Article
Engineering, Environmental
Pezhman Kazemi, Christophe Bengoa, Jean-Philippe Steyer, Jaume Giralt
Summary: This study proposes a practical data-driven framework for fault detection in anaerobic digestion process, based on predicting VFA concentration and validated using advanced techniques. The results demonstrate the good performance and feasibility of the framework in terms of fault detection.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2021)
Letter
Automation & Control Systems
Peihao Du, Weimin Zhong, Xin Peng, Linlin Li, Zhi Li
Summary: This letter addresses the issue of data-driven fault compensation tracking control for a coupled wastewater treatment process (WWTP) affected by sensor faults. Invariant set theory is utilized to eliminate the conditions of coupled non-affine dynamics and explicitly express the control inputs. An adaptive fault compensation mechanism is developed to adapt to the effects of sensor faults. Experimental studies on a standardized WWTP platform are conducted to demonstrate the effectiveness of the proposed strategy.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Review
Engineering, Chemical
Pengfei Yan, Minghui Gai, Yuhong Wang, Xiaoyong Gao
Summary: Anaerobic digestion process requires real-time monitoring of key variables to improve efficiency and stability. However, the current market real-time monitoring equipment has limitations, leading to the necessity of soft sensor modeling as a solution.
Article
Automation & Control Systems
Qingqiang Sun, Zhiqiang Ge
Summary: The article first demonstrates the necessity and significance of deep learning for soft sensor applications by analyzing the merits of deep learning and the trends of industrial processes. It then summarizes mainstream deep learning models, tricks, and frameworks/toolkits, and discusses the demands and problems occurred in practical applications. Finally, outlook and conclusions are given for future research directions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Energy & Fuels
Diana Dominguillo-Ramirez, Jorge Aburto, Hector Hugo Leon-Santiesteban, Elias Martinez-Hernandez
Summary: In this study, an artificial neural network (ANN) model was developed to predict methane yield using a collected dataset of 340 experimental data. The model's input parameters were biomass composition in terms of total solids (TS), volatile solids (VS), lipids, protein, and lignin. The results showed that the ANN-based model had a superior predictive power compared to conventional multiple regression models, with lower RMSE values and lower prediction errors in most cases. Therefore, the model is useful for preliminary stages of process design and evaluation of AD-based bioenergy projects.
Article
Environmental Sciences
Mohsen Asadi, Kerry McPhedran
Summary: Anaerobic digestion processes produce biogas which can be used as an energy source. Developing data-driven models using operating parameters can increase biogas production rates. The study compared processed and unprocessed input variables to develop regression models for estimating biogas production rates from municipal wastewater treatment plant anaerobic digestors. The results showed that the developed non-linear regression model with unprocessed inputs performed the best, with a balance between accuracy and uncertainty when compared to artificial neural network and adaptive network-based fuzzy inference system models. The models were further optimized using a genetic algorithm, with maximum biogas production rate estimates ranging from 22.0 to 28.6 m3/min.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Automation & Control Systems
Jeremiah Corrigan, Jie Zhang
Summary: This paper introduces a data-driven soft-sensor modelling approach based on dynamic kernel slow feature analysis (KSFA), which can extract nonlinear driving forces and improve soft-sensor performance by utilizing a neural network to reduce noise. The combination of KSFA with a neural network further enhances soft-sensor performance in cases of nonlinear relationships.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Multidisciplinary Sciences
Dong Xiao, Lu Huang, Mohamed Keita, Hailun He, Dayong Chen, Jin Li
Summary: The CC30A CH4-CO2 combined analyzer with an infrared gas sensor as the core detection device can be widely used for online gas component analysis. A model for calculating effective values was designed using dimensionality reduction of dynamic data, improving efficiency and reducing the size of data analysis windows.
Article
Environmental Sciences
Moonil Kim, Fenghao Cui
Summary: In this study, a multilayer statistical technique using regression models was employed to support the development of anaerobic digestion models. Experimental data from lab-scale, pilot-scale, and full-scale reactors were used to demonstrate the modelling process. The developed models showed high accuracy in predicting biogas production during anaerobic digestion.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Optics
Kai Sun, Zhenhua Wang, Qimeng Liu, Hao Chen, Weikun LI, Weicheng Cui
Summary: In this paper, a multi-joint waveguide bending sensor based on color dyed filters is designed to detect bending angles, directions, and positions. The sensors are fabricated using soft silicone rubber through the casting method. Time series neural networks are utilized to predict bending position and angle quantitatively. The results confirm that the waveguide sensor demodulated by the data-driven neural network algorithm performs well and can be used for engineering applications.
