Hasil untuk "Sewage collection and disposal systems. Sewerage"

SUN Zhuoran, CAI Yu, SONG Qian et al.

【目的】饮用水在氯消毒过程中生成一系列的氯化消毒副产物(Cl-DBPs),带来了潜在的环境和健康风险，本文综述了致人体健康危害的饮用水Cl-DBPs流行病学调查研究进展，并进行总结与展望，从而为饮用水质量管理与公共卫生保障提供科学依据。【方法】文章以Cl-DBPs与人体膀胱癌、结直肠癌等恶性肿瘤的关联性为切入点，结合生殖激素紊乱、不良妊娠结果及胎儿生长受限等健康影响，总结分析了水质标准中重要的Cl-DBPs对人体健康危害的研究进展，结合我国饮用水新国标中相关限值的制定与修订背景，探讨其健康效应的关联性与可能机制，以期为促进饮用水质量管理与保障人民群众的身体健康提供参考。【结果】长期暴露于饮用水中Cl-DBPs与多种健康结果存在统计学关联。如对膀胱癌、结直肠癌、生殖健康方面、胎儿生长发育等方面存在着重大影响。在未来的研究中，开展饮用水中Cl-DBPs的全球系统性调查，可揭示Cl-DBPs的全球分布规律及其驱动因素，从而科学识别高风险区域与易感人群，提高饮用水质量。【结论】Cl-DBPs对人体健康存在多系统潜在危害，尤其在致癌与生殖发育方面值得高度关注。我国《生活饮用水卫生标准》(GB 5749—2022)加强了对Cl-DBPs的管控，未来需进一步开展全球系统性调查、内暴露评估及多途径暴露研究，以更准确评估其健康风险。

Marios Impraimakis, Feiyu Zhou, Andrew Plummer

The system identification capabilities of a novel information-theoretic method are examined here. Specifically, this work uses information-theoretic metrics and vibration-based measurements to enhance damping estimation accuracy in mechanical systems. The method refers to a key limitation in system identification, signal processing, monitoring, and alert systems. These systems integrate various components, including sensors, data acquisition devices, and alert mechanisms. They are designed to operate in an environment to calculate key parameters such as peak accelerations and duration of high acceleration values. The current operational modal identification methods, though, suffer from limitations related to obtaining poor damping estimates due to their empirical nature. This has a significant impact on alert warning systems. This occurs when their duration is misestimated; specifically, when using the vibration amplitudes as an indicator of danger alerts for monitoring systems in damage or anomaly detection scenarios. To this end, approaches based on the Shannon entropy and the Kullback-Leibler divergence concept are proposed. The primary objective is to monitor the vibration levels in near real-time and provide immediate alerts when predefined thresholds are exceeded. In considering the proposed approach, both new real-world data from the multi-axis simulation table at the University of Bath, as well as the benchmark International Association for Structural Control-American Society of Civil Engineers (IASC-ASCE) structural health monitoring problem are considered. Importantly, the approach is shown to select the optimal model, which accurately captures the correct alert duration, providing a powerful tool for system identification and monitoring.

Nicholas A. Pearson, Francesca Cairoli, Luca Bortolussi et al.

We introduce a novel deep learning approach that harnesses the power of generative artificial intelligence to enhance the accuracy of contextual forecasting in sewerage systems. By developing a diffusion-based model that processes multivariate time series data, our system excels at capturing complex correlations across diverse environmental signals, enabling robust predictions even during extreme weather events. To strengthen the model's reliability, we further calibrate its predictions with a conformal inference technique, tailored for probabilistic time series data, ensuring that the resulting prediction intervals are statistically reliable and cover the true target values with a desired confidence level. Our empirical tests on real sewerage system data confirm the model's exceptional capability to deliver reliable contextual predictions, maintaining accuracy even under severe weather conditions.

Sungjun Seo, Kooktae Lee

This paper addresses the fundamental problem of non-uniform area coverage in multi-agent systems, where different regions require varying levels of attention due to mission-dependent priorities. Existing uniform coverage strategies are insufficient for realistic applications, and many non-uniform approaches either lack optimality guarantees or fail to incorporate crucial real-world constraints such as agent dynamics, limited operation time, the number of agents, and decentralized execution. To resolve these limitations, we propose a novel framework called Density-Driven Optimal Control (D2OC). The central idea of D2OC is the integration of optimal transport theory with multi-agent coverage control, enabling each agent to continuously adjust its trajectory to match a mission-specific reference density map. The proposed formulation establishes optimality by solving a constrained optimization problem that explicitly incorporates physical and operational constraints. The resulting control input is analytically derived from the Lagrangian of the objective function, yielding closed-form optimal solutions for linear systems and a generalizable structure for nonlinear systems. Furthermore, a decentralized data-sharing mechanism is developed to coordinate agents without reliance on global information. Comprehensive simulation studies demonstrate that D2OC achieves significantly improved non-uniform area coverage performance compared to existing methods, while maintaining scalability and decentralized implementability.

