• Title/Summary/Keyword: BMP 테스트

Search Result 4, Processing Time 0.008 seconds

Characteristics for Co-digestion of Food Waste and Night Soil using BMP Test (BMP실험을 이용한 음식물폐기물 및 분뇨의 병합소화 특성)

  • Cho, Jinkyu;Kim, Hyungjin;Oh, Daemin
    • Journal of the Korean GEO-environmental Society
    • /
    • v.15 no.9
    • /
    • pp.13-18
    • /
    • 2014
  • BMP test was carried out to evaluate the characteristics for co-digestion of night soil and food waste. 6 types of sludge were tested in 30 days which were raw, excess, digested, night soil/septic tank (1:1), food waste (food : dilution water = 1:1), and mixed sludge. Bio gas was produced actively after 2 days, and continued in 2 weeks. Gas generation amount was decreased rapidly after considerable space of time. Especially maximum productivity of gas was shown in 7~8 days. The ultimate methane yields of raw, excess, digested, night soil/septic tank, food waste, and mixed sludge were 64.63, 67.49, 66.45, 72.44, 107.85, and 46.71 mL $CH_4/g$ VS respectively from Modified Gompertz model. The lag growth phase time and maximum specific methane production rate of mixed sludge were 1.88 day and 80.4 mL/day respectively. The methane potential of mixed sludge was higher than individual sludge. So high methane potential was expected by controlling mixing ratio of food waste. Besides stable operation of digestion tank and the solution of oligotrophic problem were possible.

Estimation of Ultimate Methane Yields and Biodegradability from Urban Stream Sediments Using BMP Test (BMP(Biochemical Methane Potential) test를 통한 도심하천 퇴적물의 최종메탄발생수율 및 생분해도 산정)

  • Song, Jaehong;Kim, Seogku;Lee, Junki;Koh, Taehoon;Lee, Taeyoon
    • Journal of the Korean GEO-environmental Society
    • /
    • v.11 no.2
    • /
    • pp.33-42
    • /
    • 2010
  • The main objective of this study was to offer informations about the current conditions of stream sediments and to evaluate biochemical methane potentials of stream sediments from the urban streams in Busan city using conventional BMP tests. First we select total 5 urban streams and collect sediment samples. Then, COD, proximate analysis, volatile solid, organic carbon content and elemental analysis were conducted to determine characteristics of the sediments. Results show that COD, volatile solid and organic carbon content are determined in the range of $15.20{\sim}75.07mg\;g^{-1}$, 2.34~11.54% and 1.28~34.21%, respectively. Also, several biochemical methane potential tests were performed in a laboratory. As a result, pH values of the reactors generally increased and then stabilized at 7.11~7.35. In addition, C/N ratio, ultimate methane and carbon dioxide yield (mL/g VS) and biodegradability (%) were determined to 1.05~10.27, 10.1~179.4, 10.3~34.4 and 4.0~30.1, respectively. For the determination of the correlations between ultimate methane yield and ultimate carbon dioxide yield, C/N ratio, COD, volatile solid and organic carbon content, a linear model was fitted to the data using a least-squares algorithm. As a result, except for COD ($r^2=0.7586$) and volatile solid ($r^2=0.7876$), Linear model was well fitted to each data with good values of the correlation coefficient ($r^2=0.9795{\sim}0.9858$). Finally, we propose empirical equations, which contain C/N ratio or TOC, for the prediction of ultimate methane yield for the urban streams in Busan city.

Median Filtering Detection using Latent Growth Modeling (잠재성장모델링을 이용한 미디언 필터링 검출)

  • Rhee, Kang Hyeon
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.52 no.1
    • /
    • pp.61-68
    • /
    • 2015
  • In recent times, the median filtering (MF) detector as a forensic tool for the recovery of forgery images' processing history has concerned broad interest. For the classification of MF image, MF detector should be designed with smaller feature set and higher detection ratio. This paper presents a novel method for the detection of MF in altered images. It is transformed from BMP to several kinds of MF image by the median window size. The difference distribution values are computed according to the window sizes and then the values construct the feature set same as the MF window size. For the MF detector, the feature set transformed to the model specification which is computed using latent growth modeling (LGM). Through experiments, the test image is classified by the discriminant into two classes: the true positive (TP) and the false negative (FN). It confirms that the proposed algorithm is to be outstanding performance when the minimum distance average is 0.119 in the confusion of TP and FN for the effectivity of classification.

Biogas potential estimation for mono- and co-digestion of cow manure and waste grass (우분뇨와 폐잔디의 단독 및 병합소화 잠재량 평가)

  • Ahn, Johng-Hwa;Gillespie, Andrew;Shin, Seung Gu
    • Journal of the Korea Organic Resources Recycling Association
    • /
    • v.28 no.1
    • /
    • pp.15-25
    • /
    • 2020
  • Biogas production potential was experimentally estimated for mono- and co-digestion of cow manure and waste grass. The two organic wastes were mixed at five different ratios (100:0, 75:25, 50:50, 25:75, 0:100) on the volatile solids basis, and were assessed using biochemical methane potential (BMP) test. Thee reaction temperatures, 25℃, 30℃ and 35℃, were applied as well, resulting in 15 different combinations for the test. The results showed that both higher temperature and waste grass mixing ratio resulted in higher methane yield and maximum methane production rate. Based on the experimental results, a theoretical farm- or community-scale (240 or 2400 ㎥) anaerobic digester was designed to evaluate the energy balance associated with mono- and co-digestion of the wastes at different temperatures. Although the energy production increased as the temperature and the waste grass mixing ratio increased, the net energy gain, energy production subtracted by energy consumption for heating and maintenance, was estimated to be the highest at 30℃, followed by at 35℃ and 25℃. Therefore, it is advised that both the experimental methane production and the detailed design parameters must be considered for the optimization of the net energy gain from these wastes.