Operational Control Research Articles

THE MATHEMATICAL MODELS OF ELECTROCHEMICAL GRINDING FOR THE PRECISION PRODUCTION

This article considers the development of a mathematical model of electrochemical grinding for processing precision components operating at varying loads. The combination of processes (for example, the mechanical and electrochemical material removal processes) significantly improves operation control capabilities by increasing the number of control inputs and selected input variables. The results of the research are presented as evaluated based on the capacity of products manufactured using this grinding method. The conducted qualitative and quantitative assessments demonstrate the adequacy of mathematical models. The difference between experimental and calculated values made up 5-10%. The electrochemical grinding helps improve the operability of components operating at varying loads compared to mechanical grinding.

Fuel recycling feedback control via real-time boron powder injection in EAST with full metal wall

Abstract A feedback control of fuel recycling via real-time boron powder injection, addressing the issue of continuously increasing recycling in long-pulse plasma discharges, has been successfully developed and implemented on EAST tokamak. The feedback control system includes four main parts: the impurity powder dropper (IPD), a diagnostic system measuring fuel recycling level represented by Dα emission, a plasma control system (PCS) implementing the Proportional Integral Derivative (PID) algorithm, and a signal converter connecting the IPD and PCS. Based on this control system, both active control and feedback control experiments have recently been performed on EAST with a full metal wall. The experimental results show that the fuel recycling can be gradually reduced to lower level as PCS control voltage increases. In the feedback control experiments, it is also observed that the Dα emission is reduced to the level below the target Dα value by adjusting boron injection flow rate, indicating successful implementation of the fuel recycling feedback control on EAST. This technique provides a new method for fuel recycling control of long pulse and high parameter plasma operations in future fusion devices.

Enhancing Grid-Connected Photovoltaic Systems' Power Quality through a Dynamic Voltage Restorer Equipped with an Innovative Sliding Mode and PR Control System.

This study focuses on enhancing power quality in on-grid photovoltaic (PV) schemes through an innovative dynamic voltage restorer (DVR) that integrates two control strategies with a multi-level inverter. The DVR, a power electronic compensator, corrects voltage disturbances such as sag and swell by adjusting the voltage at the point of common coupling (PCC). It utilizes sliding mode control (SMC) for normal operations and proportional resonance (PR) during voltage disruptions, ensuring accurate voltage correction. The system's multi-level inverter offers a distinct advantage over traditional high-frequency inverters, which typically suffer from significant switching losses in high-power applications. The multi-level inverter effectively detects and mitigates voltage issues while minimizing harmonic distortion. The study evaluates the DVR's performance under various conditions, including voltage swell, disruption, mild sag, and severe sag. Simulation results using the Simulink tool demonstrate that the proposed DVR significantly reduces voltage disturbances and enhances power quality in the PV panel's output, the PCC, and the injected voltage. The findings suggest that this dual-control DVR designe, with its efficient use of a multi-level inverter, is a promising solution for improving power quality and stability in on-grid PV arrangements.

Microwave-aided sensitive and eco-friendly HPTLC method for estimation of mirabegron using NBD-Cl as bio-sensing fluorescent probe by Integration of principal component Analysis, response surface modelling and white analytical chemistry approach

A large number of analytical methods have been used in in-vivo pharmacokinetic investigations and assays of mirabegron, which is used to treat overactive bladder. Because mirabegron does not give fluorescence, there is no known chromatographic method that uses this property in conjunction with environmentally safe solvents. In order to develop and assess analytical procedures that are precise, sensitive, environmentally friendly, economical, and easy to use, white analytical chemistry was recently presented. Hence, a microwave-aided HPTLC method with fluorescence detection was developed and applied for mirabegron quantification; this method is both sensitive and environmentally acceptable, and it makes use of NBD-Cl, a bio-sensing fluorescent-probe. The analytical-QbD approach, which includes chemometric and response-surface modeling concepts, was used to design this targeted chromatographic method. Critical method variables and performance parameters were identified and optimized using principal component analysis and Box-Behnken design. The targeted method was used to estimate mirabegron through the development of method operable design range navigation and control strategy. A mobile phase consisting of ethyl-acetate and ethanol (8.0 + 2.0, v/v) was used to develop the chromatogram of NBD-Cl derivatised-mirabegron into 8.0 mm bands on a TLC-plate that was supported with aluminum and precoated with silica-gel G60 F254. In a mirabegron concentration range of 50–250 ng/band, the suggested method exhibited linearity. Results showed that the suggested method has a recovery rate of 98 % to 102 %. When estimating mirabegron, the %RSD for the precision and robustness study was determined to be less than 2.0. The mirabegron %assay in the commercially available formulations was determined to be between 98 % and 102 % of the labelled claimed value. Mirabegron had a limit of detection of 10 pg/band and a limit of quantification of 50 pg/band. Marketed tablet formulations of mirabegron had a maximum plasma concentration of 71.58 ng/mL in rats. Using metrics from green analytical chemistry and the RGB model scoring system, we compared the whiteness and greenness profiles of the published and suggested methods. The suggested method was found to be sensitive, eco-friendly, quick, cost-effective, and easy to use for estimation of mirabegron.

Experimental assessment of communication delay's impact on connected automated vehicle speed volatility and energy consumption

Communication delays within connected and autonomous vehicles (CAVs) pose significant risks. It is imperative to address these issues to ensure the safe and effective operation of CAVs. However, the exploration of communication delays on CAV operations and their energy use remains sparse in the literature. To fill the research gap, this study leverages the facilities at America Center of Mobility (ACM) Smart City Test Center to implement and evaluate a CAV merging control algorithm through vehicle-in-the-loop testing. This study aims at achieving three main objectives: (1) develop and implement a CAV merging control strategy in the experimental test bed through vehicle-in-the-loop testing, (2) propose analytical models to quantify the impacts of communication delay on the variability of CAV speed and energy consumption based on field experiment data, and (3) create a predictive model for energy usage considering various CAV attributes and dynamics, e.g., speed, acceleration, yaw rate, and communication delays. To our knowledge, this is one of the first attempts at evaluating the impacts of communication delays on CAV merging operational control with field data, making critical advancement in the field. The results suggest that communication delay has a more substantial effect on energy consumption under high-speed volatility compared to low-speed volatility. Among all factors examined, acceleration is the dominant characteristic that influences energy usage. It also revealed that even minor improvements in communication delay can yield tangible improvements in energy efficiency. The results provide guidance on CAV field experiments and the influence of communication delays on CAV operation and energy consumption.

Multi-Objective Evolutionary Framework for Layout and Operational Optimization of a Multi-Body Wave Energy Converter

As global energy demand continues to rise, the focus has increasingly shifted toward renewable energy sources. In this context, multi-body Wave Energy Converters (WECs) stand out due to their superior power capture efficiency and enhanced survivability, facilitated by their operational flexibility. Nevertheless, the complexity associated with deploying multi-body WECs in arrays has constrained extensive research in this domain. This study introduces an optimization strategy for the layout design and control of multi-body WECs aimed at efficiently harnessing wave energy. Utilizing Evolutionary Multi-Objective Optimization (EMO) algorithms, this framework optimizes the arrangement and operational parameters of WEC arrays, specifically tailored for the marine conditions off the coast of Oman. The research encompasses two primary optimization phases: layout optimization, which seeks an optimal balance between power production and the separation distance between WEC devices, and operational control optimization, which adjusts WEC configurations according to varying wave conditions. This approach aims to maximize energy capture and ensure sustainable array performance while addressing technical challenges. Simulation results indicate that the optimized configurations not only enhance energy extraction but also significantly reduce hydrodynamic loads, promising improved longevity and efficiency for multi-body WEC systems in extreme marine environments.

Adaptive iterative learning unified operation control for high-speed train considering electrical structure model and temperature compensation

Adaptive iterative learning unified operation control for high-speed train considering electrical structure model and temperature compensation

Enhancing operation effectiveness by maximizing daily EBITDA as a turnaround strategy execution system to enhance operation performance and profitability

