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This work identifies and models the inline devices in an experimental surface-plasmon resonance spectroscopy setup to determine the system's transfer function. This allows for the comparison of theoretical and experimental responses and the analysis of the dynamics of the components of an analyte placed on the sensor at the nanometer scale. The transfer functions of individual components, including the light source, polarizers, spectrometer, optical fibers, and the SPR sensor, were determined experimentally and theoretically. The theoretical model employed Planck's law for the light source, manufacturer specifications for some components, and experimental characterization for others, such as the polarizers and optical fibers. The SPR sensor was modeled using characteristic matrix theory, incorporating the optical constants of the prism, gold film, chromium adhesive layer, and analyte. The combined transfer functions created a comprehensive model of the entire experimental system. This model successfully reproduced the experimental SPR spectrum with a similarity greater than 95%. The system's operational range was also extended, constrained by the signal-to-noise ratio at the spectrum's edges. The detailed model allows for the accurate correction of the measured spectra, which will be essential for the further analysis of nanosuspensions and molecules dissolved in liquids. [ABSTRACT FROM AUTHOR]

The “hard water” factor shows the management of water in the Nusa Tenggara Timur, which shows a higher ratio based on the ion’s minerals. The incessant use of hard water presents kidney dysfunction, which produces diabetic and vascular kinds of diseases. Therefore, it is essential to recognize the influences of hard water on kidney function. A novel design of a stochastic solver using the transfer radial basis function is provided by applying the Bayesian regularization neural network for solving the model. The kidney dysfunction mathematical system is divided into humans (susceptible, infected, recovered) and water components (magnesium, calcium). Twelve numbers of neurons with the radial basis transfer function have been used in the hidden layers for solving the model. The approach performance is remarked through the results comparison and further reducible absolute error found around 10−06 to 10−08 develop the scheme’s exactness. Moreover, the statistical performances including regression coefficient performances around 1 for each case of the model validate the reliability and exactness of the scheme for solving the model. [ABSTRACT FROM AUTHOR]

Multiple tuned mass dampers (MTMDs) reduce dynamic response with multiple specified frequencies of building structures. Many optimization algorithms for placement design exist, though they rarely conform to code-based verification nor produce high quality solutions without high computational effort and high complexity. This study proposes an inverse element exchange method (IEEM) with multi-level programming and compares it to a single tuned mass damper (STMD) and uniform distribution of multiple tuned mass dampers in the frequency and time domains. A ten-story shear building is used for the numerical case study. The results show that the proposed method can offer improvement over the STMD, uniform distribution of multiple tuned mass dampers, and distribution optimized by genetic algorithms (GA) with regard to minimizing the interstory drift ratio (IDR) in both the frequency and time domains and the time consumption for optimization. [ABSTRACT FROM AUTHOR]

The pavement mechanistic-empirical design (PMED) is a widely used pavement analysis and design approach. The transfer functions are generally calibrated to implement the PMED for local conditions. The least square (LS) approach has been commonly used to calibrate these transfer functions. Although LS is a simplistic approach, the assumptions may not be valid, especially for non-normally distributed data. This paper uses the maximum likelihood estimation (MLE) approach to calibrate bottom-up cracking, total rutting, and international roughness index (IRI) transfer function for flexible pavements. The results show that overall, MLE outperforms the LS approach for synthetic and measured data. The difference is more evident in the case of bottom-up cracking data, which does not follow a normal distribution. Gamma distribution for bottom-up cracking and total rutting, whereas negative binomial for IRI is the most suitable distribution for the MLE approach. Overall, MLE using resampling methods provides a robust and better estimate than the LS approach. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative algorithm for forecasting the motion response of floating offshore wind turbines by employing force-to-motion transfer functions and state-space models. Traditional numerical integration techniques, such as the Newmark-β method, frequently struggle with inefficiencies due to the heavy computational demands of convolution integrals in the Cummins equation. Our new method tackles these challenges by converting the problem into a system output calculation, thereby eliminating convolutions and potentially enhancing computational efficiency. The procedure begins with the estimation of force-to-motion transfer functions derived from the hydrostatic and hydrodynamic characteristics of the wind turbine. These transfer functions are then utilized to construct state-space models, which compactly represent the system dynamics. Motion responses resulting from initial conditions and wave forces are calculated using these state-space models, leveraging their poles and residues. We validated the proposed method by comparing its calculated responses to those obtained via the Newmark-β method. Initial tests on a single-degree-of-freedom (SDOF) system demonstrated that our algorithm accurately predicts motion responses. Further validation involved a numerical model of a spar-type floating offshore wind turbine, showing high accuracy in predicting responses to both regular and irregular wave conditions, closely aligning with results from conventional methods. Additionally, we assessed the efficiency of our algorithm over various simulation durations, confirming its superior performance compared to traditional time-domain methods. This efficiency is particularly advantageous for long-duration simulations. The proposed approach provides a robust and efficient alternative for predicting motion responses in floating offshore wind turbines, combining high accuracy with improved computational performance. It represents a promising tool for enhancing the development and evaluation of offshore wind energy systems. [ABSTRACT FROM AUTHOR]

