Optimization Of Treatment Process Research Articles

Artificial intelligence: basic terms and concepts, the application in healthcare and clinical medicine

Objective: to explore the potential and challenges of artificial intelligence (AI) in clinical medicine and healthcare, and to determine the prospects for its implementation to improve diagnosis, treatment, and medical data management.Material and methods. A literature review on the main terms and concepts of AI, its classification by application area, technologies, and methodologies was carried out. The learning methods such as supervised, unsupervised, and reinforcement learning were considered, as well as examples of AI application in various areas of medicine, including disease diagnosis and personalized medicine.Results. AI shows significant potential in improving diagnosis, optimizing treatment processes, and managing healthcare resources. Main application areas are related to medical image analysis, developing individualized treatment plans, and healthcare management. However, using AI faces challenges such as data availability and bias, fragmentation of systems, and complexity of algorithm interpretation.Conclusion. Despite the existing challenges, the implementation of AI in medicine has great prospects, including improved diagnostic accuracy, reduced task completion time, and development of personalized medicine. It is important to consider the ethical aspects and the demand for further study of AI application in medicine to achieve the best results.

Comparative analyses on nitrogen removal microbes and functional genes within anaerobic-anoxic-oxic and deoxidation ditch sewage-treating processes in Wuhan and Xi'an cities, China.

Anaerobic-anoxic-oxic (A2/O) and deoxidation ditch (DOD) processes are being increasingly preferred owing to their effectiveness in treating various wastes in wastewater treatment plants (WWTPs). Considering seasonal variations is crucial in optimizing treatment processes, ensuring compliance with regulations, and maintaining the overall efficiency and effectiveness of WWTPs. This study aimed to determine the influence of seasonality on nitrogen removing microbes and functional genes within A2/O and DOD processes in the humid Wuhan and semi-arid Xi'an cities, China. The physicochemical parameters of water quality were determined, and molecular and bioinformatic analyses of the bacterial community and nitrogen metabolism functional genes in the two different treatment processes of two WWTPs were performed over four seasons. Our analyses revealed a significant difference in all physicochemical parameters across all experimental groups (p < 0.05). At the genus level, the abundance of Dokdonella, one unidentified genus of Nitrospiraceae, Terrimonas, and one unidentified genus of Chloroflexi was the highest in all groups. Generally, warmer seasons exhibited higher biodiversity indices. The A2/O system exhibited higher values in terms of most nitrogen metabolism functional genes than those of the DOD sewage treatment system. In both WWTPs, the abundance of most genes in spring and summer were higher than that of autumn and winter seasons. Taken together, changes in temperature, caused by seasonal changes, may contribute to changes in abundance of nitrogen metabolic functional genes.

Environmental management of microplastics and additives: a critical review of treatment technologies and their impact

Microplastics (MPs) and their associated chemical additives, such as bisphenol A (BPA), nonylphenol (NP), nonylphenol ethoxylate (NEPO), and tetrabromobisphenol (TBBPA), are widely recognized as significant environmental contaminants due to their widespread presence in ecosystems and their potential impact on human health. This review evaluates advanced treatment technologies, such as membrane filtration and oxidation processes, for mitigating these risks and highlights gaps in sustainability and efficiency. Actionable strategies for improving the removal of MPs and MP additives were presented in the assessment of innovative hybrid treatment tailored to different water matrices. The importance of anti-fouling technologies, comprehensive life cycle assessments (LCAs), and standardizing treatment methods to enhance the sustainability and applicability of these technologies were further highlighted. To further improve and optimize treatment processes and ensure sustainability, existing knowledge gaps must be addressed by framing a comprehensive understanding of the long-term ecological effects of MPs and their additives.

