Demonstration and Study of the Dispersion of Water Waves with A
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Glossary Physics (I-Introduction)
1 Glossary Physics (I-introduction) - Efficiency: The percent of the work put into a machine that is converted into useful work output; = work done / energy used [-]. = eta In machines: The work output of any machine cannot exceed the work input (<=100%); in an ideal machine, where no energy is transformed into heat: work(input) = work(output), =100%. Energy: The property of a system that enables it to do work. Conservation o. E.: Energy cannot be created or destroyed; it may be transformed from one form into another, but the total amount of energy never changes. Equilibrium: The state of an object when not acted upon by a net force or net torque; an object in equilibrium may be at rest or moving at uniform velocity - not accelerating. Mechanical E.: The state of an object or system of objects for which any impressed forces cancels to zero and no acceleration occurs. Dynamic E.: Object is moving without experiencing acceleration. Static E.: Object is at rest.F Force: The influence that can cause an object to be accelerated or retarded; is always in the direction of the net force, hence a vector quantity; the four elementary forces are: Electromagnetic F.: Is an attraction or repulsion G, gravit. const.6.672E-11[Nm2/kg2] between electric charges: d, distance [m] 2 2 2 2 F = 1/(40) (q1q2/d ) [(CC/m )(Nm /C )] = [N] m,M, mass [kg] Gravitational F.: Is a mutual attraction between all masses: q, charge [As] [C] 2 2 2 2 F = GmM/d [Nm /kg kg 1/m ] = [N] 0, dielectric constant Strong F.: (nuclear force) Acts within the nuclei of atoms: 8.854E-12 [C2/Nm2] [F/m] 2 2 2 2 2 F = 1/(40) (e /d ) [(CC/m )(Nm /C )] = [N] , 3.14 [-] Weak F.: Manifests itself in special reactions among elementary e, 1.60210 E-19 [As] [C] particles, such as the reaction that occur in radioactive decay. -
Dispersion of Tsunamis: Does It Really Matter? and Physics and Physics Discussions Open Access Open Access S
EGU Journal Logos (RGB) Open Access Open Access Open Access Advances in Annales Nonlinear Processes Geosciences Geophysicae in Geophysics Open Access Open Access Nat. Hazards Earth Syst. Sci., 13, 1507–1526, 2013 Natural Hazards Natural Hazards www.nat-hazards-earth-syst-sci.net/13/1507/2013/ doi:10.5194/nhess-13-1507-2013 and Earth System and Earth System © Author(s) 2013. CC Attribution 3.0 License. Sciences Sciences Discussions Open Access Open Access Atmospheric Atmospheric Chemistry Chemistry Dispersion of tsunamis: does it really matter? and Physics and Physics Discussions Open Access Open Access S. Glimsdal1,2,3, G. K. Pedersen1,3, C. B. Harbitz1,2,3, and F. Løvholt1,2,3 Atmospheric Atmospheric 1International Centre for Geohazards (ICG), Sognsveien 72, Oslo, Norway Measurement Measurement 2Norwegian Geotechnical Institute, Sognsveien 72, Oslo, Norway 3University of Oslo, Blindern, Oslo, Norway Techniques Techniques Discussions Open Access Correspondence to: S. Glimsdal ([email protected]) Open Access Received: 30 November 2012 – Published in Nat. Hazards Earth Syst. Sci. Discuss.: – Biogeosciences Biogeosciences Revised: 5 April 2013 – Accepted: 24 April 2013 – Published: 18 June 2013 Discussions Open Access Abstract. This article focuses on the effect of dispersion in 1 Introduction Open Access the field of tsunami modeling. Frequency dispersion in the Climate linear long-wave limit is first briefly discussed from a the- Climate Most tsunami modelers rely on the shallow-water equations oretical point of view. A single parameter, denoted as “dis- of the Past for predictions of propagationof and the run-up. Past Some groups, on persion time”, for the integrated effect of frequency dis- Discussions the other hand, insist on applying dispersive wave models, persion is identified. -
Type-I Hyperbolic Metasurfaces for Highly-Squeezed Designer
