Hasil untuk "Sewage collection and disposal systems. Sewerage"

Wang Jian, Wang Chen, Wang Yanzhi et al.

【目的】随着全球淡水资源日益匮乏，海水淡化技术的重要性愈发凸显。然而，海水中较高浓度的硼元素给淡化过程带来挑战。研究表明：过量硼摄入会对人体健康产生毒性效应，并破坏生态系统平衡。而反渗透作为主流工艺，其单级脱硼效果不理想，需探究合适的方法和参数来达到更高效的脱硼效果。本文系统评述海水除硼技术的研究现状与发展趋势，旨在为海水资源的高效利用提供理论依据和技术参考。【方法】本文首先介绍了硼的基本性质及其在海水中的存在形式和对动植物的影响；继而重点评述了当前海水除硼的主流技术，包括反渗透技术、离子交换树脂法、电渗析技术和吸附法等，从作用机理、技术特点和研究进展3个维度进行系统比较分析。【结果】反渗透技术虽然已被广泛应用于海水淡化，但其脱硼效果高度依赖溶液pH且需多级处理能耗较高。离子交换树脂法能有效降低硼浓度，但存在树脂再生困难及成本较高等问题。电渗析技术具有出水水质稳定、操作简便等优点，但高能耗限制其推广应用。吸附法应用广泛，传统吸附剂对硼吸附能力有限，而新型有机-无机杂化吸附材料显示出良好的吸附性能，当前的研究重点在优化基体材料选择和杂化方法来提高吸附官能团负载量。【结论】综合分析表明：基于活性炭等传统吸附剂开发的新型有机-无机杂化吸附材料具有显著优势，不仅保留了基体材料成本低廉、比表面积大的特点，通过功能化改性更能实现选择性吸附能力和吸附容量的提升。本技术路线在海水除硼领域展现出广阔的应用前景，是未来研究的重要方向。

Mingxuan Li, Wei Wei, Yin Xu et al.

Extreme events such as earthquakes pose significant threats to integrated electricity-gas distribution systems (IEGDS) by causing widespread damage. Existing restoration approaches typically assume full awareness of damage, which may not be true if monitoring and communication infrastructures are impaired. In such circumstances, field inspection is necessary. This paper presents a novel adaptive restoration framework for IEGDS, considering dynamic damage assessment and repair. The restoration problem is formulated as a partially observable Markov decision process (POMDP), capturing the gradually revealed contingency and the evolving impact of field crew actions. To address the computational challenges of POMDPs in real-time applications, an advanced belief tree search (BTS) algorithm is introduced. This algorithm enables crew members to continuously update their actions based on evolving belief states, leveraging comprehensive simulations to evaluate potential future trajectories and identify optimal inspection and repair strategies. Based on the BTS algorithm, a unified real-time decision-making framework is developed for IEGDS restoration. Case studies on two distinct IEGDS systems demonstrate the effectiveness and scalability of the proposed method. The results indicate that the proposed approach achieves an outage cost comparable to the ideal solution, and reduces the total outage cost by more than 15% compared to strategies based on stochastic programming and heuristic methods.

Hossein B. Jond

Collective behaviors such as swarming and flocking emerge from simple, decentralized interactions in biological systems. Existing models, such as Vicsek and Cucker-Smale, lack collision avoidance, whereas the Olfati-Saber model imposes rigid formations, limiting their applicability in swarm robotics. To address these limitations, this paper proposes a minimal yet expressive model that governs agent dynamics using relative positions, velocities, and local density, modulated by two tunable parameters: the spatial offset and kinetic offset. The model achieves spatially flexible, collision-free behaviors that reflect naturalistic group dynamics. Furthermore, we extend the framework to cognitive autonomous systems, enabling energy-aware phase transitions between swarming and flocking through adaptive control parameter tuning. This cognitively inspired approach offers a robust foundation for real-world applications in multi-robot systems, particularly autonomous aerial swarms.

Qasim Khadim, Peter Manzl, Emil Kurvinen et al.