Comparative analysis and application of soft sensor models in domestic wastewater treatment for advancing sustainability

ABSTRACT This study focuses on the development and evaluation of soft sensor models for predicting NH3-N values in a wastewater treatment process. The study compares the performance of linear regression (LR), neural networks (NN) and random forest regression (RFR) models. The proposed methodology involves optimizing the sequencing batch reactor process using artificial intelligence and an automatic control system. Real-time NH3-N values are obtained by inputting data from electronic conductivity and temperature sensors into the prediction models. Once the predicted NH3-N value falls below the effluent standard, the cycle ends, improving energy efficiency and sustainability by cutting down the agitator and aerator. The research results demonstrate that the RNN-based NH3-N soft sensor built in this study exhibits the best performance, which is promising for wastewater treatment process optimization and evaluation. The results show that sensor model NNR[0.5Y]H exhibits exceptional performance, utilizing recurrent neural network with 5-step input delays. Sensor NNR[0.5Y]H exhibits an R2 of 0.921, an RMSE of 6.110, and an MAE of 4.558. Based on the findings, recurrent neural network (RNN) variants emerge as the most effective modeling technique due to their ability to capture temporal dependencies and handle variable-length sequences. This study provides satisfied performance results for the NNR[0.5Y]H soft sensor model in NH3-N monitoring and process optimization in wastewater treatment, highlighting the effectiveness of recurrent neural networks and their contribution to improving interpretability, accuracy, and adaptability of soft sensor models.

Engineered biochar for advanced oxidation process towards tetracycline degradation: Role of iron and graphitic structure

The excessive accumulation of tetracycline (TC) presents significant challenges to both human health and the ecological environment. This study explores the impact of Fe-loaded sawdust graphitic carbon (engineered biochar) on TC degradation in water, utilizing an advanced oxidation process facilitated by H2O2 activation. The investigation encompasses an examination of the structural characteristics of Fe-loaded sawdust graphitic carbon and an in-depth analysis of its catalytic degradation mechanism concerning TC. Density functional theory (DFT) was utilized to construct an adsorptive degradation system for TC in water, thereby scrutinizing the optimal treatment process for TC. The findings highlight that Fe-loaded biochar exhibits not only a substantial pore structure but also inherent defects and a graphitic structure. The porous configuration enhances the TC adsorption capacity of the biochar system, while the graphitic structure bolsters the stability of the carbon framework, ensuring efficient charge transfer via the carbon defects. The activation effect of Fe(III) on H2O2 into ·O2- is dependent on its specific location within the carbon structure. In the presence of 5 mmol H2O2, Fe-loaded biochar achieves a nearly 100 % degradation rate of TC, with its degradation proficiency minimally influenced by varying pH conditions.

Characterization of microbiome, resistome, mobilome, and virulome in anoxic and oxic wastewater treatment processes in Slovakia and Taiwan

This study presents a comprehensive analysis of samples from urban wastewater treatment plants using anoxic/oxic processes in Slovakia and Taiwan, focusing on microbiome, resistome, mobilome, and virulome, which were analyzed using a shotgun metagenomic approach. Distinct characteristics were observed; in Taiwan, a higher abundance and diversity of antibiotic resistance genes were found in both influent and effluent samples, while there was a higher prevalence of mobile genetic elements and virulence factor genes in Slovakia. Variations were noted in microbial community structures; influent samples in Taiwan were reflected from fecal and hospital sources, and those in Slovakia were derived from environmental elements. At the genus level, the samples from Taiwan's sewage treatment plants were dominated by Cloacibacterium and Bacteroides, while Acinetobacter was predominant in samples from Slovakia. Despite similar antibiotic usage patterns, distinct wastewater characteristics and operational disparities influenced microbiome, resistome, mobilome, and virulome compositions, with limited reduction of most resistance genes by the studied anoxic/oxic processes. These findings underscore the importance of region-specific insights into microbial communities for understanding the dynamics of antimicrobial resistance and pathogenicity in urban wastewater treatment systems. Such insights may lay the groundwork for optimizing treatment processes and reducing the dissemination of antibiotic resistance and pathogenicity genes for safeguarding public health.

Sludge Recovery from Wastewater Treatment Plants: A Review of Current Practices and Tips

Sludge recovery from “wastewater treatment plants” (WWTP) is an important aspect of the wastewater treatment process as it allows for the reuse of valuable resources and the reduction of waste. In this review, we examine current practices and tips for sludge recovery from wastewater treatment plants. We first discuss the various types of sludge produced in the treatment process, including primary, secondary, and tertiary sludge, and their respective characteristics. We then review the different methods used for sludge recovery, including thickening, dewatering, drying, and their respective advantages/disadvantages, and provide tips for optimizing sludge recovery, including proper sludge management, optimization of treatment processes, and incorporation of energy-efficient technologies. In parallel, we present an overview of the production, operation and nutrient composition of these sludges. Overall, the aim of this study is to provide an overview of sludge recovery in wastewater treatment plants and to offer practical insights for improving the efficiency and sustainability of this important process as well as the valorization of this important raw material.

