System Stabilizer Research Articles

Effect of sintering temperature on color stability and translucency of various zirconia systems after immersion in coffee solution.

Achieving the aesthetic standards in tooth-colored restorative materials requires close attention to their color, translucency, and resistance to discoloration. This study aimed to evaluate the effect of sintering temperature on color stability and translucency in zirconia systems with low, high, and ultra-high translucencies. This experimental study was conducted on 60 zirconia disks with low, high and ultra-high translucencies (n = 20 per group), each group divided into subgroups to be sintered at either 1450°C or 1550°C (n = 10 per subgroup). Baseline color and translucency parameters were measured, the specimens were then immersed in coffee solution for 30 days, and the measurements were repeated post-immersion. Changes in color (ΔE) and translucency (ΔTP) were calculated via CIELAB formula and compared by using two-way ANOVA and Tukey's post hoc test (α = 0.05). Results of two-way ANOVA showed that the ΔE was significantly different among the three zirconia translucencies (P<0.001), but no significant difference was found between the two sintering temperatures (P = 0.712). Additionally, the interaction between zirconia type and sintering temperature was not statistically significant for ΔE (P = 0.264). The low-translucency group showed significantly greater ΔE than the high-translucency and ultra-high-translucency groups (P<0.05), while the high- and ultra-high-translucency groups were not significantly different in this regard (P>0.05). Regarding the ΔTP, two-way ANOVA showed that the difference was not statistically significant either among the three zirconia types (P = 0.4430) or between the two sintering temperatures (P = 0.4544). Nor was the interaction between zirconia type and sintering temperature statistically significant (P = 0.5505). It was concluded that sintering temperature had no effect on color and translucency changes after immersion in coffee. Whereas zirconia type significantly affected the color changes after immersion in coffee; with the higher-translucency zirconia types being significantly more color-stable than the low-translucency zirconia.

Artificial Optimizer Algorithm for Power System Stabilizer design problem and multidisciplinary engineering applications

The novelty of this research lies in presenting a fresh stochastic algorithm enthused via ‘Velociraptor’ social intelligence in wildlife (or nature), known as the Velociraptor Group Optimization algorithm (VROA). In this strategy, ‘Velociraptor’ co-operative natural life cycle is mathematically framed, and novel mechanisms are presented to perform search (or exploration) and hunting (or exploitation). This suggests that the proposed method reveals a noteworthy ability in both exploitation and exploration. Furthermore, it successfully stabilities exploration and exploitation, supporting the search process. In the direction of evaluating the VROA, we utilized it on 51 CEC'17, CEC'20, and CEC'22 standard benchmark suites and six multidisciplinary engineering optimization functions. Furthermore, well-known statistical methods like Wilcoxon rank-sum test and Friedman's test have been used to verify the strength of the proposed algorithm against various optimizers. The tabulated numerical and statistical solutions show that VROA performs better than recent optimizers on most standard test suites and has efficiently attained the most competent resolution while concurrently upholding adherence to the designated constraints. The results validate that VROA can offer efficient and accurate optimal solutions in evaluation with recent metaheuristics.

PID-based control strategies for enhancing stability and precision in electro-hydraulic actuation systems

Electro-hydraulic actuation systems are essential in industrial applications but often face challenges related to nonlinearity, leading to instability and reduced precision. This paper explores the application of Proportional-Integral-Derivative (PID) control strategies to enhance the stability and precision of these systems. A detailed system model is developed, and the PID controller is designed and tuned using optimization techniques. Simulation results demonstrate improvements in performance metrics, such as reduced overshoot, settling time, and steady-state error. The proposed control strategy is validated experimentally on a physical setup, confirming its effectiveness in real-world applications. The findings show that PID-based control significantly enhances both stability and precision in electro-hydraulic actuation systems, offering a practical solution for industrial control challenges.

Intelligent Control Framework for Improving Energy System Stability Through Deep Learning-Based Modal Optimization Scheme

Ensuring the stability of power systems is essential to promote energy sustainability. The integrated operation of these systems is critical in sustaining modern societies and economies, responding to the increasing demand for electricity and curbing environmental consequences. This study focuses on the optimization of energy system stability through the coordination of power system stabilizers (PSSs) and power oscillation dampers (PODs) in a single-machine infinite bus energy grid configuration that has flexible AC alternating current transmission system (FACTS) devices. Intelligent control strategies using PSS and POD techniques are suggested to increase power system stability and generate supplementary control signals for both the generator excitation system and FACTS device switching control. An intelligent optimal modal control framework equipped with deep learning methods is introduced to control the generator excitation system and thyristor-controlled series capacitor (TCSC). By optimally choosing the weighting matrix Q and implementing close-loop pole shifting, an optimal modal control approach is formulated. To harness its adaptive potential in fine-tuning controller parameters, an auxiliary deep learning-based optimization algorithm with actor–critic architecture is implemented. This comprehensive technique provides a promising path to effectively reduce electromechanical oscillations, thereby enhancing voltage regulation and transient stability in power systems.

