scholarly journals Improved Model for Predicting Total Dissolved Gas Generation With the Residence Time of the Water in the Stilling Phase

2022 ◽  
Vol 9 ◽  
Author(s):  
Yiyun Peng ◽  
Yuqing Lin ◽  
Chenjun Zeng ◽  
Wei Zha ◽  
Feijian Mao ◽  
...  
Keyword(s):  
Mass Transfer ◽  
Residence Time ◽  
Empirical Model ◽  
Prediction Models ◽  
Generation Process ◽  
Dissolved Gas ◽  
Gas Generation ◽  
Water Renewal ◽  
Total Dissolved Gas ◽  
Renewal Model

Quantitative predictions of total dissolved gas (TDG) super-saturation are essential for developing operation schemes for high dams. Most TDG generation prediction models have various shortcomings that affect the accuracy of TDG super-saturation estimation, such as oversimplification of influencing factors and uncertainty in parameter values. In this study, the TDG generation process was divided into three parts, gas-liquid mass transfer process in the stilling phase, dilution resulting from the water jet plunging into the stilling phase, and outflow of TDG–super-saturated water from the stilling phase, while considering the water body and bubbles in the stilling phase as a whole. The residence time of the water in the stilling phase (Tr) was introduced to estimate mass transfer time, along with dimensional analysis methods. The properties of TDG generation were evaluated experimentally under varying Tr values. Based on the theoretical analysis and experimental results, a basic water renewal model was proposed and was validated using experimental data. Furthermore, prediction results of this model were compared with those of a classical empirical model and mechanical model based on observed data from a field survey at Xiluodu Dam. The results show that the relative errors between the predicted and experimental measurements were all less than 5%, indicating that the developed prediction model has a good performance. Compared with the mechanism model, the developed model could reduce the standard error (SE), normalized mean error (NME), and error of maximum (REMAX) by 60, 96, and 15%, respectively. Meanwhile, the developed model could reduce the SE, NME, REMAX by 17.4, 36, and 23%, respectively, compared with the empirical model. Considering all the error indexes, it can be concluded that the prediction performance of the water renewal model is the best among the three models. The proposed model was also more generically versatile than the existing models. Prediction results of water regeneration model for TDG could aid the drafting of governing strategies to minimize the risk of super-saturated TDG.

scholarly journals Energy dissipation efficiency as a new variable in the empirical correlation of total dissolved gas

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jingying Lu ◽  
Xiaolong Cheng ◽  
Zhenhua Wang ◽  
Ran Li ◽  
Jingjie Feng ◽  
...  
Keyword(s):  
Energy Dissipation ◽  
Standard Error ◽  
Air Entrainment ◽  
Empirical Equations ◽  
Generation Process ◽  
Field Observations ◽  
Dissolved Gas ◽  
Total Dissolved Gas ◽  
Future Work ◽  
Hydropower Stations

AbstractTotal dissolved gas (TDG) supersaturation, which occurs during dam spilling, may result in fish bubble disease and mortality. Many studies have been conducted to identify the factors pertaining to TDG generation, such as the spilling discharge and tailwater depth. Additionally, the energy dissipation efficiency should be considered due to its effect on the air entrainment, which influences the TDG generation process. According to the TDG field observations of 49 cases at Dagangshan and Xiluodu hydropower stations, the TDG was positively related to the energy dissipation efficiency, tailwater depth and discharge per unit width. A correlation between the generated TDG level and these factors was established. The empirical equations proposed by the USACE were calibrated, and the TDG level estimation performance was compared with the established correlation for 25 spillage cases at seven other dams. Among the considered cases, the standard error of the TDG estimation considering the energy dissipation efficiency was 5.7%, and those for the correlations obtained using the USACE equations were 13.0% and 10.0%. The findings indicated that the energy dissipation efficiency considerably influenced the TDG level, and its consideration helped enhance the precision of the TDG estimation. Finally, the generality of this approach and future work were discussed.

Understanding gas bubble trauma in an era of hydropower expansion: how do fish compensate at depth?

