Impact of Temperature on Viscosity of Liquid

Impact of Temperature on Viscosity of Liquid INTRODUCTION    Hydrodynamics, as defined by the Merriam Webster Dictionary, is the branch of physics that deals with the motion of fluids, and the forces acting on solid bodies immersed in fluids and in motion relative to them (2017). The study of fluids originated in Ancient Greece, was coupled with the works of Persian philosophers in Medieval times, and eventually, with many contributions made by scientists such as Archimedes, Leonardo Da Vinci and Isaac Newton, was developed into the branch of fluid dynamics that exists today (WiseGeek, 2017). Any substance can be classed as a fluidif it changes shape uniformly in response to external forces. Many characteristics of such a substance include; pressure, temperature, mass, density and viscosity (Washington.edu, 2017). The term viscosity is defined as a fluids resistance to flow in relation to its inner molecular structure, and is largely affected by temperature (Viscopedia, 2017). As the temperature of a fluid increases, so does the thermal/kinetic energy of its liquid molecules, which results in increased amounts of movement as the particles begin to move faster. Due to this increased amount of movement, the attractive binding energy of the fluid is reduced, consequently decreasing the fluids resistance to flow (Azom, 2013). This principle is demonstrated in the following theoretical figures, which depict the relationship between the temperatures and viscosities of various fluids:          From using the known viscosities of fluids at various temperatures, and developing functions that model these relationships in programs such as Microsoft Excel or on a graphics calculator, the approximate viscosity of a liquid at any temperature can be found by substituting values for temperature into the relevant formula. An example of this process is seen below: As seen in Figure 1, the equation that models the relationship between temperature and viscosity of water is y = 1.5396e-0.018x. If the temperature of the water was 4à ¡Ã‚ µÃ¢â‚¬â„¢Cà ¢Ã¢â€š ¬Ã‚ ¦. y = 1.5396e-0.018x y = 1.5396e-0.018 x 4 y = 1.433 mPas Therefore, the viscosity of the water at 4à ¡Ã‚ µÃ¢â‚¬â„¢C is 1.433 mPas. Viscosity is also what causes an object to slow as it travels through a fluid, and is one component in the phenomenon of drag force, the retarding force that acts opposite to the direction of motion of a body or object. The drag force of any object is dependent on the viscosity of the fluid it travels through, velocity of the object, reference area of the object, and the drag coefficient. The following formula can be used to calculate the total drag force acting upon an object (Wikipedia, 2017): Where: = Drag force (N), = Mass density of fluid (mPas), = Flow speed of object relative to fluid (ms-1), = Drag coefficient (no units), A = Reference area (m2) A worked example of this calculation with assumed and exact values is modelled below: Assume that for a flat surfaced mass travelling through water at 4à ¡Ã‚ µÃ¢â‚¬â„¢Cà ¢Ã¢â€š ¬Ã‚ ¦. mPas = 0.3ms-1 0.82 A = 2.5 x 10-4 The values are then substituted into the drag force formulaà ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦ Therefore the drag force of the mass travelling through water at 4à ¡Ã‚ µÃ¢â‚¬â„¢C is approximately 4.6125 x 10-5N. One component of this force, as represented by in the drag force equation, is a drag coefficient (The Free Dictionary, 2017). As stated in The Physics of Sailing by Ryan M. Wilson (2010), intuitively, the drag should depend linearly on the density of the fluid in which the body is immersed (because force depends linearly on mass) and linearly on the area of the body that is exposed to the flow because the volume of fluid that must be displaced as the body moves through it is proportional to this area. A range of calculated drag coefficients for various shapes can be seen in Figure 3. It can therefore be concluded that the lower the drag coefficient of an object, the lower the amount of drag force that occurs as it travels through a fluid (Brock University, 2017). As seen in Figure 2, the drag coefficient of an object is reliant on its shape. It can be concluded that a mass with a flat reference area will travel almost two times slower than that with a spherical reference area. A conical reference area will cause an object to fall slightly slower than a spherical mass, but faster than one with a flat reference area. Theoretically, as deducted from Figure 2, it is concluded that a mass with a spherical reference area will travel faster than one with either a conical and flat surfaced reference area, the latter of these theoretically having the slowest time of fall through a liquid out of the three. Although many different fields of study incorporate knowledge of drag forces and