dimensional chains along the $a$-axis. We have obtained anisotropic optical properties of a single crystal Ta$_{2}$NiSe$_{5}$ along the $a$- and $c$-axes. The measured $a$- and $c$-axis optical conductivities exhibit large anisotropic electronic and phononic properties. With regard to the $a$-axis optical conductivity, a sharp peak near 3050 cm$^{-1}$ at 9 K, with a well-defined optical gap ($\Delta^{EI} \simeq$ 1800 cm$^{-1}$) and a strong temperature-dependence, is observed. With an increase in temperature, this peak broadens and the optical energy gap closes around $\sim$325 K($T_c^{EI}$). The spectral weight redistribution with respect to the frequency and temperature indicates that the normalized optical energy gap ($\Delta^{EI}(T)/\Delta^{EI}(0)$) is $1-(T/T_c^{EI})^2$. The temperature-dependent superfluid plasma frequency of the excitonic condensation in Ta$_{2}$NiSe$_{5}$ has been determined from measured optical data. Our findings may be useful for future research on excitonic insulators.Comment: 17 pages, 5 figure

Heating temperature prediction of concrete structure damaged by fire using a Bayesian approach

A fire that occurs in a reinforced concrete (RC) structure accompanies a heating temperature, and this negatively affects the concrete material properties, such as the compressive strength, the bond between cement paste and aggregate, and the cracking and spalling of concrete. To appropriately measure the reduced structural performance and durability of fire-damaged RC structures, it is important to accurately estimate the heating temperature of the structure. However, studies in the literature on RC structures damaged by fire have focused mostly on structural member tests at elevated temperatures to ensure the fire resistance or fire protection material development; studies on estimating the heating temperature are very limited except for the very few existing models. Therefore, in this study, a heating temperature estimation model for a reinforced concrete (RC) structure damaged by fire was developed using a statistical Bayesian parameter estimation approach. For the model development, a total of 77 concrete test specimens were utilized; based on them, a statistically highly accurate model has been developed. The usage of the proposed method in the framework of the 500 ◦C isotherm method in Eurocode 2 has been illustrated through an RC column resistance estimation application

Tailoring Low-field Strain Properties of [0.97Bi1/2(Na0.78K0.22)1/2TiO3-0.03LaFeO3]-Bi1/2(Na0.82K0.18)1/2TiO3 Lead-Free Relaxor/Ferroelectric Composites

We investigated the effect of Bi1/2(Na0.82K0.18)1/2TiO3 (BNKT) modification on the ferroelectric and electric-field-induced strain (EFIS) properties of lead-free 0.97Bi1/2(Na0.82K0.18)1/2TiO3-0.03LaFeO3 (BNKTLF) ceramics as a function of BNKT content (x= 0, 0.1, 0.2, 0.3, 0.5, and 1). BNKT-modified BNKTLF powders were synthesized using a conventional solid-state reaction method. As the BNKT content x increased from 0 to 1 the normalized electric-field-induced strain (Smax/Emax) was observed to increase at relatively low fields, i.e., below the poling field. Moreover, BNKTLF-30BNKT showed about 460 pm/V as low as at 3 kV/mm, which is a considerably high value among the lead-free systems reported so far. Consequently, it was confirmed that ceramic-ceramic composite, a mixture of an ergodic relaxor matrix and embedded ferroelectric seeds, is a salient way to make lead-free piezoelectrics practical with enhanced EFIS at low field as well as less hysterical.ope

Comparative Data Mining Analysis for Information Retrieval of MODIS Images: Monitoring Lake Turbidity Changes at Lake Okeechobee, Florida

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates might be empirical regression, neural network model, support vector machine, genetic algorithm/genetic programming, analytical equation, etc. This paper compares three types of data mining techniques, including multiple non-linear regression, artificial neural networks, and genetic programming, for estimating multi-temporal turbidity changes following hurricane events at Lake Okeechobee, Florida. This retrospective analysis aims to identify how the major hurricanes impacted the water quality management in 2003-2004. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite imageries were used to retrieve the spatial patterns of turbidity distributions for comparison against the visual patterns discernible in the in-situ observations. By evaluating four statistical parameters, the genetic programming model was finally selected as the most suitable data mining tool for classification in which the MODIS band 1 image and wind speed were recognized as the major determinants by the model. The multi-temporal turbidity maps generated before and after the major hurricane events in 2003-2004 showed that turbidity levels were substantially higher after hurricane episodes. The spatial patterns of turbidity confirm that sediment-laden water travels to the shore where it reduces the intensity of the light necessary to submerged plants for photosynthesis. This reduction results in substantial loss of biomass during the post-hurricane period