Steady Flow Model Research Articles

Design optimization of floating offshore wind farms using a steady state movement and flow model

Abstract In this study, we demonstrate how to carry out the design optimization of floating offshore wind farms by considering the impacts brought by the movements of the floating wind turbines. A steady state movement and flow model is applied in the modelling process. This model is developed by building a turbine surrogate model for estimating the steady state movement and power production of floating wind turbines and incorporating it in an open-source static wind farm simulator, PyWake. Using this modelling methodology, layout optimization problems of floating offshore wind farms are solved by using algorithms like Random Search to maximize the energy yield while satisfying certain constraints. Case studies are carried out for two wind farms with met-ocean conditions from a real planned site in Scottland to show the potential of layout optimization for floating wind farms.

Effects of steady flow and side hull layouts on motions and added resistance of a trimaran sailing in waves

As a high-performance ship, the trimaran holds significant potential in military and civilian fields. This study proposes a novel numerical method based on the Rankine panel method for predicting the time domain motion and wave loads of trimarans navigating in waves. This approach incorporates a more accurate steady flow model for trimarans and meticulously derives the boundary value problem for the unsteady disturbance potential, while retaining the steady terms related to steady flow throughout the process. This approach ensures a comprehensive consideration of the impacts of speed effect and ship wave. The method was innovatively validated using the trimaran hull form, and its accuracy and reliability were confirmed through comparisons with experimental data. Then, the influence of steady flow on time domain motions and added resistance of trimarans was thoroughly investigated. Comparative analysis of different steady flow models demonstrates that the steady flow model for trimaran proposed provides high precision and advantages in predicting the time domain motions of high-speed trimarans in waves. Furthermore, a systematic investigation into the effects of ship speed and side hull layouts on trimaran's motion and added resistance in waves has been conducted, offering crucial technical support for trimarans' seakeeping optimal solution selection.

Effect of flow modifiers on the fluid flow characteristics in a slab caster tundish

ABSTRACT In a slab caster tundish, controlling liquid steel flow is of paramount importance for clean steel production. A conventional tundish design consists of a pouring box, a weir and a dam. To improve the overall performance of a 40 ton slab caster tundish, three different arrangements by incorporating additional flow modifiers have been examined. A three-dimensional steady state fluid flow model has been developed using a RANS (Reynolds-Averaged Navier-Stokes) approach. Subsequently, transient scalar-transport equations were solved to obtain the C-curve of the tundish. A different approach has been followed to evaluate the inlet boundary condition to mimic the process conditions more accurately. The CFD predictions were validated with the results of the water model. Mean residence time, dead volume fraction and flow structures have been considered for evaluating tundish performance. All the proposed configurations have shown improvements in comparison to the base case. The mean residence time of the fluid was found to be the highest for the case having two pairs of weir and dam. However, the insights derived from the flow structures specifically plug flow in zone 2 and near the tundish outlet region suggest that that having a single weir and two dams is the optimal choice.

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.

Fluid-to-fluid similarity and CFD predictions of surrogate fluid as a replacement for R11 refrigerant used in a subcooled flow boiling analysis: Validation against reference experimental data

In this study, we present the possibility of substituting the primary fluid Freon 11 (CCl3F, R11) used in the experimental thermohydraulic test facility which offers the advantage to obtain phase change at relatively low heat fluxes and pressure if compared to water working fluid. Nevertheless, R11 is a CFC (Chlorofluorocarbures) part of the gases that contribute to the degradation of the ozone layer.For this purpose, four working fluids (non-CFC) are judiciously selected to replace the R11, namely the R123, R134a, R143a and CO2, and this through multidimensional Computational Fluid Dynamics (CFD) modeling of steady state flow boiling phenomenon. The calculation model covers a wide range of mass fluxes (435 – 1443 kg/m2s) and heat fluxes (1.2– 36 W/cm2); it predicts the heat transfer rates and transitions points for each flow regime. In this research, the experiment's data were compared to the outcomes of Ansys-CFX computations, using a steady Reynolds-Averaged Navier-Stokes (Steady-RANS) model, to investigate the best replacement refrigerant for R11. The turbulence effects on the mean flow and near wall are taken into consideration using the Shear Stress Transport (SST k-ω) turbulence model. The results from the four fluids were transposed to their water equivalent and compared to those deduced from the experimentation and correlations available in the literature to select the appropriate substitution fluid. The results qualitative and quantitative for vertical and horizontal subcooled boiling flow at the CHF location show that, the most effective surrogate fluid is R123 (HCFC), is still widely used in the refrigeration and air-conditioning industry, then R134a (HFC), then R143a (HFC).

