Flow Analysis Research Articles

MPNG: A MATPOWER-Based Tool for Optimal Power and Natural Gas Flow Analyses

MPNG is an open-source simulation package for solving Optimal Power and Natural Gas Flow (OPNGF) problems. It is coded in <small>Matlab</small> and developed using the widely-used tool for power systems research and education, <small>Matpower</small>. MPNG assembles a nonlinear steady state OPNGF formulation for analyzing the integration of electricity and natural gas networks with order-of-priority classes of consumers and gas nodal price-controlled storage facilities. This paper presents the details of the nonlinear optimization model behind MPNG, as well as several features that were designed into it for the purpose of achieving robustness. These include an approximation of the Weymouth equation for handling bi-directional gas flows in pipelines, a per-unit representation for the natural gas network, and penalized slack variables for power and gas balances. Simulation results using a test case and the Colombian power and natural gas networks are presented to highlight MPNG&#x0027;s capabilities to solve OPNGF problems.

Extended Research on Microwave Heating-Healing Capacity of Asphalt Mixture: Asphalt Flow Analysis Combining Capillary Flow Test with Temperature Distribution

Extended Research on Microwave Heating-Healing Capacity of Asphalt Mixture: Asphalt Flow Analysis Combining Capillary Flow Test with Temperature Distribution

Two Models on the Unsteady Heat and Fluid Flow Induced by Stretching or Shrinking Sheets and Novel Time-Dependent Solutions

Abstract This study sheds light on unsteady heat and fluid flow problems over stretching and shrinking surfaces, enriching our understanding of these complex phenomena. We derive two mathematical models using a rigorous approach. The first model aligns with the model commonly employed by researchers in this field, but its steady-state solution remains trivial. The second model, introduced in this work, demonstrably captures the physically relevant steady-state solutions well-studied in the literature. Notably, we introduce new similarity solutions for the temperature field specifically within the first model. We further demonstrate that a uniform wall temperature condition leads to the optimal heat transfer rate. While similarity solutions can be derived for specific cases with the second model, nonsimilar solutions may be necessary for more general scenarios. We discuss the implications of our analysis for stagnation-point flow and non-Newtonian viscoelastic fluid flow problems, illuminating future research directions in the open literature.

Quantitative analysis of the electromagnetic hybrid nanofluid flow within the gap of two tubes using deep learning neural networks

Purpose(1) A mathematical model for the Hybrid nanofluids flow is used as carriers for delivering drugs. (2) The flow conditions are controlled to enable drug-loaded nanofluids to flow through the smaller gap between the two tubes. (3) Hybrid nanofluids (HNFs) made from silver (Ag) and titanium dioxide (TiO2) nanoparticles are analyzed for applications of drug delivery. (Ag) and (TiO2) (NPs) are suitable candidates for cancer treatment due to their excellent biocompatibility, high photoactivity, and low toxicity. (4) The new strategy of artificial neural networks (ANN) is used which is machine-based and more prominent in validation, and comparison with other techniques.Design/methodology/approachThe two Tubes are settled in such a manner that the gap between them is uniform. The Control Volume Finite Element Method; Rk-4 and Artificial Neural Network (ANN).Findings(1) From the obtained results it is observed that the dispersion and distribution of drug-loaded nanoparticles within the body will be improved by the convective motion caused by hybrid nanofluids. The effectiveness and uniformity of drug delivery to target tissues or organs is improved based on the uniform flow and uniform gap. (2) The targeting efficiency of nanofluids is further improved with the addition of the magnetic field. (3) The size of the cylinders, and flow rate, are considered uniform to optimize the drug delivery.Research limitations/implications(1)The flow phenomena is considered laminar, one can use the same idea through a turbulent flow case. (2) The gap is considered uniform and will be interesting if someone extends the idea as non-uniform.Practical implications(1) To deliver drugs to the targeted area, a suitable mathematical model is required. (2) The analysis of hybrid nanofluids (HNFs) derived from silver (Ag) and titanium dioxide (TiO2) nanoparticles is conducted for the purpose of drug delivery. The biocompatibility, high photoactivity, and low toxicity of (Ag) and (TiO2) (NPs) make them ideal candidates for cancer treatment. (3) Machine-based artificial neural networks (ANN) have a new strategy that is more prominent in validation compared to other techniques.Social implicationsThe drug delivery model is a useful strategy for new researchers. (1) They can extend this idea using a non-uniform gap. (2) The flow is considered uniform, the new researchers can extend the idea using a turbulent case. (3) Other hybrid nanofluids flow, in the same model for other industrial usages are possible.Originality/valueAll the obtained results are new. The experimental thermophysical results are used from the existing literature and references are provided.

