A Practical, Basic Guide to Quasi-Geostrophic Theory
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10-1 CHAPTER 10 DEFORMATION 10.1 Stress-Strain Diagrams And
EN380 Naval Materials Science and Engineering Course Notes, U.S. Naval Academy CHAPTER 10 DEFORMATION 10.1 Stress-Strain Diagrams and Material Behavior 10.2 Material Characteristics 10.3 Elastic-Plastic Response of Metals 10.4 True stress and strain measures 10.5 Yielding of a Ductile Metal under a General Stress State - Mises Yield Condition. 10.6 Maximum shear stress condition 10.7 Creep Consider the bar in figure 1 subjected to a simple tension loading F. Figure 1: Bar in Tension Engineering Stress () is the quotient of load (F) and area (A). The units of stress are normally pounds per square inch (psi). = F A where: is the stress (psi) F is the force that is loading the object (lb) A is the cross sectional area of the object (in2) When stress is applied to a material, the material will deform. Elongation is defined as the difference between loaded and unloaded length ∆푙 = L - Lo where: ∆푙 is the elongation (ft) L is the loaded length of the cable (ft) Lo is the unloaded (original) length of the cable (ft) 10-1 EN380 Naval Materials Science and Engineering Course Notes, U.S. Naval Academy Strain is the concept used to compare the elongation of a material to its original, undeformed length. Strain () is the quotient of elongation (e) and original length (L0). Engineering Strain has no units but is often given the units of in/in or ft/ft. ∆푙 휀 = 퐿 where: is the strain in the cable (ft/ft) ∆푙 is the elongation (ft) Lo is the unloaded (original) length of the cable (ft) Example Find the strain in a 75 foot cable experiencing an elongation of one inch. -
Heat Advection Processes Leading to El Niño Events As
1 2 Title: 3 Heat advection processes leading to El Niño events as depicted by an ensemble of ocean 4 assimilation products 5 6 Authors: 7 Joan Ballester (1,2), Simona Bordoni (1), Desislava Petrova (2), Xavier Rodó (2,3) 8 9 Affiliations: 10 (1) California Institute of Technology (Caltech), Pasadena, California, United States 11 (2) Institut Català de Ciències del Clima (IC3), Barcelona, Catalonia, Spain 12 (3) Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain 13 14 Corresponding author: 15 Joan Ballester 16 California Institute of Technology (Caltech) 17 1200 E California Blvd, Pasadena, CA 91125, US 18 Mail Code: 131-24 19 Tel.: +1-626-395-8703 20 Email: [email protected] 21 22 Manuscript 23 Submitted to Journal of Climate 24 1 25 26 Abstract 27 28 The oscillatory nature of El Niño-Southern Oscillation results from an intricate 29 superposition of near-equilibrium balances and out-of-phase disequilibrium processes between the 30 ocean and the atmosphere. Several authors have shown that the heat content stored in the equatorial 31 subsurface is key to provide memory to the system. Here we use an ensemble of ocean assimilation 32 products to describe how heat advection is maintained in each dataset during the different stages of 33 the oscillation. 34 Our analyses show that vertical advection due to surface horizontal convergence and 35 downwelling motion is the only process contributing significantly to the initial subsurface warming 36 in the western equatorial Pacific. This initial warming is found to be advected to the central Pacific 37 by the equatorial undercurrent, which, together with the equatorward advection associated with 38 anomalies in both the meridional temperature gradient and circulation at the level of the 39 thermocline, explains the heat buildup in the central Pacific during the recharge phase. -
Impulse and Momentum
Impulse and Momentum All particles with mass experience the effects of impulse and momentum. Momentum and inertia are similar concepts that describe an objects motion, however inertia describes an objects resistance to change in its velocity, and momentum refers to the magnitude and direction of it's motion. Momentum is an important parameter to consider in many situations such as braking in a car or playing a game of billiards. An object can experience both linear momentum and angular momentum. The nature of linear momentum will be explored in this module. This section will discuss momentum and impulse and the interconnection between them. We will explore how energy lost in an impact is accounted for and the relationship of momentum to collisions between two bodies. This section aims to provide a better understanding of the fundamental concept of momentum. Understanding Momentum Any body that is in motion has momentum. A force acting on a body will change its momentum. The momentum of a particle is defined as the product of the mass multiplied by the velocity of the motion. Let the variable represent momentum. ... Eq. (1) The Principle of Momentum Recall Newton's second law of motion. ... Eq. (2) This can be rewritten with accelleration as the derivate of velocity with respect to time. ... Eq. (3) If this is integrated from time to ... Eq. (4) Moving the initial momentum to the other side of the equation yields ... Eq. (5) Here, the integral in the equation is the impulse of the system; it is the force acting on the mass over a period of time to . -
