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1. Detection of Very High-energy Gamma-Ray Emission from the Radio Galaxy M87 with LHAASO

Author

Zhen Cao, F. Aharonian, Axikegu, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, W. Bian, A. V. Bukevich, Q. Cao, W. Y. Cao, Zhe Cao, J. Chang, J. F. Chang, A. M. Chen, E. S. Chen, H. X. Chen, Liang Chen, Lin Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, M. C. Chu, M. Y. Cui, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzengluobu, X. Q. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, J. Fang, J. H. Fang, K. Fang, C. F. Feng, H. Feng, L. Feng, S. H. Feng, X. T. Feng, Y. Feng, Y. L. Feng, S. Gabici, B. Gao, C. D. Gao, Q. Gao, W. Gao, W. K. Gao, M. M. Ge, T. T. Ge, L. S. Geng, G. Giacinti, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, O. A. Hannuksela, M. Hasan, H. H. He, H. N. He, J. Y. He, Y. He, Y. K. Hor, B. W. Hou, C. Hou, X. Hou, H. B. Hu, Q. Hu, S. C. Hu, C. Huang, D. H. Huang, T. Q. Huang, W. J. Huang, X. T. Huang, X. Y. Huang, Y. Huang, Y. Y. Huang, X. L. Ji, H. Y. Jia, K. Jia, H. B. Jiang, K. Jiang, X. W. Jiang, Z. J. Jiang, M. Jin, M. M. Kang, I. Karpikov, D. Khangulyan, D. Kuleshov, K. Kurinov, B. B. Li, C. M. Li, Cheng Li, Cong Li, D. Li, F. Li, H. B. Li, H. C. Li, Jian Li, Jie Li, K. Li, S. D. Li, W. L. Li, X. R. Li, Xin Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, D. B. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Q. Luo, Y. Luo, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, Z. Min, W. Mitthumsiri, H. J. Mu, Y. C. Nan, A. Neronov, K. C. Y. Ng, L. J. Ou, P. Pattarakijwanich, Z. Y. Pei, J. C. Qi, M. Y. Qi, B. Q. Qiao, J. J. Qin, A. Raza, D. Ruffolo, A. Sáiz, M. Saeed, D. Semikoz, L. Shao, O. Shchegolev, X. D. Sheng, F. W. Shu, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, D. X. Sun, Q. N. Sun, X. N. Sun, Z. B. Sun, J. Takata, P. H. T. Tam, Q. W. Tang, R. Tang, Z. B. Tang, W. W. Tian, L. H. Wan, C. Wang, C. B. Wang, G. W. Wang, H. G. Wang, H. H. Wang, J. C. Wang, Kai Wang, L. P. Wang, L. Y. Wang, P. H. Wang, R. Wang, W. Wang, X. G. Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, Q. W. Wu, S. Wu, X. F. Wu, Y. S. Wu, S. Q. Xi, J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, Y. L. Xin, Y. Xing, D. R. Xiong, Z. Xiong, D. L. Xu, R. F. Xu, R. X. Xu, W. L. Xu, L. Xue, D. H. Yan, J. Z. Yan, T. Yan, C. W. Yang, C. Y. Yang, F. Yang, F. F. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, W. X. Yang, Y. H. Yao, Z. G. Yao, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. Yue, H. D. Zeng, T. X. Zeng, W. Zeng, M. Zha, B. B. Zhang, F. Zhang, H. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, Li Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. B. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, X. H. Zhao, F. Zheng, W. J. Zhong, B. Zhou, H. Zhou, J. N. Zhou, M. Zhou, P. Zhou, R. Zhou, X. X. Zhou, B. Y. Zhu, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, Y. C. Zou, and X. Zuo

Subjects
Active galactic nuclei, High energy astrophysics, Astrophysics, QB460-466
Abstract

