Development of Energy Efficient Lighting Technology

Development of Energy Efficient Lighting Technology 

LED VS TUNGSTEN 

Abstract

Since many government regulations are clamping down on wastage of energy. Incandescent lighting technology and many Lighting producing companies focusing on developing more energy efficient lighting technology. Therefore, it is important to discuss the emergence and growing popularity of the lighting.

Contents

1 Introduction

1.1 Background

2 Key Themes

3 Aims and Objectives

3.1 Project Aim

3.2 Project objectives

4 Rationale

5 Tasks

6 Resources

7 Literature Research Methodology

8 Risk Assessment

9 Ethics Review

10 Appendices

10.1 A1: Bibliography

10.2 A2: Schedule

Introduction

1.1         Background

LED is used for light fixtures which were created in 1962 to produce light using a light emitting diode (LED). Since then the technology has grown rapidly, with LED lights becoming an extremely popular lighting solution in recent years amongst many Studio lighting producing companies. LEDs have become the most efficient source of lighting available, using up to 90% less energy than incandescent lighting and 60% less than fluorescent lighting (Bevan, 2017).  The process of generating light is what distinguishes LEDs from traditional lighting, as regular incandescent bulbs produce light by creating heat.

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Light Emitting Diodes is an electrical light source that only allows an electrical current to flow in one direction. LEDs contain two conductive materials that are placed in contact with each other. Once electricity is applied to the diode, the atoms in one material become charged with energy. This energy is then released in the form of electrons into the other conductive material – this release of energy is what creates light (Bevan, 2017). It is basically a semiconductor that can convert electricity to light.

Tungsten lighting refers to the common incandescent light bulb. Incandescent light is an electric light that is heated to such a temperature that it glows to provide artificial light to indoor areas. The filament used in tungsten is metal, with a very high melting point and capability to glow when heated (McGill, 2015). This method of producing artificial lighting is highly inefficient as they can only convert 5-10% of the energy they produced into the light, while the remaining energy is converted to heat. This results in an extreme waste of electricity (Beaconlighting.com.au, 2019). Whereas, most attractive benefits of LED lighting over traditional lighting technology has been its super efficiency when compared to other light sources.

In order to prepare great art, it is necessary to control and manipulate light correctly to get the best luminosity, texture, colour and vibrancy. Advanced technology and innovative gadgets had overall changed dynamics of the media industry. It now demands a professional production and for that lighting carries great weight in terms of settings and toning up mood (PAUL, 2016). However, most of the productions are still using traditional light kits but since last decade LED’s are becoming convenient and a conservative option.

The following project will tend to look into the technology behind Led lighting and Tungsten Lighting. Various comparisons would be made ranging from their efficiency, cost effectiveness, environmental friendliness, availability, life span and specifically their uses in the studio when it comes to cinematography. The advantages and disadvantages of both technologies would be discussed as well. Moreover, an in-depth study of lighting kits available at the university would be done. Furthermore, we would be evaluating LED lighting and Tungsten fixtures in terms of their output power and colour accuracy.

3.1         Project Aim

According to online records, Spaghetti studio – a popular hire studio, have over 25 lighting kits ranging from LED Top light to Fluorescent Flolight to 3x Fresnel Dedolight. This lightning comes in different power ranges powered by different lighting technology giving one different option to choose from.

This project aims to:

3.2         Project objectives

The following research is expected to act as a catalyst for a better change in the university lighting and improved content creation. At the end of this project the following objectives would have been achieved:

      Evaluating LED light availability in University

      Monitoring output power and colour accuracy

      Critically evaluating benefits of LED over Tungsten.

      Comparing results of all different tests

      Evaluating and concluding new lights requirements

      Proposal on best Lighting kits to University for future purchase based on findings

As it is often said – ‘Change is constant’, there is a need for constant re-evaluation of kits accessible at the university. Technology is fast evolving based on unending demands for more energy efficient, environmentally friendly, safer and easy to use lighting source, more lighting producing companies such as ARRI and ROTO light are focusing on LED lighting technology, as it is observed in their recent products.

It is important that the university too gradually starts embracing the LED lighting technology as it has been predicted by many productions of Tungsten lighting will reduce over the years with more focus and research on the earlier mentioned technology (Beaconlighting.com.au, 2019).

There is also an increasing advantage of LED over Tungsten lighting in the cinematography world as its technological advances. This is highlighted by the major lighting renovation done by KNPB-TV a broadcast studio as they transitioned to LED lighting, replacing all the Incandescent fixtures (Leeper, 2018)

5         Tasks

The following project is expected to be completed in 4 phases. Each phase consists of a few tasks, all the task of each needs to be completed before moving on to the next phase.

