This paper presents a modified fractional-order model (FOM) for microorganism stimulation in an up-flow anaerobic sludge blanket (UASB) reactor treating low-strength wastewater. This study aimed to examine the famine period of methanogens due to biomass accumulation in the UASB reactor over long time periods at a constant organic loading rate (OLR). This modified model can investigate the substrate biodegradation in a UASB reactor while considering substrate diffusion into biological granules during the feast and famine periods of methanogens. The Grünwald-Letnikov numerical technique was used to indicate the effect of biomass degradation on the biogas production rate and substrate biodegradation in a UASB reactor installed at Zenein Wastewater Treatment Plant (WWTP) in Giza, Egypt. Several fractional orders were applied in the dynamic model at biomass concentrations of 20 and 4 kg/ m3 in the reactor bed and blanket zones, respectively. An OLR of 0.9 kgCOD/ m3/ day using the calibrated kinetic parameters at 11 ?C was applied to comply with the experimental outcomes. The simulation results indicate that the removal efficiency of chemical oxygen demand (COD) was maintained at approximately 55 – 65 % , whereas the biogas production rate declined from 0.35 to 0.05 m3CH4/ kgCODr in the reactor bed zone due to a decline in food to microorganism (F/M) ratio from 0.04 to 0.018 d- 1 during the sludge retention time (SRT) in the UASB reactor. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Review of activated carbon adsorbent material for textile dyes removal: Preparation, and modelling
Water contamination with colours and heavy metals from textile effluents has harmed the ecology and food chain, with mutagenic and carcinogenic effects on human health. As a result, removing these harmful chemicals is critical for the environment and human health. Various standard physicochemical and biological treatment technologies are used; however, there are still some difficulties. Adsorption is described as a highly successful technology for removing contaminants from textile-effluents wastewater compared to other methods. Several adsorbent materials, including nanomaterials, natural materials, and biological biomasses, are identified as effective adsorbents for textile effluents. Activated carbon preparation from these different adsorbents is an excellent pre-treatment to remove the adsorption capacity. Therefore, through this study various adsorbent types, especially activated carbon adsorbents will be discussed in addition to the factors affecting adsorption and models applied for optimising the adsorption process. © 2022
Correction to: Modified fractional-order model for biomass degradation in an up-flow anaerobic sludge blanket reactor at Zenein Wastewater Treatment Plant (Environmental Science and Pollution Research, (2022), 29, 17, (25980-25986), 10.1007/s11356-022-18797-9)
The 6th Nomenclature should be CXin, CSin. The Original article has been corrected. © Springer-Verlag GmbH Germany, part of Springer Nature 2022.
Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control
Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Modeling of Soft Pneumatic Actuators with Different Orientation Angles Using Echo State Networks for Irregular Time Series Data
Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning is presented to model the kinematics of Soft Pneumatic Actuators (SPAs). An Echo State Network (ESN) architecture is used to predict the SPA’s tip position in 3 axes. Initially, data from actual 3D printed SPAs is obtained to build a training dataset for the network. Irregularintervals pressure inputs are used to drive the SPA in different actuation sequences. The network is then iteratively trained and optimized. The demonstrated method is shown to successfully model the complex non-linear behavior of the SPA, using only the control input without any feedback sensory data as additional input to the network. In addition, the ability of the network to estimate the kinematics of SPAs with different orientation angles ? is achieved. The ESN is compared to a Long Short-Term Memory (LSTM) network that is trained on the interpolated experimental data. Both networks are then tested on Finite Element Analysis (FEA) data for other ? angle SPAs not included in the training data. This methodology could offer a general approach to modeling SPAs with varying design parameters. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Enhanced removal of crystal violet using rawfava bean peels, its chemically activated carbon compared with commercial activated carbon