Purpose: In order to solve the factors affecting the modeling of seismic shaking table array system, the transfer function of two-array system under three-parameter and multi-parameter control is studied, and the nonlinear characteristics of the system are considered. Methods: In-depth modeling analysis was performed by using MATLAB/Simulink software. Results: The results show that the peak value decreases and the notch increases with the damping ratio increasing, and the interaction effect of G11 and G22 decreases with the damping ratio increasing. In addition, the increase of the mass and natural frequency of the specimen not only leads to the increase of the peak value, but also the decrease of the notch wave, and the interaction effect of G11 and G22 becomes more obvious. Conclusion: These results provide important theoretical support for the optimization of the shaking table array system in order to improve its effectiveness in seismic simulation applications. [ABSTRACT FROM AUTHOR]

Since the modern automatic control theory imposes constraints on the mathematical models of control objects, further development and verification of mathematical models of nuclear power facilities suitable for the synthesis of automatic power control systems is a topical problem. This article deals with a low-order dynamic model with lumped parameters of the Russian-designed pressurized water reactor, as well as with its verification with experimental data from the full-size simulator of the VVER–1200 nuclear reactor in two tests involving the variation of the position of group 12 of CPS CR and the variation of the inlet coolant temperature. This model was created as a MATLAB S-function lv.2 model because of its capability to process any input signals. Within this approach, the equation describing the heating of the coolant is represented as a «two well-stirred tanks in series» model. The article demonstrates the advantage of the given approach over the conventional approach, where the average temperature of the coolant is determined as the arithmetic mean of the inlet and outlet coolant temperatures on the basis of a test with a sudden change in the reactor inlet coolant temperature. In the frequency domain, the authors carry out the stability analysis of the given model in the state-space form with respect to various external perturbations. Conclusions are drawn about the possibility of using the model as a fifth-order control object for the parametric synthesis of a controller for the automatic power control system of a nuclear power facility. [ABSTRACT FROM AUTHOR]

Power transformers, as critical components in regional power distribution and transmission systems, require early fault detection to ensure system reliability. This paper presents a scalable design capable of rapidly simulating winding faults in experimental transformers. By diagnosing three-phase transformer winding short-circuit faults using oscillatory shock voltages and numerical statistical methods, the relationship between the transfer function and winding short-circuit faults is investigated. The experimental results show that winding short-circuit faults cause significant changes in the transfer function curve. By analyzing transfer function variations across different phases, the location of a fault can be effectively determined. Furthermore, the correlation coefficient and absolute logarithmic deviation provide a clear indication of the fault severity. The transfer function of the high-voltage phase-to-phase is particularly sensitive to winding short-circuit faults. In non-fault phases, after the application of damped oscillatory waves, the transfer function correlation coefficient becomes negative and the absolute logarithmic deviation increases linearly with fault severity. These findings provide a rapid diagnostic solution for determining both the faulty phase and the severity of damage in three-phase transformer winding short-circuit faults. [ABSTRACT FROM AUTHOR]

