Beijing Institute of Petrochemical Technology

About: Beijing Institute of Petrochemical Technology is a education organization based out in Beijing, China. It is known for research contribution in the topics: Catalysis & Corrosion. The organization has 2468 authors who have published 1937 publications receiving 19270 citations.

Optimizing environmental insulation thickness of buildings with CHP-based district heating system based on amount of energy and energy grade

Abstract: The increase of insulation thickness (IT) results in the decrease of the heat demand and heat medium temperature. A mathematical model on the optimum environmental insulation thickness (OEIT) for minimizing the annual total environmental impact was established based on the amount of energy and energy grade reduction. Besides, a case study was conducted based on a residential community with a combined heat and power (CHP)-based district heating system (DHS) in Tianjin, China. Moreover, the effect of IT on heat demand, heat medium temperature, exhaust heat, extracted heat, coal consumption, carbon dioxide (CO2) emissions and sulfur dioxide (SO2) emissions as well as the effect of three types of insulation materials (i.e., expanded polystyrene, rock wool and glass wool) on the OEIT and minimum annual total environmental impact were studied. The results reveal that the optimization model can be used to determine the OEIT. When the OEIT of expanded polystyrene, rock wool and glass wool is used, the annual total environmental impact can be reduced by 84.563%, 83.211%, and 86.104%, respectively. It can be found that glass wool is more beneficial to the environment compared with expanded polystyrene and rock wool.

A TG-IR study on the co-pyrolysis characteristics of oily sludge and crops

Abstract: The co-pyrolysis characteristics of oily sludge (OS), wheat straw (WS), peanut straw(PS), and coconut shell (CS) have been studied experimentally with the thermogravimetric infrared analyzer, and the precipitation characteristics of the main reaction products were analyzed. During the separate pyrolysis of OS, the main weight loss stage appeared in 200–500 °C and the maximum weight loss peak appeared at 460 °C; its value is 8.42%/min. For the three additives, the main weight loss stage of all the three additives appeared in 200–400 °C; the maximum weight loss peak values of WS, PS, and CS were 11.38%/min, 8.77%/min, and CS 12.03%/min, respectively. It has been found that the three additives promoted the pyrolysis reaction of OS, and the mean apparent activation energy of the reaction was significantly reduced when the content of WS was 40%, PS was 40%, and CS was 50%. WS and PS make the pyrolysis process more adequate, and the amount of residual material is reduced. The addition of three additives could reduce the production of CH4 and CO and increase the precipitation of CO2.

A Feature Selection Algorithm Based on Boosting for Road Detection

Abstract: Feature selection is very important for road detection. Generally, optimal feature set is very hard to be determined manually by prior-knowledge. In this paper, a feature selection algorithm based on boosting is proposed. To fully utilize potential feature correlations, the features are combined. The feature vector is enlarged by the combined features, and the new feature vector is called raw feature vector. In this paper, the classify power of each feature is evaluated by the error rate and converge speed of boosting classifier which is based on single feature. After that, the features are selected according to itpsilas classify power. The selected features are reassembled to B-feature vector. Then features are weighted according to its power in classification. The weighted B-feature vector is called B-W-Feature Vector. Three classifiers are used to evaluate the raw feature vector, the B-Feature and the B-W-Feature. The experiment results show selected and weighted feature vector can improve the classification performance.

First measurement of e(+)e(-) -g pK(S)(0)(n)over-barK(-) + c.c. above open charm threshold

Abstract: The process e(+)e(-) -> pK(S)(0)(n) over barK(-) + c.c. and its intermediate processes are studied for the first time, using data samples collected with the BESIII detector at BEPCII at center-o ...