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TRANSCRIPT
Physics Session
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International Scientific Conference eRA-6
Physics Session
Low temperature extraction of essential oil bearing plants by liquificate gases: Fruits from sweet fennel (Foeniculum officinale Mill.)
Tanya Girova1, Velizar Gochev1, Ivanka Stoilova2, Krasimira Dobreva3,
Neno Nenov4, Veselin Stanchev5, Albena Stoyanova 6
1“Department “Biochemistry and microbiology”, Paisii Hilendarski” University of Plovdiv,
24 Tzar Asen str., Plovdiv 4000, Bulgaria, [email protected]
2Department of Biotechnology, University of Food Technologies,
26 Maritza Blvd, 4002 Plovdiv, Bulgaria, [email protected]
3 Subsidiary of the University of Stara Zagora, 38 Graf Ignatiev str., 8600 Yambol, Bulgaria,
4Department of Heating Technology, University of Food Technologies,
26 Maritza Blvd, 4002 Plovdiv, Bulgaria, [email protected]
5Department of Automatic, informatics and managing engineering, University of Food Technologies, , 26 Maritza Blvd, 4002 Plovdiv, Bulgaria, [email protected]
6Department of Essential Oils, University of Food Technologies,
26 Maritza Blvd, 4002 Plovdiv, Bulgaria, [email protected]
Abstract
The chemical composition of extract from the fruits of sweet fennel (Foeniculum officinale Mill.) by extraction with C2H2F4 (1,1,1,2-tetrafluorethane) was analyzed using GC and GC/MS. The main compounds (concentration higher than 3 %) of extract were: anethole (68.3) and fenchone (17.7).The studied extract demonstrated antimicrobial activity against Gram-positive and Gram-negative bacteria. The extract has antioxidant activity against DPPH radical.
Keywords: fennel, 1,1,2-tetrafluorethane, composition, antimicrobial and antioxidant activities.
1. Introduction
Fennel (Foeniculum officinale All. = F. vulgare Mill. = F. capillaceum Gilib), family Apiaceae, originates from the Mediterranean and is cultivated in all countries temperate climate.There are two varieties - sweet (var. dulce (Mill) Thell.) and bitter (var. vulgare (Mill) Thell), which differs in morphological features, content and composition of essential oil [3].
In Bulgaria, both varieties are processed. Obtained essential oil (3 to 6%) is used in food industry, and to isolate the main component - anethole [4].
Various biological and technological factors influence on the quantity of essential oil content and its main component: stage of harvesting [10], duration of storage [8], processed part of the plant [10], digest the fruit [11], processing by steam distillation [7] and extraction [7, 9].
According to Ehlers et al. [7], extraction is more suitable for processing because the extract contains less toxic cis-anethole and p-anisaldehid and content of trans-anethole is the same.
Simandi et al. [17] monitored changes in the composition of oil derived from processing of fruit in four ways - steam distillation, extraction with hexane, ethyl alcohol and CO2. The authors obtained the lowest yield of oil in the steam distillation, the highest in the alcohol extraction and the extraction with hexane and CO2 yields were close. Anethole level is lowest in the steam distillation, and the highest in CO2.
In Bulgaria, sweet fennel fruit is mainly processed by steam distillation [4]. There are studies for their extraction by liquid CO2 in the following technological parameters: temperature 18-22 OC, pressure from 4.8 to 5.4 MPa and duration 270 min. The yield of extract is 1.4%, the main components are: anethole (72.3%), fenchone (11,3%) and estragole (4.3%) [5]. The extract occurs more marked antimicrobial activity against tested Gram-positive bacteria than Gram-negative bacteria and yeasts [6].
Perspective liquid gas, allowed to obtain extracts for application in food industry, is C2H2F4 (1,1,1,2-tetrafluorethane).
The aim of the present work was to obtain freon extract from fruits of sweet fennel and to determine its antioxidant and antimicrobial activity.
2. Exposition
2.1. Materials and Methods
· Plant material.
The used fruits from sweet fennel (Foeniculum officinale Mill.), harvest 2009 and humidity 7% [16] were purchased from trade market.
· Obtaining of extract.
The air-fruits of sweet fennel were ground separately in an attrition mill to a size of 0.15 – 0.25 mm and the extract obtained by a 1 dm3 volume C2H2F4 (1,1,1,2-tetrafluorethane) laboratory-extractor [14] under following conditions (continuous flow and evaporation of solvent): pressure 0,5 MPa; temperature 18 - 20 ОС and time 60 min.
The physico-chemical properties were measured according to Russian Pharmacopoeia [16].
· Determination of chemical composition.
GC analysis was performed using an Agilent 7890A gas chromatograph equipped with FID detector and HP-INNOWax Polyethylene Glycol column (60 m x 0,25 mm; film thickness 0,25 (m); temperature: 70 О - 10 min, 70 - 240 ОC - 5 ОC/min, 240 ОC – 5 min; 240 - 250 ОC - 10 ОC/min, 250 ОC – 15 min; carrier gas helium, 1 ml/min constant flow; injector split, 250 ОC, split ratio 50:1.
Gas Chromatography-Mass Spectrometry Analysis: GC/MS analysis was carried out on an Agilent 5975C gas chromatograph, carrier gas helium, column and temperature as for GC analysis, FID, 280 ОC, MSD, 280 ОC, transfer line.
· Determination of antimicrobial activity.
Antimicrobial activity of fennel extract was determined against pathogenic and spoilage bacteria and yeasts from clinical and food isolates and also against reference strains. The used test microorganisms and their origins are listed in Table 2. The strains are deposited in the microbial culture collection of Department “Biochemistry and microbiology”, “Paisii Hilendarski” University of Plovdiv, Bulgaria. Minimal Inhibitory Concentration (MIC) and Minimal Bactericidal Concentration (MBC) of fennel extract were determined by serial broth dilution method in accordance with CLIS (ex NCCLS) [13]. A stock solution to be tested was prepared by diluting the respective fennel extract sample in DMSO (Sigma-Aldrich Co.). Antimicrobial activity of the extract was determined in concentrations ranging from 0.00025 to 1.6 %.
· Scavenging effect on 2,2-diphenyl-1-picrylhydrazyl radical (DPPH).
The radical scavenging capacity was determined according to the method described by Mensor et al. [12]. 1.0 ml from 0.3 mM alcohol solution of DDPH was added to 2.5 ml from the samples with different concentration of fennel extract. The samples were kept at room temperature in the dark and after 30 min the optic density was measured at 518 nm. The optic density of the samples, the control and the empty samples were measured in comparison with ethanol.
The IC50 value represented the concentration of the compounds that caused 50 % inhibition of radical formation.
All experiments were done in triplicate and the results were statistically evaluated using a level of confidence γ = 0.95.
2.2. Results and discussion
The produced fennel extract was green liquid with strong characteristic for the raw material aroma, which freezes at 4 0C. The yield extract was 3.8 % (v/w).
The physico-chemical properties are follows: dry substance (105 OC): 8.8%, refractive index (20 OC): 1.5249, specific gravity (20 OC): 0,9743, acid number: 3.9.
The yield and the physical-chemical properties of the studied fennel extract are comparable with the yield and the properties of fennel essential oil [4].
The chemical composition of the extract is presented in Table 1.
№
Components
RI
%
1.
Anethole
1269
68.3
2.
Fenchone
1090
17.7
3.
Estragole
1183
2.8
4.
(-Pinene
939
2.5
5.
Limonene
1026
1.9
6.
Мyrcene
990
1.2
7.
(-Terpinene
1059
0.7
8.
Camphor
1132
0.5
9.
(- Phellanderne
1031
0.5
10
(-Phellanderne
1000
0.4
11.
Camphene
940
0.3
12.
(-Pinene
981
0.2
13.
Sabinene
973
0.2
14.
(-Terpinolene
1077
0.1
15.
Menthone
1154
0.1
16.
Sabinene hydrate
1054
0.1
17.
p-Anisaldehyde
1252
0.1
18.
p-Cymene
1020
0.1
Table 1: Chemical composition of fennel extract.
As seen 18 components representing 97.7% of the total content were identified. Six of them were in concentrations over 1 % and the rest 12 constituents were in concentrations under 1%. The major constituents (over 3 %) were anethole (68.3%) and fenchone (17.7%). Estragole (2.8%), (-pinene (2.5%), limonene (1.9%) and myrcene (1.2%) were at concentrations over 1 %. According to the content of major constituents the produced freon extract of fennel fruits was similar to the published in literature [7, 9]. As regards to the rest of the constituents the qualitative differences are due to the type of the used solvent and the process parameters.
The classification of the identified compounds, based on functional groups, is summarized on Figure 1. The total phenyl propanoids constituted the highest percentage among the components of the extract (73.0%). The extract included also oxygenated monoterpenes (18.8%), monoterpenes (7.3%) and sesquiterpenes (0.9%).