The nearby radio galaxy M87 is a very high-energy (VHE) gamma-ray emitter established by observations with ground-based gamma-ray detectors. Here we report the long-term monitoring of M87 from 2021 to 2024 with the Large High Altitude Air Shower Observatory (LHAASO). M87 has been detected by LHAASO with a statistical significance ∼ 9 σ . The observed energy spectrum extends to 20 TeV, with a possible hardening at ∼20 TeV and then a clear softening at higher energies. Assuming that the intrinsic spectrum is described by a single power law up to 20 TeV, a tight upper bound on the extragalactic background light intensity is obtained. A strong VHE flare lasting 8 days, with a rise time of ${\tau }_{r}^{\mathrm{rise}}=1.05\pm 0.49$ days and decay time of ${\tau }_{d}^{\mathrm{decay}}=2.17\pm 0.58$ days, was found in early 2022. A possible GeV flare is seen also in Fermi Large Area Telescope data during the VHE flare period. The variability time as short as 1 day seen in the LHAASO data suggests a compact emission region with a size of ∼3 × 10 ^15 δ cm ( δ being the Doppler factor of the emitting region), corresponding to a few Schwarzschild radii of the central supermassive black hole in M87. The continuous monitoring of the source reveals a duty cycle of ∼1% for VHE flares with a flux above 10 ^−11 erg cm ^−2 s ^−1 .

Published
2024
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2. Discovery of Very High Energy Gamma-Ray Emissions from the Low-luminosity AGN NGC 4278 by LHAASO

Author

Zhen Cao, F. Aharonian, Axikegu, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, W. Bian, A. V. Bukevich, Q. Cao, W. Y. Cao, Zhe Cao, J. Chang, J. F. Chang, A. M. Chen, E. S. Chen, H. X. Chen, Liang Chen, Lin Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, M. Y. Cui, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzengluobu, X. Q. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, J. Fang, J. H. Fang, K. Fang, C. F. Feng, H. Feng, L. Feng, S. H. Feng, X. T. Feng, Y. Feng, Y. L. Feng, S. Gabici, B. Gao, C. D. Gao, Q. Gao, W. Gao, W. K. Gao, M. M. Ge, L. S. Geng, G. Giacinti, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, M. Hasan, H. H. He, H. N. He, J. Y. He, Y. He, Y. K. Hor, B. W. Hou, C. Hou, X. Hou, H. B. Hu, Q. Hu, S. C. Hu, D. H. Huang, T. Q. Huang, W. J. Huang, X. T. Huang, X. Y. Huang, Y. Huang, X. L. Ji, H. Y. Jia, K. Jia, K. Jiang, X. W. Jiang, Z. J. Jiang, M. Jin, M. M. Kang, I. Karpikov, D. Kuleshov, K. Kurinov, B. B. Li, C. M. Li, Cheng Li, Cong Li, D. Li, F. Li, H. B. Li, H. C. Li, Jian Li, Jie Li, K. Li, S. D. Li, W. L. Li, X. R. Li, Xin Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, D. B. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Q. Luo, Y. Luo, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, Z. Min, W. Mitthumsiri, H. J. Mu, Y. C. Nan, A. Neronov, L. J. Ou, P. Pattarakijwanich, Z. Y. Pei, J. C. Qi, M. Y. Qi, B. Q. Qiao, J. J. Qin, A. Raza, D. Ruffolo, A. Sáiz, M. Saeed, D. Semikoz, L. Shao, O. Shchegolev, X. D. Sheng, F. W. Shu, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, D. X. Sun, Q. N. Sun, X. N. Sun, Z. B. Sun, J. Takata, P. H. T. Tam, Q. W. Tang, R. Tang, Z. B. Tang, W. W. Tian, C. Wang, C. B. Wang, G. W. Wang, H. G. Wang, H. H. Wang, J. C. Wang, Kai Wang, L. P. Wang, L. Y. Wang, P. H. Wang, R. Wang, W. Wang, X. G. Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, Q. W. Wu, S. Wu, X. F. Wu, Y. S. Wu, S. Q. Xi, J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, Y. L. Xin, Y. Xing, D. R. Xiong, Z. Xiong, D. L. Xu, R. F. Xu, R. X. Xu, W. L. Xu, L. Xue, D. H. Yan, J. Z. Yan, T. Yan, C. W. Yang, C. Y. Yang, F. Yang, F. F. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, W. X. Yang, Y. H. Yao, Z. G. Yao, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. Yue, H. D. Zeng, T. X. Zeng, W. Zeng, M. Zha, B. B. Zhang, F. Zhang, H. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, Li Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. B. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, X. H. Zhao, F. Zheng, W. J. Zhong, B. Zhou, H. Zhou, J. N. Zhou, M. Zhou, P. Zhou, R. Zhou, X. X. Zhou, B. Y. Zhu, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, Y. C. Zou, X. Zuo, and The LHAASO Collaboration