This paper explores the importance of the electric eel foraging optimization (EEFO) algorithm in addressing feature selection (FS) problems, with the aim of ameliorating the practical benefit of FS in real-world applications. The use of EEFO to solve FS problems props our goal of providing clean and useful datasets that provide robust effectiveness for use in classification and clustering tasks. High-dimensional feature selection problems (HFSPs) are more common nowadays yet intricate where they contain a large number of features. Hence, the vast number of features in them should be carefully selected in order to determine the optimal subset of features. As the basic EEFO algorithm experiences premature convergence, there is a need to enhance its global and local search capabilities when applied in the field of FS. In order to tackle such issues, a binary augmented EEFO (BAEEFO) algorithm was developed and proposed for HFSPs. The following strategies were integrated into the mathematical model of the original EEFO algorithm to create BAEEFO: (1) resting behavior with nonlinear coefficient; (2) weight coefficient and confidence effect in the hunting process; (3) spiral search strategy; and (4) Gaussian mutation and random perturbations when the algorithm update is stagnant. Experimental findings confirm the effectiveness of the proposed BAEEFO method on 23 HFSPs gathered from the UCI repository, recording up to a 10% accuracy increment over the basic BEEFO algorithm. In most test cases, BAEEFO outperformed its competitors in classification accuracy rates and outperformed BEEFO in 90% of the datasets used. Thereby, BAEEFO has demonstrated strong competitiveness in terms of fitness scores and classification accuracy. When compared to its competitors, BAEEFO produced superior reduction rates with the fewest number of features selected. The findings in this research underscore the critical need for FS to combat the curse of dimensionality concerns and find highly useful features in data mining applications such as classification. The use of a new meta-heuristic algorithm incorporated with efficient search strategies in solving HFSPs represents a step forward in using this algorithm to solve other practical real-world problems in a variety of domains. [ABSTRACT FROM AUTHOR]

For the description of power transmission through drive links, a system of linear first-order differential equations has been applied taking into account the accelerations and rates of changes in stresses under torsional and transverse oscillations. An eighth order vector equation has been derived and solved, including algebraic elements, making it possible to calculate the fluctuations of stresses and motion velocities in any link of the system to a first approximation with the use of an engineering method. For a particular drive, the effect of the inertial properties of the load and the features of resistance torque formation exerted on the dynamic characteristics of the drive has been analyzed. [ABSTRACT FROM AUTHOR]

Objectives: Blood pressure (BP) management is challenging in patients with acute ischemic supratentorial stroke undergoing recanalization therapy due to the lack of established guidelines. Assessing dynamic cerebral autoregulation (dCA) may address this need, as it is a bedside technique that evaluates the transfer function phase in the very low-frequency (VLF) range (0.02–0.07 Hz) between BP and cerebral blood flow velocity (CBFV) in the middle cerebral artery. This phase is a prognostically relevant parameter, with lower values associated with poorer outcomes. This study aimed to evaluate whether early cranial computed tomography perfusion (CTP) can predict this parameter. Methods: In this retrospective study, 165 consecutive patients with hemispheric strokes who underwent recanalizing therapy were included (median age: 73 years; interquartile range (IQR) 60–80; women: 43 (26%)). The cohort comprised 91 patients treated with intravenous thrombolysis (IV-lysis) alone (median National Institute of Health Stroke Scale (NIHSS) score: 5; IQR 3–7) and 74 patients treated with mechanical thrombectomy (median NIHSS: 15; IQR 9–18). Regression analysis was performed to assess the relationship between pretreatment CTP-derived ischemic penumbra and core stroke volumes and the dCA VLF phase, as well as CBFV assessed within the first 72 h post-stroke event. Results: Pretreatment penumbra volume was a significant predictor of the VLF phase (adjusted r2 = 0.040; β = −0.001, 95% confidence interval (CI): −0.0018 to −0.0002, p = 0.02). Core infarct volume was a stronger predictor of CBFV (adjusted r2 = 0.082; β = 0.205, 95% CI: 0.0968–0.3198; p = 0.0003) compared to penumbra volume (p = 0.01). Additionally, in the low-frequency range (0.07–0.20 Hz), CBFV and BP were inversely related to the gain, an index of vascular tone. Conclusion: CTP metrics appear to correlate with the outcome-relevant VLF phase and reactive hyperemic CBFV, which interact with BP to influence vascular tone and gain. These aspects of dCA could potentially guide BP management in patients with acute stroke undergoing recanalization therapy. However, further validation is required. [ABSTRACT FROM AUTHOR]