1
2
3
4
Figure 1: Group of components in the fennel extract, %.
1 - phenyl propanoids, 2 - oxygenated monoterpenes, 3 – monoterpenes, 4 – sesquiterpenes
The results of antimicrobial testing are presented in Table 2. As seen the fennel extract demonstrated equal antimicrobial activity against Gram-positive and Gram-negative bacteria, belonging to species S. epidermidis, S. aureus, E. coli, S. abony and the both strains of yeasts belonging to species C. albicans. The extract was inactive against both strains of P. aeruginosa, which belong to the group of the most resistible bacterial strains. The ability of P. aeruginosa to grow in a form of biofilm and the production of extracellular polysaccharide increased antimicrobial resistance of these bacteria mainly through permeability barrier. These strains also produced two types of soluble pigments, pyoverdin and pyocyanin, which probably participate in cell defence against antimicrobials.
№
Test microorganisms
Origin
MIC,% (w/v)
MBC,% (w/v)
1
Staphylococcus epidermidis
Clinical isolate
0.8
0.8
2
Staphylococcus aureus
ATCC 6538
0.8
0.8
3
Escherichia coli
Food isolate
0.8
0.8
4
Escherichia coli
ATCC 8739
0.8
0.8
5
Salmonella abony
Clinical isolate
0.8
0.8
6
Salmonella abony
ATCC 6017
0.8
0.8
7
Pseudomonas aeruginosa
Food isolate
inactive
8
Pseudomonas aeruginosa
ATCC 9627
inactive
9
Candida albicans
Clinical isolate
0.8
0.8
10
Candida albicans
ATCC 10231
0.8
0.8
Тable 2: Аntimicrobial activity of fennel extract.
The results of antioxidant testing of fennel extract are presented in Figure 2. As seen 78.9% inhibition of DPPH radical was reached at concentration 10 mg/ml and the IC50 value was 6.03 mg/ml (correlation coefficient R2 = 0.998). In comparison with strong antioxidants such as ascorbic acid (4.20 (g/cm3), rutin (14.65 (g/cm3), BHT (1.12 (g/cm3) and BHA (4.41 (g/cm3) [1], which are traditionally used in cosmetics and food industry, the produced fennel extract possessed considerably lower antioxidant activity. In comparison with other extracts produced by low temperature extraction with 1,1,1,2-tetrafluorethane, the fennel extract demonstrated near antioxidant activity with the extract from anise fruits (IC50 е 8.32 mg/ml), the main compound - anethole [1], higer antioxidant activity with the extract from coriander fruits (IC50 е 17.74 mg/ml), the main compound - linalool [2] and lower antioxidant activity with the extract from cinnamon barks (IC50 0.38 mg/ml), the main compound - cinnamal [15].
0
10
20
30
40
50
60
70
80
90
146810
Concentration, mg/ml
Inhibition,%
Figure 2: Effect of the fennel extract in the DPPH assay.
3. Conclusion
The aroma product with characteristic odour and taste and higher content of anethole (68.3%) was produced through low temperature extraction of fruits of sweet fennel (Foeniculum officinale Mill.) with 1,1,1,2-tetrafluoroethane. The produced extract demonstrated antimicrobial activity against some of the most widely spread pathogenic and spoilage bacteria and yeasts and higher antioxidant activity in comparison with other extracts produced by low temperature extraction. Currently the experiments for application of the produced fennel extract in cosmetic and food products are in progress.
References
1. Atanasova T., „Technological investigation for obtaining of the essential and vegetable oil from fruits of anise (Pimpinella anisum L.).” PhD, University of Food Technologies, Plovdiv, 2007.
2. Atanasova T., T. Girova, V. Gochev, I. Stoilova, N. Nenov, M. Stoyanova, A. Stoyanova, “Low temperature extraction of essential oil bearing plants by liquificate gases. 5. Fruits from coriander (Coriandrum sativum L.)”, Scientific Works of University of Food Technologies, vol. 57, no. 1, pp.363–368, 2010.
3. Bauer K., D. Garbe, H. Surburg, „Common fragrance and flavor materials”, 3rd Ed., VCH, Weinheim, 1997.
4. Georgiev E., A. Stoyanova, “A guide for the specialist in aromatic industry”, Plovdiv, 2006.
5. Damianova S., A. Stoyanova, A. Konakchiev, I. Djurdjev, “Supercritical carbon dioxide extracts of spices. 2. Fennel (Foeniculum vulgare Mill. var. dulce Mill.)”. Journal of Essential Oil Bearing Plants. vol. 7, no.3, pp.247-249, 2004.
6. Damianova S., A. Stoyanova, “Antimicrobial activity of aromatic products. 14. Extracts from fruits of sweet fennel (Foeniculum vulgare Mill. var. dulce Mill.) and coriander (Coriandrum sativum L.)”. Journal of Essential Oil Bearing Plants, vol.10, no.5, pp.440– 445, 2007.
7. Ehlers D., J. Faerber, A. Martin, K. Quirin, D. Gerard, “Analysis of essential fennel-comparison of CO2 extracts and steam distillation”, Deutsche Lebensmittel-Rundschau, vol. 96, pp.330, 2000.
8. Fehr D., „Untersuchungen zur lagerstabilitat von Anis, Fennel und Kummel“, Pharmazeutische Zeitung, vol. 125, no.27, pp.1300-1303, 1980.
9. Lawrence В., “Progress in essential oils”, Perfumer & Flavorist Journal, vol. 27, no.5, pp.74–79, 2002.
10. Lawrence В., “Progress in essential oils”, Perfumer & Flavorist Journal, vol. 28, no.2, pp.57–62; no.4, pp. 90–101, 2003.
11. Marotti M., R. Piccaglia, “The influence of distillation conditions on the essential oil composition of three varieties of Foeniculum vulgare Mill.”, Journal of Essential Oil Research, vol. 4, no.4, pp.569–576, 1992.
12. Mensor L., F. Menezes, G. Leitao, „Screening of Brazilian plant extracts for antioxidant activity by the use of DPPH free radical method”, Phytotherapie, vol.15, pp.127-130, 2001.
13. National Committee Clinical Laboratory Standards, “Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically”, Approved Standard, NCCLS Publication M7-A2, Villanova, PA, USA, 1990.
14. Nenov N.,. “Low temperature extraction of essential oil bearing plants by liquificate gases. 1. Laboratory installation”, Scientific Works of University of Food Technologies, vol. 53, no.2, pp.195–200, 2006.
15. Nenov N., V. Gochev, T. Girova, I. Stoilova, T. Atanasova, V. Stanchev, A. Stoyanova,. “Low temperature extraction of essential oil bearing plants by liquificate gases. 6. Bark from cinnamon (Cinnamomum zeylanicum Nees)”, Journal of Essential Oil Bearing Plants, vol. 14, no.1,pp.67–75, 2011.
16. Russian Pharmacopoeia, Moscow, 1990.
17. Simandi B., D. Andras, T. Veress, E. Lemberkovics, M. Then, A. Sass-Kiss, Z. Vamos-Falusi, “Supercritical carbon dioxide extraction and fractionation of fennel oil”, Journal of Agricultural and Food Chemistry, vol. 47, pp.1635–1640, 1999.
3. Development of a Computer-based Educational Laboratory Experiment for Teaching the Fundamentals of Photovoltaic Cells
Zachariadou K., Yiasemides K., Trougkakos N., Prezerakos G.,
Technological Educational Institute of Piraeus, P. Ralli & Thivon 250, 12244, EGALEO, Greece
*e-mail: [email protected]
Abstract
Photovoltaic technology provides an attractive tool for teaching fundamental concepts of physics while keeping students informed in current engineering trends as well as promoting renewable energy technologies. For this purpose, a fully computer-based laboratory experiment is under development, aimed to be used to undergraduate courses concerned with electrical engineering and physics.
The system’s monitoring and data acquisition is implemented on an open source electronics prototyping platform whereas the user-interface is developed in C++ and C# programming languages by combining a commercial software design environment with an object-oriented framework for data analysis.
Observation results on the current versus voltage and power versus voltage curves, on the conversion efficiency as well as on the maximum power output of a photovoltaic module are presented.
Expanding the actual system to exploit the dependence of the cell’s current versus voltage characteristic curve on the tilting angle has been developed by using a computer-controlled motor.
Furthermore, a simulator demonstrating the performance of a photovoltaic module under various temperature conditions is incorporated into the system.
1. Introduction
During the last few decades, photovoltaic technology is growing in popularity all over the world as the manufacturing cost decreases while the world energy demands as well as the cost of conventional energy are rising.