Entropy analysis of a non-Darcian mixed convective flow of Cu-Al2O3-based hybrid nanofluid with thermal dispersioneffect

Entropy measures the disorderness or randomness of the systems. It may affect the effectiveness and performance of the thermal systems. That is why entropy analysis is one of the trending research topic in modern era of society. The motive of this article is to present a comprehensive analysis of entropy generation and thermal dispersion effect on mixed convective flow of (Cu-Al2O3)/(H2O) based hybrid nanofluid along a plate submerged in a non-Darcy porous medium. The mathematical model describing the flow problem encompasses a system of partial differential equation, resulting from the single-phase flow model of the nanofluid combined with the Darcy-Forchheimer expression for porous medium flow. The dimensional system of partial differential equation is transformed into a non-dimensional nonlinear ordinary differential system through a similarity transformations and subsequently, the system is solved using the BVP4C module in MATLAB. The study analyzes the flow variables and entropy generation with respect to the parameters inherent in the problem. The findings suggests that, the increasing thermal dispersion effects enhances the Heat transfer rate of the hybrid nanofluid. Further, it is reported that the entropy generation in hybrid nanofluid is lower than the mono nanofluid which makes the hybrid nanofluid a better choice for entropy management in the thermal systems. The outcome of the research has practical implications in various real-life applications, such as crude oil production, oil flow filtration, electronic cooling equipment, etc.

Melting heat transfer and entropy analysis of ternary Casson nanofluids flow with second slip conditions: Application on rocket engine cooling

Heat transfer analysis of Casson nanofluid flow with single and multi-walled carbon nanotubes and Al2O3 or GO nanoparticles, which are suspended in kerosene oil, is elucidated. The impact of second slip conditions on the flow system’s velocity, temperature, and solutal is considered, along with the effect of melting heat transfer and nanoparticle shape factor. The appraisal’s novelty is the incorporation of second slip conditions on kerosene oil flow containing with new three distinct nanoparticles. Similar variables are used to convert the governing equations into ordinary equations which are then solved using homotopy perturbation method (HPM). The profiles of velocity, temperature, concentration, and Bejan number are estimated for various values of relevant parameters. Results demonstrate that the Bejan number declines due to enhance the first thermal parameter and second velocity parameter, while the contrary tendency is examined by raising the Casson fluid parameter and first velocity parameter. Al2O3-SWCNT-MWCNT TNF responds more strongly than GO-SWCNT-MWCNT TNF when the temperature is coupled with (nanoparticles volume fraction, first thermal parameter), axial velocity with (nanoparticles volume fraction, first velocity parameter, first thermal parameter), and Bejan number with melting parameter. This study is to help rocket engine designers identify the optimal nanofluids for cooling and fuel.

Multi-Directional Wind Turbine with Combined Savonius and Darrieus Rotors: A Comparative Performance Analysis

This study presents a comprehensive investigation into five distinct combinations of wind turbine configurations, each integrating Savonius and Darrieus rotors on a single shaft. The studied configurations include Single Stage Savonius and H-Darrieus, Two-Stage Savonius and D-Darrieus, Two-Stage Savonius and H-Darrieus, Helical Darrieus and Two-Stage Savonius, and Two-Stage Savonius and H-Darrieus in series. Our research uses Computational Fluid Dynamics (CFD) simulations conducted using ANSYS Fluent to meticulously analyze and optimize these turbine designs. Through rigorous computational modeling and flow analysis, we aim to elucidate the performance characteristics, including torque generation, torque nature, flow time, and power output, for each configuration. Following thorough comparison, our findings highlight the double-stage Savonius and D Darrieus turbine as exhibiting superior performance attributes. This research contributes valuable insights into the advancement of multi-directional wind turbine technology, facilitating enhanced energy harnessing from varying wind conditions.

CT-derived Fractional Flow Reserve: How, When, and Where to use this Novel Cardiac Imaging Tool.