SMALL DEFORMATION RHEOLOGY for CHARACTERIZATION of ANHYDROUS MILK FAT/RAPESEED OIL SAMPLES STINE RØNHOLT1,3*, KELL MORTENSEN2 and JES C
bs_bs_banner A journal to advance the fundamental understanding of food texture and sensory perception Journal of Texture Studies ISSN 1745-4603 SMALL DEFORMATION RHEOLOGY FOR CHARACTERIZATION OF ANHYDROUS MILK FAT/RAPESEED OIL SAMPLES STINE RØNHOLT1,3*, KELL MORTENSEN2 and JES C. KNUDSEN1 1Department of Food Science, University of Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark 2Niels Bohr Institute, University of Copenhagen, Copenhagen Ø, Denmark KEYWORDS ABSTRACT Method optimization, milk fat, physical properties, rapeseed oil, rheology, structural Samples of anhydrous milk fat and rapeseed oil were characterized by small analysis, texture evaluation amplitude oscillatory shear rheology using nine different instrumental geometri- cal combinations to monitor elastic modulus (G′) and relative deformation 3 + Corresponding author. TEL: ( 45)-2398-3044; (strain) at fracture. First, G′ was continuously recorded during crystallization in a FAX: (+45)-3533-3190; EMAIL: fluted cup at 5C. Second, crystallization of the blends occurred for 24 h, at 5C, in [email protected] *Present Address: Department of Pharmacy, external containers. Samples were gently cut into disks or filled in the rheometer University of Copenhagen, Universitetsparken prior to analysis. Among the geometries tested, corrugated parallel plates with top 2, 2100 Copenhagen Ø, Denmark. and bottom temperature control are most suitable due to reproducibility and dependence on shear and strain. Similar levels for G′ were obtained for samples Received for Publication May 14, 2013 measured with parallel plate setup and identical samples crystallized in situ in the Accepted for Publication August 5, 2013 geometry. Samples measured with other geometries have G′ orders of magnitude lower than identical samples crystallized in situ. -
What Is Hooke's Law? 16 February 2015, by Matt Williams
What is Hooke's Law? 16 February 2015, by Matt Williams Like so many other devices invented over the centuries, a basic understanding of the mechanics is required before it can so widely used. In terms of springs, this means understanding the laws of elasticity, torsion and force that come into play – which together are known as Hooke's Law. Hooke's Law is a principle of physics that states that the that the force needed to extend or compress a spring by some distance is proportional to that distance. The law is named after 17th century British physicist Robert Hooke, who sought to demonstrate the relationship between the forces applied to a spring and its elasticity. He first stated the law in 1660 as a Latin anagram, and then published the solution in 1678 as ut tensio, sic vis – which translated, means "as the extension, so the force" or "the extension is proportional to the force"). This can be expressed mathematically as F= -kX, where F is the force applied to the spring (either in the form of strain or stress); X is the displacement A historical reconstruction of what Robert Hooke looked of the spring, with a negative value demonstrating like, painted in 2004 by Rita Greer. Credit: that the displacement of the spring once it is Wikipedia/Rita Greer/FAL stretched; and k is the spring constant and details just how stiff it is. Hooke's law is the first classical example of an The spring is a marvel of human engineering and explanation of elasticity – which is the property of creativity. -
Balanced Flow Natural Coordinates
Balanced Flow • The pressure and velocity distributions in atmospheric systems are related by relatively simple, approximate force balances. • We can gain a qualitative understanding by considering steady-state conditions, in which the fluid flow does not vary with time, and by assuming there are no vertical motions. • To explore these balanced flow conditions, it is useful to define a new coordinate system, known as natural coordinates. Natural Coordinates • Natural coordinates are defined by a set of mutually orthogonal unit vectors whose orientation depends on the direction of the flow. Unit vector tˆ points along the direction of the flow. ˆ k kˆ Unit vector nˆ is perpendicular to ˆ t the flow, with positive to the left. kˆ nˆ ˆ t nˆ Unit vector k ˆ points upward. ˆ ˆ t nˆ tˆ k nˆ ˆ r k kˆ Horizontal velocity: V = Vtˆ tˆ kˆ nˆ ˆ V is the horizontal speed, t nˆ ˆ which is a nonnegative tˆ tˆ k nˆ scalar defined by V ≡ ds dt , nˆ where s ( x , y , t ) is the curve followed by a fluid parcel moving in the horizontal plane. To determine acceleration following the fluid motion, r dV d = ()Vˆt dt dt r dV dV dˆt = ˆt +V dt dt dt δt δs δtˆ δψ = = = δtˆ t+δt R tˆ δψ δψ R radius of curvature (positive in = R δs positive n direction) t n R > 0 if air parcels turn toward left R < 0 if air parcels turn toward right ˆ dtˆ nˆ k kˆ = (taking limit as δs → 0) tˆ R < 0 ds R kˆ nˆ ˆ ˆ ˆ t nˆ dt dt ds nˆ ˆ ˆ = = V t nˆ tˆ k dt ds dt R R > 0 nˆ r dV dV dˆt = ˆt +V dt dt dt r 2 dV dV V vector form of acceleration following = ˆt + nˆ dt dt R fluid motion in natural coordinates r − fkˆ ×V = − fVnˆ Coriolis (always acts normal to flow) ⎛ˆ ∂Φ ∂Φ ⎞ − ∇ pΦ = −⎜t + nˆ ⎟ pressure gradient ⎝ ∂s ∂n ⎠ dV ∂Φ = − dt ∂s component equations of horizontal V 2 ∂Φ momentum equation (isobaric) in + fV = − natural coordinate system R ∂n dV ∂Φ = − Balance of forces parallel to flow. -