viscosity, arguably one of the most important applications is found within the engineering of ships and the design of the hulls, specifically in relation to sailing competitions such as the Americas Cup. As one of the largest sailing races in the world, this competition has strict guidelines for ship design, consequently meaning that vessel engineers must find the best combinations (of measurements) to create the fastest ship possible (Krepal, 2014). When building, engineers must be familiar with the environmental sailing conditions of the race in order to build the most suitable hull with the least amount of drag this is determined in regards to the temperature of the sea and its viscosity. As calculating viscosity is a complex procedure, ship engineers often refer to data such as seen in Figure 2 to determine aspects of ship design. In regards to the speed of the ship, it can be concluded from previous knowledge on drag force that the lower the drag coefficient of a vessel, the easier it is for it to break through the water, overcoming shear force and resulting in a faster travelling time (Krepal, 2014). When unknown, the drag force formula can be rearranged to find the drag coefficient; however, often these values are computed from graphical designs of the ship as the phenomenon of drag force is dependent on many variables. Testing on model ships is also performed to determine how vessels will travel under different conditions (Mecaflux, 2013). HYPOTHESIS Based on the previous research, the hypothesis for this experiment is that: If a body is falling in a liquid, then i) the lower the viscosity of the liquid, which decreases as temperature increases, the faster will be the rate of fall of the object, and ii) the lower the drag coefficient of the body, the smaller its drag force will be, as the velocity of an object as it travels through a fluid is inversely proportional to the amount of resistance it encounters. METHOD The supplies needed 1L glass measuring cylinder, 2L water, 2kg honey, 2L canola oil, 3 x 53g cylindrical masses with different reference areas of the same 0.9cm radius (flat, spherical, streamlined/conical), a Thermomix, thermometer, a logbook and pencil, and a video recording device. All measurements and data were to be collected and stored in a logbook and on the video recording device. A risk assessment form was completed before the commencement of the experiment, in order to recognise any potential hazards regarding the equipment that was to be used. It was identified that any device used to heat up the liquids, and the hot liquids themselves, had potential to burn the person completing the experiment, and it was possible for the glass cylinder to topple over and shatter as it was filled with each liquid. Covered shoes were worn during the experimental procedures to protect the feet from any falling objects and glass, and care was taken when using heating devices and handling ho t liquids. As the hypothesis was written in two parts, there were two variables that remained constant depending on the experimental procedure (independent variables) the first was the temperature/viscosity of each liquid, and the second was the reference area of the masses travelling through each. The dependent variable in both was the velocity of the object. The equipment was set up for the experiment as depicted in Figure 6. 1L of each liquid was placed in the fridge and cooled to 5à ¡Ã‚ µÃ¢â‚¬â„¢C. 1L of the first liquid, water, was heated in the Thermomix to 37à ¡Ã‚ µÃ¢â‚¬â„¢C and then poured into the glass cylinder. The flat ended mass was dropped from the 1L mark, and its fall was timed and recorded on the video recording device. The object was then extracted from the bottom of the cylinder, and this process was repeated two more times. The flat ended mass was then removed, and the same procedure was performed again for both the spherical and conical shaped masses. After these tests were completed, the water was poured back into the Thermomix and was heated to 50à ¡Ã‚ µÃ¢â‚¬â„¢C. Once at temperature, the water was again poured into the cylinder, and the previously stated processes were repeated for each mass. After these tests were completed, the water was poured into the Thermomix. The chilled water from the fridge was then take n out, checked with a thermometer to be at 4à ¡Ã‚ µÃ¢â‚¬â„¢C, and poured into the cylinder for testing. The previously stated processes for each mass were repeated. After all of the masses had been dropped into the water at all three temperatures, the water was disposed of, and the experimental space cleaned up to prepare for the next round of testing. All results were recorded into various tables in the logbook, and later graphed for analysis. The second liquid, canola oil, was heated in the Thermomix to 35à ¡Ã‚ µÃ¢â‚¬â„¢C and then poured into the glass cylinder. The