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Simulation of hard X-ray time evolution in the stable region of plasma tokamak by using the NARX-GA hybrid neural network | ||
| Journal of Interfaces, Thin Films, and Low dimensional systems | ||
| دوره 5، شماره 2، اردیبهشت 2022، صفحه 537-545 اصل مقاله (1.55 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22051/jitl.2023.40718.1073 | ||
| نویسندگان | ||
| Amir Alavi1؛ Shervin Saadat* 2؛ Modamad Reza Ghanbari3؛ Seyed Enayatallah Alavi4؛ Ali Kadkhodaie5 | ||
| 1Department of Physics, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran | ||
| 2Canadian Light Source Inc., University of Saskatchewan, Saskatoon, Saskatchewan, S7N2V3, Canada | ||
| 3Department of Basic Sciences, Garmsar Branch, Islamic Azad University, Garmsar, Iran | ||
| 4Department of Computer Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran | ||
| 5Earth Sciences Department, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran | ||
| چکیده | ||
| The time evolution of hard X-ray has been simulated using the NARX-GA hybrid neural network in the stable region of the plasma tokamak. Loop voltage and hard X-ray measured by the tokamak diagnostics tools were selected as network inputs. The NARX network has been trained using the Genetic Algorithm (GA) and the time evolution of the hard X-ray up to 500 μs (MSE = 4.13 × 10-5) is accurately simulated. Increasing the confinement time is the particular purpose of applying tokamak to produce energy through fusion. The real-time application of this methodology brings us closer to this goal. Hard X-ray prediction can prevent plasma energy reduction. It can also reduce the severe damage caused by runaway electrons (RE) colliding with the tokamak wall. Early prediction of hard X-ray time evolution is critical in attempting to mitigate the REs potentially dangerous effects. | ||
| کلیدواژهها | ||
| Methodology؛ Hard X-ray؛ Runaway electrons؛ NARX-GA network | ||
| عنوان مقاله [English] | ||
| شبیه سازی تحول زمانی اشعه ایکس سخت در ناحیه پایدار پلاسمای توکامک با استفاده از شبکه عصبی مصنوعی هیبریدی NARX-GA | ||
| نویسندگان [English] | ||
| امیر علوی1؛ شروین سعادت2؛ محمد رضا قنبری3؛ O علوی4؛ علی کدخدایی5 | ||
| 1گروه فیزیک، دانشگاه آزاد اسلامی، واحد شوشتر، شوشتر، ایران | ||
| 2شرکت کانادایی چشمه نور، دانشگاه ساسکاتچوان، ساسکاتون، کانادا | ||
| 3گروه علوم پایه، دانشگاه آزاد اسلامی، واحد گرمسار، گرمسار، ایران | ||
| 4گروه کامپیوتر، دانشکده مهندسی، دانشگاه شهید چمران اهواز، اهواز، ایران | ||
| 5گروه زمین شناسی، دانشکده علوم پایه، دانشگاه تبریز، تبریز، ایران | ||
| چکیده [English] | ||
| تکامل زمانی پرتو ایکس سخت با استفاده از شبکه عصبی هیبریدی NARX-GA در ناحیه پایدار توکامک پلاسما شبیهسازی شد. ولتاژ حلقه و اشعه ایکس سخت اندازه گیری شده توسط ابزار تشخیصی توکامک به عنوان ورودی شبکه انتخاب شدند. شبکه NARX با استفاده از الگوریتم ژنتیک (GA) آموزش داده شد و به طور دقیق تکامل زمانی پرتو ایکس سخت را تا 500 میکرو ثانیه شبیهسازی کرد (MSE = 4.13×10-5). افزایش زمان محصور سازی هدف ویژه ای در استفاده از توکامک برای تولید انرژی از طریق همجوشی می باشد. کاربرد بلادرنگ این روش ما را به این هدف نزدیکتر می کند. پیشبینی سخت اشعه ایکس میتواند از کاهش انرژی پلاسما جلوگیری کند. همچنین می تواند آسیب شدید ناشی از برخورد الکترون های گریزان (RE) با دیواره توکامک را کاهش دهد. پیشبینی تکامل زمانی پرتو ایکس سخت برای کاهش اثرات بالقوه خطرناک الکترون های گریزان امری حیاتی است. | ||
| کلیدواژهها [English] | ||
| روش شناسی, پرتو ایکس سخت, الکترون های گریزان, شبکه NARX-GA | ||
| مراجع | ||
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