Fractional flow reserve computed tomography (FFRCT) is a novel imaging modality. It utilizes computational fluid dynamics analysis of coronary blood flow obtained from CCTA images to estimate the decrease in pressure across coronary stenosis during the maximum hyperemia. The FFRCT can serve as a valuable tool in the assessment of coronary artery disease (CAD). This non-invasive option can be used as an alternative to the invasive fractional Flow Reserve (FFR) evaluation, which is presently considered the gold standard for evaluating the physiological significance of coronary stenoses. It can help in several clinical situations, including Assessment of Acute and stable chest pain, virtual planning for coronary stenting, and treatment decision-making. Although FFRCT has demonstrated potential clinical applications as a non-invasive imaging technique, it is also crucial to acknowledge its limitations in clinical practice. As a result, it is imperative to meticulously evaluate the advantages and drawbacks of FFRCT individually and contemplate its application in combination with other diagnostic examinations and clinical data.

Industrial Park low-carbon energy system planning framework: Heat pump based energy conjugation between industry and buildings

The accelerating urbanization, rapid industrial development, and excessive consumption of fossil fuels pose survival challenges such as energy depletion and environmental degradation for humanity. In the context of industrial park development, constructing a low-carbon energy system, increasing the proportion of renewable energy, enhancing energy-level matching, and utilizing heat pumps for deep waste heat recovery are effective approaches to reduce fossil energy consumption and alleviate environmental pressures. Addressing issues such as diverse thermal flows in industrial sites, complex electricity-heat-cooling energy demands, and unclear industrial-building energy coupling mechanisms, this paper proposes a two-stage planning framework, comprising the following five steps: (1) constructing a waste heat utilization system centered around heat pumps, (2) establishing a mechanism for matching heat sources, equipment, and thermal sinks, (3) establishing an energy conversion model and energy quality quantification system, (4) optimizing waste heat utilization path allocation, and (5) conducting a system energy flow analysis. Case studies demonstrate that the proposed system achieves optimized matching of multiple heat sources and sinks in industrial and building scenarios through thermal integration, meeting diverse energy demands in the park, including electricity, cooling, and multi-grade heat. After coupling with traditional steam pipeline networks, the annual total cost and annual steam power consumption decrease by 33% and 39% respectively, with a waste heat contribution rate of up to 26% and a renewable energy penetration rate of up to 25%, and a waste heat recovery system payback period of 6 years. By establishing an energy quality quantification system and conducting multi-objective optimization considering losses and economic costs, this paper provides Pareto frontier solutions, offering references for engineering proposals. The proposed networked waste heat recovery system is characterized by low energy consumption and high economic efficiency, effectively integrating the energy characteristics of industrial parks and demonstrating engineering applicability.

Analyzing the quality differences between healthy and moldy cigar tobacco leaves during the air-curing process through fungal communities and physicochemical components.

The air-curing process of cigar tobacco, as a key step in enhancing the quality of cigars, is often susceptible to contamination by mold spores, which severely constrains the quality of cigar tobacco. This study employed high-throughput Illumina sequencing technology and a continuous flow analysis system to analyze the differences between the microbial communities and physicochemical components of moldy and healthy cigar tobacco leaves. Furthermore, correlation analysis was performed to reveal the impact of mold on the quality of cigar tobacco. The differences between the microbial flora and physicochemical compositions of moldy (MC) and healthy (HC) tobacco leaves were analyzed, revealing significant disparities between the two groups. Aspergillus spp. represented the dominant mold in MC, with nine out of twelve isolated molds showing higher quantities on MC than on HC. Mold contamination notably decreased the total nitrogen (TN), total phosphorus (TP), total alkaloids (TA), starch, protein, and flavor constituents while increasing the total fatty acid esters (TFAA), which was accompanied by a shift towards weakly acidic pH in the leaves. Fungal community analysis indicated a significant reduction in the fungal operational taxonomic unit (OUT) numbers and diversity indices in MC, contrasting with the bacterial trends. Aspergillus exhibited significantly higher relative abundance in MC, with LEfSe analysis pinpointing it as the primary driver of differentiation. Furthermore, significant negative correlations were observed between Aspergillus and TP, starch, TA, and protein, while a significant positive association was evident with TFAA. Network analysis underscored the pivotal role of Aspergillus as the species influencing disparities between HC and MC, with its abundance serving as a critical determinant during the air-curing process. This study elucidated substantial quality distinctions between MC and HC during air-curing, with Aspergillus emerging as the key species contributing to leaf mold.