By taking advantage of the attractiveness of the photovoltaic technology, the presented laboratory experiment aims to assist students in developing science process skills as well as learning fundamental concepts of physics. It will provide students with the necessary methodology and software tools that will enhance their critical thinking and will encourage them to perform the experimental observations which are adequate to give answers to their curiosity about the performance of a photovoltaic module. Specifically, students are expected to be familiarized with the concept of scientific inquiry of designing and run experimental observations, recording and afterwards interpreting and analyzing experimental data in order to draw scientific conclusions. Moreover, in this framework students will gain knowledge of the significance of the simulation procedure in the science process by validating a photovoltaic model with their experimental data and predicting its response by varying the parameters that affect its performance.
In parallel, through the experimental methodology applied in the particular subject of the designed lab, students should learn fundamental aspects of semiconductors and electricity. Specifically, they should a) explore the characteristics of the current versus
voltage and power versus voltage curves of a commercial photovoltaic module b) investigate the effect of load resistance on the power output of the module c) estimate the efficiency of conversion of light to electrical energy d) test the response of the photovoltaic module to different tilt angle, light intensity and temperature.
To accomplish the objectives described above, we have designed a low cost and fully computer based laboratory experiment. Its implementation is based on an open source electronics prototyping platform (Arduino [1]) whereas the control panel is developed in C++ and C# programming languages by combining a commercial software design environment (Microsoft Visual Studio [2]) with an open-source, object-oriented framework for large scale data analysis developed at CERN (ROOT [3]).
Presented in the following sections are the design and implementation of the laboratory experiment, experimental tests of the system’s performance in a test-bench as well as the performance of a simulator which describes the influence of the temperature on photovoltaic modules.
2. Design & Implementation of the Lab
Photovoltaic cells are semiconductor devices that produce DC current from light. Solar photovoltaic panels are created by connecting individual cells together. The DC power is converted to AC power with an inverter and can be used to power local loads. The most commonly known solar cell consists of a p-n junction fabricated in a thin wafer or layer of semiconductor. In the dark, the current versus voltage (I-V) output of the cell has an exponential characteristic similar to that of a diode. When light enters the cell, photons with energy greater than the band gap energy of the semiconductor create electron-hole pairs. These carriers are swept apart under the influence of the internal electric field of the p-n junction creating a current proportional to the incident radiation.
The simplest equivalent circuit of a solar cell is a current source in parallel with a diode. In practice no solar cell is ideal so a shunt resistance (
p
R
) and a series resistance (
s
R
) are also considered (Figure 1). In practice, photovoltaic panels are composed of several photovoltaic cells and the characteristic equation which mathematically describes the output current and voltage is given by equation [4]:
(
)
p
s
s
d
s
L
p
s
d
L
R
I
R
V
kTN
n
I
R
V
q
I
I
R
I
R
V
I
I
V
I
+
-
ú
û
ù
ê
ë
é
-
÷
÷
ø
ö
ç
ç
è
æ
+
×
-
=
+
-
-
=
1
exp
)
(
0
(1)
where:
L
I
is the photo-current generated by the panel,
d
I
is the diode current for the case of a panel consisting of
s
N
cells wired in series,
0
I
is the reverse saturation current of the panel,
C
q
19
10
6
.
1
-
´
=
is the electron charge,
K
J
k
23
10
38
.
1
-
´
=
is the Boltzmann’s constant, T is the absolute temperature,
d
n
is the diode ideality factor (
1
=
d
n
for an ideal diode),
s
R
is the equivalent series resistance of the array and
p
R
is the equivalent parallel resistance. In an ideal photovoltaic cell
0
=
s
R
whereas
p
R
is considered high enough so the last term of the characteristic equation can be neglected, which is a relatively common assumption.
For teaching the fundamentals of a photovoltaic module, the laboratory experiment described in this paper is built around the following components: a) a commercially available photovoltaic module, b) two bright light sources (LED), c) a digital potentiometer, d) a servo motor used to change the angle of the panel with respect to the light source, e) a digital temperature sensor, f) a light to frequency IC to control the light intensity g) an electronics prototyping platform (Arduino) for monitoring and data acquisition and h) a computer work station (in this case running on Windows XP operating system) used for the data acquisition and monitoring as well as the analysis of experimental data. The latter is equipped with the drivers and the software of the Arduino platform, the Microsoft Visual Studio design environment and the ROOT framework
The system’s schematic is shown in Figure 2. A DC wall adapter provides 12V 2A power to the circuit. This power is converted to 5.5V DC bus by an LM317T voltage regulator that will power the logic circuits and to a 6.6V 700mA bus that will power the two high brightness LEDs across the photovoltaic cell. The latter is accomplished by two Lm317T regulators; one configured as a voltage regulator and one as a constant current regulator and will be switched by a PWM controlled relay in order to change the intensity of the emitted light. A non-inverting amplifier connected to the positive terminal of the photovoltaic cell scales and feeds the voltage of the photovoltaic to the first Analogue to Digital converter of the Arduino while a current to voltage converter connected to the negative terminal scales and feeds the current
value to the second ADC. Connected to the cathode of the photovoltaic cell is also the High terminal and Wiper terminal of the Arduino controlled digital potentiometer (CAT5113) which will act as the load. An Arduino controlled servo motor tilts the PV thus changing the angle of incidence of the light that falls on the cell. The temperature and light intensity of the photovoltaic cell are measured by a digital temperature sensor (DS18B20) and a light intensity to frequency IC (TSL230R) and reported to the Arduino.
As it has been mentioned above, the user interface (Figure 3) is developed by combining the commercial software design environment Visual Studio and the open source, object oriented framework ROOT. Specifically, a graphical interface has been developed (in C# programming language by using Visual Studio) which runs in batch mode the ROOT C++ interpreter (CINT). In turn CINT executes scripts (developed in C++ programming language) that process and analyze the data and/or perform the simulations. Finally, the graphical output of the data analysis and/or simulation results is loaded as an image in the Visual Studio graphical interface.
The ROOT framework contains several alternatives designed for statistical data exploration, performing multi-dimensional histograms, curve fitting, reporting and simulation. Although ROOT is a framework that is specifically designed for large scale data analysis it is consider to be an appropriate solution even for smaller data sets because of its efficiency in storing and accessing subsets of data. For curve fitting ROOT provides several alternatives including least squares regression, method of maximum likelihood, neural networks, etc. In the framework of the actual laboratory, the algorithms have been developed to fit the data by using the maximum likelihood method.
The main operations available via the user interface are shown in Figure 3 and described in details in the following sections. Moreover, a panel in the user interface for controlling the simulation studies is under development.
3. Laboratory observations
A test-bench has been set up in order to test the performance of the designed laboratory. For exploiting the current versus voltage (I-V) and the power versus voltage (P-V) characteristic curves of the photovoltaic module, data have been acquired by adjusting the digital potentiometer. By using the ROOT framework, dedicated algorithms have been developed in C++ language that fit the I-V and P-V curves and return important parameters of the photovoltaic module such as the a) the maximum output voltage obtained when there is no load connected across the cell, defined as open circuit voltage
oc
V
and b) the maximum power produced by the cell, defined as the maximum power point (Figure 4)
Data are fitted by using equation (1) for the simplest case of an ideal diode (
0
=
s
R
and
®µ
p
R
). The input parameters of the fit are the photo-current generated by the panel (
L
I
), the number (
s
N
) of cells wired in series, the temperature (T) and the ideality factor (
d
n
). During the laboratory activity students should measure the temperature and estimate the number of cells, the photo-current (
L
I
) and the ideality factor (
d
n
) inputs by giving trial and errors values such that equation (1) fits to their experimental data.
The effect of the tilt angle on the photovoltaic module’s maximum power point has been tested. For this, the photovoltaic module has been slant at ~20-degree intervals away from the direct perpendicular position. An algorithm has been developed in C++ language by using the ROOT framework to fit the I-V curve for each orientation (Figure 5). During the laboratory activity students should notice that as the angle increases from perpendicular with respect to the light direction emitted by the led, the amount of light hitting the PV cells decreases, reducing the output electric current and power.
Furthermore, the maximum power point as a function of the tilt angle as well as the maximum efficiency versus the tilt angle has been estimated. The later is evaluated to be ~12% for the case of normal inclination.
4. Simulation Studies
0
2
''(1)(3)
b
netnet
net
N
N
ss
=+
As it has been emphasized above, the main objective of the designed laboratory experiment is to improve student’s attitude towards science by teaching them the process of how the scientific knowledge gathered in their books is built as well as how scientific research develops new knowledge. For this, it is important that students gain experience of the significance of the simulation procedure in a science process thus a simple simulator based on equation (1) has been developed in C++ by using the ROOT framework. During the laboratory activity students should first validate the simulator with their experimental data by varying the input parameters of the model (Figure 6) and subsequently predict the response of the photovoltaic module under different temperature conditions (Figure 7).
