Flow Variables Research Articles

Visualized generator for the simulation of wastewater quality and quantity variations in the sewer system

Data generators are imperative to support design, management, scenario simulation, risk assessment, and regulatory compliance. Hybrid sewer systems struggle with accurate water quality and quantity monitoring due to variable flow patterns, missing connections, limited monitoring capacity. To accurately regenerate operational data for hybrid sewer system along the sewer shed, a visualized generator was developed to simulate wastewater quantity and quality variations within different scales in the sewer system. The generator was constructed using a multi-level, tree-structured model incorporating various modules, including domestic, industrial, WWTP, and pump stations, to simulate time series variations. A novel instantaneous unit pollutant-hydrograph modeling associated with wastewater conductivity monitoring data was proposed in the generator. The validated generation data of flow, COD, ammonia nitrogen, and phosphate were well-fitted with the full-scale measured data in residential areas, pump stations, and WWTPs. The proposed generator could be used to predict and simulate the dynamic flow and wastewater quality variations at different scale regions in sewer network-wide to support the operation and management of pump stations and WWTPs. The generator modules enable accurate simulation and visualization of water quality and quantity in hybrid sewer system, enhancing the understanding of infiltration, inflow, and pollutant dynamics, especially under challenging conditions like simultaneous RDII and overflow.

A novel heart rate estimation framework with self-correcting face detection for neonatal intensive care unit

Remote photoplethysmography (rPPG) is a non-invasive method for monitoring heart rate (HR) and other vital signs by measuring subtle facial color changes caused by blood flow variations beneath the skin, typically captured through video-based imaging. Current rPPG technology, which is optimized for ideal conditions, faces significant challenges in real-world clinical settings such as Neonatal Intensive Care Units (NICUs). These challenges primarily arise from the limitations of automatic face detection algorithms embedded in HR estimation frameworks, which have difficulty accurately detecting the faces of newborns. Additionally, variations in lighting conditions can significantly affect the accuracy of HR estimation. The combination of these positional changes and fluctuations in lighting significantly impacts the accuracy of HR estimation. To address the challenges of inadequate face detection and HR estimation in newborns, we propose a novel HR estimation framework that incorporates a Self-Correcting face detection module. Our HR estimation framework introduces an innovative rPPG value reference module to mitigate the effects of lighting variations, significantly reducing HR estimation error. The Self-Correcting module improves face detection accuracy by enhancing robustness to occlusions and position changes while automating the process to minimize manual intervention. Our proposed framework demonstrates notable improvements in both face detection accuracy and HR estimation, outperforming existing methods for newborns in NICUs.

Characterization and comparative appraisal of two novel annular channel designs with variable flow areas for supercritical heat transfer

Deterioration of heat transfer is a common concern for any supercritical heat transport system, regardless of the geometric orientation. Present study proposes two novel designs of annular channel with variable cross-sectional area and numerically assesses their respective performances, with the primary objective being the enhancement of overall heat transport characteristics in comparison with an equivalent traditional plain annular channel. Both the configurations exhibit substantial gain in terms of overall heat transfer coefficient and prevailing temperature level, while also eliminating deterioration over the entire parametric ranges explored here, with the diverging one demonstrating relatively superior characteristics. The converging channel generally maintains a flatter temperature profile and comparatively lower maximum temperature, and hence can be employed at larger power-to-mass-flux ratios. Taper angle is earmarked as the most influencing design variable, illustrating enhanced performance with greater tapering, albeit at the cost of nominal increase in pressure drop. Both the designs are found to be insensitive to flow acceleration, which is a primary reason of not encountering deterioration. Strong buoyancy effect can be present within the entrance region of the converging design, affecting its overall performance. Local thermalhydraulics have been noted to be contingent to the effective level of turbulence and distribution of specific heat in the radial direction, which also contribute to the favorable response from the diverging design.

