Generator Model Research Articles

Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving

We present the Process Engineering Operations Assistant (PEOA), an AI-driven framework designed to solve complex problems in the chemical and process industries. The framework employs a modular architecture orchestrated by a meta-agent, which serves as the central coordinator, managing an action generator and instruction-tuned small-scale language models (expert models). The action generator decomposes complex problems into sub-tasks and identifies suitable expert models to execute each, delivering precise solutions for multi-step problem-solving. Key techniques include advanced knowledge modeling using property graphs for improved information retrieval, facilitating more accurate and contextually relevant solutions. Additionally, the framework utilizes a teacher-student transfer-learning approach with GPT-4 (Omni) to fine-tune the action generator and expert models for domain adaptation, alongside an iterative problem-solving mechanism with sophisticated error handling. Custom datasets were developed to evaluate the framework against leading proprietary language models on various engineering tasks. The results demonstrate the framework’s effectiveness in automating calculations, accelerating prototyping, and providing AI-augmented decision support for industrial processes, marking a significant advancement in process engineering capabilities.

Dynamic Control of Piezoelectric Sandwich Beams with Multi-Frequency Excitations

In this work, we present a non-linear analysis of the dynamics of a sandwich beam with piezoelectric patches under multi-frequency excitations. The model takes into account geometrical non-linearities, piezoelectric non-linearities, and inertia. Hamilton’s principle is used to determine the electromechanical equation of motion, and Garlekin’s technique is used to determine the equivalent model of the piezoelectric generator. A mathematical methodology based on the multi-scale method for vibration control and stability is reviewed in this work to determine a system of amplitude and phase equations. The control of primary and secondary mode resonances is developed, and feedback effects are analyzed for small and large amplitudes of vibrations of sandwich beams. Frequency response curves are presented and discussed for various gain parameters.

High-Resolution SAR-to-Multispectral Image Translation Based on S2MS-GAN

Synthetic aperture radar (SAR) has been extensively applied in remote sensing applications. Nevertheless, it is a challenge to process and interpret SAR images. The key to interpreting SAR images lies in transforming them into other forms of remote sensing images to extract valuable hidden remote sensing information. Currently, the conversion of SAR images to optical images produces low-quality results and incomplete spectral information. To address these problems, an end-to-end network model, S2MS-GAN, is proposed for converting SAR images into multispectral images. In this process, to tackle the issues of noise and image generation quality, a TV-BM3D module is introduced into the generator model. Through TV regularization, block-matching, and 3D filtering, these two modules can preserve the edges and reduce the speckle noise in SAR images. In addition, spectral attention is added to improve the spectral features of the generated MS images. Furthermore, we construct a very high-resolution SAR-to-MS image dataset, S2MS-HR, with a spatial resolution of 0.3 m, which is currently the most comprehensive dataset available for high-resolution SAR-to-MS image interpretation. Finally, a series of experiments are conducted on the relevant dataset. Both quantitative and qualitative evaluations demonstrate that our method outperforms several state-of-the-art models in translation performance. The solution effectively facilitates high-quality transitions of SAR images across different types.

Unlocking the potential of simulated hyperspectral imaging in agro environmental analysis: a comprehensive study of algorithmic approaches

This study focuses on identifying and evaluating the severity of powdery mildew disease in tomato plants. The uniqueness of this work lies in combining the imaging and advanced deep learning methods to develop a technique that transforms Red Green Blue (RGB) images into Simulated Hyperspectral Images (SHSI) to perform spectral and spatial analysis for precise detection and assessment of powdery mildew severity, thereby enhancing disease management. Furthermore, this research evaluates three advanced pre-trained VGG16 models, ResNet50 and EfficientNet-B7 algorithms for image preprocessing and feature extraction. Extracted features are passed to a neural network generator model to convert RGB image features into SHSIs, providing insights into the spectrum. This method enables the image analysis to perform assessments from SHSIs for health classification using Normalized Difference Vegetation Index (NDVI) values, which are meticulously compared with accurate hyperspectral data using metrics like mean absolute error (MAE) and root mean squared error (RMSE). This strategy enhances precision farming, environmental monitoring, and remote sensing accuracy. Results show that ResNet50’s architecture offers a robust framework for this study’s spectral and spatial analysis, making it a suitable choice over VGG16 and EfficientNet-B7 for transforming RGB images into SHSI. These simulated hyperspectral images offer a scalable and affordable approach for precise assessment of crop disease severity.

