Dynamic Response Time Research Articles

Control Method for Improving Dynamic Characteristics of a DM-Coupled Inductor Boost Converter Using a 2D Look-Up Table

This paper proposes a control method to improve the dynamic performance of a two-phase DM (Differential Mode)-coupled boost converter designed for applications such as hybrid vehicles and railway systems. A conventional boost converter can be modified to a two-phase interleaved configuration to reduce current ripple and incorporate a differential mode (DM)-coupled inductor to reduce the volume of magnetic components, thereby achieving a decrease in cost and volume. However, when this converter is operated using a conventional PI controller, significant issues arise, particularly in the discontinuous conduction mode (DCM), where dynamic characteristics and response times are considerably slow. For a conventional boost converter, the steady-state duty cycle during DCM operation can be calculated analytically and used for feedforward compensation in a current-duty controller. In contrast, the duty cycle of a two-phase DM-coupled boost converter during DCM operation exhibits non-linear behavior depending on input/output voltages and load conditions, making analytical computation infeasible. To address this, steady-state duty cycle data is extracted through experiments and simulations, and a Look-Up Table is constructed to perform feedforward compensation. Given the multiple input and output specifications, multiple Look-Up Tables are required, leading to excessive MCU (Micro Controller Unit) computation load. The proposed correction algorithm enables feedforward compensation in the DCM region with a single Look-Up Table for all input and output specifications, achieving improvements in dynamic characteristics and reducing MCU computational load. This method achieves a reduction in settling time by up to 77 ms, with a minimum improvement of 10 ms, thereby significantly enhancing the responsiveness of the converter.

Thermally Induced Enhancement of Photoresponse in Radio Frequency‐Sputtered CdS Thin‐Film Photodetectors

This work focuses on understanding the defect‐related electronic transport in cadmium sulfide (CdS) thin films, and finds thermal treatment as an efficient tool to tailor its intrinsic defect charge carrier concentration for optimum visible‐light photodetection performance. The radio frequency (RF)‐sputtered CdS thin‐films show a substantial decrease in measured dark‐current by three orders of magnitude (μA to nA) with an increase in substrate deposition temperature (Ts) from room‐temperature (RT) to a maximum of 400 °C. With increase in Ts, the current conduction behavior changes from Ohmic (at RT) to Schottky‐behavior (Ts ≥ 100–400 °C). The decrease in dark‐current and the crossover from Ohmic to Schottky electronic transport behavior, pointed to a decrease in defect‐density charge carrier concentration, with increased Ts. Additionally, post‐deposition thermal annealing of CdS thin films also is found to result in a similar decrease in dark‐current (μA to nA). The photo‐to‐dark‐current ratio of CdS thin‐film visible‐light photodetectors increased by two‐orders of magnitude, and its dynamic response time decreased by an order of magnitude via. thermal engineering. The thermal‐annealing treatment possibly reduced the defect‐related trap‐sites, which enables a reliable and faster photo‐switching response for CdS thin‐film‐based visible‐light photodetectors.

A Novel Chaotic Particle Swarm Optimized Backpropagation Neural Network PID Controller for Four-Switch Buck–Boost Converters

The emergence of intelligent control strategies has made optimization techniques essential for the precise control of DC converters. This study aims to enhance the performance of the Four-Switch Buck–Boost (FSBB) converter through control system optimization. Backpropagation neural networks (BPNNs) have been widely used for optimizing proportional–integral–derivative (PID) controllers. To further improve the FSBB control system, particle swarm optimization (PSO) is employed to optimize the BPNN, reducing dynamic response time and enhancing robustness. Despite these advantages, the PSO method still suffers from limitations, such as slow convergence and poor stability. To address these challenges, chaotic optimization algorithms are integrated with BPNN. The chaotic particle swarm optimization (CPSO) algorithm enhances the global search capability, enabling a faster system response and minimizing overvoltage. This hybrid CPSO-BPNN approach refines the optimization process, leading to more precise control of the FSBB converter. The simulation results show that the CPSO-BPNN-PID controller reaches a steady state more quickly and exhibits superior performance compared to traditional PID controllers.

