Flow Modeling Research Articles

Cross-Scale Modeling of Shallow Water Flows in Coastal Areas with an Improved Local Time-Stepping Method

A shallow water equations-based model with an improved local time-stepping (LTS) scheme is developed for modeling coastal hydrodynamics across multiple scales, from large areas to detailed local regions. To enhance the stability of the shallow water model for long-duration simulations and at larger LTS gradings, a prediction-correction method using a single-layer interface that couples coarse and fine time discretizations is adopted. The proposed scheme improves computational efficiency with an acceptable additional computational burden and ensures accurate conservation of time truncation errors in a discrete sense. The model performance is verified with respect to conservation and computational efficiency through two idealized tests: the spreading of a drop of shallow water and a tidal flat/channel system. The results of both tests demonstrate that the improved LTS scheme maintains precision as the LTS grading increases, preserves conservation properties, and significantly improves computational efficiency with a speedup ratio of up to 2.615. Furthermore, we applied the LTS scheme to simulate tides at grid scales of 40,000 m to 200 m for a portion of the Northwest Pacific. The proposed model shows promise for modeling cross-scale hydrodynamics in complex coastal and ocean engineering problems.

CFD approach for determining the losses in two-phase flows through the last stage of condensing steam turbine

Analyzing and simulating wet steam flows within steam turbines holds significant importance, especially due to the presence of a liquid phase in the low-pressure stages of the turbine, resulting in consequential losses that demand careful consideration. Considering these conditions, this study employs advanced predictive CFD models to simulate the wet steam flow within the actual 3D geometry of the final stage in a 200 MW steam turbine, which is observed in the least research due to the complexity of modeling and analysis of three-dimensional flows. This advancement promises more precise and reliable results. Employing the ANSYS CFX software, this study engages in numerical simulations of steady-state compressible two-phase flow. Furthermore, the study offers practical equations to quantify the losses within the entire stage, which serves as a valuable metric for assessing loss levels and offers a benchmark for design improvements aimed at loss reduction. Based on the results, 10 % of losses occur along the stator and 1 % along the rotor, and a total of 11 % of losses occur along the entire stage. Finally, the efficiency of the stage is calculated to be 89 %. Steam condensation strengthens the shock waves, changes their location, diminishes Mach number and the flow velocity, and alters the flow angle. It reduces the efficiency of the turbine by 1.27 % and also reduces the work done by the turbine by 13.97 %. This emphasizes the significant influence of condensation on flow characteristics, emphasizing the necessity of conducting comprehensive investigations into this phenomenon.

Comparison Study Of BIM Modeling In Seismic Analysis For Different Building Functions Based on SNI 1726:2019

The research on optimizing Equivalent Motorized Passenger Car Unit (EMP) values for motorcycles in Jabodetabek addresses the pressing traffic challenges in Indonesia's largest metropolitan area. With rapid population growth and increasing motor vehicles, accurate traffic flow modeling is crucial. Motorcycles, dominant in Jabodetabek's transport, are often misrepresented by EMP values equivalent to cars, leading to inaccurate traffic estimates. Adjusting EMP values, especially in macroscopic modeling, is imperative for precise transportation planning. This study explores the necessity of recalibrating EMP values for motorcycles, crucial for sustainable development and future transportation technology integration. By analyzing traffic dynamics and adjusting EMP values, the research aims to provide more accurate depictions of traffic conditions, essential for effective policymaking and infrastructure planning. Results indicate a clear correlation between traffic density and motorcycle efficiency, emphasizing the need for tailored EMP values. This research offers insights for improving transportation planning and addressing future metropolitan traffic challenges.

Reduced-Order Modeling of Steady and Unsteady Flows with Deep Neural Networks

Large-eddy and direct numerical simulations generate vast data sets that are challenging to interpret, even for simple geometries at low Reynolds numbers. This has increased the importance of automatic methods for extracting significant features to understand physical phenomena. Traditional techniques like the proper orthogonal decomposition (POD) have been widely used for this purpose. However, recent advancements in computational power have allowed for the development of data-driven modal reduction approaches. This paper discusses four applications of deep neural networks for aerodynamic applications, including a convolutional neural network autoencoder, to analyze unsteady flow fields around a circular cylinder at Re = 100 and a supersonic boundary layer with Tollmien–Schlichting waves. The autoencoder results are comparable to those obtained with POD and spectral POD. Additionally, it is demonstrated that the autoencoder can compress steady hypersonic boundary-layer profiles into a low-dimensional vector space that is spanned by the pressure gradient and wall-temperature ratio. This paper also proposes a convolutional neural network model to estimate velocity and temperature profiles across different hypersonic flow conditions.

