The battery power state (SOP) is the basic indicator for the Battery management system (BMS) of the battery energy storage system (BESS) to formulate control strategies. Although there have been many studies on state estimation of lithium-ion batteries (LIBs), aging and temperature variation are seldom considered in peak power prediction during the whole life of the battery. To fill this gap, this paper aims to propose an adaptive peak power prediction method for power lithium-ion batteries considering temperature and aging is proposed. First, the Thevenin equivalent circuit model is used to jointly estimate the state of charge (SOC) and SOP of the lithium-ion power battery, and the variable forgetting factor recursive least squares (VFF-RLS) algorithm and extended Kalman filter (EKF) are utilized to identify the battery parameters online. Then, multiple constraint parameters including current, voltage, and SOC were derived, considering the dependence of the polarization resistance of... [more]

Select porous carbonate cores are used to carry out water-flooding oil micro-CT flooding experiments, and use image processing to separate oil, water, microfacies, and rock skeleton. The gray value is used to determine the distribution position of the microfacies sub-resolution remaining oil. The gray image resolution is improved by the SRCNN method to improve the pore identification accuracy. The distribution and evolution law of the sub-resolution remaining oil after the displacement is determined by the oil-water distribution results. Using the SRCNN method, the pore recognition accuracy of the original scanned images of the two samples was increased by 47.88 times and 9.09 times, respectively. The sub-resolution residual oil and the macro-pore residual oil were determined from the CT scan images after the brine was saturated and divided into five categories. With the increase in the displacement ratio, the columnar and droplet residual oil of the low-permeability samples first incr... [more]

Machine learning is the main technical means for lithofacies logging identification. As the main target of shale oil spatial distribution prediction, mud shale petrography is subjected to the constraints of stratigraphic inhomogeneity and logging information redundancy. Therefore, choosing the most applicable machine learning method for different geological characteristics and data situations is one of the key aspects of high-precision lithofacies identification. However, only a few studies have been conducted on the applicability of machine learning methods for mud shale petrography. This paper aims to identify lithofacies using commonly used machine learning methods. The study employs five supervised learning algorithms, namely Random Forest Algorithm (RF), BP Neural Network Algorithm (BPANN), Gradient Boosting Decision Tree Method (GBDT), Nearest Neighbor Method (KNN), and Vector Machine Method (SVM), as well as four unsupervised learning algorithms, namely K-means, DBSCAN, SOM, and... [more]

Implementing intelligent identification of faults in hydroelectric units helps in the timely detection of faults and taking measures to minimize economic losses. Therefore, improving the accuracy of fault signal recognition has always been a research focus. This study is based on the improved empirical mode decomposition (EMD) theory to study the denoising and feature extraction of vibration signals of hydroelectric units and uses the backpropagation neural network (BPNN) to establish corresponding connections between signal features and vibration fault states. The improved EMD in this study can improve the performance of noise reduction processing and contribute to the accurate identification of vibration faults. The vibration fault identification criteria can adopt three dimensionless feature parameters: peak skewness coefficient, valley skewness coefficient, and kurtosis coefficient of the second- and third-order components of the signal, with recognition rates and accuracy reaching... [more]

This article aims to enhance technological advancements in the classification of polyethylene terephthalate (PET) bottle plastic, positively impacting sustainable development and providing effective solutions for collection centers (CC) in Mexico. Three experimental designs and machine learning tools for data processing were developed. The experiments considered three factors: bottle size, liquid volume, and bottle labels. The first experiment focused on determining the sensor distance from post-consumer PET bottles. The second experiment aimed to evaluate the sensor’s detection ability with varying liquid levels, while the third experiment assessed its detection capability for bottle labels. A digital lux meter integrated with a microcontroller was developed to monitor illuminance in post-consumer PET bottles containing liquid as they moved through a conveyor belt at an average rate of three bottles per second. The implemented methodology successfully detected liquids inside transpare... [more]

Pesticide residues have long been a significant aspect of food safety, which has always been a major social concern. This study presents research and analysis on the identification of pesticide residue fast detection cards based on the enzyme inhibition approach. In this study, image recognition technology is used to extract the color information RGB eigenvalues from the detection results of the quick detection card, and four regression models are established to quantitatively predict the pesticide residue concentration indicated by the quick detection card using RGB eigenvalues. The four regression models are linear regression model, quadratic polynomial regression model, exponential regression model and RBF neural network model. Through study and comparison, it has been shown that the exponential regression model is superior at predicting the pesticide residue concentration indicated by the rapid detection card. The correlation value is 0.900, and the root mean square error is 0.106.... [more]

