Complete Scheme Research Articles

Power Transformer Faults: Analysis, Classification and Protection

With the increase in power consumption, the safety of the power transformers has increased manifolds. Ideally, there should be a no-fault operation of power transformer which is yet to be achieved. The objective of this paper is to provide a complete protection scheme of power transformers. The faults are analysed and classified using Discrete Fourier Transform (DFT) and Wavelet Transform. The DFT based controller is used to detect inrush and fault currents. We have used wavelet transform and it has proven to be a very effective tool for detailed analysis of these transients. In addition, Fuzzy logic controller, with minimal computational complexity, is implemented for the differentiation of inrush, internal and external faults using the detailed coefficients obtained by wavelet analysis providing successful classification. On the basis of the obtained coefficients, we have developed a Rapid Prototype of FFT based algorithm on differential protection scheme of the transformer providing the speed between 1-15 msec as compared to 100msec as per the standards of IEEE. The obtained results show that our proposed approach is rapid and could protect the power transformer from faults with accuracy.

Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics

ABSTRACT Sweetness and acidity are the two most important indicators to evaluate cherry quality. In this research, hyperspectral imaging (380–1030 nm) technology was applied to visually detect the sweetness and acidity of cherry. To improve the imaging performance, two spectral pretreatment methods (wavelet transform, standard normal variable transformation and detrend), three feature selection methods (successive projection algorithm, genetic algorithm, and shuffled frog leaping algorithm), and four regression modeling methods (principal components regression, partial least squares regression, least square-support vector regression, convolutional neural network) were employed and compared. After the chemometrics related to hyperspectral imaging had been examined, the least square-support vector regression models based on the feature bands, which were selected by the shuffled frog leaping algorithm, showed the best performance, and the determination coefficients of prediction (R2 P) for cherry sugar content and acidity reached 0.976 and 0.906, respectively. Based on the spectral principal components, three classifiers were built to classify the maturity level: support vector machine, backpropagation neural network, and radial basis function neural network. Excellent results with a classification accuracy of 100% were obtained. This research provides a complete and useful scheme to evaluate the quality and classify the maturity of cherry.

Electronic structure, spectroscopic constants, and transition properties of NaC [formula omitted] diatomic species: An ab initio investigation

Diatomic species play a pivotal role in complex media, such as the interstellar and circumstellar media. Furthermore, there is a notable lack of information regarding NaC and its ions, NaC+ and NaC−, despite the pervasiveness of the carbon element (C) and the validated role of Na-bearing molecules as organic reagents or in catalytic processes. In this study, ab initio multi-reference calculations, including core valence and complete basis set schemes, were employed to accurately determine the potential energy curves (PECs), dipole moment functions (DMFs) and transition dipole moments (TDMs) of ten, three and ten low-lying electronic states energies, respectively, for NaC, NaC+ and NaC− diatomics species. The obtained results permitted the accurate determination of spectroscopic constants and vibrational transition properties, including vibrational level energies, Franck–Condon factors (FCFs), Einstein coefficients, absorption band oscillator strengths, vibrational transition energies and radiative lifetimes of allowed transitions. The predicted adiabatic ionisation energy value for NaC is 6.659 eV, while the vertical ionisation energy value is 6.676 eV. Similarly, the predicted adiabatic electron affinity value for NaC is 0.614 eV, while the vertical electron affinity value is 0.613 eV.

Comparative analysis of two novel chaotic systems, and validation of hybrid function projective and complete synchronization using active-adaptive control

Abstract This study investigates the nonlinear characteristics of two novel 3D-chaotic models using phase portraits, bifurcation diagrams, Lyapunov exponents, time series analysis, and Poincaré maps. Here, we have examined hybrid-function projective and complete synchronization schemes via adaptive and active control methods. Moreover, the performance of hybrid-function projective synchronization, utilizing sine, cosine, and exponential terms, is compared to complete synchronization through two control strategies. Our designed controllers ensure asymptotic global chaotic synchronization based on Lyapunov stability principles. We have also compared our results with other competitive schemes and validated the theoretical findings through simulations on the MATLAB platform.

