• Nuclear Engineering and Technology
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• 제40권3호
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• pp.175-182
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• 2008

The results of process development for the blending of waste salt from the electrorefining of spent fuel with zeolite-A are presented. This blending is a key step in the ceramic waste process being used for treatment of EBR-II spent fuel and is accomplished using a high-temperature v-blender. A labscale system was used with non-radioactive surrogate salts to determine optimal particle size distributions and time at temperature. An engineering-scale system was then installed in the Hot Fuel Examination Facility hot cell and used to demonstrate blending of actual electrorefiner salt with zeolite. In those tests, it was shown that the results are still favorable with actinide-loaded salt and that batch size of this v-blender could be increased to a level consistent with efficient production operations for EBR-II spent fuel treatment. One technical challenge that remains for this technology is to mitigate the problem of material retention in the v-blender due to formation of caked patches of salt/zeolite on the inner v-blender walls.

• 약학회지
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• 제21권2호
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• pp.95-100
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• 1977

The effects of the particle size on the homogeneity of mixing and segregation of caffeine-lactose (1:99) mixture were studied. Using the two kinds of caffein, milled and unmilled caffein, V-type blender, the degree of mixing according to the particle size was predicted and the experiment on the change of mixedness by mixing time was carried out by the method derived from mixing index theory by Poole et al. and Hersey. the results could be summarized as follows; (1) The homogeneity of mixing was greatly affected by the particle size and the particle size should be reduced to the adepuate level to attain the desirable mixedness. (2) The homogeneity was not proportional to the mixing time and optimum mixing time for caffein-lactose was about 10 minutes. (3) Segregation tendency was increased by the particle size increase and greatly affected by the flow time in the segregation cell.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권4호
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• pp.387-394
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• 2016

This paper presents a fully digital delay locked loop (DLL) that can acquire lock in four clock cycles with a resolution of a 1/4 NAND-delay. The proposed DLL with a multi-dither-free phase detector acquires the initial lock in four clock cycles with 1/2 NAND-delay. Then, it utilizes a multi-dither-free phase detector, a region accumulator, and phase blenders, to improve the resolution to a 1/4 NAND-delay. The region accumulator which continuously steers the control registers and the phase blender, adaptively controls the tracking bandwidth depending on the amount of jitter, and effectively suppresses the dithering jitter. Fabricated in a 65 nm CMOS process, the proposed DLL occupies $0.0432mm^2$, and consumes 3.7 mW from a 1.2-V supply at 2 GHz.

• 분석과학
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• 제16권1호
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• pp.70-77
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• 2003

Hydroxyanilide계 살균제 fenhexamid의 작물 (오이, 딸기, 포도) 중 잔류량을 전자포획검출기가 장착된 기체크로마토그래피를 이용하여 최적 분석조건을 설정하고, 처리시기별 잔류량을 구하였다. 각 시료를 blender로 마쇄 후 acetone으로 1차 추출 한 후 dichloromethane으로 2차 추출하였으며, silica gel이 충전된 plastic 컬럼에서 acetone:hexane (5:95, 15:85, v/v) 혼합액으로 분리하였다. 표준 검량선의 회귀방정식은 0.05~0.20 ng에서 오이 Y=312.40X+10.26, 딸기 Y=313.33X+5.54, 포도 Y=253.27X-2.23 이었으며, 각각 $R^2=0.9996$, $R^2=0.9998$, $R^2=0.9994$의 직선성을 나타내었다. 0.10 mg/L 과 0.40 mg/L의 표준시료 처리시 평균 회수율은 오이, 딸기, 포도 각각 94.8%, 88.1%, 93.7% 이었으며, 순수표준품의 검출한계는 0.01 mg/L이었다. 각 작물체의 잔류량은 0.01~0.58 mg/L 범위이었다.

• 한국식품영양과학회지
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• 제11권3호
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• pp.29-33
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• 1982

맛있고 과학적인 생란을 만들기 위해서 생강의 매운맛 빼는 정도, 생강을 다지는 기구의 차이, 졸이는 시간의 변화, 생강 꿀 설탕 물 등의 배합재료와 배합 비의 차이가 있게 생란을 만들어서 관능검사를 하여 우수한 recipe와 좋은 조건을 알아내고, texurometer로 그 texture를 측정한 결과 다음과 같은 결론을 얻었다. (1) 생란을 만드는 생강의 매운맛을 빼는 방법은 칼로 다진 생강 200g에 물 600ml를 넣고 1차 가열 후 그 물을 버리고 다시 물 1400ml로 헹구어내고, 다시 물 600ml를 부어 2차 가열 후 생강무게가 130g이 되도록 짠 것이 매운맛 정도가 적당했다. (2) 졸이는 시간에 변화를 준 생란은 시간이 긴 편이 hardness와 adhesiveness는 높았으나 cohesiveness, elasticity, gumminess, cheviness는 낮았다. 졸이는 시간은 55분이 좋았다. (3) 생강을 다질 때 칼로 다져서 만든 생란이 Blender에 갈아서 만든 생란보다 hardness, cohesiveness, elasticity, gumminess, chewiness가 높고 adhesiveness만이 낮았다. (4) 꿀의 양에 변화를 준 생란은 꿀이 많을수록 hardness, cohesiveness, elasticity, gumminess, chewiness가 낮았고 adhesiveness만이 높았으므로 꿀의 양은 74g이 좋았다. (5) 생란의 이상적인 recipe는 매운맛 뺀 생강 130g, 설탕 100g, 물 200ml, 꿀 74g을 넣고 55분 가열한 것이다. 이 때의 온도는 $102^{\circ}C$, 당도는 76%였다.

• Smart Structures and Systems
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• 제31권5호
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• pp.469-483
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• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.