Physical Characteristic Parameters Research Articles

Identification method for inter-turn faults in transformers based on digital twin concept

A transformer inter-turn fault identification method is proposed based on the digital twin concept to tackle the challenges of high operational complexity and low accuracy associated with traditional transformer fault identification methods. Initially, the Bald Eagle Search algorithm is employed to optimize the critical parameters of the Extreme Learning Machine (ELM), determining the optimal input layer weight and hidden layer threshold of the Extreme Learning Machine. Subsequently, leveraging the digital twin concept, a digital replica of the physical transformer is established, enabling multi-physical field coupling simulation encompassing electrical, thermal, and acoustic domains to elucidate the variation patterns of various physical parameters across different operational scenarios and fault scenarios. Furthermore, key physical characteristic parameters such as sound pressure and winding hot spot temperature are carefully selected to drive a fault identification model tailored to inter-turn faults within the framework of the digital twin concept. Through a detailed investigation using 630 kV A/10 kV transformers as a case study, the results exhibit an impressive fault identification accuracy of 95.24% for the proposed method. Comparative analysis reveals notable enhancements in fault identification accuracy of 12.22%, 7.85%, and 3.73% for ELM, Support Vector Machine and Tuna Swarm Optimization—ELM models, respectively. These findings underscore the effectiveness and practicality of the transformer inter-turn fault identification method based on the digital twin concept, offering valuable insights for the real-time monitoring and diagnosis of inter-turn faults in transformers.

Physical Characteristics of Fishbone Gelatin (Gel Strength, Viscosity, and pH): Review

Gelatin is a polypeptide molecule derived from collagen, the main protein that forms the skin and bones in animals. Gelatin serves various functions in the food industry, acting as a stabilizer, whipping agent, gel-former, and binder agent. Research on utilizing fish bones for gelatin production has been widely conducted. Gel strength, viscosity, and pH are some of the physical characteristic parameters of fish bone gelatin. Gelatin's ability to transition between the gel and sol phases, or its reversible nature, is reflected in its gel strength. Viscosity of gelatin reflects the molecule's ability to flow in solutions, whether they are simple organic liquids or dilute suspensions, playing a crucial role in maintaining emulsion stability. The acidity level (pH) in fish bone gelatin is influenced by the pH of the hydrolysis or extraction solution, while the source of gelatin, acidity level, extraction method, temperature, and duration also impact the gel strength and viscosity values. Therefore, there is a need for a study on the physical characteristics such as gel strength, viscosity, and pH of fish bone gelatin.

Deep learning-driven underwater polarimetric target detection based on the dispersion of polarization characteristics

Underwater target detection especially in turbidity environments is a crucial and challenging area of study due to its extensive applications. In this work, we propose an underwater target detection method that combines the dispersion of polarization characteristics with a neural network framework. The polarization dispersion distribution features are effective at reducing the influence of the scattering effect of particulate matter in a turbidity environment, and highlighting the polarization state variations, especially in the edge contour features between the target and background. According to the physical detection model of dispersion of polarization characteristics, the neural network is constructed to extract dispersion values of the angle of polarization (AOP) and degree of linear polarization (DOLP) from the underwater polarization image datasets with different turbidity levels, which we then used to train the network to map physical characteristic parameters of the target for the detection. When compared to target detection methods based on light intensity images and polarization characteristic images (AOP and DOLP), the experimental results indicate that the proposed network model with polarization dispersion images has a significant improvement in locating and identifying targets of different materials, particularly in high turbidity underwater environments. These results provide deeper understanding of polarization polarimetric target detection, and further improve the functionality of a polarimetric target detection optical system.