Seyed Pedram Jazayeri Farsani, Ramtin Moeini

Pressure and residual chlorine concentration are among the key parameters in urban water distribution networks that require continuous monitoring and control. These networks must ensure that consumer water demands are met with adequate pressure while optimizing water quality parameters, such as residual chlorine concentration, to maximize service satisfaction. In this study, the Najaf Abad urban water distribution network was selected as a real large-scale case study. A simultaneous optimization model was developed to determine nodal average pressure, residual chlorine concentration, and network combined reliability. The multi-objective optimization problem was solved using the NSGA-II algorithm under two extreme water consumption scenarios-maximum and minimum water withdrawal during warm and cold seasons. A Pressure-Driven Analysis approach was employed to calculate network parameters. Additionally, three objective functions were optimized using the NSGA-II multi-objective optimization algorithm. The optimal solution was selected from the Pareto front using the TOPSIS method. The network under study includes four operational pressure-reducing valves; after determining their optimal set pressure values, the average network pressure was reduced by 2.9% during ward days and 13.5% during cold days. The average residual chlorine concentration did not undergo significant changes however, its further reduction was prevented through optimization, effectively achieving this objective as well. Lastly, the combined reliability increased by 1.7% and 1.3% for warm and cold days, respectively.

Sunyu Wang, Yutong Xia, Huanfa Chen et al.

Designing a cost-effective sensor placement plan for sewage surveillance is a crucial task because it allows cost-effective early pandemic outbreak detection as supplementation for individual testing. However, this problem is computationally challenging to solve, especially for massive sewage networks having complicated topologies. In this paper, we formulate this problem as a multi-objective optimization problem to consider the conflicting objectives and put forward a novel evolutionary greedy algorithm (EG) to enable efficient and effective optimization for large-scale directed networks. The proposed model is evaluated on both small-scale synthetic networks and a large-scale, real-world sewage network in Hong Kong. The experiments on small-scale synthetic networks demonstrate a consistent efficiency improvement with reasonable optimization performance and the real-world application shows that our method is effective in generating optimal sensor placement plans to guide policy-making.

Max H. Cohen, Ryan K. Cosner, Aaron D. Ames

Certifying the safety of nonlinear systems, through the lens of set invariance and control barrier functions (CBFs), offers a powerful method for controller synthesis, provided a CBF can be constructed. This paper draws connections between partial feedback linearization and CBF synthesis. We illustrate that when a control affine system is input-output linearizable with respect to a smooth output function, then, under mild regularity conditions, one may extend any safety constraint defined on the output to a CBF for the full-order dynamics. These more general results are specialized to robotic systems where the conditions required to synthesize CBFs simplify. The CBFs constructed from our approach are applied and verified in simulation and hardware experiments on a quadrotor.

Jillian Maxcy-Brown, Mark A. Elliott, Bennett Bearden

Country-level sanitation access is monitored globally by the Joint Monitoring Programme (JMP). However, recent reports on sanitation access in high-income countries indicate that the JMP data may underestimate the prevalence of unsafely managed sanitation in these settings. This study explains the surveys that collect household-level wastewater management data in the U.S. and analyzes the accuracy and reliability of these data sets. From 1940 to 1990, sewage disposal data were collected comprehensively through the U.S. Decennial Census. These data are currently collected through the American Housing Survey (AHS) which appears to greatly underestimate the usage of onsite wastewater treatment systems (OWTS). In addition to these surveys, we highlight current efforts to introduce a sewage disposal question to the American Community Survey (ACS), localized efforts to collect wastewater data, and the Point-in-Time count of people experiencing homelessness. Using estimates of OWTS usage in new housing, this study provides the first defensible national estimate of OWTS usage since 1990. We estimate that 25.03% of U.S. households use OWTS which exceeds the AHS estimate (15.7%) by over 12 million households. This study discusses the potential for better wastewater data collection to inform future wastewater policy and improve the quality of life for U.S. residents.

Mohsen Esamaeilpour, Majid Ghahraman Afshar, Morteza Faghihi et al.