Article
Optics
Kai Sun, Zhenhua Wang, Qimeng Liu, Hao Chen, Weikun Li, Weicheng Cui
Summary: In this paper, a multi-joint waveguide bending sensor based on color dyed filters is designed to detect bending angles, directions and positions. The sensors are fabricated using soft silicone rubber and time series neural networks are utilized for quantitative prediction. The results confirm the good performance of the sensor for engineering applications.
Article
Agronomy
Reza Salehi, Qiuyan Yuan, Sumate Chaiprapat
Summary: In this study, two data-driven models, k-nearest neighbours (k-NN) and support vector machine (SVM), were proposed to predict biogas production from anaerobic digestion. The results showed that the Gaussian-based SVM model performed slightly better than the k-NN model in predicting biogas production. These findings suggest that SVM modeling is a reliable technique for predicting biogas production in anaerobic digestion processes.
Article
Engineering, Geological
Geng-Fu He, Pin Zhang, Zhen-Yu Yin, Yin-Fu Jin, Yi Yang
Summary: This study proposes a modelling framework based on multi-fidelity data to accurately model the rate-dependent behavior of soft clays. The framework captures stress-strain-strain rate correlations using both low-fidelity and high-fidelity data, and utilizes a residual neural network for final predictions. The results demonstrate that the framework has strong modeling capability, low demand for experimental data, and good robustness.
GEORISK-ASSESSMENT AND MANAGEMENT OF RISK FOR ENGINEERED SYSTEMS AND GEOHAZARDS
(2023)
Article
Engineering, Civil
Hoseong Jeong, Sun-Jin Han, Seung-Ho Choi, Jae-Hyun Kim, Kang Su Kim
Summary: This study derived a practical equation using genetic programming to predict the transfer length of prestressing strands, which exhibited a higher level of accuracy compared to other existing equations.
ENGINEERING STRUCTURES
(2021)
Article
Green & Sustainable Science & Technology
Federico Moretta, Alessia Goracci, Flavio Manenti, Giulia Bozzano
Summary: Anaerobic digestion is an environmentally friendly technology that utilizes organic substrates to produce biogas. This study focuses on the optimization of blended feedstock composition to maximize methane potential, considering supply chain issues. A database and data-driven model are developed to evaluate the optimal composition, taking into account influencing parameters and validated through experimental tests.
JOURNAL OF CLEANER PRODUCTION
(2022)
Review
Green & Sustainable Science & Technology
Ulysse Bremond, Aude Bertrandias, Jean-Philippe Steyer, Nicolas Bernet, Helene Carrere
Summary: The future European Green Deal aims to reduce greenhouse gas emissions by 2030, with a focus on decarbonizing the gas sector and developing biomethane. The biogas sector is shifting towards utilizing organic wastes and agricultural by-products as feedstocks, upgrading biogas to biomethane for various applications, and reducing subsidy schemes to increase sustainability and reduce production costs. This article identifies and discusses key improvement tracks for the biogas sector to ensure growth towards 2030 and beyond.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Environmental
Pezhman Kazemi, Christophe Bengoa, Jean-Philippe Steyer, Jaume Giralt
Summary: This study proposes a practical data-driven framework for fault detection in anaerobic digestion process, based on predicting VFA concentration and validated using advanced techniques. The results demonstrate the good performance and feasibility of the framework in terms of fault detection.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2021)
Article
Engineering, Environmental
Alexandre Mallet, Cyrille Charnier, Eric Latrille, Ryad Bendoula, Jean-Philippe Steyer, Jean-Michel Roger
Summary: Near infrared spectroscopy (NIRS) is used for organic waste management, with a customized system allowing simultaneous scanning of spectra and estimation of dry matter content during the drying process. Water effects on near infrared spectra are complex, involving both physical and chemical effects, and are influenced by sample characteristics and moisture levels.
Article
Environmental Sciences
Mohammad Shaiful Alam Amin, Frank Stuber, Jaume Giralt, Agustin Fortuny, Azael Fabregat, Jose Font
Summary: The study utilized a novel integrated technology of ceramic supported carbon membrane (CSCM) to degrade azo dyes through an anaerobic mixed culture. The CSCM functioned as biofilm support, redox mediator, and nano-filter to enhance dye decolorization efficiency. Different B-CSCMs were studied for dye removal experiments, showing efficient, cost-effective, and eco-friendly azo dye decolorization method under specific conditions.
