Modeling, Instrumentation, Automation, and Optimization of Water Resource Recovery Facilities (2020) DIRECT.

A review of the literature published in 2019 on topics relating to water resource recovery facilities (WRRF) in the areas of modeling, automation, measurement and sensors and optimization of wastewater treatment (or water resource reclamation) is presented.

[1]  G. Daigger,et al.  Activated sludge morphology significantly impacts oxygen transfer at the air–liquid boundary , 2019, Water environment research : a research publication of the Water Environment Federation.

[2]  Jiannan Cai,et al.  A Novel Model with GA Evolving FWNN for Effluent Quality and Biogas Production Forecast in a Full-Scale Anaerobic Wastewater Treatment Process , 2019, Complex..

[3]  Ni-Bin Chang,et al.  Advances in control technologies for wastewater treatment processes: status, challenges, and perspectives , 2019, IEEE/CAA Journal of Automatica Sinica.

[4]  W. Rauch,et al.  Sweating the assets - The role of instrumentation, control and automation in urban water systems. , 2019, Water research.

[5]  Pastora Vega,et al.  Analytical Fuzzy Predictive Control Applied to Wastewater Treatment Biological Processes , 2019, Complex..

[6]  Pasquale Contestabile,et al.  Combined Exploitation of Offshore Wind and Wave Energy in the Italian Seas: A Spatial Planning Approach , 2019, Front. Energy Res..

[7]  Raquel Dormido,et al.  Machine Learning Weather Soft-Sensor for Advanced Control of Wastewater Treatment Plants , 2019, Sensors.

[8]  G. Orellana,et al.  Unprecedented Reversible Real-Time Luminescent Sensing of H2S in the Gas Phase. , 2019, Analytical chemistry.

[9]  Israel Joel Koenka,et al.  Capillary electrophoresis for continuous nitrogen quantification in wastewater treatment processes. , 2019, Talanta.

[10]  Juan de Santiago,et al.  Wave Power Output Smoothing through the Use of a High-Speed Kinetic Buffer , 2019, Energies.

[11]  M. Zappi,et al.  A Methodology for Global Sensitivity Analysis of Activated Sludge Models: Case Study with Activated Sludge Model No. 3 (ASM3) , 2019, Water environment research : a research publication of the Water Environment Federation.

[12]  Khaled Zoroufchi Benis,et al.  A systematic approach for selecting an optimal strategy for controlling VOCs emissions in a petrochemical wastewater treatment plant , 2018, Stochastic Environmental Research and Risk Assessment.

[13]  Jian Liu,et al.  Interval multiple-output soft sensors development with capacity control for wastewater treatment applications: A comparative study , 2019, Chemometrics and Intelligent Laboratory Systems.

[14]  Carlos E. T. Dorea,et al.  Oxygen Uptake Rate Measurement Using Kalman Filter and PWM Control in Activated Sludge Systems , 2019, IEEE Transactions on Instrumentation and Measurement.

[15]  Isaac Chairez Oria,et al.  A survey on artificial neural networks application for identification and control in environmental engineering: Biological and chemical systems with uncertain models , 2019, Annu. Rev. Control..

[16]  Yongqiang Cheng,et al.  Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography , 2019, Complex..

[18]  Tzahi Y Cath,et al.  Data-driven performance analyses of wastewater treatment plants: A review. , 2019, Water research.

[19]  Walter Z. Tang,et al.  Statistical analysis of sustainable production of algal biomass from wastewater treatment process , 2019, Biomass and Bioenergy.

[20]  David E. Gorelick,et al.  Multiobjective Optimal Siting of Algal Biofuel Production with Municipal Wastewater Treatment in Watersheds with Nutrient Trading Markets , 2019, Journal of Water Resources Planning and Management.

[21]  D. Vamvuka,et al.  Combustion Performance of Sludge From a Wastewater Treatment Plant in Fluidized Bed. Factorial Modeling and Optimization of Emissions , 2019, Front. Energy Res..

[22]  Ying Hou,et al.  Optimal control for wastewater treatment process based on an adaptive multi-objective differential evolution algorithm , 2017, Neural Computing and Applications.

[23]  Xiaoyun Sun,et al.  A Biological Mechanism Based Structure Self-Adaptive Algorithm for Feedforward Neural Network and Its Engineering Applications , 2019, IEEE Access.

[24]  Impacts of feed dilution and lower solids retention time on performance of thermal hydrolysis/anaerobic digestion , 2019, Water environment research : a research publication of the Water Environment Federation.

[25]  Jing Wu,et al.  Modeling of Adaptive Multi-Output Soft-Sensors With Applications in Wastewater Treatments , 2019, IEEE Access.

[26]  W. Parker,et al.  Effect of solids residence time on dynamic responses in chemical P removal , 2019, Water environment research : a research publication of the Water Environment Federation.

[27]  Ziyi Yang,et al.  Modified anaerobic digestion model No.1 (ADM1) for modeling anaerobic digestion process at different ammonium concentrations , 2019, Water environment research : a research publication of the Water Environment Federation.

[28]  M. Kriipsalu,et al.  Factors affecting SVI in small scale WWTPs. , 2019, Water science and technology : a journal of the International Association on Water Pollution Research.

[29]  Zhiqiang Ge,et al.  Multirate Factor Analysis Models for Fault Detection in Multirate Processes , 2019, IEEE Transactions on Industrial Informatics.

[30]  Junfei Qiao,et al.  Multiobjective optimal control for wastewater treatment process using adaptive MOEA/D , 2018, Applied Intelligence.

[31]  K. Gernaey,et al.  Plant-wide model-based analysis of iron dosage strategies for chemical phosphorus removal in wastewater treatment systems. , 2019, Water research.

[32]  K. Chandran,et al.  Nitrate residual as a key parameter to efficiently control partial denitrification coupling with anammox , 2019, Water environment research : a research publication of the Water Environment Federation.

[33]  M. V. van Loosdrecht,et al.  Resource recovery and wastewater treatment modelling , 2019, Environmental Science: Water Research & Technology.

[34]  Stefan Weijers,et al.  The future of WRRF modelling - outlook and challenges. , 2018, Water science and technology : a journal of the International Association on Water Pollution Research.

[35]  Francisco J. Pérez-Reche,et al.  Challenges of biofilm control and utilization: lessons from mathematical modelling , 2019, Journal of the Royal Society Interface.