Lack of water is considered the most important threat to the survival of human beings and natural ecosystems. Food and energy security, health and industrial progress, which are the main components of the sustainable development of societies, depend on water more than anything else. Water consumption in Loshan power plant is 2600 L/MWh raw water, which is very high compared to the production capacity and is due to having a tower in its cooling system. Considering the high volume of water consumed in this power plant compared to the production efficiency and on the other hand, reducing the amount of rainfall and droughts that have occurred, it is necessary to provide a solution to modify the consumption pattern for this power plant. Considering the special position of this power plant, solutions to modify the water consumption pattern by recycling clean drains (blow down of boilers, back wash of sand filters and water sampling), purification and recycling the blow down of cooling towers into the water cycle and optimization of cooling towers (replacing drippers, replacing nozzles and optimizing water distribution to increase efficiency, using a rotating nozzle to increase the time and speed of the water droplets hitting the air in order to transfer more heat) are suggested. According to the experimental data, the conductivity of boiler blowdown is about 10 μs/cm and the expenses of recycling the blowdown of boiler by using heat exchanger is estimated about 324.425.000 Rials.

Chaozhong Xue, Yongqi Dong, Jiaqi Liu et al.

With social progress and the development of modern medical technology, the amount of medical waste generated is increasing dramatically. The problem of medical waste recycling and treatment has gradually drawn concerns from the whole society. The sudden outbreak of the COVID-19 epidemic further brought new challenges. To tackle the challenges, this study proposes a reverse logistics system architecture with three modules, i.e., medical waste classification & monitoring module, temporary storage & disposal site (disposal site for short) selection module, as well as route optimization module. This overall solution design won the Grand Prize of the "YUNFENG CUP" China National Contest on Green Supply and Reverse Logistics Design ranking 1st. This paper focuses on the description of architectural design and the module on site selection. Specifically, regarding system architecture, a framework diagram is provided, together with brief descriptions of the three proposed modules and a case study under the COVID-19 epidemic with the customized model. Regarding the disposal site selection module, a multi-objective optimization model is developed, and considering different types of waste collection sites (i.e., prioritized large collection sites and common collection sites), a hierarchical solution method is developed employing linear programming and K-means clustering algorithms sequentially. The proposed site selection method is verified with a case study using real-world data, and compared with the baseline, it can immensely reduce the daily operational costs and working time. Limited by length, detailed descriptions of the whole system as well as the remaining medical waste classification & monitoring module and route optimization module can be found at https://shorturl.at/cdY59.

Xucheng Liu, Lindong Liu, Yifu Li et al.

Players cooperating in a line is a special while essential phenomenon in real life collaborating activities such as assembly line production, pipeline supply chain management and other streamlining operational settings. In this paper, we study the scenario of cooperative sewage discharge with multiple participants positioning in a line along a river such that the optimization decision and cooperation strategy are mutually affected by both upstream and downstream players. We make three main contributions accordingly: Firstly, we formalize the sewage discharge problem (SDP) for different groups of players, and use greedy strategy and dynamic programming to design the optimal algorithms to solve the SDP in polynomial time. Secondly, we show that the cooperative game defined on sewage discharge problem, referred to as SDG, has a non-empty core due to its special line-positioning structure. Therefore, a grand stable cooperation is guaranteed. Furthermore, inspired by the fact that the SDG is core non-empty while non-convex, we successfully identify a relaxed concept of convexity -- directional-convexity, which can also serve as a sufficient condition for a cooperative game having a non-empty core.

Hossein Daneshmehr, Osman Hedayat

Current study seeks to present a narrative of the residents of the suburbs of Sanandaj on the provision of services and urban facilities. This was in contrast to the narratives of the Water and Wastewater Company's experts and statistics, documentation and information were posted on the company's website. The underlying assumption of this study revolves around the fact that suburbs lack adequate facilities and services and have been neglected. To this end, we have used sustainable urban development approaches, urban regeneration and quality of life to explain and change this. With regard to the subject and purpose of the study, we used the institutional ethnographic method by which the researcher seeks to expose the status quo and then provide strategies for changing the status quo. Therefore, data were gathered through theoretical, purposeful sampling with maximum diversity and semi-structured interviews until theoretical saturation with 20 subscribers and 7 experts of Kurdistan Water and Wastewater Company, as well as statistics and relevant documents were collected. The information collected was discussed in terms of concepts, primary and secondary categories. Primary categories were conflicting secondary services, quality of technical management, poor technical management, lack of coordination of events, lack of inter-organizational collaboration, inappropriate network infrastructure, and lack of customer-centricity, uncertainties, and overheads. They were drawn and extracted from these categories; the nuclear category of structural and institutional exclusion and the lack of coordination in the implementation and ambiguities of the bill. The results indicate a lack of sustainable urban development in the marginal areas and consequently a decline in the quality of life. This is reflected in the structural and institutional challenges faced by the suburbs in terms of their utilization of urban facilities. The lack of coordination in the implementation and ambiguities of the water and wastewater company has aggravated the process and caused underdevelopment issues. Therefore, what is needed on the outskirts of Sanandaj is the re-creation of a city that is making changes to the development of water and wastewater network infrastructure, maintaining and protecting the network, and transparency in customer billing and promotion, which is the quantity and quality of service provided in these areas.

