Equivalent Model Research Articles

State of energy estimation of lithium-ion battery based on long short-term memory optimization Adaptive Cubature Kalman filter.

State of energy (SOE) is an important parameter to ensure the safety and reliability of lithium-ion battery (LIB) system. The safety of LIBs, the development of artificial intelligence, and the increase in computing power have provided possibilities for big data computing. This article studies SOE estimation problem of LIBs, aiming to improve the accuracy and adaptability of the estimation. Firstly, in the SOE estimation process, adaptive correction is performed by iteratively updating the observation noise equation and process noise equation of the Adaptive Cubature Kalman Filter (ACKF) to enhance the adaptive capability. Meanwhile, the adoption of high-order equivalent models further improves the accuracy and adaptive ability of SOE estimation. Secondly, Long Short-term Memory (LSTM) is introduced to optimize Ohmic internal resistance (OIR) and actual energy (AE), further improving the accuracy of SOE estimation. Once again, in the process of OIR and AE estimation, the iterative updating of the observation noise equation and process noise equation of ACKF were also adopted to perform adaptive correction and enhance the adaptive ability. Finally, this article establishes a SOE estimation method based on LSTM optimized ACKF. Validate the LSTM optimized ACKF method through simulation experiments and compare it with individual ACKF methods. The results show that the ACKF estimation method based on LSTM optimization has an SOE estimation error of less than 0.90% for LIB, regardless of the SOE at 100%, 65%, and 30%, which is more accurate than the SOE estimation error of ACKF alone. It can be seen that this study has improved the accuracy and adaptability of LIB's SOE estimation, providing more accurate data support for ensuring the safety and reliability of lithium batteries.

Equivalent Models of an Infinite Track for Frequency and Time Domain Analyses

Equivalent Models of an Infinite Track for Frequency and Time Domain Analyses

Managing ESG ratings disagreement in sustainable portfolio selection

In sustainable portfolio selection, investors have a twofold objective: they want to achieve the best compromise between portfolio risk and return, but they also want to take into account the sustainability of their investment, assessed through some Environmental, Social, and Governance (ESG) evaluation criteria. The inclusion of sustainable goals in the portfolio selection process may have an impact on the portfolio financial performance. ESG scores provided by the rating agencies are generally considered good proxies for the sustainability performance of an investment, as well as appropriate measures for Socially Responsible Investments (SRI). In this framework, the lack of alignment between ratings provided by different agencies is a crucial issue that inevitably undermines the robustness and reliability of these evaluation measures. In fact, the ESG rating disagreement may produce conflicting information, implying difficulty for the investors in the ESG evaluation of their portfolios. This may cause underestimation or overestimation of the market opportunities for a sustainable investment.In this paper, we deal with a multi-criteria portfolio selection problem, taking into account risk, return, and ESG criteria. For the ESG evaluation of the securities, we consider more than one agency and propose a new approach to overcome the problem related to the disagreement between the ESG ratings given by different agencies. For our three-criteria portfolio selection problem, we present an optimization model which adopts the so-called k−sum operator to formulate a concise ESG evaluation measure. The natural formulation of the model, in which the portfolio risk is measured by the variance of its returns, leads to a nonlinear program, but we show that it can be reformulated as an equivalent convex quadratic model. We also show that the model can be generalized to include any convex portfolio risk measures. An extensive empirical analysis of the out-of-sample performance of this model is provided on real-world financial data sets. From a theoretical viewpoint, our work extends the use of k−sum methodology to quadratic programming.

