Transient Response Research Articles (Page 5)

Investigation of the transient thermal shock response of an interface crack using the interaction energy integral method

Abstract Modern integrated hydrologic models (IHMs) are powerful tools for investigating coupled hydrologic system dynamics. The tradeoff for this realism is a high computational burden and large numbers of parameters in each cell, few of which can be specified with a high degree of confidence. These factors combined make uncertainty quantification (UQ) a problem for IHM‐based simulations, yet without rigorous UQ, it is not clear how much confidence can be placed on conclusions made with IHMs. Previous work evaluated steady‐state cases where the permeability field was a random variable, and a logical continuation is to consider transient conditions. This work assesses the confidence of an IHM representation of a first‐order basin in central Idaho, USA, using an ensemble of 250 permeability realizations under three different recharge forcing signals. The results show that surface water is simulated with high confidence across all the permeability realizations, but the groundwater system and changes to it have lower confidence. However, uncertainty in changes to the groundwater system decrease with time since an increase in the recharge, meaning that the farther one gets from a “peak” in the flow (of any size) the more confident one can be in the response (i.e., smaller inter‐quartile range). The ensemble was also used to assess how many realizations were needed to capture expected behaviors of the ensemble and their range of variability. Unsurprisingly, groundwater requires larger ensembles than surface flows, but the size of the ensembles necessary for convergence were smaller than initially expected.

Understanding the microscopic mechanism of interaction between ultrafast laser and quartz materials is vital for laser fabrication of quartz optical waveguide device. Recently, the time-dependent density functional theory (TDDFT) based on quantum mechanics becomes an effective theoretical tool to investigate the ultrafast photoexcitation dynamics in quartz. However, the role of electron cooling has not been involved in previous studies. In fact, the electron cooling as a key physical process significantly affects electron–lattice spatiotemporal evolution as well as the transient optical response of quartz. This paper employs the real-time TDDFT method to simulate the femtosecond laser irradiation of α-quartz at room temperature with a consideration of the electron cooling effect. It was found that the electron cooling increased the lattice temperature and atomic displacements within tens of femtoseconds through the electron–lattice energy transfer. Particularly, the bandgap of quartz presented a drastic reduction by up to 38%, which mainly originated from the rapid lattice structure evolution. This paper demonstrates that the electron cooling effect should not be ignored in the calculation of laser–quartz interaction because it stimulates the renormalization of electronic structure and lattice structures of quartz, which has a huge impact on optical and electrical properties of quartz materials.

In this paper, a new indirect multithread attracting manifold adaptive controller for a general class of aerospace mechanical/robotic systems is presented. The controller certifies closed-loop stability for any given bounded reference trajectory while adapting many estimates of unknown parameters such that any one particular estimate almost never moves further away from the unknown truth in a distance measure when compared with its current estimate. While maintaining this “no-regret” learning feature for each individual thread, all threads are mixed into a single composite estimate using a judiciously designed weighting scheme that rewards past performance of each individual thread. This provides faster error elimination and superior transient response performance compared with traditional adaptive control implementations that utilize only a single thread. The need for rapid convergence of poorly determined parameters is particularly relevant to on-orbit servicing applications such as capturing non-cooperative space objects and debris. The beneficial features of the proposed multithread learning scheme are demonstrated via numerical simulations of various prototype problems ranging from robotic manipulators to spacecraft control applications.

Control strategy to improve damping and transient response of VSG-based renewable power plants

Rupture of the anterior cruciate ligament (ACL) is a common injury resulting in joint instability. Tendon autografts, the gold standard to reconstruct a ruptured ACL, contain dead or dying cells upon implantation that can initiate early localized catabolic and inflammatory events. This is hypothesized to contribute to detrimental remodeling, which may compromise graft stability and increase the risk of rupture. To address this, we propose using decellularized grafts. However, the cells used to reseed decellularized tendons cannot be detected anymore invivo, potentially due to the dynamic loading conditions. Therefore, the repopulation efficiency of decellularized tendons under dynamic load was investigated using a custom developed bioreactor. As a proof of concept, human gracilis tendons were decellularized and reseeded with human dermal fibroblasts and cultured for 7 days dynamically (2%-6% strain at 1 Hz for 7 h a day) or statically. Thereafter, the viability and infiltration ability of the reseeded cells were assessed. The loading protocol used in this study demonstrated that the bioreactor could measure the transient response of tendon mechanical behavior and could detect changes in mechanical properties over time. The application of dynamic load to reseeded decellularized tendons had no significant effect on cell adhesion, viability, cell metabolism, and infiltration. In both loading groups, cell infiltration was localized rather than globally observed. As bioreactors can serve as an invitro or exvivo model to potentially predict invivo outcomes, this bioreactor shows promising potential for future ACL graft research.