Who benefits from strong patent protection? An oil‐dependent country's perspective

AbstractIn this paper, a complex interplay is demonstrated, indicating that the impact of intellectual property rights (IPR) and patent protection varies in certain trade contexts. We review the IPR and patent laws in Oman and subsequent amendments following the signing of free trade agreements and investigate how strong protection of patents and IPRs affects Oman's trade. A panel data set comprising the majority of Oman's trading partners from 2000 to 2021 was utilized to achieve this objective. Under the Oman Intellectual Property (IP) Laws, 5617 patent applications were used to calculate the patent index scores. This study contributes four significant findings. First, it analyzes how strong IP and patent protection affect Oman's exports and imports. Second, it assesses the variation in overall trade flows and manufacturing trade flows. Third, while most studies use the IPR index, this study offers a more specific perspective by examining the patent index, particularly concerning manufacturing trade, which is primarily associated with patent‐protected technologies. Fourth, this study provides the first comprehensive analysis of a GCC country that is heavily dependent on oil. This study reveals that Oman's strong IPR and patent regimes significantly enhance overall exports. Strong patent protection promotes the import of high‐tech goods, whereas robust IPR protection unexpectedly reduces manufacturing trade.

Electrical characteristics of photovoltaic (PV) solar panel and hybrid PV/thermal (PV/T) solar panel

Solar collectors and photovoltaic (PV) solar panels can convert solar radiation into heat and electrical energy. A hybrid PV/thermal (PV/T) solar panel was tested in this study. The hybrid PV/T solar panel was tested using a spiral absorber and water flow levels range from 0.01 kg/s to 0.03 kg/s. As a result, with variable water flow rates and irradiation intensity of 700 and 900 W/m2, the efficiency of hybrid PV/T solar panels varied. The highest electrical efficiency attained was 4.06% in hybrid PV/T solar panels at 900 W/m2 with 0.025 kg/s of mass flow while 3.65% by PV solar panels. In addition, plotted current-voltage and power-voltage curves were used to show the electrical properties of the solar PV panels and hybrid PV/T solar panels.

Evaluation of groundwater travel time through a multilayered aquifer using multiple tracers and a novel transport approximation

AbstractAquifer long-term replenishment (ALTR) is a managed aquifer recharge (MAR) strategy by which reclaimed water is continuously delivered by injection wells to depleted, confined aquifer systems to increase groundwater storage and increase the potentiometric surface over space and time. One implication of large-scale continuous recharge is a large radial impact and the need to quantify transport in radially extensive strata. The use of an artificial tracer can be cost-prohibitive as the radial front moves further from the injection well. This investigation employs a novel approximation for radial transport to track the radial front of recharge, injectate constituents and simulation of tracer breakthrough concentrations under transient recharge rates, variable depth-dependent flow distributions over time, and variable influent concentrations. Six constituents—sulfate, chloride, total organic carbon (TOC), fluoride, 1,4-dioxane and N-nitrosodimethylamine (NDMA)—were chosen to evaluate conservative transport and semiqualitatively assess attenuation of nonconservative constituents relative to conservative tracers. Results indicate that sulfate acted as the most effective conservative tracer for characterization of transport and travel times at the study site. The analytical model was modified to account for variable operations at the MAR demonstration facility and was effective in simulating breakthrough curves over the period of performance, particularly sulfate concentrations at a monitoring well located 104 m from the injection well. The behavior of the remaining constituents is discussed, and the qualities of an effective intrinsic tracer for future ALTR projects are identified.

Advancing Water Security and Agricultural Productivity: A Case Study of Transboundary Cooperation Opportunities in the Kabul River Basin