The precision, stability, and performance of lightweight high-strength steel structures in heavy machinery is affected by their highly nonlinear dynamics. This, in turn, makes control more difficult, simulation more computationally intensive, and achieving real-time autonomy, using standard approaches, impossible. Machine learning through data-driven, physics-informed and physics-inspired networks, however, promises more computationally efficient and accurate solutions to nonlinear dynamic problems. This study proposes a novel framework that has been developed to estimate real-time structural deflection in hydraulically actuated three-dimensional systems. It is based on SLIDE, a machine-learning-based method to estimate dynamic responses of mechanical systems subjected to forced excitations.~Further, an algorithm is introduced for the data acquisition from a hydraulically actuated system using randomized initial configurations and hydraulic pressures.~The new framework was tested on a hydraulically actuated flexible boom with various sensor combinations and lifting various payloads. The neural network was successfully trained in less time using standard parameters from PyTorch, ADAM optimizer, the various sensor inputs, and minimal output data. The SLIDE-trained neural network accelerated deflection estimation solutions by a factor of $10^7$ in reference to flexible multibody simulation batches and provided reasonable accuracy. These results support the studies goal of providing robust, real-time solutions for control, robotic manipulators, structural health monitoring, and automation problems.

H. Jahish, N. Mehrdadi, G. R. N. Bedhendi

L. K. Häfner

This essay conceives of Moscow’s water supply, sewage disposal, and a sewerage system as a field of tension between urbanization, industrialization, water pollution, hygiene, and health from the Late Imperial Russia, through the First World War, the Russian Revolution of 1917 and into the Civil War period. The article understands the allocation of water, especially in times of scarcity, as a question of political power and raises the following central questions: How did the people of Moscow quench their thirst? Where, when, how, to what extent and at what price was water made available? How and where was the used water disposed of and by what methods, if any, was it treated in order to avoid further water pollution?

Maria Belen Arévalo, D. Ballari, Andrés Alvarado

On-site sanitation systems such as septic tanks are widely used for treating domestic wastewater in urban and rural areas which lack sewage systems. However, a large portion of these systems do not properly treat human excreta. A main challenge to improve this is the absence of comprehensive data regarding the usage, emptying and maintenance. In this study, records of septic tank desludging frequency during 2009–2022 and the sewerage coverage updated to 2022 were used to investigate their spatial and temporal utilisation, and the persistence of septic tank usage in areas with sewer networks and uncover the current state of Faecal Sludge Management in Cuenca, Ecuador. The spatial behaviour revealed that OSSs are still in use besides the presence of a sewer network. In 2022, there were 109 septic tanks in urban areas with 14.7% in sectors with sewerage service. In rural areas, 469 septic tanks were recorded with 7.8% situated in areas with sewer networks. Although there is no specialised infrastructure in place for the treatment and disposal of faecal sludge, the city has effectively managed it with the existing sanitation facilities. This assessment contributes to the formulation of a secure framework for a safely managed sanitation.

Abbas Aghaeinejad Meybodi, Amanollah Ebadi, Amin Alamdari

Discharge of pharmaceutical wastewater into surface and underground water has harmful effects on human health and living organisms, even in low concentrations. For this reason, pharmaceutical wastewater treatment is very important. In this research, wastewater treatment of Aria Pharmaceutical's Fluoxetine production unit was studied using γ-alumina catalysts. The catalyst was synthesized using the co-precipitation method and characterized by XRD, FTIR, FESEM, EDX, and BET methods. In the synthesis of γ-alumina catalyst, aluminum nitrate was used as a precursor, and sodium carbonate was used as the precipitating agent. The central composite design method was used to design experiments and to model and optimize the wastewater treatment using catalytic ozonation. In addition, the effect of the operating parameters on the catalytic ozonation process of Fluoxetine-containing wastewater, including the inlet ozone concentration, the amount of the catalyst, and reaction time, were investigated. Based on the obtained results, a significant agreement was observed between the experimental data of COD removal for wastewater and the values predicted by the CCD method. The results of the Pareto analysis showed that among the studied operational parameters, the reaction time, the amount of catalyst, and the initial concentration of ozone are the most effective parameters on the COD removal with percentages of 35.58%, 34.64% and 10.87%, respectively. Finally, by optimizing the process, the maximum value of COD removal of 92.13% was obtained experimentally for pharmaceutical wastewater using catalytic ozonation process in the reaction time of 30 min, the amount of catalyst of 1 g/L and the ozone concentration of 30 mg/L as optimal conditions.

Maryam Daraee, Shima Khosravi, Ehsan Neshan Shahjooei et al.

Due to the expansion of industries and the increase in the volume of industrial wastewater, as well as the reduction of natural water resources and the water shortage crisis in human societies, adopting appropriate methods to remove pollutants and treat wastewater has become necessary. In this way, the high volume of industrial effluents can be optimized by recycling the water used to bring the pollutants to the standard level for various purposes such as washing factory equipment, watering green spaces and trees, etc. Among different methods such as membrane filtration, reverse osmosis, etc., the use of absorbents to remove pollutants can be effective in achieving the goal with optimal efficiency and low cost. Coagulants, both chemical and natural, are used to remove the blockage of the absorbent and reduce the need for their regeneration or replacement. This research aims to compare the performance of several different coagulants from different groups, along with zeolite adsorbent, to treat the central sewage effluent of Semnan Industrial Park. The role of this process in reducing COD, TSS and turbidity is also investigated. The obtained results show the optimal performance of polyammonium chloride with a reduction of 60% for COD, 85% for TSS and 85% for turbidity. Similarly, Moringa, as a natural absorbent, exhibits high removal efficiency, with a reduction of 70% for COD, 75% for TSS, and 80% for turbidity. The use of two chemical and natural methods will be very effective in reducing pollutants to the allowed amount depending on the type of wastewater.

Joseph Nyangon

Climate change significantly increases risks to power systems, exacerbating issues such as aging infrastructure, evolving regulations, cybersecurity threats, and fluctuating demand. This paper focuses on the utilization of Grid Enhancing Technologies (GETs) to strengthen power system resilience in the face of extreme weather events. GETs are pivotal in optimizing energy distribution, enabling predictive maintenance, ensuring reliable electricity supply, facilitating renewable energy integration, and automating responses to power instabilities and outages. Drawing insights from resilience theory, the paper reviews recent grid resilience literature, highlighting increasing vulnerabilities due to severe weather events. It demonstrates how GETs are crucial in optimizing smart grid operations, thereby not only mitigating climate-related impacts but also promoting industrial transformation. Keywords: Climate change, power systems, grid enhancing technologies (GETs), power system resilience, extreme weather

A. U. Alka, U. A. Abubakar, S. B. Igboro

Sanitation is a basic human requirement with the primary aim of separating human waste from settlements to prevent the spread of diseases. This study presents a preliminary design of a centralized sewerage collection, transportation, treatment, and final disposal system for the Nigerian College of Aviation Technology (NCAT) Zaria, Kaduna State (Site 1). The results of physico-chemical analysis of samples showed concentrations of Nitrates (2,550mg/l) and total suspended solids T.S.S. (1,778mg/l) were above the acceptable standard limits. The concentrations of Zinc (5.31mg/l) and Lead (2.78mg/l) were also above the acceptable limits. A sewerage system which comprised of 18 manholes, 22 junction chambers and 39 sewers covering a distance of 2,816m was designed for the college. The results of the design showed that 3 facultative and 3 maturation ponds were required. The capital cost for implementing the proposed sewerage system and WSPs for the college was determined to be ₦14,649,855.75 with an annual cost of operation and maintenance of ₦3,030,000.00. A comparison of the proposed sewerage and WSPs system with the existing septic tank and soak-away system revealed that the proposed sewerage and WSPs system had a higher cost-benefit ratio (0.94), longer lifespan (30 years), lower cost of annual desludging (₦30,000.00), and lower risks of groundwater contamination.

Joana Wensing, R. Cremades, Eveline S. van Leeuwen

M. Alresheedi, Husnain Haider, Abdulmohsen M. Albuaymi et al.

Small communities and most rural settlements in the Kingdom of Saudi Arabia (KSA) store domestic wastewater in residential septic tanks and transport it to the nearest centralized wastewater treatment plant. Without a sanitary sewerage system, the residents encounter various socioeconomic and environmental challenges related to sewage collection vehicles, the production of objectionable gases, and leaking septic tanks. The present study developed a resident perception-based methodology to appraise the sustainability of a low-cost ceramic filter bioreactor-type decentralized wastewater treatment system (DWWTS) for a small community of 1300 residents (160 households) in Qassim (KSA). In addition to six demographic factors, nine indicators assessed residents’ perceptions about existing and proposed wastewater management systems. A hierarchical-based system of sub-indices evaluated the three dimensions of sustainability using four environmental, nine social, and three economic indicators. The indicators translated into dichotomous questions posed to 34 respondents in the study area. The statistical analysis assessed the association of responses with the willingness to accept (WTA) the proposed DWWTS. A subjective rating scheme translated the responses into performance scores, and a fuzzy-based method aggregated the scores into sub- and top-level indices. The top of the hierarchy showed a close agreement between the resident’s perception and DWWTS’ sustainability. The study found that residents’ knowledge about environment and resource conservation resulted in a moderately high willingness to reuse treated effluent and WTA the decentralized system. The study also showed that the economic viability of a DWWTS remained at a moderate performance level due to a low monthly waste disposal cost. The study’s findings present a high potential for sustainable community-maintained DWWTS initially supported by the government. The proposed approach facilitates decision-makers working in ministries concerning water resources, environmental protection, and agricultural production in evaluating the sustainability of DWWTS for small communities in arid regions.

Zijian Feng, Xin Chen, Zijian Lv et al.

Deep learning (DL) algorithms have been widely applied to short-term voltage stability (STVS) assessment in power systems. However, transferring the knowledge learned in one power grid to other power grids with topology changes is still a challenging task. This paper proposed a transferable DL-based model for STVS assessment by constructing the topology-aware voltage dynamic features from raw PMU data. Since the reactive power flow and grid topology are essential to voltage stability, the topology-aware and physics-informed voltage dynamic features are utilized to effectively represent the topological and temporal patterns from post-disturbance system dynamic trajectories. The proposed DL-based STVS assessment model is tested under random operating conditions on the New England 39-bus system. It has 99.99\% classification accuracy of the short-term voltage stability status using the topology-aware and physics-informed voltage dynamic features. In addition to high accuracy, the experiments show good adaptability to PMU errors. Moreover, The proposed STVS assessment method has outstanding performance on new grid topologies after fine-tuning. In particular, the highest accuracy reaches 99.68\% in evaluation, which demonstrates a good knowledge transfer ability of the proposed model for power grid topology change.

Seunghee Koh, Hyounguk Shon, Janghyeon Lee et al.

Transfer learning is widely used for training deep neural networks (DNN) for building a powerful representation. Even after the pre-trained model is adapted for the target task, the representation performance of the feature extractor is retained to some extent. As the performance of the pre-trained model can be considered the private property of the owner, it is natural to seek the exclusive right of the generalized performance of the pre-trained weight. To address this issue, we suggest a new paradigm of transfer learning called disposable transfer learning (DTL), which disposes of only the source task without degrading the performance of the target task. To achieve knowledge disposal, we propose a novel loss named Gradient Collision loss (GC loss). GC loss selectively unlearns the source knowledge by leading the gradient vectors of mini-batches in different directions. Whether the model successfully unlearns the source task is measured by piggyback learning accuracy (PL accuracy). PL accuracy estimates the vulnerability of knowledge leakage by retraining the scrubbed model on a subset of source data or new downstream data. We demonstrate that GC loss is an effective approach to the DTL problem by showing that the model trained with GC loss retains the performance on the target task with a significantly reduced PL accuracy.