WBS

Task Name

Duration

Start

Finish

Predecessors

0

LED VS TUNGSTEN

38 days

3/4/2019

4/24/2019

1

   Project Initiation

12 days

3/4/2019

3/19/2019

1.1

      Defining Purpose

3 days

3/4/2019

3/6/2019

1.2

      Defining Aims and Objectives

3 days

3/7/2019

3/11/2019

2

1.3

      Initiating Research

2 days

3/12/2019

3/13/2019

3

1.4

      Comparing Led lights with Tungsten

4 days

3/14/2019

3/19/2019

4

2

   Project Plan

8 days

3/14/2019

3/25/2019

2.1

      Preparing Project Plan

3 days

3/14/2019

3/18/2019

4

2.2

      Preparing a Procurement Plan

2 days

3/19/2019

3/20/2019

7

2.3

      Documenting the benefits

3 days

3/21/2019

3/25/2019

8

2.4

      Preparing Risk plan

2 days

3/19/2019

3/20/2019

7

3

   Project Execution

18 days

3/19/2019

4/11/2019

3.1

      Looking at popular hire studios

2 days

3/19/2019

3/20/2019

7

3.2

      Conducting Research

2 days

3/21/2019

3/22/2019

12

3.3

      Conducting Test

3 days

3/25/2019

3/27/2019

3.3.1

         Tungsten Power Consumption

2 days

3/25/2019

3/26/2019

13

3.3.2

         Texture differences

1 day

3/25/2019

3/25/2019

13

3.3.3

         Colour Differences

3 days

3/25/2019

3/27/2019

13

3.3.4

         Vibrancy Test

2 days

3/25/2019

3/26/2019

13

3.4

      Comparing Results

2 days

3/28/2019

3/29/2019

14

3.5

      Evaluation

3 days

4/1/2019

4/3/2019

19

3.6

      Preparing Proposal for new equipment

3 days

4/4/2019

4/8/2019

20

3.7

      Documenting comparative advantages

2 days

4/9/2019

4/10/2019

21

3.8

      Documenting competitive advantage

3 days

4/9/2019

4/11/2019

21

4

   Project Closing

9 days

4/12/2019

4/24/2019

4.1

      Forwarding the proposal

2 days

4/12/2019

4/15/2019

11

4.2

      Ensuring All Test Are Conducted Fairly

3 days

4/16/2019

4/18/2019

25

4.3

      Highlighting Importance of LED’s

2 days

4/19/2019

4/22/2019

26

4.4

      Proposing Innovative Lights

1 day

4/23/2019

4/23/2019

27

4.5

      Providing Pictures of Different studios

1 day

4/24/2019

4/24/2019

28

5

   Research Complete

0 days

3/4/2019

3/4/2019

Resources play an important for the development of any project. In order to conduct the research we would be needing following resources to test texture, colour, luminosity and vibrancy of the project;

      Human Capital

      Equipment

      Knowledge of American Cinematography

      LED Lighting: Professional Techniques for Digital Photographers

      Online tools

      Statistical tools

      Light meter

The role of a methodology in research is the process which is used to collect data, process it into meaningful information that is basically used to support the aim of the thesis. The methods for gathering this data will be in a systematic form so as to guarantee that the correct statistical data is gathered. This following research project methodology constitutes a systematic literature review. The key purpose to conduct the research is to synthesize the result of colour, texture, luminosity, and vibrancy with the advanced LED lighting compared to Tungsten lighting.

The data for all following test is to be collected from university premises using data collection tools. Moreover, the project follows 4 phase process in order to complete with the research methodology

Risk assessment has now become a very important part of the project management, the key purpose is to remove uncertainty, prevent accidents and control the overall project cost while executing, controlling and implementing the project (MAJEED, 2018). Although there are no set rules for risk assessment and control procedures usually researchers take some general steps to identify risk and practicable control measures to ensure project success and purpose.

There is no risk attached to this project, as findings would be acquired from the online sources and visiting the site. However, while conducting the research and executing the project following risk can be deduced;

ID

Risk Name

Risk Description

Impact

Probability

Proactive Response Plan

1

Systematic Risk

Every proposed imaging project starts with some kind of challenge or a combination of challenges

H

M

Recheck every detail before processing things further.

2

Team Ability

Results in underestimating efficiency and performance.

L

H

Ensure team is capable enough.

3

Gremlins

But something won’t work the way it is supposed to

M

M

Monitoring the project results carefully.

4

Training to adjust LED Light

Quality training for certain skills can be difficult to secure. 

H

L

Hiring experts/consultants

5

Design lacks flexibility

Poor design makes change requests difficult and costly

VH

VH

Ensuring design adapts to the core purpose of photography and cinematography.

Ethics is simply knowing the difference between the right and wrong where every right step builds blocks for a better society. The one who isn’t aligned with ethics is a wild beast who is lost in this world. There are no major ethical implications surrounded by the following research. Comparatively, the following research plan strives for a better environment by saving energy for a better future.