УНІВЕРСАЛЬНА МАТЕМАТИЧНА МОДЕЛЬ АВТОНОМНОГО АСИНХРОННОГО ГЕНЕРАТОРА З КОНДЕНСАТОРНИМ САМОЗБУДЖЕННЯМ

A universal mathematical model of an autonomous asynchronous generator with capacitor self-excitation in retarded phase coordinates is proposed, taking into account the electromagnetic connections between the windings of the stator and rotor phases, saturation of the main magnetic circuit, and active power losses in the magnetic circuit elements. The model provides an opportunity to analyze stable periodic modes and transient electromagnetic and electromechanical processes in autonomous power supply systems with arbitrary switching schemes of its elements and asynchronous generators. The model provides the possibility of taking into account the residual magnetization of the magnetic circuit of an asynchronous generator and the change in rotor speed during the course of the self-excitation process of an asynchronous generator with a grounded neutral of the stator winding and an asymmetric load. References 10, figures 2.

A novel hybrid CNN-GRU model for website-based user interface code generator

As software engineering techniques evolve, conventional methods become less efficient due to prolonged development cycles and repetitive tasks. There is a growing need for automated systems that can incorporate User Interface (UI) designs into code. This study proposes a novel Hybrid CNN-GRU model for automatically generate website-based UI codes from UI design images. The proposed method consists of a visual model and a language-decoder part. The visual model employs pretrained CNN models, including EfficientNetV2B0, Xception, and EfficientNetV2M, to extract features from images, whereas a GRU serves as the language model and decoder. An empirical study was conducted to evaluate the effectiveness of various hybrid CNN-GRU approaches for generating UI codes. The EfficientNetV2B0 GRU model demonstrated the fastest training time, whereas the Xception GRU model was the most robust for various data complexities. The results of this study will advance the field of automated code generation, simplify the front-end development process, and shorten the time and effort necessitated for UI code implementations.

An Analysis of a Complete Aircraft Electrical Power System Simulation Based on a Constant Speed Constant Frequency Configuration

Recent developments in aircraft electrical technology, such as the design and production of more electric aircraft (MEA) and major steps in the development of all-electric aircraft (AEA), have had a significant impact on aircraft’ electrical power systems (EPSs). However, the EPSs of the latest aircraft produced by the main players in the market, Airbus with the Neo series and Boeing with the NG and MAX series are still completely traditional and based on the constant speed constant frequency (CSCF) configuration. For alternating current ones, the EPS is composed of the following: prime movers, namely the aircraft turbofan engine (TE); the electrical power source, i.e., the integrated drive generator (IDG); the command and control system, the generator control unit (GCU); the transmission and the system distribution system; the protection system, i.e., the CBs (circuit breakers); and the electrical loads. This paper presents the analysis of this system using the Simscape package from Simulink v 8.7, a MATLAB v 9.0 program, which is actually the development of some systems designed in two previous personal papers. For the first time in the literature, a complete MATLAB modelled EPS system was presented, i.e., the aircraft turbofan engine model, driven by the constant speed drive system (CSD) (model presented in the first reference as a standalone type and with different parameters), linked to the synchronous generator (SG) (model presented in second reference for lower power and rotational speed) in the so-called integrated drive generator (IDG) and electrical loads.

Stable Walking of a Biped Robot Controlled by Central Pattern Generator Using Multivariate Linear Mapping.

In order to improve the walking stability of a biped robot in multiple scenarios and reduce the complexity of the Central Pattern Generator (CPG) model, a new CPG walking controller based on multivariate linear mapping was proposed. At first, in order to establish a dynamics model, the lower limb mechanical structure of the biped robot was designed. According to the Lagrange and angular momentum conservation method, the hybrid dynamic model of the biped robot was established. The initial value of the robot's passive walking was found by means of Poincaré mapping and cell mapping methods. Then, a multivariate linear mapping model was established to form a new lightweight CPG model based on a Hopf oscillator. According to the parameter distribution of the new CPG model, a preliminary parameter-tuning idea was proposed. At last, the joint simulation of MATLAB and V-REP shows that the biped robot based on the new CPG control has a stable periodic gait in flat and uphill scenes. The proposed method could improve the stability and versatility of bipedal walking in various environments and can provide general CPG generation and a tuning method reference for robotics scholars.