previously stated procedures were repeated. All results were recorded into a table, and later graphed for analysis. The third liquid, honey, was heated in the Thermomix to 35à ¡Ã‚ µÃ¢â‚¬â„¢C and then poured into the glass cylinder. The previously stated procedure was repeated. All results were recorded into a table, and later graphed for analysis. In this experiment, it is noted that apart from that which were independent and dependant, all other variables were controlled, consequently meaning that every aspect of the testing remained consistent. These controlled variables included the positioning of the glass cylinder and video recording device, the dropping point of the masses, the weight of the small masses used, the radius of the masses, the distance each mass fell, the type of oil and honey used, etc. By controlling all other variables, the results recorded from the testing become more accurate. RESULTS (HYPOTHESIS PART 1) CALCULATED VALUES FOR VISCOSITY By using the formulas generated from the Excel graphs in Figure 1, which model the relationships between the viscosity and temperature of each liquid, and substituting in the experimental temperatures for x (4, 37 and 50), the empirical viscosities of each fluid at different temperatures were calculated. The tables and graphs of these results follow, with all calculations performed recorded in the logbooks. WATER Temperature (à ¡Ã‚ µÃ¢â‚¬â„¢C) Viscosity (mPas) 4 1.433 37 0.791 50 0.626 y = 1.5396e-0.018x CANOLA OIL y = 186.16e-0.049x Temperature (à ¡Ã‚ µÃ¢â‚¬â„¢C) Viscosity (mPas) 4 153.026 37 30.375 50 16.064 HONEY y = 138468e-0.117x Temperature (à ¡Ã‚ µÃ¢â‚¬â„¢C) Viscosity (mPas) 4 86716.073 37 1825.108 50 398.774 Water Flat Surfaced Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Time of Fall (s) 4 0.41 0.62 0.81 0.61 37 0.62 0.50 0.50 0.54 50 0.66 0.60 0.69 0.65 Spherical Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Time of Fall (s) 4 0.91 0.68 0.37 0.65 37 0.53 0.59 0.55 0.56 50 0.43 0.62 0.60 0.55 Conical Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Time of Fall (s) 4 0.40 0.57 0.54 0.50 37 0.78 0.50 0.62 0.63 50 0.59 0.50 0.43 0.51 Canola Oil Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Time of Fall (s) 4 0.60 0.55 0.65 0.60 37 0.62 0.69 0.58 0.63 50 0.49 0.52 0.46 0.49 Flat Surfaced Mass Spherical Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Rate of Fall (s) 4 0.63 0.59 0.69 0.636667 37 0.56 0.56 0.53 0.55 50 0.45 0.46 0.42 0.443333 Conical Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Rate of Fall (s) 4 0.67 0.53 0.43 0.543333 37 0.46 0.49 0.38 0.443333 50 0.36 0.45 0.39 0.4 Honey Flat Surfaced Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Rate of Fall (s) 4 2040 2257.2 2008.2 2101.8 37 498.6 489 508.2 498.6 50 84 91.2 95.4 90.2 Spherical Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Rate of Fall (s) 4 1428 1537.2 1362.6 1442.6 37 362.4 370.2 389.4 374 50 72 70.8 73.8 72.2 Conical Mass Temperature of Fluid (à ¡Ã‚ µÃ¢â‚¬â„¢C) Time 1 (s) Time 2 (s) Time 3 (s) Average Rate of Fall (s) 4 1188 1135.2 1305 1209.4 37 307.2 305.4 320.4 311 50 66.6 65.4 67.2 66.4 HYPOTHESIS PART 2 CALCULATED DRAG FORCES Worked Example: Flat surfaced mass travelling through water at 4 °C mPas = 0.2916 ms-1 0.82 A = 2.545 x 10-4 The values are then substituted into the drag force formulaà ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦ WATER: TEMPERATURE ( °C) DRAG FORCE (Nx10-5) Flat 4 4.3600 37 3.0830 50 1.6840 Spherical 4 3.9480 37 2.9358 50 2.4084 Conical 4 132.3700 37 46.0270 50 55.5820 CANOLA OIL: TEMPERATURE ( °C) DRAG FORCE (Nx10-5) Flat 4 483.020 37 86.971 50 76.033 Spherical 4 434.850 37 116.860 50 96.567 Conical 4 12120.000 37 3620.000 50 2320.000 HONEY: TEMPERATURE ( °C) DRAG FORCE (Nx10-5) Flat 4 0.0223060 37 0.0083423 50 0.0556950 Spherical 4 0.0485340 37 0.0151850

Free Process Essays - How to Procrastinate :: Free Expository Process Essays

How to Procrastinate Have you ever heard friends or family members brag about how productive they were that day, or week, or month? Those people really bother me. And it's because I can never get anything done; it takes me a long time to accomplish the simplest tasks. I pride myself in being a grade A procrastinator. My three specific examples will help anyone perfect the arts of wasting time and procrastination. Then you can brag about how extremely unproductive you were today. I am not a super messy person, but I don't necessarily keep my room clean all the time, either. Many a time I have opted to put away my clothes, clean out my binder and my backpack, make my lunch for the next day, and/or take a shower before I get to my homework. Doing all these activities takes a while, and I usually end up doing all of them on nights when I have a lot of homework, or if I have a test the next day. Any type of cleaning or household chore would