Response surface method approach for analyzing flow characteristics in an abruptly expanding channel

Analysis of flow in an abruptly expanding channel for five characteristics namely sequent depth ratio ‘Y2/Y1’, efficiency ‘E2/E1’, relative height of jump ‘hj/E1’, relative length of jump ‘Lj/Y1’ and relative length of roller ‘Lr/Y1 were studied experimentally and using Response Surface Method (RSM) technique. Physical explanations of these characteristics against Froude number were also discussed based on experiments. Dimensional analysis has also been followed for different fluid properties and geometric dimensions of the setup for reducing number of complexity involved in hydraulic jump phenomenon. Obtained results are well presented as regression models for all flow characteristics. Further, Response Surface Method (RSM) is applied to determine most significant parameter influencing jump characteristics and to identify any unusual behavior of flow parameters. The central composite rotatable design (CCRD) was employed to generate the experimental runs using Minitab software version 21. These developed models are characterized as highly accurate as prediction efficiency of RSM model is deemed highly effective for sequent depth, relative height, efficiency, relative length of roller and relative length of jump as reflected in the Nash-Sutcliffe Efficiency (NSE) values within the 0.9 NSE range.

Applications of Matrix Multiplication

In this paper we present some interesting applications of the matrix’s multiplication, that include the Leslie matrix and population change, which we calculate this kind of changes from year to other year by matrix multiplication. Another important part of the paper is Analysis of Traffic Flow, we represent the flow of traffic through a network of one-way streets. Another much important part is the production costs, this is fantastic usage of matrix multiplication, in which, A company manufactures three products. Its production expenses are divided into three categories, here in this paper we well describe this beautiful issue. By matrix multiplication, we can encode and decode messages. To encode a message, we choose an invertible matrix and multiply the uncoded row matrices (on the right) by to obtain coded row matrices, this idea will be clarify by some useful examples. Also we used to study certain relationships between objects by matrix multiplication. We will clarify all of these applications by useful examples. In this paper, we present six different applications of matrix multiplication.

Pleistocene climate oscillations have shaped the expansion and contraction speciation model of the globose Eriosyce sect. Neoporteria cacti in Central Chile.

Pleistocene climatic oscillations, characterized by arid (interglacial) and pluvial (glacial) phases, have profoundly impacted the floras of Mediterranean climates. Our study investigates the hypothesis that these climatic extremes have promoted phases of range expansion and contraction in the Eriosyce sect. Neoporteria, resulting in pronounced genetic structuring and restricted gene flow. Utilizing nuclear microsatellite markers, we genotyped 251 individuals across 18 populations, encompassing all 14 species and one subspecies within the Eriosyce sect. Neoporteria. Additionally, Species Distribution Models (SDMs) were employed to reconstruct past (Last Interglacial, Last Glacial Maximum, Mid-Holocene) and current potential distribution patterns, aiming to delineate the climatic influences on species' range dynamics. The gene flow analysis disclosed disparate levels of genetic interchange among species, with marked restrictions observed between entities that are geographically or ecologically separated. Notably, E. subgibbosa from Hualpen emerged as genetically distinct, warranting its exclusion for clearer genetic clustering into north, central, and south clusters. The SDMs corroborated these findings, showing marked range expansions during warmer periods and contractions during colder times, indicating significant shifts in distribution patterns in response to climatic changes. Our findings emphasize the critical role of Pleistocene climatic fluctuations in driving the dynamic patterns of range expansions and contractions that have led to geographic isolation and speciation within the Eriosyce sect. Neoporteria. Even in the face of ongoing gene flow, these climate-driven processes have played a pivotal role in sculpting the species' genetic architecture and diversity. This study elucidates the complex interplay between climatic variability and evolutionary dynamics among Mediterranean cacti in central Chile, highlighting the necessity of considering historical climatic millenial oscillations in conservation and evolutionary biology studies.

Three-phase model of SCIG-based variable speed wind turbine for unbalanced DSLF analysis

Steady state performances of the electric power distribution system are normally assessed or evaluated based on load flow analysis. To properly carry out the analysis, a valid steady state load flow model of each distribution system component, including the wind power plant (WPP), needs to be developed. The present paper proposes a method for modeling and integrating squirrel cage induction generator (SCIG)-based variable speed WPP into a three-phase unbalanced distribution system load flow (DSLF) analysis. The proposed method is based on a single-phase T-circuit model of fixed speed WPP, which has successfully been applied to balanced electric power systems. In the present work, the single-phase T-circuit model is extended and modified to be used in steady state load flow analysis of three-phase unbalanced distribution systems embedded with SCIG-based variable speed WPP. Results of the case studies confirm the validity of the proposed method.