10.1    A1: Bibliography

      Bevan, R. (2019). What is led a beginner’s guide to led lighting? [Online] https://www.lyco.co.uk. Available at: https://www.lyco.co.uk/advice/what-is-led-a-beginners-guide-to-led-lighting/ [Accessed 24 Jan. 2019].

      Beaconlighting.com.au. (2019). What is LED lighting? [Online] Available at https://www.beaconlighting.com.au/what-is-led-lighting [Accessed 20 Jan. 2019].

      Leeper, S. (2019). An Easy Introduction To LED Studio Lights – Rosco Braq…. [Online] Rosco Spectrum. Available at: https://www.rosco.com/spectrum/index.php/2018/08/easy-intro-to-led-studio-lights-braq-cubes/ [Accessed 23 Jan. 2019].

      McGill, J. (2019). What is a tungsten light bulb? [Online] hunker.com. Available at: https://www.hunker.com/13412704/what-is-a-tungsten-light-bulb [Accessed 22 Jan. 2019].

      MAJEED, M., 2018. Risk Management: an Important Part of Project Management. 10 October.

      PAUL, J., 2016. LED lights are being used more in production, but how do they stack up against fluorescent and tungsten?. 6 January.

      Staff, S. (2019). Lighting Comparison: LED vs Incandescent Lighting. [Online] Stouchlighting.com. Available at: https://www.stouchlighting.com/blog/light-comparison-led-lighting-vs-incandescent-lighting [Accessed 21 Jan. 2019].

10.2    A2: Schedule

Critical Analysis of Efficient Market Hypothesis and Behavioural Finance

Investment Management
This essay will assess and perform a critical analysis with respect to the efficient market hypothesis and the theory associated with behavioural finance. In addition to this, this will further evaluate whether stock prices are determined on the basis of these theories or not.
The stock market is an essential part of the capital market, without which Hall, Foxon, and Bolton (2017) showed, economic development is impossible. Against this background, the exchange, being known to be just a secondary market, nevertheless:

acts as the most important macroeconomic institution for the redistribution of financial resources,
is an instrument for determining the actual value of technology corporations whose assets are connected with the stock market; 
the values ​​of its indices are considered as one of the key indicators of the economic situation as a whole. 

Since the exchange is only a place that provides the opportunity for trade transactions between sellers and buyers of securities, the question arises: is the result of such transactions effective in terms of the mechanism of functioning of the capital market? It will be effective if, as a result of transactions, a fair price is set for the relevant financial assets, under which corporate shares most often act (Hall, Foxon, and Bolton, 2017). In other words, if the stock price set during the exchange trading is correct, then the stock market functions efficiently.
In domestic literature, an effective market is understood in some cases as an ideal market, and in others as an institutional structure with zero transaction costs, equal access to information and equal benefits for all participants (Lo, 2017). There are various trends in the real market, but in general, the tendency to increase the ego of efficiency is constantly making its way through opposing trends. In principle, oscillatory movements are impossible in an ideal market and in its ideal institutional environment. In this regard, an effective market is the antipode of a cyclical market. The efficient market hypothesis built its evidence base on the random walk hypothesis. Paul Samuelson in the mid-1960s published evidence that if the market is efficient, then the price movement is random. Lo (2017) developed this idea in his doctoral dissertation and brought it to the hypothesis of an effective market.

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According to the hypothesis of an effective market, the normal state of the market is effective. In this regard, the market is balanced and does not require any external influences – adjustments (Tuyon and Ahmad, 2016). An inefficient market indicates a crisis and requires external adjustments. For half a century of existence, the efficient market hypothesis has become one of the most influential concepts in modern economics and the cornerstone of financial theory. The hypothesis has become the theoretical basis for measuring an effective and inefficient market, but has not provided criteria to evaluate market performance levels. Market efficiency is presented as a state (axiomatic approach). Special tests of market efficiency/inefficiency have been developed (Tuyon and Ahmad, 2016). Based on the hypothesis of an effective market, various models have been created:
•        A model of rational expectations, on the basis of which a series of correlations of price changes are carried out, informing about the level of market efficiency taking into account risk;
•        A model based on the Pearl Harbour effect (the attack on the US Navy by Japan was preceded by the strange behaviour of the Japanese military). Search for unusual transactions and unusual behaviour of market agents allows you to highlight the first signs of change. Special models capture changes and allow certain conclusions to be drawn;
•        Tests “outside the trading rules” and systematic “randomness” expanded understanding of the behaviour of financial markets. However, they did not play any role in the development of trading practice.
If the efficient market hypothesis assumes a perfectly even, non-cyclical development of the market, then the proponents of the theory of behavioural finance take the opposite position with respect to the effective market hypothesis (Ţiţan, 2015). When analysing the real estate market, Schiller came to the conclusion that a bubble has formed in the mortgage lending market, which indicates the inevitability of a change in the phase of the cycle from growth to crisis.
For an effective market, two dimensions are important – time and space, within which the exchange and all actions take place (Ţiţan, 2015). Trust controls the efficiency of the market, and in its absence, the market itself is impossible. Each market agent is well aware that psychology greatly influences decision-making in financial markets. Excessive gullibility, herd behaviour and following the leader, hope, fear and various emotions can explain some market anomalies, for example, an increase in the frequency of purchases on certain dates (Ţiţan, 2015). Dozens of such anomalies are documented, for example, the effect of calendar investments: many investors make the purchase and sale of assets on the same dates and in the same scenario. Market abnormalities usually increase the level of risk.

The rationality of economic agents is the foundation of neoclassical economics and finance (Jakub, 2015). However, in the past few decades, disciplines such as behavioural economics, behavioural finance and neuroeconomics, which aim at finding phenomena the irrational behaviour of individuals and their explanation. Many studies by psychologists and economists showed that decision-making by consumers, manufacturers, investors, managers and other agents are subject to significant distortion (Jakub, 2015). However, proponents of the theory of economic agents maximizing utility based on all available information, consider that the efficient market hypothesis reflects the most important characteristics of the market, and on average individuals are rational. There are three forms of market efficiency: weak, medium and strong. According to the weak form of the hypothesis in market prices reflects all publicly available historical information about quotes (Jakub, 2015). According to the average form, all publicly available information about quotes and the performance of the issuing company. A strong form of hypothesis implies that the value of securities reflects all possible information, including internal insider (Jakub, 2015). Even proponents of the efficient markets’ hypothesis find a strong form impossible to real life.
The efficient market hypothesis is based on the following points:

the presence of many market participants;
individuals collect and process market information, analyse it until the valuation
market participants will not approximately coincide with the observed market price;
prices reflect information available to market participants, which means limited opportunity
make a profit above the normal level on an ongoing basis;
securities with a higher degree of risk, on average, have a higher yield;
stock returns cannot be predicted, that is, it is subject to “random walk”

Nardo, Petracco‐Giudici, and Naltsidis (2016) argued that stock market prices were changing randomly and were impossible to predict. However, they began to study this topic in more detail in the second half of the 20th century. The most significant works on the subject of the efficient markets’ hypothesis are the book “Random wandering around Wall Street “in 1973 B. In these works, scientists argue that the individual cannot receive a higher return permanent market average and the return on securities is best described by random wandering around.

The opposite point of view is held by economists and financiers of behavioural directions. The theory of behavioural finance combines finance, psychology and sociology. This discipline gained wide popularity after the Nobel Prize in Economics (Hamid, Suleman, Ali Shah, Akash, and Shahid, 2017). A little earlier, in 1999, these professors of finance The Massachusetts Institute of Technology and the University of Pennsylvania have written the book “Non-random Wandering on Wall Street, “where they disproved the hypothesis of efficient markets. The theory of behavioural finance is based on the following premises:

Investors exhibit excessive or inadequate response as a result of distortion in processing information.
The mistakes of individual investors correlate with each other, and therefore they do not compensate for each other.
Limited arbitrage opportunities which refers to having rational investors is not enough to make the market efficient

Over the past 50 years, the hypothesis of efficient markets has been tested a lot of research. The Wall Street Journal conducted an experiment in 1988. It concluded comparing the results of professional investors and randomly choosing stocks to invest newspaper staff (Ramiah, Xu, and Moosa, 2015). Out of 100 times, professional investors won the 61st competition. However, only 51 times out of 100 professional investors were able to surpass the passive strategy investing in the Dow Jones index. Studies carried out by various scientists’ hypotheses of effective markets on real data have shown conflicting results. Most a common result was the fulfilment of the hypothesis for developed countries and the failure to fulfil development.
As an example of the complete opposite of this theory, one can point to the well-known and widely applied theory of Elliott waves (Thaler, 2016). According to this theory, periodic trends arise in stock markets that can be represented as a certain combination of impulse and correction (directed against the trend) waves. These are two mutually exclusive concepts that simulate the behaviour of prices in stock markets. Martingales, in the theory of Elliott waves corresponds to lateral correction, i.e. movement in which prices fluctuate in a certain corridor around its average value (Thaler, 2016). This is also called as trend waves in the martingale model is explained by random walk, and the trend itself as a result of a randomly formed serial correlation.

When individuals make decisions, the following types of cognitive distortion arise:

Heuristics – the presence of mental programs that simplify decision-making, but do not take into account many significant factors (Thaler, 2016). There are two main types of heuristics:

Availability heuristic – revaluation of the probability of those events that are easier to remember or imagine.
Representation heuristic – a judgment on the probability of an event based on stereotypes. An example of a representativeness heuristic is investor revaluation of continuation current trends in the future. Investors often buy assets that are popular in the given time and avoid securities that have recently shown poor results. That’s an example representativeness heuristic that cause speculative bubbles on stock markets.