Acetone Gas Sensor with SnO2-Modified MoS2 Nanospheres

This study employed a hydrothermal method to prepare molybdenum disulfide (MoS2) and a two-step hydrothermal process to synthesize tin oxide (SnO2)-modified MoS2 nanostructured materials. The manufacturing process is simple and cost-effective, and the produced materials were analyzed using various techniques to confirm their high purity and crystallinity. The SnO2-modified MoS2 nanostructured materials were then utilized to fabricate acetone gas sensors. The high surface area of MoS2, coupled with the heterojunction interfaces formed by SnO2 modification, enhances the performance of the gas sensor. At 150 °C, the sensor exhibits a remarkable response of 37.1% to 100 ppm acetone gas. The dynamic response, including response and recovery times, is also impressive. Gas sensors developed with this material can effectively detect acetone concentrations in various environmental conditions.

El béisbol: un deporte exigente con la función visual

Sports vision is an emerging optometric discipline that seeks to improve visual fusion to obtain better sport performance. The relevant visual skills during sport practice depend on the type of sport played and, in the case of team sports, also on the playing position and task performed. Baseball is a fast-action sport that is very visually demanding. In this work, a literature review and analysis of the studies that investigate important aspects of vision in baseball practice has been carried out. Most of the studies reviewed focus on the analysis of the visual skills of batters, as batting is a highly visually demanding task. The results of the research show that baseball players have better visual skills than the non-athlete population, with dynamic visual acuity, eye movements, eye-hand-body coordination, response time and anticipation being among the most important for a good visual performance of the athletes. Studies show significant differences in certain visual skills depending on athlete-level and/or their playing position.

Adaptive temperature compensation for [formula omitted] humidity sensor in complex environments using ISSA-BP neural network

High-precision humidity detection in complex environments is essential across various fields. In this study, a high-performance MoS2 humidity sensor with a dynamic response time of less than 3 s was developed using molten salt-assisted chemical vapor deposition. To address the challenges posed by dynamic ambient temperature changes on sensor accuracy, an improved sparrow search algorithm-back propagation (ISSA-BP) neural network was constructed to mitigate temperature drift and correct nonlinear errors in the sensor output. The ISSA-BP neural network utilizes a global optimization strategy with adaptive learning, significantly enhancing accuracy and efficiency by optimizing the initialization and iterative update processes of traditional algorithms. Experimental results indicate that the proposed ISSA-BP achieves an average relative error of just 0.75% in humidity sensors across various environmental conditions, representing a 5.8-fold improvement in accuracy compared to traditional methods. Additionally, the algorithm demonstrated high robustness and accuracy across different environments, sensors, and datasets, confirming its applicability in complex and variable scenarios.

Fast detection of humidity sensor with a weakly coupled fiber coated with carbomer

Humidity, as one of the basic environmental physical quantities, is essential in medical monitoring, food production and pharmaceutical industries.Fast and highly sensitive humidity sensing technology has become an urgent need in areas such as medical monitoring. We proposed and realized a novel coupled fiber-optic humidity sensor based on double tapered fiber twisted weakly coupled structure coated with carbomer film. The sensor adopts 2 × 2 coupler structure with waist diameter of 10 μm. The Carbomer film is coated in the weakly coupled area to improve the sensitivity of the sensor, and the thickness of this coating is about 79.2 nm. The sensor provides linear sensing over a relative humidity range of 40%–65% RH, with a dynamic response time of 208 ms and a recovery time of 464 ms. The sensitivity of the sensor is up to −0.28 dB/%RH and the linearity of the sensor is as high as 99.89%. Moreover, the sensor has good stability, reversibility, and low temperature crosstalk. Based on these characteristics, it can be expected that the sensor will bring a great breakthrough in applications where sensitive monitoring of humidity is required.