Research and improvement of the design of a sedimentation tank for hydropower and irrigation

The study is devoted to the analysis and optimisation of the design of the sedimentation tank to increase the efficiency of settling solid particles in hydropower and irrigation systems. Both experimental and numerical methods were used to analyse and optimise the design of sedimentation tanks to increase their efficiency in hydropower and irrigation systems. The study examined and analysed various types of sedimentation tanks according to design schemes, flow regime, deposition dynamics and sediment flushing methods, and also considered recommended improvements for hydropower and irrigation of various types of sedimentation tanks. During the study, it was revealed that optimising the geometry of the sedimentation tank significantly increases the efficiency of solid particle deposition. Experimental data have shown that changing the angle of inclination of the walls and increasing the area of the bottom of the sedimentation tank contribute to improving the deposition of silt and sand. It has also been found that the use of special turbulent inserts reduces the particle deposition time and improves the quality of treated water. Hydraulic flow modelling has confirmed that a more uniform velocity distribution in the sedimentation tank reduces turbulence and promotes more efficient particle deposition. The introduction of automated systems for monitoring and controlling the cleaning process has made it possible to increase the reliability and stability of the sedimentation tank. As a result, it was proved that the proposed design and technological changes can significantly increase the efficiency and durability of sedimentation tanks in hydropower and irrigation. The study provides practical recommendations for improving the design of sedimentation tanks, which helps to increase their efficiency and reliability in hydropower and irrigation, thereby improving water management

Correction: The Effect of LVAD Aortic Outflow-Graft Placement on Hemodynamics and Flow Implantation Technique and Computer Flow Modeling.

Correction: The Effect of LVAD Aortic Outflow-Graft Placement on Hemodynamics and Flow Implantation Technique and Computer Flow Modeling.

Robust modeling of material flows to end‐uses under uncertainty: UK wood flows and material efficiency opportunities

AbstractIn this study we quantify wood flows from raw materials to end‐uses for the United Kingdom in a robust way using a new material flow analysis (MFA) model with uncertainty. This is important to identify opportunities for efficiency given constraints on wood supply. We have developed a new “ProbPACTOT” MFA model which introduces a systematic method to handle mixed units during reconciliation and uncertainty in data observations, conversion factors, and process recipes. This makes it possible to track material flows all the way to end‐uses, which is otherwise difficult because the diverse materials, data types, and units used to quantify end‐products are hard to integrate into standard allocation‐based MFA models. We apply the model for the case of wood in the United Kingdom by defining 56 process recipes and reconciling 117 data observations from various sources. The results quantify upstream production and trade flows, through to 19 specific end‐uses of wood fibers. We use this to show the potential scale of savings by enhancing material efficiency; for example, if pallets were used 25% more intensively, 0.49 0.2 of wood fibers could be saved, corresponding to 4%–7% of the total soft sawnwood consumption of the United Kingdom. Judging the scale of opportunities for wood material efficiency in the United Kingdom is important domestically, and has global significance as the United Kingdom is the second largest net importer of wood products in the world. Moreover, this study proposes an important advancement in MFA giving a structure for modeling uncertain material flows up to end‐uses, applicable to any material. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.