Crystal violet is a basic dye that is widely used by various industries, such as textiles and paints. These industries discharge their effluents, contaminated with crystal violet, into water streams, and these effluents have an adverse effect on aquatic organisms, the environment, and human health. Crystal violet is a basic dye that is widely used by various industries, such as textiles and paints. These industries discharge their effluents, contaminated with crystal violet, into water streams, and these effluents have an adverse effect on aquatic organisms, the environment, and human health. Hence, this paper is directed at studying the removal of crystal violet using environmentally friendly, cost-effective adsorbent materials such as raw fava bean (RFP-H3F), and chemically activated carbon (H3F) in comparison to commercial activated carbon (CAC).Various characterization techniques are applied, such as XRD, FT-IR,and SEM analyses. Then, the process of optimizing is shown through some preliminary experiments and a Response Surface Methodology (RSM) experiment to find the best conditions for removing crystal violet efficiently. Results revealed that the raw fava bean peels and the commercial activated carbon have the maximum removal efficiency of 95 %, and 83 % respectively, after 180 min of contact time. It is hypothesized that raw fava bean peels (RFP) and chemically activated carbon using phosphoric acid RFP-H3F will exhibit comparable efficiency in removing crystal violet when compared to commercial activated carbon (CAC). Various characterization techniques, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR),and scanning electron microscopy (SEM), are applied to analyze the properties of the adsorbent materials. Afterwards, the optimization process is displayed through some preliminary experiments followed by a Response Surface Methodology (RSM) experiment to obtain the optimum conditions, which achieve high crystal violet removal efficiency. The results demonstrate that both raw fava bean peels and commercial activated carbon exhibit significant removal efficiencies, with raw fava bean peels achieving a maximum removal efficiency of 95 % and commercial activated carbon achieving 83 %. © 2023 The Authors
Modified kinetic-hydraulic UASB reactor model for treatment of wastewater containing biodegradable organic substrates
This paper addresses a modified kinetic-hydraulic model for up-flow anaerobic sludge blanket (UASB) reactor aimed to treat wastewater of biodegradable organic substrates as acetic acid based on Van der Meer model incorporated with biological granules inclusion. This dynamic model illustrates the biomass kinetic reaction rate for both direct and indirect growth of microorganisms coupled with the amount of biogas produced by methanogenic bacteria in bed and blanket zones of reactor. Moreover, the pH value required for substrate degradation at the peak specific growth rate of bacteria is discussed for Andrews’ kinetics. The sensitivity analyses of biomass concentration with respect to fraction of volume of reactor occupied by granules and up-flow velocity are also demonstrated. Furthermore, the modified mass balance equations of reactor are applied during steady state using Newton Raphson technique to obtain a suitable degree of freedom for the modified model matching with the measured results of UASB Sanhour wastewater treatment plant in Fayoum, Egypt. © IWA Publishing 2016.
Bio-inspired adsorption sheets from waste material for anionic methyl orange dye removal
Abstract: Nano zero-valent iron (nZVI), bimetallic nano zero-valent iron-copper (Fe0–Cu), and Raw algae (sargassum dentifolium) activated carbon-supported bimetallic nano zero-valent iron-copper (AC-Fe0–Cu) are synthesized and characterized using FT-IR, XRD, and SEM. The maximum removal capacity is demonstrated by bimetallic activated carbon AC-Fe0–Cu, which is estimated at 946.5 mg/g capacity at the condition pH = 7, 30 min contact time under shaking at 120 rpm at ambient temperature, 200 ppm of M.O, and 1 g/l dose of raw algae-Fe0–Cu adsorbent. The elimination capability of the H3PO4 chemical AC-Fe0–Cu adsorbent is 991.96 mg/g under the conditions of pH = 3, 120 min contact time under shaking at 120 rpm at room temperature, 200 ppm of M.O, and 2 g/l doses of H3PO4 chemical AC-Fe0–Cu adsorbent. The Bagasse activated carbon adsorbent sheet achieves a removal capacity of 71.6 mg/g MO dye solution. 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, AC-Fe0–Cu, H3PO4 chemical AC-Fe0–Cu and bagasse activated carbon(CH), with corrected R-Squared values of 0.9656, 0.9926, 0.964, and 0.951respectively. 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. Highlights: 1.The Fe0–Cu composite, when combined with activated carbon from Bagasse Pulp (CH), exhibited the most effective decolorization effectiveness for anionic colours present in wastewater.2.The utilization of composites presents a promising opportunity for efficient dye removal due to its cost-effectiveness and environmentally sustainable nature. 3.The utilization of response surface approach and artificial neural network modelling improves the efficacy of removal processes and treatment techniques. © 2023, The Author(s).