Optimized wastewater management utilizing multivariate statistical analysis: a case study of the Mascara wastewater treatment plant, Algeria.

Effective wastewater management is crucial in regions experiencing water scarcity and environmental stressors, such as pollution and climate change. Optimizing treatment processes is essential for achieving environmental sustainability. This study aims to highlight the importance of effective wastewater management strategies, particularly in regions facing water scarcity. Our objective was to identify key factors influencing the treatment process. Therefore, we evaluated associations between physicochemical parameters using multivariate statistical methods, including Principal Component Analysis (PCA) and Hierarchical Ascendant Classification (HAC). Our findings categorize the monthly water samples into three distinct groups based on levels of organic pollution: the first group (July, August, and September) is characterized by high oxygenation levels and significantly low organic pollution, indicating optimal system operation. The second group (April, October, November, and December) exhibits low oxygenation and low organic pollution, promoting sludge settling and pollutant reduction. The third group (January, February, March, May, and June) shows significantly high organic pollution and low oxygenation, which corresponds to unfavorable environmental conditions. Our study demonstrates the effectiveness of multivariate statistical methods in optimizing wastewater treatment processes, providing crucial insights for environmental sustainability and water resource management.

Study on the Aging Precipitation Behavior and Kinetics of Al-10.0Zn-3.0Mg-2.8Cu Alloy by Pre-Deformation Treatment.

In this paper, the effect of thermomechanical treatment process on the hardening behavior, grain microstructure, precipitated phase, and tensile mechanical properties of the new high-strength and high-ductility Al-10.0Zn-3.0Mg-2.8Cu alloy was studied, and the optimal thermomechanical treatment process was established. The strengthening and toughening mechanisms were revealed, which provided technical and theoretical guidance for the engineering application of this kind of high strength-ductility aluminum alloy. Al-10.0Zn-3.0Mg-2.8Cu alloy cylindrical parts with external longitudinal reinforcement were prepared by a composite extrusion deformation process (reciprocal upsetting + counter-extrusion) with a true strain up to 2.56, and the organizational evolution of the alloys during the extrusion deformation process and the influence of pre-stretching treatments on the subsequent aging precipitation behaviors and mechanical properties were investigated. The results show that firstly, the large plastic deformation promotes the fragmentation of coarse insoluble phases and the occurrence of dynamic recrystallization, which results in the elongation of the grains along the extrusion direction, and the volume fraction of recrystallization reaches 42.4%. Secondly, the kinetic study showed that the decrease in the activation energy of precipitation increased the nucleation sites, which further promoted the diffuse distribution of the second phase in the alloy and a higher number of nucleation sites, while limiting the coarsening of the precipitated phase. When the amount of pre-deformation was increased from 0% to 2%, the size of the matrix precipitated phase decreased from 5.11 μm to 4.1 μm, and when the amount of pre-deformation was increased from 2% to 7%, the coarsening of the matrix precipitated phase took place, and the size of the phase increased from 4.1 μm to 7.24 μm. The finalized heat treatment process for the deformation of the aluminum alloy tailframe was as follows: solution (475 °C/3 h) + 2% pre-stretching + aging (120 °C/24 h), at which the comprehensive performance of the alloy was optimized, with a tensile strength of 634.2 MPa, a yield strength of 571.0 MPa, and an elongation of 15.2%. The alloy was strengthened by both precipitation strengthening and dislocation strengthening. After 2% pre-stretching, the fracture surface starts to be dominated by dense tough nest structure, and most of them are small tough nests, and small and dense tough nests are the main reason for the increase in alloy toughness after 2% pre-stretching deformation.

The role of stabilization technology on the enhancement of corrosion resistance and corrosion mechanism for weathering steel

This study aims to form a protective rust layer for weathering steel (WS) via the stabilization technology for rust layer. The optimal treatment process of rust layer stabilization is determined by orthogonal test: NaF 0.25 g /L, tannic acid 0.75 g /L, SeO2 0.75 g /L, MgSO4 0.50 g /L, and the treatment time was 5 days. The role of stabilization technology on corrosion mechanism for WS was characterized by SEM, EDS, XPS and electrochemical testing. The results show the dry riverbed film can effectively block the intrusion of corrosive ions in the atmosphere and improves the stability of the rust layer. Meanwhile, it promotes the entry of oxygen which reacts with the internal corrosion product FeOOH, and promotes the transformation of unstable phase substances into stable phase substances to enhance the corrosion resistance.

The fate of various organic compounds including pharmaceuticals in the treatment of landfill leachate and anaerobic digestate using deammonification

Studies focusing on the fate of organic compounds specifically recalcitrant organics and pharmaceuticals in a deammonification plant are scarce. This study downscaled a full-scale deammonification plant, which was being operated with the same wastewater streams of this study and evaluated for the first time the fate of different fractions of organic compounds in deammonification process along with the removal of nitrogenous compounds. Organic compounds in the feed and effluent were analyzed and their changes in the deammonification process were characterized. The results demonstrate that deammonification achieved over 90% of ammonium removal. COD monitoring revealed that around 11% of COD was reduced during the process mainly due to aerobic COD degradation and heterotrophic denitrifying bacteria. Analysis of the organic fractions revealed that high molecular weight components (around 11 kDa) are susceptible to removal and their concentrations tend to decrease in the reactor. Concentrations of humic substances, specifically fulvic acid-like substances, were reduced. Tracking nine different pharmaceutical residues revealed that morphine and cotinine were completely removed, while pregabalin and oxazepam which are known to be highly recalcitrant were more than 60% removed. The research finding can help in optimizing treatment processes by revealing the fate of different organic compounds, especially pharmaceuticals, within the deammonification process, thereby contributing to better effluent quality, regulatory compliance, and environmental protection.

Failure analysis and heat treatment process optimization of NOS525 rotary flat binaural hot forging die

A NOS525 steel rotary flat binaural hot forging die frequently failed too early due to collapse and wear in service. In this paper, the rotating planar binaural failure die was taken as the research object. Firstly, the sample design and sample processing of the failure die with different depths and directions were carried out. The material composition, hardness and metallographic structure of the samples were analyzed, and the tensile and impact properties were tested by direct-reading spectrometer, Rockwell hardness tester, optical microscope, scanning electron microscope, MTS testing machine and impact testing machine, etc. Meanwhile, with the help of Deform-HT software and JMatPro software, the coupling simulation of hardness, temperature and structure of the heat treatment of NOS525 steel was realized, and the hardness change of the material after heat treatment was predicted and verified by heat treatment test. The research results show that the composition of the die material is abnormal, especially the excessive P and C elements, at the same time, there is a phenomenon of quenching overheating and insufficient tempering, resulting in insufficient strength, toughness and hardness of the die material, in addition, the die surface is subjected to the cold and hot alternating load, and finally, the die surface collapses and wear too soon, resulting in its failure. Through the combination of heat treatment simulation optimization and test, the optimal heat treatment temperature of NOS525 steel was finally determined, that is, the quenching temperature of 1090℃, the first tempering temperature of 560℃, the second tempering temperature of 600℃, the third tempering temperature of 600℃, so that the mechanical properties of the material have been significantly improved.

Customized heat treatment process enabled excellent mechanical properties in wire arc additively manufactured Mg-RE-Zn-Zr alloys

Customized heat treatment is essential for enhancing the mechanical properties of additively manufactured metallic materials, especially for alloys with complex phase constituents and heterogenous microstructure. However, the interrelated evolutions of different microstructure features make it difficult to establish optimal heat treatment processes. Herein, we proposed a method for customized heat treatment process exploration and establishment to overcome this challenge for such kind of alloys, and a wire arc additively manufactured (WAAM) Mg-Gd-Y-Zn-Zr alloy with layered heterostructure was used for feasibility verification. Through this method, the optimal microstructures (fine grain, controllable amount of long period stacking ordered (LPSO) structure and nano-scale β′ precipitates) and the corresponding customized heat treatment processes (520 °C/30 min + 200 °C/48 h) were obtained to achieve a good combination of a high strength of 364 MPa and a considerable elongation of 6.2%, which surpassed those of other state-of-the-art WAAM-processed Mg alloys. Furthermore, we evidenced that the favorable effect of the undeformed LPSO structures on the mechanical properties was emphasized only when the nano-scale β′ precipitates were present. It is believed that the findings promote the application of magnesium alloy workpieces and help to establish customized heat treatment processes for additively manufactured materials.