Improved General Relativity Search Algorithm (IGRSA) for Designing Power System Stabilizers

This paper proposes a novel optimization algorithm for designing power system stabilizers (PSSs). The prospect of attaining higher stability motivated the authors to creat a new optimization algorithm for this study. A novel algorithm named the Improved General. Relativity Search Algorithm (IGRSA) was also developed by cloud theory to improve the performance of GRSA. The supremacy of the proposed approach is tested by comparing it with an introduced objective function in a medium multi-machine power system. The nonlinear simulation results and eigenvalues analysis has demonstrated that the proposed approach in this study is highly effective in enhancing the dynamic stability of the power system.

Intelligent Control Algorithms for Enhanced Frequency Stability in Single and Interconnected Power Systems

Ensuring stable power system performance is crucial for reliable grid operation. This study assesses various Load Frequency Control (LFC) strategies, including conventional PID, pole placement, Genetic Algorithm (GA)-optimized PID, Particle Swarm Optimization (PSO)-optimized PID, and an Artificial Neural Network (ANN)-based controller, in single and interconnected power grids. The results reveal that GA- and PSO-optimized PID outperform conventional methods, offering minimal overshoot and fast settling times. Pole placement strikes a balance between response time and stability, while the ANN controller demonstrates adaptability and quick rise times but exhibits higher overshoot and longer settling times compared to the optimization techniques. Tie-line bias control aids in frequency stabilization but presents challenges with overshoot and prolonged settling times. Notably, PSO-optimized PID emerges as a promising solution, effectively mitigating overshoot and achieving rapid frequency recovery. This study underscores the importance of tailored control strategies for optimal LFC, which are essential for enhancing power system stability and efficiency. Future research should explore the potential of advanced techniques, such as deep learning and reinforcement learning, to further improve control performance.

Optimal control design for power system stabilizer using a novel crow search algorithm dynamic approach

This paper proposes the first application of a novel improved metaheuristic optimization technique, dynamic crow search algorithm (DCSA) to find the optimal design of the power system stabilizer (PSS). Using the novel DCSA adaptive approach provides a global search capability as well as fastness and effectiveness to get the PSS best parameters under the search space constraints and local optimums. Moreover, PSS parameters has a crucial effect on power system stability that is a major nowadays engineering concern, where its best parameters could make a difference by damping small-signal stability oscillations effectively and in the smallest amount of time if they are obtained through a robust algorithm. As a result, PSS will prevent large types of instabilities which could reach up to some generation stations shedding. The novel proposed algorithm is for first time used and tested under different power system instabilities scenarios by using single-machine infinity bus model over multiple operating conditions to damp out perturbation signals effectively by means of getting optimal PSS design parameters, where Integral absolute error (IAE) performance index is used as an objective function to be minimized. Additionally, results obtained by the proposed approach are compared with those obtained by other methods. It is observed that the proposed method has better convergence characteristics and robustness compared to the original version and other comparison methods. It is revealed that the proposed adaptive method is able to improve the power system stability dynamics and damp out perturbation oscillations successfully.

Νew approach to power system stabilizer optimization techniques

Νew approach to power system stabilizer optimization techniques

Effect of (Zr, Ta) doping on electronic and magnetic properties of zinc-blende MgTe DMS compound: AB-initio approach

This study utilizes density functional theory (DFT) and the Korringa-Kohn-Rostoker coherent potential approximation (KKR-CPA) to explore the effects of zirconium (Zr) and tantalum (Ta) doping on the electronic and magnetic properties of zinc-blende MgTe. The electronic configurations of Mg1-x(TM)xTe (TM = Zr, Ta) were analyzed, revealing that Zr induces magnetic behavior with near-total spin polarization, while Ta doping leads to metallic behavior with partial polarization. The variations in magnetic moments are largely determined by impurity concentrations, with ferromagnetic stability in both systems driven by a double exchange interaction mechanism. Additionally, Curie temperatures exceeding room temperature were observed for specific doping concentrations. These results suggest significant potential for MgTe-based materials in spintronic applications. The findings further illustrate that Zr-doped alloys display half-metallicity, making them especially promising for future spintronics device development. KEY WORDS: DMS, KKR-CPA, Polarization, Metallic behavior, Curie temperature, Double exchange, Spintronic Bull. Chem. Soc. Ethiop. 2025, 39(1), 153-164. DOI: https://dx.doi.org/10.4314/bcse.v39i1.13