Subjects
High energy astrophysics, Gamma-ray astronomy, Low-luminosity active galactic nuclei, LINER galaxies, Blazars, Fanaroff-Riley radio galaxies, Astrophysics, QB460-466
Abstract

The first source catalog of the Large High Altitude Air Shower Observatory (LHAASO) reported the detection of a very high energy gamma-ray source, 1LHAASO J1219+2915. This Letter presents a further detailed study of the spectral and temporal behavior of this pointlike source. The best-fit position of the TeV source (R.A. = 185.°05 ± 0.°04, decl. = 29.°25 ± 0.°03) is compatible with NGC 4278 within ∼0.°03. Variation analysis shows an indication of variability on a timescale of a few months in the TeV band, which is consistent with low-frequency observations. Based on these observations, we report the detection of TeV γ -ray emissions from this low-luminosity active galactic nucleus. The observation by LHAASO's Water Cherenkov Detector Array during the active period has a significance level of 8.8 σ with a best-fit photon spectral index Γ = 2.56 ± 0.14 and a flux f _1–10 TeV = (7.0 ± 1.1 _sta ± 0.35 _syst ) × 10 ^−13 photons cm ^−2 s ^−1 , or approximately 5% of the Crab Nebula. The discovery of VHE gamma-ray emission from NGC 4278 indicates that compact, weak radio jets can efficiently accelerate particles and emit TeV photons.

Published
2024
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3. The First LHAASO Catalog of Gamma-Ray Sources

Author

Zhen Cao, F. Aharonian, Q. An, Axikegu, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, J. T. Cai, Q. Cao, W. Y. Cao, Zhe Cao, J. Chang, J. F. Chang, A. M. Chen, E. S. Chen, Liang Chen, Lin Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, M. Y. Cui, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzengluobu, D. della Volpe, X. Q. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, X. T. Feng, Y. L. Feng, S. Gabici, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, W. K. Gao, M. M. Ge, L. S. Geng, G. Giacinti, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. Y. He, X. B. He, Y. He, M. Heller, Y. K. Hor, B. W. Hou, C. Hou, X. Hou, H. B. Hu, Q. Hu, S. C. Hu, D. H. Huang, T. Q. Huang, W. J. Huang, X. T. Huang, X. Y. Huang, Y. Huang, Z. C. Huang, X. L. Ji, H. Y. Jia, K. Jia, K. Jiang, X. W. Jiang, Z. J. Jiang, M. Jin, M. M. Kang, T. Ke, D. Kuleshov, K. Kurinov, B. B. Li, Cheng Li, Cong Li, D. Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, Jian Li, Jie Li, K. Li, W. L. Li, X. R. Li, Xin Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, R. Lu, Q. Luo, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, Z. Min, W. Mitthumsiri, H. J. Mu, Y. C. Nan, A. Neronov, Z. W. Ou, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, A. Sáiz, D. Semikoz, C. Y. Shao, L. Shao, O. Shchegolev, X. D. Sheng, F. W. Shu, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Q. W. Tang, Z. B. Tang, W. W. Tian, C. Wang, C. B. Wang, G. W. Wang, H. G. Wang, H. H. Wang, J. C. Wang, K. Wang, L. P. Wang, L. Y. Wang, P. H. Wang, R. Wang, W. Wang, X. G. Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, X. F. Wu, Y. S. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, Z. Xiong, D. L. Xu, R. F. Xu, R. X. Xu, W. L. Xu, L. Xue, D. H. Yan, J. Z. Yan, T. Yan, C. W. Yang, F. Yang, F. F. Yang, H. W. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. Yue, H. D. Zeng, T. X. Zeng, W. Zeng, M. Zha, B. B. Zhang, F. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, L. X. Zhang, Li Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. B. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, B. Zhou, H. Zhou, J. N. Zhou, M. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo, and (The LHAASO Collaboration)

Subjects
Gamma-ray astronomy, Gamma-ray observatories, Catalogs, Astrophysics, QB460-466
Abstract

We present the first catalog of very-high-energy and ultra-high-energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory. The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array from 2021 March to 2022 September and 933 days of data recorded by the Kilometer Squared Array from 2020 January to 2022 September. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering decl. from −20° to 80°. In total, the catalog contains 90 sources with an extended size smaller than 2° and a significance of detection at >5 σ . Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy ( E > 100 TeV) emission at >4 σ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog.