The most significant influence of the temperature in the current-voltage characteristic curve is via its effect on the diode’s current (in the exponential part of equation (1)) and via its effect on the reverse saturation current of the panel (I0). The latter is modeled mathematically by the following equation [6]:
(
)
(
)
(
)
÷
÷
ø
ö
ç
ç
è
æ
÷
÷
ø
ö
ç
ç
è
æ
-
×
×
÷
ø
ö
ç
è
æ
×
=
T
T
k
n
T
qE
T
T
T
I
T
I
n
d
n
g
n
n
n
1
1
exp
3
0
0
(2)
where
n
T
is the temperature at nominal condition (
K
T
n
298
=
),
g
E
is the band-gap energy of the semiconductor (
eV
E
g
12
.
1
=
for polycrystalline Si at 25◦ C [6]),
d
n
is the diode’s ideality factor and
(
)
×
n
T
I
0
is the reverse saturation current of the panel at nominal condition given by the formula:
(
)
(
)
(
)
1
exp
0
-
÷
÷
ø
ö
ç
ç
è
æ
×
=
T
kN
n
T
qV
T
I
T
I
s
d
n
oc
n
sc
n
(3)
In the above equation
(
)
n
sc
T
I
and
(
)
n
oc
T
V
is the short circuit current (the greatest value of the current produced by the photovoltaic cell when V=0) and the open-circuit voltage respectively at nominal condition. According to equations (1), (2), (3), the input parameters of the model are the temperature (T), the number of cells (
s
N
) the short circuit current at nominal condition (
(
)
n
sc
T
I
), the open circuit voltage at nominal condition (
(
)
n
oc
T
V
) and the diode’s ideality factor (
d
n
).
Furthermore, a simulator predicting the performance of a photovoltaic module consisting of various numbers of cells wired in series and in parallel is under development.
5. Summary
A low cost and fully computer based laboratory experiment has been developed aiming to assist students developing science process skills as well as learning fundamental aspects of semiconductors and electricity.
Its implementation is based on an open source electronics prototyping platform (Arduino) whereas the user interface is developed in C++ and C# programming languages by combining a commercial software design environment (Microsoft Visual Studio) with an open-source, object-oriented framework for data analysis (ROOT).
Presented in the current work are the design and implementation of the laboratory experiment, experimental tests of the system’s performance in a test-bench as well as tests of the performance of a simulator which describes the influence of the temperature on photovoltaic modules.
Furthermore, a simulator predicting the performance of a photovoltaic module consisting of different number of cells wired in series or in parallel is underway along with a dedicated panel in the user interface for control. Moreover, a panel that controls the LEDs brightness and provides tools for studying the influence of irradiance on performance of a photovoltaic module is under development.
6. References
1. Arduino, http://www.arduino.cc/
2. Microsoft Visual Studio, http://www.microsoft.com/visualstudio/en-us
HYPERLINK "http://root.cern.ch/" ROOT -A Data Analysis Framework, root.cern.ch/
3. S. Rauschenbach, Solar Cell Array Design Handbook. NewYork: Van Nostrand Reinhold, 1980.
4. Arduino Uno board http://arduino.cc/en/Main/ArduinoBoardUno
5. W. De Soto, S. A. Klein, andW. A. Beckman, “Improvement and validation of a model for photovoltaic array performance,” Solar Energy, vol. 80, no. 1, pp. 78–88, Jan. 2006.
4. Statistical uncertainty in educational experiment on the attenuation of gamma radiation
Mirofora Pilakouta
Department of Physics Chemistry and Material Technology, T.E.I. of Piraeus, Greece Tel: 2105381583 E-mail:[email protected]
Abtract
Due to time and financial restrictions in an educational laboratory, we are making compromises, using experimental setups in which limitations and uncertainties are important. In these cases we should pay particular attention to the role of different factors that affect our experiment, in order to achieve the best possible educational outcome and to avoid misconceptions.
In this paper problems related to the use of very low activity source 60Co in the experiment of measuring the linear attenuation coefficient of gamma rays through matter, will be presented. The role of background radiation in measurements and in the relative statistical uncertainty as well as the role of statistical uncertainty in the choice of representative measurements is discussed. Moreover students’ difficulties and misconceptions related mainly to the statistical uncertainty and its connection to measurements overlapping are recorded. An explanation for the possible reasons of these misunderstandings is attempted in order to improve the educational outcome in this experiment.
Keywords: γ- attenuation, statistical uncertainty, student’s misconceptions
1. Introduction
The experiment on the attenuation of gamma radiation is usually included in the most introductory physics courses.
A 60Co radioactive source is sited in front of a small detector (Geiger Muller tube) in an appropriate distance and plates of Pb (or other absorber) are inserted among them. The counting rate as a function of the thickness of the irradiated material is measured and the tasks are: to determine the half-value thickness X1/2 (the thickness at which the initial counting rate is reduced by half) the absorption coefficient μ of some materials and to calculate the mass attenuation coefficient from the measured values.
The attenuation of the gamma rays when they pass through an absorber of thickness x is expressed by the exponential law
N(x)=Nο e-μχ (1)
(where No: initial radiation intensity, x: the thickness of the material and μ: the linear absorption coefficient). The exponential law is valid under certain conditions i.e monoenergetic point source under narrow beam conditions and absence of background radiation [1].
Furthermore depending on the counting rate yielded by the experimental setup, an appropriate time period for each measurement should be selected in order to have statistically acceptable measurements.
Using experimental setups with low activity source (that commonly happens in an educational lab), the issues concerning background radiation and low statistic are particularly present. In this case the uncertainty of measurements has a very important influence in the design of the experiment. Due to the increased statistical fluctuations, we often get measurements that overlap. This seems to be very difficult for the students to understand. At least, they should have a good understanding in uncertainty of measurements, to understand the reason of the overlapping and the need to get the most representative measurements.
In an introductory physics lab, students are almost never engaged to the design of the experiment. So in practice they have only a theoretical view of the limitations of the experimental setup and the way these limitations affect the measurements uncertainty. Furthermore they rarely care about how uncertainty may vary during the experiment and how this affects the quality of their measurements.
Several authors have studied student’s difficulties and misconceptions about the nature and the uncertainty of experimental measurements [3-6]. Their findings show that although the students may successfully calculate mean values and standard deviations or fit data, they have very low understanding of the role of the uncertainty in their measurements and thus they show low ability to evaluate their measurements and form conclusions (4-6).
This paper is focused on the issues of background radiation and low statistics in the experiment on the attenuation of gamma radiation. The role of background radiation in measurements and in the relative statistical uncertainty as well as the role of statistical uncertainty in the choice of representative measurements (under time limitations) is discussed. Moreover (non major in Physics) student’s difficulties and misconceptions related mainly to the statistical uncertainty, and its connection to measurements overlapping are recorded. Finally, the first results of a revised instruction sheet that partly engages the students to the design of the experiment are discussed.
2. Theoretical approach
2.1 Limitations of the experimental setup
As mentioned above, in low statistic measurements the presence of background radiation is important. The common method to deal with this problem is to obtain firstly a value of the background level and then subtract it from each measurement. Due to the propagation of errors the background subtraction increases the statistical uncertainty of each measurement. Furthermore, as the experimentally recorded net counts Nnet, (Nnet is proportional to radiation intensity) decreases with the increase of the absorber thickness, the relative statistical uncertainty increases even more and leads frequently in the overlapping of successive measurements. Because of time and experimental setup restrictions we can have only a few numbers of measurements in the above experiment. Thus, a careful selection of the thickness of the absorber for each measurement is needed to get the most representative data. Otherwise, some of the few measurements may have a significant overlap and become meaningless.
To illustrate this situation, let examine the case we often have with our experimental setup in the Physics Laboratory of TEI Piraeus. The "counting rate" from our experimental setup, without any absorbent material, is about 84 counts/min and the background radiation is about 14 counts/min. Thus, we have about 70 counts/min net counting rate.
The time for each measurement is restricted to 4 minutes, so in the available time we can take only 7 measurements in this experiment: two background measurements, a reference measurement (without absorber plates) and four measurements with absorber plates of different thickness.
According to the source net count rate, in a four minute measurement, the initial measurement (Nnet) would be about 280 counts with a relative statistical uncertainty of about 6%. Increasing the thickness of the absorber, the combined statistical uncertainty (σ) may become comparable to the difference ΔΝ between successive measurements. In order to reduce the possibility of overlapping between two consecutive measurements, the change (ΔN) of the recorded number of counts should be at least twice the statistical uncertainty of the measurements.
Taking into account statistical reasons [1,2], more than 100 net counts are needed in all measurements. Thus the maximum absorber thickness is limited to such a value that the initial radiation intensity is reduced at least to 100 counts.