Stability and Bifurcations in Time-Delay Systems: A Novel and Efficient Blend of Methods

The goal of this paper is to introduce a hybrid technique, combining two existing methods conveniently, to analyze the stability and bifurcations of equilibrium points and periodic orbits in delay-differential equations of retarded type. One method is called the frequency-domain approach, an analytical tool based on control theory allowing to detect and represent periodic solutions emerging from the Hopf bifurcations, via Fourier series and harmonic balances. The second one, the so-called semi-discretization method, provides a numerical scheme to approximate the monodromy operator of a periodic solution, thus permitting to establish the stability and bifurcations of limit cycles as well as analyzing the equilibrium points. It is shown that a proper combination of these methods provides a straightforward strategy to study both local and global bifurcations in time-delay systems. The usefulness of the proposed approach is shown by three examples, where the results are compared with those given by the software DDE-BIFTOOL.

A new integrated modelling and control of ternary pumped storage hydro power generation for small signal stability studies

Pumped storage hydro power generation (PSHPG), a reliable renewable energy source with an energy storage feature, can impart efficient damping torque to power system oscillations to improve small signal stability with appropriate modelling and additional compensation through the governor. But ternary PSHPG (T-PSHPG) has the unique feature of hydraulic short circuit (HSC) mode, where both pumping and generating modes operate simultaneously. This study presents a novel fourth-order modified Heffron Phillips (MHP) model of T-PSHPG in coordination with a multi-band Power system stabilizer (MB-PSS) employing 2-way penstock, where primary penstock circulates water from the upper reservoir to the lower reservoir through the turbine and secondary penstock divides primary penstock, thereby creating short-circuit path through the pump. Also, this model includes additional reactive power droop control to maintain the voltage profile. A new state space matrix has been developed for coordinating T-PSHPG in HSC mode with MB-PSS. The control parameters of the proposed coordinated model are set by a new multi-objective differential evolution-improved particle swam optimization (DE-IPSO) algorithm. With variable load, random solar and wind source penetrations, it has been found that the proposed model can provide adequate damping actions. The sensitivity of the proposed model has been observed by varying critical model parameters by ±50 %. For all conditions, the settling time of speed variation is within 2.672 s to 5.951 s and the minimum damping ratio lies within 0.105 to 0.455. The minimum damping ratio is 0.32 and the settling time is found to be 3.1 s for system response subject to sudden solar power variation, which has been observed by shifting system eigenvalues toward the left half of the complex plane. Time and frequency domain parameters with sensitivity analysis predict system oscillations being damped effectively with consistency for the proposed modelling and control strategy. The results are verified in real-time with OPAL-RT real-time digital simulator. It has been justified by the present study that appropriate modelling of T-PSHPG along with coordinated control action provided by MB-PSS can handle critical power system oscillations efficiently and effective damping torque can be imparted in HSC mode.

Study on Dynamic Characteristics of Single-Span Rotor Under Cross-Coupling Stiffness Control on Non-drive End

Abstract The sealing-induced cross-coupling stiffness (CCS) often decreases the rotordynamic stability of turbomachinery. In our previous study, an active negative CCS control strategy applied between two bearings in the middle of the rotor was validated to enhance the stability of the rotor system. In this paper, a different approach was taken by applying both positive and negative CCS control strategies to the non-drive end, aiming to investigate their effects on rotordynamic stability using a rotordynamic model. The model represented a single-span centrifugal compressor rotor with CCS at the seal node. The logarithmic decrements and unbalance response of the rotor system were compared under different CCS applications at the non-drive end and in the span. The results demonstrate that applying both positive and negative CCS at the non-drive end can improve system stability, but the positive CCS strategy has limitations, and its applicability is not as extensive as Negative CCS. A “critical stiffness” phenomenon emerges when the rotor system is actively stabilized at the non-drive end, resembling critical resonance. Furthermore, when components like seals introduce cross-coupling stiffness out of the span, they contribute to system stabilization. These findings provide valuable insights into actively enhancing the stability of rotor systems.