Soil-Structure Interaction (SSI) represents an interdisciplinary issue characterized by complex material and geometrical nonlinearities affecting mutually the supporting soil and the superstructure of the system during a seismic event that can compromise serviceability. In this study the following objectives are developed: i) to evaluate the effects of the inelastic supporting soil behavior on the interaction of soil-structure systems; ii) to investigate the changes in the dynamic behavior of archetype low and mid-rise moment resisting building frames when inelastic soil deformation develops. To reach these goals, numerical models of linear-elastic and nonlinear-inelastic underlain soil of buildings on shallow foundations are subjected to earthquake time histories with different frequency content. By employing the finite difference software FLAC2D, the direct method which is capable to tackle SSI issues is used to accounting for soil nonlinearities. A succession of parametric analyses is performed. The slenderness of the superstructure as well as the frequency content of input excitations are important parameters. Nonlinear analyses show a significant increase in deformability and damping of the soil-structure system, implying a consequent reduction of the seismic forces on the structure. As a result, the base shear values dropped by approximately 57.56%, 44.46%, and 69% in the 3, 6, and 9-story frames, respectively. [ABSTRACT FROM AUTHOR]

This study introduces Gaussian Binary Particle Swarm Optimization (G-BPSO), designed to address binary optimization challenges effectively. G-BPSO employs new transfer functions of the Gaussian type derived from the power functions to enable mapping of real-valued vectors of individual encodings into binary form. This ensures smooth change between steps and improved convergence. To assess the effectiveness of G-BPSO, a host of complex optimization problems such as the un-capacitated facility location problem are investigated. Enhanced efficiency and improvement over existing methods in binary optimization is observed. The MATLAB code of G-BPSO is made open-access through https://github.com/kanak02/GBPSO. [ABSTRACT FROM AUTHOR]

CERN, the European Organisation for Nuclear Research is studying the feasibility of the Future Circular Collider, considering both financial and technical aspects. One of the challenges is that the performance of particle accelerators relies on the dynamic stability of structures, affected by multiple sources of vibrations, including crosstalk vibration between two particle accelerators, the Booster and Collider, in the Future Circular Lepton Collider. This research aims to find a methodology for determining transfer functions, specifically crosstalk transfer functions, between the Collider and Booster within an underground tunnel. Also, it aims to determine how significant crosstalk is compared to the vibration from other sources, such as ground vibrations. The transfer functions of the tunnel were independently determined from internal structures using the Finite Element Method, employing 2D plane strain and the standard absorbing boundary to model the underground tunnel. It was found that the overall gain of crosstalk was less than 10% of that of ground-to-magnetic axis of either the Collider or Booster. This method may be used to optimize the tunnel layout from a vibration point of view. It appears that vibrations from crosstalk are far lower compared to vibrations from ground vibrations.

Efforts to optimize the design and enhance the efficiency of standing-wave thermoacoustic refrigerators (SWTARs), particularly those with parallel plate stacks, are crucial for achieving rapid and straightforward engineering estimates. This study primarily focused on optimizing the coefficient of performance (COP) by combining linear thermoacoustic theory (LTT) with the design of experiments (DOE) approach. The investigation centered around five key parameters affecting the COP once the working gas had been selected. Then, based on LTT, the COP was estimated numerically over defined intervals of those five parameters. Moreover, through quantitative and qualitative effect analyses, these five parameters and their interactions were determined. Utilizing a transfer function, the study aimed to delineate the best COP value (1.76) over a defined interval of the parameters as well as the contribution of the thermoacoustic main parameters (55.69%) and their interactions (two-way interactions = 33.30%, three-way interactions = 7.36%, and four-way interactions = 3.35%). Furthermore, a comparison between contour and surface responses and several statistical decision approaches applying the full factorial design verified the robustness of the study's findings. Ultimately, the COP results obtained aligned with the existing literature, underscoring the validity and relevance of the study's methodologies and conclusions. [ABSTRACT FROM AUTHOR]

Mathematical tools have been developed that are analogous to the tool that allows one to reduce the description of linear systems in terms of convolution operations to a description in terms of amplitude-frequency characteristics. These tools are intended for use in cases where the system under consideration is described by partial digital convolutions. The basis of the proposed approach is the Fourier–Galois transform using orthogonal bases in corresponding fields. As applied to partial convolutions, the Fourier–Galois transform is decomposed into a set of such transforms, each of which corresponds to operations in a certain Galois field. It is shown that for adequate application of the Fourier–Galois transform to systems described by partial convolutions, it is necessary to ensure the same number of cycles in each of the transforms from the set specified above. To solve this problem, the method of algebraic extensions was used, a special case of which is the transition from real numbers to complex numbers. In this case, the number of cycles varies from p to p n / k , where p is a prime number, n and k are integers, and an arbitrary number divisor of p n can be chosen as k . This allows us to produce partial Fourier–Galois transforms corresponding to different Galois fields, for the same number of cycles. A specific example is presented demonstrating the constructiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Distributed Acoustic Sensing (DAS) is a photonics technology converting seafloor telecommunications and optical fiber cables into dense arrays of strain sensors, allowing to monitor various oceanic physical processes. Yet, several applications are hindered by the limited knowledge of the transfer function between geophysical variables and DAS measurements. This study investigates the quantitative relationship between surface gravity DAS‐recorded wave‐generated strain signals along the seafloor and the pressure at a colocated sensor. A remarkable linear correlation is found over various sea conditions allowing us to reliably determine significant wave heights from DAS data. Utilizing linear wave potential theory, we derive an analytical transfer function linking cable deformation and wave kinematic parameters. This transfer function provides a first quantification of the effects related to surface gravity waves and fiber responses. Our results validate DAS's potential for real‐time reconstruction of the surface gravity wave spectrum over extended coastal areas. It also enables the estimation of waves hydraulic parameters at depth without the need from offshore deployments. Plain Language Summary: Distributed Acoustic Sensing (DAS) technology converts submarine communication cables into real‐time networks of thousands of seismo‐acoustic sensors. The high sensitivity of DAS measurements (nano‐deformation) makes the recorded signals extremely rich in information, and capable of capturing multiple oceanographic processes. Numerous applications can be envisaged such as monitoring turbidity currents, tsunamis, marine renewable energy parks, etc., and some are already in progress, including monitoring surface vessels, marine currents, cetaceans, etc. However, despite all these developments, the relationship between DAS measurements and certain key ocean variables remains poorly understood. In the littoral zone, this study aims to investigate the link between the deformation signals recorded by DAS due to wave passage at the sea surface and the pressure measured by a sensor located nearby, at the bottom. Our findings demonstrate a strong correlation under varying sea conditions. This correlation allows to reliably determine significant wave heights using DAS data. By applying a simplified theory of wave propagation, the linear wave theory, it was possible to develop an analytical transfer function that relates cable deformation to wave movement parameters. The results confirm that DAS has the potential to reconstruct parameters associated with ocean waves, and could ultimately facilitate their real‐time estimation. Key Points: A simple transfer function between Distributed Acoustic Sensing (DAS) and a collocated pressure sensor is retrieved for surface gravity waves heightsOcean waveheights are correctly reconstructed from nearshore DAS measurementsThe signals recorded by DAS can be described from the standpoint of the linear wave theory [ABSTRACT FROM AUTHOR]

Defining the required trackability level of the target condition for the testing facility reconditioning unit represents an unresolved challenge in improving the reproducibility of load-based tests and corresponding performance rating standards development. To enhance the reproducibility of such testing methodology, this paper presents and discusses a new feed-forward compensation technique based on the development of a transfer function model for the delay and offset characteristics of the psychrometric room's air temperature and humidity modulations with reference to the target signal from the room emulator. It is demonstrated that the proposed methodology enables offset and delay reduction in the trackability of the return air condition within 60 s at different testing conditions, enhances the reproducibility of the test results to limit performance deviations to within 2 %, and achieves closely matched controlled parameter modulations during load-based tests. [ABSTRACT FROM AUTHOR]

The article focuses on the well-posedness of the boundary control system for nonlinear chemical reactions in non-isothermal axial dispersion reactors. Topics include the characterization of the system's approximate controllability, the construction of an extended space to derive explicit classical solutions, and the derivation of a transfer function for the boundary control system to ensure well-posedness.

Understanding responses of stream discharge to precipitation in a watershed is important in gaining insights into watershed hydrology and estimating hydraulic parameters. Transfer functions in the spectral domain are commonly used to quantify the relationship between precipitation and discharge, and estimate watershed hydraulic parameters. However, previous models have not adequately accounted for the impact of the unsaturated zone. To address this, we have developed a novel analytical model that considers the effect of the unsaturated zone to obtain transfer functions within watersheds. These transfer functions are derived by the spectral method and verified through numerical simulations. The results indicate that the transfer functions are influenced significantly by the relative hydraulic conductivity exponent αk in the moisture characteristic curve. A higher αk results in a lower transfer function, indicating more robust filtering of hydrological signals. A thicker unsaturated zone results in lower transfer functions at higher frequencies. The traditional transfer functions, which neglect the retention capacity of the unsaturated zone, tend to overestimate hydrological responses at high frequencies. Our transfer functions agree well with integrated watershed‐scale flow models and are also applied to observed data from four watersheds in Iowa, providing reasonable estimates for the hydraulic parameters. This study contributes to a deeper understanding of watershed behavior and offers an enhanced tool for estimating hydraulic parameters with practical applications. Key Points: Transfer functions are proposed to quantify hydrological signal filtration considering unsaturated flow described by Richards equationThicker unsaturated zones or higher conductivity exponents enhance the filtration of hydrological signalsUnsaturated zone generally possesses a stronger ability to filter watershed hydrological signals than that of saturated zone [ABSTRACT FROM AUTHOR]

Mathematical modeling and numerical simulation have a considerable presence in the vast universe of engineering disciplines, given their usefulness in explaining, comprehending, and simulating phenomena and processes with which engineers are in contact in their daily creative and problem‐solving work. For this reason, engineering study programs have at least one course dedicated to dealing with the mathematical modeling of dynamic systems as an essential complement to subsequent courses such as automatic control, structural dynamics, and mechanical vibrations. Nowadays, many technological tools illustrate the applications of mathematical modeling interactively through experiments that offer an incomparable motivation to the students to corroborate with real‐world examples, the utility and veracity of the theory presented to them in the classroom and that in many occasions seems lacking utility and direct relation with the world in which they develop. Based on those mentioned above, this paper presents an example of applying the Laplace transform in modeling physical systems, using a second‐order circuit attached to an Arduino Due board in conjunction with the Jupyter Notebook environment. The numerical and experimental results can be obtained through three optional kernels: Python, Octave, or MATLAB®. For educational purposes, the resulting computer application was presented to undergraduate students of Mechatronics Engineering as an illustrative complement to two courses entitled Signals and Systems Analysis, part of the second semester, and Mathematical Modeling, part of the fifth semester. [ABSTRACT FROM AUTHOR]

Deepwater subsea wellhead system is subjected to the various cyclic loads transmitted from the drilling riser due to ocean waves, currents and platform motion during drilling operation; therefore, the fatigue damage is accumulated. A fatigue damage assessment methodology and its detailed analysis procedure for subsea wellheads utilising transfer function theory based on monitoring acceleration data at the drilling riser are developed. Studies on an actual monitoring case for a subsea wellhead under drilling operation with 336 h of monitoring events are conducted and a verification method by comparison of the measured fatigue results and predicted fatigue results based on wave and current data are introduced. The results for wave and vortex-induced vibration (VIV) fatigue life based on measured acceleration data are calculated, and the fatigue bias with predicted results are summarised. The developed fatigue damage assessment method and monitoring case studies can be valuable references for deepwater drilling engineering. [ABSTRACT FROM AUTHOR]