Type-I hyperbolic metasurfaces for highly-squeezed designer polaritons with negative group velocity Yihao Yang1,2,3,4, Pengfei Qin2, Xiao Lin3, Erping Li2, Zuojia Wang5,*, Baile Zhang3,4,*, and Hongsheng Chen1,2,* 1State Key Laboratory of Modern Optical Instrumentation, College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China. 2Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang, The Electromagnetics Academy at Zhejiang University, Zhejiang University, Hangzhou 310027, China. 3Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore. 4Centre for Disruptive Photonic Technologies, The Photonics Institute, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore. 5School of Information Science and Engineering, Shandong University, Qingdao 266237, China *[email protected] (Z.W.); [email protected] (B.Z.); [email protected] (H.C.) Abstract Hyperbolic polaritons in van der Waals materials and metamaterial heterostructures provide unprecedenced control over light-matter interaction at the extreme nanoscale. Here, we propose a concept of type-I hyperbolic metasurface supporting highly-squeezed magnetic designer polaritons, which act as magnetic analogues to hyperbolic polaritons in the hexagonal boron nitride (h-BN) in the first Reststrahlen band. Comparing with the natural h-BN, the size and spacing of the metasurface unit cell can be readily scaled up (or down), allowing for manipulating designer polaritons in frequency and in space at will. Experimental measurements display the cone-like hyperbolic dispersion in the momentum space, associating with an effective refractive index up to 60 and a group velocity down to 1/400 of the light speed in vacuum. -
Analysis of Flow Structures in Wake Flows for Train Aerodynamics Tomas W. Muld
Analysis of Flow Structures in Wake Flows for Train Aerodynamics by Tomas W. Muld May 2010 Technical Reports Royal Institute of Technology Department of Mechanics SE-100 44 Stockholm, Sweden Akademisk avhandling som med tillst˚and av Kungliga Tekniska H¨ogskolan i Stockholm framl¨agges till offentlig granskning f¨or avl¨aggande av teknologie licentiatsexamen fredagen den 28 maj 2010 kl 13.15 i sal MWL74, Kungliga Tekniska H¨ogskolan, Teknikringen 8, Stockholm. c Tomas W. Muld 2010 Universitetsservice US–AB, Stockholm 2010 Till Mamma ♥ iii iv The Only Easy Day Was Yesterday Motto of the United States Navy SEALs Aerodynamics are for people who can’t build engines Enzo Ferrari v Analysis of Flow Structures in Wake Flows for Train Aero- dynamics Tomas W. Muld Linn´eFlow Centre, KTH Mechanics, Royal Institute of Technology SE-100 44 Stockholm, Sweden Abstract Train transportation is a vital part of the transportation system of today and due to its safe and environmental friendly concept it will be even more impor- tant in the future. The speeds of trains have increased continuously and with higher speeds the aerodynamic effects become even more important. One aero- dynamic effect that is of vital importance for passengers’ and track workers’ safety is slipstream, i.e. the flow that is dragged by the train. Earlier ex- perimental studies have found that for high-speed passenger trains the largest slipstream velocities occur in the wake. Therefore the work in this thesis is devoted to wake flows. First a test case, a surface-mounted cube, is simulated to test the analysis methodology that is later applied to a train geometry, the Aerodynamic Train Model (ATM). -
Mechanical Dispersion of Clay from Soil Into Water: Readily-Dispersed and Spontaneously-Dispersed Clay Ewa A
Int. Agrophys., 2015, 29, 31-37 doi: 10.1515/intag-2015-0007 Mechanical dispersion of clay from soil into water: readily-dispersed and spontaneously-dispersed clay Ewa A. Czyż1,2* and Anthony R. Dexter2 1Department of Soil Science, Environmental Chemistry and Hydrology, University of Rzeszów, Zelwerowicza 8b, 35-601 Rzeszów, Poland 2Institute of Soil Science and Plant Cultivation (IUNG-PIB), Czartoryskich 8, 24-100 Puławy, Poland Received July 1, 2014; accepted October 10, 2014 A b s t r a c t. A method for the experimental determination of Clay particles can either flocculate or disperse in aque- the amount of clay dispersed from soil into water is described. The ous solution. When flocculation occurs, the particles com- method was evaluated using soil samples from agricultural fields bine to form larger, compound particles such as soil in 18 locations in Poland. Soil particle size distributions, contents microaggregates. When dispersion occurs, the particles of organic matter and exchangeable