For this range of absorber thicknesses the uncertainty will vary from about 6 to 12%. Thus to get the most representative measurements we should increase the absorber thickness in our successive measurements nonlinearly in order for the measurements to be approximately equally-spaced in the range 280 and 100 counts and have less possibility to overlap.
2.2 The role of background radiation in the statistical uncertainty of measurements - Measurements overlapping
The contribution of the background radiation in the estimation of combined uncertainty [2] is given in the Appendix.
The relative statistical uncertainty of the net counts of a measurement as a function of the ratio Nb /No net and the reduction factor α of the initial radiation intensity is given by Eq. (4) in the Appendix.
For α=2, the initial intensity of the radiation is reduced by half and the corresponding relative statistical uncertainty becomes:
0
/2
'
4
1.4'(1)(2)
net
b
net
onet
N
N
ss
=+
Equation (2) indicates that the relative statistical uncertainty in this case, increases at least 1.4 times in comparison to the relative uncertainty of the measurement without absorber. In addition, the presence of background radiation causes further enlargment of the statistical uncertainty.The importance of background radiation in low statistic measurements is illustrated in Table 1.
Three cases with different number of initial counts Νs (Ns includes background) are presented. In each case the absolute σnet and relative σ'net statistical uncertainty for the initial measurement and σ' net/2 and σ net/2 respectively for a measurement with half the initial counts are listed. All the counts correspond to the same period of time, 4 minutes. The background radiation is considered Nb = 56 counts.
Ν
s
N
o net
σ'
neto
σ'
net
σ
net
N
o net
/ 2 σ'
net/2
σ
net/2
1000 944 0.03 0,03 32 472 0.05 24
500 444 0.05 0,05 24 222 0.08 18
350 294 0.06 0,07 20 147 0.11 16
Table 1: Absolute and relative statistical uncertainty for three cases with different number of initial counts.
In the first case we have Ns = 1000 counts and the range of possible values (with 68% confidence level) is 944 ± 32. This means that a decrease in intensity by 10% (which roughly corresponds to a thickness of 2 mm Pb using source Co) will give ΔN~ 95 > 2 σnet and the probability of overlapping of two successive measurements is negligible. However, in the region of No net / 2 , a 10 % intensity change is comparable to twice the σ net / 2.
In the second case with Ns = 500 counts, a 10% reduction of the initial net counts is comparable to 2 σnet. So we should use absorber with a suitable thickness to produce a reduction greater than 10% at the beginning. In the region of No net / 2, the change between two successive measurements must be at least 16% (Table 1)
The third case corresponds to the case referred in the previous subsection. Ns = 350 and in order to have 68% chance to get distinctness between two successive measurements, the initial absorber thickness should reduce roughly 14% the initial counts (~ 2.5 mm Pb) while in the region of No net / 2, the change must be at least 22% (~ 5 mm Pb). In this case an increasingly larger Δx is needed to measure substantial differences between two successive measurements.
In summary, in case there is sufficient count rate or if there is plenty of time to take many measurements, no particular problem will be noticed related to measurements overlapping during successive increase of the thickness x of the absorber. Under low count rate and limited time conditions we should take care to get the most representative measurements. Therefore in this case we should increase the absorber thickness between successive measurements nonlinearly and take into consideration the statistical uncertainty.
3. Educational approach
3.1 Student’s difficulties and misconceptions associated to measurements uncertainty and measurements overlapping
The measurements overlapping that appears frequently due to the limitations of the experimental setup, has revealed several difficulties and misconceptions related to the uncertainty and its significance in this experiment. Interviewing more than 40 students that faced problems during the acquisition of their data, we have recorded these difficulties and misconceptions but we have also recorded difficulty to link the uncertainty with the overlapping of measurements. Most of our observations are similar to the findings mentioned in educational studies related to students’ understanding of measurements [4-6]. In the following we present our observations accompanied with comments and the first results of a revised instruction sheet that partly engages students to the design of the experiment.
· Origin of the statistical uncertainty when measuring gamma radiation
The majority of students do not seem to realize the source of the uncertainty in a counting experiment such as the radiation measurement. They connect the uncertainty (“measurement error”) with the counter and not with the random nature of the emitted radiation. They view each reading of N counts as an exact value because it is taken by a digital counter.
This misconception is possibly related to their little experience with the statistical fluctuation of the nuclear radiation but also because many of them have difficulties to understand the existence of uncertainty in one measurement [5]. Some of them consider that the uncertainty of the counts recorded by the counter is similar to the uncertainty corresponding to the measuring of a length with a ruler (i.e consider as uncertainty the lowest division of the measuring instrument.
· Uncertainty calculation in gamma radiation experiment
More than 80% of the students fail to calculate correctly the statistical uncertainty (absolute and relative) because they underestimate or ignore the background radiation or they do not feel enough confident to use the combined uncertainty. Thus measuring Ns counts they find Nnet =Ns-Nb but estimate the uncertainty using
net
N
instead of using
22
netsb
NN
sss
=+
This may be related to the fact that background radiation is not enough underlined in the most introductory textbooks and that in theoretical problems related to the attenuation of radiation, most of the times the background radiation is ignored.
· The role of uncertainty in measurements interpretation
Almost all the students have difficulties to interpret their measurements using the uncertainty associated with them.
In this experiment, students consider as an expected result the decrease of the recorded counts after any increase of absorber thickness. They also expect to find clearly distinct measurements when increasing the absorber thickness. Moreover they consider that increasing the thickness by ΔΧ they should always get about the same difference ΔΝ in recorded counts. As mentioned above, increasing ΔΧ linearly, it is mostly probable for some of the measurements to overlap significantly (within the range ± σ).
Students become skeptical if the counter indicates about the same number of counts for two different absorber thicknesses, and they consider it as a conflicting result, if in two successive measurements, they find more counts in the measurement taken with the thicker absorber. For example, in an experiment with initial Nnet=290 counts, using 5 mm of Pb the counter recorded Nnet(5)=205 counts. Adding another 2 mm (thus total thickness 7 mm) the counter recorded Nnet(7)=212 counts. It appeared to be very hard for the students to understand that the above measurement is valid within the statistical uncertainty. When they face the above problem, they consider either that the counter is not working properly or that they have done something wrong and most of the times they repeat the measurement.
Actually students tend to compare measurements as point numbers without taking into account the range (± σ) of possible values within which the true value of the measurement lies. Thus they are not able to see the above example as a case of measurements overlapping.
In the preparatory physics lab, the students do not have the opportunity to clarify aspects like the sensitivity of the experimental setup. In most experiments the range and the step of measurements is determined by the teacher, or a large number of measurements is available so the students can analyze their data without any doubt or consideration about the quality of the measurements.
3.2 Extending the objectives of the experiment
In an attempt to improve our students’ understanding on the meaning of their measurements in this experiment, we expanded the objectives of the experiment. Apart of using the experimental technique to find the attenuation coefficient of some absorbers, the students are engaged partly to the design of the experiment to realize in practice the importance of measurement uncertainty.
In the above experiment, it’s possible to determine the uncertainty of the measurements at the beginning of the experimental process. All that is needed for this is the background and the source counting rate. Thus we inserted in the laboratory worksheet questions with which the students are guided to
· decide for the duration and the number of measurements
· discuss the main sources of uncertainty in their measurements
· discuss how they could reduce the uncertainty in this experiment
· preestimate the range of the uncertainty (using relation (2)) for some representative cases as indicated in Table 1 and use the results for the justification of their measurements or for deciding for the appropriate thickness of the absorber to be used to get the most distinct measurements.
The revised sheet accompanied with personal instructions was tested in 18 students (6 groups of 3 students) during the last semester. The first findings using this revised laboratory instruction sheet shows that at least half of the students show a better understanding of the experimental procedure and of their measurements and admit that the preestimation of the uncertainty helps them to understand better the outcome of the experiment.
4. Conclusion and outlook
In this paper issues related to the use of a low activity source in the experimental setup for measuring the linear attenuation coefficient of gamma rays through Pb, were presented. Students’ difficulties and misconceptions in this experiment indicates the need for further explanation and clarification of:
· the main sources of uncertainty in measurements and the combined uncertainty
· the significance of the uncertainty to the interpretation of the measurements and the experimental designing
Furthermore, effort should be taken to help students to develop a conceptual understanding of the uncertainty insisting not only to the mathematical calculations used to quantify uncertainty but also to the several ways with which uncertainty may influence the experiment evolution and the results.
The first findings of a revised instruction sheet that partly engages the students to the design of the experiment seem to be encouraging. The revised instruction sheet in combination to students interviewing will be used in the following semesters for a greater number of students as a step to achieve a better educational outcome from this experiment.
