Economic Dispatch by Water Cycle Algorithm
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The document describes the Water Cycle Algorithm (WCA), a nature-inspired metaheuristic optimization algorithm. It presents the key steps of the WCA, which simulates the natural water cycle process. Initial solutions are generated randomly as raindrops. The raindrops flow into rivers based on intensity calculations, and rivers flow into the sea, the lowest point. Positions are exchanged if better solutions are found. Evaporation and raining processes improve solutions until convergence is reached. The WCA is compared to other metaheuristics, with rivers guiding solutions and resemblance to genetic mutation.
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- A conceptual model was developed based on simulations from a detailed full hydrodynamic model to reduce computation time for real-time flood control applications.
- The conceptual model was developed through identifying representative discharges, storage points, and hydraulic structures from the river network and calibrating it using a limited number of full model simulations.
- The performance of the conceptual model was evaluated against historical flood events and showed close agreement with the full model, enabling its use for real-time flood control applications requiring many model iterations.
English ayur
The document summarizes a study on hydraulic modeling of a side-channel spillway at Iven Dam in Mongolia. The goals were to determine flow regimes using physical and numerical modeling, study hydraulic modeling methodology, and identify ways to improve standard design methods. Hydraulic modeling methods used included analytical fluid dynamics, experimental fluid dynamics with a physical model, and computational fluid dynamics. Results from physical and CFD models showed significant differences from the standard design method, indicating the need to update standard methods. The study concluded the spillway capacity should be increased and validated all hydraulic structures with physical and numerical models before construction.
Investigating WetSpa model application in the Distributed Model Intercomparis...
Ali Safari conducted PhD research from 2005-2009 investigating the WetSpa hydrological model. The research aimed to apply WetSpa to basins in the US using radar rainfall data, calibrate WetSpa parameters using PEST, improve high flow and peak predictions, and modify WetSpa to better predict flows in nested sub-basins. Key findings were that calibration improved WetSpa performance significantly but calibration of parent basins did not guarantee good performance in sub-basins, and WetSpa needed improvement in simulating high flows and peaks which was achieved by modifying surface runoff calculation.
johan_malmberg_thesis_pres_final
The document summarizes a numerical analysis of improving the aerodynamic performance of trucks through modifications to the design of the rear section. The analysis used computational fluid dynamics to simulate different boat-tail and rear flap designs. The best design was found to reduce drag by 21.2% compared to the baseline design. Further work is recommended to better capture unsteady effects and optimize designs for real trucks.
Mechanistic models
This document presents a method for predicting stream flow distributions based on climatic and geomorphic data alone, without discharge measurements. It combines a physically-based stream flow model with water balance and geomorphic recession flow models. Key parameters of the stream flow model are estimated from rainfall, potential evapotranspiration, and digital elevation model data. The method was tested on calibration and test catchments. While offering a unique approach, the method has limitations including additional assumptions and reduced accuracy of parameter estimates and flow regime predictions.
Using Fractals To Determine a Reservoir's Hydrocarbon Distribution
In order to determine a field’s hydrocarbon in place it is necessary to model the distribution of fluids throughout the reservoir. A water saturation vs. height (Swh) function provides this for the reservoir model. A good Swh function ensures the three independent sources of fluid distribution data are consistent. These being the core, formation pressure and electrical log data. The Swh function must be simple to apply, especially in reservoirs where it is difficult to map permeability or where there appears to be multiple contacts. It must accurately upscale the log and core derived water saturations to the reservoir model cell sizes.
This presentation clarifies the often misunderstood definitions for the free-water-level, transition zone and irreducible water saturation. Using capillary pressure theory and the concept of fractals, a practical Swh function is derived. Logs and core data from eleven fields, with very different porosity and permeability characteristics, depositional environments and geological age are compared. This study demonstrated how this Swh function is independent of permeability and litho-facies type and accurately describes the reservoir fluid distribution.
The shape of the Swh function shows that of the transition zone is related more to pore geometry rather than porosity or permeability alone. Consequently, this Swh function gives insights into a reservoir’s quality as determined by its pore architecture. A number of case studies are presented showing the excellent match between the function and well data. The function makes an accurate prediction of water saturations even in wells where the resistivity log was not run due to well conditions. The function defines the free water level, the hydrocarbon to water contact, net reservoir and the irreducible water saturation for the reservoir model. The fractal function provides a simple way to quality control electrical log and core data and justifies using core plug sized samples to model water saturations on the reservoir scale.
12 Fluid dynamics.pdf
This document introduces fluid dynamics and its biological and medical applications. It discusses key concepts such as:
- Flow rate and its relationship to velocity and how flow rate is calculated.
- Bernoulli's equation, which relates pressure and velocity in fluids and describes how pressure drops where velocity increases due to a gain in kinetic energy.
- Applications of Bernoulli's principle like how shower curtains bulge inward due to lower pressure caused by high velocity water, and how passing vehicles can be pushed together for the same reason.
- Other topics covered include the equation of continuity, laminar and turbulent flow, viscosity, and diffusion. Real-world examples involve calculating blood flow and vessel speeds.
GROUNDWATER MODELING SYSTEM
use of gms environment for numerical modeling of groundwater. modflow and modpath flow and transport models
Engineering project non newtonian flow back step
This document describes a numerical simulation of non-Newtonian fluid flow over a backward-facing step using two viscosity models: the power law model and Carreau model. The incompressible Navier-Stokes equations are solved using finite element analysis in MATLAB. Boundary conditions of no-slip walls and zero traction at the outlet are applied. Simulation results at different inlet velocities show shear thinning and thickening behavior for both models. The Carreau model is found to better handle very low or high shear rates compared to the power law model.
