On the Bulk Density of Boiling Liquid Oxygen

The apparent specific gravities of boiling liquid oxygen which resulted from weighing in the liquid a series of metals and other substances were given in a lecture entitled “New Researches on Liquid Air,” printed in the Royal Institution ‘Proceedings’ for 1896. For instance, silver, calc spar, rock crystal, and iodide of silver gave the respective apparent densities 1·1278, 1·1352, 1·1316, and 1·1372. On correcting the weight of liquid displaced by each substance for contraction to — 182°·6—by calculating a Fizeau mean coefficient of expansion for the range of temperature employed, on the assumption that the parabolic formula might be legitimately extended to low temperatures,—it was found that the real density of liquid oxygen so deduced for all the bodies used was, as a mean, 1·137.

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A novel approach to white liquor control in a continuous digester using the Box-Jenkins methodology to predict chip bulk density

TAPPI Journal ◽

10.32964/tj14.6.395 ◽

2015 ◽

Vol 14 (6) ◽

pp. 395-402

Author(s):

FLÁVIO MARCELO CORREIA ◽

JOSÉ VICENTE HALLAK D’ANGELO ◽

SUELI APARECIDA MINGOTI

Keyword(s):

Bulk Density ◽

Moving Average ◽

Pulp Mill ◽

Statistical Decision ◽

White Liquor ◽

Novel Approach ◽

Cooking Process ◽

Eucalyptus Kraft Pulp ◽

Relevant Variables ◽

Kraft Cooking

Alkali charge is one of the most relevant variables in the continuous kraft cooking process. The white liquor mass flow rate can be determined by analyzing the chip bulk density fed to the process. At the mills, the total time for this analysis usually is greater than the residence time in the digester. This can lead to an increasing error in the mass of white liquor added relative to the specified alkali charge. This paper proposes a new approach using the Box-Jenkins methodology to develop a dynamic model for predicting chip bulk density. Industrial data were gathered on 1948 observations over a period of 12 months from a Kamyr continuous digester at a bleached eucalyptus kraft pulp mill in Brazil. Autoregressive integrated moving average (ARIMA) models were evaluated according to different statistical decision criteria, leading to the choice of ARIMA (2,0,2) as the best forecasting model, which was validated against a new dataset gathered during 2 months of operations. A combination of predictors has shown more accurate results compared to those obtained by laboratory analysis, allowing a reduction of around 25% of the chip bulk density error to the alkali addition amount.

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