cations were measured by separate in suspension due to their electrical charge. Clay standard methods. Sub-samples were placed in distilled water flocculation leads to soils that are considered to be stable in wa- and were subjected to four different energy inputs obtained by ter whereas dispersion is associated with soils that are consi- different numbers of inversions (end-over-end movements). The dered to be unstable in water. We may note that this termi- amounts of clay that dispersed into suspension were measured by light scattering (turbidimetry). An empirical equation was devel- nology is the opposite of that used in colloid science where oped that provided an approximate fit to the experimental data for the terms ‘stable’ and ‘unstable’ are used in relation to the turbidity as a function of number of inversions. -
Waves and Weather
Waves and Weather 1. Where do waves come from? 2. What storms produce good surfing waves? 3. Where do these storms frequently form? 4. Where are the good areas for receiving swells? Where do waves come from? ==> Wind! Any two fluids (with different density) moving at different speeds can produce waves. In our case, air is one fluid and the water is the other. • Start with perfectly glassy conditions (no waves) and no wind. • As wind starts, will first get very small capillary waves (ripples). • Once ripples form, now wind can push against the surface and waves can grow faster. Within Wave Source Region: - all wavelengths and heights mixed together - looks like washing machine ("Victory at Sea") But this is what we want our surfing waves to look like: How do we get from this To this ???? DISPERSION !! In deep water, wave speed (celerity) c= gT/2π Long period waves travel faster. Short period waves travel slower Waves begin to separate as they move away from generation area ===> This is Dispersion How Big Will the Waves Get? Height and Period of waves depends primarily on: - Wind speed - Duration (how long the wind blows over the waves) - Fetch (distance that wind blows over the waves) "SMB" Tables How Big Will the Waves Get? Assume Duration = 24 hours Fetch Length = 500 miles Significant Significant Wind Speed Wave Height Wave Period 10 mph 2 ft 3.5 sec 20 mph 6 ft 5.5 sec 30 mph 12 ft 7.5 sec 40 mph 19 ft 10.0 sec 50 mph 27 ft 11.5 sec 60 mph 35 ft 13.0 sec Wave height will decay as waves move away from source region!!! Map of Mean Wind -
Colloidal Suspensions
Chapter 9 Colloidal suspensions 9.1 Introduction So far we have discussed the motion of one single Brownian particle in a surrounding fluid and eventually in an extaernal potential. There are many practical applications of colloidal suspensions where several interacting Brownian particles are dissolved in a fluid. Colloid science has a long history startying with the observations by Robert Brown in 1828. The colloidal state was identified by Thomas Graham in 1861. In the first decade of last century studies of colloids played a central role in the development of statistical physics. The experiments of Perrin 1910, combined with Einstein's theory of Brownian motion from 1905, not only provided a determination of Avogadro's number but also laid to rest remaining doubts about the molecular composition of matter. An important event in the development of a quantitative description of colloidal systems was the derivation of effective pair potentials of charged colloidal particles. Much subsequent work, largely in the domain of chemistry, dealt with the stability of charged colloids and their aggregation under the influence of van der Waals attractions when the Coulombic repulsion is screened strongly by the addition of electrolyte. Synthetic colloidal spheres were first made in the 1940's. In the last twenty years the availability of several such reasonably well characterised "model" colloidal systems has attracted physicists to the field once more. The study, both theoretical and experimental, of the structure and dynamics of colloidal suspensions is now a vigorous and growing subject which spans chemistry, chemical engineering and physics. A colloidal dispersion is a heterogeneous system in which particles of solid or droplets of liquid are dispersed in a liquid medium. -
A Review of Wind Turbine Wake Models and Future Directions
A Review of Wind Turbine Wake Models and Future Directions 2013 North American Wind Energy Academy (NAWEA) Symposium Matthew J. Churchfield Boulder, Colorado August 6, 2013 NREL/PR-5200-60208 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. Why Are Wind Turbine Wakes Important? Wind speed (m/s) • Wake effects impact: o Power production o Mechanical loads • High importance in wind- plant-level control strategies • Having a good wake model is a necessity in predicting plant performance and understanding fatigue Contours of instantaneous wind speed in simulated flow through loads the Lillgrund wind plant 2 What Does a Wake Look Like? Flow field generated from large-eddy simulation (velocity field minus mean shear) top view Characteristics: • Velocity deficit • Low-frequency meandering • Intermittent edge • Shear-layer-generated turbulence view from downstream Notice how many of the characteristics describe some sort of unsteadiness 3 Differing Needs in Wake Modeling • Power Prediction and Annual Energy Production (AEP) o Steady, time-averaged • Loads o Unsteady, time-accurate • Control Strategies o Steady and unsteady may both be needed • Basic Physics o As much fidelity as possible 4 Hierarchy of Wake Models Type Example Empirical -Jensen (1983)/Katíc (1986) (Park) Linearized -Ainslie (1985) (Eddy-viscosity) i Reynolds-averaged -Ott et al. (2011) (Fuga) ncreasing cost/fidelity Navier-Stokes (RANS) Other -Larsen et al. (2007) -
The Kelvin Wedge
The shape of ship wakes: The Kelvin wedge 1 1 o 2sin 3 38.9 Dr Andrew French. August 2013 1 Contents • Ship wakes and the Kelvin wedge • Theory of surface waves – Frequency – Wavenumber – Dispersion relationship – Phase and group velocity – Shallow and deep water waves – Minimum velocity of deep water ripples • Mathematical derivation of Kelvin wedge – Surf-riding condition – Stationary phase – Rabaud and Moisy’s model – Froude number • Minimum ship speed needed to generate a Kelvin wedge • Kelvin wedge via a geometrical method? – Mach’s construction • Further reading 2 A wake is an interference pattern of waves formed by the motion of a body through a fluid. Intriguingly, the angular width of the wake produced by ships (and ducks!) in deep water is the same (about 38.9o). A mathematical explanation for this phenomenon was first proposed by Lord Kelvin (1824-1907). The triangular envelope of the wake pattern has since been known as the Kelvin wedge. http://en.wikipedia.org/wiki/Wake 3 Venetian water-craft and their associated Kelvin wedges Images from Google Maps (above) and Google Earth (right), (August 2013) 4 Still awake? 5 The Kelvin Wedge is clearly not the whole story, it merely describes the envelope of the wake. Other distinct features are highlighted below: Turbulent Within the Kelvin wedge we flow from bow see waves inclined at a wave and slightly wider angle propeller from the direction of travel of wash. * These the ship. (It turns effects will be out this is about 55o) * addressed in this presentation. The others Waves disperse within a ‘few will not! degrees’ of the Kelvin wedge. -
Group Velocity
Particle Waves and Group Velocity Particles with known energy Consider a particle with mass m, traveling in the +x direction and known velocity 1 vo and energy Eo = mvo . The wavefunction that represents this particle is: 2 !(x,t) = Ce jkxe" j#t [1] where C is a constant and 2! 1 ko = = 2mEo [2] "o ! Eo !o = 2"#o = [3] ! 2 The envelope !(x,t) of this wavefunction is 2 2 !(x,t) = C , which is a constant. This means that when a particle’s energy is known exactly, it’s position is completely unknown. This is consistent with the Heisenberg Uncertainty principle. Even though the magnitude of this wave function is a constant with respect to both position and time, its phase is not. As with any type of wavefunction, the phase velocity vp of this wavefunction is: ! E / ! v v = = o = E / 2m = v2 / 4 = o [4] p k 1 o o 2 2mEo ! At first glance, this result seems wrong, since we started with the assumption that the particle is moving at velocity vo. However, only the magnitude of a wavefunction contains measurable information, so there is no reason to believe that its phase velocity is the same as the particle’s velocity. Particles with uncertain energy A more realistic situation is when there is at least some uncertainly about the particle’s energy and momentum. For real situations, a particle’s energy will be known to lie only within some band of uncertainly. This can be handled by assuming that the particle’s wavefunction is the superposition of a range of constant-energy wavefunctions: jkn x # j$nt !(x,t) = "Cn (e e ) [5] n Here, each value of kn and ωn correspond to energy En, and Cn is the probability that the particle has energy En. -
