Water–energy nexus

Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 75 - 102

Опубликована: Янв. 1, 2025

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Data-driven soft sensors targeting heat pump systems

Energy Conversion and Management, Год журнала: 2023, Номер 279, С. 116769 - 116769

Опубликована: Фев. 4, 2023

The development of smart sensors, low cost communication, and computation technologies enables continuous monitoring accumulation tremendous amounts data for heat pump systems. But the measurements, especially domestic pump, usually suffer from incompleteness given technical and/or economic barriers, which prevents database measurements being exploited to its full potential. To this end, work proposes a data-driven soft sensor approach compensating multiple missing information. sensors are developed based on an ANN model, integrated multivariate polynomial regression model empirical by considering different constrains like information availability during establishing process. All three models have been validated against field test installation, showed good performance all compensated variables. Of models, shows best but it has highest requirement additional resources collect training data. While demonstrates excellent accuracy majority with manufacturers' subcomponent needs no extra cost. Even though is not as accurate other two still performs limited map. methods in present study paves way available measured thousands installations be fully utilized innovative services including to: improved control strategies, fault detection diagnosis, communication local energy grids.

Язык: Английский

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Machine learning framework for wastewater circular economy — Towards smarter nutrient recoveries

Desalination, Год журнала: 2024, Номер 592, С. 118092 - 118092

Опубликована: Сен. 7, 2024

Язык: Английский

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Flexible supply-demand side management towards a sustainable decentralized distribution network: A net-negative Water-energy-emissions Nexus assessment

Applied Energy, Год журнала: 2024, Номер 375, С. 124108 - 124108

Опубликована: Авг. 6, 2024

Язык: Английский

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High photocatalytic activity of Nb2O5/Ag composite in solar light-driven photodegradation of Reactive Blue 109 dye

Emergent Materials, Год журнала: 2025, Номер unknown

Опубликована: Апрель 14, 2025

Язык: Английский

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Machine learning models for the economic dispatch of islanded micro water-energy systems

Energy Conversion and Management, Год журнала: 2025, Номер 336, С. 119827 - 119827

Опубликована: Май 9, 2025

Язык: Английский

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A risk-based soft sensor for failure rate monitoring in water distribution network via adaptive neuro-fuzzy interference systems

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Июль 27, 2023

Water Distribution Networks (WDNs) are considered one of the most important water infrastructures, and their study is great importance. In meantime, it seems necessary to investigate factors involved in failure urban distribution network optimally manage resources environment. This investigated impact influential on rate Birjand, Iran. The outcomes can be a case study, with possibility extending any similar city worldwide. soft sensor based Adaptive Neuro-Fuzzy Inference System (ANFIS) was implemented predict effective features. Finally, WDN assessed using Failure Modes Effects Analysis (FMEA) technique. results showed that pipe diameter, material, pressure factors. Besides, polyethylene pipes have rates four times higher than asbestos-cement pipes. Moreover, directly proportional but inversely related diameter. FMEA analysis knowledge management technique demonstrated WDNs main policy for risk reduction leakage failure.

Язык: Английский

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Aging behaviour assessment of cellulosic fibres in alkaline media: A green technology approach in construction materials

Journal of Building Engineering, Год журнала: 2024, Номер 92, С. 109685 - 109685

Опубликована: Май 20, 2024

With the increasing demand for buildings, utilisation of green materials represents a novel approach toward achieving sustainable development goals. Cellulose-based materials, such as jute, exemplify eco-friendly substances civil engineering applications. The present study aims at studying aging behavior jute fibers in an alkaline environment. For this purpose, three alkali environments (NaOH, KOH, Ca(OH)2) with different concentrations were selected. Samples treated periods (7d, 14d, and 28d) to assess impact treatment on fiber properties. This introduces pioneering concept jute-based fibres evaluate tensile strength weight loss, marking first its kind. incorporates various characterisation techniques, including Differential Scanning Calorimetry (DSC), Thermo-Gravimetric Analysis (TGA), Electron Microscopy (SEM) process. In our experimental procedures, we evaluated key parameters type alkali, concentration, curing time their influence strength. Subsequently, applied Response Surface Methodology (RSM) conjunction bagging techniques develop mathematical models based acquired data. Results demonstrated varied strengths type, duration. Fibres 15 g/L concentration NaOH exhibited increase from 7 days (79.66 MPa) 28 (225.05 MPa). highest KOH was observed 14 (237.58 Ca(OH)₂ treatments, 30 (111.28 It also that prolonged exposure very high could adversely affect strength, case (84.73 Among tested, greater effectiveness compared Ca(OH)2. According RSM analysis, sample found be most significant factor P-value 0.009. On average, changes by 54%, 52%, 35% NaOH, Ca(OH)₂, respectively, when shifts days.

Язык: Английский

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Successive-Station Streamflow Prediction and Precipitation Uncertainty Analysis in the Zarrineh River Basin Using a Machine Learning Technique

Water, Год журнала: 2023, Номер 15(5), С. 999 - 999

Опубликована: Март 6, 2023

Precise forecasting of streamflow is crucial for the proper supervision water resources. The purpose present investigation to predict successive-station using Gated Recurrent Unit (GRU) model and quantify impact input information (i.e., precipitation) uncertainty on GRU model’s prediction Generalized Likelihood Uncertainty Estimation (GLUE) computation. Zarrineh River basin in Lake Urmia, Iran, was nominated as case study due importance location its significant contribution lake inflow. Four stations were considered from upstream downstream. yielded highly accurate all stations. future precipitation data generated under Representative Concentration Pathway (RCP) scenarios used estimate effect prediction. p-factor (inside interval) r-factor (width indices evaluate uncertainty. GLUE predicted reliable ranges 0.47 0.57 61.6% 89.3% p-factor.

Язык: Английский

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Customer Complaints-Based Water Quality Analysis

Water, Год журнала: 2023, Номер 15(18), С. 3171 - 3171

Опубликована: Сен. 5, 2023

Social media has become a useful instrument and forum for expressing worries about various difficulties day-to-day concerns. The pertinent postings containing people’s complaints water quality as an additional source of information can be automatically acquired/retrieved analyzed using natural language processing machine learning approaches. In this paper, we search social analysis propose scalable messaging system quality-related issues to the subscribers. We classify WaterQualityTweets dataset, our newly collected collection, in two phases. first phase, tweets are classified into classes (water or not). second four (color, illness, odor/taste, unusual state). best performance results BERT CNN, respectively, binary multi-class classification. Also, these sent different subscribers via topic-based with their location timing information. Depending on topics that online users interested in, some spreads faster than others. also predict diffusion understand issues’ spreading. time effort required manual comments obtained through crowd-sourcing techniques will significantly decline result automatic issues.

Язык: Английский

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