Numerical Computational Fluid Dynamics Research Articles

Multiphase Numerical CFD Simulation of the Hydrothermal Liquefaction Process (HTL) of Sewage Sludge in a Tubular Reactor

This article presents multiphase numerical computational fluid dynamics (CFD) for simulating hydrothermal liquefaction of sewage sludge in a continuous plug-flow reactor. The discrete particle method (DPM) was used to analyze the solid particles’ interaction in liquid–solid high shear flows to investigate coupling computational fluid dynamics (CFD). Increasing solid particles’ interactions were observed with the increasing liquid velocity. The study examined the influence of parameters such as flow rate, temperature, and residence time on the efficiency of bio-oil production. An increase in temperature from 500 to 800 K caused an increase in the amount of biocrude oil produced from 12.4 to 32.9% within 60 min. In turn, an increase in the flow rate of the suspension from 10 to 60 mL/min caused a decrease in the amount of biocrude oil produced from 38.9 to 12.9%. This study offers insights into optimizing the flow channel of tubular reactors to enhance the HTL conversion efficiency of sewage sludge into biocrude oil. A parametric study was performed to investigate the effect of the slurry flow rate, temperature, and the external heat transfer coefficient on the biocrude oil production performance. The simulation data will be used in the future to design and scale up a large-scale HTL reactor.

Optimizing air inlet designs for enhanced natural ventilation in indoor substations: A numerical modelling and CFD simulation study

This paper investigates the ventilation and heat dissipation performance of a 110 kV indoor substation under natural ventilation conditions using computational fluid dynamics (CFD). The objectives are to evaluate the influences of air inlet design parameters including location and size, and transformer load, on the airflow distribution, temperature field, and cooling efficiency. The study finds that staggered opposite inlets optimize cooling uniformity without airflow attenuation. Compared to a single inlet, the maximum transformer temperature is reduced by 1.3 °C and energy utilization increases by 9.1 % with staggered inlets. Increasing the inlet length ratio initially improves cooling until an optimal point (The length ratio is 1.10), while reducing the inlet height ratio decreases airflow and efficiency. With load increasing, the intake airflow rises but at a reduced rate, and the temperature difference can exceed 15 °C under high loads. In summary, optimizing inlet design enhances natural ventilation performance in indoor substations, but limitations exist at high loads, indicating supplemental mechanical ventilation may be required.

A shape-predictive model for the spreading of photo-curable polymers in material extrusion additive manufacturing

Recently, there is a growing interest in material extrusion to print thermoset resins to manufacture large format and high-performance parts. However, the fidelity and mechanical integrity of the printed parts are limited by challenges such as uncontrolled spreading of individual beads (filament/droplet) after deposition and during cure. There is a considerable lack of experimental and theoretical studies on the spreading of reactive beads on solid substrates. In this work, we studied the simultaneous spreading and photo-curing of the photopolymerizable thermoset beads via experiment and numerical simulations. We used a novel experimental setup to track the spreading of droplets and filaments during photopolymerization and validate a moving mesh computational fluid dynamics (CFD) model. The CFD model was used to develop an approach (predictive model) to accurately predict the final spreading coefficient of cured resin beads without the need for full numerical simulations. The predictive model combines the generalized theory of a Newtonian spreading filament with a characteristic viscosity μave and time to gelation, τgel. Interestingly, μave is shown to be a material parameter that does not depend on processing conditions, but only on the material’s chemorheology. The predictive model is tested against a wide range of chemorheology and cure kinetic parameters and found to be in excellent agreement with the full numerical CFD simulations. This work will be very useful in estimating the final shape of beads during the material extrusion printing process, as well as a model to successfully parameterize extrusion-based 3D printers to control the shape of printed beads a-priori.

Large eddy simulation of aerodynamic wind pressure on a tall rectangular building by modified synthetic volume forcing method

To accurately predict wind pressures on a tall building by numerical Computational Fluid Dynamics (CFD) using the Large-Eddy Simulation (LES) turbulent model, it is essential to generate inflow with realistic turbulence characteristics. The Discretizing and Synthesizing Random Flow Generation (DSRFG) method, as one of the synthetic Fourier methods, has received significant attention in the Computational Wind Engineering (CWE) community because of its ability to strictly satisfy the continuity condition and generate turbulent wind with the desired power spectra. In traditional LES, the desired turbulent wind is normally generated and specified at the inlet. However, this treatment often leads to significant attenuation in turbulence energy in the high-frequency band of the fluctuating wind speed spectrum along the flow direction and unrealistic large-amplitude wind pressure fluctuations, resulting in unsatisfactory prediction performance. The Synthetic Volume Forcing (SVF) method effectively overcomes these limitations by introducing turbulence as volume force into the moment Navier-Stokes (N-S) equations. In this study, the DSRFG method is applied to generate a fluctuating wind field in combination with the SVF method to simulate dynamic wind pressures on a tall rectangular building through open-source software OpenFOAM. The turbulence intensity amplification factor (TIAF) is introduced in the SVF method to further improve its simulation accuracy. Comparison of results with wind tunnel test results verifies that the proposed TIAF-SVF numerical method developed in this study achieved sufficient accuracy in predicting wind pressures on tall buildings.

3D Numerical Model Validation Using Experimental Test Data for Patrind Hydropower Project

Whilst numerical modelling is commonly used for simulation to check the design of water conveyance, sluicing and spillway structure design, the numerical modelling has rarely been compared with the physical model tests. The objective of this research presented in this paper was to examine the validity and suitability of the numerical computational fluid dynamics (CFD) modeling method within an ANSYS Fluent/CFD R 18.2 software and compare its results with a fully instrumented and well-run physical model test at the 1:45 scale, carried out for Patrind Hydropower Project located in Pakistan. The physical model test was conducted for confirmation and optimization of a natural de-sanding basin, and diversion of suspended sediment-rich flood waters using a bypass tunnel. The numerical simulation was able to reproduce physical model test results and data gathered over a 7-year project operation to an acceptable level of accuracy. A detailed explanation of the approach used in numerical modelling together with analysis of simulation diagrams of ANSYS Fluent/CFD is also presented. The research shows that a 3D numerical model with accurate boundary conditions and mesh size can replace the need for physical model tests.

Numerical and experimental investigation of aerodynamic noise from a cooling fan in a turbulent flow

The investigation into aerodynamic noise arising from rotating surfaces bears significant practical implications. Among these, engine cooling fans have persistently been identified as primary contributors to vehicle noise. This study aims to provide a deeper comprehension of the complex unsteady flow dynamics surrounding an automotive cooling fan and its consequential impact on the generation of aerodynamic noise. Prediction of sound generated from fluid flow, despite its difficulty, can be simulated using modern numerical techniques and computational fluid dynamics (CFD). This research undertakes both numerical and experimental investigations. The experiment involves evaluating fan pressure against mass flow rate at 1500 rpm, while aerodynamic noise assessment transpires at two rotational speeds of 1500 rpm and 2500 rpm. Empirical sound pressure level data of the fan is meticulously captured using the requisite measurement apparatus. In addition, numerical investigations of the aerodynamic noise of an automotive cooling fan based on computational fluid dynamics and computational aeroacoustic (CAA) method have been performed. Initially, a steady-state aerodynamic simulation is carried out, followed by the simulation of the flow field through the application of the improved delayed detached eddy simulation (IDDES) formulation. The pressure rise of the fan versus the mass flow rate is obtained. The satisfactory concurrence observed between the simulation outcomes derived from the numerical method and the experimental dataset stands as notable validation. For the aeroacoustic computation, the Ffowcs Williams-Hawkings model is invoked to deduce sound pressure levels at specific flow points. The broadband noise sources model is also used to obtain the sound power level on the blade surface. Conclusively, it emerges that maximal noise manifestation occurs at a 90° degree angle, corresponding to the hub’s frontal orientation, with discernible dominance of tonal noise within lower frequency ranges (sub-1000 Hz).

Influence of structural parameters of descaling nozzle on jet behavior

Compared to alternative descaling methods, the high-pressure water descaling technology offers cheaper costs and higher descaling rate, which has obvious advantages. As a key component, the descaling nozzle will have a direct impact on the descaling effect. Based on the detailed study of the traditional U-shaped and V-shaped grooving methods, this paper discovered a conical curve grooving method where the grooving curve shape factor lies between those of the two aforementioned methods, and established a full-scale model of the descaling nozzle. For the conical groove nozzle, numerical Computational Fluid Dynamics (CFD) simulations were performed using the shape factor of the groove curve between 0 and 1 and the throat diameter between 2.1 and 2.4 mm. It has been determined that a descaling nozzle with the shape factor between 0.75 and 0.9 has superior dynamic performance, and that when the throat diameter is between 2.3 and 2.4 mm, the nozzle has a higher outlet average velocity and a reasonable outlet flow rate. In conclusion, the dimensionless functional relationship between taper shape factor, throat diameter, nozzle outlet average velocity, effective descaling width and area is established in order to provide certain theoretical support for various production requirements of nozzles.

A Probabilistic Approach to Turbine Uncertainty

Abstract Efficiency is an essential metric for assessing turbine performance. Modern turbines rely heavily on numerical computational fluid dynamics (CFD) tools for design improvement. With more compact turbines leading to lower aspect ratio airfoils, the influence of secondary flows is significant on performance. Secondary flows and detached flows, in general, remain a challenge for commercial CFD solvers; hence, there is a need for high-fidelity experimental data to tune these solvers used by turbine designers. Efficiency measurements in engine-representative test rigs are challenging for multiple reasons; an inherent problem to any experiment is to remove the effects specific to the turbine rig. This problem is compounded by the narrow uncertainty band required to detect the incremental improvements achieved by turbine designers. Efficiency measurements carried out in engine-representative turbine rigs have traditionally relied upon assumptions such as constant gas properties and neglecting heat loss. This research presents an uncertainty framework that combines inputs from experiments and computational tools. This methodology allows quantifying uncertainty for high-fidelity efficiency data in engine-representative turbine facilities. This paper presents probabilistic sampling techniques to allow for uncertainty propagation. The effect of rig-specific effects, such as heat transfer and gas properties, on efficiency is demonstrated. Sources of uncertainty are identified, and a framework is presented which divides the sources into bias and stochastic. The framework allows the combination of experimental and numerical uncertainty. