Gamma ray spectra analysis for pulsed fast thermal neutron activation (PFTNA) of bulk coal samples

In this study it is aimed to make a real time analysis of coal samples. The coal analysis is conducted in terms of its calorific value, sulphur content, ash and amount of moisture. Coal materials are classified for better combustion and minimum detrimental effects to environment. These beneficial features of coal samples are determined by burning the material before they are classified. Nuclear techniques conduct such determinations in non-destructive ways. Therefore, these methods are important in coal industry. The main principle of this array of experiments is based on the interaction of neutrons with coal material. Coal materials exposed to neutrons are radio actively excited and disintegrate by emitting gamma rays. These gamma rays have energy values which are the fingerprint of the elements presenting in coal. The elements are identified thanks to their certain gamma ray energy values. For the coal analyzing, Pulsed Fast Thermal Neutron Activation Analysis (PFTNAA) is utilized. This technique gives precise result even in a short period of time. Coal material interacts with neutrons and there are neutron inelastic scattering and thermal neutron capture processes. One of these kind of interaction branches are dominated for some of the elements. PFTNAA method also gives more precise results and information for some critical elements such as carbon and oxygen. There are other kinds of neutron sources used for neutron activation process, however these neutron sources such as Cf252 are not sufficient for identifying some certain elements. Carbon has specific energy value at 4.44MeV and this certain energy value is identified via fast neutron interaction mechanism. Neutron generator emits fast neutrons with 14 MeV energy and therefore it is detected carbon elements in material if they exist. In PFTNAA technique it is obtained two separate spectra. In these spectra some elements belong to fast and some of them belong to thermal neutron induced gamma spectra. They are identified via thermal and fast neutron interaction mechanisms. Therefore, it is nedded to separate thermal and fast neutron induced gamma ray spectra. For this purpose, collected gamma ray data is in the raw form. List mode data acquisition system allows for the data collection when the neutron generator in ON and OFF state. When the neutron generator is ON, resulted gamma rays belong to the fast neutron induced spectrum, when the neutron generator in OFF the neutrons are thermalized through the material and obtained spectrum is thermal neutron induced gamma ray. In the experiment, BGO detector gate port is directly connected to the neutron generator. In this way, BGO detector is triggered according to the ON/OFF mode of neutron generator. In order to allow fast neutrons to be thermalized, it is needed a certain duration to be waited without neutron emission. In this period of time neutrons are thermalized and they lose their energy. Operation time and duty cycle are adjusted via neutron generator interface. Voltage and current values are also set with the aid of interface control of neutron generator. PFTNAA technique is also useful in terms of radiation concern. The radiation only produced when the neutron generator is ON. Additionally, during experiment it is used WiFi router so as to study far away from the experimental setup therefore detrimental effects of the radiation. By the aid of remote desktop connection, both BGO detector and neutron generator are controlled confidentally. After obtaining the data colledcted by BGO detector, they are classified as two separate spectra. In order to obtain these spectra, it is written a C++ decoding code reading 32-word data coming from each of gamma ray entering detector. Raw data is analysed according to bitwise operators and decoding instruction of digiBASE-E module. Each bit carries its information about peak data or time of gamma ray photon striking the detector. The instruction manuel says that digiBASE-E module is active when 32-bit word first bit is 1 and it is at its OFF state when the first bit is 0. After decoding the list mode file the gamma ray photons are converted from histogram to a spectrum data. Each event corresponds to the same amplitude value are collected and stored in a channel where they belong to. In this way spectrum data is obtained. After obtaining the separate spectra, elements in coal material are identified clearly. The peaks appear individually without overlapping as in the total gamma ray spectra. The most dominant cross section values for the energy of elements are recognized in the apperant peaks in the spectra. By separating fast and thermal neutron induced gamma ray spectra element libraries are created. This database gives the information about the behavior of elements in the energy versus amplitude domain. This data store is used for a calibration process and determination of elemental content in the coal sample. This element library can be used for different coal samples but similar weights. By using library least square method element concentration of coal sample can be found easily. After data acquisition system is completed, offline analyzing methods are used for identifying the elements in coal and calculating their concentrations. There are various kinds of methods used in determination of element content. In this work it is conducted some experimental studies including both synthetic and real coal materials. There are two types of techniques are adopted for creating element library. They are; experimental studies and semi – experimental studies. These hybrid works are done with some mathematical formulation sets as well. Experimental studies can be grouped as synthetic coal sample experiments and real coal sample experiment arrays as stated. The synthetic coal sample concentration is known and therefore the system can be calibrated according to known values. Afterwards, a linear set of equations are created by using calibration coefficients in order to obtain unknown coal sample contents. The element library is found for the purpose of element concentration. This data base is found by different kinds of methods. Firstly, it is used least square method by taking inverse of a matrix obtained from a coal sample that has a known concentration. Obtained matrix includes the information for element library for coal samples with similar weights and type. In order to use this element library for another coal sample, working conditions and neutron emission durations should be the same as the experiment conducted for finding element library. Real coal samples are used for the identification and determination of some critical elements appearing in the bulk coal sample. It is tested that obtained element library works well or not by using real coal sampels. Element library data set can be found by using both experimental data and some mathematical algorithms as well. Obtained gamma ray spectra includes background information and element energy peaks are located just over this background data. These energy peaks are specific for each element and it is known their peak distribution shapes. By using these information, special Gaussian peaks are created correspond to certain energy values for the elements in coal sample. These peaks are summed with background data calculated by the aid of ROOT Background algorithm. Calculated background data gets the source data as gamma ray spectrum for real coal sample. After obtaining library set for each element, they are fitted to a real coal sample gamma ray spectrum in order to check their consistency to the real data. Both matrix inversion operation and background calculation algorithm used as fundamental techniques for elemental responses are fitted well with experimental gamma ray spectrum. Deconvolution process is other part of the offline analysis of this study. BGO detector cannot resolve accurately the energy peaks of elements. There are some multiplets appearing in the spectrum. Gamma ray – material interaction mechanisms coming from the environment interfere with fundamental nuclear reactions and then certain energy peaks cannot be identified easily. At this stage ROOT Deconvolution algorithm is used so as to separate multiplets. This mathematical formulation takes gamma ray spectrum as a source data for input and a response function for the relevant element as a second input. The result gives a spectrum for individual elements in energy – amplitude scale. They can be treated also as responses for elements. In this experimental study, it is conducted a non – destructive testing of coal material. Some critical element contents are determined in the aim of reaching calorific value, moisture, ash and sulphur concentration. These parameters have crucial importance in coal industry in terms of classification of coal. This procedure is performed by burning of coal. Our study helps to find contents of coal non – destructively and in a more accurate way. All of these experimental and numerical efforts are spent for this purpose.