Many companies struggle with strategy implementation due to the complex nature of execution. Some strategy execution systems depend on numerous indicators, making it challenging for managers to oversee effectively. Additionally, during times of financial difficulty, companies require a straightforward turnaround strategy execution system featuring clearly defined Key Performance Indicators (KPIs). This system should empower employees at all levels, fostering a shared sense of alignment and unity as the organization pursues common goals. The researchers aim to provide a simplified system for implementing turnaround strategies that ensures the company's profitability. To achieve this, they recommend utilizing daily Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA) as the primary KPI, as it is entirely under operational control. Moreover, EBITDA can be integrated into business processes and remains solely within the purview of operations leaders and employees, thereby cultivating a sense of ownership and accountability. Once the company reaches a certain level of profitability, it can then incorporate additional KPIs. The researchers developed hypotheses based on deductive reasoning following a comprehensive literature review. They analyzed qualitative data from interviews and quantitative data from surveys. After implementing their program in a ferry company, they observed an approximate 33 % increase in revenue, a staggering 300 % surge in EBITDA, and an expansion of the EBITDA margin by over 250 %. The researchers validated their hypotheses through multiple case studies across ferry, shipbuilding, and aircraft manufacturing companies. This research contributes to the development of a straightforward turnaround strategy execution system by translating strategic programs and EBITDA targets into actionable plans for business processes daily. This approach assists leaders and employees in enhancing company culture and systems to achieve improved performance and profitability. The researchers focus on executing turnaround strategies effectively within company operations.

Regional variation in demographics, reproduction, and body mass growth rates of wild pigs: Implications for population control

AbstractWild pigs are a destructive invasive species throughout many regions of the world and have proven difficult to control or eliminate. Their success as an invasive species is, in part, from their high reproductive potential, which can vary based on available resources, ancestry, and other factors. We opportunistically collected data on demographics (i.e., age and sex), reproduction, and body mass on 2,762 wild pigs throughout various research and operation control activities in Texas, Alabama, Hawai'i, Guam (USA), and Queensland (Australia) during 2016–2024. We evaluated these data for differences among study sites that might lead to a better understanding of wild pig ecology and more effective control of their populations. We found that the age structures of wild pigs varied greatly among sites, with areas with more intense control having younger populations. The timing and frequency of birth pulses also varied by site. Large disparities among populations demonstrated the elasticities of wild pigs in invaded ranges; for example, the Alabama study site had a mostly young population with fast body mass growth rates and 2 discernable birth pulses per year, whereas the Guam study site had an older population with slow body mass growth rates and an indistinguishable birth pulse. We hypothesized that intense population control may increase reproduction rates in younger females through increased body mass growth rates and subsequent reproductive maturity. We recommend that managers identify the seasonal birth pulses of wild pigs in their region, and then intensively focus on removing wild pigs during the 115 days (i.e., gestation period) prior to those birth pulses. This may be counterintuitive to managers that focus on trapping after observing a birth pulse, but it increases the probability of simultaneously removing pregnant females and any associated offspring from previous litters that remained with the pregnant female. We also recommend evaluating regional‐specific intensities of removal that might be required for reducing populations with specific emphasis on whether compensatory reproductive behaviors are generated and how to avoid them.

An Algorithm for Locating the Coordinates of Unauthorized Consumers in the Distribution Electricity Network

This paper explores operational detection and control of unauthorized electricity consumption (UEC) in distribution electricity networks (DENs) with the Automated System for Commercial Metering of Electricity (ASCME) in operation. This problem pertains to the class of problems characterized by significant uncertainty about the current state of the object under study and the parameters of external disturbances, which are represented by unauthorized electricity consumers. In this regard, in order to reduce the level of uncertainty and obtain additional necessary information about the state of the object, the concept of a virtual model of the DEN is introduced. This concept is intended to describe the desired state of DEN, which is characterized by the absence of unauthorized consumers in the network. A new method and an algorithm for solving the formulated problem based on the concept of a virtual model of the DEN are proposed. Conditions for identifying the current state of the DEN are obtained. Vectors of effective values of currents and voltages of the virtual network are determined. A criterion for locating the UEC is formulated and a computational algorithm for the automated control method is developed. The findings allow enhancing the DEN reliability and can be used to create special software for the subsystem for locating the UEC coordinates in the distribution network as part of the ASCME.