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.

Physics-informed neural network for solution of forward and inverse kinematic wave problems

The one-dimensional kinematic wave (KW) model (KWM) is widely used in surface water and water quality hydrology as well as for modeling the movement of traffic on long highways. The KW model involves a first-order nonlinear partial differential equation which is solved numerically for realistic geometric representation, input, and initial and boundary conditions. This paper developed a method to solve the partial differential equation using a neural network structure, called the physics-informed neural network (PINN). The PINN was applied to solve the one-dimensional nonlinear KWM for forward and inverse problems. To enhance the accuracy and convergence and to suppress the spurious oscillation at the steep front, a technique with redistributed collocation points as an improved algorithm of PINN was employed. To deal with the fractional order of the nonlinear advection term, a stop-gradient technique was proposed. For validation, the KWM for steady and unsteady overland flow, and open channel flow without lateral inflow was analyzed for the forward problem. For the inverse problem, the unknown Manning coefficient was correctly computed, demonstrating the capability of the proposed algorithm for the identification of KWM parameters.

A numerical study of thermal and diffusion effects on MHD Jeffrey fluid flow over a porous stretching sheet with activation energy

The primary aim of this research work is to develop a mathematical model for the two-dimensional steady incompressible flow of a Jeffrey fluid over a vertical stretching sheet immersed in a Darcy porous medium. The combined effects of Soret and Dufour numbers, activation energy, viscous dissipation, thermal radiation, mixed convection, and Joule heating are included in the energy and concentration equations within this model. Using appropriate similarity variable transformations, the governing partial differential equations were altered into nonlinear ordinary differential equations and then solved numerically using the Runge-Kutta-Fehlberg method along with the shooting technique. The impact of various physical parameters on concentration, velocity, and temperature profiles is deployed through graphs. The velocity increased with a gradual increment in the values of the viscous ratio, thermal, and solutal stratification parameters, whereas the reverse trend was noticed for the magnetic strength. The temperature diminishes as the Prandtl number increases, whereas the opposite scenario exists for Eckert and Dufor numbers and radiation. The fluid concentration rises for a monotonic increment of the Soret number, while it reduces as the Schmidt number, activation energy, and reaction constraint escalate. The amplification of skin friction is observed with an increase in magnetic field strength, while it decreases with an increasing viscous ratio factor. The Nusselt number decreases as radiation increases and the Eckert number rises, but the opposite scenario occurs with increases in the Prandtl number. The Sherwood number is heightened by an increase in the Schmidt number, reaction, and activation energy factors. Moreover, the numerical values of skin friction and the Nusselt number are compared with the previously published work, demonstrating excellent agreement between the results.

Accelerate the numerical convergence of incompressible flows: Novel preconditioned characteristic boundary conditions