Published
2024
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13. Physics-informed neural networks for modeling astrophysical shocks

Author

S P Moschou, E Hicks, R Y Parekh, D Mathew, S Majumdar, and N Vlahakis

Subjects
physics-informed neural networks, computational fluid dynamics, machine learning, astrophysics theory & modeling, heliophysics theory & modeling, astrophysical shocks, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95
Abstract

Physics-informed neural networks (PINNs) are machine learning models that integrate data-based learning with partial differential equations (PDEs). In this work, for the first time we extend PINNs to model the numerically challenging case of astrophysical shock waves in the presence of a stellar gravitational field. Notably, PINNs suffer from competing losses during gradient descent that can lead to poor performance especially in physical setups involving multiple scales, which is the case for shocks in the gravitationally stratified solar atmosphere. We applied PINNs in three different setups ranging from modeling astrophysical shocks in cases with no or little data to data-intensive cases. Namely, we used PINNs (a) to determine the effective polytropic index controlling the heating mechanism of the space plasma within 1% error, (b) to quantitatively show that data assimilation is seamless in PINNs and small amounts of data can significantly increase the model’s accuracy, and (c) to solve the forward time-dependent problem for different temporal horizons. We addressed the poor performance of PINNs through an effective normalization approach by reformulating the fluid dynamics PDE system to absorb the gravity-caused variability. This led to a huge improvement in the overall model performance with the density accuracy improving between 2 and 16 times. Finally, we present a detailed critique on the strengths and drawbacks of PINNs in tackling realistic physical problems in astrophysics and conclude that PINNs can be a powerful complimentary modeling approach to classical fluid dynamics solvers.

Published
2023
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21. Towards the construction of the Mu2e electromagnetic calorimeter at Fermilab

Author

Atanov, N., primary, Baranov, V., additional, Borrel, L., additional, Bloise, C., additional, Budagov, J., additional, Ceravolo, S., additional, Cervelli, F., additional, Colao, F., additional, Cordelli, M., additional, Corradi, G., additional, Davydov, Y. I., additional, Di Falco, S., additional, Diociaiuti, E., additional, Donati, S., additional, Donghia, R., additional, Echenard, B., additional, Ferrari, C., additional, Gioiosa, A., additional, Giovannella, S., additional, Giusti, V., additional, Glagolev, V., additional, Grancagnolo, F., additional, Hampai, D., additional, Happacher, F., additional, Hitlin, D., additional, Lin, D., additional, Marini, A., additional, Martini, M., additional, Middleton, S., additional, Miscetti, S., additional, Morescalchi, L., additional, Pasciuto, D., additional, Pedreschi, E., additional, Porter, F., additional, Raffaelli, F., additional, Saputi, A., additional, Sarra, I., additional, Spinella, F., additional, Taffara, A., additional, Tassielli, G. F., additional, Tereshchenko, V., additional, Usubov, Z., additional, Vasilyev, I. I., additional, Zanetti, A., additional, and Zhu, R. Y., additional

Published
2022
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26. Enhanced digital water level measurement for irrigation channel

Author

J A Loekito, R Y Tallar, O Pattipawaej, M C Sutandi, T O Sihombing, P P Yapinus, J Chandra, M Tanubrata, H Lesmana, L Karsten, null Tonny, null Efferiki, P Madvi H A S, and F P Purba

Subjects
General Medicine, General Chemistry
Abstract

Indonesia needs to improve its irrigation system by implementing respectable technology. Recently, Indonesian irrigation systems have intended to switch from analog to digital technology. However, it appeared that Indonesia was having some issues applying digital technology in many areas. For instance, delivering water from water sources to irrigation subversives requires a computer infrastructure. A manual water level monitoring tool has been used in irrigation canals to gauge the water level that flows through them. The major goal of this project is to design a digital measuring device for water level and water temperature in the irrigation channel. The appropriate information must be entered into the irrigation channels. An experimental investigation has been conducted into the accuracy of digital instrument design for detecting water level and water temperature in irrigation channels. The creation of the digital water level measurement design will be tested against manual measurement to determine the percentage difference. The percentage difference between the traditional water level measurement and the digital water level measurement is the anticipated outcome. It is possible to infer that it is crucial to use digital tools, especially when determining the water level in irrigation channels.