Eviews Analysis: Investigating the Relationship Tunneling Incentive, Leverage Ratio, and Hedging in Indonesian Stock Exchange-Listed Firms

Manufacturing companies carry out many operational activities, so the more activities carried out, the more problems will be faced, especially problems related to the company's finances. So that the company experiences less than the maximum profit. For this reason, accurate financial management is needed to record and measure manufacturing company costs and profits so that the financial problems that occur in these manufacturing companies can be prevented or minimized through appropriate financial and operational controls. The method utilized in this study is a causal relationship. From the research results obtained using Eviews12 for manufacturing, Tunneling Incentives, Leverage, and Hedging can increase company value. It can also be concluded that Tunneling Incentive, as measured by Distributed Ownership Structure, has no significant effect on Leverage and Hedging. In contrast, Tunneling Incentive, as measured by Concentrated Ownership Structure, has a positive and significant effect on Leverage and Hedging. The managerial implications of this research are how important tunneling is for companies. The emergence of tunneling is due to agency problems between majority and minority shareholders. By holding tunneling by the controlling shareholder, there will be no dividend payment so that the controlling shareholder benefits the minority shareholder.

Design and Implementation of SCADA Architecture Based on MATLAB App Designer for a Hybrid Power System

Hybrid renewable power systems (HRPS) are now considered reliable solutions for power generation under various conditions. A critical challenge for deploying HRPS involves the design and implementation of an effective supervisory control and data acquisition (SCADA) system, which is essential for real-time monitoring and control. The SCADA system plays a vital role in remote monitoring and control by enabling real-time data management, early fault detection, and timely troubleshooting. This study presents the design and implementation of a SCADA architecture based on a MATLAB App Designer for an HRPS consisting of wind turbines, photovoltaic panels, diesel generators, and batteries. The system utilizes Arduino Mega 2560 as remote terminal units (RTUs) to interface with actuators and measure critical system parameters such as voltage and current. Arduino boards can be controlled directly from MATLAB® via the MATLAB® Support Package for Arduino® Hardware. A laptop is the main terminal unit (MTU), communicating with the Arduino via the Firmata protocol. MATLAB App Designer is the central monitoring interface, providing real-time data acquisition, processing, and visualization. In addition, a relay module is used to control the operation of the diesel generator. The relay module acts as an intermediary between the control system and the diesel generator, allowing for automated control of the generator's operation. It receives commands from the SCADA system to either start or stop the generator based on the energy demands and the availability of renewable resources. By managing the diesel generator's activity, the relay module helps ensure that the HRPS maintains a balanced and efficient power supply, minimizing reliance on non-renewable sources when renewable energy is sufficient. Based on experimental results, the proposed SCADA system effectively monitors and controls HRPS under different conditions.

Simulation study of pharmaceutical supply chains based on system dynamics

Focusing on the multi-stage complex logistics distribution process of distribution centers, this study proposes and establishes a characteristic state model, analysis, and control methods for logistics distribution centers. These are combined with system dynamics simulation methods for logistics systems to conduct an in-depth study on the optimization and control of distribution center operations. Based on actual distribution process data from a pharmaceutical logistics distribution center, the proposed theories and methods are validated against real-world engineering backgrounds.

Optimization method for nozzle control of governing turbine

The compressed air energy storage (CAES) system necessitates rapid and precise adjustment of turbine operational states to align with fluctuating system loads during the energy release process. As the air storage pressure continuously declines, the adoption of an appropriate air distribution method becomes imperative to enhance turbine performance. This study innovatively investigates the coupled optimal method of nozzle control (NC) and relative stator installation angle (RSIA) to achieve maximum specific work under certain output work conditions, initially proposing the optimal method as a strong candidate for engineering applications. The stator channel has undergone redesign to allow adjustment of the stator installation angle. It is investigated to obtain the response surface model of specific work and output work with base pressure (BP), regulated pressure, inlet nozzle number, and RSIA as independent variables, and the maximum specific work as the optimization objective. The results indicate that, compared with the original NC method at rated output work, the optimized operation markedly elevates the specific work by a maximum of 6.1 % and an average of 3.4 %. Furthermore, the majority of losses within the turbine are attributed to entropy production rate by turbulent dissipation, accounting for up to 88.7 % of the total losses. The optimal method satisfies the output work requirement by adjusting the inlet nozzle number and RSIA without throttling the inlet nozzles under different BP conditions. This is achieved by adopting the 3-nozzle inlet method under high BP and the 4-nozzle inlet method under relatively lower BP conditions. The present study offers theoretical support for the optimal design and operation control of NC turbines, which has broad prospective applications in the optimized air distribution regulation of CAES systems.