Small-signal models of a buck converter working in the discontinuous conduction mode that are available in the literature usually can be divided into those which contain a single pole and refer to non-ideal converters and those that describe ideal converters and contain two poles. Even though the models are noticeably different they have been validated through simulations and measurements, which suggests both of them are correct. The purpose of this paper is to provide a comprehensive comparison of the existing models with transient simulations done in OrCAD software and through measurements, to show that both of the mentioned models are true for a specific set of converter parameters, and to propose a two-pole, control-to-output and input-to-output transfer functions of a non-ideal buck converter, that can be used in any buck converter working in discontinuous conduction mode. [ABSTRACT FROM AUTHOR]

In response to improve the quality and level of hydrostatic transmission (HST) products for modern mobile machineries, the closed-loop transfer functions of a HST are established by mathematical modeling, a comprehensive testing equipment is developed employing a proportional relief valve for automatic program loading and fuzzy-PID oil temperature control, the testing equipment is capable of conducting various performance tests for various models of HST integrated pump-motor products, including factory and type tests, especially continuous impact and endurance performance tests under high temperature and high-speed conditions. Comprehensive performance test of the above test sample is carried out using the developed equipment, that the test results agree well with the previous simulation results verifies the correctness of the established theoretical analysis model. The obtained theory and equipment from this work provide theoretical and experimental technical support for improving design and development of high-end fluid components for modern mobile machinery HST. [ABSTRACT FROM AUTHOR]

During the fault period, a phase angle jump may occur at the stator or the point of common coupling, which will deteriorate the low-voltage ride-through (LVRT) characteristics of a doubly fed induction generator (DFIG). The existing LVRT studies focus on the impact of a voltage drop on DFIGs but often ignore that of a phase angle jump. The time-domain simulation is accurate in describing the response of a DFIG during the LVRT process, but it is time-consuming for a DFIG with the full-order model. In this paper, by using the voltage magnitude and phase angle of the stator or the point of common coupling as the inputs, and the state variables as the outputs, the transfer function of a DFIG is derived to analyze its response and find the LVRT measures against the voltage drop and, especially, the phase angle jump. Firstly, the differential-algebraic equations of the DFIG are linearized to propose their transfer function model. Secondly, considering its high-order characteristic, a model reduction method for the transfer function of the DFIG using the Schur decomposition is proposed, and the analytical expression of the output variables of the DFIG with the phase angle jump is derived by the inverse Laplace transformation to judge the necessity of the LVRT measures. Finally, the simulation results of the DFIG are provided to verify the accuracy of the transfer function model and its reduced-order form and validate the feasibility of the LVRT against the phase angle jump with the proposed models. [ABSTRACT FROM AUTHOR]

This work presents an unprecedented resolution for the lack of harmony between wired network TCP, which transacts with stationary routers, and the Ad-hoc, which appoints mobile hosts as routers, causing failure. This is done by modifying the TCP's queue via fuzzy logic as a controller (FLC). The novelty is that when the mobile router changes location, leading to failure, the controller keeps tracking error signals, which become a behavior prediction base for the next error before occurring. The transfer function is designed with respect to the I/O parameters to optimize the system, leading to the steady with free of fluctuation and overshoot. Other than previous techniques, which depend on fixed criteria or proactive strategies such as AQM, the proposed system is distinguished by dynamic adaptation with continuous changes like mobility and signal power. Using FLC, the system response is improved by reducing time delay, packet loss, and enhancing stability and spectral efficiency. A simulation is designed to continuously monitor these parameters' results, represented by the metrics rise time, undershoot, overshoot, and steady time. For comparison purposes, the PID controller is applied, and the results show surpassing this system where the metrics rise time, undershoot, overshoot, and steady time values are for FLC 0.55, 0.017, 0, and 2.5, respectively, with fluctuation-free, while for PID 0.6, 0.526, 9.341, and 3.6533, respectively, with fluctuation. Furthermore, by dealing the FLC with the challenges of high mobility and the signal power changes, it exceeds the traditional PID controller, as the simulation results show that in terms of reducing the delay time by 28.6%, packet loss by 50%. Besides, there is a remarkable increase in the throughput by 20% and spectral efficiency by 16.7%. [ABSTRACT FROM AUTHOR]