Ebrahim Yazdian, musa ahmadi, mahmood noraei

This study presents a conceptual model with regard to the fundamental role of economic attitude towards water industry as one of the key aspects of the development of internal marketing in the water and wastewater industry. In this study, Interpretive Structural Analysis (ISM) method was used to collect data, interview, design conceptual model and gather data. The results show that according to the conceptual model presented in this study, the economic attitude towards the water industry with high penetration power is recognized as the most fundamental and influential aspect of the development of internal marketing. According to the linkage analysis method, especially the dimension of economic attitude to water industry, infiltration power - dependency is one of the most important aspects of development of internal marketing. In this respect, drafting of outsourcing regulation to improve the performance of water and wastewater industry is necessary.

Khoi Khac Nguyen, Trung Q. Duong, Tan Do-Duy et al.

Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the network performance and coverage in wireless communication. However, due to the limitation of their on-board power and flight time, it is challenging to obtain an optimal resource allocation scheme for the UAV-assisted Internet of Things (IoT). In this paper, we design a new UAV-assisted IoT systems relying on the shortest flight path of the UAVs while maximising the amount of data collected from IoT devices. Then, a deep reinforcement learning-based technique is conceived for finding the optimal trajectory and throughput in a specific coverage area. After training, the UAV has the ability to autonomously collect all the data from user nodes at a significant total sum-rate improvement while minimising the associated resources used. Numerical results are provided to highlight how our techniques strike a balance between the throughput attained, trajectory, and the time spent. More explicitly, we characterise the attainable performance in terms of the UAV trajectory, the expected reward and the total sum-rate.

Lam Duc Nguyen, Amari N. Lewis, Israel Leyva-Mayorga et al.

Urban areas are negatively impacted by Carbon Dioxide (CO2 ) and Nitrogen Oxide (NOx) emissions. In order to achieve a cost-effective reduction of greenhouse gas emissions and to combat climate change, the European Union (EU) introduced an Emissions Trading System (ETS) where organizations can buy or receive emission allowances as needed. The current ETS is a centralized one, consisting of a set of complex rules. It is currently administered at the organizational level and is used for fixed-point sources of pollution such as factories, power plants, and refineries. However, the current ETS cannot efficiently cope with vehicle mobility, even though vehicles are one of the primary sources of CO2 and NOx emissions. In this study, we propose a new distributed Blockchain-based emissions allowance trading system called B-ETS. This system enables transparent and trustworthy data exchange as well as trading of allowances among vehicles, relying on vehicle-to-vehicle communication. In addition, we introduce an economic incentive-based mechanism that appeals to individual drivers and leads them to modify their driving behavior in order to reduce emissions. The efficiency of the proposed system is studied through extensive simulations, showing how increased vehicle connectivity can lead to a reduction of the emissions generated from those vehicles. We demonstrate that our method can be used for full life-cycle monitoring and fuel economy reporting. This leads us to conjecture that the proposed system could lead to important behavioral changes among the drivers

Patryk Grelewicz, Thanh Tung Khuat, Jacek Czeczot et al.

In this paper, a novel machine learning derived control performance assessment (CPA) classification system is proposed. It is dedicated for a wide class of PID-based control industrial loops with processes exhibiting dynamical properties close to second order plus delay time (SOPDT). The proposed concept is very general and easy to configure to distinguish between acceptable and poor closed loop performance. This approach allows for determining the best (but also robust and practically achievable) closed loop performance based on very popular and intuitive closed loop quality factors. Training set can be automatically derived off-line using a number of different, diverse control performance indices (CPIs) used as discriminative features of the assessed control system. The proposed extended set of CPIs is discussed with comprehensive performance assessment of different machine learning based classification methods and practical application of the suggested solution. As a result, a general-purpose CPA system is derived that can be immediately applied in practice without any preliminary or additional learning stage during normal closed loop operation. It is verified by practical application to assess the control system for a laboratory heat exchange and distribution setup.