Novel hydrogen-bonded organic frameworks-based coating for fat oil and grease deposition control in the sewer system

Hydrogen-bonded organic frameworks (HOFs) represent an emerging class of porous materials characterized by crystalline frame structures, self-assembled from organic molecules through hydrogen bonding. This study demonstrates that HOFs fragment into small particles while preserving their original structure when dispersed in a polymeric epoxy solution. The intermolecular hydrogen bond structural and electronic properties of the LH4-HOF complex as well as the mechanism of HOF incorporated epoxy were extensively studied using density functional theory. LH4-HOF has a high Langmuir surface area of 2758.3 m2/g and nonlocal density functional theory pore size distributions of 3 A°. This unique solution processability enables the fabrication of coatings with high stability in aqueous systems. Results from a 30-day leaching test under controlled conditions (pH 7, temperature 20 ± 2 °C) indicate that LH4-HOF incorporated epoxy-coated concrete samples exhibited an over 85 % reduction in calcium release compared to uncoated samples, with epoxy-coated samples alone showing a 60 % reduction in calcium leaching. Additionally, the LH4-HOF-incorporated epoxy coating reduced the formation of fats, oils and grease deposits by more than 73 % on the concrete samples. Thus, this novel coating approach offers a sustainable solution with significant potential applications in sewer management.

Investigation on luminescence photoswitching stability in diarylethene-perovskite quantum dot hybrids.

Perovskite quantum dots (pQDs) have gathered a lot of attention because of their outstanding optoelectronic properties. Photoswitchable pQDs have the potential for application in single particle optical memories and bio-imaging. Hybrids of photochromic diarylethenes (DAE) and pQDs show a luminescence photoswitching property, however, the cycle stability in such systems is low because of photoinduced electron transfer (PET) from pQDs to DAE. In this study, various hybrids of DAEs and pQDs with different spacer lengths between the pQD donors and DAE acceptors were synthesized and their stability towards multiple cycles of luminescence photoswitching was evaluated. It was found that the electron transfer pathway can be blocked and very stable switchable hybrids can be produced when the distance between the donors and acceptors was long enough. Furthermore, the effect of softness of the basic ligands and the synthesis method of the pQDs on the cycle stability of the hybrids were investigated. The findings of this study suggest that the photoswitching stability can be improved in hybrid systems by proper molecular design of the photochromic molecule.

Incorporating concrete waste as additive in acidic fermentation–A novel approach for enhanced biohydrogen production and concrete mass reduction

Acidic fermentation (AF) of organic waste/wastewater generates valuable byproducts, including hydrogen, volatile fatty acids, and ethanol; however, its sensitivity to pH drops limits the stability and efficiency of the process. A reversal process, the acidic chemical treatment of concrete waste (CW) to recycle its aggregates, generates calcium hydroxide, which can serve as buffering agent. Meanwhile, integrating both processes can introduce a sustainable win-win approach, which is the aim of this study. To assess this approach, a series of batch AF experiments were conducted at 50 °C and pH 5.5, using glucose as the substrate. Cementitious specimen (1.5 × 1.5 × 0.8 cm) was supplemented to each 200 mL-fermenter. Unamended fermenters, with and without additional NaHCO3-buffering, were used as controls to compare with the amended ones. Introducing cementitious specimens to AF increased H2-production by 2-fold and 1.7-fold compared to controls with and without NaHCO3-addition, respectively, after three consecutive feed-cycles. The surface analysis of incorporated specimen confirmed the Ca, Al, Mg, and Si leaching. The AF efficiency and resulting cementitious mass reduction were further assessed at different organic loads and specimens’ volume, surface area, and porosity (by changing water-to-cement [W/C] ratio). Increasing the organic load from 10 to 20 g-glucose/L resulted in lower H2-production, higher specimen mass reduction (up to ∼32%), and higher Ca2+ release (up to 2 g/L); however, no significant effect was observed when using specimens with higher W/C ratio or surface area. Moreover, the presence of cementitious specimens significantly influenced the microbial composition, leading to notable developments in the abundant genera Thermoanaerobacterium and Bacillus. This study presents a novel approach to sustainably enhancing AF process using CW as both an additive and a treatable substance, with reusable aggregates as a byproduct. It provides valuable insights for optimizing the process and guiding future practical applications. This includes considering various concrete compositions, adjusting organic load conditions, and evaluating long-term stability in larger-scale systems.