Photons That Travel in Free Space Slower Than the Speed of Light Authors
Title: Photons that travel in free space slower than the speed of light Authors: Daniel Giovannini1†, Jacquiline Romero1†, Václav Potoček1, Gergely Ferenczi1, Fiona Speirits1, Stephen M. Barnett1, Daniele Faccio2, Miles J. Padgett1* Affiliations: 1 School of Physics and Astronomy, SUPA, University of Glasgow, Glasgow G12 8QQ, UK 2 School of Engineering and Physical Sciences, SUPA, Heriot-Watt University, Edinburgh EH14 4AS, UK † These authors contributed equally to this work. * Correspondence to: [email protected] Abstract: That the speed of light in free space is constant is a cornerstone of modern physics. However, light beams have finite transverse size, which leads to a modification of their wavevectors resulting in a change to their phase and group velocities. We study the group velocity of single photons by measuring a change in their arrival time that results from changing the beam’s transverse spatial structure. Using time-correlated photon pairs we show a reduction of the group velocity of photons in both a Bessel beam and photons in a focused Gaussian beam. In both cases, the delay is several microns over a propagation distance of the order of 1 m. Our work highlights that, even in free space, the invariance of the speed of light only applies to plane waves. Introducing spatial structure to an optical beam, even for a single photon, reduces the group velocity of the light by a readily measurable amount. One sentence summary: The group velocity of light in free space is reduced by controlling the transverse spatial structure of the light beam. Main text The speed of light is trivially given as �/�, where � is the speed of light in free space and � is the refractive index of the medium. -
Basin Scale Tsunami Propagation Modeling Using Boussinesq Models: Parallel Implementation in Spherical Coordinates
WCCE – ECCE – TCCE Joint Conference: EARTHQUAKE & TSUNAMI BASIN SCALE TSUNAMI PROPAGATION MODELING USING BOUSSINESQ MODELS: PARALLEL IMPLEMENTATION IN SPHERICAL COORDINATES J. T. Kirby1, N. Pophet2, F. Shi1, S. T. Grilli3 ABSTRACT We derive weakly nonlinear, weakly dispersive model equations for propagation of surface gravity waves in a shallow, homogeneous ocean of variable depth on the surface of a rotating sphere. A numerical scheme is developed based on the staggered-grid finite difference formulation of Shi et al (2001). The model is implemented using the domain decomposition technique in conjunction with the message passing interface (MPI). The efficiency tests show a nearly linear speedup on a Linux cluster. Relative importance of frequency dispersion and Coriolis force is evaluated in both the scaling analysis and the numerical simulation of an idealized case on a sphere. 1 INTRODUCTION The conventional models in the global-scale tsunami modeling are based on the shallow water equations and neglect frequency dispersion effects in wave propagation. Recent studies on tsunami modeling revealed that such tsunami models may not be satisfactory in predicting tsunamis caused by nonseismic sources (Løvholt et al., 2008). For seismic tsunamis, the frequency dispersion effects in the long distance propagation of tsunami fronts may become significant. The numerical simulations of the 2004 Indian Ocean tsunami by Glimsdal et al. (2006) and Grue et al. (2008) indicated the undular bores may evolve in shallow water, as the phenomenon evidenced in observations (Shuto, 1985). In the simulation for the same tsunami by Grilli et al. (2007), the dispersive effects were quantified by running the dispersive Boussinesq model FUNWAVE (Kirby et al., 1998) and the NSWE solver.