Enhancing performance in solar air channels: A numerical analysis of turbulent flow and heat transfer with novel shaped baffles

Solar air heaters are emerging as a promising solution for sustainable heating, as they harness abundant solar energy to provide heat for a variety of applications. However, their optimum efficiency remains a major challenge. Deflectors have significant potential to improve the performance of solar air heaters by redirecting airflow and optimizing heat transfer, making them more efficient and more suitable for large-scale adoption. This article examines the performance of a new baffle design aimed at improving heat transfer in the channel by increasing the exchange surface between fluid and solid surface. It consists of a “≠” -shaped baffle mounted on the top and bottom walls of the channel. An in-depth analysis of the spacing between these baffles was carried out to assess their impact on the thermal and aerodynamic properties of the solar air channel. Computational Fluid Dynamics (CFD) was used to perform the calculations, using the Finite Volume Method (FVM) in conjunction with the SIMPLE algorithm. All studies are carried out using the CFD code Fluent. Crucial steps in this research include studying the influence of these new baffles at different Reynolds numbers, ranging from 15000 to 35000, as well as varying the separation distance between the two baffles, chosen periodically (DBaffle/2, 3DBaffle/4, DBaffle, 5DBaffle/4 and 3DBaffle/2). Some of the numerical results were validated with the available experimental data and showed satisfactory agreement. The study identified an optimal case for the new baffles, by reducing the distance between the baffles, an improvement in system performance was observed, by increasing the flow strength and widening the recycling cells, which has an impact on dynamic behavior and heat transfer. The presence of this new baffle design, with minimal separation distance between them, demonstrated a significant thermal improvement, with a thermal improvement factor increasing by 44% compared to the simple channel without baffles, thus highlighting the effectiveness of the new solar air channel with “≠” -shaped baffles.

Phase and microstructure evolutions of fiber reinforced aerogel composites with different fiber components during calcination

In the high temperature industry, controlling the external surface temperature of the kiln shell is crucial for reducing heat loss, energy consumption, and carbon emissions. While aerogels are esteemed for their superior thermal insulation properties and considered as optimal materials in the thermal insulation layer of energy saving lining for burning zone of cement rotary kiln, their structural integrity at elevated temperatures confines their applications to medium and low temperature settings. To overcome this limitation, the fiber-reinforced aerogel composites have been developed to bolster the high-temperature endurance of aerogel products. Notably, composites containing ZrO2-enhanced fibers exhibit significantly higher resistance to thermal degradation from local overheating, such as flame impingement, compared to their counterparts without ZrO2. However, the mechanisms of performance degradation and the reinforcing role of ZrO2 in fiber reinforced aerogel composites at high temperatures especially above 1000 °C, remain unclear. This study specifically focuses on the thermal conductive properties of commercial aerogel felts, both with and without the inclusion of ZrO2 across a range of temperatures, and examines the subsequent phase transitions and microstructural evolutions upon thermal treatment. Critical analyses of heat flow, mass change, density, linear shrinkage, and pore size distribution during the calcination process were conducted. After 6 hours of heat treatment, composites with ZrO2-enhanced fibers retained an 81.44% porosity, unlike composites without ZrO2 which sintered and became denser. The experimental findings demonstrate that the performance of fiber reinforced aerogel composites mainly depends on the fiber’s framework microstructure and fiber-aerogel reactions, which provides the references for developing excellent aerogel composites and evaluating of the usability in high temperature zone of kiln.

Coarsened Mixtures of Hierarchical Skew Normal Kernels for Flow and Mass Cytometry Analyses

Cytometry is the standard multi-parameter assay for measuring single cell phenotype and functionality. It is commonly used for quantifying the relative frequencies of cell subsets in blood and disaggregated tissues. A typical analysis of cytometry data involves cell classification—that is, the identification of cell subgroups in the sample—and comparisons of the cell subgroups across samples or conditions. While modern experiments often necessitate the collection and processing of samples in multiple batches, analysis of cytometry data across batches is challenging because differences across samples may occur due to either true biological variation or technical reasons such as antibody lot effects or instrument optics across batches. Thus a critical step in comparative analyses of multi-sample cytometry data—yet missing in existing automated methods for analyzing such data—is cross-sample calibration, whose goal is to align corresponding cell subsets across multiple samples in the presence of technical variations, so that biological variations can be meaningfully compared. We introduce a Bayesian nonparametric hierarchical modeling approach for accomplishing both calibration and cell classification simultaneously in a unified probabilistic manner. Three important features of our method make it particularly effective for analyzing multi-sample cytometry data: a nonparametric mixture avoids prespecifying the number of cell clusters; a hierarchical skew normal kernel that allows flexibility in the shapes of the cell subsets and cross-sample variation in their locations; and finally the “coarsening” strategy makes inference robust to departures from the model not captured by the skew normal kernels. We demonstrate the merits of our approach in simulated examples and carry out a case study in the analysis of a multi-sample cytometry data set. We provide an R package for our method.