Hybrid peroxymonosulfate/activated carbon fiber-sequencing batch reactor system for efficient treatment of coking wastewater: Establishment and influential factors

Coking wastewater contains high concentrations of toxic and low biodegradable organics, causing long hydraulic retention times for its biological treatment process. This study developed a pretreatment method for coking wastewater by using activated carbon fiber (ACF) activated peroxymonosulfate (PMS) to improve the treatment performance of subsequent biological post-treatment process, sequencing batch reactor (SBR). The results showed that, after optimization of treatment processes, the removal efficiency of chemical oxygen demand (COD), phenol, and chroma in coking wastewater reached to 76, 98, and 98%, respectively, with a significantly improved biodegradability. Compared with the sole SBR system without any pretreatment that could remove 73% of COD, the ACF/PMS+SBR system removed over 97% of COD in coking wastewater. Moreover, this pretreatment method facilitated the growth of functional bacteria for organics biodegradation, indicating its high potential as a highly efficacious pretreatment strategy to improve the overall treatment efficiency of coking wastewater.

Highly efficient removal of contaminant from typical dye wastewater by using individual AOPs-A/O processes: Design, performance, and mechanism

The individual process design suitable for different types of dye wastewater is less reported, and the performance and mechanism of advanced oxidation processes (AOPs)–anaerobic/aerobic (AOPs-A/O) is also unclear. In this experiment, different processes were designed to treat three typical dyes, namely, Disperse Blue (DB), Indigo Blue (IB), and Reactive Red (RR). Their performance and mechanism were studied. Results showed that sodium persulphate oxidation (SPO)/Fenton oxidation (FO) coupling treatment was the optimal treatment process for DB and IB wastewater, and SPO/ozone oxidation (OO) coupling treatment was the optimal treatment process for RR wastewater. After individual AOPs-A/O, the total chemical oxygen demand (COD) removal efficiency (CODre) of DB, IB, and RR were 96.25%, 96.35%, and 96.73%, respectively, and the overall mineralisation efficiency (ME) was 67.04%, 85.97%, and 72.24%, respectively. The contribution efficiency of the three treatment units to wastewater decreased as follows: AOPs > anoxic > aerobic. The initial B/C (B/C is the ratio of BOD to COD, which can indicate the biodegradability of wastewater) of DB, IB, and RR was 0.064, 0.065, and 0.262, respectively. The effluent B/C of DB, IB, and RR increased to 0.292, 0.392, and 0.795, respectively. Sequencing results showed that at the phylum level, its dominant group changed from Proteobacteria to Firmicutes. At the class level, its dominant group changed from Gammaproteobacteria to Clostridia.

Planning a Sewage Treatment System for Smart Housing Societies: A Review

Smart housing societies are increasingly incorporating sustainable practices, including on-site sewage treatment. This paper reviews key considerations for planning a sewage treatment system in such communities. Factors like resident population, water usage patterns, and available space are analyzed. Different treatment technologies, including activated sludge, constructed wetlands, and membrane bioreactors, are evaluated for their suitability in smart housing contexts. The integration of smart monitoring and control systems for optimizing treatment processes and water reuse is discussed. Finally, the importance of adhering to local regulations and involving residents in the planning process is highlighted.