"Machine Learning for Enhanced Heat Transfer: LMT-ABPNN Modeling of Hybrid Nanofluid Flow on a Vertical Plate"

"Machine Learning for Enhanced Heat Transfer: LMT-ABPNN Modeling of Hybrid Nanofluid Flow on a Vertical Plate"

Three-Dimensional Numerical Simulation of a Two-Phase Supercritical Open Channel Junction Flow

This study investigates the computational fluid dynamics (CFD) modeling of supercritical open channel junction flow using two different turbulence models: k-ω shear stress transport (SST) and k-ω SST scale-adaptive simulation (SAS), in conjunction with Volume of Fluid (VOF) and mixture multiphase models. The efficacy of these models in predicting the intricate free surface fluctuation and free surface elevation in a supercritical junction is evaluated through a comprehensive analysis of time-averaged free surface data obtained from CFD simulations and Light Detection and Ranging (LIDAR) measurements. The dimensionless Reynolds (Re) and Froude (Fr) numbers of the investigated scenario were Fr = 9 and Re = 5.1 × 104 for the main channel, and Fr = 6 and Re = 3.3 × 104 for the side channel. The results of the analysis demonstrated a satisfactory level of agreement with the experimental data. However, certain limitations associated with both CFD and LIDAR were identified. Specifically, the CFD performance was limited by the model’s incapacity to consider small-scale turbulent effects and to model air bubbles smaller than the cell size while the LIDAR measurements were limited by instrument range, inability to provide insight into what is happening below the water surface, and blind spots. Nonetheless, the k-ω SST turbulent model with the VOF multiphase model most closely matched the LIDAR results.

Structural Uncertainty Due to Fault Timing: A Multimodel Case Study from the Perth Basin.

Faults can fundamentally change a groundwater flow regime and represent a major source of uncertainty in groundwater studies. Much research has been devoted to uncertainty around their location and their barrier-conduit behavior. However, fault timing is one aspect of fault uncertainty that appears to be somewhat overlooked. Many faulted models feature consistent layer offsets, thereby presuming that block faulting has occurred recently and almost instantaneously. Additionally, barrier and/or conduit behavior is often shown to extend vertically through all layers when a fault may in fact terminate well below-ground surface. In this study, we create three plausible geological interpretations for a transect in the Perth Basin. Adjacent boreholes show stratigraphic offsets and thickening which indicate faulting; however, fault timing is unknown. Flow modeling demonstrates that the model with the most recent faulting shows profoundly different flow patterns due to aquifer juxtaposition. Additionally, multiple realizations with stochastically generated parameter sets for layer, fault core, and fault damage zone conductivity show that fault timing influences flow more than layer or fault zone conductivity. Finally, fault conduit behavior that penetrates aquitards has significant implications for transport, while fault barrier behavior has surprisingly little. This research advocates for adequate data collection where faults may cause breaches in aquitards due to layer offsets or conduit behavior in the damage zone. It also promotes the use of multiple geological models to address structural uncertainty, and highlights some of the hurdles in doing so such as computational expense and the availability of seamless geological-flow modeling workflows.

Advances in granular flow modeling: GPU-based multi-sphere DEM approach and tumbling mill dynamics

Modeling irregular-shaped particulate flow systems poses challenges, especially in mineral processing where accurate representation of particle shape is crucial for capturing macroscopic behavior. The multi-sphere approach, employing DEM, addresses this by approximating particles as overlapping spheres within GPU computing. This study validates particle flow dynamics using literature-based data, showcasing the model’s fidelity and GPU advantages. However, calibration and shape approximation limitations require careful consideration. A quaternion-based orientation method enhances DEM and validates experimental data from packing, hoppers, and tumbling mills. Simulations reveal how particle shape influences granular dynamics, affecting lift-off tendencies, responses to lifter face angles, and power draw trends with mill speed changes. Cubical and spherical particles exhibit orderly packing behavior, contrasting with irregular shapes. This investigation underscores the significant role of particle shape in granular dynamics and its implications for industrial processes.

The general patterns of water flow in loess slope system and implications for slope geological security