Excessive confidence – reassessing your ability to achieve any result. Evidence of investor overconfidence was cited by scientist Thaler (2016) in his study where he interviewed 300 professional managers of investment funds and found that almost 100% of them consider that they make a profit at an average level and above average. 
Conservatism – an underestimation of the changes taking place due to confidence in the soon return to normal the state of affairs (Ito, Noda, and Wada, 2016). However, if the changes last long enough, individuals are rebuilt and act inconsistent with the heuristic of representativeness, overestimating the duration of trends.
The desire to avoid loss – a negative reaction to losses is much more than positive to profit. This phenomenon explains the fact that individuals are more likely to take risks in order to avoid losses, not to increase profits (Ito, Noda, and Wada, 2016). Striving to Avoid Losses Underpins Strategy motivation through the imposition of fines, which is often more effective than the motivation of any either a reward.

When it is said that the hypothesis of an effective market implies the equality of market and “right” prices, another, more serious and strong content is invested in this (Ito, Noda, and Wada, 2016). No matter what investments the company intends – in the development of new products, production processes, etc. – market participants are always able to assess the value of these investments, wondering what effect they will have on the nearest quotes of this company, as well as assess the most likely income from the primary placement of shares. Capital markets will provide funds for those investments that have the highest market value (Ito, Noda, and Wada, 2016). If other markets do not experience serious falls, then the hypothesis of an effective market states that the selected investments will be most useful from the point of view of society.
References

Hall, S., Foxon, T.J. and Bolton, R., 2017. Investing in low-carbon transitions: energy finance as an adaptive market. Climate policy, 17(3), pp.280-298.
Hamid, K., Suleman, M.T., Ali Shah, S.Z., Akash, I. and Shahid, R., 2017. Testing the weak form of efficient market hypothesis: Empirical evidence from Asia-Pacific markets. Available at SSRN 2912908.
Ito, M., Noda, A. and Wada, T., 2016. The evolution of stock market efficiency in the US: A non-Bayesian time-varying model approach. Applied Economics, 48(7), pp.621-635.
Jakub, B., 2015. Does Bitcoin follow the hypothesis of efficient market?. International Journal of Economic Sciences, 4(2), pp.10-23.
Lo, A.W., 2017. Efficient markets hypothesis. The New Palgrave Dictionary of Economics, pp.1-17.
Nardo, M., Petracco‐Giudici, M. and Naltsidis, M., 2016. Walking down wall street with a tablet: A survey of stock market predictions using the web. Journal of Economic Surveys, 30(2), pp.356-369.
Ramiah, V., Xu, X. and Moosa, I.A., 2015. Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature. International Review of Financial Analysis, 41, pp.89-100.
Thaler, R.H., 2016. Behavioral economics: Past, present, and future. American Economic Review, 106(7), pp.1577-1600.
Ţiţan, A.G., 2015. The efficient market hypothesis: Review of specialized literature and empirical research. Procedia Economics and Finance, 32, pp.442-449.
Tuyon, J. and Ahmad, Z., 2016. Behavioural finance perspectives on Malaysian stock market efficiency. Borsa Istanbul Review, 16(1), pp.43-61.

 

Is Premium Grade Fuel More Efficient?

What is Gasoline?
Gasoline is made up of molecules made up of hydrogen and carbon atoms arranged in chains. Gasoline molecules have anywhere from, 7 to 11 carbon atoms in each chain. When you burn gasoline under STP, you get carbon dioxide. Which is from the carbon atoms   within the gasoline. A litre of Advance grade Gasoline contains about 1.3 x 108 joules of energy, which is equivalent to 123,000 BTU or 36,047 watt-hours. If it were possible for human beings to digest gasoline, a litre would contain about 31,070 food calories, the energy in a litre of gasoline is equivalent to the energy in about 130 McDonalds hamburgers.