Port Conducted HEMP Environment of Distribution Transformers Considering Transient Response of Power Lines

In contemporary hybrid power systems, persistent load fluctuations disrupt the delicate balance between electrical output and mechanical torque, thereby compromising frequency stability. Load frequency control (LFC) mechanisms are indispensable in maintaining this equilibrium, particularly in systems integrating renewable and thermal energy sources. This study introduces a three-degree-of-freedom proportional-integral-derivative (3DOF-PID) controller optimized via the novel chess optimization algorithm (COA) and evaluates its efficacy against the ant lion optimizer (ALO) and Harris Hawks optimization (HHO). Extensive MATLAB/Simulink simulations were conducted on a hydrothermal system, with performance assessed through objective functions—integral of absolute error (IAE) and integral of time-weighted absolute error (ITAE). The COA consistently yielded the lowest cumulative error values (IAE=0.1548 and ITAE=0.2965), demonstrating its superiority in steady-state performance. However, COA exhibited substantial dynamic deviations, including an overshoot of 387.79% and undershoot of 4513.8% in ∆ftie. Conversely, HHO offered a significantly enhanced transient response, achieving 0% undershoot in ∆ftie with minimal oscillatory behavior. ALO displayed moderate performance but struggled with higher undershoots and prolonged settling time. The findings underscore the criticality of algorithm selection in controller design. While COA excels in minimizing long-term errors, HHO is preferable for applications requiring heightened dynamic stability and responsiveness.

Transient response of low-temperature ALD-grown ZnO thin film-based p–i–n UV photodetector

Dynamic current reference technique for enhanced transient response in current-feedback low-dropout regulators

The primary objective of the automated voltage regulator (AVR) is to maintain the terminal voltage of the synchronous generator at the specified level with great precision in power production systems. Accurate voltage regulation improves the longevity of equipment intended for operation at the specified voltage within a power system network. This study presents a robust control of an AVR system utilizing proportional integral derivative (PID) control based on sliding mode techniques. The suggested control method is implemented by utilizing the particle swarm optimization (PSO) technique to tune the parameters of the proposed controller in the AVR system. A comparative performance analysis is conducted between the proposed controller, PID controller, and (PSO-fractional order proportional integral derivative (FOPID) controller. The comparison is derived using transient response characteristics and parameter uncertainty. The results reveal that the proposed PSO-PID-sliding mode control (SMC) controller has superior performance, characterized by rapid convergence, reduced overshoot, stability achievements in time domains, and robustness against parameter fluctuations. The proposed controller has markedly enhanced the performance of the AVR system and can be effectively implemented inside it.

Adaptive body biasing technique based digital LDO regulator for transient response improvement

Real-time full-field estimation of transient responses in time-dependent partial differential equations using causal physics-informed neural networks with sparse measurements

Dynamic analysis of unsaturated subgrades with pot cover effect: Saturation-dependent transient response

In this paper, a wireless power transfer (WPT) system composed of a voltage-mode fully integrated resonance regulating rectifier (IR${{}^{3}}$) and an on-chip antenna running at 402 MHz has been designed for bioimplants in deep tissue. The proposed IR${{}^{3}}$, including a 200 pF decoupling capacitor, is implemented in a 0.22 mm${{}^{2}}$ active area in the 180-nm CMOS process. A charging duration based regulation compensation circuit offers a low ripple factor of 0.3% at a 1.8 V output voltage and a high voltage conversion efficiency (VCE) of 1.73 to overcome the low inductive coupling coefficient (under 0.01) due to the deep implant scenario. And a clock gating VCDL-based on-&-off delay compensation scheme is proposed to compensate for the phase error of the IR${{}^{3}}$. Performing rectification and regulation simultaneously in a single stage, the IR${{}^{3}}$ effectively enhances power conversion efficiency. The whole system achieves a power conversion efficiency (PCE) of 65% with a 1.5 mW load. In addition, digital control-based compensation circuits also improve its transient response performance, the 1% setting time is only 6.9 $\mu$s when the load changes from 65 $\mu$W to 1.5 mW.

Abstract Four approximate models are presented and used to predict the transient response of a solid to heating/cooling (adsorption/desorption) driven by stepwise constant, cyclic surface temperature (species concentration) boundary conditions. The one-dimensional solid sphere, one-dimensional solid cylinder, and one-dimensional plane wall are considered, along with a representative three-dimensional triply periodic minimal surface (TPMS) structure, operating in the quasi-steady regime of the transient response. From comparison of the approximate predictions to benchmark numerical solutions, it is shown that a novel, modified dimensionless conduction heat rate (q*) model offers superior performance relative to the other three approximate models which include two variations of the linear driving force (LDF) model that is typically applied to cyclic mass diffusion processes. Building on the recent discovery of a remarkable similarity between the transient conduction responses of three-dimensional TPMS solids and that of the one-dimensional plane wall, application of the modified q* model to a TPMS solid operating in the quasi-steady regime of the cyclic transient response is demonstrated. Utilization of the modified q* model, in lieu of numerically solving the transient, three-dimensional form of the heat conduction (species diffusion) equation applied to TPMS solids undergoing cyclic heating/cooling (adsorption/desorption), can provide reasonably accurate heat (mass) transfer predictions in conjunction with many orders-of-magnitude reductions in computational costs.

