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Vladimir Mikhailovich Levin ◽  
Ammar Abdulazez Yahya ◽  
Diana A. Boyarova

Power transformers are one of the most important and complex parts of an electric power system. Maintenance is performed for this responsible part based on the technical condition of the transformer using a predictive approach. The technical condition of the power transformer can be diagnosed using a range of different diagnostic methods, for example, analysis of dissolved gases (DGA), partial discharge monitoring, vibration monitoring, and moisture monitoring. In this paper, the authors present a digital model for predicting the technical condition of a power transformer and determining the type of defect and its cause in the event of defect detection. The predictive digital model is developed using the programming environment in LabVIEW and is based on the fuzzy logic approach to the DGA method, interpreted by the key gas method and the Dornenburg ratio method. The developed digital model is verified on a set of 110 kV and 220 kV transformers of one of the sections of the distribution network and thermal power plant in the Russian Federation. The results obtained showed its high efficiency in predicting faults and the possibility of using it as an effective computing tool to facilitate the work of the operating personnel of power enterprises.

2022 ◽  
Vol 165 ◽  
pp. 108336
Mian Zhang ◽  
Decai Li ◽  
KeSheng Wang ◽  
Qing Li ◽  
Yue Ma ◽  

Kumrawat Kajal ◽  
Tiwari Archana

Sacubitril/valsartan, traded under the brand name Entresto between others, is a fixed-dose combination medication for use heart failure. Sacubitril is a neprilysin inhibitor (A prodrug) and is used in combination with valsartan to reduce the risk of cardiovascular events in patients with chronic heart failure. It is anti - hypertensive drug. Valsartan is an Angiotensin Receptor Blocker (ARB) that may be used to treat a variety of cardiac conditions including hypertension, diabetic nephropathy and heart failure. Two UV-spectrophotometric methods have been developed and validated for simultaneous estimation of Sacubitril and Valsartan in a tablet dosage form. The first method employed solving of simultaneous equations based on the measurement of absorbance at two wavelengths, 226.0 nm and 254.0 nm, 𝜆max for Sacubitril and Valsartan, respectively. The second method was absorbance ratio method, which involves formation of Q-absorbance equation at 240 nm (isoabsorptive point) and also at 254 nm (𝜆max of Valsartan). The methods were found to be linear between the range of 4-12 𝜇g/mL for Sacubitril and 2-10 𝜇g/mL for Valsartan using Methanol as solvent. The mean percentage recovery was found to be 96.68%and 101.89% for the simultaneous equation method and 100.2% and 104.53% for the absorbance ratio method, for sacubitril and valsartan respectively. It could be concluded from the results obtained in the present investigation that the two methods for simultaneous estimation of sacubitril and valsartan in tablet dosage form are simple, rapid, accurate, precise and economical and can be used, successfully, in the quality control of pharmaceutical formulations and other routine laboratory analysis. The reviewed highlights various analytical techniques such as high-performance liquid chromatography (HPLC), ultra- performance liquid chromatography (UPLC), UV Spectroscopy, high per-formance thin layer chromatography (HPTLC), liquid chromatography coupled to tandem mass spectrometry (LC- MS), RP-HPLC and other chromatographic method used. The combination of these drugs with different method was examine and the commonly use of the drugs in hypertensive.

2022 ◽  
pp. 1420326X2110650
Li Bai ◽  
Huageng Dai ◽  
Jun Wang ◽  
Guangming Li

In extremely cold areas with long winter months and exceptionally cold weather, classrooms are inadequately ventilated, resulting in the continuous accumulation of indoor air pollutants that may endanger human health. This article uses adsorption tube sampling-thermal desorption-gas chromatography mass spectrometry to analyze the type and concentration of volatile organic compounds (VOCs) in the classroom. The source analysis and health risk assessment were performed, and the real-time concentration of total volatile organic compounds (TVOC) was computed using the multifunctional ventilation. The result shows that the air in the classroom contains 25 kinds of VOCs. Among them, the carcinogenic risk value of seven kinds of VOCs (3.40 × 10-5) exceeds the acceptable risk value (1 × 10-6) given by the U.S. Environmental Protection Agency (US EPA). There are 17 kinds of VOCs that pose a certain non-carcinogenic risk to the human body. After quantitative analysis by the principal component analysis (PCA) and the characteristic quantity concentration ratio method, human activities, furnishings, outdoor penetration, etc., were found to be main sources of VOCs in the classroom. In addition, TVOC concentration is directly proportional to class time. In winter, classrooms in severely cold areas must take necessary measures to reduce the concentration of VOCs and ensure students' health.

Energies ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 328
Roberto Bruno ◽  
Piero Bevilacqua ◽  
Daniela Cirone ◽  
Stefania Perrella ◽  
Antonino Rollo

The Trombe wall is a passive system used in buildings that indirectly transfers thermal energy to the adjacent environment by radiation and convection, and directly by the thermo-circulation that arises in the air cavity delimited between a transparent and an absorbing surface. Nevertheless, the latter is painted black to increase the energy gains, but this produces a negative visual impact and promotes the overheating risk in summer. To mitigate these aspects, a hybrid Trombe wall equipped with PV panels can be employed. The PV installation results in a more pleasing wall appearance and the overheating risk reduces because part of the absorbed solar radiation is transformed into electricity. To determine the actual performance of a such system, transient simulation tools are required to consider properly the wall thermal storage features, variation of the optical properties, air thermo-circulation, and PV power production. Alternatively, regarding the traditional Trombe wall, the literature provides a simplified empirical method based on the dimensionless parameter solar load ratio (SLR) that allows for preliminary evaluations and design. In this paper, the SLR method was calibrated to determine the monthly auxiliary energy to be supplied in buildings equipped with PV-Trombe walls in heating applications. The SLR method was tuned by a multiple linear regression by data provided by TRNSYS simulation that allowed to obtain the energy performances in actual conditions of PV-Trombe walls installed on the same building but located in different localities. The comparison between the TRNSYS results and the calibrated SLR method determined average errors ranging between 0.7% and 1.4%, demonstrating the validity of the proposed methodology.

