The discharge of effluents from dye industries into water streams poses a significant environmental and public health risk. In response, eco-friendly adsorbents derived from agricultural waste, such as Fava Bean Peels (R–FBP), have been investigated as potential materials for the removal of such pollutants. In this study, R–FBP and their corresponding physical and chemically activated carbon (P-RFB-AC and C-FBP-AC) were synthesized using H3PO4 acid and characterized using FT-IR, and SEM analyses. An optimization process was conducted to determine the optimum conditions for achieving high Methyl Orange (M. Orange) removal efficiencies using the prepared materials, namely R–FBP, P-RFB-AC, and C-FBP-AC. The adsorption mechanism was examined by analyzing the isotherm and kinetics. The results revealed that the physical raw-activated carbon exhibited the highest removal efficiency of 96.8% compared to other materials. This outcome was achieved through the use of ANN combined with Moth Search Algorithm (MSA), which was found to be the most effective model for achieving the highest M. Orange removal efficiency from Physical raw fava bean activated carbon. Under parameters of 1000 mg/l M. Orange concentration, 2 g/l dose, 15 min contact time, and 120 rpm shaking, the best experimental and predicted removal efficiencies for physical-activated carbon fava bean rind were 96.8 RE%, 96.01 indicated RSM RE%, and 95.75 predicted ANN RE%. The highest experimental and predicted removal efficiencies for the H3PO4 chemical activated carbon fava bean peel were 94%RE. This study aimed to develop an economical solution for treating industrial wastewater contaminated with anionic M. Orange dye using raw fava bean peel and their generated activated carbon, in both physical and chemical forms. The Temkin and Langmuir isotherm models were found to best fit the data for raw fava bean peel, while Temkin agreed well with the data from physical-activated carbon. Temkin and Freundlich’s models were fitted with the H3PO4 chemical activated carbon. Pseudo-second-order kinetics was identified as the most suitable model for both physically and chemically activated carbons. Future research may explore the capacity of the produced activated carbon-based algae to extract a wider range of contaminants from contaminated wastewater. In summary, this work contributes to the development of eco-friendly and cost-effective methods for removing dyes, specifically M. Orange, from industrial effluents. By synthesizing and characterizing R–FBP and their relative activated carbon, the adsorption mechanism was studied, and the optimum conditions for achieving high M. Orange removal efficiencies were determined. The results showed that physical raw-activated carbon exhibited the highest removal efficiency, and pseudo-second-order kinetics was the most suitable model for both physically and chemically activated carbon. © 2023 The Authors
A review of coagulation explaining its definition, mechanism, coagulant types, and optimization models; RSM, and ANN
The textile business is one of the most hazardous industries since it produces several chemicals, such as dyes, which are released into water streams with ef-fluents. For the survival of the planet’s life and the advancement of humanity, water is a crucial resource. One of the anthropogenic activities that pollute and consume water is the textile industry. Thus, the purpose of the current effort is to Apply coagulation as a Physico-chemical and biological treatment strat-egy with different techniques and mechanisms to treat the effluent streams of textile industries. The discharge of these effluents has a negative impact on the environment, marine life, and human health. Therefore, the treatment of these effluents before discharging is an important matter to reduce their adverse ef-fect. Many physico-chemical and biological treatment strategies for contaminants removal from polluted wastewater have been proposed. Coagulation is thought to be one of the most promising physico-chemical strategies for removing con-taminants and colouring pollutants from contaminated water. Coagulation is accompanied by a floculation process to aid precipitation, as well as the collection of the created sludge following the treatment phase. Different commercial, and natural coagulants have been applied as a coagulants in the process of coagulation. Additionally, many factors such as; pH, coagulant dose, pollu-tants concentration are optimized to obtain high coagulants removal capacity. This review will discuss the coagulation process, coagulant types and aids in addition to the factors affecting the coagulation process. Additionally, a brief comparison between the coagulation process, and the other processes; princi-ple, advantages, disadvantages, and their efficiency were discussed throgh the review. Furthermore, it discusses the models and optimization techniques used for the coagulation process including response surface methodology (RSM), ar-tificial neural network (ANN), and several metaheuristic algorithms combined with ANN and RSM for optimization in previous work. The ANN model has more accurate results than RSM. The ANN combined with genetic algorithm gives an accurate predicted optimum solution. © 2023 The Authors
Crystal violet removal using bimetallic Fe0–Cu and its composites with fava bean activated carbon