Study on the High Temperature Heat Treatment Process Optimization of Different Sizes High Jc Nb$_{\text{3}}$Sn Wire Produced by WST

Study on the High Temperature Heat Treatment Process Optimization of Different Sizes High Jc Nb$_{\text{3}}$Sn Wire Produced by WST

Mechanical Behavior and Shape‐Memory Effects of NixTi1−x Alloys with Tunable Mixing of Ni/Ti Powders by Laser‐Directed Energy Deposition

As it is known, controlling NiTi alloy's microstructure is an urgent problem in additive manufacturing, which directly affects the mechanical properties of the alloy. In laser‐directed energy deposition (LDED) technology, the simultaneous powder feeding equipment with double powder barrels can effectively control the material ratio and realize the generation of NixTi1−x alloys with different atomic ratios. First, the performance differences of NiTi alloy under different thermal treatments are explored. Based on this, the optimal thermal treatment process is used to adjust the microstructure of NiTi alloy fabricated by LDED by changing the Ni/Ti atomic ratio to improve mechanical properties. The results indicate that Ni4Ti3 precipitates can induce the R phase, change the phase transition, and improve the mechanical properties in Ni‐rich NiTi alloys. Besides, the mechanical properties of NixTi1−x alloy can be enhanced by adjusting the Ni/Ti atomic ratio to change the content of Ni4Ti3 precipitates. Ni52Ti48 alloy has a tensile strength of 771 MPa, an elongation of 11.6%, and a recovery rate of 95.2%.

Advancing wastewater treatment technologies: The role of chemical engineering simulations in environmental sustainability

Wastewater treatment stands as a critical component in mitigating environmental pollution and safeguarding public health. This review delves into the pivotal role of chemical engineering simulations in advancing wastewater treatment technologies towards enhanced environmental sustainability. The modernization of wastewater treatment processes necessitates a comprehensive understanding of the complex physical, chemical, and biological interactions involved. Chemical engineering simulations offer a powerful toolset for modeling and optimizing these processes with a focus on efficiency, effectiveness, and sustainability. Firstly, simulations enable the prediction and analysis of pollutant removal mechanisms within treatment systems. By simulating various operating conditions and configurations, engineers can optimize treatment processes to achieve higher removal efficiencies while minimizing resource consumption and waste generation. Secondly, simulations aid in the design and development of innovative treatment technologies, such as membrane filtration, advanced oxidation processes, and biological nutrient removal systems. Through computational modeling, engineers can assess the performance and feasibility of these technologies under different scenarios, facilitating informed decision-making and accelerating their implementation. Furthermore, chemical engineering simulations play a crucial role in addressing emerging challenges in wastewater treatment, including the removal of emerging contaminants such as pharmaceuticals, microplastics, and endocrine-disrupting chemicals. By simulating the behavior of these contaminants within treatment systems, engineers can devise targeted strategies for their removal, thus mitigating their adverse environmental and public health impacts. Chemical engineering simulations serve as indispensable tools for advancing wastewater treatment technologies towards greater environmental sustainability. By facilitating the optimization, design, and innovation of treatment processes, simulations contribute to the development of more efficient, cost-effective, and environmentally friendly solutions for managing wastewater and protecting our ecosystems. Embracing these simulation-driven approaches is essential for achieving the ambitious goals of sustainable development and ensuring a cleaner, healthier future for generations to come.

Comprehensive carbon footprint analysis of wastewater treatment: A case study of modified cyclic activated sludge technology for low carbon source urban wastewater treatment

To reduce pollution and carbon emissions, a quantitative evaluation of the carbon footprint of the wastewater treatment processes is crucial. However, micro carbon element flow analysis is rarely focused considering treatment efficiency of different technology. In this research, a comprehensive carbon footprint analysis is established under the micro carbon element flow analysis and macro carbon footprint analysis based on life cycle assessment (LCA). Three wastewater treatment processes (i.e., anaerobic anoxic oxic, A2O; cyclic activated sludge technology, CAST; modified cyclic activated sludge technology, M-CAST) for low carbon source urban wastewater are selected. The micro key element flow analysis illustrated that carbon source mainly flows to the assimilation function to promote microorganism growth. The carbon footprint analysis illustrated that M-CAST as the optimal wastewater treatment process had the lowest global warming potential (GWP). The key to reduce carbon emissions is to limit electricity consumption in wastewater treatment processes. Under the comprehensive carbon footprint analysis, M-CAST has the lowest environmental impact with low carbon emissions. The sensitivity analysis results revealed that biotreatment section variables considerably reduced the environmental impact on the LCA and the GWP, followed by the sludge disposal section. With this research, the optimization scheme can guide wastewater treatment plants to optimize relevant treatment sections and reduce pollution and carbon emissions.