Analysis of the critical pool level of partially submerged slopes

Author(s):  
Wei Wang ◽  
D.V. Griffiths
Keyword(s):  
2011 ◽  
Vol 130-134 ◽  
pp. 1894-1897
Author(s):  
Zhong An Yu ◽  
Wei Qin Tan ◽  
Zheng Hua Xie

Grinding-classification procedure is the key link of dressing production. This paper briefly introduced the technology of grinding and classification, and designed the computer control system of grinding and classification process, the realization of the grinder concentration control is by variable ratio control and the control of pump pool level is realized by average control, which realized automatic control for the concentration and flow of the grinding and classification, and presented the design of hardware and software for the control system.


1992 ◽  
Vol 26 (1) ◽  
pp. 13-20 ◽  
Author(s):  
�. K. Aleksandrovskaya ◽  
V. P. Volkov ◽  
O. G. Margolina ◽  
L. N. Pavlovskaya ◽  
O. N. Nosova
Keyword(s):  

SPE Journal ◽  
2017 ◽  
Vol 23 (03) ◽  
pp. 841-867 ◽  
Author(s):  
Mazda Irani

Summary Steam-assisted-gravity-drainage (SAGD) industry experience indicates that the majority of producer workovers occur because of liners or electrical submersible pumps (ESPs), and both failures appear to result from inefficient “steam-trap control.” Thermodynamic steam-trap control, also termed “subcool control,” is a typical operation strategy for most SAGD wells. Simply, subcool (or reservoir subcool vs. pump subcool) is the temperature difference between the steam chamber (or injected steam) and the produced fluid. The main objective is to keep subcool higher than a set value that varies between 0 to 40° and even higher values. This study presents a method to calculate the liquid-pool level from the temperature profile in observation wells, and liquid-pool shrinkage as a function of time. Unfortunately, it is not practical to monitor the liquid level by having observation wells for every SAGD well pair. For this reason, the algebraic equation for liquid-pool depletion on the basis of wellbore-drawdown, subcool, and emulsion productivity is generated. By use of this equation, the envelopes are suggested to differentiate three different regimes: “stable production,” “liquid-pool depletion,” and “steam-breakthrough limit.” Gas lift operations such as the MacKay River thermal project suggested that envelopes for constant wellbore drawdown are not practical. Therefore, the steam-breakthrough limit is defined for constant rate, which is more consistent in gas lift operations. In this study, the steam-breakthrough limit is validated for operation data from the MacKay River. This study provides a new insight into how factors such as production rate and wellbore drawdown can compromise subcool control and cause steam breakthrough, and how liquid-pool depletion may result in uncontrolled steam coning at long time. As a part of this study, a minimum-subcool concept (or target reservoir subcool) is presented as a function of skin and pressure drawdown. It is shown that the minimum subcool is highly dependent on the maturity of steam-chamber and underburden heat loss especially for zero-skin producers. The results of this work emphasize that the target subcool on the producer should increase slightly with chamber maturity, considering that the skin is nonzero for most SAGD producers.


2015 ◽  
Vol 833 ◽  
pp. 15-18 ◽  
Author(s):  
Zhi Pu Pei ◽  
Dong Ying Ju ◽  
Hong Yang Zhao ◽  
Xiao Dong Hu

A quantitative understanding of the twin-roll casting process is required to get high quality as-cast magnesium alloy strips. In this paper, a thermal flow-solidification simulation was carried out to study the behavior of casting zone and its effects on defects generation deeply. Results show that a lower pouring temperature is not suitable for producing defect-free magnesium alloy strips. With increasing of the casting speed, the tendency of cracks formation will getting smaller because of the more uniform temperature distribution. A low pool level leads to a small metal-roll contact area, and a sharp temperature distribution will generates under this situation, which is not good for strips quality.


The authors apply deep neural networks, a type of machine learning method, to model agency mortgage-backed security (MBS) 30-year, fixed-rate pool prepayment behaviors. The neural networks model (NNM) is able to produce highly accurate model fits to the historical prepayment patterns as well as accurate sensitivities to economic and pool-level risk factors. These results are comparable with model results and intuitions obtained from a traditional agency pool-level prepayment model that is in production and was built via many iterations of trial and error over many months and years. This example shows NNM can process large datasets efficiently, capture very complex prepayment patterns, and model large group of risk factors that are highly nonlinear and interactive. The authors also examine various potential shortcomings of this approach, including nontransparency/“black-box” issues, model overfitting, and regime shift issues.


2015 ◽  
Vol 16 (1) ◽  
pp. 104-121 ◽  
Author(s):  
Uwe Dulleck ◽  
Jonas Fooken ◽  
Jacob Fell

Abstract We compare the consistency of choices in two methods used to elicit risk preferences on an aggregate as well as on an individual level. We ask subjects to choose twice from a list of nine decisions between two lotteries, as introduced by Holt and Laury (2002, 2005) alternating with nine decisions using the budget approach introduced by Andreoni and Harbaugh (2009). We find that, while on an aggregate (subject pool) level the results are consistent, on an individual (within-subject) level, behaviour is far from consistent. Within each method as well as across methods we observe low (simple and rank) correlations.


2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
Zhenhong Wang ◽  
Ming Zhang ◽  
Junfeng Yu ◽  
Ruicong Jiang ◽  
Xiaolu Yin ◽  
...  

Information on the maintenance of diversity patterns from regional to local scales is dispersed among academic fields due to the local focus of community ecology. To better understand these patterns, the study of ecological communities needs to be expanded to larger scales and the various processes affecting them need to be integrated using a suitable quantitative method. We determined a range of communities on a flora-subregional scale in Yunnan province, China (383210.02 km2). A series of species pools were delimited from the regional to plot scales. Plant diversity was evaluated and abiotic and biotic processes identified at each pool level. The species pool effect was calculated using an innovative model, and the contribution of these processes to the maintenance of plant species diversity was determined and integrated: climate had the greatest effect at the flora-subregional scale, with historical and evolutionary processes contributing ∼11%; climate and human disturbance had the greatest effect at the local site pool scale; competition exclusion and stress limitation explained strong filtering at the successional stage pool scale; biotic processes contributed more on the local community scale than on the regional scale. Scale expansion combined with the filtering model approach solves the local problem in community ecology.


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