Improving Solar PV System Performance with DC-DC Converters with MPPT Technique in Real-Time Simulation

A Photo Voltaic (PV) system turns Solar Energy (SE) into electricity that needs efficient converter topology. One significant obstacle associated with solar systems is the fluctuation in energy production from solar PV modules due to meteorological factors like temperature and irradiance. The advancement of Maximum Power Point Tracking (MPPT) algorithms has enhanced the effectiveness of solar panels. Implementing an effective operational control approach may optimize the performance of PV panels, while utilizing proper semiconductor materials can maximize the efficiency of converters. This work introduces a MPPT method based on Perturb and Observe (P&O) algorithm. The PV system performs with optimal efficiency when it is near the IV curve, where it produces the highest amount of electricity due to its non-linear voltage-current characteristics. The power output is determined by the degree of irradiance and the temperature of the cells, resulting in the maximum achievable power output. The conditions vary according on the season, time of day, and environmental factors. Rapid variations in light can occur due to factors like clouds. Thus, it is imperative to precisely monitor the maximum power point (MPP) in all settings to optimize power generation. This study proposes a method to optimize the power output of a PV system by integrating MPPT with a DC-DC energy converter. This approach ensures that the PV generator operates at its maximum power level, irrespective of external factors such as sunshine intensity and temperature. MPPT algorithms exhibit variations in their implementation and performance, with a range of MPPT control algorithms being accessible. The P&O algorithms are widely used due to their ability to regulate the MPP of PV panels. The method is validated in real-time using Typhoon Hill Simulation.

Human Resource Efficiency in Sustainable Railway Transport Operation

This manuscript deals with research in the field of human resource efficiency in the operation of railway transport, which is currently a very actual and important topic. The correct efficiency and organization of the work of employees in railway operations have a significant impact on sustainable railway transport and the sustainable functioning of the transport sector. This research investigated two fundamental principles of railway transport operation control: local control and remote control. Local control involves physically managing transport processes from a traffic office within the station, with a focus on direct supervision. In contrast, remote control, which relies on optical cables, allows for system operation even during malfunctions. The article compares these control methods from technological and economic perspectives. Notably, local control requires a larger number of qualified employees, impacting efficiency. This research reveals that remote control, facilitated by a relay room and traffic office at each station, enhances teamwork, providing an immediate response to situations and enabling dynamic operational adjustments. Moreover, the article assesses the required personnel for optimal staffing, considering factors such as track configuration, departing trains, and reporting district size. Economic indicators, particularly wages, show significant savings with remote control, impacting stations with excluded passenger movement more pronouncedly. The findings highlight the efficiency and economic advantages of remote control in railway transport. The specific contribution of the research to the sustainability of transport and sustainable rail transport is presented in the discussion of the manuscript.

Application of Distributed Collaborative Optimization in Building Multi-Energy Complementary Energy Systems

This article investigates the application and physical mechanism exploration of distributed collaborative optimization algorithms in building multi-energy complementary energy systems, in response to the difficulties in coordinating various subsystems and insufficient dynamic control strategies. On the basis of modeling each subsystem, the Dual Decomposition algorithm is used to decompose the global optimization problem of the system into several independent sub problems, achieving independent optimization of each subsystem. Through an adaptive dynamic scheduling strategy, real-time data and predictive information are continuously updated and controlled, effectively allocating system resources. The experimental results show that compared to the original system before optimization, the improved algorithm in this paper reduces the total energy consumption of the system by 6.9% and 2.8% on typical summer and winter days, respectively. The conclusion shows that the algorithm proposed in this paper can effectively solve the problem of system coordination difficulties, improve system resource allocation and overall operation level, and provide a new perspective for the optimization design and operation control of energy systems.

Dose-Related Effects and Bleeding Risk of Ketorolac in Pediatric Tonsillectomy.