Pore-fracture structures and seepage flow characteristics during spontaneous coal combustion based on CT 3D reconstruction

To study the evolution characteristics of the pore-fracture structures and seepage properties of coal in the process of spontaneous combustion, a high-temperature tube furnace was used to heat the coal samples. The coal samples were scanned using Xray-CT scanning technology, and the CT 3D reconstruction technology was used to extract the 3D pore structure and equivalent pore network model of each group of coal samples. Firstly, the specific surface area and volume of pore cleavage is statistically characterized; the change rules of Ep, Et, Lc, and Cn are quantitatively analyzed. At 200 °C, the coal body produces a large number of pore fractures, the development of coal samples is more significant, and the pore-specific surface area and the number of pore throats reached their maximum value. In addition, the changes of fractal dimension, porosity, connectivity, and permeability of coal with temperature were discussed, and the best permeability of the coal was achieved at 200 °C. The connectivity and permeability were weakened with the further increase of temperature, and the structural changes had a close influence on the gas seepage pressure and seepage flow rate. The results of the study provide important engineering guidance for deepening fire prevention in coalfields.

Task-based image quality assessment of an intraoperative CBCT for spine surgery compared with conventional CT

Purpose:To analyze the image quality of a novel, state-of-the art platform for CBCT image-guided spine surgery, focusing particularly on the dose–effectiveness compared with conventional CT (the gold standard for postoperative assessment). Methods:The ClarifEye platform (Philips Healthcare) with integrated augmented-reality surgical navigation, has been compared with a GE Revolution CT (GE Healthcare). The 3D spatial resolution (TTF) and noise (NPS) were evaluated considering relevant feature contrasts (200–900 HU) and background noise for differently sized patients (200–300 mm water-equivalent diameter). These measures were used to determine the noise equivalent quanta (NEQ) and observer model detectability. Results:The CBCT system exhibited a linear response with 50% TTF at 5.7 cycles/cm (10% TTF at 9.2 cycles/cm), and the axial noise power peaking at about 3.6 cycles/cm (average frequency of 4.1 cycles/cm). The noise magnitude and texture differed markedly compared to iteratively reconstructed CT images (GE ASiR-V). The CBCT system had 26% lower detectability for a high-frequency task (related to edge detection) compared with CT images reconstructed using the Bone kernel combined with ASiR-V 50%. Likewise, it had 18% lower detectability for low- and mid-frequency tasks compared with CT images reconstructed using the Standard kernel. This difference translates to 50%–80% higher CBCT imaging doses required to match the CT image quality. Conclusions:The ClarifEye platform demonstrates intraoperative CBCT-imaging capabilities that under certain circumstances are comparable with conventional CT. However, due to limited dose–effectiveness, a trade-off between timeliness and radiation exposure must be considered if end-of-procedure CBCT is to replace postoperative CT.

Moderate beta-cell ablation triggers synergic compensatory mechanisms even in the absence of overt metabolic disruption

Regeneration, the ability to replace injured tissues and organs, is a phenomenon commonly associated with lower vertebrates but is also observed in mammals, in specific tissues. In this study, we investigated the regenerative potential of pancreatic islets following moderate beta-cell loss in mice. Using a rapid model of moderate ablation, we observed a compensatory response characterized by transient inflammation and proliferation signatures, ultimately leading to the recovery of beta-cell identity and function. Interestingly, this proliferative response occurred independently of inflammation, as demonstrated in ablated immunodeficient mice. Furthermore, exposure to high-fat diet stimulated beta-cell proliferation but negatively impacted beta-cell function. In contrast, an equivalent slower ablation model revealed a delayed but similar proliferative response, suggesting proliferation as a common regenerative response. However, high-fat diet failed to promote proliferation in this model, indicating a differential response to metabolic stressors. Overall, our findings shed light on the complex interplay between beta-cell loss, inflammation, and stress in modulating pancreatic islet regeneration. Understanding these mechanisms could pave the way for novel therapeutic strategies based on beta-cell proliferation.

Development of an equivalent system frequency response model based on aggregation of distributed energy storage systems

Energy storage systems (ESSs) installed in distribution networks have been widely adopted for frequency regulation services due to their rapid response and flexibility. Unlike existing ESS design methods which focus on control strategies, this paper proposes a new method based on an ESS equivalent aggregated model (EAM) for calculating the capacity and the droop of an ESS to maintain the system frequency nadir and quasi-steady state frequency using low-order functions. The proposed method 1) uses first-order functions to describe the frequency response (FR) of synchronous generators (SGs); 2) ignores the control strategies of SGs, making the method systematic and allowing it to avoid analyzing complex high-order functions; and 3) is suitable for low inertia systems. The applicability and accuracy of the method is demonstrated using a modified four-generator two-area (4G2A) system.