Active Support Pre-Synchronization Control and Stability Analysis Based on the Third-Order Model of Synchronous Machine

When traditional grid-forming converters directly participate in the grid-connected operation of the power grid, due to the lack of a pre-synchronization control system, the voltage amplitude and initial phase on both sides of the grid-connected point will deviate, resulting in voltage and current distortion during grid-connected mode. An active support phase-locked loop free pre-synchronization control strategy based on the third-order model of a synchronous generator is proposed to address the grid-connected problem of the grid-forming converter mentioned above. First, a model of active support control with frequency integral feedback at small signal levels was constructed. The root locus method was employed to examine how system parameters affect the stability of the active support control system. Second, by adding phase pre-synchronization controllers and amplitude pre-synchronization controllers to the active frequency loop and excitation voltage loop of the third-order model, it was ensured that the frequency, phase, and voltage amplitude of the unit are consistent with the power grid, achieving a fast and smooth grid-connected mode of the unit. Finally, by using a DC source to simulate all types of new energy power generation equipment, the active support pre-synchronization control system based on the three-order model of synchronous generator is built in the MATLAB/Simulink simulation environment, and the accuracy and effectiveness of the control strategy in this paper is verified.

Online Monitoring System of Electromechanical Transient Simulation Data of Distribution Network Based on Edge Computing

The current distribution network is developing toward the direction of information and intelligent distribution Internet of Things (IoT). In order to explore the online monitoring system for transient electromechanical simulation of distribution networks, this paper is based on the equivalent model of generator sets. Firstly, it describes the relevant theoretical knowledge of edge computing, designs the distribution IoT based on edge computing, and briefly introduces its network architecture. Secondly, based on the discrete-time domain equivalent model of generators, the electromechanical transient simulation distribution network is constructed by introducing the machine network division of the power network. Finally, the Western System Coordinating Council (WSCC)-3 units and 9 nodes are taken as an example, and simulation experiments are conducted under two fault simulation conditions to verify the effectiveness of the simulation model. The results show that under the two fault simulation conditions, the results of equivalent model simulation of generator terminal voltage and relative power angle change are like those of the Power System Analysis Software Package (PSASP). The changing trend of the two is similar and stable. After the PSASP results are stabilized at a value, the simulation results fluctuate extremely up and down the value. For example, under fault condition 1, the changing trend of the relative power angle of the No. 2 generator is first fluctuating and then becomes stable. After violent fluctuation, the relative power angle tends to be stable from about 20s to -12.35°. The result of PSASP software is stable at -12.35°. The transient electromechanical simulation of the generator equivalent model can provide some ideas for the online monitoring system of the distribution network.

Effect of Axial Clearance Between Turbine and Guide Wheel on Hydraulic Performance of Mine Borehole Turbo Generator

Abstract In order to study the influence law of axial clearance between turbine and guide wheel on the performance of mine turbine generator. The three-dimensional unsteady internal flow and external characteristics of 8 kinds of turbine generator models with different coaxial clearance are calculated. The results show that: As the axial clearance coefficient between the turbine and the guide wheel increases, the pressure loss at the inlet and outlet of the guide wheel and turbine increases gradually, the torque and shaft power of the turbine are reduced, the hydraulic efficiency of turbine generator decreases gradually; The hydraulic efficiency of the turbine increases first and then decreases. Considering the external and internal flow characteristics comprehensively, the axial clearance coefficient between the turbine and the guide wheel is between 0.12 and 0.15, and the turbine generator performance is the best. It can provide some reference for the design optimization of Mine Borehole Turbo Generator.

Research on inertia characteristics of two-stage photovoltaic systems under generalized sag control

With the vast majority of photovoltaic (PV) power generation linked to the grid, the mainstream maximum power point tracking control cannot provide effective inertia support capability for the system. This paper examines the inertia source and action rules of three typical grid-tied photovoltaic systems under generalized sag control at the physical mechanism level, using the theory of the static synchronous generator model as a guide. It is found that the PV system under generalized sag is also capable of supporting the system through inertia. The boost converter, direct current bus capacitor, and inverter all contribute to the inertia capability of the PV system, but it is necessary to couple the control of the responding link with the grid frequency. The closer the action link is to the grid, the faster the speed of the corresponding grid frequency, but the weaker the inertia effect is provided to the system. The accuracy of the aforementioned analysis is confirmed by the simulation.