In this paper, we propose a damage identification method based on minimum mean square error estimation for a wind tunnel flexible plate condition monitoring system. Critical structural members of important equipment are large in size, and the measurement systems used to monitor their condition are often complex. The proposed damage identification method is based on the minimum mean squared error estimator and the generalized likelihood ratio test. It introduced activation function to generate the standard deviation of the data, which can then simulate the sensor output. A single sensor damage only affects a single dimension of the output data matrix of the measurement system. However, structural damage affects the output of multiple sensors. The damage identification method proposed in this paper can not only distinguish the sensor damage from the structure damage, but also locate the damaged sensor or structure damage location. This method can identify the measurement system output an... [more]

The Gulong shale oil reservoir is situated in freshwater to slightly saline lacustrine basins mainly consisting of a pure shale geological structure, which is quite different from other shale reservoirs around the world. Currently, the development of Gulong shale oil mainly relies on hydraulic fracturing, while the subsequent shut-in period for imbibition has been proven to be an effective method for enhancing shale oil recovery. To clarify the characteristics of the fluid occurrence space and the variation in the fluid occurrence during saltwater imbibition in Gulong shale, this paper carried out porosity and permeability tests on Gulong shale cores and analyzed the fluid occurrence space characteristics and imbibition oil recovery based on nuclear magnetic resonance (NMR). In the porosity and permeability tests, T2 distributions were used to correct the porosity measured by the saturation method to obtain the NMR porosity. Combined with the identification of fractures in shale cores... [more]

CO2 is a potential fluid for absorbing and accumulating thermal energy; an accurate and fast calculation method for the heat capacity is essential for the study of the flow state near the critical point. However, the calculation of the heat capacity near the critical point by the equations suggested by NIST can easily be divergent, such as for CO2, nitrogen, methane, etc. Therefore, an explicit fitting equation was studied. The fitting equation, which used density and temperature as variables and contained three constants, was derived from the nature of heat capacity change (molecular kinetic energy and potential energy). Based on the heat capacity data of the NIST WebBook, the heat capacity of CO2 is taken as the example for the equation deduction and parameter fitting. The three constants were defined in order by Origin fitting software. By this new approach, it is found that the heat capacity at the critical point is below 1% deviant from that of the NIST WebBook. Moreover, the heat... [more]

Accurate parameter estimation of photovoltaic (PV) cells is crucial for establishing a reliable cell model. Based on this, a series of studies on PV cells can be conducted more effectively to improve power output; an accurate model is also crucial for the operation and control of PV systems. However, due to the high nonlinearity of the cell and insufficient measured current and voltage data, traditional PV parameter identification methods are difficult to solve this problem. This article proposes a parameter identification method for PV cell models based on the radial basis function (RBF). Firstly, RBF is used to de-noise and predict the data to solve the current problems in the parameter identification field of noise data and insufficient data. Then, eight prominent meta-heuristic algorithms (MhAs) are used to identify the single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM) parameters of PV cells. By comparing the identification accuracy of the three models... [more]

This manuscript presents the remote monitoring of the main parameters in the 18O isotope separation technological process. It proposes to monitor the operation of the five cracking reactors in the isotope production system, respectively, the temperature in the preheating furnaces, the converter reactors and the cracking reactors. In addition, it performs the monitoring of the two separation columns from the separation cascade structure, respectively, the concentrations of the produced 18O isotope and the input nitric oxides flows. Even if the production process is continuously monitored by teams of operators, the professionals who designed the technical process and those who can monitor it remotely have the possibility to intervene with the view of making the necessary adjustments. Based on the processing of experimental data, which was gathered from the actual plant, the proposed original model of the separation cascade functioning was developed. The process computer from the monitori... [more]

Limitations regarding process design, optimization, and control often occur when using particular process simulators. With the implementation of connection methodologies, integrated tools could be made by coupling popular process simulation software with each other or with programming environments. In the current paper, we summarized and categorized the existing research regarding the application of multi-software engineering in the chemical industry, with an emphasis on software connections. CAPE-OPEN, COM, OPC, and native integration were discussed in detail, with the intention to serve as a guide for choosing the most suitable software combination and connection. These hybrid systems can handle complex user-defined problems and can be used for decision support, performing custom unit operations, operator training, process optimization, building control systems, and developing digital twins. In this work, we proposed the use of process simulator Aspen HYSYS linked together with the n... [more]

Identifying the gender of a person and his age by way of speaking is considered a crucial task in computer vision. It is a very important and active research topic with many areas of application, such as identifying a person, trustworthiness, demographic analysis, safety and health knowledge, visual monitoring, and aging progress. Data matching is to identify the gender of the person and his age. Thus, the study touches on a review of many research papers from 2016 to 2022. At the heart of the topic, many systematic reviews of multimodal pedagogies in Age and Gender Estimation for Adaptive were undertaken. However, no current study of the theme concerns connected to multimodal pedagogies in Age and Gender Estimation for Adaptive Learning has been published. The multimodal pedagogies in four different databases within the keywords indicate the heart of the topic. A qualitative thematic analysis based on 48 articles found during the search revealed four common themes, such as multimodal... [more]