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Where does gasoline come from?
Gasoline is made from crude oil which is drilled from the earth. This crude oil consists of organic material that has been decomposing over millions of thousands of years. The crude oil is then pumped out of the ground and is then refined to get different resources, Petroleum. Petroleum is a liquid that contains hydrocarbons which is used to make gasoline. All hydrocarbon molecules of different lengths have different properties. ex, a chain with just one carbon atom is, (CH4-Methane) it is the lightest chain. As the chains get longer, they get heavier. CH4 (methane), C2H6 (ethane), C3H8 (propane) and C4H10 (butane) are all gases, and they boil at -161, -88, -46 and -1 degrees F, (-107, -67, -43 and -18 degrees C). The chains C5H12 up through C18H32 are all liquids at STP, and the chains above C19 are all solids at STP. The different chain lengths have progressively higher boiling points, so they can be separated out by distillation. This is what happens in an oil refinery, crude oil is heated and the different chains are pulled out by their vaporization temperatures. The chains in the standard range are all very light and are easily vaporized and create clear liquids called naphthas. Dry, cleaning fluids can be made from these liquids, as well as paint solvents and other quick-drying products. The chains from C7H16 through C11H24 are blended together and used for gasoline. All of them vaporize at temperatures below the boiling point of water. That’s why if you spill gasoline on the ground it evaporates very quickly. Next is kerosene, in the C12 to C15 range, followed by diesel fuel C16 – C18 and heavier fuel oils (like heating oil for houses). Next come the lubricating oils. These oils no longer vaporize in any way at standard temperatures. For example, engine oil can run all day at 250 degrees F (121 degrees C) without vaporizing at all. Oils go from various viscosity from motor oil which is able to pass through the very high gear oils and then semi-solid greases. Vaseline falls in there as well. Chains above the C20 range form solids, starting with paraffin wax, then tar and finally asphaltic bitumen, which used to make asphalt roads. All of these different substances come from crude oil. The main difference is the length of the carbon chains.

What is Octane?
Almost all cars use four-­stroke gasoline engines. One of the strokes is the compression stroke, where the engine compresses a cylinder-full of air and gas into a much smaller volume before igniting it with a spark plug. The amount of compression is called the compression ratio of the engine. A typical engine might have a compression ratio of 8-to-1. The octane rating of gasoline tells you how much the fuel can be compressed before it spontaneously ignites. When gas ignites by compression rather than because of the spark from the spark plug, it causes knocking in the engine. Knocking can damage an engine, so it is not something you want to have happening. Lower-octane gas (like “regular” 87-octane gasoline) can handle the least amount of compression before igniting. The compression ratio of your engine determines the octane rating of the gas you must use in the car. One way to increase the horsepower of an engine is to increase its compression ratio and the displacement of the engine. So a “high-performance engine” has a higher compression ratio and requires higher-octane fuel. The advantage of a high compression ratio is that it gives your engine a higher horsepower rating for a given engine weight, that is what makes the engine “high performance”, which means the engine is more efficient. The disadvantage is that the higher octane gasoline for your engine costs more. The name “octane” comes from when you take crude oil and “crack” it in a refinery, you end up getting hydrocarbon chains of different lengths. These different chain lengths can then be separated from each other and blended to form different fuels. For example, methane, propane and butane are all hydrocarbons. Methane has a single carbon atom. Propane has three carbon atoms chained together, etc. It turns out that heptane handles compression very poorly. Compress it just a little and it ignites spontaneously. Octane handles compression very well, you can compress it a lot and nothing happens. 87 octane gasoline is gasoline that contains 87-percent octane and 13-percent heptane (or some other combination of fuels that has the same performance of the 87/13 combination of octane/heptane). It spontaneously ignites at a given compression level, and can only be used in engines that do not exceed that compression ratio.
Table 1: Grades of fuel

Grade

Octane

% Ethanol

Carbon chain range

Density g/ml

Standard

87

10

C7H16 – C11H24

0.73

Advanced

89

5

C7H16 – C11H24

0.73

Premium

91

0

C7H16 – C11H24

0.73

Diesel

12

0

C16H34 – C18H38

0.84

Question: Is there value in buying higher grade fuel? Comparison of fuel grades using ∆H?
Hypothesis: Premium gas which has a higher octane rating will be more efficient than standard gas. Premium gas contains less ethanol, which has short chains, so has more longer chains which release more energy. 
Independent variable: Grades of fuel, Standard, Advanced, Premium ,and Diesel
Dependent variable: Temperature change
Other measured: Mass of fuel burned
Sample collections and plus transport:
Materials:

1 jerry can

Collection of fuel from gas station:
Method:
–          Clean and dry jerry can, starting from
–          Collect samples of fuel from gas stations
–          Transport to lab
–          Approximately measure 150ml of each fuel into a clean beaker.
Experiment
Materials:
●       Thermometer
●       Thermometer clamp
●       Stand
●       Spirit burner with wicks
●       Glass erlenmeyer flask
●       200ml Water
●       Clamp
●       Funnel
●       Lighter
●       Timer
●       Graduated cylinder
Method:

Pour approximately 150 ml of gasoline in a clean dry 250ml beaker.
Place ‘50 ml’ of fuel into clean, dry spirit burner in fume hood.
Weigh the filled fuel burner.
Measure and 200 cm3 of water into beaker.
Clamp beaker 15 cm above level ground.
Place thermometer in thermometer clamp.
Place thermometer in beaker and record initial temperature.
Place spirit burner under beaker plus light wick.
After 5 minutes record final temperature and extinguish flame.
Reweigh spirit burner.
Record data in table.
Repeat step 2-11, 9 more times with fuel sample.
Clean and dry spirit burner, let wick dry out.
Repeat steps 1-13 for other fuel samples.