The Kabul River Basin (KRB) is witnessing frequent flood and drought events that influence food production and distribution. The KRB is one of the world’s poorest regions regarding food security. Food security issues in the KRB include shifts in short-term climate cycles with significant river flow variations that result in inadequate water distribution. Due to the lack of hydro-infrastructure, low irrigation efficiency, and continuing wars, the Afghanistan portion of the KRB has experienced low agricultural land expansion opportunities for food production. This research assesses the relationship between flood mitigation, flow balances, and food production and, cumulatively, assesses the social and economic well-being of the population of the KRB. SWAT modeling and climate change (CCSM4) implications are utilized to assess how these relationships impact the social and economic well-being of the population in the KRB. The intricacies of transboundary exchange and cooperation indicate that the conservation of ~38% of the water volume would nearly double the low flows in the dry season and result in the retention of ~2B m3/y of water for agricultural developmental use. Results show that the peak flood flow routing in reservoirs on the Afghanistan side of the KRB would have a substantial positive impact on agricultural products and, therefore, food security. Water volume conservation has the potential to provide ~44% more arable land with water, allowing a ~51% increase in crop yield, provided that improved irrigation efficiency techniques are utilized.

Sim‐Net: Simulation Net for Solving Seepage Equation Under Unsteady Boundary

ABSTRACTThe seepage equation plays a crucial role in fields such as groundwater management, petroleum engineering, and civil engineering. Currently, physical‐informed neural networks (PINNs) have become an effective tool for solving seepage equations. However, practical applications often involve variable flow rates, which pose significant challenges for using neural networks to find solutions. Inspired by Deep Operator Network (DeepONet), this paper proposes a new model named Simulation Net (Sim‐net) to deal with unsteady sources or sinks problems. Sim‐net is designed to simulate and solve seepage equations without the need for retraining. This model integrates potential spatial and temporal features based on spatial pressure distribution and well bottom–hole pressure, respectively, which serve as additional signposts to guide neural networks in approximating seepage equations. Sim‐net exhibits transfer learning capabilities, enabling it to handle variable flow rate problems without retraining for new flow conditions. Numerical experiments demonstrate that the trained model can directly solve seepage equations without the need for retraining, indicating its superior applicability compared to existing PINNs‐based methods. Additionally, in comparison to the DeepONet, Sim‐net achieves higher accuracy.

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

Tectonostratigraphic models of an extensional back-arc basin: inferences for the evolution of the Pannonian Basin System

The subsidence history and sedimentary architecture of extensional basins are controlled by the interplay between tectonics, mantle dynamics and climatic variations. Observations from outcrop to regional seismic scales coupled with numerical modelling techniques, including basin-scale stratigraphic, crustal-scale tectonic and mantle-scale subduction models, contribute to the quantification of basin evolution. Here, we review and discuss both tectonic and stratigraphic applications of such models and compare them with observations from the Pannonian Basin system of Central Europe. We show that diachronous localization of back-arc extension, crustal thinning, asthenospheric upwelling and subsequent thermal relaxation are superimposed on an overall slow plate convergence. These processes result in contrasting subsidence and uplift patterns and a variable heat flow evolution in different parts of the basin system. The crustal stress-field of the sub-basins does not always reflect their contrasting vertical motions. Extensional deformation generally migrates from the basin margins towards the basin centre. Structural inversion is localized along hot and weak inherited zones from the Middle Miocene to Present. Tectonic subsidence focuses sedimentation along deep depocentres, sourced by exhumed footwalls and from the neighbouring orogens. The overall post-rift sediment progradation is influenced by inherited bathymetries from the preceding syn-rift stage and by enhanced differential vertical motions.

Temporal Patterns in Migration Flows Evidence from South Sudan

ABSTRACTWhat explains the variation in migration flows over time and space? Existing work has contributed to a rich understanding of the factors that affect why and when people leave. What is less understood are the dynamics of migration flows over time. Existing work typically focuses on static variables at the country‐year level and ignores the temporal dynamics. Are there recurring temporal patterns in migration flows? And can we use these patterns to improve our forecasts of the number of migrants? Here, we introduce new methods to uncover temporal sequences—motifs—in the number of migrants over time and use these motifs for forecasting. By developing a multivariable shape similarity‐based model, we show that temporal patterns do exist. Moreover, using these patterns results in better out‐of‐sample forecasts than a benchmark of statistical and neural networks models. We apply the new method to the case of South Sudan.