Technological feature of hypan-acid treatment

The paper considers one of the effective methods of cleaning the well filter from various impurities and deposits – injection of hypanic acid. The technology of implementation of this promising type of treatments has been studied and the chemical compositions and their concentrations used in modern conditions of oil field development have been comprehensively studied. The results of laboratory studies to determine the optimal chemical composition for various tectonic and stratigraphic sites are presented. By screening and analyzing field experiments on injection of hypanoic acid, a number of recommendations have been formed concerning the issues of effective alignment of the pick-up profile: boundary parameters of geological and physical characteristics of productive formations have been determined, at which technological indicators of treatments will be the highest; a positive effect on the dynamics of changes in the indicator of water content of extracted products has been revealed, which significantly expands the scope of this technology. According to the results of the study, the use of this method of cleaning the bottom-hole formation zone is recommended for many deposits of the Russian Federation.

A novel in-depth intelligent evaluation approach for the gas drainage effect from point monitoring to surface to volume

Developing a comprehensive and intelligent evaluation approach for dynamic gas extraction parameters is especially important for the operation and management of gas drainage in coal mines. However, existing approaches lack an in-depth intelligent evaluation approach for acquiring surface parameters of gas flow and volume characteristic parameters of the entire drainage area from the finite monitoring data. To fill this gap, a novel Field-Zone-Network model as a unique approach were presented to overcome the above-mentioned challenges, with innovative multi-parameter solution and inversion models. It utilized advanced mathematical algorithms for parameter estimation of gas drainage, by integrating the finite monitoring points data of pipe network and physical characteristic parameters of pipe network and coal seam. The model's accuracy and reliability were validated through rigorous comparisons with field data collected from coal mines and numerical simulations conducted in simulated scenarios. It realized the sufficient mining of finite monitoring data from points (monitoring points) to surface (network) to volume (coal seam). Further, the newly comprehensive software was developed to enable real-time monitoring, analysis, and evaluation of gas drainage effect, providing valuable insights for optimizing extraction operations in coal mines. This research contributes to the advancement of gas drainage in coal mines by presenting a novel Field-Zone-Network model and comprehensive software, empowering efficient and intelligent gas extraction operations with enhanced monitoring and evaluation capabilities.

Experimental Study on the Electrical Resistivity Characteristics of Uniformly Graded Calcareous Sand

The resistivity of calcareous sand is one of its inherent physical characteristic parameters, and the study of the resistivity characteristics of calcareous sand is of great significance in the subsequent study of the relationship between the resistivity of calcareous sand under different loads and its mechanical properties. This study uses alternating current (AC) electrical resistance testing equipment based on the two-electrode method to study the effects of pore water, temperature, relative density, saturation, and other factors on the resistivity of calcareous sand. We used the experimental results to analyze in detail the effects of various influencing factors on the resistivity of calcareous sand and established a relationship between them. Research has shown that as the temperature increases, the conductivity of the medium in the solution increases and the resistivity decreases. The resistivity of the calcareous sand of the three size fractions decreases with increasing saturation, and the relationship between them is a power function. The resistivity of saturated calcareous sand with three size fractions increases with increasing density, and the two show a good linear relationship. The results of this research can provide support for the study of the relationship between the resistivity and mechanical properties of calcareous sand under different loads.

Investigation of the surface layer of wheel steel by indentation method

The article considers methods of measurement of microhardness and modulus of elasticity of plasma hardened wheel steel by kinetic indentation method. It provides features of measurement of microhardness, modulus of hardness, elastic recovery, influencing on wear resistance of surface layers of steel. Measurement of these characteristics of material allows estimating and choosing optimum technology of surface modification by surface plasma hardening. It is confirmed that objectivity of determination of microhardness, modulus of elasticity, elastic recovery and flow stress depends on strict observance of imprint depth requirements depending on thickness of hardened layer. It is noted that in spite of the increased amount of factual information, obtained by indentation method, the physical substantiation of hardness micro-mechanisms remains poorly understood, which necessitates substantiation of physical representations of the nature of hardness of metallic materials. It is established that the measurement of microhardness, elastic modulus and elastic recovery by the kinetic indentation method is expedient to use for certification of the surface layer of plasma-hardened wheel steel according to the parameters of physical and mechanical characteristics.