Loess regions face significant challenges in quantifying hydrological processes and assessing geological environmental risks due to the prevalent development of preferential pathways and the limitations of existing monitoring technologies. To advance this knowledge, this study presents an improved electrical resistivity tomography (ERT) device, specifically designed for loess moisture observations. By refining the testing principle, power supply mode, and data collection method within the existing ERT framework, the new device offers unmanned operation, automatic data acquisition, remote transmission, and cost efficiency. It effectively tracks water movement and groundwater level fluctuations across various hydrological conditions, supporting long-term online monitoring of hydrological processes of loess slopes. Through the analysis of monitoring data and classification of 12 observed preferential flow types, water movement in loess systems can be generalized into four general patterns: uniform infiltration, preferential infiltration, inflowing diffusion, and lateral flow. This generalized scheme provides a simplified modeling approach for other researchers to quantify slope hydrodynamics and to assess geological safety risks involving preferential flow. Based on these insights and field investigations, a conceptual framework is proposed to elucidate the seepage-structure synergistic initiating mechanism of loess landslides. This framework suggests that water entry and movement patterns within the slope depend on the slope geological structure related to preferential pathways and the prevailing hydrological scenarios. Landslide occurs as the result of the progressive failure and reciprocal evolution between the slope hydrological environments and geological structure, which may also pose potential eco-hydrological risks. The outcome advances the development of slope hydrological monitoring technology and enhances the understanding of water movement laws and the associated geological environmental risks in loess slope systems, which is of vital importance to the early warning methods of loess landslides that account for preferential flow and for theoretical modeling of preferential flow in related disciplines.

Coupling hydrological methods with ‘Flow Health’ to simulate ecological flow in the Weihe River Basin, China

AbstractReducing river flows significantly affects livelihoods, ecology and industrial production. Therefore, allowing for ecological flow requirements has been applied to limiting human water consumption and is incorporated into water allocation planning. However, the unavailability of ecological data greatly limits e‐flow studies and this lack of sufficient ecosystem data is mostly addressed by using hydrological metrics as surrogates of the river ecosystem. This study employed the nine indicators of the ‘Flow Health’ model to assess river hydrological health and explore optimal ecological flow regimes. The modelling estimated the required flow and the extra flood flows of ecosystem conservation under default and custom thresholds. Ecological flows were calculated for five stations of the Weihe River through coupling with three hydrological methodologies. The index of flow deviation indicated that the flow regimes in Weihe River have partially changed from the reference period. Fish and other aquatic habitats have changed by reduced flows, but the health of the floodplain ecosystem has not been seriously affected. The ecological flow modelling results showed that the extra flow required for the ecology restoration in five stations is concentrated from July to September. The optimal ecological flows in dry seasons by coupling three hydrological methods were less than the average current flow, which is reasonable. This coupling provides ideas on how environmental flow assessments are undertaken in similar regions.

Liquidate the collector in deformed oil modeling of non-isothermal flow in a horizontal well

In the article, an effective approximate solution to the determination of the flow formula in a horizontal well during non-isothermal percolation of fluid in the reservoir deformable layers is provided. The analysis of the conducted reports showed that in this case, the conclusions made in the literature regarding the non-isothermal filtration process are valid even when determining the ratio of the flow rate of the horizontal well to the flow rate of the vertical well. It was determined that the flow rate of a horizontal well in a deformed formation is less than the flow rate of a well from a non-deforming formation drainage at the same pressure drop.

Modelling spillway and weir operation during major overflows. On optical measurements in prototypes: pros and cons

At weirs and dams, the spillway flow is a high-velocity turbulent motion operating at very-large Reynolds numbers and physical measurements are challenging. In these high-speed free-surface flows, the upstream flow is not aerated and some air entrainment takes place downstream of the inception of free-surface aeration. The state-of-the-art knowledge in large dam spillway hydrodynamics currently reaches a major knowledge gap because of a lack of detailed quantitative field measurements in both the non-aerated and air-water flow regions. In this contribution, a review of prototype observations and measurements is presented based upon optical data sets conducted between 2010 and 2022 during floods at several large dam spillways in eastern Australia, with a focus on the key requirements for successful optical velocity measurements in high-velocity (prototype) spillway flows. The experience and expertise gained in these studies provide new insights into the operation of large dam spillways and their modelling. The intricacy of field measurement techniques is discussed using the experience at dam spillways during large floods, encompassing optical velocity measurements of spillway hydrodynamics at two structures. Overall, the paper presents current challenges on the modelling of large dam spillway flows.