Strategy for enhancing energy conversion efficiency and cyclist helmet safety: A theoretical and experimental study of diverse thermoelectric generator models

Recent studies have focused on Thermoelectric Generators (TEGs) as a key to sustainable energy, using thermal power through temperature differentials to produce electric power. Despite the promise of TEGs, there is diversity of TEG models and the shortage of comprehensive evaluations on energy conversion. In particular, measuring the output of electrical energy and time of production across temperature variances, which has impeded their broad adoption. This research conducted a comprehensive analysis of TEG models. It used a new test rig designed in SolidWorks and actualized, coupled with MATLAB simulations to validate the predicted results. This includes developing a wearable device such as a helmet-mounted warning light for motorcyclists or cyclists. In the study, five different thermoelectric generator models (TEG1-12703, TEG1-12706, TEG1-12709, TEG1-12712, and TEG1-12715) were tested, these models showed varying power outputs of 66.46, 97.51, 117.5, 191.72 and 358.74 mW. Their efficiencies were 1.78 %, 1.982 %, 2.097 %, 2.567 % and 2.93 %, respectively, when ΔT reaches 30 °C. The experimental and theoretical data indicate discrepancies in results and thermal response delays due to heat transfer and energy conversion within the test rig’s layers. These discrepancies were addressed to adjust simulations closer to reality. A differential correction ratio (19.133 % for power, 17.94 % for efficiency) was applied to enhance prediction accuracy. After adjustment, the maximum power generation reached 1.64355, 2.8386, 3.83433, 4.6843, 4.96746 W. The maximum efficiency peaked at 2.236, 3.59462, 4.1184, 6.278154, 6.75779 %, respectively, when ΔT reaches 70 °C. The output power and efficiency from these TEGs could run certain sensors.The study shows that TEG model 12,715 excels in generating electrical energy with large temperature differences. However, its output nearly vanished under a 1 °C differential, ending tests prematurely. In contrast, the model 12,703 consistently generates electricity over long periods (more than 420 min) under minimal temperature differential, while it is unable to produce high power under greater differentials. This suggests that using diverse TEG models and integrating together to enhance the efficiency and continuity of free energy generation, depends on the models’ varied performance and temperature differences. Utilizing the results, five TEG units connected in parallel were installed on a cyclist’s helmet to power a rear warning light, this installation enhances night-time safety. These TEG models demonstrated continuous power generation, producing an average of 55.7 mW per hour with a temperature difference ΔT between 3.2 °C and 7.4 °C.

Performance investigation of a thermoelectric generator for vehicle exhaust recovery using graded pore density foam metal

Improving the efficiency of thermoelectric generators (TEGs) used to harness residual heat from automobile exhausts is crucial for their widespread adoption. To enhance fluid heat transfer, the Kelvin tetrahedron model is employed for metal foam, and a multiphysical field model of the thermoelectric generator based on metal foam is established. The effects of inserting metal foam with uniform and gradient pore densities into the heat exchanger on the performance of the TEG are investigated. Experimental verification is conducted by constructing a test bench with dimensions identical to those of the model The findings suggest that inserting foam metal significantly enhances the output performance of the TEG, resulting in increases in both output power and efficiency as pore density rises. At Ta = 573 K and ma = 30 g/s, the output power of the TEG with inserted 20 PPI foam metal is enhanced by 140.46 %, while the efficiency experiences a remarkable increase of 197.50 % compared to a smooth pipe. Compared to the performance metrics of uniform foam metal, the positive gradient foam metal exhibits a maximum power increase of 7.89 % and a maximum efficiency increase of 34.46 %, along with an average pressure drop reduction of 27.29 %.

Control of a 15MW off-shore wind turbine for black-start operation

Grid forming wind turbines are crucial for achieving a 100% renewable based grid. The mechanical control of the wind turbines is usually designed for maximum power tracking operation. This paper includes the development of a wind turbine pitch controller considering the wider operational range of a grid forming wind turbine. The proposed controller tracks the optimal generation characteristic of the wind turbine when grid connected and is designed to cater for the different power levels when the wind turbine is operated in islanded mode (or grid-connected at partial power). The proposed controller does not require wind speed estimation for its operation and shows better performance than standard pitch controllers during grid-forming operation, particularly, limiting wind turbine speed excursion during block de-loading. Moreover, the proposed controller does not increase the mechanical loads of the key wind turbine elements. The performance of the proposed control is validated in a black start procedure with a full wind farm realistic real-time simulator, including detailed electrical and aeroelastic models of the wind turbine generator, wind farm and connecting HVDC link. Time and frequency domain validation using the real-time model has shown the performance of the proposed controller during black start operation.