Green emission characteristics of Er3+ -doped TeO2-WO3-GeO2 glasses through up and down conversion processes

Different concentrations of Er3+ions doped TeO2-WO3-GeO2 transparent oxyfluoride glassy materials were fabricated by conventional melt quench method and analyzed through X-ray diffraction, Fourier Transform infrared, scanning electron microscope and energy dispersive X-ray, photoluminescence-excitation, visible emission and luminescence decay studies. Various physical, structural, spectroscopic and laser characteristic parameters were evaluated following the Judd-Ofelt theory. The studied glasses were capable of emitting intense green luminescence through (2H11/2,4S3/2) → 4I15/2 transitions. The emission of green luminescence was studied through down-conversion process at 377 nm excitation and up-conversion process at 980 nm excitation. The color coordinates were found to fall in the green region of chromaticity diagram and close to the European Broadcosting Union green illuminant. The evaluated branching ratio, stimulated emission cross-section, gain linewidth, figure of merit and the quantum efficiency corresponding to 4S3/2 → 4I15/2 transition suggests that the studied glasses find wide suitability to design green emitting solid state lighting devices.

An Application of Elastic-Net Regularized Linear Inverse Problem in Seismic Data Inversion

In exploration geophysics, seismic impedance is a physical characteristic parameter of underground formations. It can mark rock characteristics and help stratigraphic analysis. Hence, seismic data inversion for impedance is a key technology in oil and gas reservoir prediction. To invert impedance from seismic data, one can perform reflectivity series inversion first. Then, under a simple exponential integration transformation, the inverted reflectivity series can give the final inverted impedance. The quality of the inverted reflectivity series directly affects the quality of impedance. Sparse-spike inversion is the most common method to obtain reflectivity series with high resolution. It adopts a sparse regularization to impose sparsity on the inverted reflectivity series. However, the high resolution of sparse-spike-like reflectivity series is obtained at the cost of sacrificing small reflectivity. This is the inherent problem of sparse regularization. In fact, the reflectivity series from the actual impedance well log is not strictly sparse. It contains not only the sparse major large reflectivity, but also small reflectivity between major reflectivity. That is to say, the large reflectivity is sparse, but the small reflectivity is dense. To combat this issue, we adopt elastic-net regularization to replace sparse regularization in seismic impedance inversion. The elastic net is a hybrid regularization that combines sparse regularization and dense regularization. The proposed inversion method was performed on a synthetic seismic trace, which is created from an actual well log. Then, a real seismic data profile was used to test the practice application. The inversion results showed that it provides an effective new alternative method to invert impedance.

Structure Size Optimization and Internal Flow Field Analysis of a New Jet Pump Based on the Taguchi Method and Numerical Simulation

Interlayer contradiction (high-pressure oil that prevents low-pressure oil from being extracted) has always been the main factor affecting the oil-recovery efficiency of the many oil-bearing series in shale oil wells in Eastern Shandong, China. If steps to deal with interlayer contradiction are not taken, Shengli Oilfield’s oil-recovery efficiency will be significantly reduced after a certain period of exploitation. Furthermore, as the drilling depth increases, the formation-fluid supply capacity of Shengli Oilfield becomes worse and further increases the difficulty of oil recovery as well as production costs. In order to improve the oil-recovery efficiency of shale oil wells in Eastern Shandong and realize cost reductions and efficiency increases, we designed a new jet pump in this study. The pump can be used for oil recovery according to the principle of Venturi jet propulsion, as the required power fluid is not a high-pressure fluid injected from the ground, but rather high-pressure oil that is present in the formation. Through the analysis of the overall structure of the new jet pump, it was found that the pump could not only transform the existing interlayer contradiction (co-mining of high and low oil layers by utilizing interlayer contradiction), but also had the characteristics of a simple structure and low production costs. Since the structural dimensions of the jet pump and the physical characteristic parameters of the fluid have significant impacts on pump efficiency, we first analyzed the internal flow field of the jet pump by using numerical simulations and found that the throat–nozzle distance, area ratio, throat length–diameter ratio, diffuser angle, and flow ratio had the most significant impacts on pump efficiency. After obtaining the specific numerical range of the abovementioned structural parameters when the pump efficiency was as its maximum, an orthogonal array designed according to the Taguchi method was used to conduct experiments. According to a range analysis and an analysis of variance, at an unchanged flow ratio (0.3156), the new jet pump achieved the highest efficiency (31.26%) when the throat–nozzle distance was 2.62 mm, the throat length was 46 mm, the throat diameter was 6.8 mm, and the diffuser angle was 7.5°. In comparing its efficiency with that before optimization, we noticed that the efficiency was significantly improved by about 10%. These research results not only offer a new idea for the existing oil-recovery mode, but also introduce a new method for optimizing the structure of jet pumps.