Identifying hemodynamic factors associated with the rupture of anterior communicating artery aneurysms based on global modeling of blood flow in the cerebral artery network

Anterior communicating artery (ACoA) aneurysms are more prone to rupture compared to aneurysms present in other cerebral arteries. We hypothesize that systemic blood flow in the cerebral artery network plays an important role in shaping intra-aneurysmal hemodynamic environment thereby affecting the rupture risk of ACoA aneurysms. The majority of existing numerical studies in this field employed local modeling methods where the physical boundaries of a model are confined to the aneurysm region, which, though having the benefit of reducing computational cost, may compromise the physiological fidelity of numerical results due to insufficient account of systemic cerebral arterial hemodynamics. In the present study, we firstly carried out numerical experiments to address the difference between the outcomes of local and global modeling methods, demonstrating that local modeling confined to the aneurysm region results in inaccurate predictions of hemodynamic parameters compared with global modeling of the ACoA aneurysm as part of the cerebral artery network. Motivated by this finding, we built global hemodynamic models for 40 ACoA aneurysms (including 20 ruptured and 20 unruptured ones) based on medical image data. Statistical analysis of the computed hemodynamic data revealed that maximum wall shear stress (WSS), minimum WSS divergence, and maximum WSS gradient differed significantly between the ruptured and unruptured ACoA aneurysms. Optimal threshold values of high/low WSS metrics were determined through a series of statistical tests. In the meantime, some morphological parameters of aneurysms, such as large nonsphericity index, aspect ratio, and bottleneck factor, were found to be associated closely with aneurysm rupture. Furthermore, multivariate logistic regression analyses were performed to derive models combining hemodynamic and morphological parameters for discriminating the rupture status of aneurysms. The capability of the models in rupture status discrimination was high, with the area under the receiver operating characteristic curve reaching up to 0.9. The findings of the study suggest that global modeling of the cerebral artery network is essential for reliable quantification of hemodynamics in ACoA aneurysms, disturbed WSS and irregular aneurysm morphology are associated closely with aneurysm rupture, and multivariate models integrating hemodynamic and morphological parameters have high potential for assessing the rupture risk of ACoA aneurysms.

Dynamic evolution of temperature field, flow field, and solidification behavior during multilayer multitrack laser cladding

During multilayer multitrack laser cladding, secondary melting and solidification in the interlayer lap zone have a significant impact on the mechanical properties of cladding coatings. However, mathematical modeling of the melt flow and solidification behavior of multilayer, multitrack laser cladding interlayer lap zones is lacking. In this paper, a 3D finite element model was established to investigate the mass and heat transfer processes in both lap and non-lap zones during the laser cladding of multilayer multitrack Fe-Cr-based alloys on 45# steel surface. A dynamic grid is used to track the free surface of the melt pool, while the enthalpy method is used to simulate the solid-liquid phase transition. The change in thermophysical properties with temperature, as well as the change in laser energy and alloy powder flow density in the lap zone, were taken into consideration. The influence of the number of cladding layers on the heat and mass transfer in the molten pool, remelting, and solidification in the lap zone was investigated, along with its intrinsic mechanism. The results show that the model can accurately predict the size and microstructural change law of coating layers, including the grain size of the lap region between layers. The melt pool temperature and grain size increase with the number of cladding layers, while the convection and cooling velocities decrease. In addition, the grain size in the lap zone of the cladding is larger than that in the nearby non-lap zone. Using solidification parameters extracted from the solidification front of the molten pool, changes in grain size and morphology were predicted for both the interlayer lap and non-lap zones. The numerical calculation results were consistent with the experimental measurements.

Continuum modelling of size segregation and flow in dense, bidisperse granular media: accounting for segregation driven by both pressure gradients and shear-strain-rate gradients

Dense mixtures of particles of varying size tend to segregate based on size during flow. Granular size segregation impacts many industrial and geophysical processes, but the development of coupled, continuum models capable of predicting the evolution of segregation dynamics and flow fields in dense granular media across different geometries remains a challenge. One reason is because size segregation stems from two driving forces: pressure gradients and shear-strain-rate gradients. Another reason is the challenge of integrating segregation models with rheological constitutive equations for dense granular flow. In this paper we develop a continuum model that accounts for pressure-gradient-driven and shear-strain-rate-gradient-driven segregation, coupled to rheological modelling of a dense granular medium across the quasi-static and dense inertial flow regimes. To calibrate and test the continuum model, we perform discrete element method (DEM) simulations of dense flow of bidisperse granular systems in two flow geometries in which both segregation driving forces are present: inclined plane flow and planar shear flow with gravity. Steady-state DEM data from inclined plane flow is used to determine the dimensionless material parameters in the pressure-gradient-driven segregation model for both spheres and disks. Then, predictions of the continuum model are tested against DEM data across different cases of inclined plane flow and planar shear flow with gravity, while varying parameters such as the size of the flow geometry, the flow speed and the initial conditions. We find that it is crucial to account for both driving forces to capture segregation dynamics across both flow geometries with a single set of parameters.