This study aims to develop a control system for a robot arm, designed to perform precise movements along a predefined path, suitable for various industrial applications. The robot arm's movements are driven by three electric motors, each responsible for controlling a joint, enabling the arm to follow the required path accurately. To manage the complexity of multiple motors and dynamic movement requirements, an automated control system has been developed, tailored to meet the specific demands of the proposed task. A highly efficient, reliable, and safe control system design is being developed and simulated to evaluate its effectiveness in executing the required path. A simulation model is being constructed to assess the system's ability to follow the prescribed path, its responsiveness to disturbances and transient conditions, and the overall accuracy of the arm's movements. Simulation results will be analyzed to determine the system's performance across various scenarios, evaluating its adaptability to the work environment and its ability to achieve tasks with high accuracy, thereby enhancing system effectiveness. [ABSTRACT FROM AUTHOR]

The continuous enhancement of optimization algorithms and their parameters has spurred the expansion of AI into novel application domains such as image recognition and smart home technology. This paper employs the system response curve (SRC) to the adaptive learning rate optimizer, addressing challenges associated with the establishment of the optimizer control model and parameter adjustments affecting the dynamic performance of the system. These insights offer theoretical support for the optimizer's application in deep learning models. To begin, the adaptive learning rate optimizer is a time‐varying system. Based on the intrinsic relationship between the network optimization and the control system, the time domain expression and approximate transfer function of the adaptive learning rate optimizer are derived, and the system dynamic model is established. Furthermore, based on the system control model of the optimizer, it is proposed to explain the performance impacts of different optimizers and their hyperparameters on the deep learning model through the SRC. Finally, experiments are performed on the MNIST, CIFAR‐10, UTKinect‐Action3D, and Florence3D‐Action datasets to validate the control theory of explaining optimizers through system response curves. The experimental results show that the recognition performance of the Adaptive Moment Estimate (Adam) is better than that of the Adaptive Gradient (AdaGrad) and Root Mean Square Propagation (RMSprop). Additionally, the learning rate affects the model training speed, and the practical application aligns with the theoretical analysis. [ABSTRACT FROM AUTHOR]

Resonant converters operate by using the natural behavior of certain components to minimize switching losses. These converters have the Soft Switching Characteristics which reduces the stress on the devices and leads to higher efficiency. The family of hybrid resonant converters includes the advantages of series and parallel resonant converters. LCC resonant converter is a type of resonant power converter that leverages a combination of series and parallel resonant elements to achieve soft switching and improved efficiency in high-frequency power supply applications. In this work, LCC resonant converter is simulated in open loop and closed loop with PID controller and fuzzy logic controller. The Converter is studied for operation in different modes and state Space Modeling is done. Transfer Function is obtained for the modeled converter. The converter is also examined for stability with location of poles and zeros in root locus and Bode plot. Entire software analysis is done in MATLAB Simulink. [ABSTRACT FROM AUTHOR]

This proposed work investigates the performance of dc voltage of a three-phase Active Front-End (AFE) Sinusoidal Pulse Width Modulated (SPWM) rectifier during load switching. To obtain desired performances, a transfer function is derived in synchronous reference frame (dq), from which the gain of the PI controllers are estimated and observed the performance accordingly. In this research, the load current is feed-forwarded with d-axis current by a suitable choice of gain factor, which results a fractional feedback d-axis current control and improves the transient behaviour simultaneously. This will unalter the other performance parameters of the system such as, UPF operation, less Total Harmonic Distortion (THD) of input current, dc voltage boost etc. All the simulation results exhibits satisfactory performance and validated with a prototype developed using STM32F303RE microcontroller accordingly. [ABSTRACT FROM AUTHOR]