The dynamics of evolutionary branching in an ecological model

Eco-evolutionary modelling involves the coupling of ecological equations to evolutionary ones. The interaction between ecological dynamics and evolutionary processes is essential to simulating evolutionary branching, a precursor to speciation. The creation and maintenance of biodiversity in models depends upon their ability to capture the dynamics of evolutionary branching. Understanding these systems requires low-dimension models that are amenable to analysis. The rapid reproduction rates of marine plankton ecosystems and their importance in determining the fluxes of climatically important gases between the ocean and atmosphere suggest that the next generation of global climate models needs to incorporate eco-evolutionary models in the ocean. This requires simple population-level models, that can represent such eco-evolutionary processes with orders of magnitude fewer equations than models that follow the dynamics of individual phenotypes. We present a general framework for developing eco-evolutionary models and consider its general properties. This framework defines a fitness function and assumes a beta distribution of phenotype abundances within each population. It simulates the change in total population size, the mean trait value, and the trait differentiation, from which the variance of trait values in the population may be calculated. We test the efficacy of the eco-evolutionary modelling framework by comparing the dynamics of evolutionary branching in a six-equation eco-evolutionary model that has evolutionary branching, with that of an equivalent one-hundred equation model that simulates the dynamics of every phenotype in the population. The latter model does not involve a population fitness function, nor does it assume a distribution of phenotype abundance across trait values. The eco-evolutionary population model and the phenotype model produce similar evolutionary branching, both qualitatively and quantitatively, in both symmetric and asymmetric fitness landscapes. In order to better understand the six-equation model, we develop a heuristic three-equation eco-evolutionary model. We use the density-independent mortality parameter as a convenient bifurcation parameter, so that differences in evolutionary branching dynamics in symmetric and asymmetric fitness landscapes may be investigated. This model shows that evolutionary branching of a stable population is flagged by a zero in the local trait curvature; the trait curvature then changes sign from negative to positive and back to negative, along the solution. It suggests that evolutionary branching points may be generated differently, with different dynamical properties, depending upon, in this case, the symmetry of the system. It also suggests that a changing environment, that may change attributes such as mortality, could have profound effects on an ecosystem’s ability to adapt. Our results suggest that the properties of the three-dimensional model can provide useful insights into the properties of the higher-dimension models. In particular, the bifurcation properties of the simple model predict the processes by which the more complicated models produce evolutionary branching points. The corresponding bifurcation properties of the phenotype and population models, evident in the dynamics of the phenotype distributions they predict, suggest that our eco-evolutionary modelling framework captures the essential properties that underlie the evolution of phenotypes in populations.

A Method for Calculating the Reliability of 2-Separable Networks and Its Applications

This paper proposes a computational method for the reliability of 2-separable networks. Based on graph theory and probability theory, this method simplifies the calculation process by constructing a network equivalent model and designing corresponding algorithms to achieve the efficient evaluation of reliability. Considering independent random failures of edges with equal probability q, this method can accurately calculate the reliability of 2-separable networks, and its effectiveness and accuracy are verified through examples. In addition, to demonstrate the generality of our method, we have also applied it to other 2-separable networks with fractal structures and proposed linear algorithms for calculating their all-terminal reliability.

