Search Results (4)

Concrete-filled steel tubular (CFST) composite columns can overcome the brittleness of concrete and improve the plastic deformation ability of concrete, thus improving its strength and deformation ability. At present, most of the published models for predicting the axial bearing capacity of CFST columns are empirical models based on the nonlinear fitting of experimental data, which has some limitations on the application of the models. Therefore, to establish a new unified theoretical model, a new ultimate compressive strength of core concrete was established by the Hoek–Brown failure criterion, and the conversion formula between the cube and cylinder compressive strength was also established in this paper. At the same time, the strength-reduction coefficient influenced by the slenderness ratio was also established. The newly established unified model can predict the axial bearing capacity of CFST columns with different steel types, concrete types, slenderness ratios, diameter-to-thickness ratios, and cross-sectional dimensions. At the same time, the newly established unified model can be applied to a wider range of test parameters. To determine the parameters in the proposed model and assess the models, a total of 798 test data were collected. Based on the test database, the existing models and the proposed model were evaluated. The results show that the proposed model has very high accuracy in predicting the test results of CFST short and long columns, and the average value (AV) and integral absolute error (IAE) are 1.012 and 0.094, respectively. In addition, the model proposed in this paper also has high accuracy in predicting the axial bearing capacity of CFST columns under high temperatures. Full article

The need for energy is always increasing as civilization evolves. Renewable energy sources are crucial for meeting energy demands as conventional fuel resources are slowly running out. Researchers are working to extract the most amount of power possible from renewable resources. Numerous resources are in demand, including solar, wind, biomass, tidal, and geothermal resources. Solar energy outperformed all the aforementioned resources in terms of efficiency, cleanliness, and pollution freeness. Intermittency, however, is the resource’s main shortcoming. Maximum power point tracking algorithm (MPPT) integration is required for the system to achieve continuous optimum power by overcoming the feature of intermittency. However, generating electrical energy from solar energy has presented a significant problem in ensuring the output power’s quality within a reasonable range. Total harmonic distortion (THD), a phenomenon, may have an impact on the power quality. Depending on the properties of the load, variables like power factor, voltage sag/swell, frequency, and unbalancing may occur. The quality of power and its criterion exhibits a non-linear connection. The article’s primary objective is to analyze the PV interface grid-linked system’s qualitative and quantitative performance. With respect to varying solar irradiation conditions, partial shading conditions, and solar power quality within the acceptable dimension, a novel intelligent multiple-objective horse herd optimization (HHO)-based adaptive fractional order PID (HHO-AFOPID) controller is used to achieve this goal. Adaptive fractional order PID (AFOPID), conventional FOPID, and PID controllers were used to evaluate the performance of the suggested controller, which was then validated using a commercially available PV panel in MATLAB/Simulink by varying the productivity of non-conventional resources, the inverter’s level of uncertainty, and the potential at the grid’s end. In order to realize the features of the system, sensitivity examination is also carried out for solar energy’s sensitive parameters. The stability analysis of the proposed control topology is also carried out in terms of the integral absolute error (IAE) and integral time absolute error (ITAE). The examination of the sensitivity of variations in solar radiation in kilowatt per square meter per day is based on the total net present cost (TNPC) and levelized cost of energy (LCOE), as optimal dimension and energy cost are both aspects of priority. The suggested control methodology is an approach for the qualitative and quantitative performance analysis of a PV interface grid-oriented system. Full article

This paper aims to present efficient efforts to optimize the proportional-integral-differential (PID) controller of clinker cooling in grate coolers, which have a fixed grate and at least two moving ones. The process model contains three transfer functions between the speed of the moving grate and the pressures of the static and moving grates. The developed software achieves the identification of the model parameters using industrial data and by implementing non-linear regression methods. The design of the PID controller follows a loop-shaping technique, imposing as a constraint the maximum sensitivity, M_s, of the open-loop transfer function and providing a set of PIDs that satisfy a range of M_s. A simulator determines the optimal PID sets among those calculated at the design step using the integral of absolute error (IAE) as a performance criterion. The combination of a robustness constraint with a performance criterion, M_s and IAE respectively, leads to an area of controllers with M_s belonging to the range of 1.2 to 1.35. The IAE is between 4.2% and 4.8%, depending on the set-point value. PID sets located near the middle of this area can be chosen and implemented in the cooler’s routine operation. Full article

Currently, fuzzy proportional integral derivative (PID) controller schemes, which include simplified fuzzy reasoning decision methodologies and PID parameters, are broadly and efficaciously practiced in various fields from industrial applications, military service, to rescue operations, civilian information and also horticultural observation and agricultural surveillance. A fusion particle swarm optimization (PSO)–evolutionary programming (EP) algorithm, which is an improved version of the stochastic optimization strategy PSO, was presented for designing and optimizing controller gains in this study. The mathematical calculations of this study include the reproduction of EP with PSO. By minimizing the integral of the absolute error (IAE) criterion that is used for estimating the system response as a fitness function, the obtained integrated design of the fusion PSO–EP algorithm generated and updated the new elite parameters for proposed controller schemes. This progression was used for the complicated non-linear systems of the attitude-control pilot models of a tricopter unmanned aerial vehicle (UAV) to demonstrate an improvement on the performance in terms of rapid response, precision, reliability, and stability. Full article