Contribution of Horizontal Advection to the Interannual Variability of Sea Surface Temperature in the North Atlantic
964 JOURNAL OF PHYSICAL OCEANOGRAPHY VOLUME 33 Contribution of Horizontal Advection to the Interannual Variability of Sea Surface Temperature in the North Atlantic NATHALIE VERBRUGGE Laboratoire d'Etudes en GeÂophysique et OceÂanographie Spatiales, Toulouse, France GILLES REVERDIN Laboratoire d'Etudes en GeÂophysique et OceÂanographie Spatiales, Toulouse, and Laboratoire d'OceÂanographie Dynamique et de Climatologie, Paris, France (Manuscript received 9 February 2002, in ®nal form 15 October 2002) ABSTRACT The interannual variability of sea surface temperature (SST) in the North Atlantic is investigated from October 1992 to October 1999 with special emphasis on analyzing the contribution of horizontal advection to this variability. Horizontal advection is estimated using anomalous geostrophic currents derived from the TOPEX/ Poseidon sea level data, average currents estimated from drifter data, scatterometer-derived Ekman drifts, and monthly SST data. These estimates have large uncertainties, in particular related to the sea level product, the average currents, and the mixed-layer depth, that contribute signi®cantly to the nonclosure of the surface tem- perature budget. The large scales in winter temperature change over a year present similarities with the heat ¯uxes integrated over the same periods. However, the amplitudes do not match well. Furthermore, in the western subtropical gyre (south of the Gulf Stream) and in the subpolar regions, the time evolutions of both ®elds are different. In both regions, advection is found to contribute signi®cantly to the interannual winter temperature variability. In the subpolar gyre, advection often contributes more to the SST variability than the heat ¯uxes. It seems in particular responsible for a low-frequency trend from 1994 to 1998 (increase in the subpolar gyre and decrease in the western subtropical gyre), which is not found in the heat ¯uxes and in the North Atlantic Oscillation index after 1996. -
REVIEW the Quasigeostrophic Omega Equation: Reappraisal
VOLUME 143 MONTHLY WEATHER REVIEW JANUARY 2015 REVIEW The Quasigeostrophic Omega Equation: Reappraisal, Refinements, and Relevance HUW C. DAVIES Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland (Manuscript received 29 March 2014, in final form 1 September 2014) ABSTRACT A two-component study is undertaken of the classical quasigeostrophic (QG) omega equation. First, a reappraisal is undertaken of extant formulations of the equation’s so-called forcing function. It pinpoints shortcomings of various formulations and prompts consideration of alternative forms. Particular consider- ation is given to the contribution of flow deformation to the forcing function, and to the role of the advection of the geostrophic flow by the thermal wind (the R vector). The latter is closely related to the Q vector, the horizontal component of the ageostrophic vorticity, and the forcing function itself. The reexamination pro- motes further examination of the physical interpretation and diagnostic use of the omega equation particu- larly for assessing richly structured subsynoptic flow features. Second, consideration is given to the dynamics associated with the equation and its more general utility. It is shown that the R vector is intrinsic to a quasigeostrophic cascade to finer-scaled flow, and that a fundamental feature of the QG omega equation—the in-phase relationship between cloud-diabatic heating and the at- tendant vertical velocity—has important potential ramifications for the assimilation of data in numerical weather prediction (NWP) models. Finally, it is shown that, in the context of considering NWP model output, mild generalizations of the quasigeostrophic R vector retain interpretative value for flow settings beyond geostrophy and warrant consideration when addressing some contemporary NWP challenges. -
A Generalization of the Thermal Wind Equation to Arbitrary Horizontal Flow CAPT