For the first time, the locally power-law preconditioning method (LPLPM) is used to formulate the preconditioned characteristic boundary conditions (CBCs). Then, it is implemented to solve the numerical modeling of unsteady and steady flows from viscous to turbulent regimes. The compatibility equations and Riemann invariants are mathematically derived and then utilized to the incompressible flow solvers as suitable boundary conditions. This method discretizes time derivative and governing equations' space terms by applying the four-stage, fourth-order Runge–Kutta method, and a finite volume, respectively. The preconditioning matrix in the LPLPM is automatically derived by local velocity sensors through a power-law formulation. The baseline k−ω is applied as an appropriate turbulence model. Several test cases are conducted around airfoils of Office National d'Etudes et de Recherches Aerospatiales, NACA0012 (National Advisory Committee for Aeronautics), and S809 at varied angles of attack of 0–20 and Reynolds numbers of 500 to 5.25 × 106 to examine the effectiveness and accuracy of the LPLPM employing preconditioned CBCs. A sensitivity analysis is also performed to examine how numerical parameters affect the simulation. The results show that using preconditioned CBCs in conjunction with LPLPM at the artificial boundary is precise, reliable, and computationally efficient in simulating viscous/turbulent flows. Furthermore, it is also concluded that the present approach considerably improves the convergence speed contrasted to the simplified boundary conditions.

Dynamic characteristics analysis and valve core optimization for second stage hydrogen pressure reducer of hydrogen decompression valve

As an important component of pressure management system, hydrogen decompression valve (HDV) is used in hydrogen fuel cell vehicles, hydrogen refueling stations, etc. The high-pressure difference causes severe pressure fluctuation. Thus, the HDV is composed of multi-stage pressure reducers. Specially, the outlet pressure from the HDV highly affects the pressure of fuel cell. The service life and operation condition of fuel cell is affected significantly by the HDV. This paper conducted the research of the second stage hydrogen pressure reducer (SHPR) of on-boarding hydrogen decompression valve. The force and dynamic characteristics of the valve core are obtained and the flow characteristic is analyzed through the steady and transient flow model. The results are shown that the fluid force and combined force on the valve core exhibit linear increase with inlet pressure and throttling area. The flow characteristics in the throttling gap exhibit similar distribution law under different throttling lengths and inlet pressures. The pressure-drop at entrance and exit of the throttling gap is drastic. Besides, the spring stiffness has a significant impact on the dynamic characteristics of the valve core. With the increase of spring stiffness, the dynamic characteristics change from unstable-state to stable-state under the sudden increase of inlet pressure. The larger spring stiffness initially causes displacement fluctuation of the valve core and then the valve core maintains a stable opening under the stable state. Finally, the optimized structure of valve core is proposed and the better stability of SHPR has been achieved. Meanwhile, there is no significant difference in flow performance but the dynamic characteristics are improved.

Research on the influence of fluid viscosity on the inlet flow parameters of wiped film molecular distillation

Wiped film molecular distillation is a kind of evaporation device with rotating scraping film structure, which is used to separate and purify viscous materials at molecular level. The feed pump of a wiped film molecular distillation is a centrifugal pump driven by a brushless DC motor. The fluid flow at the outlet has an important effect on the evaporation process. Based on the geometric model of the test pump generated by Gambit, the unsteady flow and head in the pump under optimal, low flow and shut off conditions were calculated, and the influence of liquid viscosity on the flow parameter pulsation behind the impeller, that is, inside the volute was investigated. The head calculated by unsteady flow model and steady flow model is compared with the experimental values. In addition, the calculated liquid velocity distribution during water transport is compared with the measured results of LDV in detail. The results show that the increase of fluid viscosity weakens the flow parameter pulsation behind the impeller of the feed pump and the flow separation tendency near the blade face.

Modeling and optimization of steady flow of natural gas and hydrogen mixtures in pipeline networks

We extend the canonical problems of simulation and optimization of steady-state gas flows in pipeline networks with compressors to the transport of mixtures of highly heterogeneous gases injected throughout a network. Our study is motivated by proposed projects to blend hydrogen generated using clean energy into existing natural gas pipeline systems as part of efforts to reduce the reliance of energy systems on fossil fuels. Flow in a pipe is related to endpoint pressures by a basic Weymouth equation model, with an ideal gas equation of state, where the wave speed depends on the hydrogen concentration. At vertices, in addition to mass balance, we also consider mixing of incoming flows of varying hydrogen concentrations. The problems of interest are the heterogeneous gas flow simulation (HGFS), which determines system pressures and flows given fixed boundary conditions and compressor settings, as well as the heterogeneous gas flow optimization (HGFO), which extremizes an objective by determining optimal boundary conditions and compressor settings. We examine conditions for uniqueness of solutions to the HGFS, as well as compare and contrast mixed-integer and continuous nonlinear programming formulations for the HGFO. We develop computational methods to solve both problems, and examine their performance using four test networks of increasing complexity.