Published
2023

27. Application of Fuzzy Adaptive Control in Gun Servo System

Author

P Dai, C W Han, R Y Kong, G S Zhang, and M Liu

Subjects
History, Computer Science Applications, Education
Abstract

Friction torque is an important parameter affecting the servo system, which will decrease with the increase of service time. With the change of friction torque, the control characteristics of the servo system will change, resulting in the servo dynamic and static performance can not meet the system requirements. On the basis of expounding the composition and working principle of gun pitching servo system, a control method of gun servo system based on fuzzy adaptive control is proposed. The problem of system performance change caused by the change of servo system parameters is solved. Through MATLAB simulation, it shows that the method can eliminate the influence of friction torque change on the system, make the system insensitive to the change of torque parameters, and meet the use requirements under various parameter conditions.

Published
2023

28. Design and development of type-1 FBG based high temperature sensor

Author

R Y M Khan, R Ullah, and M Faisal

Subjects
Condensed Matter Physics, Mathematical Physics, Atomic and Molecular Physics, and Optics
Abstract

Thermal metrology is critical in many high-energy industrial processes to optimize the process efficiency, energy consumption and quality of end product. Here, we present the design and development of a double thimble type standard type-1 fiber Bragg grating (FBG) high temperature sensing probes. Two different probes named probe-1 and probe-2 are developed by encapsulating type-1 FBGs in two stainless steel thimbles with ceramic filling. The probes are experimentally tested in a high temperature box furnace and their responses are interrogated by an optical spectrum analyzer. FBGs encapsulated in both probe-1 and probe-2 exhibited a linear red-shift in their Bragg wavelength with increase in temperature from 30 °C to 700 °C with sensitivities of 13.86 ± 0.1 pm/°C and 14.10 ± 0.2 pm/°C which are 4.8% and 3.16% lower than temperature sensitivity of bare FBG, respectively. A deformation in the Bragg spectrum of probe-1 is observed at temperatures above 500 °C however, probe-2 is found to be thermally stable up to 700 °C. An estimated life-time of about 6 years is offered by the optimized probe-2 with a negligible hysteresis and repeatability of 1°C–5°C.

Published
2023

33. Artificial Intelligent For Rainfall Estimation In Tropical Region : A Survey

Author

R Y Mardyansyah, B Kurniawan, S Soekirno, D E Nuryanto, and H Satria

Subjects
General Medicine, General Chemistry
Abstract

Rainfall monitoring in real-time is a mandatory in tropical areas such as Indonesia. As a country with various topographical conditions ranging from low-lying urban areas, highlands, to mountainous valleys, Indonesia is prone to hydrometeorological disasters in the form of flash floods and landslides. The strategic geographical position at the equator, between the Pacific and Indian oceans, and surrounded by vast oceans, combined with various natural phenomena related to the dynamics of the atmosphere and the ocean, makes high-density rainfall observations indispensable for both disaster mitigation and climate monitoring. As a vast tropical and archipelagic country, Indonesia currently has around 1000 automatic rainfall sensors and still requires more sensors to increase the spatial resolution of the observation network. Increasing the density of the observation network using both rain gauges and weather radar poses a problem of high operational costs. Therefore, several alternative rainfall observation systems are required. In the last decade, there have been several studies related to rainfall measurements using artificial intelligence from various meteorological variables, including the exploitation of microwave signals from radio telecommunications links, both terrestrial and satellite using high frequency bands. In this survey paper, we review and discuss research articles related to rainfall estimation using state-of-the-art methods in artificial intelligence using meteorological observation data, remote sensing, terrestrial and satellite microwave communication links. In conclusion, we present several future research challenges that can be applied to increase the density of rainfall observation networks.