DSD-INT 2020 Real Time Hydrologic, Hydraulic and Water Quality Forecasting in...
Presentation by Tony McAlister, WaterTech, at the Delft3D User Days - Australian Time zone: Inland to Estuary, during Delft Software Days - Edition 2020. Tuesday, 10 November 2020.
Epanet for e.s. class 2011 6-21
Here are the key steps for working with EPANET and ArcGIS:
1. Create a water distribution network in ArcGIS by digitizing pipes, nodes, tanks, pumps etc. and add attribute data like diameters, elevations etc.
2. Export the GIS network to an EPANET input file with coordinates and attributes.
3. Run hydraulic and water quality simulations in EPANET.
4. Import EPANET output data like pressures, flows back into ArcGIS as event themes on the map for visualization and analysis.
5. Perform further analysis like locating low pressure areas, fire flow deficiencies etc. in ArcGIS by overlaying EPANET results on the network map.
CE573_Poster2
This study developed a rainfall-runoff model using HEC-HMS to simulate runoff from Irwin Creek watershed in Charlotte, North Carolina under current and future climate change precipitation scenarios. The model was calibrated and validated using stream gauge data and produced comparable results. Simulation of design storms indicated that an 18% increase in storm depth due to climate change could increase peak discharge by 43%. The study concluded HEC-HMS is a useful tool for watershed modeling and that future flood management should consider potential impacts of climate change.
Chapter 5 Fetter Ground water flow to wells
1) The document discusses groundwater flow to wells and pumping tests. It covers basic well hydraulics, assumptions of groundwater flow, and equations for confined, unconfined, and leaky aquifers.
2) The Theis and Jacob methods are presented for analyzing pumping test data from confined aquifers, while the Hantush and Walton methods are used for leaky aquifers.
3) Pumping tests are important to determine an aquifer's hydraulic properties and long-term well yield.
Modeling the water food-energy nexus in the arab world: River basin simulatio...
Modeling the water food-energy nexus in the arab world: River basin simulatio...International Food Policy Research Institute (IFPRI)
1. The document discusses using the RIBASIM river basin simulation model to model the water-food-energy nexus in Egypt. RIBASIM allows modeling of a river basin system including infrastructure, water allocation, and how the system changes over time.
2. Key components that can be modeled include reservoirs, dams, weirs, irrigation networks, hydropower production, water demands from cities and industries, and how available water is allocated. Scenarios can be run to simulate current and future situations up to 2030.
3. The model has been applied to the National Water Resources Plan of Egypt in order to test the impacts of climate change and measures under consideration. It is useful for simulatingSimilar to Economic Dispatch by Water Cycle Algorithm (20)
Investigating WetSpa model application in the Distributed Model Intercomparis...
Investigating WetSpa model application in the Distributed Model Intercomparis...
Using Fractals To Determine a Reservoir's Hydrocarbon Distribution
Using Fractals To Determine a Reservoir's Hydrocarbon Distribution
DSD-INT 2020 Real Time Hydrologic, Hydraulic and Water Quality Forecasting in...
DSD-INT 2020 Real Time Hydrologic, Hydraulic and Water Quality Forecasting in...
Modeling the water food-energy nexus in the arab world: River basin simulatio...
Modeling the water food-energy nexus in the arab world: River basin simulatio...
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Economic Dispatch by Water Cycle Algorithm
- 3. PRESENTATION FLOW • Introduction to WCA • Schematic Diagram of hydrologic Cycle • Mathematical Formulation of WCA • Schematic View of WCA • Strength Comparison University of Engineering & Technology 20/6/2018
- 4. Introduction to Water Cycle Algorithm Metaheuristic Nature Inspired based on water Cycle
- 6. Mathematical Formulation of WCA Step 1: Choose the initial parameters of the WCA: Npop, Nsr, dmax, max_iteration. Step 2: Generate random initial population and form the initial streams (raindrops), rivers, and sea using the Equation • Raindrop=[x1; x2; x3; . . . ; xN] • Nsr: • Nraindrop=Npop- Nsr Step 3: Calculate the value (cost) of each raindrops using Equation Step 4: Determine the intensity of flow for rivers and sea using
- 7. Step 5: The streams flow to the rivers by Equation Step 6: The rivers flow to the sea which is the most downhill place using Equation Step 7: Exchange positions of river with a stream which gives the best solution as shown in figure Step 8: Similar to Step 7, if a river finds better solution than the sea, the position of river is exchanged with the sea Schematic view of stream’s flow to a specific river
- 8. EVAPORATION: Step 9: Check the evaporation condition using the Psuocode Evaporation and raining process end Step 10: If the evaporation condition is satisfied, the raining process will occur using Eqs. (11) and (12). Step 11: Reduce the value of dmax which is user defined parameter using Equation Step 12: Check the convergence criteria. If the stopping criterion is satisfied, the algorithm will be stopped, otherwise return to Step 5
- 9. Schematic view of WCA
- 10. Strength of WCA in Contrast to Other Metaheuristic • Rivers as “Guidance point” • Resemblance to Mutation as in GA Comparison of statistical results for various algorithms for constrained problem Comparison of the best solution given by previous studies for constrained problem