To investigate the safety and effectiveness of dose-related ketorolac administration in children who underwent tonsillectomy. Data sourced from PubMed, SCOPUS, Embase, Web of Science, and Cochrane databases, encompassing literature from their inception until June 2024. The perioperative administration of ketorolac in comparison with a control group was included in this analysis. The outcomes assessed were postoperative pain levels; utilization patterns of analgesic medication in terms of quantity and frequency; and the incidence rates of postoperative nausea, vomiting, and bleeding. Eighteen studies with 11,729 patients that investigated. The ketorolac treatment group with postoperative bleeding had a higher incidence of primary bleeding (significant bleeding and operative bleeding control) compared to the control group. However, ketorolac treatment did not affect the risk of secondary bleeding. Subgroup analysis showed that 0.9 to 1 mg/kg of ketorolac significantly increases primary operative control (odds ratio [OR] = 4.0700 [1.6352; 10.1302]; I2 = 0.0%) and primary significant bleeding (OR = 2.3200 [1.1322; 4.7538]; I2 = 0.0%). On the other hand, 0.5 mg/kg ketorolac did not show any influence on primary operative control. The administration of ketorolac (both 0.9-1 and 0.5 mg/kg) led to a significant decrease in postoperative pain (2-24 hours), nausea, and vomiting compared to the control group. Low-dose (0.5 mg/kg) ketorolac administration to children could significantly reduce the risk of primary significant bleeding and surgical hemostasis compared to high-dose administration (0.9-1.0 mg/kg). In addition, low-dose ketorolac administration could provide sufficient pain control and reduce postoperative nausea and vomiting.

Transforming by-products into renewable energy: Biochemical analysis of anaerobic digestion of biowastes for bioreactors optimization supporting the low-carbon agroindustry

With the expansion in agro-industrial operations there is an urgent need to solve the challenge of dealing with the products waste. Today, an overwhelming portion of this waste ends up in industrial waste disposal sites. Wherefore, anaerobic co-digestion (ACoD) emerges as an effective technique for waste treatment, being environmentally and economically viable, since a microbial community converts by-products into renewable energy in the form of biogas, with high levels of hydrogen and other gases. ACoD has proven effective in the management of organic waste from agro-industry. However, mastering the biochemistry of the process, especially when varying the mixtures of waste used, is essential for controlling biological reactors and optimizing energy production. Even though separate studies have evaluated the anaerobic digestion of rice parboiling effluent and peach processing residue, co-digestion of both are scarcely investigated. The knowledge and mastery of the process parameters using this mixture are essential to ensure effective operational control of anaerobic reactors with maximum energy generation. Therefore, this research evaluated the biogas production from ACoD of rice parboiling effluent and waste of peaches processing. The experiment followed a batch regime based on a 22-factorial arrangement. The factors used were the peach percentage in the substrate (P), which varied from 2.5 to 5%, and the substrate-inoculum ratio (S/I), which was alternated between 1.5 and 2.5 gCOD/gVSS. The average Chemical Oxygen Demand (COD) removal efficiency of the reactors was 82.1% and, after the digestion process, the pH of the reactors remained neutral, showing that anaerobic digestion is a suitable method for treating the assessed wastes. In the analyzed proportions, the higher the peach percentage in the substrate, the lower the total methane production, whereas the S/I demonstrated the opposite effect. Reactors III (S/I = 2.5 and P = 2.5%), presented the most durable and the highest production, being the best combination of the factorial studied. Finally, it can be said that for the state of Rio Grande do Sul, the largest rice and peach producer in Brazil, ACoD of the wastes assessed in this research represents a significantly relevant option, enabling the development of the circular economy, the industrial symbiosis, and the sustainable production in the State.

Human Resource Management in Complex Environments: A Viable Model Based on Systems Thinking

Developing the company’s capacity to deal with changing environments means ceasing to see processes as a traditional and linear model. Therefore, the objective of this research is to apply VSM to HRM to show its complexity. It is qualitative research, which is carried out in two moments. The first consists of a literature review in the WoS, and the second, is the design of the model “MV-HRM”, based on the approach of complex adaptive systems, viable system model, soft system methodology, and holistic theory. The MV-HRM consists of five systems: (S1) HRM processes, (S2) information system (S4) operational control, (S4) strategic planning and (S5) governance. The model emphasizes the relationships and interactions it has with its immediate and future environment. Finally, the contribution of the research is to show another look and understanding of the functioning of HRM, in addition to awakening the interest of strategists to develop best practices that allow them to respond in an agile way to the dynamic and complex environment.