Flood Hazard Mapping and Risk Assessment in Narayani River Basin, Nepal

Floods, earthquakes, forest fires, landslides, and other natural hazard are common in Nepal. Among them, the flood is one of the natural disasters and that occurred in the Narayani River basin. The Narayani River Basin's exposures and vulnerabilities are at danger from a flood catastrophe of this kind, hence this studies attempts to reduce and control the risk of flooding in order to better manage disasters. The factors of flood hazard, flood exposures, and flood vulnerability are investigated as part of the ward-level flood risk assessment, which aims to prevent and manage the flood disaster. The hydraulic model (HEC-RAS) for the 2018 flood event was used in this study to create the GIS- based modeling of the flood inundation maps. Additionally, it calculated the various return periods for floods in the river basin—5, 10, 25, 50, 75, and 100 years. Furthermore, the flood extent was confirmed using the flood map produced by the Google Earth Engine (GEE) using remotely sensed techniques. For Hydraulic modelling, ALOS/PALSAR Digital Elevation Model (12.5m.) spatial resolution was used. In addition, RAS-MAPPER generated the geometric data for the hydraulic modeling, which was then transferred into HEC-RAS. This data included the cross-section, flow route, streamline, and bank lines. On both sides of the river, the necessary Manning value "n" values were computed for every cross-section. The steady-flow models of the anticipated flood hydrographs were created using the hydraulic model. Google Earth Engine (GEE) flood maps generated from Sentinel-1C radar satellite data were used to validate the results for the 2018 flood events. When comparing the simulated result's flood inundation area with the remote sensing data's flood area, the overlap area for the 2018 flood event is 65%. Additionally, the flood area is verified. In addition, the hydraulic model generated flow conditions for 5, 10, 25, 50, 75, and 100 year return periods. The river basin's surface water level and flood extent are both progressively rising. In order to effectively manage and prepare for potential flood hazards in the study area, an analysis of the flood risk assessment was conducted by taking into consideration three primary factors: the flood hazard map, flood exposure, and flood vulnerability. The layers of the population, crops, schools, hospitals, and road network were all exposed to flooding, and the factors that determined flood vulnerabilities were literacy, urban area, and agecomposition (less than 14 and more than 65). The higher flood risk area was found in Ward number 1, 3, 4,16,18,26 of Bharatpur metropolitan, Gaindakot municipality ward number 1 and 12, 15 of Madhyabindu Municipality.

Stagnation point flow of magnetized convective nanofluid via porous stretchy surface subjected to ohmic heating and heat generation

ABSTRACT Nanotechnology is progressively deploying more complicated functional nanofluid materials that can be tweaked to improve efficiency. Motivated by these advances, the present simulation has aimed to generalize the steady flow models for nanofluid stagnation point flow through a porous stretchy surface. Additionally, the model enriches by incorporating the impacts of Brownian motion and thermophoresis because of the Buongiorno model process, heat generation and Ohmic heating. The fluid model transformation is done by adopting appropriate similarity variables, and the solutions to the set of ordinary derivative equations are computationally done by employing the Fehlberg Runge-Kutta scheme and the shooting method. The significant structural behaviour of the entrenched fluid quantities is presented graphically and deliberated in the discussion section. Also, some exciting engineering quantities are calculated and offered in tabular form. As revealed, the nanoliquid velocity decays for large numbers of modified convective and magnetic terms. The heat generation, dissipation, magnetic and radiation terms augmented the nanoliquid thermal dispersion. The reverse impact is detected on the heat transfer field and species distribution with rising Brownian movement term. An increasing heat source inspired the thermal gradient along the boundary domain. Finally, to support the current findings, a result verification is conducted with the existing method, which portrays the correctness of the solution approach.