The Influence of Temperature Disturbance on Space Inertial Sensors.

The TianQin program is an independently proposed space-borne detection initiative from China. The inertial sensor, as a crucial component, is susceptible to disturbances from temperature fluctuations, the impact of which on acceleration measurements remains elusive. Therefore, a comprehensive analysis on the influence of temperature disturbance is necessary to avoid errors in acceleration measurement. In this study, we proposed a complete scheme for calculating the level of acceleration noise. Based on the traditional temperature control scheme of using a heat pipe, we developed a systematic heat transfer simulation model to obtain the temperature signals. These signals can then be converted into the frequency domain and used to calculate the acceleration noise level within the target bandwidth. Our results indicate that, with a temperature control of 0.13 K/Hz1/2@1 mHz, the largest contributions to acceleration noise come from the outgassing effect, radiometer effect, and radiative pressure effect, in descending order. The total noise peak is 3.6×10-12 m/(s2⋅Hz1/2) at 1 mHz, which is more than three orders of magnitude higher than the TianQin target of 10-15 m/(s2⋅Hz1/2). This study provides new avenues for evaluating measurement errors and solutions for the TianQin program.

A method of nucleus image segmentation and counting based on TC-UNet++ and distance watershed

Nucleus segmentation and counting play a crucial role in many cell analysis applications. However, the dense distribution and blurry boundaries of nucleus make nucleus segmentation tasks challenging. This paper proposes a novel segmentation and counting method. Firstly, TC-UNet++ is proposed to achieve a global segmentation. Then, the distance watershed method is used to finish local segmentation, which separate the adhesion and overlap part of the image. Finally, counting method is performed to obtain information on the counting number, area and center of mass of nucleus. TC-UNet++ achieved a Dice coefficient of 89.95% for cell instance segmentation on the Data Science Bowl dataset, surpassing the original U-Net++ by 0.23%. It also showed a 5.09% improvement in counting results compared to other methods. On the ALL-IDB dataset, TC-UNet++ reached a Dice coefficient of 83.97%, a 7.93% increase over the original U-Net++. Additionally, its counting results improved by 16.82% compared to other approaches. These results indicate that our method has a more complete and reasonable nucleus segmentation and counting scheme compared to other methods.

Toward production zonal flow allocation using novel completion tracer dosing line and diffuser: Prototype laboratory flow loop experiments and computational fluid dynamics studies

Complex completion schemes with inflow control valves (ICVs) in multi-lateral wells are now the industry standard for modern fields. Understanding the production contributions from different production zones/laterals is of great importance in optimizing the zonal flow rates to prolong the field lifetimes, reduce water cuts and the associated costs, and achieve production targets. Furthermore, the improved operational efficiency can reduce the producers’ energy usages and carbon footprints for a more sustainable operation. For the past decade, inflow tracer technology based on embedding tracers in degradable polymer matrices, which are then placed in downhole completion zones at initial installation, has been used in understanding production zonal flow contributions in field demonstrations as well as in commercial projects. However, the current technology based on degradable polymers has the following limitations: (1) there are limited lifetimes for the degradable polymer matrices that will lose their functionality past their expiration dates, and (2) the tracers are released from the polymer matrices at a constant rate; so in order to create a transient for tracer flowback measurements the wells need to be shut-in for a period of time which will interfere with normal production and possibly, with the long-term productivity of the well. Here, we introduce an alternative approach for deploying inflow tracers that has no such limitations mentioned above. Specifically, we propose the installation of passive chemical tracer dosing lines connected to diffuser chambers at the annular regions downhole during completion. Pulses of tracers can be injected into the different production zones and monitored for their flowback characteristics on-demand. The passive tracer dosing lines and diffusers only require minimum upfront investments and have no limitations of lifetime compared to the degradable polymer matrices. Furthermore, the injection of tracer pulses into the annulus near production zones creates appropriate transient responses for their flowback measurements, which do not require well shut-in and will not affect normal production.Laboratory flow loop experiments and computational fluid dynamics (CFD) studies were performed to demonstrate the proposed methodology and to understand the underlying physics. Half-scale and quarter-scale flow loops made of transparent polyvinyl chloride (PVC) pipes that resemble annular regions near the ICVs were constructed with tracer dosing lines and diffusers attached within. Colored dyes were injected into the flow loops to visualize their flush out and flowback behaviors. In CFD studies, a two-step approach was used with first solving for the turbulent fluid flow profiles, and then solving for the tracer convection diffusion behaviors in the turbulent fields. The CFD model parameters were carefully matched with flow loop experiments to predict the possible real field responses. With appropriate diffuser design, we can achieve desirable zonal flow-rate-dependent tracer flowback responses with reasonable sampling times and injected tracer quantities.

