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University of Florida - AOE - 4643
time ainfallobserved hyetograph rateinfiltration interception subsurface storage surface storage overland flow channel flow subsurface flowstream flow rate direct runoff baseflow timeAOM 4643Rainfall-Discharge Relationships AOM 4643 - Surface Waters La
University of Florida - AOE - 4643
AOM 4643Principles and Issues in Environmental HydrologyDefinitionsaHydrologic Science Focuses on the global hydrologic cycle and the processes involved in the land phase of that cycle. Predicts spatial and temporal distribution of water in the terre
University of Florida - AOE - 4643
AOM 4643Principles and Issues in Environmental HydrologyDefinitions Hydrologic Science Focuses on the global hydrologic cycle and the processes involved in the land phase of that cycle. Predicts spatial and temporal distribution of water in the terres
University of Florida - AOE - 4643
Public SupplyAmount WithdrawnMillions of Gallons per Day.12-9.69 11.39-39.50 59.56-123.81 184.39 306.46Rural UseAmount Withdrawn Million Gallons per Day0.00-1.84 2.15-3.97 4.15-7.35 7.71-11.82 13.13-21.65Industrial UseAmount Fresh Water Withdrawn
University of Florida - AOE - 4643
Basic Hydrological ConceptsAOM 4643 Principles and Issues in Environmental HydrologyStructure and Properties of Water Water is a held together by a covalent bond one side has a negative charge and the other a positive charge. The positive end of one H2
University of Florida - AOE - 4643
Earth's Energy Balance The hydrologic cycle is fueled by energy from the sun. Planetary geometry creates areas of energy surpluses and deficits which drive all active meteorological processes. Earth and the atmosphere are the media through which the ener
University of Florida - AOE - 4643
Composition/Characterstics of the Atmosphere 80% Nitrogen, 20% Oxygen- treated as a perfect gas Lower atmosphere extends up to 50 km. Lower atmosphere most active part of atmosphere where most of the mass and energy transfer (leading to earth's weather p
University of Florida - AOE - 4643
Formation of Precipitation Requires Cooling of air to dew point temperature (requires a lifting mechanism) Condensation of water vapor onto nuclei (dust, ions) to form droplets Growth of droplets so that a) terminal velocity > updraft velocity b) suffic
University of Florida - AOE - 4643
Estimation of Areal Precipitation from point measurements Most often interested in quantifying rainfall over an entire watershed. Has to be inferred from some sort of weighted average of available point measurements P(xi)P = i P ( xi )i =1 N Several m
University of Florida - AOE - 4643
Evaporation and Transpiration Evaporation- change of water from liquid to vapor phase Potential Evaporation - climatically controlled evaporation from a surface when the supply water to the surface is unlimited Transpiration - evaporation occurring from
University of Florida - AOE - 4643
Subsurface Water unit volume of subsurface consists of soil/rock, and pores which may be filled with water and/or air total porosity= volume voids/total volume water content=volume water/total volume saturation=volume water/volume voids degree of saturat
University of Florida - CWR - 6536
Goal of Stochastic Hydrology Develop analytical tools to systematically deal with uncertainty and spatial variability in hydrologic systems Examples of variable driving parameters and processes include rainfall rates, soil properties, aquifer properties
University of Florida - CWR - 6536
Review of Probability TheoryCWR 6536 Stochastic Subsurface HydrololgyRandom Variable (r.v.) A variable (x) which takes on values at random, and may be thought of as a function of the outcomes of some random experiment. The r.v. maps sample space of exp
University of Florida - CWR - 6536
Review of Random Process TheoryCWR 6536 Stochastic Subsurface HydrologyRandom Process A random process may be thought of as a collection or ensemble of random variables which change through time, any realization of which might be observed on any trial