INCREASING THE RELIABILITY OF DEFECT DETECTION THREAD, FIBRE AND YARN

A method and algorithm for increasing the reliability of decision-making in the problem of detecting defects in extended products – threads, wires, cables, fibres, yarn, etc., based on the following principles are proposed: using several statistical criteria at the same time rather than one, developing a rule for coor-dinated decision-making based on the results of testing using several statistical criteria, implementing the testing procedure in the online mode as data are received and checked. The algorithm is a sequential test of the hypothesis about the violation of stationarity by the average level and variability of the data flow from the scanning device using simultaneously used Student, Wilcoxon, Fisher and Ansari – Bradley tests, taking into account the information already accumulated about the flow at the previous stages of testing.

Energy-Saving Effects of the Intermittent Control of Pumps in Ground Source Variable Refrigerant Flow Systems with a Buffer Water Tank

Energy-Saving Effects of the Intermittent Control of Pumps in Ground Source Variable Refrigerant Flow Systems with a Buffer Water Tank

Initial Experimental Investigation of Hydraulic Characteristics at Right-Angle Diversion in a Combined Canal and Pipe Water Conveyance System

To enhance the efficiency of irrigation water utilisation, China is progressively converting irrigation ditches into pipelines. The water distribution outlets in irrigation zones are predominantly right-angled, and there are typically occurrences of erosion, sedimentation, and structural deterioration in the surrounding areas. This article employs a synthesis of indoor physical model experiments and theoretical analysis to examine the distribution of channel flow velocity and variations in water surface profile, pipeline flow rate, diversion ratio, circulation intensity, and turbulence energy across different relative water depths. The experimental results indicate that the water surface adjacent to the main canal wall demonstrates a pattern of initial decline, followed by an increase and subsequently another decline; furthermore, as the water level in the main channel rises, the magnitude of this fluctuation progressively diminishes. In some sections of the canal, the water surface elevation progressively increases, albeit with minimal amplitude. With a constant relative water depth, an increase in main channel flow results in a corresponding increase in pipeline flow; however, the diversion ratio is inversely related to the main channel flow. Conversely, when the main channel flow rate is constant, the diversion ratio increases as relative water depth rises. The vertical flow velocity near the water diversion outlet has a negative value, signifying the existence of a backflow zone, while the horizontal flow velocity varies considerably, facilitating the formation of circulation and resulting in localised deposition and erosion. The water flow near the pipe inlet downstream of the lower lip of 0.5 times the pipe diameter is impacted by the return zone, which has a higher turbulence energy and circulation strength and is more susceptible to siltation. The turbulence energy of the water flow is higher in the range of 0.5 times the pipe diameter upstream and downstream of the pipe inlet. This research is highly significant in facilitating the conversion of irrigation channels into pipelines.

Impacts of river flow and thermal regimes on fish growth dynamics during early life history

Growth during early life stages is critical to fish population persistence. Few studies explore how river discharge and thermal regimes impact growth dynamics of young-of-the-year (YOY) fishes. We used otolith biochronologies and generalised additive mixed models to partition the effects of age, individual, river, temperature, discharge, and variance in discharge on daily growth rates of YOY fishes with an opportunistic life-history strategy: Galaxias vulgaris and Gobiomorphus breviceps. Growth of both species increased with temperature. Galaxias growth decreased with discharge, while Gobiomorphus growth increased with lowered discharge but only to a point (ca. 1/3 of median discharge), after which growth plateaued. Floods had a strong negative effect on YOY growth. Our study systems and species had different characteristics to those that formed the basis of the Riverscape Recruitment Synthesis Model (RRSM) and may explain why our results were only partially consistent with flow predictions for opportunistic species of the RRSM. Further, Galaxias growth was a negative function of high-frequency, daily variation in flow, and we present testable hypotheses to explain this result.

How Can Machine Learning Contribute to the Credit Scoring Process in SME Lending?