Michael Crosscombe, Jonathan Lawry

The design of distributed autonomous systems often omits consideration of the underlying network dynamics. Recent works in multi-agent systems and swarm robotics alike have highlighted the impact that the interactions between agents have on the collective behaviours exhibited by the system. In this paper, we seek to highlight the role that the underlying interaction network plays in determining the performance of the collective behaviour of a system, comparing its impact with that of the physical network. We contextualise this by defining a collective learning problem in which agents must reach a consensus about their environment in the presence of noisy information. We show that the physical connectivity of the agents plays a less important role than when an interaction network of limited connectivity is imposed on the system to constrain agent communication. Constraining agent interactions in this way drastically improves the performance of the system in a collective learning context. Additionally, we provide further evidence for the idea that `less is more' when it comes to propagating information in distributed autonomous systems for the purpose of collective learning.

Mohammad Jamalinezhad, Amirhesam Hasani, Seyd Mehdii Borghei et al.

The aim of this study is the pilot performance evaluation and comparison of wastewater disinfection methods consisted of ultrafiltration, ultraviolet radiation and ozonation, to tertiary treatment and effluent quality improvement in Isfahan north wastewater treatment plant. Therefore, the filtered effluent by a pretreatment unit from microscreen type entered the disinfection pilots. In this study, the membrane flux of ultrafilter (17.5-70 L/hr.m2), UV dose (400-3700 mW.s/cm2), ozone dose (10-40 mg/L) and contact time (1-15 min) with ozone were variable and TSS, Turbidity, COD, fecal and total coliform, before and after  units were measured. The results showed that the total suspended solids were below the detection limits in UF effluent and it reduced at the maximum dose of UV radiation and at the highest concentration and contact time with ozone by 61.27% and 89.36%, respectively. Though the turbidity and chemical oxygen demand were not reduced by UV, their removal percentage in UF was 76 and 39%, respectively, and their maximum removal by ozone was 80.52% and 40.74%, respectively. Also, the fecal and total coliform was reduced in UF 5.28 and 5.08 log, respectively, and at the maximum UV radiation was 3.82 and 3.79 log;  at the highest concentration and contact time with ozone it was 4.11 and 3.55 log, respectively. The results showed that influent quality and the loading in UF do not have a significant effect on their effluent quality. Also, the contact time to UV radiation compared to the average intensity of MP lamp radiation has a greater effect on the removal of coliforms. In ozonation, the influent COD had a major role in reduction of turbidity and COD. According to the results, the combination of microscreen and UF is an effective process for reducing the physical parameters and coliforms in the secondary effluent. It can provide the US Environmental Protection Agency standards for many uses (TSS≤5 mg/L, Turbidity≤2 NTU, Fecal coliform≤14 MPN/100mL). However, only a 300W MP UV lamp with a contact time of 40 s and (3700 mW.s/cm2) an ozone dose of 40 mg/L at a contact time of 15 min can meet the fecal coliform to the EPA standards for some uses including restricted urban uses, agricultural irrigation for processed or non-food crops (Fecal coliform≤200 MPN/100mL).