Plant Growth-promoting Potential of Oil Palm Boiler Ash-based Organomineral Fertilizer for Green Mustard Cultivation Under Reduced Urea Dose in Ultisols

This study aims to demonstrate the capability of Oil Palm Boiler Ash (OPBA)-based organomineral fertilizer (OMF) to maintain the growth, green biomass yield, and N uptake of green mustard under a reduced N application rate. This research was carried out from March to May 2021 in a research area in Bengkulu City with a Randomly Complete Block Design scheme and three replications. The treatment consisted of P0 = control (without OMF or urea), P1 = 200 kg urea ha−1, P2 = 325 kg OMF ha−−1 + 50 kg urea ha−−1, P3 = 650 kg OMF ha−−1 + 50 kg urea ha−−1, P4 = 975 kg OMF ha−−1 + 50 kg urea ha−−1, and P5 = 1300 kg OMF ha−−1 + 50 kg urea ha−−1. The results showed that the growth and green biomass yield increased as the application rate of OMF increased. Treatment of P5 produced the highest growth, green biomass yield, and N uptake, equivalent to P2 treatment. The green biomass yield at P5 was 161% higher than that at P0. Therefore, OMF has the potential to promote the agronomic performances of green mustard under 50% reduced N dose in Ultisols. Keywords: slow release fertilizer, nutrient management, oil palm waste, organic pellet fertilizer, green mustard

Repurposing idle wells in the North German Basin as deep borehole heat exchangers

This study investigates the feasibility to repurpose wells from gas production for geothermal closed-loop application in the North German Basin (NGB). The objective for this research topic is to extend the value-added chain of idle wells by re-completion as coaxial deep borehole heat exchangers as an efficient way to produce green energy without drilling new wells by saving the carbon emission and costs of building a new geothermal well. With numerical models of two typical geological settings of the NGB and two different completion schemes, it is possible to simulate the thermal performance over a lifetime of 30 years. The calculated heat extraction rates range from 200 to 400 kW, with maximum values of up to 600 kW. Sensitivity analyses demonstrate that re-completion depth and injection temperature are the most sensitive parameters of thermal output determination. The heat demand around the boreholes is mapped, and heat generation costs are calculated with heating network simulations. The initial production costs for heat are comparable to other renewable energy resources like biomass and competitive against gas prices in 2022. This study highlights available geothermal resources’ environmental and economic potential in already installed wells. The application has almost no geological and no drilling risks and may be installed at any idle well location.

Full-progress crop management and harvesting scheme with integrated space information: A case of jujube orchard

Space information integration can better obtain the environmental information, crop information, climate information and other key factors of the farmland, which is more helpful for crop management and harvesting. In the traditional crop management and harvesting process, crop management and harvesting are two relatively independent processes, lacking a complete full-process scheme. In this regard, this paper proposes a full-process crop management and harvesting scheme with integrated space information, which takes the space information of the crop planting area as the core, fully associates and closely integrates the crop management process and harvesting process, and carries out scientific field management, accurate yield estimation, and reasonable harvesting path planning for crops, to improve the intelligence and precision of the crop management and harvesting process. By using the jujube orchard as a case study, it was verified that the full-process crop management and harvesting scheme with integrated space information can improve the management level and economic benefits of the jujube orchard.