work, though, such as scrubbing the shower, vacuuming, or dusting. Another great way to waste time is to daydream. I can sit for fifteen minutes or more before I realize that I should be doing something else. I usually think about something that happened that day, and then imagine an alternate ending. Or I will imagine calling someone on the phone, and play out the entire conversation in my head. Sometimes I look out the window and look at all the trees, clouds, squirrels, or even the grass in my backyard. This is a great procrastination method when combined with a simple cleaning task, like cleaning out a backpack. The best way to procrastinate is to interact with other people. That way you can lay part of the blame on someone else: "Well, Mom was talking to me about something important. I couldn't just walk away." I prefer to talk on the phone to friends who go to schools far away. We usually don't talk too often, so when we do, we have to make it count. For those that who don't want to spend a mountain of money on phone bills, any kind of messaging system on the Internet is a great way to communicate.

Mia philippines Essay

The Philippines was first put on the map by Portuguese adventurer Magellan working for the Spanish throne on March 16, 1521. The Philippines had become a Spanish colony and was the first country to be named after a sovereign, Phillip II of Spain.1 Spanish rule had continued until 1898 when the Philippines had become an American colony following the Spanish-American War for the stately sum of $20 million. In 1942 during WWII, the Philippines had fallen under Japanese occupation and was liberated by American and Filipino forces under the leadership of General Douglas MacArthur in a fiercely contested battle that raged on between 1944 and 1945. The Philippines had attained its independence on July 4, 1946, and had a functioning democratic system. 2 The Philippines Archipelago consisted of 7,100 islands, covering an area of 299,735 square kilometers and was slightly larger than Arizona. The capital city of Manila was situated on the largest Philippine island of Luzon (see Exhibit 1). The Philippines had a gross domestic product (GDP) per capita of $3,400.3 The percentage of the population of the Philippines living below US$2 a day was 45.2 per cent in 2006.4 PHILIPPINE BUSINESS ENVIRONMENT Research conducted in 2009 showed that the Philippines was ranked 140th for ease of doing business and 155th for starting a business, out of a total of 178 countries. It took on average 15 procedures and a total of 52 days to complete business startup procedures in the Philippines compared to six procedures and 44.2 days and 5.8 procedures and 13.4 days for the same process in Asia and Organisation for Economic Cooperation and Development (OECD) countries, respectively.5 The Philippines had the second lowest savings and investment as share of GDP ratio in Asia6 (see Exhibit 2). PHILIPPINE FISHING INDUSTRY The Philippines has total territorial waters of 2.2 million square kilometers, of which coastal waters comprise 266,000 square kilometers and coastal reef area (10 to 20 fathoms deep, where reef fishing takes place) comprise 27,000 square kilometers.7 In 2003, the Philippines ranked eighth among the top fish-producing countries in the world with its total production of 3.62 million metric tons of fish, crustaceans, mollusks and aquatic plants (including seaweed). The production constituted 2.5 per cent of the total world production of 146.27 million metric tons.8 The fishing industry’s contribution to the country’s GDP was 2.3 per cent and 4.2 per cent, at current and constant prices, respectively. The industry employed a total of 1,614,368 fishing operators nationwide,9 of which the artisanal fisheries sector accounted for 1,371,676.10 Artisanal fishing operations were typically family-based and used smaller craft. There were a total of 469,807 fishing boats in the Philippines, of which 292,180 were non-motorized and 177,627 were motorized.11 Fish was not only an important source of nutrition, but as fishing did not require landownership or special permits it was an employment of last resort for people who had no other means of subsistence. MIA, DENMARK MIA was established in Denmark in 1975 by wealthy businessman Hagen Nordstrom, who dedicated the NGO to his wife Mia and made fighting poverty his life’s work. (MIA stood for â€Å"beloved† in Danish.) MIA had initially focused solely on poverty-alleviating projects in Africa and had expanded its operations to Latin America and the Caribbean only in the early 1990s. The grandson of Nordstrom, Gillis Nordstrom, had taken over as MIA chairman in 2004 on the eve of the Bander Aceh Tsunami of December 26, 2004, which devastated Southeast Asia and killed as many as 130,000 people.12 Nordstrom had taken initiative and redirected MIA