Assessment of Manning coefficient for Dujila Canal, Wasit/-Iraq

Abstract Assessment of Manning’s unevenness factor is of critical significance in hydraulic readings of open channel stream. Manning’s ( n n ) is obligatory for the computation of releases, water levels, and backwater curves, as well as plan curve additions. The correct value of Manning’s roughness coefficient ( n n ), i. H. a value that accurately reflects the observed data, is selected by the calibration process. The current study aims to calculate the Manning coefficient of the Dujila Canal due to this factor helps in developing water management systems, the Dujila Canal (a branch of the Tigris River) was modeled using the Hydrologic Engineering Center River Analysis System steady-flow model to guess the rate of Manning’s factor. The information was reserved for seven cross sections for calibration, then another cross section is applied for the verification process. A statistical test on the recorded data must be used to verify the calibration process. It uses the Root Mean Square (RMS) test. The outcomes show that the appropriate Manning’s ( n n ) rate was (0.025), providing a reasonable arrangement amid the designed and perceived sketches

The Significant Effect of Hydromagnetic on Carbon Nanotubes Based Nanofluids Flow and Heat Transfer Past a Porous Stretching/Shrinking Sheet

The 2D steady flow model of carbon nanotubes-based nanofluids and heat transfer past a porous stretchable or shrinkable sheet is studied analytically and numerically. A mathematical model that is governed by a system of partial differential equations (PDEs) subjected to boundary conditions is transformed into a system of dimensionless ordinary equations (ODEs). The non-dimensional ODEs system is solved using MATLAB bvp4c solver. The effect of various parameters such as magnetic field, porosity, the stretching/ shrinking velocity parameter, and CNTs volume friction on velocity and temperature profile, skin friction, Nusselt number and heat transfer rate are investigated numerically and the results are presented using graphical illustration. From the results, non-unique solutions are obtained in the cases where the sheet is shrunk, the magnetic parameter less than 0.1, or the porosity parameter is less than 30. Besides, the increment of magnetic field into the flow will increase both the skin friction and the heat transfer coefficient, while on the contrary, the decreasing in both the skin friction and the heat transfer coefficient will occur if the porosity parameter is raised. We are also showing that SWCNTs is more effective both in the skin friction and the heat transfer coefficient compared to MWCNTs.

Effect of external magnetic field on realistic bifurcated right coronary artery hemodynamics

Diagnostic technology based on magnetic fields is commonly used in medicine for diagnosis and therapy. However, the exposure to strong electromagnetic fields has adverse outcomes in patients. Thus, the objective of the current study is to investigate the effect of applying external uniform magnetic fields on the blood flow in both healthy and diseased cases of right coronary artery and determine the safe values of the applied magnetic field strengths. The diseased cases include a 40% stenosed artery along with two blood disorder cases with a hematocrit level of 20% and 60%. A comprehensive three-dimensional steady non-Newtonian flow model is developed using the Casson model to investigate the effect of the magnetic field on both shear rate and hematocrits. The model is numerically simulated at different values of magnetic field strengths and its orientation. The results indicated that the magnetic field in the Y-direction has a dominant effect compared to other directions. Moreover, the maximum increase in the main branch mass flow rate fraction is about 6.2%. Another interesting finding is that the wall shear stress is slightly affected by the magnetic field strength. For the stenosed case, it is found that the high magnetic field strengths can reduce the formulation of the vortices and hence reduce the risk of thrombosis, which agrees with published works. Additionally, the obtained results confirm that using a magnetic field up to 11.7 T, which is used in magnetic resonance imaging devices, is safe, and has a slight effect on blood flow parameters such as the wall shear stress.