2022 ◽  
Xiaolong Deng ◽  
Guangji Sun ◽  
Naiwu He ◽  
Yonghua Yu

Abstract A new model, integrating information theory, fractal theory and statistical model for accurate landslide susceptibility mapping (LSM) at regional scales, has been proposed. In this model, landslide conditional factors are firstly classified with an optimal number of classes, which is determined by maximizing their information coefficients estimated from Shannon’s entropy model. The spatial association between influencing factors and induced landslides has been measured by introducing the variable fractal dimension method (VFDM). The VFDM approach fully considers the characteristics of landslide fractal distribution. Then the fractal dimensions (\(D\)) are calculated to provide multiple factors with various numerical weights. The proposed model eventually combines the landslide frequency ratio (\(fr\)) of each factor with corresponding weight to achieve spatial prediction of landslides, illustrated by an example area in China. In the study area, 500 landslides have been identified by aerial photograph interpretation, extensive field investigations, historical and bibliographical landslide data. In the model, these landslides are randomly split into a training dataset (70 %)and a validating dataset (30 %) Seven factors are recognized and analyzed by frequency ratio (FR) method, including lithology, distance to fault, altitude, slope, aspect, distance to stream and distance to the road. The receiver operating characteristic curve (AUROC) has been adopted to compare and validate the model results. Results show that the proposed landslide model achieved a more accurate prediction with AUROC equal to 0.8467, over-performing than the conventional frequency ratio method (AUROC=0.8088). According to the final prognostic landslide susceptibility map, 16.37 % f the study area shows very high and high susceptibility, accounting for 63.55 % f the entire landslides. Evaluation of relative factor importance based on a one-by-one factor removal test indicates that the lithology factor contributes unique information for landslides. In conclusion, the example demonstrates that the proposed framework is promising for further improvement of LSM.

Naihao Liu ◽  
Shengtao Wei ◽  
Yang Yang ◽  
Shengjun Li ◽  
Fengyuan Sun ◽  

2022 ◽  
Vol 11 (1) ◽  
pp. 1-17
Shuai Li ◽  
Jingjing An ◽  
Jiangxia Nan

The compromise ratio method (CRM) is an effective method to solve multiple attribute group decision making (MAGDM). Distance measure of intuitionistic fuzzy (IF) numbers (IFNs) is important for CRM. In this paper, according to the IF distance of IFNs, an extended compromise ratio method (CRM) is developed for (MAGDM) problems which attribute weights and evaluation values of alternatives on attributes are expressed in linguistic variables parameterized using TIFNs. Finally, the effectiveness and practicability of the extended CRM with IF distance are demonstrated by solving a software selection problem.

2021 ◽  
Vol 6 (2) ◽  
pp. 112
Thema Arrisaldi ◽  
Wahyu Wilopo ◽  
Teuku Faisal Fathani

Landslide often occurred in Tinalah watershed, Kulon Progo District, every year. The frequency of landslide events is increasing after high rainfall intensity. Some factors control landslides such as slope gradient, land use, geological structure, slope hydrology, and geological condition. This research has an objective to develop the susceptibility map of Tinalah watershed and to identify the rainfall threshold to trigger a landslide. The development of the susceptibility map using frequency ratio method with four parameters including slope, type of rock, land use, and lineament density. The landslide data were collected during the field survey and from regional disaster management authority (BPBD) Kulon Progo. Rainfall data were collected from BMKG and GSMap. Soil analysis also was conducted to develop a numerical model to verify the rainfall threshold value. The result shows a high susceptibility of the landslide area is dominated in Tinalah watershed. The rainfall threshold for the low susceptibility of the landslide zone is I=490.14 D-1.404with 5-7 days antecedent rain. The rainfall threshold for medium susceptibility map is I=164.32D-0,689 3-7 days antecedent rain. Moreover, the rainfall threshold for the high susceptibility of the landslide zone is 111.62 D-0.779, with 2-7 days antecedent rain.

Agronomy ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 52
Xi Sun ◽  
Jie Li ◽  
Donald Cameron ◽  
Gregory Moore

The measurement of sap movement in xylem sapwood tissue using heat pulse velocity sap flow instruments has been commonly used to estimate plant transpiration. In this study, sap flow sensors (SFM1) based on the heat ratio method (HRM) were used to assess the sap flow performance of three different tree species located in the eastern suburbs of Melbourne, Australia over a 12-month period. A soil moisture budget profile featuring potential evapotranspiration and precipitation was developed to indicate soil moisture balance while the soil-plant-atmosphere continuum was established at the study site using data obtained from different monitoring instruments. The comparison of sap flow volume for the three species clearly showed that the water demand of Corymbia maculata was the highest when compared to Melaleuca styphelioides and Lophostemon confertus and the daily sap flow volume on the north side of the tree on average was 63% greater than that of the south side. By analysing the optimal temperature and vapour pressure deficit (VPD) for transpiration for all sampled trees, it was concluded that the Melaleuca styphelioides could better cope with hotter and drier weather conditions.

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