Analysis of thermal production effect of multi-horizontal U-shaped well

The multi-horizontal section hot dry rock (HDR) heat extraction system is proposed for efficient deep geothermal resources mining in this study. The thermal-hydraulic numerical model of the multi-horizontal section geothermal exploitation system is set up, the space-time evolution of temperature field is analyzed. The sensitivity factors including completion schemes, horizontal well diameter, quantity of horizontal sections and spacing of horizontal sections are investigated. The simulation results show that the production temperature and heating power of the multi-horizontal HDR production system decrease with the development of mining, and the decreasing speed gradually slows down. The open hole completion can be preferred when the formation conditions permit. The variation of horizontal well diameter has little effect on heat production when other conditions remain unchanged. The quantity of horizontal sections to be 3 or 4 for better heat extraction performance under the spacing of horizontal section remains 300m and the spacing of the horizontal section to be 150m is recommended within the scoped of this study. The results of this study can provide guidance for HDR mining research.

On local divisor class groups of complete intersections

Samuel conjectured in 1961 that a (Noetherian) local complete intersection ring that is a UFD in codimension at most three is itself a UFD. It is said that Grothendieck invented local cohomology to prove this fact. Following the philosophy that a UFD is nothing else than a Krull domain (that is, a normal domain, in the Noetherian case) with trivial divisor class group, we take a closer look at the Samuel–Grothendieck Theorem and prove the following generalization: Let A be a local Cohen–Macaulay ring.(1)A is a normal domain if and only if A is a normal domain in codimension at most 1.(2)Suppose that A is a normal domain and a complete intersection. Then the divisor class group of A is a subgroup of the projective limit of the divisor class groups of the localizations Ap, where p runs through all prime ideals of height at most 3 in A. We use this fact to describe for an integral Noetherian locally complete intersection scheme X the gap between the groups of Weil and Cartier divisors, generalizing in this case the classical result that these two concepts coincide if X is locally a UFD.

Benefits of Repeated SARS-CoV-2 Vaccination and Virus-induced Cross-neutralization Potential in Immunocompromised Transplant Patients and Healthy Individuals.

Current COVID-19 vaccines primarily target the Spike protein of defined virus variants, offering limited protection against emerging variants in immunocompetent individuals. Similarly, protective immunity following natural SARS-CoV-2 infection is variable and of short duration, raising concerns about immunocompromised individuals' vaccination strategies. This prospective multicenter study examined 66 sera from 59 immunocompromised and 451 sera from 215 immunocompetent individuals from different pandemic periods. We establish and validate a live virus-based neutralization assay to determine the virus-inactivating potential against ancestral and current SARS-CoV-2 isolates. Our virus-based neutralization assay demonstrated superior performance over surrogate neutralization assays. We found strong but transient immunity after complete vaccination schemes, with single doses providing minimum neutralization, regardless of vaccine type. Combining vaccination-induced immunity with SARS-CoV-2 infection before or after vaccination yielded higher neutralizing titers than vaccination or infection alone, consistent across both study groups. Additional doses after a full vaccination course restored neutralization levels. Potentially protective SARS-CoV-2 neutralization is reliably induced in immunocompromised individuals by prior attenuation of immunosuppression. First-generation vaccines protect against various SARS-CoV-2 variants in immunocompetent individuals, with effective cross-neutralization demonstrated up to the Delta variant but largely absent for later Omicron variants. Continuous vaccine updates are necessary to address emerging SARS-CoV-2 variants.

Finite element modelling of linear rolling contact problems

The present work is devoted to the finite element modelling of linear hyperbolic rolling contact problems. The main equations encountered in rolling contact mechanics are reviewed in the first part of the paper, with particular emphasis on applications from automotive and vehicle engineering. In contrast to the common hyperbolic systems found in the literature, such equations include integral and boundary terms, as well as time-varying transport velocities, that require special treatment. In this context, existence and uniqueness properties are discussed within the theoretical framework offered by the semigroup theory. The second part of the paper is then dedicated to recovering approximated solutions to the considered problems, by combining discontinuous Galerkin finite element methods (DGMs) with explicit Runge–Kutta (RK) schemes of the first and second order for time discretisation. Under opportune assumptions on the smoothness of the sought solutions, and owing to certain generalised Courant–Friedrichs–Lewy (CFL) conditions, quasi-optimal error bounds are derived for the complete discrete schemes. The proposed algorithms are then tested on simple scalar equations in one space dimension. Numerical experiments seem to suggest the theoretical error estimates to be sharp.