Appendix
· How the background radiation affects the relative statistical uncertainty of the measurements
Here
b
N
: are the counts due to background radiation and
b
Nb
N
s
=
their statistical uncertainty. The total number of counts is
s
N
and
s
Ns
N
s
=
their statistical uncertainty. The Nnet is the symbol for the net counts of a measurement
netsb
NNN
=-
and
net
s
their combined statistical uncertainty
22
2(1)
netsb
NNsbnetb
NNNN
sss
=+=+=+
Τhe relative statistical uncertainty of the net counts
'
net
s
is given by:
22
1
'(1)(1)(2)
net
net
bb
netnet
netnetnetnetnet
N
NN
N
NNNNN
s
s
==+=+
And setting
0
'
net
net
net
N
N
s
=
( the relative statistical uncertainty in the case of zero background) Eq. (2) becomes
Equation (3), shows how the background radiation affects the relative statistical uncertainty of the measurements.For
bnet
NN
<<
the ratio
b
net
N
N
is very small and approximately
0
''
netnet
ss
=
When the net recorded counts are low, the background radiation contributes substantially to the overall relative statistical uncertainty
(for example if
0.2
b
net
N
N
=
then
0
'1.18'
netnet
ss
=
)
· How is the relative statistical uncertainty changes due to the absorption of the radiation through matter
If
onet
N
are the net counts taken with no absorber present and
onet
N
a
the net counts taken with an absorber of thickness Χ1/α (that corresponds to attenuation of the initial intensity by a factor of α ), the corresponding relative statistical uncertainty
/
'
neta
s
is given by:
/
/0
'
2
'(1)(4)
net
a
neta
b
net
onet
onet
aN
a
N
N
a
s
ss
==+
Acknowledgements
The author would like to thank all the associates of the physics lab II for helpful discussions and especially Dr. Christos Dedes for his comments and suggestions for this manuscript.
References
1. Harald A. Enge, “Introduction to nuclear physics, p.191,235”, 9th Ed.(Addison- Wesley, 1979)
2. John R. Taylor, “An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements”, 2nd ed. (Univ. Science Books, 1997)
3. Rebecca Lippmann Kung, “Teaching the concepts of measurement: An example of a concept-based laboratory course”, Am.J.Phys. vol.78, no 8, pp.771-777, August 2005.
4. Marie-Genevieve Sere, Roger Journeaug, and Claudine Larcher. “Learning the statistical analysis of measurement errors”, Int. J. Sci. Educ.,vol 15 ,no 4, pp. 427-438, July 1993)
5. S. Allie, A. Buffler, B. Campbell, F. Lubben, D. Evangelinos, D. Psillos, and O. Valassiades “Teaching measurement in the introductory physics laboratory, ” Phys. Teach. Vol.41, pp.394-401, October 2003.
6. Trevor S. Volkwyn, Saalih Allie, Andy Buffler and Fred Lubben “Impact of a conventional introductory laboratory course on the understanding of measurement” Phys. Rev. S.T – Phys. Edu Res. Vol.4, no.1, pp.010108_1-10 ,May 2008.
5. TEI Piraeus students' knowledge on the beneficial applications of nuclear physics: Nuclear energy, radioactivity - consequences
Mirofora Pilakouta
Department of Physics Chemistry and Material Technology
T.E.I. of Piraeus, Greece
Tel: 2105381583 E-mail:[email protected]
Abstract
The recent nuclear accident in Japan revealed the confusion and the inadequate knowledge of the citizens about the issues of nuclear energy, nuclear applications, radioactivity and their consequences
In this work we present the first results of an ongoing study which aims to evaluate the knowledge and the views of Greek undergraduate students on the above issues. A web based survey was conducted and 131 students from TEI Piraeus answered a multiple choice questionnaire with questions of general interest on nuclear energy, nuclear applications, radioactivity and their consequences. The survey showed that students, like the general population, have a series of faulty views on general interest nuclear issues. Furthermore, the first results indicate that our educational system is not so effective as source of information on these issues in comparison to the media and internet
Keywords: student views, nuclear energy, radioactivity
1. Introduction
The recent nuclear disaster in Japan has increased the interest and the fears of general population in all over the world about nuclear issues, radiations in general and especially radioactivity, and their consequences in human health and the environment. There is a great number of issues that are related to nuclear physics and its applications and touch, political, economical and social aspects of our lives. So it is very important for the citizens to have an acceptable level of knowledge on these issues.
Several studies have been conducted in different countries [1-3], trying to evaluate the knowledge, perceptions and views of secondary school students about various nuclear issues. Other surveys focus to investigate the attitude of students [4] or general population [5] towards nuclear power and nuclear applications. The general conclusion is that there is poor understanding about these issues and it is underlined that the educational system, especially the secondary school, should give more attention to make the students (the future citizens) aware of nuclear issues [1-4].
The secondary school curricular in Greece contains some topics on nuclear physics but they are not always of first priority either for the teachers or for the majority of the students. Taking into account that secondary education is the last chance for the largest part of general population to achieve reliable information on these issues, we assume that most of the Greek undergraduate (non major in physics) students have more or less the same confusion on nuclear issues as the general population.
In this work we present results from a recent survey conducted at TEI Piraeus that evaluates the knowledge and views of TEI Piraeus students on some nuclear issues of general interest.
This is the first step of an ongoing research which aims
· To investigate the knowledge of Greek students on some nuclear application issues,
· To compare student’s knowledge to that of general population
· To propose ways to link the educational material with topics of current interest, in order to motivate students to explore these concepts in a more serious manner.
Using the advantage of the increased interest (due to Fukushima accident) on these issues, we used the survey as an extra tool to motivate students to participate in a seminar about the nuclear energy and the nuclear accidents. The seminar aimed to make the students aware of both, the useful applications of nuclear physics in our life and the harmful effects of radioactivity in health and environment.
2. Survey development and administration
Since our target population is students (engineers) that have a positive attitude towards internet, the survey was conducted using an online questionnaire. The questionnaire was created using a form in Google Docs and was posted for a week on the Internet accompanied by the announcement of the seminar (about Nuclear energy, accidents, radioactivity and consequences) that would take place in a week. An invitation for filling the questionnaire was posted on the forum of the automation department students. The questionnaire was also sent in a number of students by e-mail and to Secretariats of the STEF faculty of TEI Piraeus. Finally, students (from civil and mechanical engineering departments) who were exercising in the physics lab that week were also asked to fill optionally the questionnaire using a computer in the laboratory.
The questionnaire was filled by 131 students. Data were automatically collected in a spreadsheet (in Google Docs) and were analyzed after the completion of the survey.
A great number of questions could have been incorporated in this questionnaire. In this preliminary study the questionnaire was consisted of 10 multiple-choice questions. Eight of the questions were examining basic and attractive topics related to nuclear issues, based on commonly documented misconceptions [1-3]. The other two questions ask for the source of their information and their attitude towards the seminars of general interest in the TEI. The questions are given in Table 1.
QUESTIONNAIRE
QUESTION OPTIONS
Q1: Which of the following radiations
may produce genetic problems
a) Visible radiation
b) Ultraviolet radiation
c) Gamma rays
d) Mobile phone radiation
e) Don’t Know
Q2:The gamma rays are
electromagnetic waves emmited by
a) nuclei and have higher energy than
X-rays
b) atoms and have lower energy than
X-rays
c) Laser devices
d) Don’t Know
Q3:The ionizing radiation which
mainly contributes to the total
irradiation of humans during their
lives, comes from:
a) Nuclear Plants
b) Nuclear accidents
c) Medical tests
d) Natural Radioactivity
e) Don’t Know
Q4: How is energy produced in a
Nuclear plant?
a) Spontaneous disintegration of heavy
nuclei
b) The fusion nuclear reactions
c) The fission nuclear reactions
d) Don’t Know
Q5: Which European country covers
more than 70% of its energy needs
using nuclear energy?
a) Belarus
b) France
c) Germany
d) Great Britain
e) Don’t Know
Q6: Which is the pair of radioactive
elements of high concern that are
released in the environment during a
nuclear accident
a) Iodine and Uranium
b) Plutonium and Uranium
c) Cesium and Iodine
d) Don’t Know
Q7: How many deaths are directly
attributed to the nuclear accident
during the first three months after
Chernobyl disaster in 1986?
a) 5-50
b) 50-100
c) More than 1000
d) More than 100000
e) Don’t Know
Q8: Which is the most unknown
application of ionizing radiation for
you?
a) Medicine (diagnosis, treatment)
b) Sterilization of instruments used in
medicine or food products
c) Research-Industry applications
(radiography)
d) I Know all of them
e) I don’t know any of them
Table 1: Questions on general interest Nuclear Issues
3. Survey outcomes
In the following we discuss the result for every individual question and try to analyze the underlying reasons for some incorrect answers.
· Which of the following radiations may produce genetic problems?