Effects of Aluminum/Carbon and Morphology on Optical Characteristics and Radiative Forcing of Alumina Clusters Emitted by Solid Rockets in the Stratosphere

Alumina (Al2O3) particles, the primary combustion products of solid rockets, can accumulate in the stratosphere, changing the global radiative balance. These Al2O3 particles were usually treated as homogeneous spheres. However, they contain impurities and may form clusters during the combustion process. Models representing Al-containing and C-containing Al2O3 clusters were developed, denoted as Al2O3 shell model (ASM) and Al2O3 core model (ACM), respectively. The superposition T-matrix method (STMM) was applied to examine their optical characteristics. Subsequently, a method to obtain the top-of-atmosphere flux was proposed by integrating the models with the moderate resolution atmospheric transmission code (MODTRAN). With the addition of Al/C, the absorption cross-section enhances by several orders of magnitude at 0.55 μm and increases slightly at 10 μm. The equivalent sphere models will weaken their scattering ability. A 4Tg mass burden of Al2O3 produces radiative forcing of −0.439 Wm−2. However, the addition of Al and C reduces the forcing by up to 15% and 12%, respectively. In summary, the optical characteristics and radiative forcing of Al2O3 clusters are sensitive to Al/C and morphology models. While our findings are impacted by various uncertainties, they contribute valuable insights into the radiative forcing of Al2O3 particles, potential climatic changes by space activities.

Time-domain equivalent model for harmonic simulations of wind and photovoltaic plants

Equivalent models of wind power plants or photovoltaic systems reduce the computational burden relative to detailed models (DMs) during power quality studies. However, existing time-domain equivalent models are ineffective for predicting harmonic currents because they do not consider switching behavior from power converters. This paper proposes a novel time-domain equivalent model, the aggregated harmonic model (AHM), to perform harmonic current prediction in large plants. The AHM uses the National Renewable Energy Laboratory method to equalize the collector system and applies the superposition principle to include the dead time and switching effects. Simulations were executed using the DM and AHM of actual plants. Field measurements were performed to validate the AHM. The results show that the proposed model produced well-matched curves for current waveforms, frequency responses, and harmonic spectra. Consequently, this model is an accurate tool for transmission system operators.

Determination of dominant oscillation section in power system based on MSSA algorithm and dissipated energy

The identification of dominant oscillation paths is one of the key aspects in studying the stability of inter-area power grids. This paper proposes an improved multi-channel singular spectrum analysis (MSSA) algorithm combined with dissipative energy to identify dominant oscillation section in power systems. First, an improved MSSA method is introduced, which determines the order using the singular value energy spectrum and can effectively identify inter-area oscillation modes in power systems. Second, an energy function analysis method is proposed, which is well-suited for determining dominant oscillation section in power systems. This method is minimally affected by time-varying and nonlinear factors and allows for the visualization of generator states. Finally, the IEEE 68-bus system is used to construct an equivalent model, demonstrating the method's versatility. Simulation results validate the noise resistance, computational efficiency, and applicability to topology change scenarios of the proposed method. This method can accurately analyze inter-area oscillation modes and help to establish the dominant oscillation section.

On solving a rank regularized minimization problem via equivalent factorized column-sparse regularized models

On solving a rank regularized minimization problem via equivalent factorized column-sparse regularized models