This paper investigates the problem of quadcopter altitude stabilization under external disturbances, particularly wind gusts. For the analysis, a mathematical model of a multirotor UAV based on the Newton–Euler equations for a rigid body with six degrees of freedom (6-DOF) was used. The study was carried out in the MATLAB/Simulink environment, which made it possible to simulate the operation of a closed-loop control system under realistic environmental influences. The aim of the work is to compare three approaches to altitude control: the classical PID controller, the fuzzy PD controller (fuzzy-PD), and the optimal Linear Quadratic Regulator (LQR). For each strategy, tuning, simulation, and analysis of transient responses were performed. The effectiveness was evaluated using key indicators: settling time, overshoot, and root mean square error (RMSE) under wind disturbances. The obtained results showed that the fuzzy-PD controller provides the best overall control quality: the fastest transient response, minimal overshoot, and the lowest error under disturbances. The LQR regulator demonstrated high robustness and a balance between speed and accuracy, significantly outperforming the classical PID in all criteria. The PID controller served as a basic benchmark but exhibited the highest sensitivity to wind effects. Thus, the study confirms the feasibility of using adaptive and optimal approaches (fuzzy-PD and LQR) to ensure reliable quadcopter altitude stabilization in a changing environment, which is practically important for aerial photography, monitoring, inspection, and search-and-rescue missions.

The project aims at applying Model Predictive Control (MPC) to increase the power quality of grid-tied inverters connected to photovoltaic (PV) and wind systems. The presence of increased renewable energy on the power grid has led to an increased possibility of occurrence of harmonic distortion, voltage variations and a decline in quick response that may compromise the grid and violate power quality norms such as IEEE 519. Conventional controllers like proportional--integral (PI) and hysteresis control cannot always produce the correct result in a response to system dynamics and various properties of systems. These problems are eliminated in the framework which predicts what will take place in the system and switch the inverter appropriately to minimize a given cost function. With this solution, harmonics rejection and efficient current monitoring as well as rapid adaptation to grid issues and changed demand are realized. Simulation study In MATLAB / Simulink, the comparison of the proposed MPC controller against conventional control methods was achieved through simulation with different irradiance variations and loads being switched on / off. The results state that MPC-based inverter control introduces THD of less than 3%, ensures that the voltage remains in a range of +/- 2 percent of the nominal value and enables quicker transient responses, renovating renewable energy systems more dependable and compliant. Besides, MPC enables safety and control properties that makes it flexible to suit the future needs in smart grids. This method brings a practical solution that highly benefits a power grid to operate normally, provide high power quality and operate effectively with increased renewable energy, promoting the usage of intelligent inverters within the power supply system.

This paper proposes a novel hybrid control strategy integrating a Finite Control Set Model Predictive Controller (FCS-MPC) with a universal droop controller (UDC) for effective load power sharing in inverter-fed microgrids. Traditional droop-based methods, though widely adopted for their simplicity and decentralized nature, suffer from limitations such as steady-state inaccuracies and poor transient response, particularly under mismatched impedance conditions. To overcome these drawbacks, the proposed scheme incorporates detailed modeling of inverter and source dynamics within the predictive controller to enhance accuracy, stability, and response speed. The UDC complements the predictive framework by ensuring coordination among inverters with different impedance characteristics. Simulation results under various load disturbances demonstrate that the proposed approach significantly outperforms conventional PI-based droop control in terms of voltage and frequency regulation, transient stability, and balanced power sharing. The performance is further validated through real-time simulations, affirming the scheme’s potential for practical deployment in dynamic microgrid environments.

This paper presents a modular high-voltage DC-DC converter designed for integrating industrial renewable energy sources (RES) into HVDC transmission systems. Using a modular multilevel converter (MMC) architecture, the design offers scalability, fault tolerance, and efficiency exceeding 98%. The converter achieves high voltage conversion ratios—up to 700 V output from 20–40 V input—by connecting low-voltage submodules in series, reducing component stress and electromagnetic interference. Advanced control strategies, including pulse-width modulation and circulating current suppression, ensure stable power flow. Simulations in MATLAB®/Simulink® validate a sliding mode control (SMC) approach, maintaining output voltage at 170 V despite input variations, with rapid transient response (0.05 s) and minimal voltage deviation (±2%). Under dynamic load changes (50–100%), SMC outperforms conventional PI and LAD controllers, maintaining voltage deviation within ±1.5% and faster recovery (~0.03 s). These results demonstrate the converter’s robustness in regulating voltage and handling disturbances typical of renewable energy inputs and load fluctuations. The system’s modularity enables flexible adaptation to applications such as offshore wind farms and photovoltaic plants, facilitating the efficient and resilient integration of Renewable Energy Sources (RES) into existing High-Voltage Direct Current (HVDC) grids. This work highlights the potential for enhancing power transmission efficiency and stability amid growing renewable penetration.