Использование компьютерной программы «ПРОЕКТ ВПУ» для проведения технологического расчета и анализа технологий обессоливания воды на ТЭС и АЭС

There are many viable options of desalination schemes that allow us to obtain purified water of the required quality. To conduct process design of a water treatment plant, thermal power plants and nuclear power plants use special software provided by manufacturers of ion exchangers and membrane elements. However, these software programs consider individual water treatment technologies and are attached to filter and membrane materials of a specific manufacturer. They do not provide the ability to calculate complete water desalination schemes, as well as determine the performance indicators of the water treatment plant. It is relevant to develop a software program that allows us to conduct process design of complete water treatment schemes, which include various water treatment technologies, and to determine technological, environmental, and technical-economic indicators. Multivariate calculations with different initial data will allow us to identify the advantages and disadvantages of scheme solutions and determine areas of their rational use. The method of mathematical modeling of chemical and technological processes of water treatment at thermal power plants and nuclear power plants has been used. An application software program “PROJECT WTP” has been developed. It is designed for process design of various water treatment schemes, which are visually assembled from individual elements, and allows one to determine the technological, environmental, and performance indicators of the operation of water treatment plant. Computation data on the auxiliary need coefficient has been obtained for the main water desalination schemes and under condition of different mineralization of the source water. The developed software program can be used for process design of various water treatment schemes and assessment of the degree of improvement of water desalination technology.

Dynamics Parameter Identification of Articulated Robot

Dynamics parameter identification in the establishment of a multiple degree-of-freedom (DOF) robot’s dynamics model poses significant challenges. This study employs a non-symbolic numerical method to establish a dynamics model based on the Newton–Euler formula and then derives a proper dynamics model through decoupling. Initially, a minimum inertial parameter set is acquired by using QR decomposition, with the inclusion of a friction model in the robot dynamics model. Subsequently, the least squares method is employed to solve for the minimum inertial parameters, forming the basis for a comprehensive robot dynamics parameter identification system. Then, after the optimization of the genetic algorithm, the Fourier series trajectory function is used to derive the trajectory function for parameter identification. Validation of the robot’s dynamics parameter identification is performed through simulation and experimentation on a 6-DOF robot, leading to a precise identification value of the robot’s inertial parameters. Furthermore, two methods are employed to verify the inertia parameters, with analysis of experimental errors demonstrating the effectiveness of the robot dynamics parameter identification method. Overall, the effectiveness of the entire calibration system is verified by experiments, which can provide valuable insights for practical engineering applications, and a complete and effective robot dynamics parameter identification scheme for a 6-DOF robot is established and improved.

Anisotropic magnetic and quadrupolar H−T phase diagram of CeRh2As2

The tetragonal heavy-fermion compound CeRh2As2 has intriguing low-temperature symmetry-breaking phases whose nature is unclear. The unconventional superconducting phase is complemented by other normal-state phases which presumably involve ordering of 4f electron multipoles supported by the Kramers doublets split by the tetragonal crystal electric field (CEF). The most striking aspect is the pronounced anisotropic H−T phase boundary for in-plane and out-of plane field directions. Using a localized 4f CEF model we demonstrate that its essential features can be understood as the result of competing low-field easy-plane magnetic order and field-induced quadrupolar order of xy type. We present calculations based on coupled multipole random phase approximation response function approach as well as molecular field treatment in the ordered regime. We use an analytical approach for a reduced quasiquartet model and numerical calculations for the complete CEF level scheme. We discuss the quantum critical properties as function of multipolar control parameters and explain the origin of a pronounced ac anisotropy of the H−T phase diagram. Finally, the field and temperature evolution of multipolar order parameters is derived and the high-field phase diagram is predicted. Published by the American Physical Society 2024

Association between vitamin A supplementation and stunting and anemia in socially vulnerable Brazilian children.