Novel Phononic-Like Crystal Wave Barrier Structure for Vibration Isolation

As an efficient, environmentally friendly, and economical urban public transportation tool, the subway has significant advantages compared to other urban public transportation tools and plays an irreplaceable role in the urban rail transit system. While the subway brings many conveniences to people, its operation has also brought a series of problems to urban development and residents’ lives, especially the vibration and noise problems generated by the subway have become unavoidable and urgent problems to be solved. The traditional wave barriers have a certain effect on attenuating and suppressing the vibration generated by the subway, but it has shortcomings in terms of the width and quantity of elastic wave bandgap (BG), so its application in low-frequency vibration reduction and isolation of subway systems is greatly limited. In order to broaden the elastic BG width and quantity of the wave barrier, this paper designs a novel phononic-like crystal subway wave barrier (PLCSWB) for subway vibration isolation based on locally resonant theory. Firstly, the dispersion curves of the novel PLCSWB are calculated using the improved plane wave expansion method and finite element method (FEM), and compared with the dispersion curves of traditional phononic crystal (PC) wave barriers. Secondly, the frequency response function of the novel PLCSWB is calculated using FEM to evaluate its attenuation effect on vibration, and the energy distribution characteristics at its BG boundary are analyzed. Then, the main factors affecting the BG of the novel PLCSWB are analyzed, and a spring–mass system equivalent model of the novel PLCSWB is established to theoretically estimate its BG range. Finally, the vibration data of the tunnel wall monitored on site are used to analyze and verify the vibration isolation effect of the novel PLCSWB. The results show that the novel PLCSWB opens five low-frequency BGs in the 200[Formula: see text]Hz frequency band, which increased the total width of the opened BGs by 49% compared to traditional PC wave barriers. In the frequency range of the BG, the attenuation value of the novel PLCSWB to vibration is mostly above 30[Formula: see text]dB, and the energy distribution inside the structure is mainly concentrated in the primitive cell that controls the BG, indicating good attenuation and control effects on vibration. The main factors affecting the BG of the novel PLCSWB are the density of the scatterer material, the elastic modulus, and the thickness of the wrapping layer material. Moreover, during subway operation, the novel PLCSWB has a good attenuation effect on the vibration transmitted from the tunnel wall to the soil. Among them, the maximum vibration acceleration amplitude of the novel PLCSWB with nine rows is reduced by 47%, and the vibration isolation performance is remarkable. The relevant research results of this paper provide a novel approach and method for the study of subway vibration reduction and isolation, and can also provide specific references for the design and development of wave barriers.

An Equivalent PCS Model for Energy Storage System

Abstract The power conversion system (PCS) for energy storage system (ESS) has been rapidly developed in recent years, due to the more and more integration of new energy sources. Before the large-scale applications of PCSs in practice, the simulation works are essential to verify its performances. The conventional switching PCS model has been reliably used to complete simulation work, when the number of PCS is less. Nevertheless, when the simulation work with large-scale PCSs is carried out, the number of PCS will be enormous, the simulation work will be difficult to be completed by the switching PCS model, because of the unacceptable long simulation time. Hence, an equivalent PCS model is needed and proposed in this paper. The topology and control mothed of the equivalent PCS model are concretely introduced. The simulation works with steady state and dynamic process are completed by both switching PCS model and the proposed equivalent PCS model. The compared results illustrate the high accuracy of proposed equivalent PCS model. The real simulation times for two models are calculated and compared, which illustrates the high rapidity of proposed equivalent PCS model.

Research on simulation accuracy of equivalent aggregate electromagnetic model optimization for large renewable energy stations

Abstract The traditional power grid is rapidly transforming into a new power system with high penetration of new energy. Simulation modeling plays an important role in supporting the cognition and research of the new power system. A high proportion of renewable energy is connected to the grid through power electronic components, which puts forward a higher demand for research on the accuracy and stability of power grid simulation modeling. Renewable energy plants usually have a large number of single units, and equivalent aggregation modeling is the usual way to simplify the modeling of renewable energy plants. However, the transmission line power multiplier equivalent module inevitably introduces series impedance into the network, resulting in errors between simulation and actual engineering. Therefore, the study of lossless multiplier elements based on Modified Nodal Analysis (MNA) can improve the simulation accuracy, and it is verified with the simulation results of detailed models in actual scenarios, proving that MNA lossless multiplier elements can optimize the accuracy and stability of equivalent aggregation modeling of large-scale multi-unit renewable energy stations.