2020 ◽  
Vol 77 (3) ◽  
pp. 556-563 ◽  
Author(s):  
Naomi K. Pleizier ◽  
Charlotte Nelson ◽  
Steven J. Cooke ◽  
Colin J. Brauner
Keyword(s):  
Bubble Growth ◽  
Gas Bubble ◽  
Hydroelectric Dams ◽  
Dissolved Gas ◽  
Empirical Relationships ◽  
Lethal Effects ◽  
Exposed Fish ◽  
Total Dissolved Gas ◽  
Rainbow Trout Oncorhynchus Mykiss ◽  
The Relationship

Hydrostatic pressure is known to protect fish from damage by total dissolved gas (TDG) supersaturation, but empirical relationships are lacking. In this study we demonstrate the relationship between depth, TDG, and gas bubble trauma (GBT). Hydroelectric dams generate TDG supersaturation that causes bubble growth in the tissues of aquatic animals, resulting in sublethal and lethal effects. We exposed fish to 100%, 115%, 120%, and 130% TDG at 16 and 63 cm of depth and recorded time to 50% loss of equilibrium and sublethal symptoms. Our linear model of the log-transformed time to 50% LOE (R2 = 0.94) was improved by including depth. Based on our model, a depth of 47 cm compensated for the effects of 4.1% (±1.3% SE) TDG supersaturation. Our experiment reveals that once the surface threshold for GBT from TDG supersaturation is known, depth protects rainbow trout (Oncorhynchus mykiss) from GBT by 9.7% TDG supersaturation per metre depth. Our results can be used to estimate the impacts of TDG on fish downstream of dams and to develop improved guidelines for TDG.

scholarly journals Building prediction models for coronary heart disease by synthesizing multiple longitudinal research findings

2005 ◽  
Vol 12 (5) ◽  
pp. 459-464 ◽  
Author(s):  
Guizhou Hu ◽  
Martin M. Root
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Prediction Model ◽  
Empirical Model ◽  
Complex Disease ◽  
Prediction Models ◽  
Longitudinal Research ◽  
Study Data ◽  
Individual Risk ◽  
Data Set

Background No methodology is currently available to allow the combining of individual risk factor information derived from different longitudinal studies for a chronic disease in a multivariate fashion. This paper introduces such a methodology, named Synthesis Analysis, which is essentially a multivariate meta-analytic technique. Design The construction and validation of statistical models using available data sets. Methods and results Two analyses are presented. (1) With the same data, Synthesis Analysis produced a similar prediction model to the conventional regression approach when using the same risk variables. Synthesis Analysis produced better prediction models when additional risk variables were added. (2) A four-variable empirical logistic model for death from coronary heart disease was developed with data from the Framingham Heart Study. A synthesized prediction model with five new variables added to this empirical model was developed using Synthesis Analysis and literature information. This model was then compared with the four-variable empirical model using the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Follow-up Study data set. The synthesized model had significantly improved predictive power ( x2 = 43.8, P < 0.00001). Conclusions Synthesis Analysis provides a new means of developing complex disease predictive models from the medical literature.

The Effect of Shear Flow and Dissolved Gas Diffusion on the Cavitation in a Submerged Journal Bearing

2000 ◽  
Vol 123 (3) ◽  
pp. 494-500 ◽  
Author(s):  
M. Groper ◽  
I. Etsion
Keyword(s):  
Mass Transfer ◽  
Shear Flow ◽  
Mass Transport ◽  
Transport Mechanism ◽  
Journal Bearing ◽  
Gas Diffusion ◽  
Gas Bubble ◽  
Dissolved Gas ◽  
Rotating Shaft ◽  
Mass Transfer Mechanism

Two possible, long standing speculated mechanisms are theoretically investigated in an attempt to understand previous experimental observations of pressure build up in the cavitation zone of a submerged journal bearing. These mechanisms are (1) the shear of the cavity gas bubble by a thin lubricant film dragged through the cavitation zone by the rotating shaft and (2) the mass transfer mechanism which dictates the rate of diffusion of dissolved gas out of and back into the lubricant. A comparison with available experimental results reveals that while the cavitation shape is fairly well predicted by the “shear” mechanism, this mechanism is incapable of generating the level of the experimentally measured pressures, particularly towards the end of the cavitation zone. The “mass transport” mechanism is found inadequate to explain the experimental observations. The effect of this mechanism on the pressure build up in the cavitation zone can be completely ignored.

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