A majority, 89 percent of the students, gave correct answer in this question (gamma rays), while 11 % seems not to understand the difference between ionizing and non ionizing radiation, which is a common misunderstanding for general population as well.
· Which is the origin and nature of gamma rays?
The majority of the students (71%) seem to know the origin and distinguish γ radiation from X-rays. However, a total of 21 % demonstrated confusion about the nature of gamma rays, when another 8% admit that they don’t know. It is notable that 8% of the students have the faulty conception that gamma rays can be produced by laser devices. This is probably related to the confusion about the term "radiation" which is used to describe several sources of radiation.
· Where does the ionizing radiation, which mainly contributes to the total irradiation of humans during their lives, come from?
Only one out of three (34%) of the students knows that the main contribution to human irradiation comes from natural radioactivity. The majority, 40%, believe that the main source of irradiation comes from medical examinations, 15% from nuclear plants or nuclear accidents and a minority 11% answers that they do not know.
The belief that the contribution of medical examinations is higher than the contribution of other sources is related to the general fear about medical examinations using ionizing radiation as well as to the fact that general population have poor knowledge about natural radioactivity.
· How is energy produced in a nuclear plant?
Two out of three of the students (66%) know that energy is released due to the nuclear fission. Far fewer answers concerned to the nuclear fusion (13%), or spontaneous disintegration of heavy nucleus (7%). The percentage of the students that declared they don't know was 14%.
· Which European Country covers more than 70% of its energy needs using Nuclear Energy?
Most of the students did not know this information. Only 26 % of the student’s knew that France is pioneer in using nuclear energy. Another 27% declared they don’t know and 2% thinks is the Great Britain. It is noticeable that 21% of the students considered that Belarus is the country that mostly depends on nuclear energy, although this country does not have nuclear plants yet. This wrong impression may be attributed, firstly to the fact that this country was mostly affected by the nuclear accident at Chernobyl in 1986 and secondly to the poor understanding of the global effects of a nuclear accident.
· Which is the pair of radioactive elements of high concern that are released in the environment during a nuclear accident?
A big number of students (58%) have the wrong perception that Plutonium and Uranium are the radioactive elements that are mainly released in the environment.
Only 18% answered correctly (cesium and iodine). A minority of 12% think of iodine and plutonium and 11% declared that they don’t know. This indicates that the majority of the student confuses the nuclear fuel with the reaction products.
· How many deaths are directly attributed to the nuclear accident during the first three months after Chernobyl disaster in 1986?
Only 4% of the students knew that less than 50 deaths can be attributed directly to the radioactive contamination due to the Chernobyl accident. The majority of 96% either declare that they don’t know (28%), or believe that deaths were more than 10.000 (35%), more than 100.000 (27%) or about 50-100 (6%). The above result shows the huge misconception, most of the students (and general population) have about the direct and the aftermath effects of radioactive contamination. The main reason for this faulty impression is that the media and several organizations (UN, Atomic Energy Agency, WHO) report mainly the potential effects of the ionizing radiation. Furthermore estimations of the number of deaths potentially resulting from Chernobyl accident, vary enormously between experts [2, 6].
· Which is the most unknown application of ionizing radiation for you?
The responses indicate that only 31% of the students know all the proposed useful applications of ionizing radiation. The most unknown application (24% stated that is the most unknown for them) was the sterilization of instruments used in medicine or of food products. It is notable that 15% of the students stated that they ignore the use of ionizing radiation in medicine (diagnosis, treatment) although in our country it is used in excessive degree. Finally 16% consider the Research-Industry applications as the most unknown for them and 14% didn’t know any of them.
· What is your main source of information about radioactivity issues?
Overall, an average of three out of four students (73%) has information from mass media (internet (56%) and radio-TV (17%)). A small number of students (13%) have other source of information and only 14% indicate school as the source of their information about radioactivity topics. This indicates that our school fails to offer the appropriate knowledge about these serious issues that affect our lives.
· Students’ appreciation of the seminars related to issues of general interest
The majority of the students (98%), believe that seminars on issues of general interest (like the above mentioned) should be organized in TEI (128 out of 131 students gave positive answer). This indicates a positive attitude about non formal ways of learning.
In figure 1, the percentage of the correct, incorrect, and “not know” answers in the first 7 of the questions are summarized. In this graph we can see that in more than half of the questions, the percentage of students that give incorrect answers is higher than those who answered correctly and much higher than that of the students that declare that they don’t know. This suggests that our students have inadequate and confused knowledge in these topics.
Figure 1: Percentage of the correct, incorrect, and “not know” answers in some of the questions
4. Discussion and conclusions
The first results of an ongoing research which aims to investigate the knowledge of Greek undergraduate students on some nuclear application issues were presented.
The above results show that the TEI Piraeus students have in general low awareness of the above nuclear issues although they seem to have increased interest about these issues. The students show a highly positive attitude about nontraditional types of education, like general interest seminars, and this is something that we, the teachers, must use in order to improve our students knowledge about modern physics issues. Furthermore, a serious effort must be made in secondary school to motivate students’ interest for both, the useful applications of nuclear physics in our life and the harmful effects of radioactivity in health and environment.
The outcome of this survey, in combination with some students’ comments, will be used to develop a revised survey that will be administered to a greater number of Greek students. In the mean time, a similar survey, with slight revision of some questions, is to be conducted soon with target group the administrative staff of TEI Piraeus, to compare the “general population” knowledge and views in nuclear issues with that of the “non major in physics” students. The identification of the most common misconceptions and faulty views of students and general population will contribute in the development of educational material that will improve the understanding of nuclear issues related to our everyday life.
Acknowledgements
The author would like to thank the students of the Automation Department Dimitris Pantelis and Enkeleda Bocaj for their assistance in the conduct of this survey.
References
1. Florbela Rego and Luis Peralta , “Portuguese students' knowledge of radiation physics” Phys. Education Vol. 41 ,pp259-262, May 2006
2. Sarina Cooper , Shelley Yeo, Marjan Zadnik “Australian students' views on nuclear issues: Does teaching alter prior beliefs?” Phys. Education, Vol.38, no.2, pp.123-129,March 2003
3. Robin Millar, Kees Klaassen, Harrie Eijkelhof ,“Teaching about radioactivity and ionising radiation: an alternative approach” Phys. Education, Vol.25, pp.338-342, 1990
4. Rawatee Maharaj-Sharma “A comparative study of the impact of students’ feelings regarding the use of nuclear energy” Science Education International Vol.22, No.1, pp.18-30,March 2011.
5. http://www.iaea.org/Publications/Reports/gponi_report2005.pdf
6. http://en.wikipedia.org/wiki/Chernobyl_disaster)
6. 3D Techniques and Tools for Preservation and Visualization of Cultural Heritage
Dimitrios Tzanakis1, Yannis Psaromiligkos2, Daune West3
1 MSc Student, TEI Piraeus & University of the West of Scotland, Mpizaniou 2, Alimos, 17456, Greece, Tel: +306944221554, E-mail: [email protected]
2 Professor, TEI Piraeus, Greece, E-mail: [email protected]
3 Senior Lecturer, University of the West of Scotland, UK, E-mail: [email protected]
Abstract
Cultural heritage is considered very important given that it classifies unions and countries and that it is the humanity beacon among centuries. Accordingly cultural heritage preservation and documentation is essential. There are various parameters that should be taken into consideration regarding cultural heritage surveying (e.g. cultural heritage object size, geometry, complexity) along with the usage. As a consequence there is not an all-in-one fitting solution. There is a variety of approaches to acquire data concerning cultural heritage sites, monuments and artifacts with the use of numerous state-of-the-art technologies of scanning and surveying, mainly 3D. These approaches generate a range of deliverables e.g. CAD designs, panoramas, 3D point clouds, triangular meshes. Additional procedures are used to further process, store and present these data.
In this paper, we investigate the needs, problems and solutions of cultural heritage objects digitization focusing on 3D methods for cultural heritage preservation and visualisation. The currently main available 3D digitization techniques are categorized, compared and evaluated according to specific criteria. The dominant and most preferable cultural heritage 3D digitization techniques are identified. Moreover, a Case Study is presented upon an Orthodox Church digitization, modelling and virtual presentation based on photogrammetry using the tools Arc3D Webservice, MeshLab and PixMaker. Finally, conclusions are formulated.
1. Introduction
Cultural heritage objects belong to the entire world and every individual must obtain the right to access them. This is quite difficult however, because cultural heritage objects are spread around the world. Additionally, in contrast with cultural heritage artifacts that are usually protected in museums, the cultural heritage sites and monuments are always in jeopardy. They are subject to various environmental effects like pollution, rain, sun, wind, fire, earthquakes along with humans’ catastrophic interference (e.g. war actions). The above demonstrate the fact that cultural heritage is essential to be preserved and documented.