Batch processes in the biopharmaceutical and chemical manufacturing industries often develop new products to meet changing market demands. When the dynamic models of these new products are trained, dynamic modeling with limited data for each product can lead to inaccurate results. One solution is to extract useful knowledge from past historical production data that can be applied to the product of a new grade. In this way, the model can be built quickly without having to wait for additional modeling data. In this study, a subspace identification combined common feature learning scheme is proposed to quickly learn a model of a new grade. The proposed modified state-space model contains common and special parameter matrices. Past batch data can be used to train common parameter matrices. Then, the parameters can be directly transferred into a new SID model for a new grade of the product. The new SID model can be quickly well trained even though there is a limited batch of data. The effec... [more]

CDK1 (cyclin dependent kinase 1) is a key regulator of the cell cycle and is frequently dysregulated in cancer, making it a promising target for anticancer therapy. Securigera securidaca L. (S. securidaca) seeds, traditionally used in folk medicine for various ailments including cancer, were examined for their potential as CDK1/Cks2 inhibitors using in silico approaches. A total of 14 phytocompounds was identified in the GC/MS chromatogram, with gingerone being the most abundant at 25.67% and hippeastrine the least at 2%. Major constituents of the essential extract, including gingerol, eugenol, α-curcumene, and gingerol, showed high values and made up 52% of the total content of the volatile extract. Molecular docking and ADMET studies suggested that hippeastrine and naringenin are potential hit candidates against CDK1, exhibiting good drug-like properties and molecular interactions with desirable pharmacokinetic and toxicological characteristics close to dinaciclib. Furthermore, molec... [more]

Electric vehicles (EVs) have become a viable solution to the emerging global climate crisis. Rechargeable battery packs are the basic unit of the energy storage system of these vehicles. The battery thermal management system (BTMS) is the primary control unit of the energy source of the vehicles. EV performance is governed by specific power, charging/discharging rate, specific energy, and cycle life of the battery packs. Nevertheless, these parameters are affected by temperature, making thermal management the most significant factor for the performance of a battery pack in an EV. Although the BTMS has acquired plenty of attention, research on the efficiency of the liquid cooling-based BTMS for actual drive cycles has been minimal. Liquid cooling, with appropriate configuration, can provide up to 3500 times more efficient cooling than air cooling. Direct/immersive and indirect liquid cooling are the main types of liquid cooling systems. Immersive/direct cooling utilizes the technique of... [more]

This article concerns the identification of connections between the energy intensity of rail transport and spatial integration (convergence processes in the EU and spatial proximity) and the economic situation of countries that are in international export−import trade relations. Three research questions are formulated in the article: (1) Does the improvement of the economic situation of the importing country reduce the energy intensity of the Polish export of goods by rail transport to the partner country? (2) Does EU integration contribute to reducing the energy intensity of the export of goods by rail transport? (3) Is there a positive spatial effect (convergence) of reducing the energy intensity of the export of goods by rail transport? This study concerned 14 geographical destinations (export destinations from Poland) during the years 2010−2020. A comprehensive study of convergence was used by building a spatial (club) and type β convergence model and using an unconventional method... [more]

This paper presents the authors’ multi-channel measurement systems designed and built to conduct research on partial discharge phenomena using the acoustic emission method. The systems provide real-time monitoring, recording of signals and analysis of recorded signals. The analysis is carried out in time, frequency, time-frequency and discrimination threshold domains. In particular, a descriptor with the ADC acronym is defined, which ranks the signals according to the so-called degree of advancement. Studies have been carried out, showing that for a single partial discharge source, when tested in parallel, using the electrical and acoustic emission methods, the ranking of the signals using this descriptor is identical to the ranking according to the value of the apparent charge introduced by sources. This paper presents the authors’ patented method of partial discharge location and identification in power oil transformers. The results of tests of power oil transformer at the test stati... [more]

The scarcity of inertial resources in the new AC−DC hybrid grids makes the grid frequency prone to fluctuation. In this paper, the relationship between the grid-side and load-side characteristics of the power router is constructed. By adjusting the port load parameters, the load power can respond quickly to the fluctuation of the grid frequency, thereby realizing rapid support of the grid frequency. Firstly, two kinds of mathematical models for sensitivity identification of load characteristics, variable voltage and variable frequency, are established to calculate the characteristic parameters of a multi-port load. The allocation rules of port power and allocation coefficients are designed according to the parameters. A frequency modulation control method that matches the load response capability of the multi-port router is proposed. Then, taking into consideration the uncertainty of load group characteristics and power, a variable coefficient frequency modulation control strategy for... [more]