Vitamin A is related to concentrations of insulin-like growth factor type 1, a protein produced in response to growth hormone, and to increased mobilization of body iron stores. Thus, vitamin A aids in increased hematopoiesis and may be useful in preventing stunting and anemia. This study aimed to identify the association between vitamin A supplementation from the National Vitamin A Supplementation Program instituted in Brazil and stunting and anemia in socially vulnerable Brazilian children. This is a Cross-sectional population-based study. Children aged 6-59months old, living in favelas of a capital city in the Northeast of Brazil, were included. Sociodemographic variables were collected. Vitamin A supplementation was also evaluated using the child's vaccination card information. Anthropometric and capillary hemoglobin evaluations were performed to identify the presence of stunting and anemia, respectively. The association analysis was performed using Poisson regression with robust variance estimation. 598 children participated in this study; 11.3% and 55.6% had stunting and anemia, respectively. As for vitamin A supplementation, 59.5% had taken at least one dose of the supplement,and 3.5% were on the complete supplementation scheme. In the adjusted association analysis, vitamin A supplementation decreased the likelihood of children having stunting and anemia by 8% (RP:0.86; 95% IC 0.86-0.98; p = 0.014) and 31% (RP:0.69; 95% IC 0.53-0.89; p = 0.004), respectively. Children who were fully supplemented were 58% (RP:0.42; 95% IC 0.24-0.77; p = 0.008) less likely to have anemia. Thus, vitamin A supplementation is a protective tool against stunting and anemia in children living in a situation of social vulnerability.

A Complete Scheme for Multi-Character Classification Using EEG Signals From Speech Imagery.

Some classification studies of brain-computer interface (BCI) based on speech imagery show potential for improving communication skills in patients with amyotrophic lateral sclerosis (ALS). However, current research on speech imagery is limited in scope and primarily focuses on vowels or a few selected words. In this paper, we propose a complete research scheme for multi-character classification based on EEG signals derived from speech imagery. Firstly, we record 31 speech imagery contents, including 26 alphabets and five commonly used punctuation marks, from seven subjects using a 32-channel electroencephalogram (EEG) device. Secondly, we introduce the wavelet scattering transform (WST), which shares a structural resemblance to Convolutional Neural Networks (CNNs), for feature extraction. The WST is a knowledge-driven technique that preserves high-frequency information and maintains the deformation stability of EEG signals. To reduce the dimensionality of wavelet scattering coefficient features, we employ Kernel Principal Component Analysis (KPCA). Finally, the reduced features are fed into an Extreme Gradient Boosting (XGBoost) classifier within a multi-classification framework. The XGBoost classifier is optimized through hyperparameter tuning using grid search and 10-fold cross-validation, resulting in an average accuracy of 78.73% for the multi-character classification task. We utilize t-Distributed Stochastic Neighbor Embedding (t-SNE) technology to visualize the low-dimensional representation of multi-character speech imagery. This visualization effectively enables us to observe the clustering of similar characters. The experimental results demonstrate the effectiveness of our proposed multi-character classification scheme. Furthermore, our classification categories and accuracy exceed those reported in existing research.

Predictive algorithm of instrument health condition based on linear regression and radial basis function neural network

Abstract Enterprises and institutions engaged in social production activities need to apply for mandatory verification of general instruments and meters on production equipment according to law, and its verification period is determined by national or local verification and calibration procedures, but the health condition in the calibration intervals is difficult to know. To improve equipment reliability, this paper relies on the linear regression model to research the health condition of general instruments and meters, uses MATLAB tools to analyze the data samples of typical equipment pressure gauge, and combines radial basis function neural network to form a complete algorithm, and finally provides a complete implementation scheme for the health condition prediction of general instruments and meters in service.