Preparation and Properties Improvement of Decynediol-Ethoxylate-Modified Trisiloxane Surfactant.

Silicone surfactants are increasingly used in the industrial field due to their advantages such as low surface energy, stable performance, and good biocompatibility. However, many polyether-modified silicone surfactants' foam stability and easy hydrolysis in non-neutral aqueous systems limit their application in many fields. In this article, the decynediol-ethoxylate chain segment was grafted onto heptamethyltrisiloxane to synthesize a modified trisiloxane surfactant (G2). FT-IR and 1H NMR characterized its structure. Its surface activity, aggregation behavior, and wetting and spreading properties in water were studied by using instruments such as a surface tension meter, transmission electron microscope (TEM), dynamic light scattering (DLS), and contact angle tester. G2 can reduce the surface tension of water to 19.24 mN/m at a lower CMC (40.44 mg/L), and the foaming properties and hydrolysis stability of decynediol-ethoxylate-modified trisiloxane (G2) in water are significantly improved compared with allyl-polyoxyethylene-ether-modified trisiloxane (X5).

The Impact of Industrial Robot Applications on Global Value Chains Division Position

This paper surveys the GVC division position across forty-five countries and fourteen manufacturing sub-sectors during the period from 1999 to 2018 to illustrate the impact of applications of industrial robots on the GVC position. The study proves that an increasing level of utilization of industrial robots significantly improves the GVC division position in the manufacturing sector. By automating repetitive and precision tasks, robots enhance efficiency and productivity, therefore allowing deeper specialization in specific stages of the manufacturing process. This technological progress allows for a more connected global production network and hence better integration into GVC. The study also evaluates the spillover effects across value chains and the moderating impact of industrial agglomeration on smart manufacturing.The empirical results show that the application of industrial robots enhances productivity and encourages innovation in related sectors, thereby driving downstream industry growth and promoting industry specialization.Despite the improvement in GVC division positions, robots also contribute to making global value chains more diversified and resilient. Flexible and adaptive manufacturing systems can adapt to disruptions, such as pandemics and geopolitical tensions, ensuring continuity in production and increasing stability and competitiveness in smart manufacturing systems.

Probabilistic coordinated design of multi-band power system stabilizers using the unscented transformation

Probabilistic coordinated design of multi-band power system stabilizers using the unscented transformation

Air Canvas Using MediaPipe for Computer Vision in Unity 3D Hand Tracking

In this paper, we present the implementation of an Air Canvas using MediaPipe for Computer Vision within a 3D environment using the Unity Game Engine. In our previous work, we found that, regardless of the initial parameters, simulations often led to rapid extinctions. In this model, we implemented an Air Canvas and Computer Vision system integrated with Unity’s 3D World. Our goal was to achieve system stabilization, long-term operation, and more realistic simulation by incorporating 3D evolution. Using the Unity Game Engine, we created and managed a closed 3D ecosystem environment, either based on artificial or real-world maps. This simulation of ecosystems and the analysis of the data generated can serve as a starting point for further research, particularly in sustainability. Our system is openly accessible, allowing users to customize and upload their parameters, maps, and objects, and define inheritance and behavioural patterns, enabling them to test their hypotheses based on the data generated. The goal of this article is not to create and validate a model but to provide an IT tool. For evolutionary researchers, the system allows the creation and presentation of simulations, including animated conference presentations for enhanced visualization and engagement. The use of 3D simulation is particularly valuable for educational purposes, engaging students and increasing their interest in 3D interactive worlds. Students can observe how ecosystems behave, how natural selection supports adaptability, and how competition impacts species.

Endogenous Risk Exposure and Systemic Instability

Most research on systemic stability assumes an economy where banks are subject to exogenous shocks. However, in practice, banks choose their exposure to risk. I show that there exists a network risk-taking externality: the risk exposure choices made by connected banks are strategically complementary. Banks within financial networks, especially densely connected ones, become endogenously exposed to excessive risks. The theory offers several novel perspectives on policy debates. For instance, it suggests that limiting government bailouts to interbank exposures can effectively reduce endogenous systemic risk. This paper was accepted by Kay Giesecke, finance. Funding: This work was financially supported by the USC Dornsife Institute for New Economic Thinking Fellowship, the Marshall PhD Fellowship, and European Finance Association Doctoral Tutorial Best Paper Prize. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.01519 .