Fereshteh Valivand, Homayoon Katibeh

Groundwater is the most important source of fresh water supply in arid and semi-arid regions around the world, so it is necessary to maintain it through proper management in the use of these resources. Predicting areas of the aquifer that are most likely to be vulnerable is a powerful tool for optimally managing groundwater resources. Using numerical models, it is possible to predict how the aquifer reacts to the harvesting and feeding of the aquifer, with the prevailing trend or different management scenarios. The purpose of this study is to evaluate the effect of current management plans of the aquifer and the catchment area of the Jajroud River on changes in aquifer water levels and changes in nitrate ion concentration in the Varamin Plain, using numerical modeling. In this study, the effect of aquifer and catchment management plans of Jajrud River on changes in aquifer water level and changes in nitrate ion concentration in Varamin Plain, using numerical modeling. In this study, first a quantitative model was prepared in GMS software using MODFLOW code and then qualitative data were entered into the model.  MT3D code was used to run the model. The model was simulated in both stable and unstable modes. After calibrating the model, the hydrodynamic coefficients were corrected and then, using the obtained model, the quantitative and qualitative behavior of the aquifer for the coming years was predicted for two management scenarios. The resulting model showed that with the continuation of the current trend in the aquifer (first scenario), the trend of quantitative and qualitative decline of the aquifer will continue as in previous years, but in the second scenario, with reduced harvesting from wells, municipal wastewater treatment plant will be commissioned. The artificial feeding of the aquifer and the use of the effluent of the Tehran water treatment plant to irrigate the Varamin Plain will significantly reduce the water level decline. Comparison of model implementation in the first and second scenarios shows that with the implementation of planned projects, part of the quantitative problems of the aquifer, especially in the northern areas of the plain will be reduced, so that in some areas, groundwater loss calculated in the quantitative model of the first scenario (until 1420) is reduced by about 30 to 40 meters. The output maps of the qualitative model of the first scenario show that in 1420 the concentration of nitrate in a large part of the aquifer will reach over 40 mg/L, which indicates serious health threats to the region. Simulation in the second scenario shows that the implementation of artificial feeding plan and feeding the aquifer with the effluent of the wastewater treatment plant (with a concentration of 50 mg/L) will not have much effect on reducing nitrate in the aquifer. In general, the implementation of nutrition and consumption management plans in the Varamin aquifer can only lead to a reduction in the quantitative and qualitative decline of groundwater in the aquifer that does not significantly reduce the percentage of water entering the aquifer. Certainly, using the current management methods (second scenario) will not have much effect on improving the aquifer. In addition to the plan to import wastewater from the Tehran treatment plant to the Varamin Plain, the plain should continue to be fed from the Jajrud River as a suitable natural feeding source.

E. Brati, T. D. Rech, L. Agostinetto et al.

Pharmaceutical waste is considered emerging pollutant that can contaminate water sources and underground water, besides is serious problem for waste management in Brazil. The objective of this study was to evaluate the pharmaceutical consumption for human use and the way expired and unused medicines are disposed by the population. The study was carried out in two neighborhoods of the Lages, under outcrop of the Guarani Aquifer, in southern Brazil. In this descriptive and quantitative study, data collection occurred between August and October of 2018 via a questionnaire completed by 309 participants. The questions addressed about sociodemographic data, information on the medicine consumption, disposal of pharmaceuticals residue and about the basic sanitation in the neighborhood. The pharmaceuticals class most used were anti-hypertension and diuretics, indicating an elevated occurrence of non-transmittable chronic illnesses. About 68% of participants stated that there are leftovers of medications after medical treatment and 70.2% that there is expired medication at household. The disposal of leftover and expired pharmaceutical was in domestic waste, followed by discharged into domestic sewage. Only a small percentage (<15%) of the participants adequately dispose of their medication waste. The inadequate disposal of household pharmaceutical in the study area can result in contamination by chemical substances of the Guarani Aquifer and superficial waters.

Mengmou Li, Ioannis Lestas, Li Qiu

This work is associated with the use of parallel feedforward compensators (PFCs) for the problem of output synchronization over heterogeneous agents and the benefits this approach can provide. Specifically, it addresses the addition of stable PFCs on agents that interact with each other using diffusive couplings. The value in the application of such PFC is twofold. Firstly, it has been an issue that output synchronization among passivity-short systems requires global information for the design of controllers in the cases when initial conditions need to be taken into account, such as average consensus and distributed optimization. We show that a stable PFC can be designed to passivate a passivity-short system while its output asymptotically vanishes as its input tends to zero. As a result, output synchronization is achieved among these systems by fully distributed controls without altering the original consensus results. Secondly, in the literature of output synchronization over signed weighted graphs, it is generally required that the graph Laplacian be positive semidefinite, i.e., $L \geq 0$ for undirected graphs or $L + L^T \geq 0$ for balanced directed graphs. We show that the PFC serves as output feedback to the communication graph to enhance the robustness against negative weight edges. As a result, output synchronization is achieved over a signed weighted and balanced graph, even if the corresponding Laplacian is not positive semidefinite.