Modulation and control scheme for DC-link current minimization of an improved current source inverter

The traditional three-phase current source inverter (CSI) cannot maintain a constant DC-link current, the charging and discharging process under different operating modes will lead to the DC-link current being discontinuous or continuously increasing. To address this issue, the topology of CSI is improved, and a modulation scheme without additional losses is proposed in this paper to control the DC-link current. Then, based on the analysis of the DC-link ripple under all switching states, the calculation expression for the optimal reference of the DC-link current is derived, under the premise of meeting the current demand for the AC load, the minimum loss and harmonic distortion can be obtained by reducing the DC-link current. Finally, the math model of the AC-side is established, and the closed-loop control system including the voltage outer loop and the current inner loop is designed. The feasibility and correctness of the proposed modulation strategy and control method are validated by the simulation and experimental results, the minimum and stable DC-link current with the ripple below ± 1 A is obtained, and the high steady-state and dynamic control performances are achieved. The total harmonic distortion of the load current is less than 4 %, and the dynamic response time is 0.3 s.

Seismic vulnerability analysis of hospitals and school buildings considering the Gaussian regression algorithm

This study combines the Gaussian regression algorithm to propose a nonlinear regression model that can be used to evaluate the seismic vulnerability of regional hospitals and school buildings. The failure features and disaster mechanisms of hospital and school buildings affected by the Jishishan (JSS) earthquake on December 18, 2023, and the Wenchuan (WC) earthquake on May 12, 2008, were reported. The samples of 252 damaged buildings (37 hospitals and 215 schools) in Dujiangyan city affected by the Wenchuan earthquake for which the author participated in the survey were collected and counted. Hospitals and school buildings were classified according to the types of reinforced concrete (RC) and masonry structures, and earthquake vulnerability probability matrices for hospital and school building clusters were established considering the actual failure probabilities. A total of 2103,213 acceleration records (from the Wenchuan earthquake) monitored by 12 real stations were selected. Using dynamic time history and response spectrum analysis methods, time history and spectrum curves were generated, considering the influence of different seismic directions. Using the developed Gaussian regression model, vulnerability comparison curves and parameter matrices considering multiple regression algorithms were generated. This paper considers the effects of the construction year and number of floors on the seismic vulnerability of hospital and school buildings. Seismic vulnerability curves and failure probability matrices were generated and established on the basis of actual structural failure probabilities. According to regression and vulnerability surface analysis, the evaluation results of the proposed model are highly consistent with actual field observations.

Thermodynamic analysis and equilibration response time prediction of recuperator in the SCO2 Brayton cycle

The recuperator of supercritical carbon dioxide (SCO2) Brayton cycle significantly affects the system's flexible control due to its thermal inertia. In this study, the structural parameters and operating parameters of recuperator are considered to quantitatively analyze the law of their influence on equilibration response time. Chebyshev spectrum method has been innovatively applied to the one-dimensional dynamic response model of recuperator. The dynamic response time of recuperator under the condition of temperature variation on the hot side is analyzed. The results show that reducing the thermal inertia of solid wall (by increasing the specific surface area of recuperator) can effectively decrease the equilibrium time. Additionally, the rate of inlet temperature variation should not be too large to reduce the thermal inertia of fluid. The zigzag channel demonstrates better dynamic response characteristic than straight channel. A novel dimensionless formula, based on structure and operating parameters, is proposed to quantitatively characterize and predict the equilibrium time for both straight and zigzag channel, the error is within ±20 %. Moreover, a high-precision neural network is trained to predict the equilibrium time directly. The results provide significant theoretical and application support for alleviating the thermal inertia of PCHE and improving the flexibility of SCO2 system.

Investigation of dynamic start-up and thermal airflow characteristics for air-carrying energy heating and cooling system: Sidewall, ceiling, and composite walls

The dynamic start-up process of the air-carrying energy radiant system (ACERS) is crucial for operation control. The dynamic heat transfer process of sidewall, ceiling, and composite walls for air-carrying energy heating and cooling systems was investigated using field experiments and numerical simulation. A new dynamic start-up model was proposed to rapidly predict the dynamic response time and heat transfer surface temperature for controlling indoor temperature. Six schemes with different thermal flow characteristics resulting from temperature difference and velocity uniformity were quantitatively studied through numerical simulation, which helps determine their rationality. The results show that the dynamic start-up model aligns well with experimental data, with an error of less than 3 %. The fast response time of the air medium heat transfer surface for heating/cooling is short (less than 0.5 h). The ceiling provides better adjustability compared to the sidewall. In the unstable state (Gc < 0), the Gc-related buoyancy has a vertical promotion effect, leading to increased convection and decreased vertical temperature difference in the room. Adding the sidewall heating to the ceiling heating reduces the indoor vertical temperature difference by 23 % for the composite walls heating compared to the ceiling heating. Convection accounts for 27 % of the sidewall heating, which is 2.7 times higher than that of ceiling heating (11 %). Combining the dynamic start-up model with numerical analysis enables rapid prediction and analysis of the thermal performance of ACERS, which can be applied to advanced control and optimization for energy-saving applications.