РОЗРАХУНОК РЕГУЛЮВАЛЬНИХ ХАРАКТЕРИСТИК РЕЗОНАНСНИХ ПЕРЕТВОРЮВАЧІВ МЕТОДОМ СУПЕРПОЗИЦІЇ

The work presents the calculations of the control characteristics of the full-bridge resonant converter with a series resonant LLC circuit and frequency control by two methods - the first harmonic method and the superposition method. The theoretical results were verified by the analytical-structural modeling method. The power circuit of the resonant converter for the analysis of electromagnetic processes is replaced by a linear T-shaped circuit with two series resonant RLC-circuits and equivalent generators of rectangular voltages, which simulate a transistor inverter and a diode rectifier in the quasi-continuous current mode. Analytical-structural modeling method consists in partly analytical and partly structural ways of building a numerical model of the resonant converter in the form of the simulation model in the MATLAB-Simulink environment. Linear structural links of the model are created on the basis of integral equations of circles. Non-linear links are created based on the non-linear functions and causal relationships. The structural model based on these links takes into account the nonlinearity of the elements of the power circuit of the resonant converter and is based on simpler mathematical expressions compared to the equivalent mathematical model of the resonant converter. The structural model corresponds to the idea of the resonant converter in the form of the resonant circuit with independent equivalent voltage generators and allows to adjust the magnetic coupling coefficient between the transformer windings and simulate processes with arbitrary control functions of equivalent generators. The peculiarity of the use of the superposition method for calculating the static characteristics of the resonant converter is the need to match the voltage phases of the equivalent generators of the equivalent circuit during the changes of the operating frequency or relative load voltage. The dependence of the input voltage of the rectifier, which is simulated by the second equivalent generator, on the processes of the power circuit of the real resonant converter, determines the conditions for matching (adjusting) the phases of the equivalent generators. References 30, figures 5.

Numerical Analysis of Structural Vibrations in Masts—A Practical Study Applied to a 28-Meter Tugboat

This article investigates the vibration analysis of the mast on the bridge top of a 28 m tugboat, in the quasi-static regime. The study aims to determine the natural frequencies using an equivalent dynamic model of the mast and considers the accelerations of different degrees of freedom of the vessel. Practical design and reinforcement strategies for the local bridge top structure are proposed, utilizing numerical and analytical tools. The investigation explores various alternatives to optimize the structural arrangement. By analyzing the modal behavior, insights are provided for efficient design and reinforcement. The results contribute to understanding the mast’s vibration characteristics, offering guidance for similar structures. This study employs numerical and analytical methods, enhancing the optimization of the mast’s behavior. It determines natural frequencies, proposes practical design strategies, and explores alternatives for structural optimization. The findings provide insights for shipbuilding and mast design applications in other vessels and industries such as radar mast, compass deck, and guyed mast.

Application of multi-label convolutional neural networks on enhancement of reliability of classification, a case study on bearing fault diagnostics

In contrast to the mutli-class classification where one and only one class would be assigned to each instance, multi-label classification allows for more flexible classification and possibility of having multiple labels for instance. This property enables us to model the dependencies between the classes such as effect of one label on the probability of occurrence of the other label. Considering these connections between the classes can help us to enhance the reliability of classifier and handle the contradictory prediction. Much like how we can assign multiple classes to an instance, we can also have an instance that remains unlabeled. This class is typically referred to as the "neutral" label, allowing us to bluntly state that we lack sufficient information to label the instance with adequate certainty. Leveraging these properties, a 1D convolutional neural network (CNN) has been proposed to classify common faults occurring in the bearings. Network has the capability to assign a Confidence level between 0 to 1 to each class independently. Later, a threshold has been set on each class to identify the instance labels if any. Subsequently, instances with contradictory predicted label have been flagged as undetermined and removed from the predicted result. thus, the remaining classified instances can be labeled with sufficient confident. In the end, the multi-label CNN model performance has been compared with equivalent multi-class CNN model. Technique has been evaluated using MAFAULDA open dataset which is composed of 1951 multivariate time-series acquired by a triaxial accelerometer, a microphone, and a tachometer using SpectraQuest’s Machinery Fault Simulator (MFS) experimentally simulating different bearing states including normal operation as well as inner and outer race bearing faults. A data reduction scheme has been performed on the dataset to make the diagnostic more challenging and evaluate the performance of CNN in more realistic condition with insufficient data.

Research on equivalent modeling of wideband dielectric response of oil-paper insulation based on the Kramers-Kronig transform

Research on equivalent modeling of wideband dielectric response of oil-paper insulation based on the Kramers-Kronig transform