Nano zero-valent iron (nZVI), bimetallic nano zero-valent iron-copper (Fe0– Cu), and fava bean activated carbon-supported bimetallic nano zero-valent iron-copper (AC-Fe0-Cu) are synthesized and characterized using DLS, zeta potential, FT-IR, XRD, and SEM. The maximum removal capacity is demonstrated by bimetallic Fe0–Cu, which is estimated at 413.98 mg/g capacity at pH 7, 180 min of contact duration, 120 rpm shaking speed, ambient temperature, 100 ppm of C.V. dye solution, and 1 g/l dosage. The elimination capability of the H2SO4 chemical AC-Fe0-Cu adsorbent is 415.32 mg/g under the same conditions but with a 150 ppm C.V. dye solution. The H3PO4 chemical AC-Fe0-Cu adsorbent achieves a removal capacity of 413.98 mg/g under the same conditions with a 350 ppm C.V. dye solution and a 1.5 g/l dosage. Optimal conditions for maximum removal efficiency are determined by varying pH (3–9), time intervals (15–180 min), and initial dye concentrations (25–1000 ppm). Kinetic and isothermal models are used to fit the results of time and concentration experiments. The intra-particle model yields the best fit for bimetallic Fe0–Cu, H2SO4 chemical AC- Fe0–Cu, and H3PO4 chemical AC-Fe0-Cu, with corrected R-Squared values of 0.9656, 0.9926, and 0.964, respectively. The isothermal results emphasize the significance of physisorption and chemisorption in concentration outcomes. Response surface methodology (RSM) and artificial neural networks (ANN) are employed to optimize the removal efficiency. RSM models the efficiency and facilitates numerical optimization, while the ANN model is optimized using the moth search algorithm (MSA) for optimal results. © 2023
Preparation and Characterization of nZVI, Bimetallic Fe 0-Cu, and Fava Bean Activated Carbon-Supported Bimetallic AC-F e 0-Cu for Anionic Methyl Orange Dye Removal
Nano zero-valent iron (nZVI), bimetallic Nano zero-valent iron-copper (Fe 0- Cu), and fava bean activated carbon-supported with bimetallic Nano zero-valent iron-copper (AC-F e 0-Cu) were prepared and characterized by DLS, FT-IR, XRD, and SEM. The influence of the synthesized adsorbents on the adsorption and removal of soluble anionic methyl orange (M.O) dye was investigated using UV-V spectroscopy. The influence of numerous operational parameters was studied at varied pH (3–9), time intervals (15–180 min), and dye concentrations (25–1000 ppm) to establish the best removal conditions. The maximum removal efficiency of M.O. using the prepared adsorbent materials reached about 99%. The removal efficiency is modeled using response surface methodology (RSM). The Bimetallic Fe -Cu, the best experimental and predicted removal efficiency is 96.8% RE. For the H2SO4 chemical AC- Fe -Cu, the best experimental and removal efficiency is 96.25% RE. The commercial AC-Fe0–Cu, the best experimental and predicted removal efficiency is 94.93%RE. This study aims to produce low-cost adsorbents such as Bimetallic Fe0-Cu, and Fava Bean Activated Carbon-Supported Bimetallic AC-Fe0-Cu to treat the industrial wastewater from the anionic methyl orange (M.O) dye and illustrate its ability to compete H2SO4 chemical AC-Fe0-Cu, and commercial AC-Fe0-Cu. © 2023, The Author(s).
A Unified FPGA Realization for Fractional-Order Integrator and Differentiator
This paper proposes a generic FPGA realization of an IP core for fractional-order integration and differentiation based on the Grünwald–Letnikov approximation. All fractional-order dependent terms are approximated to simpler relations using curve fitting to enable an efficient hardware realization. Compared to previous works, the proposed design introduces enhancements in the fractional-order range covering both integration and differentiation. An error analysis between software and hardware results is presented for sine, triangle and sawtooth signals. The proposed generic design is realized on XC7A100T FPGA achieving frequency of 9.328 MHz and validated experimentally for a sine input signal on the oscilloscope. The proposed unified generic design is suitable for biomedical signal processing applications. In addition, it can be employed as a laboratory tool for fractional calculus education. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
CORDIC-Based FPGA Realization of a Spatially Rotating Translational Fractional-Order Multi-Scroll Grid Chaotic System
This paper proposes an algorithm and hardware realization of generalized chaotic systems using fractional calculus and rotation algorithms. Enhanced chaotic properties, flexibility, and controllability are achieved using fractional orders, a multi-scroll grid, a dynamic rotation angle(s) in two- and three-dimensional space, and translational parameters. The rotated system is successfully utilized as a Pseudo-Random Number Generator (PRNG) in an image encryption scheme. It preserves the chaotic dynamics and exhibits continuous chaotic behavior for all values of the rotation angle. The Coordinate Rotation Digital Computer (CORDIC) algorithm is used to implement rotation and the Grünwald–Letnikov (GL) technique is used for solving the fractional-order system. CORDIC enables complete control and dynamic spatial rotation by providing real-time computation of the sine and cosine functions. The proposed hardware architectures are realized on a Field-Programmable Gate Array (FPGA) using the Xilinx ISE 14.7 on Artix 7 XC7A100T kit. The Intellectual-Property (IP)-core-based implementation generates sine and cosine functions with a one-clock-cycle latency and provides a generic framework for rotating any chaotic system given its system of differential equations. The achieved throughputs are (Formula presented.) Mbits/s and (Formula presented.) Mbits/s for two- and three-dimensional rotating chaotic systems, respectively. Because it is amenable to digital realization, the proposed spatially rotating translational fractional-order multi-scroll grid chaotic system can fit various secure communication and motion control applications. © 2022 by the authors.