University of Florida - CWR - 6536
Estimation of ensemble pdfs, cdfs, and moments from limited sampling of random fieldsStochastic Subsurface Hydrology CWR 6536Estimation of ensemble moments from field data Assume that random field is constructed of the following components: If only one
University of Florida - CWR - 6536
Properties of Covariance and Variogram FunctionsCWR 6536 Stochastic Subsurface HydrologyThe Covariance Function The covariance function must be positive definite which requires that: positive definiteness guarantees that all linear combinations of the
University of Florida - CWR - 6536
CWR 6536 Stochastic Subsurface Hydrology Optimal Estimation of Hydrologic Parameters using KrigingPurpose of KrigingTo estimate regional distribution of a spatially variable parameter To estimate accuracy of regional distribution Need scattered point me
University of Florida - CWR - 6536
CWR 6536 Stochastic Subsurface Hydrology Optimal Estimation of Hydrologic Parameters using KrigingPurpose of KrigingTo estimate regional distribution of a spatially variable parameter To estimate accuracy of regional distribution Need scattered point me
University of Florida - CWR - 6536
CWR 6536 Stochastic Subsurface Hydrology Optimal Estimation of Hydrologic Parameters using KrigingTypes of KrigingSimple kriging is optimal estimation of a random field, e.g. T(x), with a known mean, m(x), and a known covariance PTT(x,x'). Ordinary krig
University of Florida - CWR - 6536
CWR 6536 Stochastic Subsurface Hydrology Optimal Estimation of Hydrologic ParametersBlock KrigingKriging systems discussed to date use point measurements to estimate point values of the random field at unmeasured locations. called point, or punctual, kr
University of Florida - CWR - 6536
Stochastic ModelingCWR 6536 Stochastic Subsurface HydrologySource of uncertainty in model predictions include Input parameters boundary conditions initial conditions model error measurement errorStochastic Models Characterize pdfs/moments of input pa
University of Florida - CWR - 6536
Monte Carlo SimulationCWR 6536 Stochastic Subsurface HydrologySteps in Monte Carlo Simulation Create input sample space with known distribution, e.g. ensemble of all possible combinations of v, D, , m values Run each realization of v, D, , m values thr
University of Florida - CWR - 6536
Stochastic Modeling Approximate Analytical SolutionsCWR 6536 Stochastic Subsurface HydrologyStochastic model predictions can be obtained in several ways: Exact analytical solutions Monte Carlo techniques Approximate analytical solutions Approximate num
University of Florida - CWR - 6536
Stochastic Analysis of Groundwater Flow ProcessesCWR 6536 Stochastic Subsurface HydrologyMethods for deriving moments for groundwater flow processes Exact analytic solutions possible only if analytical solution to governing equation available. Not very
University of Florida - CWR - 6536
Approximate Analytical/Numerical Solutions to the Groundwater Flow ProblemCWR 6536 Stochastic Subsurface Hydrology3-D Saturated Groundwater Flow K K K 0= + + x x y y z z K(x,y,z) random hydraulic conductivity field (x,y,z) random hydraulic head fiel
University of Florida - CWR - 6536
Approximate Analytical Solutions to the Groundwater Flow ProblemCWR 6536 Stochastic Subsurface Hydrology3-D Steady Saturated Groundwater Flow K K K 0= + + x x y y z z K(x,y,z) random hydraulic conductivity field (x,y,z) random hydraulic head field wa
University of Florida - CWR - 6536
Approximate Analytical Solutions to the Groundwater Flow ProblemCWR 6536 Stochastic Subsurface HydrologySystem of Approximate Moment Eqns to order 20 = 20 ( x) + F ( x) 0 ( x) 0 = x '2 Pf1 ( x, x' ) + x ' F ( x' ) x ' Pf1 ( x, x' ) + x ' Pff ( x, x' )
University of Florida - CWR - 6536
Stochastic Analysis of Subsurface TransportCWR 6536 Stochastic Subsurface HydrologySubsurface Solute Transportc c c + vi = Dij t xi xi xj Assumes constant porosity, non-decaying, nonsorbing, dilute solute Dij molecular diffusion and hydrodynamic disp
