Measurement of (n,γ) reaction cross section of 186W-isotope at neutron energy of 20.02±0.58 MeV

The cross-section of 186W(n,γ)187W reaction has been measured at an average neutron energy of 20.02±0.58 MeV by using activation technique. The 27Al(n,α)24Na and 115In(n,n´)115mIn reactions have been used for absolute neutron flux measurement. Theoretically the reaction cross-sections have been calculated by using the TALYS-1.9 code. The results from the present work and the EXFOR based literature data have been compared with the evaluated data and calculated data from TALYS-1.9 code

Measurement of (n,γ) reaction cross section of 186W-isotope at neutron energy of 20.02±0.58 MeV

392-396The cross-section of 186W(n,γ)187W reaction has been measured at an average neutron energy of 20.02±0.58 MeV by using activation technique. The 27Al(n,α)24Na and 115In(n,n´)115mIn reactions have been used for absolute neutron flux measurement. Theoretically the reaction cross-sections have been calculated by using the TALYS-1.9 code. The results from the present work and the EXFOR based literature data have been compared with the evaluated data and calculated data from TALYS-1.9 code

Deep learning techniques for transmission line fault classification – A comparative study

Despite advancements in technology, power system faults leading to electric power interruption remain a significant issue. Efficient restoration of the power system relies on the swift classification and clearance of faults. Among the various types of faults in transmission lines, open circuit and short circuit faults are commonly encountered. This study specifically focuses on the analysis of five types of short circuit faults: line-to-line, line-to-ground, double line-to-ground, triple line, and triple line-to-ground faults. Faults can cause both power failure and power loss in transmission lines. Once a fault occurs, it is crucial to restore electricity supply promptly to prevent further losses. Therefore, the development of a system capable of accurately and swiftly detecting and removing faults is essential. Traditionally, categorizing transmission line faults required sophisticated mathematical modeling, intricate signal processing techniques, and expert knowledge to interpret the output signals. In this paper, an alternative approach is proposed, utilizing deep learning techniques for transmission line fault classification. Specifically, the paper employs techniques such as artificial neural network (ANN), long short-term memory (LSTM), with and without window regression (WR). By implementing these deep learning techniques, automatic feature extraction and signal processing are achieved, streamlining the fault classification process. The experimental results obtained from this study demonstrate an accuracy of 42.98% for ANN, 99.98% for LSTM, and 99.99% for LSTM-WR. These outcomes underscore the effectiveness of the deep learning techniques employed in accurately classifying transmission line faults, with LSTM and LSTM-WR outperforming ANN in terms of accuracy

Steady state formation of a toroidal electron cloud

A novel scheme of injection and confinement of electrons is reported for the formation of a toroidal electron cloud in the presence of a static toroidal magnetic field. The scheme is based on the use of a combination of externally applied electric field and the self-consistent space charge field for the electron trapping and confinement. The time development of electron cloud potentials measured in the poloidal plane of the torus is presented. A potential well depth exceeding the initial kinetic energy of the electrons is observed, indicating collective effects. The effect of external field on the total charge and capacitance of the electron cloud is also presented

R&D on divertor plasma facing components at the Institute for Plasma Research

This paper is focused on various aspects of the development and testing of water cooled divertor PFCs. Divertor PFCs are mainly designed to absorb the heat and particle fluxes out flowing from the core plasma of fusion devices like ITER. The Divertor and First Wall Technology Development Division at the Institute for Plasma Research (IPR), India, is extensively working on development and testing of divertor plasma facing components (PFCs). Tungsten and graphite macro-brush type test mock-ups were produced using vacuum brazing furnace technique and tungsten monoblock type of test mock-ups were obtained by hot radial pressing (HRP) technique. Heat transfer performance of the developed test mock-ups was tested using high heat flux tests with different heat load conditions as well as the surface temperature monitoring using transient infrared thermography technique. Recently we have established the High Heat Flux Test Facility (HHFTF) at IPR with an electron gun EH300V (M/s Von Ardenne Anlagentechnik GmbH, Germany) having maximum power 200 kW. Two tungsten monoblock type test mock-ups were probed using HHFTF. Both of the test mock-ups successfully sustained 316 thermal cycles during high heat fl ux (HHF) tests. The test mock-ups were non- -destructively tested using infrared thermography before and after the HHF tests. In this note we describe the detailed procedure used for testing macro-brush and monoblock type test mock-ups using in-house transient infrared thermography set-up. An acceptance criteria limit was defined for small scale macro-brush type of mock-ups using DTrefmax value and the surface temperature measured during the HHF tests. It is concluded that the heat transfer behavior of a plasma facing component was checked by the HHF tests followed by transient IR thermography. The acceptance criteria DTrefmax limit for a graphite macro-brush mock-up was found to be ~3centi grade while for a tungsten macro-brush mock-up it was ~5centi grade

Fabrication and characterization of W-Cu functionally graded material by spark plasma sintering process

In this study, seven-layered W/Cu functionally graded material (FGM) (100 W, 80W-20Cu, 60W-40Cu, 50W-50Cu, 40W-60Cu, 20W-80Cu, 100Cu, by wt %) were fabricated by a spark plasma sintering process (SPS). The influences of sintering temperature on microstructure, physical and mechanical properties of the sintered bulk FGM were investigated. Results indicated that the graded structure of the composite densified after the SPS process and interfaces of the layers are clearly visible. All of the layers had a very high relative density, thereby indicating their densification and excellent sintering behavior. SEM and EDX study of the bulk sample crosssection reveal that the graded structure can be retained up to sintering temperature of 1050 degrees C. In addition fine microstructure within each layer with good interface bonding was also observed. Sample sintered at 1050 degrees C exhibited excellent mechanical and physical properties (hardness 239 +/- 5 Hv and relative density of 90.5%). The result demonstrates that SPS is a promising and more suitable process for fabrication of W-Cu functionally graded materials