Experimental results
Table 2: Experimental results and differences of mass and temperature

Grade of Fuel and trial number

Initial fuel mass(g)± 0.01

Final fuel mass(g)± 0.01

Initial temp(°C)
±0.5

Final temp(°C)
±0.5

Difference of mass (g)±0.02

Difference of temp (°C)±1

Standard #1

187.21

181.27

21

97

5.94

76

Standard #2

187.18

183.51

22

98

3.67

76

Standard #3

187.42

182.26

22

99

5.16

77

Standard #4

187.23

180.94

19

99

6.29

80

Standard #5

186.68

180.02

20

98

6.66

78

Standard #6

186.76

180.76

21

93

6

72

Standard #7

186.24

180.59

20

92

5.65

72

Standard #8

186.11

180.14

20

97

5.97

77

Standard #9

186.57

179.88

21

97

6.69

76

Standard #10

186.58

180.62

16

90

5.96

74

Advanced #1

184.62

179.7

25

88

4.92

63

Advanced #2

185.49

180.38

18

85

5.11

67

Advanced #3

184.58

178.6

18

87

5.98

69

Advanced #4

184.94

179.52

19

86

5.42

67

Advanced #5

185.29

180.23

17

88

5.06

71

Advanced #6

184.97

179.97

20

88

5

68

Advanced #7

185.37

180.9

20

88

4.47

68

Advanced #8

185.1

180.27

18

87

4.83

69

Advanced #9

185.01

180.1

18

88

4.91

70

Advanced #10

184.07

179.24

19

89

4.83

70

Premium #1

184.98

178.92

18

66

6.06

48

Premium #2

185.57

178.34

19

70

7.23

51

Premium #3

185.26

178.62

17

65

6.64

48

Premium #4

185.57

179.58

20

67

5.99

47

Premium #5

185.35

179.86

18

74

5.49

56

Premium #6

184.82

179.27

19

72

5.55

53

Premium #7

184.87

179.57

12

57

5.3

45

Premium #8

184.07

180.05

15

67

4.02

52

Premium #9

184.38

179.99

15

69

4.39

54

Premium #10

185.02

180.32

16

66

4.7

50

Diesel #1

192.85

187.67

21

54

5.18

33

Diesel #2

193.27

185.89

20

53

7.38

33

Diesel #3

192.92

186.25

22

57

6.67

35

Diesel #4

192.76

185.76

19

52

7

33

Diesel #5

193.17

185.99

18

49

7.18

31

Diesel #6

193.02

187.82

16

46

5.2

30

Diesel #7

193.32

187.52

19

51

5.8

32

Diesel #8

192.76

185.81

20

52

6.95

32

Diesel #9

192.98

186.99

22

60

5.99

38

Diesel #10

192.87

186.02

21

57

6.85

36

Analysis
To calculate q, we use q = M*c(constant)*∆T. Calculating heat change, q= the mass of water, 200 g, multiplied by the specific heat capacity of water multiplied by the change in temp. Then we calculate the heat change per 1 L .Finally we Average and % error for ∆H.
Calculating heat change in KJ
q =     m               c               ∆T
   = (200g)(4.18 J g-1 °C-1)(76°C)   
   = 90288 J / 1000
   = 90.288
Calculating heat change per litre
D = m/v  =>  v = m/D
            Standard #1    Density For gasoline             Diesel #1    Density for diesel
For gasoline: v =  5.94 g      /     0.73 g/mol                For Diesel:     5.18 g     /     0.84g/mol
Average Calculation
Add all V from above for each fuel and divide by 10, since there are 10 samples
(11096 + 11096 + 11242 + 11680+ 11388 + 10512 + 10512 + 11242 + 11096 + 10804) / 10 =11066.8 which is average heat change per liter.
Minimum calculation
Subtract average heat change by heat change of trial to get a positive or negative
11066.8 – 10512 = 554.8
Find largest negative number to get minimum calculation

Standard #6

6

72

86

8.2

10512

-554.8

Table 3: Calculation of heat change and heat change per Litre:

Grade of Fuel and trial number

Difference of mass (g)±0.02

Difference of temp (°C)±1

Heat Change(q) KJ

Change in Volume mL

heat change per L KJ/L

Standard #1

5.94

76

90

8.1

11096

Standard #2

3.67

76

56

5.0

11096

Standard #3

5.16

77

79

7.1

11242

Standard #4

6.29

80

101

8.6

11680

Standard #5

6.66

78

104

9.1

11388

Standard #6

6

72

86

8.2

10512

Standard #7

5.65

72

81

7.7

10512

Standard #8

5.97

77

92

8.2

11242

Standard #9

6.69

76

102

9.2

11096

Standard #10

5.96

74

88

8.2

10804

Advanced #1

4.92

63

62

6.7

9198

Advanced #2

5.11

67

68

7.0

9782

Advanced #3

5.98

69

83

8.2

10074

Advanced #4

5.42

67

73

7.4

9782

Advanced #5

5.06

71

72

6.9

10366

Advanced #6

5

68

68

6.8

9928

Advanced #7

4.47

68

61

6.1

9928

Advanced #8

4.83

69

67

6.6

10074

Advanced #9

4.91

70

69

6.7

10220

Advanced #10

4.83

70

68

6.6

10220

Premium #1

6.06

48

58

8.3

7008

Premium #2

7.23

51

74

9.9

7446

Premium #3

6.64

48

64

9.1

7008

Premium #4

5.99

47

56

8.2

6862

Premium #5

5.49

56

61

7.5

8176

Premium #6

5.55

53

59

7.6

7738

Premium #7

5.3

45

48

7.3

6570

Premium #8

4.02

52

42

5.5

7592

Premium #9

4.39

54

47

6.0

7884

Premium #10

4.7

50

47

6.4

7300

Diesel #1

5.18

33

34

6.2

5544

Diesel #2

7.38

33

49

8.8

5544

Diesel #3

6.67

35

47

7.9

5880

Diesel #4

7

33

46

8.3

5544

Diesel #5

7.18

31

45

8.5

5208

Diesel #6

5.2

30

31

6.2

5040

Diesel #7

5.8

32

37

6.9

5376

Diesel #8

6.95

32

44

8.3

5376

Diesel #9

5.99

38

46

7.1

6384

Diesel #10

6.85

36

49

8.2

6048

Graph 1: Average heat change per litre of 4 different grades of fuel:
 

Table 4: Average change of heat per Litre and maximum and minimum values

Grade of Fuel

Average heat change per litre

Max heat change per Litre

Min heat change per Litre

Standard

11066.8

11680

10512

Advanced

9957.2

10366

9198

Premium

7358.4

8176

6570

Diesel

5594.4

6384

5040

 
Conclusion
Premium gas which has a higher octane rating will be more efficient than standard gas. Premium gas contains less ethanol, which has short chains, so has more longer chains which release more energy. This hypothesis is incorrect since the efficiency of an engine is not measured by the fuel used. There are many other factors that make a engine run efficiently instead of the fuel, such as compression ratio, displacement, speed of engine size of cylinder and many other factors. The experimental data shows that the highest energy change per litre occurs in standard fuel and there is a downward trend towards diesel. This is clearly shown in graph 1. The amount of ethanol in the fuels may be affecting the comparison of each grade of fuel. It’s possible to calculate the energy coming from ethanol and then compare the grades of fuel based on their octane rating. This was not what was expected as premium gas was expected to be the most efficient since it has the highest amount of longer carbon chains. The graph represents a linear slope which is within the errors, so this graph shows my accuracy and precision with the lab.
As i proceed the lab i learned that the fume hood was causing my flame to become unstable and shift at random. This is a big error since the flame did not constantly heat up the erlenmeyer flask through the allotted time. Another source of error could be the wick, since it had to be left soaking the fuel to be fully absorbed into the fibers to allow proper combustion to occur. The 50 ml of fuel was then poured into the spirit burner to after the wick was fully soaked to make sure there was no extra fuel being soaked by the wick. Furthermore, if deionized water was used in this experiment the sources of error could be further reduced since the chances of impurities in the deionized water would be very low. Also, I would use my time more efficiently by preparing the next set of trials as the experiment was taking place since 5 minutes of standing around and doing nothing would be a waste of time, when i could be filling up my beaker with water to carry out my next results. If i was given the chance to carry out my experiment one again I would make some minor adjustments, for example, i would use  erlenmeyer flasks instead of one, since it took a long time to clean and fill up. I could quickly switch the heated erlimyer flask for the fresh one to carry out the rest of my experiment and before i walk away to clean the used flask i would start my next trial.
References

https://www.ocean.washington.edu/courses/envir215/energynumbers.pdf
https://www.quora.com/How-much-energy-is-released-by-burning-1-litre-of-petrol
https://iet.jrc.ec.europa.eu/about-jec/sites/iet.jrc.ec.europa.eu.about-jec/files/documents/report_2014/wtt_appendix_1_v4a.pdf
https://www.rapidtables.com/convert/energy/Joule_to_Calorie.html
https://auto.howstuffworks.com/fuel-efficiency/fuel-consumption/gas-price.htm
https://www.bobistheoilguy.com/forums/ubbthreads.php?ubb=showflat&Number=272881
https://afdc.energy.gov/fuels/fuel_comparison_chart.pdf
http://chemed.chem.purdue.edu/genchem/topicreview/bp/1organic/coal.html
https://www.pacelabs.com/environmental-services/energy-services-forensics/forensics-101-a-primer/identifying-hydrocarbons.html