A Generalization of the Thermal Wind Equation to Arbitrary Horizontal Flow CAPT. GEORGE E. FORSYTHE, A.C. Hq., AAF Weather Service, Asheville, N. C. INTRODUCTION N THE COURSE of his European upper-air analysis for the Army Air Forces, Major R. C. I Bundgaard found that the shear of the observed wind field was frequently not parallel to the isotherms, even when allowance was made for errors in measuring the wind and temperature. Deviations of as much as 30 degrees were occasionally found. Since the ther- mal wind relation was found to be very useful on the occasions where it did give the direction and spacing of the isotherms, an attempt was made to give qualitative rules for correcting the observed wind-shear vector, to make it agree more closely with the shear of the geostrophic wind (and hence to make it lie along the isotherms). These rules were only partially correct and could not be made quantitative; no general rules were available. Bellamy, in a recent paper,1 has presented a thermal wind formula for the gradient wind, using for thermodynamic parameters pressure altitude and specific virtual temperature anom- aly. Bellamy's discussion is inadequate, however, in that it fails to demonstrate or account for the difference in direction between the shear of the geostrophic wind and the shear of the gradient wind. The purpose of the present note is to derive a formula for the shear of the actual wind, assuming horizontal flow of the air in the absence of frictional forces, and to show how the direction and spacing of the virtual-temperature isotherms can be obtained from this shear. -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
Lecture 18 Condensation And
Lecture 18 Condensation and Fog Cloud Formation by Condensation • Mixed into air are myriad submicron particles (sulfuric acid droplets, soot, dust, salt), many of which are attracted to water molecules. As RH rises above 80%, these particles bind more water and swell, producing haze. • When the air becomes supersaturated, the largest of these particles act as condensation nucleii onto which water condenses as cloud droplets. • Typical cloud droplets have diameters of 2-20 microns (diameter of a hair is about 100 microns). • There are usually 50-1000 droplets per cm3, with highest droplet concentra- tions in polluted continental regions. Why can you often see your breath? Condensation can occur when warm moist (but unsaturated air) mixes with cold dry (and unsat- urated) air (also contrails, chimney steam, steam fog). Temp. RH SVP VP cold air (A) 0 C 20% 6 mb 1 mb(clear) B breath (B) 36 C 80% 63 mb 55 mb(clear) C 50% cold (C)18 C 140% 20 mb 28 mb(fog) 90% cold (D) 4 C 90% 8 mb 6 mb(clear) D A • The 50-50 mix visibly condenses into a short- lived cloud, but evaporates as breath is EOM 4.5 diluted. Fog Fog: cloud at ground level Four main types: radiation fog, advection fog, upslope fog, steam fog. TWB p. 68 • Forms due to nighttime longwave cooling of surface air below dew point. • Promoted by clear, calm, long nights. Common in Seattle in winter. • Daytime warming of ground and air ‘burns off’ fog when temperature exceeds dew point. • Fog may lift into a low cloud layer when it thickens or dissipates. -
OZO V.1.0: Software for Solving a Generalised Omega Equation and the Zwack–Okossi Height Tendency Equation Using WRF Model Output
Geosci. Model Dev., 10, 827–841, 2017 www.geosci-model-dev.net/10/827/2017/ doi:10.5194/gmd-10-827-2017 © Author(s) 2017. CC Attribution 3.0 License. OZO v.1.0: software for solving a generalised omega equation and the Zwack–Okossi height tendency equation using WRF model output Mika Rantanen1, Jouni Räisänen1, Juha Lento2, Oleg Stepanyuk1, Olle Räty1, Victoria A. Sinclair1, and Heikki Järvinen1 1Department of Physics, University Of Helsinki, Helsinki, Finland 2CSC – IT Center for Science, Espoo, Finland Correspondence to: Mika Rantanen (mika.p.rantanen@helsinki.fi) Received: 19 August 2016 – Discussion started: 29 September 2016 Revised: 3 February 2017 – Accepted: 6 February 2017 – Published: 21 February 2017 Abstract. A software package (OZO, Omega–Zwack– ucation, and the distribution of the software will be supported Okossi) was developed to diagnose the processes that af- by the authors. fect vertical motions and geopotential height tendencies in weather systems simulated by the Weather Research and Forecasting (WRF) model. First, this software solves a gen- eralised omega equation to calculate the vertical motions as- 1 Introduction sociated with different physical forcings: vorticity advection, thermal advection, friction, diabatic heating, and an imbal- Today, high-resolution atmospheric reanalyses provide a ance term between vorticity and temperature tendencies. Af- three-dimensional (3-D) view on the evolution of synoptic- ter this, the corresponding height tendencies are calculated scale weather systems (Dee et al., 2011; Rienecker et al., with the Zwack–Okossi tendency equation. The resulting 2011). On the other hand, simulations by atmospheric models height tendency components thus contain both the direct ef- allow for exploring the sensitivity of both real-world and ide- fect from the forcing itself and the indirect effects (related alised weather systems to factors such as the initial state (e.g.