Published
2022

34. Diversity of Hymenoptera in the Forest Area with Special Purpose (KHDTK) Aek Nauli, North Sumatra

Author

D A S Siahaan, K Berliani, R Y Pangaribuan, D Agustin, null Yulinar, F Mutiara, and T S U B Tarigan

Subjects
General Medicine, General Chemistry
Abstract

As one of the four largest insect orders, Hymenoptera are important pollinators, parasitoids, and predators in the agricultural sector. The objective of this research was to study the diversity and abundance of hymenoptera in the Forest Area with Special Purpose/KHDTK Aek Nauli, Simalungun Regency, North Sumatra, Indonesia. The insect sampling was conducted during the day and night using yellow and light trap technique. The results obtained a total of 13 species of Hymenoptera consisting of 45 ind. The relative abundance was recorded from 2.22 to 22.22 with the highest abundance from Vespula sp (Vespidae) and Sceliphron curvatum (Spechidae). The highest Importance Value Index (IVI) of Hymenoptera species was documented from Brachymyrmex sp. (Formicidae) at 115.56 and Polybia fastidiosuscula (Vespidae) at 106.67. The Shannon’s diversity (H’) of Hymenoptera ranged between 0.89 and 1.83 among sites or categorized as low-to-medium level of biodiversity with an evenness index (E) from 0.64 to 1.00. This finding may be noted as our first attempt in documenting the beta diversity of insects in the forest region.

Published
2022

40. Fast and Radiation Hard Inorganic Scintillators for Future HEP Experiments

Author

C Hu, L Zhang, and R-Y Zhu

Subjects
History, Computer Science Applications, Education
Abstract

Future HEP experiments at the energy and intensity frontiers require fast and ultrafast inorganic scintillators with excellent radiation hardness to face the challenges of unprecedented event rate and severe radiation environment. We report recent progress in fast and ultrafast inorganic scintillators for future HEP experiments. Examples are LYSO crystals and LuAG ceramics for an ultra-compact shashlik sampling calorimeter for the HL-LHC and the proposed FCC-hh, and yttrium doped BaF2 crystals for the proposed Mu2e-II experiment. Applications for GHz hard X-ray imaging will also be discussed.

Published
2022

41. Investigation of Under-Relaxation Factors in 2D Dam Break Simulation of OpenFOAM®

Author

R Widiatmono, R S N Mahmudah, I Hidayat, K A Nugroho, and R Y Apriansari

Subjects
History, Computer Science Applications, Education
Abstract

Computational fluid dynamics (CFD) is one of the most significant applied sciences in the industry. For this reason, many expensive CFD software is available in the market. OpenFOAM® is a free CFD software that has been used extensively in many ranges of fields. But, even with the free charge, it is still hard to get a good result with OpenFOAM® without extensive computational resources. This study aims to find a way to get good results with minimum computation time by investigating the under-relaxation effects. This study chose the dam break case due to its simple and readily available validation data. The simulation domain was a 200 × 200 mm2 dam filled with 50 × 100 mm2 water in the dam’s bottom left corner. The simulations were performed with under-relaxation factors, ranging from 0.3 to 1. By changing the under-relaxation factor to 0.95, the mean absolute percentage error became six times smaller, and the simulation was 366 times faster. It shows that the under-relaxation factor is essential in the quality of results and simulation time. However, the most optimal under-relaxation factor may differ from one case to another.

Published
2022

42. Indoor Wireless Multipaths Outlier Detection and Clustering

Author

J Blanza, X E Cabasal, J B Cipriano, G A Guerrero, R Y Pescador, and E V Rivera

Subjects
History, Computer Science Applications, Education
Abstract

Wireless communication systems have grown and developed significantly in recent years to fulfill the growing demand for high data rates across a wireless medium. Channel models have been used to develop various sturdy wireless systems for indoor and outdoor applications, and these are simulated in the form of datasets. The presence of outliers in clusters has been a concern in datasets, as it affects the standard deviation and mean of the dataset which reduces the data accuracy. In this study, the outliers in the Cooperation in Science and Technology (COST) 2100 MIMO channel model dataset were shifted to the means of the clusters using the Mean Shift Outlier Detection method. Afterward, the data is clustered using simultaneous clustering and model selection matrix affinity (SCAMSMA). The Mean Shift Outlier Detection method identified 52 and 46 multipaths as outliers and improved the clustering accuracy of the indoor scenarios by 3.5% and 0.93%, respectively. It also increased the precision of the clustering based on the decrease in standard deviation of the Jaccard indices from 0.2435 to 0.1807 and 0.3038 to 0.2075.

Published
2022

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