An Encryption Application and FPGA Realization of a Fractional Memristive Chaotic System
The work in this paper extends a memristive chaotic system with transcendental nonlinearities to the fractional-order domain. The extended system’s chaotic properties were validated through bifurcation analysis and spectral entropy. The presented system was employed in the substitution stage of an image encryption algorithm, including a generalized Arnold map for the permutation. The encryption scheme demonstrated its efficiency through statistical tests, key sensitivity analysis and resistance to brute force and differential attacks. The fractional-order memristive system includes a reconfigurable coordinate rotation digital computer (CORDIC) and Grünwald–Letnikov (GL) architectures, which are essential for trigonometric and hyperbolic functions and fractional-order operator implementations, respectively. The proposed system was implemented on the Artix-7 FPGA board, achieving a throughput of 0.396 Gbit/s. © 2023 by the authors.
Arithmetic optimization approach for parameters identification of different PV diode models with FOPI-MPPT
The Maximum Power Point Tracker (MPPT) provides the most efficient use of a Photo-voltaic system independent of irradiance or temperature fluctuations. This paper introduces the modeling and control of a photo-voltaic system operating at MPPT using the arithmetic optimization algorithm (AOA). The single and double Photo-voltaic models are investigated. Their optimal unknown parameters are extracted using AOA based on commercial Photo-voltaic datasheets. A comparison is performed between these optimal parameters extracted by AOA and other optimization techniques presented in the literature. These parameters generate the P – V and I – V curves for the studied models considering the temperature factor. A good match is achieved relative to the manufacturer data. A DC-DC boost converter is used as a link between the PV modules and the load. The converter duty cycle is adjusted, varying the climatic conditions using three cases: without a controller, using PI controller, and using the fractional-order PI controller (FOPI). The AOA is employed to set the optimum controllers parameters to maintain the impedance matching between the PV modules and the load. The FOPI shows a significant improvement in controlling the system performance. © 2021 THE AUTHORS
Discrete fractional-order Caputo method to overcome trapping in local optima: Manta Ray Foraging Optimizer as a case study
Enhancing the exploration and exploitation phases of the metaheuristic (MH) optimization algorithms is the key to avoiding local optima. The Manta ray foraging optimizer is a recently proposed MH optimizer. The MRFO showed a good performance in the simple optimization problems. However, it is trapped into the local optimum in the more elaborated ones due to the original algorithm’s low capability in exploiting the optimal solutions and its convergence. From this principle, in this work, a novel variant of the Manta ray foraging optimizer has been proposed for global optimization problems, engineering design optimization problems, and multi-threshold segmentation. In the proposed approach, the fractional calculus (FC) using Caputo fractional differ-sum operator has been adopted to enhance the manta rays movement in the exploitation phase via utilizing history dependency of FC to boost exploiting the optimal solutions via sharing the past knowledge over the optimization process. Moreover, to avoid premature convergence, the somersault factor has been adaptively tuned. The fractional-order Caputo Manta-Ray Foraging Optimizer (FCMRFO) has been proposed. The proposed algorithm’s sensitivity for the FC coefficients has been tested with ten-dimensional CEC2017 benchmarks. The scalability test of the proposed algorithm has been performed with 30, 50 and 100-dimensional CEC2017. Moreover, CEC2020 benchmarks with dimensions 5 and 20 have been applied for providing an extensive investigation, and the FCMRFO has been compared with recent state-of-the-art algorithms. Through utilizing the non-parametric statistical analysis and ranking test, the FCMRFO confirms its superiority and ability to avoid the local optimum in several cases. For the second part of the study, three constrained engineering design problems have been investigated; then, numerous natural images are applied to appraise the FCMRFO for multilevel threshold image segmentation. By performing several metrics, the FCMRFO proves its quality and efficiency compared to recent well-regarded algorithms in engineering applications and image segmentation. © 2021
Parameter Identification of Li-ion Batteries: A Comparative Study
Lithium-ion batteries are crucial building stones in many applications. Therefore, modeling their behavior has become necessary in numerous fields, including heavyweight ones such as electric vehicles and plug-in hybrid electric vehicles, as well as lightweight ones like sensors and actuators. Generic models are in great demand for modeling the current change over time in real-time applications. This paper proposes seven dynamic models to simulate the behavior of lithium-ion batteries discharging. This was achieved using NASA room temperature random walk discharging datasets. The efficacy of these models in fitting different time-domain responses was tested through parameter identification with the Marine Predator Algorithm (MPA). In addition, each model’s term’s impact was analyzed to understand its effect on the fitted curve. The proposed models show an average absolute normalized error as low as (Formula presented.). © 2023 by the authors.