Article
Food Science & Technology
Nerea Garcia-Gutierrez, Jorge Mellado-Carretero, Christophe Bengoa, Ana Salvador, Teresa Sanz, Junjing Wang, Montse Ferrando, Carme Guell, Silvia de Lamo-Castellvi
Summary: The study successfully used ATR-FTMIR and multivariate analysis to distinguish doughs and snacks enriched with different insect powders, with PLSR models accurately predicting the percentage of insect powder added to the products. This technology shows great potential for authentication of insect products.
Article
Materials Science, Multidisciplinary
Oleg Dubov, Jaume Giralt Marce, Agusti Fortuny, Azael Fabregat, Frank Stuber, Josep Font
Summary: Uniform flexible carbon nitride coatings were synthesized by annealing soluble triazine-based polymeric precursors, exhibiting outstanding electrochemical stability and increased capacitance. The coatings, composed of nearly equal atomic quantities of carbon and nitrogen, showed noticeable mechanical strength and optical bandgaps ranging from 1.71 to 1.99 eV, with good conductivity.
JOURNAL OF MATERIALS SCIENCE
(2022)
Article
Microbiology
Ulysse Bremond, Aude Bertrandias, Jerome Hamelin, Kim Milferstedt, Valerie Bru-Adan, Jean-Philippe Steyer, Nicolas Bernet, Helene Carrere
Summary: The recirculation of solid digestate with ligninolytic aerobic consortia did not increase methane recovery during the short-term aerobic post-treatment. The decrease in methane yields was attributed to the respiration of easily degradable fractions by the selected consortia.
Article
Engineering, Environmental
Mohammad Shaiful Alam Amin, Frank Stuber, Jaume Giralt, Agusti Fortuny, Azael Fabregat, Josep Font
Summary: A continuous compact membrane bioreactor consisting of ceramic-supported graphene oxide membrane was successfully used for anaerobic decolorization of azo dye solutions, showing stable and efficient decolorization performance under low permeate flux.
JOURNAL OF WATER PROCESS ENGINEERING
(2022)
Article
Biochemistry & Molecular Biology
Mohammad Shaiful Alam Amin, Frank Stuber, Jaume Giralt, Agustin Fortuny, Azael Fabregat, Josep Font
Summary: This study explores the application of ceramic-supported carbon membrane bioreactors and ceramic-supported graphene oxide membrane bioreactors in treating dye wastewater. The results show that the conductive surface of the graphene oxide membrane is more efficient in removing color from dye solutions.
Review
Biochemistry & Molecular Biology
Natalia Soledad Inchaurrondo, Josep Font
Summary: This review discusses the use of natural materials as catalysts in the ozonation process. It emphasizes the structural characteristics and modifications of these materials, as well as the catalytic oxidation mechanism, operating parameters, and degradation efficiency. The review suggests that further research is needed in realistic scenarios to transfer this technology to real wastewater treatment.
Article
Engineering, Environmental
Mary Farah, Jaume Giralt, Frank Stuber, Josep Font, Azael Fabregat, Agusti Fortuny
Summary: This study evaluated the extraction and transport of three pharmaceutical compounds using liquid-liquid extraction and supported liquid membrane methods. Results showed that Cy923 was an efficient extractant for diclofenac and ibuprofen, while Versatic Acid 10 was suitable for carbamazepine. The concentration of the extractants also affected the transport of diclofenac.
JOURNAL OF WATER PROCESS ENGINEERING
(2022)
Article
Biotechnology & Applied Microbiology
Mohammad Shaiful Alam Amin, Md. Salatul Islam Mozumder, Frank Stuber, Jaume Giralt, Agusti Fortuny, Azael Fabregat, Josep Font
Summary: A mathematical model was developed to describe the steady-state behavior of ceramic-supported graphene oxide membrane bioreactors treating wastewater with azo dyes. The model was calibrated and validated using experimental data and it was found that support materials with high electron transfer capacity increased the biofilm activity and hydrolysis rate. Acetate as an external carbon source improved dye removal efficiency, but the acetate to dye ratio did not directly affect the removal efficiency.
ENVIRONMENTAL TECHNOLOGY & INNOVATION
(2023)
Article
Engineering, Environmental
Mohammad Shaiful Alam Amin, Frank Stuber, Jaume Giralt, Agusti Fortuny, Azael Fabregat, Josep Font
Summary: This research focuses on a highly efficient compact tubular ceramic-supported carbon-based membrane reactor integrated with anaerobic biodegradation to decolorize azo dyes. Two different carbon-based membranes were evaluated for color removal of three structurally different azo dyes. The results showed that the tubular ceramic-supported graphene oxide membrane (TCSGOM) was more efficient in removing color from dye solutions compared to the tubular ceramic-supported carbonized membrane (TCSCM) in a wide range of feed concentrations.
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING
(2023)