Fracture mechanism and separation conditions of pineapple fruit-stem and calibration of physical characteristic parameters

Fracture mechanism and separation conditions of pineapple fruit-stem and calibration of physical characteristic parameters

Calibration of Physical Characteristic Parameters of Granular Fungal Fertilizer Based on Discrete Element Method

Based on a combination of physical and simulation experiments, a set of basic physical characteristic parameters and contact parameters suitable for granular fungal fertilizers were calibrated, which up to now have received little attention. The physical morphological characteristic parameters (overall dimension, 1000 grain weight, density, and moisture content), mechanical characteristic parameters (Poisson’s ratio, elastic modulus, and shear modulus), and contact parameters (static friction coefficient, rolling friction coefficient and recovery coefficient) of particles were measured through physical experiments. The parameters were screened for significance using the Plackett–Burman test. The results showed that the impact recovery coefficient, static friction coefficient, and rolling friction coefficient for the granular fungal fertilizer particles had a significant effect on the repose angle. The best range for the three parameters was determined using the steepest climbing test. The second-order regression model was optimized using the Box–Behnken design test. The relative error between the simulated repose angle (21.74°) and the physical test repose angle (21.84°) was small (0.50%). These optimal parameters obtained by calibration can provide a basis for the simulation analysis and parameter optimization of variable-rate fertilization systems.

Dynamic Characteristics and Effect on Thrust of Jet Tail Vortex Ring for Pump Jet Propulsion

When a pump is propelled by a propeller, the nozzle flooding of the jet wake area will produce a turbulent quasi-sequence structure and have a certain impact on the outflow field structure and thrust characteristics of the water jet propulsion pump. In this paper, a method that combined numerical simulation with vortex dynamics is adopted, which analyzes the dynamic characteristics and influence on the thrust characteristics of the water jet propulsion pump. A large eddy simulation turbulence model and a dimensionless water jet propulsion pump velocity coefficient were used to reveal flow structure and relation, with the pump operation parameters of the wake vortex ring. The thrust with a trailing vortex ring is 7.0% higher than that without a trailing vortex ring. Vortex dynamics and mathematical statistics are combined to quantitatively analyze the dynamic characteristics of the jet tail vortex ring. Finally, the formation time of the vortex ring is obtained in exponential relation with dimensionless transmission velocity and vorticity coefficient, which has nonlinear relation with vortex intensity coefficient and helicity coefficient. BP Neural Network combined with the LM algorithm is used to establish the mathematical relationship between the thrust and the physical characteristic parameters of the vortex ring.

Mechanical vibration modeling and characterization of a plastic-cased lithium-ion battery

Batteries often show the coupling change of multiple physical field characteristic parameters in the charging or discharging processes. Conventional battery modeling and characterization methods mainly focus on electrical or thermal parameters. Considering that battery state change can cause a change in the mechanical structure, research on the vibration characteristic modeling and characterization of a plastic-cased lithium-ion battery is carried out. By analyzing the mechanical structure of the battery, the first principles modeling method is selected to model the battery's mechanical performance. The vibration data in the process of battery charging and discharging are measured by a laser Doppler vibrometer (LDV). The obtained experimental data are used to identify the mechanical parameters of the battery. Based on the experimentael results, the root mean square error (RMSE) of the frequency domain amplitude fitting result of the model is less than 11.36%. The effectiveness of the battery mechanical vibration model is verified. The model and the characterization method provide tools for nondestructive battery state evaluation.

