Runoff volume model for Godavari sub-basin using HEC-RAS software

2021 ◽  
Author(s):  
S. Venkatcharyulu ◽  
G. K. Viswanadh
Keyword(s):  
Volume Model ◽  
Runoff Volume

Preliminary uncertainty analysis – a prerequisite for assessing the predictive uncertainty of hydrologic models

1996 ◽  
Vol 33 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Jian Hua Lei ◽  
Wolfgang Schilling
Keyword(s):  
Uncertainty Analysis ◽  
Model Parameters ◽  
Observation Data ◽  
Calibration Data ◽  
Model Output ◽  
Predictive Uncertainty ◽  
Runoff Volume ◽  
Output Uncertainty ◽  
Sensitive Parameters ◽  
Calculated Model

Physically-based urban rainfall-runoff models are mostly applied without parameter calibration. Given some preliminary estimates of the uncertainty of the model parameters the associated model output uncertainty can be calculated. Monte-Carlo simulation followed by multi-linear regression is used for this analysis. The calculated model output uncertainty can be compared to the uncertainty estimated by comparing model output and observed data. Based on this comparison systematic or spurious errors can be detected in the observation data, the validity of the model structure can be confirmed, and the most sensitive parameters can be identified. If the calculated model output uncertainty is unacceptably large the most sensitive parameters should be calibrated to reduce the uncertainty. Observation data for which systematic and/or spurious errors have been detected should be discarded from the calibration data. This procedure is referred to as preliminary uncertainty analysis; it is illustrated with an example. The HYSTEM program is applied to predict the runoff volume from an experimental catchment with a total area of 68 ha and an impervious area of 20 ha. Based on the preliminary uncertainty analysis, for 7 of 10 events the measured runoff volume is within the calculated uncertainty range, i.e. less than or equal to the calculated model predictive uncertainty. The remaining 3 events include most likely systematic or spurious errors in the observation data (either in the rainfall or the runoff measurements). These events are then discarded from further analysis. After calibrating the model the predictive uncertainty of the model is estimated.

scholarly journals Real Color Model of a Cadaver for Deep Brain Stimulation of the Subthalamic Nucleus

2021 ◽  
Vol 11 (11) ◽  
pp. 4999
Author(s):  
Chung-Yoh Kim ◽  
Jin-Seo Park ◽  
Beom-Sun Chung
Keyword(s):  
Deep Brain Stimulation ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Magnetic Resonance Images ◽  
Target Point ◽  
Anatomical Structures ◽  
Volume Model ◽  
Segmented Images ◽  
Volume Models ◽  
Deep Brain

When performing deep brain stimulation (DBS) of the subthalamic nucleus, practitioners should interpret the magnetic resonance images (MRI) correctly so they can place the DBS electrode accurately at the target without damaging the other structures. The aim of this study is to provide a real color volume model of a cadaver head that would help medical students and practitioners to better understand the sectional anatomy of DBS surgery. Sectioned images of a cadaver head were reconstructed into a real color volume model with a voxel size of 0.5 mm × 0.5 mm × 0.5 mm. According to preoperative MRIs and postoperative computed tomographys (CT) of 31 patients, a virtual DBS electrode was rendered on the volume model of a cadaver. The volume model was sectioned at the classical and oblique planes to produce real color images. In addition, segmented images of a cadaver head were formed into volume models. On the classical and oblique planes, the anatomical structures around the course of the DBS electrode were identified. The entry point, waypoint, target point, and nearby structures where the DBS electrode could be misplaced were also elucidated. The oblique planes could be understood concretely by comparing the volume model of the sectioned images with that of the segmented images. The real color and high resolution of the volume model enabled observations of minute structures even on the oblique planes. The volume models can be downloaded by users to be correlated with other patients’ data for grasping the anatomical orientation.

scholarly journals Effect of an Improved Yasutomi Pressure-Viscosity Relationship on the Elastohydrodynamic Line Contact Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Vincenzo Petrone ◽  
Adolfo Senatore ◽  
Vincenzo D'Agostino
Keyword(s):  
High Pressure ◽  
Film Thickness ◽  
Free Volume ◽  
Experimental Studies ◽  
Line Contact ◽  
Volume Model ◽  
Free Volume Model ◽  
Pressure Area ◽  
New Formulation ◽  
Lubricant Viscosity

This paper presents the application of an improved Yasutomi correlation for lubricant viscosity at high pressure in a Newtonian elastohydrodynamic line contact simulation. According to recent experimental studies using high pressure viscometers, the Yasutomi pressure-viscosity relationship derived from the free-volume model closely represents the real lubricant piezoviscous behavior for the high pressure typically encountered in elastohydrodynamic applications. However, the original Yasutomi correlation suffers from the appearance of a zero in the function describing the pressure dependence of the relative free volume thermal expansivity. In order to overcome this drawback, a new formulation of the Yasutomi relation was recently developed by Bair et al. This new function removes these concerns and provides improved precision without the need for an equation of state. Numerical simulations have been performed using the improved Yasutomi model to predict the lubricant pressure-viscosity, the pressure distribution, and the film thickness behavior in a Newtonian EHL simulation of a squalane-lubricated line contact. This work also shows that this model yields a higher viscosity at the low-pressure area, which results in a larger central film thickness compared with the previous piezoviscous relations.

Green roof hydrologic performance and modeling: a review

2013 ◽  
Vol 69 (4) ◽  
pp. 727-738 ◽  
Author(s):  
Yanling Li ◽  
Roger W. Babcock
Keyword(s):  
Peak Flow ◽  
Green Roof ◽  
Field Measurements ◽  
Green Roofs ◽  
Economic Benefits ◽  
Design Parameters ◽  
Technical Literature ◽  
Factors Affecting ◽  
Model Soil ◽  
Runoff Volume

Green roofs reduce runoff from impervious surfaces in urban development. This paper reviews the technical literature on green roof hydrology. Laboratory experiments and field measurements have shown that green roofs can reduce stormwater runoff volume by 30 to 86%, reduce peak flow rate by 22 to 93% and delay the peak flow by 0 to 30 min and thereby decrease pollution, flooding and erosion during precipitation events. However, the effectiveness can vary substantially due to design characteristics making performance predictions difficult. Evaluation of the most recently published study findings indicates that the major factors affecting green roof hydrology are precipitation volume, precipitation dynamics, antecedent conditions, growth medium, plant species, and roof slope. This paper also evaluates the computer models commonly used to simulate hydrologic processes for green roofs, including stormwater management model, soil water atmosphere and plant, SWMS-2D, HYDRUS, and other models that are shown to be effective for predicting precipitation response and economic benefits. The review findings indicate that green roofs are effective for reduction of runoff volume and peak flow, and delay of peak flow, however, no tool or model is available to predict expected performance for any given anticipated system based on design parameters that directly affect green roof hydrology.

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