Two-component epoxy resin is widely used in the cultural heritage restoration field. However according to mixing ratio of resin and hardener, curing property, mechanical strength and chemical structure differ which have possibility to effect the stability of cultural heritage. Result of questionnaire survey shows hands-on workers in the conservation field tend to mix the epoxy resin with his or her eye measurement when the using amount is small or mix additional hardener to shorten the pot life of epoxy resin. This research aims to analyze the curing property, mechanical strength and chemical structure of rapid curing type epoxy resin and medium curing type one depending on relative ratio of 0.25~4 of hardener to resin. When the amount of hardener was 0.5~2 times more than the resin, exothermic heat and curing speed were both increased. In case of included hardener to resin was lower than official ratio, mechanical strength (tensile shear strength, tensile strength and compressive strength) became higher along with active cross-linking bonding of the epoxy resin. Medium curing type epoxy relatively had lower exothermic heat and slower reaction during curing process. It was observed to be put to definite point of mechanical strength under lower content of hardener than official ratio. While, hardener ratio more than twice the resin slowed down the curing greatly and lowered the adhesion strength also. In conclusion, under the lower mixing rate of hardener than official ratio would show relatively fast reaction with similar mechanical strength. Over the official ratio on the other hand, material property drops rapidly. Accordingly, mixing ratio of epoxy resin is expected to be influential to the stability of cultural heritage.
Harmful cyanobacterial monitoring is time-consuming and requires skilled professionals. Recently, Phycocyanin, the accessory pigment unique to freshwater cyanobacteria, has been proposed as an indicator for the presence of cyanobacteria, with the advantage of rapid and simple measurement. The purpose of this research was to evaluate the correlation between the harmful cyanobacterial cell density and the concentration of phycocyanin and to consider how to use the real-time water quality monitoring system for algae bloom monitoring. In the downstream of the Nakdong River, Microcystis spp. showed maximum cell density (99 %) in harmful cyanobacteria (four target genera). A strong correlation between phycocyanin(measured in the laboratory) concentrations and harmful cyanobacterial cell density was observed (r = 0.90, p < 0.001), while a weaker relationship (r = 0.65, p < 0.001) resulted between chlorophyll a concentration and harmful cyanobacterial cell density. As a result of comparing the phycocyanin concentration (measured in submersible fluorescence sensor) and harmful cyanobacterial cell density, the error range increased as the number of cyanobacteria cells increased. Before opening the estuary bank, the diurnal variations of phycocyanin concentrations did not mix by depth, and in the case of the surface layer, a pattern of increase and decrease over time was shown. This study is the result of analysis when Microcystis spp. is dominant in downstream of Nakdong River in summer, therefore the correlation between the harmful cyanobacteria density and phycocyanin concentrations should be more generalized through spatio-temporal expansion.
In order to measure the volatile organic compounds (VOCs) of a sample which is too large to use commercially available chamber, a stainless steel vacuum chamber (VC) (with an internal diameter of 205 mm and a height of 50 mm) was manufactured and the temperature of the chamber was controlled using an oven. After concentrating the volatiles of the sample in the chamber by helium gas, it was made possible to remove residual volatile substances present in the chamber under reduced pressure ((2 ± 1) × 10-2 mmHg). The chamber was connected to a purge & trap (P&T) using a 6 port valve to concentrate the VOCs, which were analyzed by gas chromatography-mass spectrometry (GC-MS) after thermal desorption (VC-P&T-GC-MS). Using toluene, the toluene recovery rate of this device was 85 ± 2 %, reproducibility was 5 ± 2 %, and the detection limit was 0.01 ng L-1. The method of removing VOCs remaining in the chamber with helium and the method of removing those with reduced pressure was compared using Korean drinking water regulation (KDWR) VOC Mix A (5 μL of 100 ㎍ mL-1) and butylated hydroxytoluene (BHT, 2 μL of 500 ㎍ mL-1). In case of using helium, which requires a large amount of gas and time, reduced pressure ((2 ± 1) × 10-2 mmHg) only during the GC-MS running time, could remove VOCs and BHT to less than 0.1 % of the original injection concentration. As a result of analyzing volatile substances using VC-P&T-GC-MS of six types of cell phone case, BHT was detected in four types and quantitatively analyzed. Maintaining the chamber at reduced pressure during the GC-MS analysis time eliminated memory effect and did not affect the next sample analysis. The volatile substances in a cell phone case were also analyzed by dynamic headspace (HT3) and GC-MS, and the results of the analysis were compared with those of VC-P&T-GC-MS. Considering the chamber volume and sample weight, the VC-P&T configuration was able to collect volatile substances more efficiently than the HT3. The VC-P&T-GC-MS system is believed to be useful for VOCs measurement of inhomogeneous large sample or devices used inside clean rooms.
Purpose - Despite the importance of price, many companies do not implement pricing policies smoothly, because typical price management strategies insufficiently consider logistics efficiency and an increase in logistics costs due to logistics waste. This study attempts to examine the effect of product line pricing, which corresponds to product mix pricing, on logistics efficiency in the case of manufacturer A, and analyzes how logistics performance changes in response to these variables. Research design, data, and methodology - This study, based on the case of manufacturer A, involved research through understanding the current status, analyses, and then proposing improvement measures. Among all the products of manufacturer A, product group B was selected as the research object, and its distribution channel and line pricing were examined. As a result of simulation, for products with low loading efficiency, improvement measures such as changing the number of bags in the box were suggested, and a quantitative analysis was conducted on how these measures influence logistics costs. The TOPS program was used for the Pallet loading efficiency simulation tool in this study. To prevent products from protruding out of the pallet, the maximum measurement was set as 0.0mm, and loading efficiency was based on the pallet area, and not volume. In other words, its size (length x width) was focused upon, following the purpose of this study and, then, the results were obtained. Results - As a result of the loading efficiency simulation, when the number of bags in the box was changed for 36 products with low average loading efficiency of 73.7%, as shown in