Probabilistic material flow analysis of released nano titanium dioxide in Mexico

Engineered Nanomaterials (ENMs) or products containing ENMs, known as nano-enabled products are commercialized globally by a large number of companies. Concern about the potential risks and negative impacts of releasing ENMs into the environment is under investigation. For this reason, methodologies to estimate the probable mass concentrations of ENMs released in different regions of the world have been developed. As a first attempt to estimate the probable mass flows of nanosized titanium dioxide (nano-TiO2) released in Mexico, we developed a Probabilistic Material Flow Analysis (PMFA) for 2015.The model describes probabilistic mass flows of released nano-TiO2 during the life cycle of sunscreens, coatings, ceramic, and other nano-enabled products, including the flows through the solid waste and wastewater management systems, as well as the transfer of nano-TiO2 to three environmental compartments (atmosphere, topsoil, and surface water). The PMFA incorporates the uncertainty related to the input data. We observed that the most significant nano-TiO2 flows occur to the surface water, landfill, and soil compartments, targeted as the main “hot-spots”, where living organisms could be more exposed to this material. Further improvements in the model are needed due to some data gaps at some life cycle stages, for instance, solid waste management and reused wastewater manipulation for irrigation purposes. Finally, the model developed in this study can be adjusted to assess other ENM releases and can be beneficial for further investigation in fate modeling and environmental risk assessment.

Multi-criteria analysis of strategies towards sustainable recycling of phosphorus from sewage sludge in Austria

To promote optimal phosphorus (P) recovery from municipal wastewater and sewage sludge with viable legal instruments, it is imperative to understand the regional and national consequences of different legal requirements for recycling. In this study we develop a scenario-based analysis to assess the environmental and economic impact of different national P recovery strategies in the context of a detailed representation of the existing Austrian wastewater infrastructure. This assessment combines material flow analysis, life cycle assessment and life cycle costing and includes the indicators P recycling rate, P utilization degree, heavy metal removal rate, share of heavy metals’ content in wastewater redirected to agricultural soils, global warming potential, cumulated energy demand, terrestrial acidification potential, volume of freight transport and annual costs. The following main conclusions can be drawn. P recovery from ash shows the highest potential regarding the utilization of P from wastewater. A high P utilization from wastewater should rely on recovery technologies that decontaminate products, otherwise pollutant loads to agricultural soils might increase. P recovery to the extent of 60–85 % of P in WWTPs influent can be achieved by savings/costs of −0.8 to +4.7 EUR inhabitant−1 yr−1 in addition to current cost of the wastewater treatment/sludge disposal system. Key factors to be considered for costs are the choice of recovery process, revenues from products, and the use of existing incineration infrastructure. P recovery can lead to the reduction of greenhouse gas emissions in Austria if nitrous oxide emissions from sludge incineration are limited and efficient heat utilization strategies are implemented. There is a trade-off in terms of environmental and economic costs in choosing a more centralized or decentralized mono-incineration strategy.

Innovative Assessment of Mun River Flow Components through ANN and Isotopic End-Member Mixing Analysis

This study innovatively assesses the Mun River flow components in Thailand, integrating artificial neural networks (ANNs) and isotopic (δ18O) end-member mixing analysis (IEMMA). It quantifies the contributions of the Upper Mun River (UMR) and Chi River (CR) to the overall flow, revealing a discrepancy in their estimated contributions. The ANN method predicts that the UMR and CR contribute approximately 70.5% and 29.5% respectively, while IEMMA indicates a more pronounced disparity with 84% from UMR and 16% from CR. This divergence highlights the distinct perspectives of ANN, focusing on hydrological data patterns, and IEMMA, emphasizing isotopic signatures. Despite discrepancies, both methods validate UMR as a significant contributor to the overall flow, highlighting their utility in hydrological research. The findings emphasize the complexity of river systems and advocate for an integrated approach of river flow analysis for a comprehensive understanding, crucial for effective water resource management and planning.