to focus on disaster recovery and poverty alleviation projects in Southeast Asia. MIA had established an office in Manila in January 2006, and the young Danish development economist Borje Petersen was hired to manage the MIA Philippines office. Petersen was paid a starting salary of $75,000 a year plus housing, slightly below average for a comparable development economist position. Petersen knew that MIA’s attention was focused on Indonesia and Malaysia, which had been the hardest hit by the tsunami, and was anxious to carve out a position for MIA Philippines by designing an exceptional project. As the expansion into Asia was the pet project of MIA’s chairman, Petersen felt assured that funding would be easily appropriated and even expedited. Petersen knew that the average overseas posting for a development economist for MIA was two years and had quickly established contact with local and international stakeholders and set up numerous meetings with large development project counterparts such as the Asian Development Bank, the World Bank and the German development aid organization GFZ to get an expedited understanding of the Philippines and its unique needs. Based on the initial research, Petersen had decided that, whereas an agricultural project would be feasible, it would take a long time to realize and the outcome could be complicated given the Philippines’ proneness to be hit by typhoons. Petersen’s research had revealed that small-scale aquaculture projects had been successfully implemented in the Philippines in the past. However, there were hardly any projects to speak of directed at artisanal fishing and picking up on the vested opportunity and his desire to deliver fast results and prove himself worthy of the task that MIA and its chairman demanded, he had chosen to design a project helping artisanal fishermen. Petersen had researched the possibility of helping a fishing village close to Manila and the search for the ideal village had come to a successful ending when MIA’s driver, Vicente Tubo, had mentioned how some of his distant cousins fished for a living in a fishing village seven to nine hours by car from Manila. A factfinding mission to the village Barangay San Hagon was undertaken and the village was thus chosen as the beneficiary of MIA’s pilot project in the Philippines. BARANGAY SAN HAGON Barangay San Hagon boasted 125 households and had a resident population of 625. San Hagon lay on the south coast of Luzon, the largest island of the Philippines. The Barangay was the smallest administrative division in the Philippines and stemmed from the Spanish â€Å"Barrio.†13 Barangay San Hagon was administered by a local government unit (LGU) and consisted of seven Barangay council members and a chairman. The chairman of Barangay San Hagon was Rafael Buenaventura, age 59, who had held office for more than a decade. Fishing villages in the Philippines were very vulnerable to external risk, especially natural calamities such as typhoons, flooding and fish kills, which severely affected their financial situation.

The Battle Of The Punic Wars - 3659 Words

Introduction The Punic Wars were a defining moment in the expansion of the Roman Republic, with the Second Punic War (218 – 201 BC (Grant, 1960)) playing the part of a corner stone in the bridge to create the powerful Roman Empire. Moreover, this was the first time that Rome had expanded into territories outside of Italy which was pivotal in the development of the Roman Republic, and furthermore the Rome Empire, as it marks the beginning of an imperial Roman power (Rickard, 2001). Accordingly, this war has captured great interest as it triggered a number of significant modifications to the Roman Republic. This war between the Romans and their most powerful enemies, the Carthaginians, incurred devastating losses on both sides, with the Romans eventually rising to victory. Following their victory, the Roman Republic was almost geographically unrecognisable and had been moulded by the Second Punic War into the â€Å"super-powered Empire of the Mediterranean† (UNRV History, Results of the Second Punic War, 2015). This investigation aims to explore to what extent the most significant outcome of the Second Punic War was the changes in social hierarchy within the Roman army. In order to examine whether the impact on the Roman army following the Second Punic War was the most significant outcome, other key outcomes must also be assessed, such as peace treaties, territorial gains and the destruction of Rome’s greatest enemy: Carthage. At the onset of the war, however, a CarthaginianShow MoreRelatedThe Battle Of The Punic Wars2439 Words   |  10 PagesThe Punic Wars, a century-long conflict between Rome and Carthage started in 264 B.C. and continued until 146 B.C. when Carthage gets destroyed. 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