In the Middle East, there remain many technical challenges in the water saturation evaluation of carbonate rocks and the effective identification of reservoir fluid properties. The traditional Archie equation is not applicable to carbonate reservoirs with complex pore structures and varying reservoir space distribution, as there are obvious “non-Archie” phenomena. In this paper, by analyzing the experimental data on the rock resistivity of the target formation in the study area and analyzing the relationship between stratigraphic factors and porosity, the previous fitting method was modified as a result of using the actual data while avoiding the cementation index as a way to improve Archie’s formula to evaluate the water saturation. Based on the improved Archie formula, the mathematical differential operation of water saturation and porosity was carried out using the formation resistivity. The calculation results of irreducible water saturation were used to calibrate the oil layer, an... [more]

A method of steel structure surface crack identification based on artificial intelligence technology is proposed to solve the problem that steel cracks can not be detected and forewarned in time when they appear in the railway industrial environment. The appearance of steel cracks greatly weakens the stability of steel structures, and will seriously endanger the safety of the railway industry if it is not detected and repaired in time. However, the common steel crack detection methods cannot achieve real-time monitoring of steel structures. In order to monitor the surface of steel structure in real-time and explore the recognition effect and model the advantages of common classification neural network models for surface cracks of railway industrial steel, this study evaluates the network model with multiple indicators and parameters under two experimental conditions. In this study, the steel surface cracks in the railway industrial environment are taken as samples, and the steel cracks... [more]

The lithium-ion battery is widely used in the power system of pure electric vehicles and hybrid electric vehicles due to its high energy density. However, the chemical and electrochemical reactions generate a lot of heat. If the heat is not transferred through some refrigeration methods in time, it will lead to a rapid rise in the temperature of the battery. In this paper, an electric−thermal coupling model of a cylindrical Panasonic 21700 battery was proposed by using offline parameter identification method. Based on this model, a battery thermal management system using a heat pipe was established. The experimental results show that the model can simulate the actual performance of battery well. When the ambient temperature is 25 °C, the battery parameters change little and battery performance is better. The heat pipe battery thermal management system performs better than the non-heat pipe battery system in the discharge process, and can control the battery temperature well at low and... [more]

Environmental microbiology has been an essential part of environmental research because it provides effective solutions to most pollutants. Hence, there is an interest in investigating microorganism behavior, such as observation, identification, isolation of pollutant degraders, and interactions between microbial species. To comprehensively understand cell heterogeneity, diverse approaches at the single-cell level are demanded. Thus far, the traditional bulk biological tools such as petri dishes are technically challenging for single cells, which could mask the heterogeneity. Single-cell technologies can reveal complex and rare cell populations by detecting heterogeneity among individual cells, which offers advantages of higher resolution, higher throughput, more accurate analysis, etc. Here, we overviewed several single-cell techniques on observation, isolation, and identification from aspects of methods and applications. Microscopic observation, sequencing identification, flow cytome... [more]

The Pinghu Formation is a low permeability sandstone reservoir in the KQT Region, East China Sea. Its porosity ranges from 3.6 to 18.0%, and permeability is distributed from 0.5 to 251.19 mD. The relationship between porosity and permeability was poor due to strong heterogeneity. This led to the difficulty of quantitatively evaluating effective reservoirs and identifying pore fluids by using common methods. In this study, to effectively evaluate low permeability sandstones in the Pinghu Formation of KQT Region, pore structure was first characterized from nuclear magnetic resonance (NMR) logging based on piecewise function calibration (PFC) method. Effective formation classification criteria were established to indicate the “sweet spot”. Afterwards, several effective methods were proposed to calculate formation of petrophysical parameters, e.g., porosity, permeability, water saturation (Sw), irreducible water saturation (Swirr). Finally, two techniques, established based on the crossplo... [more]

Articular cartilage is a complex connective tissue with the fundamental functions of load bearing, shock absorption and lubrication in joints. However, traumatic events, aging and degenerative pathologies may affect its structural integrity and function, causing pain and long-term disability. Osteoarthritis represents a health issue, which concerns an increasing number of people worldwide. Moreover, it has been observed that this pathology also affects the mechanical behavior of the articular cartilage. To better understand this correlation, the here proposed review analyzes the physiological aspects that influence cartilage microstructure and biomechanics, with a special focus on the pathological changes caused by osteoarthritis. Particularly, the experimental data on human articular cartilage are presented with reference to different techniques adopted for mechanical testing and the related theoretical mechanical models usually applied to articular cartilage are briefly discussed.