University of Florida - EEL - 4744
EEL 4744C Dr. Gugel Last Name_ First Name _ Fall 2011 Exam #2 UFID#_ Open book/open notes, 90-minute exam. No electronic devices are required or permitted. All work and solutions are to be written on the exam where appropriate.Point System (for instructo
University of Florida - EEL - 4744
University of FloridaDepartment of Electrical & Computer Engineering Page 1/15EEL 4744-Spring 2011 31 March 2011Dr. Eric M. Schwartz15-Apr-11 1:29 PMExam 2Last Name, ,First NameInstructions: Turn off cell phones, beepers and other noise making de
University of Florida - EEL - 4744
27-Mar-12-1:22 PMExam 2 InfoEEL 4744EEL4744 Second Exam 120 minutes Questions require understanding Questions deal with "real stuff" Relevant topics include: Anything from Exam 1 possible Labs 1-6; HW 1-4 Class notes through lecture 15 Keypad, LCD Pa
University of Florida - EEL - 4744
University of FloridaElectrical & Computer EngineeringEEL 4744Dr. Eric M Schwartz1-Mar-12Page 1/1Homework 4Revision 0Instructions Note: Late HW is not accepted! HW is due at the beginning of class. Put your "last name, first name" and the HW numbe
University of Florida - EEL - 4744
University of Florida Electrical & Computer Engineering Dept. Page 1/5EEL 4744 Spring 2012Revision 2Dr. Eric M. Schwartz Brandon Cerge & Eric Jeffers, TAs16-Mar-122Lab 5: Interrupts, Serial Communication, External MemoryOBJECTIVESIn this lab you wi
University of Florida - EEL - 4744
University of Florida Electrical and Computer Engineering Dept. Page 1/4EEL 4744 Spring 2012Revision 3Dr. Eric M. Schwartz Michael Carroll, TA 27 March 2012Lab 6: LCD and A/D: Digital VoltmeterOBJECTIVESIn this lab you will learn how to control an L
University of Florida - EEL - 4744
Crystalfontz America, IncorporatedCHARACTER LCD MODULE SPECIFICATIONSCrystalfontz Model Number Hardware Version Data Sheet Version Product PagesCFAH1602Z-YYH-ET Revision A Revision 1.0, November 2008 www.crystalfontz.com/product/CFAH1602Z-YYH-ET.htmlC
University of Florida - EEL - 4930
Introduction to Reconfigurable Computing1Reconfigurable Logic: Best of Both WorldsReconfigurable LogicMicroprocessor Advantages ASIC Disadvantages High flexibility Low development cost and fast time-to-market Low part cost May not meet design cons
University of Florida - EEL - 4930
Generic RC ArchitectureHost CPU sLocal Interconnect(s)MemNode ArchitectureNIC Node InterconnectRC DevicesCoupling in Reconfigurable SystemsEx: xtremeDataEx: Nallatech, GiDELDifferent levels of coupling in a reconfigurable system. (Reconfigurable
University of Florida - EEL - 4930
Reconfigurable Supercomputing with Scalable Systolic Arrays and InStream Control for Wavefront Genomics ProcessingSAAHPC'10C. Pascoe (speaker), A. Lawande H. Lam, A. GeorgeNSF Center for High-Performance Reconfigurable Computing (CHREC), University of
University of Florida - EEL - 4930
INTRODUCTIONImage processing is one of the main applications to tap the maximum parallelism out of FPGA as compared to a microprocessor. Thus in order to test the speedup that can be achieved out of an FPGA as compared to microprocessor, we plan to imple
University of Florida - EEL - 4930
ASMexample.vhdLIBRARY ieee ; USE ieee.std_logic_1164.all ; ENTITY ASMexample IS PORT ( Clock, Resetn, InBit, BufFull state CountEN, RegLD, OutFlag END ASMexample ; : IN STD_LOGIC ; : BUFFER STD_LOGIC_VECTOR (1 DOWNTO 0); : OUT STD_LOGIC ) ;ARCHITECTURE
University of Florida - EEL - 4930
Reconfigurable Computing: A Survey of Systems and SoftwareKATHERINE COMPTONNorthwestern UniversityAND SCOTT HAUCKUniversity of WashingtonDue to its potential to greatly accelerate a wide variety of applications, reconfigurable computing has become a
University of Florida - EEL - 4930
DIMEtalk 3.1 Reference GuideNT108-0305 - Issue 7Contacting Nallatech: Support: WWW: Go to www.nallatech.com and click `support'. Email: support@nallatech.com Phone/Fax Europe and Asia-Pacific: Phone: +44 (0)1236 789500 WWW: www.nallatech.com North Ameri