Reduction of turbidity by adding bio coagulant-A sustainable approach

Improper management of human developmental activities such as industrialization and haphazard urban development deteriorating the quality parameters of Surface Water sources beyond the permissible limits. Turbidity in water, a major physical characteristic parameter is highly increasing due to the presence of suspended, colloidal, dissolved solids and making the water resources anaesthetic in condition. The chemical coagulants like Alum, Ferric Sulphate are widely used in turbidity treatment processes. Present study aimed sustainable approach to reduce turbidity by adding Neem (Azadirachta indica) leaf powder as bio coagulant along with Alum (Aluminum Potassium Sulphate). Laboratory investigation was done for the sample from Hussain sagar lake, Telangana, India and analysed the obtained turbidity results. Optimum dosage of neem leaf powder along with Alum has been determined by Jar Test Apparatus to increase the efficiency of treatment. The dose of bio coagulant used was 0.1 to 1gr per Litre. It has been observed that the bio coagulant is efficient in reducing turbidity upto 94.8% when it was added with reduced dosages of Alum. This paper explains sustainable method of reducing turbidity by using neem leaf powder as bio coagulant along with Alum.

Glass formation, physical and structural investigation studies of the (90-x) Sb2O3-10WO3-xNaPO3 glasses

The new series of SWN glasses were examined with the formula (90–x) Sb2O3–10WO3–xNaPO3 glasses (x ranging from 10 to 70). Certain thermal, physical, mechanical, and structural properties have been tested. The DSC curves confirmed the glassy nature as well as the thermal stability of our glasses. The Vickers hardness, modulus of elasticity and Raman spectroscopy were put to the test. The increase in elastic moduli and physical characteristic parameters is associated with an increase in the stiffness and a change in the structural network of the glass system with the addition of NaPO3 content by the forming of a P-O-M bridge (M=P, Sb or W), which increases the network connectivity and contributes to an increase in the glass transition temperature and elasticity modulus. This could be due to the polymerization of the glass network as a result of the high concentration of PO4, which acts as a bridge between them and is confirmed by Raman spectroscopy. To establish the similarity between the theoretical and observed results of elastic moduli and Poisson's ratio in our glasses, Mackenzie's Makishima theory was used. Our system has many colors (yellow, blue, transparent), which are related to an increase (reduction) or decrease (oxidation) in the number of electrons in the atomic system of such materials.

Evaluation of Physical Characteristics of Typical Maize Seeds in a Cold Area of North China Based on Principal Component Analysis

The physical properties of maize seeds are closely related to food processing and production. To study and evaluate the characteristics of maize seeds, typical maize seeds in a cold region of North China were used as test varieties. A variety of agricultural material test benches were built to measure the maize seeds’ physical parameters, such as thousand-grain weight, moisture content, triaxial arithmetic mean particle size, coefficient of static friction, coefficient of rolling friction, angle of natural repose, coefficient of restitution, and stiffness coefficient. Principal component and cluster comprehensive analyses were used to simplify the characteristic parameter index used to judge the comprehensive score of maize seeds. The results showed that there were significant differences in the main physical characteristics parameters of the typical maize varieties in this cold area, and there were different degrees of correlation among the physical characteristics. Principal component analysis was used to extract the first three principal component factors, whose cumulative contribution rate was over 80%, representing most of the information of the original eight physical characteristic parameters, and had good representativeness and objectivity. According to the test results, the classification standard of the evaluation of the physical characteristics of 15 kinds of maize seeds were determined, and appropriate evaluations were conducted. The 15 kinds of maize seeds were clustered into four groups by cluster analysis, and the physical characteristics of each groups were different. This study provides a new idea for the evaluation and analysis of the physical properties of agricultural materials, and provides a new method for the screening and classification of food processing raw materials.