Shahla Elhami, Mehdi Sagha Kahvaz, Nadereh Rahbar

Wastewaters produced from various industries and their entry into surface water is one of the most important environmental problems that have harmful effects on aquatic life. Discharging phosphate from urban and industrial wastewater to the aquatic environment causes a lot of algae growth. The aim of this study was to evaluate the removal of phosphate from aqueous solutions using sepia endoskeleton (cuttlebone) powder as a natural biomass, cheap and non-toxic absorbent. This study was conducted in a batch system. Sepia endoskeleton was washed with distilled water. It was then dried at 80 °C and thoroughly powdered by milling. Physical and chemical properties of the adsorbent were determined using the Particle Sizer, atomic force microscopy, and infrared spectroscopy and X-ray fluorescence. The effects of variables affecting phosphate uptake, such as pH, adsorbent amount, contact time, initial concentration of phosphate and stirring rate were optimized. Also, the isotherm models (Langmuir, Freundlich, Tamkin and Dubbin-Radshkvich) and first-order and second-order kinetics models were used to evaluate the data. The results showed that the highest removal percentage was observed at pH 5, adsorbent content of 5 g/L and contact time of 10 min at initial phosphate concentration of 10 mg/L. Using sepia powder under optimal laboratory conditions, the phosphate ion with the concentration of 10 mg/L was removed with a yield of over 99%. The results indicated that the Freundlich isotherm model gives a better description than other models showing the adsorption of phosphate ions occurs in a heterogeneous surface. Using Langmuir model, the maximum absorption capacity for phosphate was 68.02 mg/g. The kinetic model of phosphate removal followed the pseudo-second-order model. Besides, the percentage of removal of the real samples was over 98%, indicating the great ability of this natural and inexpensive absorbent to remove this pollutant from the water solutions.

Maryam Izadpanah, Mohammad Hosein Sarrafzadeh

In recent years, excessive usage of surface and underground water resources has exerted great stress on Iran's water resources. A survey of water use trends in the past years and forecasts of water needs in the coming years, makes undesirable  perspective for the imbalance between water demand and resources in the near future. Planning for the exploration and use of unconventional water resources, such as gray water and sullage reuse, will greatly help to balance water shortage. In this research, sewage of swimming pools has been investigated because it is a type of urban sewage that has high technical, economic and environmental potential for implementation of urban sullage recycling project. A case study was carried out on 10 public swimming pools in Tehran to determine the volume and 7 pools for qualitative investigation on sewage of different parts of swimming pools. The results indicate that pools have a high quality and high volume wastewater that cause conceivable potential for recycling. For example, the average COD of the tested samples was 153 ppm and the maximum was 246 ppm, which is equivalent to organic load of weak urban wastewater. This wastewater also meets the standards of landscape irrigation in most of parameters, and in the other parameters such as organic load of some samples has a small variance from these standards, which could be met with a simple treatment unit like a depth filtration and an activated carbon. In addition, an average of 120 cubic meters of sullage per day is generated in each aquatic center complex, which is more than the production of gray water in a 700 people capacity residential complex. Reuse of this sullage, in addition to reducing transportation costs and load of centralized treatment plants, will reduce the pressure on water resources of our country by supplying water for non-potable purposes such as irrigation of landscaping.

Leonardo Colombo, Maria Emma Eyrea Irazu

Symmetries are ubiquitous in a wide range of nonlinear systems. Particularly in systems whose dynamics are determined by a Lagrangian or Hamiltonian function. For hybrid systems which possess a continuous-time dynamics determined by a Lagrangian function, with a cyclic variable, the degrees of freedom for the corresponding hybrid Lagrangian system can be reduced by means of a method known as \textit{hybrid Routhian reduction}. In this paper we study sufficient conditions for the existence of periodic orbits in hybrid Routhian systems which also exhibit time-reversal symmetry. Likewise, we explore some stability aspects of such orbits through the characterization of the eigenvalues for the corresponding linearized Poincaré map. Finally, we apply the results to find periodic solutions in underactuated hybrid Routhian control systems.

Ritam Guha, Anik Sengupta, Ankan Dutta

CoVID-19 is currently one of the biggest threats to mankind. To date, it is the reason for infections of over 35 lakhs and the death of over 2 lakh human beings. We propose a procedure to detect CoVID-19 affected localities using a sewage mass testing and pooling mechanism which has gained ground in recent times. The proposed method named Sewage Pooling Algorithm tests wastewater samples from sewage systems to pinpoint the regions which are affected by maximum chances of the virus spread. The algorithm also uses a priority-based backtracking procedure to perform testing in sewage links depending on the probability of infection in the sub-areas. For places with very rare CoVID cases, we present a gradient-based search method to prune those areas. The proposed method has less human intervention and increases the effective tests/million people over current in-place methods.