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The strategy production in intuitionistic fuzzy multi-attribute decision-making is influenced by various factors. More realistic data representations are needed to portray ambiguity under increasingly complex decision-making contexts. Firstly, this study proposes a new approach for ranking independent trapezoidal intuitionistic fuzzy numbers based on the risk attitudes of decision-makers. The proposed ranking approach incorporates the decision-makers' risk preferences and considers all possible values in the feasible domain. After that, a novel similarity measure between two independent trapezoidal intuitionistic fuzzy numbers is presented based on the three-segment projection. The constructed similarity measure uses the image structure of the data to reflect the variation of vagueness and then also combines deviation to achieve optimization. Moreover, this study improves the VIKOR method under the independent trapezoidal intuitionistic fuzzy environment (V-ITIFE) to solve the multi-attribute decision-making problems. Finally, a numerical example is presented to illustrate the applicability and efficiency of the V-ITIFE method. [ABSTRACT FROM AUTHOR]

An efficient Cherenkov oscillator with gigawatt phase-controlled super-radiance (SR) pulses is studied for the application of coherent summation systems. To obtain phase-controlled SR pulses, an ultra-short seed pulse is required to be injected into the interaction space from the direction of the collector, which substitutes the impact of the spontaneous emission from the front edge of the electron beam. It means that, for a conventional Cherenkov oscillator, the injection seed pulse and output gigawatt SR pulse need to share the same channel. Therefore, an additional quasi-optical reflection system is needed to separate these two signals. To optimize such a scheme, we introduce a front extractor near the reflector and an injection channel at the side of the collector, allowing the output and injection channels to be independent of each other. Particle-in-cell simulations reveal that as the diode voltage is 260 kV, the beam current is 3.5 kA, and the magnetic field is 0.42 T, a short SR pulse with peak power of 1.93 GW is obtained. The corresponding conversion factor (ratio of average output power and input DC power) is up to 2.12. When the seed pulse has a rise time of 0.3 ns and a width of 0.2 ns injection, the phase of the seed pulse and the initiated SR pulse are closely correlated with the accuracy of 0.17 rad as the power ratio is down to −25 dB. The advantages of high efficiency and phase control make the oscillator a promising device used for the miniaturization and practicability of coherent summation systems. [ABSTRACT FROM AUTHOR]

The following work is based on real-time temperature monitoring during the construction and during the operation of a dam. For this purpose, we have proposed a sensing model named: the “complex wireless sensors model (CWSM)” for measuring the value of different factors like temperature, humidity and pressure on the dam. The installation of the proposed model has been discussed with its wireless networking. The model contains five types of sensors i.e. humidity, temperature, pressure, sun and irradiance sensors for measuring the variation of different factors. The computation modeling of CWSM has been discussed in the paper. 3-D Finite Element method is used for thermal analysis. As the result, it is concluded that the wireless network will be more suitable for measuring and analyzing the effects of temperature, humidity, water pressure and solar radiation on the dam.

This paper represents the thermal analysis of an under-construction concrete dam. The temperature distribution of the Dasu dam was analyzed by the thermal and heat of hydration model in this case study. An exponential function was used for the heat of hydration because an adiabatic calorimetric test was not available for the concrete mixture in Dasu. Hydration heat is estimated at five, nine, and twenty-nine days. The temperature monitoring system was installed at the dam site to record the actual temperature and it was compared with the predicted temperature using formulas. It is also necessary to note that the cooling of concrete starts from the bottom with the help of piped water. To facilitate the grouting of contractions joint, was the purpose of post-cooling by piped water. Concrete cooling with the help of piped water is not modeled by thermal code. Therefore its evaluation of temperate was not possible to simulate at that starting stage. Let us compare the observed temperature and calculated it, for the middle blocks eight-nine and thirteen-fourteen the height of the blocks is 96.00 m and the cross-section is also the same. The value was the same for the observed temperature and calculated before applying post cooling. It was observed that air temperature also has influenced due to seasonal variation near dam surfaces. The study outcomes stand unlimited influence to notice the engineers proceed with distinct measures in the design and structure of the recent concrete dam for reducing the possibility of cracking in the structure and optimizing the construction schedules.

A concrete production system (CPS) fault in dam engineering is one of the important factors influencing dam construction quality, which may directly affect the concrete-pouring construction progress and construction efficiency of the dam, and can even cause construction quality defects in the dam body. Reasonable classification and identification are of great significance to ensure the construction progress and quality of concrete dams. In this study, based on the concrete production logs of multiple concrete dams and literature reviews, a fault classification system for a CPS is proposed by comprehensively considering its mechanical structure characteristics and operating characteristics. The faults of the CPS are divided into 4 large categories and 22 subcategories. Additionally, the causes of CPS faults are summarized as human factors, environmental factors, mechanical component service life factors, and other factors. Based on the grey correlation analysis (GCA) method, a fault identification model of the CPS is established. With the actual production system fault statistical data of Shatuo hydropower station, the correlation coefficients for the four types of faults and the four influencing factors are calculated to determine the key faults of the CPS. The research results of the case study show that the service life factors of mechanical components have the greatest impact on batching metering system faults and mixer faults, with high grey correlation degrees of 84.66% and 76.85%, respectively. Environmental factors have the greatest impact on material delivery system faults and pneumatic system faults, with high grey correlation degrees of 90.81% and 94.9%, respectively. This paper provides theoretical support for the realization of fault pattern recognition of CPSs and provides a guiding reference for targeted fault handling. [ABSTRACT FROM AUTHOR]