Hierarchical thermal modeling and surrogate-model-based design optimization framework for cold plates used in battery thermal management systems

The continued advancement of battery-powered electric vehicles (EVs) towards higher energy and power densities poses significant thermal challenges for batteries. This work proposes a generalized design optimization framework for battery thermal management systems (BTMS), responding to the need for EVs with enhanced battery thermal performance, safety, and lifetime. This framework combines hierarchical thermal modeling and surrogate-model-based design optimization, explicitly tailored for liquid-cooled cold plates commonly used in EV BTMS. The hierarchical thermal modeling component decouples the battery cell, battery module, and cold plate models to reduce computational modeling costs while preserving the relative thermal performance of different cold plate designs. The design optimization component leverages our pioneer deep encoder–decoder hierarchical (DeepEDH) convolutional neural network surrogate modeling methodology to predict the cold plate’s full pressure, velocity, and temperature fields. Computationally efficient DeepEDH neural networks replace costly transient thermal simulations of cold plates and compute the objectives for evolutionary optimization using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). This work’s novel modeling and optimization framework produces optimal cold plate designs that consider battery-module-specific design features, including distributed battery cell heat generation, packaging materials, and heat-spreading characteristics. The proposed framework is evaluated through a cold plate design for modular BTMS, thoroughly assessing the impact of optimization objectives, flow path constraints, modeling assumptions, and design variable choices. The results demonstrate the effectiveness of the combined hierarchical thermal modeling and design optimization framework, with the optimized cold plates achieving reductions of 6.26K, 6.29K (22.7%), and 16.16Pa (18.7%) for maximum temperature, maximum temperature difference, and pressure loss, respectively. Moreover, compared to other methodologies that apply direct optimization without hierarchical and surrogate models, our approach significantly reduces the computational cost — from approximately 4800h to 13.5h. Our generalized multi-objective optimization framework is an effective and efficient design tool that can be leveraged to advance thermal management innovations for next-generation battery systems.

Modeling Pressure Gradient of Gas–Oil–Water Three-Phase Flow in Horizontal Pipes Downstream of Restrictions

Gas–oil–water three-phase slug flows in pipes commonly exist in the oil and gas industry as oil fields are becoming mature and water production is becoming inevitable. Although studies on multiphase flows in pipes have been ongoing for decades, most previous research has focused on gas–liquid or oil–water two-phase flows, with limited studies on gas–liquid–liquid flows. This leads to limited modeling studies on gas–liquid–liquid flows. One factor contributing to the complexity of the gas–liquid–liquid flow is the mixing between the oil and water phases, which have closer fluid properties and low interfacial tension. Restrictions or piping components play a crucial role in altering phase mixing. Unfortunately, modeling studies that consider the effects of these restrictions are limited due to the scarcity of experimental research. To address this gap, we conducted experimental studies on a gas–liquid–liquid flow downstream of a restriction and developed a new mechanistic modeling approach to predict the pressure gradient. Our model focuses on the flow pattern where the oil and water phases are partially mixed. This work emphasizes the modeling approach. The model evaluation results show that the model outperforms other existing models, with an average absolute relative error of 6.71%. Additionally, the parametric study shows that the new modeling approach effectively captures the effects of restriction size, water cut, and gas and liquid flow rates on the three-phase slug flow pressure gradient in horizontal pipes. Most previous slug flow modeling work assumes either a stratified flow or fully dispersed flow between the oil and water phases. This work provides a novel perspective in modeling a three-phase slug flow in which the oil and water phases are partially mixed. In addition, this novel approach to modeling the restriction effects on the pressure gradient paves the way for future modeling for different types of piping components or restrictions.