This research investigates the potential of machine learning to enhance the credit scoring process in small and medium-sized enterprise (SME) lending. SMEs are vital to global economies, accounting for over 90\% of businesses and more than half of total employment worldwide, according to The World Bank (2023). In emerging economies, SME lending is particularly crucial, providing access to capital that supports economic growth and development. However, assessing the credit risk of SMEs poses unique challenges due to limited financial histories and variable cash flows, making accurate credit scoring essential for lenders. Machine learning offers promising solutions for the risk assessment process in SME lending, leveraging algorithms and large datasets to identify patterns and improve decision-making. By applying techniques such as artificial neural networks, decision tree learning, gradient boosting, logistic regression, random forest, and support vector machines, machine learning can enhance the accuracy and efficiency of credit scoring models. This research explores how these machine learning methods can reduce biases, improve risk prediction, and ultimately support sustainable lending practices by enabling lenders to make more informed credit decisions. The findings aim to illustrate the transformative potential of machine learning in SME credit scoring, offering a framework for financial institutions seeking to integrate advanced data-driven technologies in the credit assessment process.

Insight into the impact of fixed transition on the aerodynamic performance and noise of airfoils with varying airfoil thicknesses

To explore the effect of surface pollution on the aerodynamics and acoustics of airfoils, the aerodynamic performance and noise of Delft University of Technology (DU) airfoils with different relative thicknesses are simulated using the shear-stress transport k-ω model and large Eddy simulation. The sensitive positions of fixed transition for DU airfoils are examined in terms of aerodynamic performance and noise, and the variations in aerodynamic performance, noise, and internal flow are analyzed. The results show that the sensitive position of fixed transition is almost unaffected by the relative thickness of airfoils. In terms of aerodynamic performance and noise, the sensitive transition positions on the suction surface are located at 1%c and 5%c, respectively. Fixed transition leads to a reduction in the aerodynamic efficiency and an elevation in noise. The impact of fixed transition on the airfoil's trailing-edge noise far exceeds its effect on radiated noise. The original airfoil's noise exhibits a typical dipole-like directional distribution. However, after the fixed transition, the dipole distribution gradually blurs, and this trend becomes more pronounced with increasing relative thickness. Fixed transition reduces the stability of wake vortex shedding and increases the energy loss, and an increase in relative thickness enlarges the high vortex region and vortex size near the fixed transition.

Seasonal Influence on the Impact of Human Chorionic Gonadotropin (hCG) on Testicular Haemodynamics and Hormonal Responses in Canines: A Comparative Study.

Human chorionic gonadotropin (hCG) is widely used to treat reproductive dysfunction by enhancing testicular blood flow and stimulating hormonal activity. This study investigates the seasonal variations in the response to hCG treatment in male dogs, focusing on its effects on testicular blood flow and plasma concentrations of testosterone and oestrogen. Conducted across different seasons (spring, summer, fall and winter), the study utilised colour Doppler ultrasonography to measure testicular haemodynamics and analysed hormonal levels at multiple time points post-hCG injection. The findings revealed that the response to hCG is modulated by seasonal factors, with significant variations in both blood flow and hormone levels. A significant negative relationship was indicated between testicular blood flow and testosterone levels, particularly during spring and summer. These results suggest that seasonality should be considered when administering hCG for reproductive treatments in canines.

Interaction regimes of surface water and groundwater in a hyper-arid endorheic watershed on Tibetan Plateau: Insights from multi-proxy data