Highly selective and sensitive potentiometric determination of favipiravir in COVID-19 antiviral drug formulations

In this study, a novel all-solid-state electrochemical sensor based on favipiravir-tetraphenylborate (FAV-TPB) electroactive material was developed and reported for FAV’s highly selective and sensitive potentiometric determination in COVID-19 antiviral drug formulations. All-solid-state FAV selective sensor was fabricated by mixing and properly pressing FAV-TPB, graphite (G), multi-walled carbon nanotube (MWCNT), and paraffin oil (PO). In order to obtain the best sensor response, the sensor component ratios were optimized. The most satisfying response characteristics was obtained with the sensor composition FAV-TPB:G:MWCNT:PO in the ratio 32.5:42.5:5:20 (w/w %). The developed sensor displayed a wide linear near-Nernstian response to FAV over the concentration of 1.0 × 10−6 − 1.0 × 10−1 molL−1 with a slope of 53.6 ± 1.4 mV (R2 = 0.9997). The detection limits of the sensor was calculated as 6.0 × 10−7 molL−1, respectively. The dynamic response time of the sensor was 7 s, and the sensor exhibited fairly reproducible potentiometric responses. In the pH range of 6.0–8.0, the sensor’s potential response was not affected by the pH change of the test solutions. The improved sensor had a wide temperature tolerance, and its response remained unchanged in the 10–40 ℃ temperature range. The interference effect of some chemical and biological species was evaluated by the matched potential method and separate solution method. The sensor worked stable for 12 weeks without any considerable change in its potential response. The analytical applications of the sensor were successfully carried out with the potentiometric titration of FAV with sodium tetraphenylborate solution and also the direct determination of favipiravir in COVID-19 antiviral drug formulations.

Optimized coordinated control method with virtual inertia based on fractional impedance model for charging stations

Due to the EV (Electric Vehicles) charging stations are characterized by weak damping and low inertia, the EV with a high degree of uncertainty can easily have an impact on the stability of the charging station system. Therefore, this paper proposes an optimization control method to improve the system inertia effect based on the fractional order impedance model of the charging station. This paper presents a study on establishing a fractional impedance model for charging stations, using the deviation between theoretical impedance spectra and actual measurements as a criterion. The goal is to enhance system inertia and optimize the parameters of the fractional-order controller to improve the supporting capacity of the charging station system and enhance its dynamic response. Initially, considering the fractional characteristics of the EV load, a fractional impedance model of the charging station is established. The analysis demonstrates that the fractional-order capacitor provides inertia to the system, enhancing its inertia support capability. In addition, a virtual inertia control strategy based on fractional-order PID (FOPID) is designed. Finally, an improved particle swarm optimization algorithm is utilized to optimize the control parameters. Through experimental verification under different operating conditions, it has been demonstrated that the fractional-order control strategy can achieve a dynamic response time of approximately 0.025s and limit the voltage deviation within 5%. Furthermore, the rotational inertia can rapidly increase to the maximum value satisfying the objective function within 0.05s. The results indicate that this control method effectively suppresses the DC voltage and power oscillations in the distribution grid.