Research on the Physical Characteristic Parameters of Banana Bunches for the Design and Development of Postharvesting Machinery and Equipment

In the operations of the banana postharvesting process, the design and development related to the dehanding machine, the cutting and crushing machine of bunch stalks, and the fiber extraction machine of bunch stalks are in the initial stages. In addition, with the development of society and urbanization, the aging populations in hilly and mountainous areas, where bananas are planted, are becoming a more and more serious problem. The basic physical characteristic parameters of banana bunches, banana hands, and bunch stalks are the basis for studying their biomechanical properties and designing and developing the corresponding mechanical equipment. We measured the diameter, thickness of rind, curvature, density, moisture content, diameter of vascular bundle, weight of bunch stalk, and axial distance and circumferential angle of Brazilian and plantain banana hands using experiments and statistical analysis. Through the combination of physical experiments and numerical statistics, we obtained the value range and changing law of the physical characteristic parameters of banana bunches.

Optimization of Gelling Agents and Emulsifiers in Emulgel Bases, and Physical Evaluation of Emulgel containing Sepabang (Melastoma malabathricum L.) Leaves Extract

Sepabang (Melastoma malabathricumshot L.) leaf contains a group of phenolic compounds and has a very strong antioxidant activity so it is potentially to be developed in the form of pharmaceutical preparations. The purpose of this research is to optimize and formulate an emulgel containing Sepabang leaf extract that physically stable. Emulgel preparations are formulated using carbopol and hydroxyprophylmethylcellulose as gelling agents and Tween 60 – Span 60 and combination of triethanolamine and stearic acid as emulsifiers, with a concentration of methanol extract of Sepabang leaves of 0.25%. Physical characteristics of emulgel preparations include pH value, viscosity determination, and spreadability test evaluated at room temperature for 4 weeks. The physical stability test is done by the Freeze Thaw method for 6 cycles, of which 1 cycle consists of 48 hours at 4°C and 48 hours at 40°C. The results showed that the Sepabang emulgel that meet physical characteristic and stability parameters are F1 with HPMC as gelling agents and Tween 60-Span 60 3% as emulsifiers.

Fabrication, physical characteristic, and gamma-photon attenuation parameters of newly developed molybdenum reinforced bismuth borate glasses

To observe the direct effect of molybdenum reinforcement on nuclear radiation shielding properties, a detailed investigation was performed with a group of bismuth borate glasses. Accordingly, glass samples with the nominal compositions (65-x)B2O3 + 20Bi2O3 + 15Na2O + xMoO3: x = 0, 1.5, 3, 4.5, 6 and 7.5 wt% have been synthesized by the solid state conventional method. The samples were named as M0 (x = 0), M1 (x = 1.5), M2 (x = 3), M3 (x = 4.5), M4 (x = 6) and M5 (x = 7.5). Physical characteristics and gamma-photon attenuation properties of (M0-M5) glasses have been investigated via MCNPX simulation code and XCOM program. XRD patterns confirmed that M0-M5 glasses were in amorphous nature. The density of the prepared glasses increased from 4.4104 for M0 glass sample to 5.3012 gm cm−3, while molar volume decreased from 33.50083 to 28.92114 cm3 mol−1. The mass attenuation coefficient (μm) increased with the increment of MoO3 concentration in mol% and followed the order: (M0)μm < (M1)μm < (M2)μm < (M3)μm < (M4)μm < (M5)μm at all photon energies. The mean free path (MFP), half value layer (HVL), and tenth value layer (TVL) for the prepared glasses M0-M5 have the same trend and follow the order: (M5)MFP, HVL, TVL < (M4) MFP, HVL, TVL < (M3) MFP, HVL, TVL < (M2) MFP, HVL, TVL < (M1) MFP, HVL, TVL < (M1) MFP, HVL, TVL. The M5 glass sample (with maximum MoO3) achieved highest effective atomic number (Zeff)and equivalent atomic numbers (Zeq) values for all photon energy ranges (low-medium-high). Among all the glass samples, the exposure build-up factor (EBF) and energy absorption build-up factor (EABF) values for M5 glass sample with the highest MoO3 additive are minimum due to the low amount of photons accumulated. These results indicate that M5 glass sample theoretically provides maximum protection for gamma-rays among all the samples.