Gyrotatic microorganisms analysis for radiative 3D Carreau nanofluid flow configured by activation energy and viscous dissipation

Nanoparticles and Bioconvection with microorganisms have inclusive and widespread of applications in the specialty of engineering, bioinformatics, biotechnology, mechanical energy and biosensors. Likewise, widespread utilization in diverse industries for-instance, geothermal technology, bio-medical, microelectronics, mechanical-chemistry, solar cells, chlorofluorocarbons toward nuclear reactors and exploitation, together along product degeneration, nuclear reactor chilling, oil emulsification and the thrust in the thermal conductivity accomplishment of the fluid, nuclear plant cooling has flourish an contemporary area for scientists and research scalars. The foremost manifesto of the existing investigation is to provide mathematical modeling and numerical simulation of the three-dimensional steady Bioconvection flow of Carreau nanofluids under the impact of nonlinear radiation and gyrotactic microorganisms. Furthermore, magnetohydrodynamic, activation energy and mixed convection inspirations are also measured. We constrained boundary layer theory to advance the basic PDEs for microorganism field, nanoparticle concentration, energy, momentum and mass, and thus condensed to extremely nonlinear ODEs by using the variable transformations. To scrutinize the problem, we acquired the numerical solution for present study with the help of bvp4c, a MATLAB practice. Graphical along with numerical consequences for the Sherwood number, density number of microorganism and wall heat transfer are as well accompanied. It is fascinating to note that microorganism field has been expanded due to having higher estimates of the bioconvection Peclet number and bioconvection Rayleigh number. It is also illustrated that higher values of heat generation/absorption parameter deteriorate the fluid temperature.

Magnetohydrodynamic flow of Copper-Water nanofluid over a rotating rigid disk with Ohmic heating and Hall Effects

In this article, a steady flow model is developed and analyzed for a water-based nanofluid that is generated by a rigid circular disk undergoing uniform rotation. Copper nanoparticles have been used for the analysis. Region over the plate is considered porous possessing uniform porosity whereas a uniformly impinged magnetic flux is assumed in the axial direction. Considerations of Hall currents and Ohmic heating are undertaken. To simplify the problem at hand, similarity transformations are utilized to transform it into a set of ordinary differential equations (ODEs), which can be more easily solved. Additionally, no-slip conditions are enforced at the boundary of the rigid disk. Numerical solutions for resulting nonlinear system are obtained via shooting method and are presented graphically for the detailed analysis. Results indicate that for magnetohydrodynamic flow with Hall effects through a porous medium, there is a direct proportion between axial velocity and volume fraction of copper-nanoparticles. Also, as the concentration of nanoparticles in the nanofluid increases, there is a corresponding increase in the temperature of the fluid. Additionally, at higher values of the Hall parameter, the impact of the Hartman number on flow variables is reduced.

Heat variation on MHD Williamson hybrid nanofluid flow with convective boundary condition and Ohmic heating in a porous material

The aim of the present study is to explore the variation of heat on MHD Williamson hybrid nanofluid (Ag-TiO2/H2O) model for steady two-dimensional and incompressible flow with a convective boundary condition in a curved coordinate porous system with Ohmic heating. Nusselt number is distinguished by the process of thermal radiation. The partial differential equations are controlled by the curved coordinate’s porous system, which depicts the flow paradigm. Employing similarity transformations, the acquired equations were turned into coupled non-linear ordinary differential equations. The governing equations were disbanded by RKF45 via shooting methodology. The focus is on examining physical characteristics such as heat flux at the wall, temperature distribution, velocity of flow, and surface friction coefficient for a variety of related factors. The analysis explained that increasing permeability, Biot and Eckert numbers enhance temperature profile and slowdown heat transfer. Moreover, convective boundary condition and thermal radiation enhance the friction of the surface. The model is prepared as an implementation for solar energy in processes of thermal engineering. Morever, this research has enormous applications in the industries of polymer and glass, also in the field of heat exchangers styling, cooling operations of metallic plates, etc.