Fast excitation structure for improving the transient time of magnetic controlled reactors

With the increasing proportion of renewable energy usage, the randomness and volatility of renewable energy have led to a corresponding increase in the demand for reactive power regulation in the power system. Magnetic controlled reactor (MCR) is one of the technical and economic means used to solve problems such as reactive power compensation and voltage regulation in the power system. However, the transient time of traditional MCR is relatively long compared to other reactive power compensation devices, which limits the further application of MCR. At present, most methods for optimizing the dynamic response time of MCR are to add additional circuits or change control strategies, which will increase the difficulty of MCR control and reduce stability. Therefore, without adding additional circuit structure and control difficulty, this paper proposes a three-phase MCR fast excitation structure that changes the winding connection method, which can improve the DC voltage in the control circuit and reduce the transient time of the MCR. A magnetic circuit model in the MCR core under the fast excitation structure is built and analyzed, based on which, the transient time of the MCR is mathematically calculated. A fast excitation MCR simulation model was constructed based on MATLAB/Simulink platform for dynamic response test simulation. Compared with typical MCR simulation results, the transient time was reduced from 400 ms to 37.1 ms. Dynamic response tests were conducted on a three-phase MCR prototype of 35 kV/18 Mvar, and drop test indicates that the fast excitation structure could reduce the transient time of the three-phase MCR prototype to 36.6 ms, which substantiate the precision of mathematical and simulation results and the efficacy of the fast excitation structure.

Multi-spring model for tubular rocking steel bridge piers subjected to earthquake loading

Recent decades have seen increased interest in using the controlled rocking concept in seismic resisting systems. Unlike conventional systems, where lateral deformation of a member is achieved through the formation of plastic hinges in critical regions, in the rocking systems this is achieved through a gap opening mechanism. Due to gravity load and/or post-tensioning forces, the rocking systems exhibit a self-centering behavior. Conducting a continuum finite element analysis to investigate the seismic response of such a system is quite expensive in terms of computational resources. On the other hand, a simplified macro model using two springs to simulate the gap opening/closing mechanism cannot accurately predict the dynamic response of the system. This study utilizes a multiple-spring model to simulate the nonlinear seismic response of circular tubular steel piers. An efficient optimization procedure based on a genetic algorithm is developed to calibrate the parameters of the springs. The results of continuum finite element analyses are compared with those obtained from the multi-spring model to verify the accuracy of the model. The proposed method is shown to be advantageous for accurately simulating the seismic response of a bridge model subjected to multi-directional ground motions, particularly the hysteretic force-displacement relationship, and dynamic response time history.

Regulatory properties of transcription factors with diverse mechanistic function.

Transcription factors (TFs) regulate the process of transcription through the modulation of different kinetic steps. Although models can often describe the observed transcriptional output of a measured gene, predicting a TFs role on a given promoter requires an understanding of how the TF alters each step of the transcription process. In this work, we use a simple model of transcription to assess the role of promoter identity, and the degree to which TFs alter binding of RNAP (stabilization) and initiation of transcription (acceleration) on three primary characteristics: the range of steady-state regulation, cell-to-cell variability in expression, and the dynamic response time of a regulated gene. We find that steady state regulation and the response time of a gene behave uniquely for TFs that regulate incoherently, i.e that speed up one step but slow the other. We also find that incoherent TFs have dynamic implications, with one type of incoherent mode configuring the promoter to respond more slowly at intermediate TF concentrations. We also demonstrate that the noise of gene expression for these TFs is sensitive to promoter strength, with a distinct non-monotonic profile that is apparent under stronger promoters. Taken together, our work uncovers the coupling between promoters and TF regulatory modes with implications for understanding natural promoters and engineering synthetic gene circuits with desired expression properties.

Tunnel indirect damage identification algorithm based on service train dynamic response time series

In this study, a tunnel indirect damage identification algorithm based on a service train dynamic response time series was proposed. First, the principles and processes of the proposed algorithm are introduced. The instantaneous frequency and spectral entropy of the trend and seasonal terms of the train dynamic response decomposed by Seasonal and Trend decomposition using Loess are calculated, respectively, to further extract the time-frequency features of the signal. The calculated sequence is input into the Bi-directional Long Short-Term Memory network, and the type of damage case is the output. Second, the feasibility of the algorithm is verified using a model test. Finally, the key links in the algorithm are discussed. The results indicate that the proposed algorithm can identify damage cases with a small number of training and test sets, and the accuracy of the test set can reach 83.33%. Through time-frequency feature extraction and normalization processing, the length of the network input sequence is reduced, the training speed is increased, and damage identification can be realized without a deep network.