The most important benefits from 3D digitization and visualisation of cultural heritage objects are:
1. Restoration study ability concerning buildings and large non-movable monuments and model study ability concerning artifacts.
2. The created models can provide an additional recording object that is possible to be incorporated in a collection (Data Base) of similar objects.
3. The opportunity that is given to a considerable number of people to meet and come in contact with cultural wealth worldwide (e.g. via virtual museums).
In the past, the common practice for the recording of cultural heritage objects was the use of non automated procedures for the measurement of feature points, by using simple measuring systems e.g.: surveyor’s tape, total station, measuring ruler, thickness gauge. The created products in this case did not depict the total object model (e.g. three-dimensional). They were usually represented as paper imprinting under scale of the characteristic facades, ground plans and elevations of the object.
The introduction of the Information Technology and of digital scanning techniques in the sciences that correlate with the study of cultural heritage objects (e.g.: topography, architecture, archaeology) has made the creation of digital models feasible. These are able to provide the 3D coordinates of a large number of feature points that compose the exterior surface of the object of interest either it being a small artifact (e.g. a statuette) or a monument-site through automated procedures.
2. General Technical Background – Definitions
Triangulation
It is the method of determining the coordinates of a point (B), by only measuring the angles a, c of two known points (A, C), instead of using direct distance measurements to the point.
Total stations
Total Stations are devices that allow with a single shooting, measurement of horizontal and vertical angle and simultaneous distance measurement of any point of the under study object (figure 2). This way the 3D coordinates of any feature point can be calculated directly without the need for other measurements [2].
Figure 1. Principal of triangulation
Figure 2. Total Station
Laser Scanning
The main 3D laser scanning solutions are based on the following methodologies:
Time of flight of a laser pulse
A laser pulse is emitted to the object and the distance between the signal sending device and the surface of the object is determined from the required time between transmission and reception of the laser pulse. This methodology is also known as Light Detection And Ranging (LIDAR).
Laser Triangulation
The sensor using the high optical definition of a laser beam, that is projected on the under study object, and via triangulation equations, calculates the position of each point that is illuminated by the laser beam in the 3D space.
Depth Map
The depth map is a two-dimensional range image where each pixel is represented by a colour value from the greyscale range.
Point Cloud
Each point of point cloud corresponds to a feature point of the under consideration object’s surface and embeds information that positions it at a specific location in the 3D space.
Triangular mesh (or triangulation network)
The depiction of a surface using a number of triangles which is called triangular mesh (or polygonal mesh or triangulation network) can be extracted from a point cloud and it is a very widespread technique for 3D visualisation. The triangular mesh can be enriched with texture information mapped onto each triangle of the surface.
3. Photogrammetry
Photogrammetry relates to the technique associated with objects’ geometric attributes identification using photographs [3]. The main photogrammetric techniques for digitization of cultural heritage monuments or sites are the following:
Monoscopic photogrammetry
In some cases the simplicity of the geometry of an object can lead to use only one photogrammetric image in order to identify the coordinates of the depicted object details.
Stereophotogrammetry (stereoscopic photogrammetry)
In stereophotogrammetry the 3D coordinates of an object’s surface are calculated by at least two photographs obtained from different positions using photogrammetric triangulation.
An essential prerequisite for stereoscopic photo processing is the realisation of photos acquisition so that the axes of the camera in the two shooting positions to be parallel to each other and vertical to the surface of the under study object (figure 3).
Figure 3. Stereoscopic shots
Convergent or non-stereoscopic photogrammetry
In this case, the camera axes converge toward the gravity centre of the object (Figure 4) and image processing is done by the use of special photogrammetric software packages (Photomodeler, iWhitness) which cost significantly less than Stereophotogrammetry.
Figure 4. Convergent photogrammetry
Figure 5. Structure from motion
Structure from motion
Although convergent photogrammetry is very similar to structure from motion, convergent photogrammetry software tools can cope with the problem of orientation using coded targets but they can not calculate 3D data of marker-less photos. On the other hand structure from motion technique’s tools can create 3D models by automatically calculating the orientation from marker-less photos. Usually the photos sequence should be ordered. But recently they came up with some new tools that can be used for input photo sequences that are un-ordered (e.g. Arc3D Webservice) [4, 5].
Stereoscopy
The function of 3D vision in humans, works in the base that the retinas perceive a slightly different image aspect for a given scene because there is a small distance between the eyes. This is achieved by a simple, for our brain, process in which the two relatively different 2D images are combined in a full 3D image of the surrounding space.
Stereoscopy creates a 3D illusion using a couple of two-dimensional photographs taken from different positions which are projected one for each eye [6, 7].
4. Web Technologies and 3D Visualisation
VRML
The virtual reality language, VRML, is a language for describing virtual worlds that are connected to the Internet. VRML file format is one of the most popular 3D model representation file formats over the Internet [8].
X3D
This standard is the enhanced successor of VRML [9].
Java
Java is the first language that managed to intergrade sound and motion in a Web page and can be applied to any browser. With Java one sends to the browser the content as well as the program to “see” this content at the same time. Among the important advantages of Java, is the independence towards operating system (OS).
5. Visual description of 3D object
For most 3D visualization applications the information provided by the “raw” point cloud is usually insufficient no matter how dense it is. Several methodologies were devised to assist the user perception of the point cloud visual information. The most common was the points’ gradation of brightness or size according to their distance from the projection level.
Currently, triangular mesh is used in most 3D imaging applications, providing the user with much more visual information than the point cloud, even in its simplest form of a “wireframe” (Figure 6).
Figure 6. Teapot “wireframe” (left), rendered teapot (right)
Apart from the triangular mesh, there are also other forms of three-dimensional depiction methodologies aiming at the most possible effective description of an object’s geometry. The most popular of these is the depiction of geometry using parametric surfaces that are described with curved lines of Basic-Spline type. The parametric surfaces provide the ability to describe smooth curved surfaces through a few control points (figure 7).
Figure 7. Surface representation using 4 points: left-depiction of geometry using parametric surfaces, right-depiction of geometry using non parametric surfaces
6. 3D digitization techniques comparison and evaluation
Comprehensive documentation of cultural heritage is often a multidimensional procedure. It deals with the digitization of cultural heritage objects as well as with the resulting digital products storage, organization, visualisation and reproduction. Cultural heritage digitization is the initial and more critical section of cultural heritage documentation. Due to the complexity of the digitization requirements, a multitude of techniques and methodologies has been developed. The objective of each approach is to efficiently handle a specific kind of objects or type of objects, or to satisfy certain needs and requirements of a particular cultural heritage surveying project (i.e. surveying for preserving, digitization for visualization, digitization for commercial purposes).
We decided to define criteria of choice for 3D digitization techniques and evaluate them since they are the key for culture heritage documentation. The requirements of cultural heritage preservation and visualisation in combination with the individual needs for the several cultural heritage surveying applications-projects provided us some criteria of choice. These, along with the particular technical specifications of 3D scanning systems and advantages-disadvantages of each cultural heritage 3D surveying technology were used to conduct an evaluation of the main cultural heritage 3D digitization techniques.
In order to assist the evaluation section, cultural heritage objects were distinguished according to their size in two categories:
1. Cultural heritage artifacts (movable objects). The main 3D digitization techniques for this category are: laser scanning techniques (triangulation), shape from silhouette, shape from structured light, shape from stereo, structure from motion.
2. Cultural heritage monuments and sites (non movable objects). The main 3D digitization techniques for this category are: empirical, topographic, laser scanning (time of flight) shape from stereo, convergent photogrammetry, structure from motion.
The results of the evaluation section are summarized in the cross reference table 1, where a summary of the main 3D digitization techniques in relation with the main selection criteria is presented.
To sum up, after the evaluation section we concluded that the prevailing dominant techniques are:
· Active sensor scanning solutions: Laser scanning techniques (laser triangulation, time of flight (LIDAR), phase comparison) and shape from structured light technique.
· Photogrammetry techniques (shape from stereo, convergent photogrammetry, structure from motion, shape from silhouette).
Laser scanning techniques achieve the most accurate geometry results. Also the shape from structured light technique provides sufficient geometric accuracy. Inferior geometry information is provided by descending order from the techniques: shape from stereo, convergent photogrammetry, structure from motion and shape from silhouette. On the other hand they can compensate the lack of high accuracy information with texture information usage.
Shape from stereo and convergent photogrammetry techniques’ provide exceptional geometrical accuracy when they are combined with topographic techniques for the accurate measurement of the required control points and in addition a metric or semi-metric photo camera or at least a consumer calibrated photo camera is used.
Structure from motion technique provides automatic calibration function and 3D models can be created by calculating the orientation from marker-less and un-ordered photos.
Till today, only the shape from silhouette ap