Deep-learning-based generative design for optimal reactive silencers

A deep-learning-based generative design method is proposed to improve the frequency-dependent characteristics of a reactive silencer, and it has been validated both numerically and experimentally. The noise attenuation performance of the reactive silencer is evaluated with its transmission loss (TL), which varies with frequency and strongly depends on the partition layout inside the reactive silencer. The artificial neural network model for the generative design of the reactive silencer consists of three subnetwork models: the generator, predictor, and converter. The generator model created numerous partition layouts, and their TL curves were estimated using the predictor model. A converter model was developed to identify the frequency-dependent characteristics of the TL curves in a low-dimensional latent space. The latent space was extensively investigated to successfully select the optimal partition layouts satisfying given design requirements, including the target shape of the TL curve and its averaged target TL value. The effectiveness of the proposed method was demonstrated by applying it to three reactive silencer design problems with different design requirements. Among the three optimal silencers, one was physically investigated, and its noise attenuation performance was validated with an acoustic experiment. Because the artificial neural network model of the proposed method was developed for a normalized silencer and requires no prior knowledge of acoustics, it can be easily applied to reduce duct noise in the industry.

FEHD model of a synchronous wind turbine generator aimed at frequency transient simulation

Frequency dynamics analysis and simulation of variable frequency systems, e.g., a synchronous wind turbine generator (WTG), require the use of models capable of accurately replicate frequency dynamics and faithfully mirror the actual behavior of their components.A commonly used methodology that models frequency dynamics, in a straightforward manner, is the flexible extended harmonic domain (FEHD). There are several FEHD models available for different types of electrical and electronic systems; however, there is a lack of a suitable FEHD approach designed to handle variable frequency systems. This lack hindered the exploration of this particular aspect in the realm of electrical system modeling.To overcome the abovementioned gap, this paper introduces a novel FEHD approach and a dedicated model approximation for the analysis of variable frequency systems. The proposed FEHD methodology exhibits significant advantages over traditional FEHD and PSCAD simulations when it comes to display, accurately and in a straightforward manner, the frequency evolution of variable frequency systems. This proposed FEHD approach shows an impressive degree of flexibility and adaptability, contributing to a more thorough comprehension of the dynamic behavior.A case study of a wound rotor synchronous WTG is presented to validate the proposed methodology.

A Computer Model of a Marx Generator Charging a Coaxial Switched Wave Oscillator

The paper describes an axisymmetric Finite-Difference Time-Domain computer model of a coaxial Switched Wave Oscillator integrated with a dipole antenna. The model analyzes the operation of a realistic circuit model of a multistage Marx generator that charges the oscillator to a high voltage. The initial field distribution is calculated with an electrostatic finite-difference method solver to speed up the time-domain analysis. The work presents the results of our circuit model of a Marx generator’s simulations of the charging phase, followed by the results from the discharge phase, using our axisymmetric Finite-Difference Time-Domain model. Our work describes new and fast numerical solvers that can observe the operation of Switched Wave Oscillator systems (also considering the connected antenna). The codes could be used in the process of designing such a system. Advanced boundary conditions modeling the spark gap and oscillator’s excitation set our work apart from the other attempts in the literature.

Walking on different inclines affects gait symmetry differently in the anterior-posterior and vertical directions: implication for future sensorimotor training

A symmetric gait pattern in humans reflects near-identical movement in bilateral limbs during walking. However, little is known about how gait symmetry changes on different inclines. This study aimed to address this knowledge gap using the central pattern generator and internal model hypotheses. Eighteen healthy young adults underwent five 2-minute walking trials (inclines of +15%, +8%, 0%, −8%, and −15%). Dependent variables included step time, step length, step width, maximum heel clearance, time to peaks of maximum heel clearance, their corresponding coefficients of variation (CV), and respective symmetry indices (SI). Significant differences were observed in SI of step length (p = .022), step length variability (p < .001), step width variability (p =.001), maximum heel clearance (p < .001), and maximum heel clearance variability (p = .049). Compared to level walking, walking at −8% and −15% inclines increased SI of step length (p = .011, p = .039 respectively) but decreased SI of maximum heel clearance (p = .025, p = .019 respectively). These observations suggested that incline walking affected gait symmetry differently, possibly due to varied internal models used in locomotion. Downhill walking improved vertical gait symmetry but reduced anterior-posterior symmetry compared to level walking. Downhill walking may be a preferable rehabilitation protocol for enhancing gait symmetry, as it activates internal model controls. Even slight downhill inclines could increase active control loading, beneficial for the elderly and those with impaired gait.

Comprehensive Analysis on Rotor Vibration Characteristics Based on a Novel Dynamic Stator Interturn Short Circuit Model of Synchronous Generator

Comprehensive Analysis on Rotor Vibration Characteristics Based on a Novel Dynamic Stator Interturn Short Circuit Model of Synchronous Generator