The interaction between surface water and groundwater is crucial for the management of water resources and the preservation of ecosystems within arid basins, but knowledge on their interaction regimes at the watershed scale remains relatively limited. The present research synthesizes a range of multi-proxy data, including satellite thermal infrared remote sensing, water piezometric level, hydrochemical analyses, and isotopic signatures (2H, 18O and 222Rn), to elucidate the interaction dynamics and patterns between surface water and groundwater within a representative hyper-arid closed basin on Tibetan Plateau. The findings indicate that the water in the basin originates primarily from the glacier/snow melt water and precipitation in the mountainous regions, and would experience multiple but spatially heterogeneous interactions between river and aquifers from the mountain pass to the tail salt lakes after entering the basin. Water interaction in the piedmont alluvial plain is dominated by the pattern of river seepage into aquifers with a water flux of 25.82 m3/s, which drives the development of hierarchical groundwater flow systems in the basin. The interaction pattern converts to groundwater discharge of the local groundwater flow system at the front of alluvial fan plain, which forms the principal spring-fed rivers and the predominant overflow zone in the basin with the groundwater discharge flux of 3.22 m3/s. Most of these discharged groundwaters would infiltrate back into the aquifers in the middle-upper part of the loess plain with the river water leakage flux of 2.89 m3/s. River water and phreatic groundwater present a gradual enrichment of hydrochemcial components and water stable isotopes (2H and 18O) along the flow path due to the intense evaporation in the loess plain. The multiple water interactions between surface water and groundwater lead to the anomalous distribution of fresh water in the middle-lower stream area, which is related to the intermediate groundwater flow system and the local variable groundwater flow system. Water interaction in the lowest salt-marsh plain is in the pattern of regional groundwater flow system discharge into the tail salt lakes under natural condition, but evolves to only discharge into the artificial brine extraction canals rather than the tail salt lakes after decades of brine exploitation. Our findings provide a conceptual and preliminarily quantificational understanding of the interaction regimes between surface water and groundwater in large arid closed basins at the watershed scale.

Cost-Effectiveness Analysis of Nearly Zero-Carbon Office Buildings in Taiwan

The formulation of an affordable and economically-feasible policy for nearly zero-carbon building design is a challenge that countries encounter in promoting net-zero building. In 2022, Taiwan promulgated Building Energy Rating System (BERS), the world's first building energy efficiency assessment system tailored for subtropical climates, as a basis for evaluating its goal of achieving nearly zero-carbon buildings by 2050. However, whether this nearly zero-carbon building policy is financially feasible has remained unknown to the government and the industry. To address the issue, the objective of the paper is to conduct a cost-benefit and payback period analysis of newly constructed nearly zero-carbon office buildings in accordance with the Building Energy-efficiency Rating System for New Buildings (BERSn) assessment framework, and thereby examines the financial affordability and feasibility of Taiwan's net-zero building policies.Firstly, this study introduces existing building energy performance evaluation methods in Europe, America, and Japan, and explains the methodology of Taiwan's Building Energy Rating System (BERS). The paper then reviews international Cost-Benefit Analyses of Nearly Zero Energy Office Buildings and parallelly conducts a Cost-Benefit Analysis of Nearly Zero-Carbon Office Buildings in Taiwan. Following the BERS methodology, this paper identifies the baseline efficiency level and the Nearly Zero-Carbon Building (NZCB) efficiency level, along with their associated solutions and investment costs, for air conditioning and lighting systems. In this study, a questionnaire survey of 28 experts identifies the air conditioning unit costs of Basic Mechanical Equipment Efficiency (BME) and energy-saving control technologies (R) for energy-efficient design of Fan Coil Unit (FCU), Air Handling Unit (AHU), and Variable Refrigerant Flow (VRF) system. Accordingly, 33 air conditioning design solutions and their corresponding construction costs complying with the BERSn requirements of EAC≦0.5 for nearly-zero carbon office buildings are identified. Regarding the nearly zero-carbon lighting design, the simulations reveal that the use of LED panel luminaires or T8 LED luminaires (including those with energy-saving labels) can achieve an average operational lighting illuminance of 500 LUX and the BERSn requirements of EL ≤ 0.5 for lighting. Finally, the study further analyzes the payback period and premium cost ratio of NZCB by employing the budget data of seven building projects. The analysis shows that the premium cost ratio and the payback period of NZCB range from 1.33%-1.50% and 6.4-7.7 years, respectively. The results demonstrate that while a higher budget is commonly associated with NZCB by the public, it is in fact economically and technologically feasible to realize NZCB with prevailing energy-efficient measures.