Enhancing the Sustainability of Eco-Friendly Potentiometric Ion-Selective Electrodes for Stability-Indicating Measurement of Ethamsylate: Application in Bulk and Pharmaceutical Formulations.

Through the use of sustainable and green chemistry concepts, scientists need to decrease waste, conserve energy, and develop safe substitutes for hazardous compounds, all for protecting and benefiting society and the environment. Four novel eco-friendly ion selective electrodes (ISE) were generated to determine Ethamsylate (ETM) in bulk powder and different pharmaceutical formulations. The present electrodes were fabricated to clearly distinguish ETM from a variety of inorganic, organic ions, sugars, some common drug excipients and the degradation product, hydroquinone (HQ) of ETM, and thus used for stability-indicating methods. The electrodes fabrication was based on 2-nitrophenyl octyl ether (NPOE) that was employed as a plasticizer in electrodes 1, 2, and 3 within a polymeric matrix of polyvinyl chloride (PVC) except for electrode 4, in which dibutyl sebacate was used as a plasticizer. Electrodes 1 and 2 were fabricated usingtetradodecylammonium bromide as an anionic exchanger, adding 4-sulfocalix-8-arene as an ionophore only to electrode 2 and preparing electrode 1 without incorporation of an ionophore. The fabrication of electrodes 3 and 4 was based on ethamsylate-tetraphenylborate (ETM-TPB) as an ion-association complex in a PVC matrix. The environmental sustainability was assessed using the green analytical procedure index (GAPI), and analytical greenness metric for sample preparation (AGREEprep). Electrodes 1 and 2 had linear dynamic ranges of 10-1-10-5 mol/L and 10-1-10-4 mol/L, respectively, with a Nernstian slope of 49.6 and 53.2 mV/decade, respectively. Electrodes 3 and 4 had linear dynamic ranges of 10-1-10-4 mol/L, with a Nernstian slope of 43.9 and 40.2 mV/decade, respectively. The electrodes' selectivity coefficients showed good selectivity for ETM. The utility of 4-sulfocalix-8-arene as an ionophore had a significant influence on increasing the membrane sensitivity and selectivity of electrode 2 compared to other electrodes. Four novel eco-friendly ISEs were used for determination of ETM in bulk powder and different pharmaceutical formulations. Different experimental parameters were performed to optimize the determination conditions such as solvent mediators, dynamic response time, effect of pH, and temperature. Stability-indicating measurement of ETM in the presence of its degradate HQ and co-formulated drug tranexamic acid. Using new ecological assessment tools to determine whiteness and greenness profiles.

A simplified control parameter optimisation method of the hybrid modular multilevel converter in the medium‐voltage DC distribution network for improved stability under a weak AC system

AbstractTo improve the stability of the hybrid modular multilevel converter (MMC), a simplified dominant mode‐based control parameter optimisation method of the hybrid MMC system is proposed. Firstly, in the medium‐voltage DC distribution network, the small‐signal model of the hybrid MMC is established. Secondly, the influence of a weak AC system on stability is analysed through eigenvalue analysis. Finally, a simplified objective function is designed for eigenvalues of the dominant mode by considering only real parts, and improved small‐signal stability can be achieved by control parameters optimisation. The proposed method optimises all control parameters at the same time, which further reduces the number of algorithm iterations. Simulation results show that by the proposed control parameter optimisation method, the hybrid MMC has better transient performance and reduced disturbance under SCR variation, indicating a significantly improved system stability, and the dynamic response time can be reduced.

Theoretical and experimental investigation of on‐chip silicon‐on‐insulator waveguide methane sensor

AbstractCompared to discrete gas sensors, on‐chip waveguide gas sensors show a wide range of application scenarios due to their small size, light weight, and low power consumption. An on‐chip silicon‐on‐insulator waveguide methane (CH4) sensor was proposed. The optimal waveguide length was determined to be 2.2 cm through theoretical analysis. By targeting an absorption line located at 3291 nm, on‐chip methane measurements were conducted using the established waveguide sensor system. The 1σ limit of detection of the waveguide sensor was measured to be 662 parts‐per‐million and the dynamic response time was 1.6 s. This work verifies the feasibility of the waveguide gas sensor and provides technical support for future research work on fully integrated waveguide sensors.