University of Florida - EEL - 4930
DIMEtalk 3.1 User GuideNT107-0305 - Issue 3Contacting Nallatech: Support: WWW: Go to www.nallatech.com and click `support'. Email: support@nallatech.com Phone/Fax Europe and Asia-Pacific: Phone: +44 (0)1236 789500 WWW: www.nallatech.com North America Ph
University of Florida - EEL - 4930
University of Florida - EEL - 4930
Lab 2(a): VHDL Finite State Machine and DatapathEEL 4930/5934 Spring 2012 Objective:The objective of Lab 2(a) is to design and simulate a circuit in VHDL that calculates Fibonacci numbers.Fibonacci Calculator Introduction:For this part of the lab, you
University of Florida - EEL - 4930
Lab 2(b): Introduction to DIMEtalk and Nallatech PlatformEEL 4930/5934 Spring 2012 Objective: In this part of Lab 2, you will be learning the basics of the Nallatech board and the DIMETalk design environment.2(b) Part 1 - Installation/Tutorial1. Follow
University of Florida - EEL - 4930
Lab 3: Fibonacci Calculator using Nallatech PlatformEEL 4930/5934 Spring 2012Objectives: In this lab, you will be implementing a Fibonacci calculator (similar to the one you did in a previous lab) on the Nallatech board and interface it with a software
University of Florida - EEL - 4930
Lab 4: Simple Pipelined DatapathEEL 4930/5934 Spring 2012Introduction:In this lab, you will be implementing a circuit with a pipelined datapath. The circuit will utilize one blockRAM (BRAM) to continually feed four 8-bit inputs into the datapath every
University of Florida - EEL - 4930
Lab 5: Clock Domain CrossingEEL 4930/5934 Spring 2012Introduction:In this lab, you will learn how to properly communicate across clock domains. If not handled correctly, signals that cross clock domains can become metastable, which if propagated throug
University of Florida - EEL - 4930
EEL 4930/5934 Reconfigurable Computing Midterm Exam Spring Semester 201018 pts.Name _1. Systolic Architecture (a) Given the following algorithm in pseudo-code, draw a datapath that is fully-pipelined and with the maximum loop-unrolling. for (i=1; i < 1
University of Florida - EEL - 4930
University of Florida - EEL - 4930
EEL 4930/5934 Reconfigurable Computing Midterm Exam Spring Semester 2011 1. Scalable Systolic Array paper The figure on the right is reproduced 14 pts. from the Scalable Systolic Array paper. It shows a scoring matrix for the Needleman-Wunsch algorithm in
University of Florida - EEL - 4930
University of Florida - EEL - 4930
University of Florida - EEL - 4930
Numerical Representation and AnalysisFor RC App DesignsNumerical RepresentationsOrder of preference1.Integer Fixedpoint FP Floatingpoint (singleprecision) FP Floatingpoint (doubleprecision)2.3.4.Integer representationAdvantages: o.Very efficie
University of Florida - EEL - 4930
EEL 4930/5935: Reconfigurable Computing Term ProjectProject team: 2 students per team; exceptions must be approved by me Due dates: Project proposal: Thursday 3/15/2012 on eLearning Project progress review: Week of 4/2 4/6; PowerPoint presentation on the
University of Florida - EEL - 4930
Project requirements and grading PowerPoint presentation and Demonstration (30 mins) Report for each team (up to 10 pages plus appendices, references, etc.) Grading: 25% of final course grade I expect each member of the group to contribute equally to th
University of Florida - EEL - 4930
Project Grading Project title:Team members:Grading factors: Complexity of the projectDesign: Amount of wide parallelism? Amount of pipeline parallelism? Elegant? Innovative?Demonstration, does it work? Simulation?On delta?Speedup Computation only Da
University of Florida - EEL - 4930
Reconfigurable Supercomputing with Scalable Systolic Arrays and In-Stream Control for Wavefront Genomics ProcessingC. Pascoe, A. Lawande, H. Lam, A. GeorgeNSF Center for High-Performance Reconfigurable Computing (CHREC) University of FloridaY. Sun, W.