Commercial Versus Natural Activated Carbon Fabricated Sheets: Applied to Dyes Removal Application
Industrial dyes are considered one of the main causes of increased water pollution of water. Many businesses, such as steel and paper, are located along riverbanks because they require large amounts of water in their manufacturing processes, and their wastes, which contain acids, alkalis, dyes, and other chemicals, are dumped and poured into rivers as effluents. For example, chemical enterprises producing aluminum emit a significant quantity of fluoride into the air and effluents into water bodies. Fertilizer facilities produce a lot of ammonia, whereas steel plants produce cyanide. Many nations consider employing wastewater treatment plants using physical, biological, and chemical methods to clean the wastewater to address environmental crises. The treated water can be used for targeting the irrigation systems in its majority, as it is biologically acceptable for that specific use, industrial dyes are considered one of the leading causes of increased water pollution of water. Many businesses, such as steel and paper, are located along riverbanks because they require large amounts of water in their manufacturing processes, and their wastes, which contain acids, alkalis, dyes, and other chemicals, are dumped and poured into rivers as effluents. For example, chemical enterprises producing aluminum emit a significant quantity of fluoride into the air and effluents into water bodies. Fertilizer facilities produce much ammonia, whereas steel plants produce cyanide. Chromium salts are used in. Many nations consider employing wastewater treatment plants using physical, biological, and chemical methods to clean the wastewater to address environmental crises. The treated water can target the majority of irrigation systems, as it is biologically acceptable for that specific use, which economizes the use of freshwater sources for municipal use. This study presents a novel method for fabricating an efficient adsorbent sheet for wastewater treatment. The sheets are fabricated by combining sugarcane bagasse pulp as a scaffold with commercial, naturally activated carbon, and bimetallic-prepared adsorbents. Sugarcane bagasse is utilized in producing activated carbon because of its high carbon contents, availability, and low cost. The prepared composite sheets are synthesized and investigated for pollutants removal of crystal violet (CV), methyl orange (MO), and Chromium (CI) dyes. Different weight ratios of activated carbon are used to form a bio-composite mixed sheet. The formed sheets’ morphology is performed via a high scanning electron microscope (SEM) and Fourier Transform Infrared Spectroscopy (FTIR). To determine the adsorption mechanism, the intra-particle diffuse screening experiment is used to test the experimental data. All the prepared sheets can retain the pollutants, with the best removal efficiency of 98% for methyl orange adsorption onto the bio-composite mixed sheet. The results of the parameter (time, concentration, and dose) sets provided valuable proof that the adsorption of methyl orange onto the bio-composite sheet mixed with naturally activated carbon is an endothermic phenomenon involving physical adsorption. © 2024 Wiley-VCH GmbH.
Crystal violet removal using algae-based activated carbon and its composites with bimetallic Fe0-Cu
The textile industry is considered a source of pollution because of the discharge of dye wastewater. The dye wastewater effluent has a significant impact on the aquatic environment. According to the World Bank, textile dyeing, and treatment contribute 17 to 20% of the pollution of water. This paper aims to prepare the bimetallic nano zero-valent iron-copper (Fe0-Cu), algae-activated carbon, and their composites (AC-Fe0-Cu), which are employed as adsorbents. In this paper, Synthetic adsorbents are prepared and examined for the adsorption and removal of soluble cationic crystal violet (CV) dye. The influence of synthetic adsorbents on the adsorption and removal of soluble cationic crystal violet (CV) dye is investigated using UV-V spectroscopy at different pH (3-10), time intervals (15-180) min, and initial dye concentrations (50-500 ppm). Raw algae exhibit an impressive 96.64% removal efficiency under the following conditions: pH 7, contact time of 180 min, rotational speed of 120 rpm, temperature range of 25 °C-30 °C, concentration of 300 ppm in the CV dye solution, and a dose of 4 g l?1 of raw algae adsorbent. The best removal efficiencies of Raw algae Fe0-Cu, and H3PO4 chemical AC-Fe0-Cu are 97.61 % and 97.46 %, respectively, at pH = 7, contact time = 150 min, rotational speed = 120 rpm, T = (25-30) °C, concentration = 75 ppm of CV dye solution, and 1.5 g l?1 doses of raw algae F e0-Cu adsorbent and 1 g l?1 dose of H3PO4 chemical AC-Fe0-Cu adsorbent. The maximum amounts (q max) of Bi-RA and RA adsorbed for the adsorption process of CV are 85.92 mg g?1 and 1388 mg g?1, respectively. The Bi-H3A-AC model, optimized using PSO, demonstrates superior performance, with the highest adsorption capacity estimated at 83.51 mg g?1. However, the Langmuir model predicts a maximum adsorption capacity (q e ) of 275.6 mg g?1 for the CV adsorption process when utilizing Bi-H3A-AC. Kinetic and isothermal models are used to fit the data of time and concentration experiments. DLS, zeta potential, FT-IR, XRD, and SEM are used to characterize the prepared materials. Response surface methodology (RSM) is used to model the removal efficiency and then turned into a numerical optimization approach to determine the ideal conditions for improving removal efficiency. An artificial neural network (ANN) is also used to model the removal efficiency. © 2024 The Author(s). Published by IOP Publishing Ltd.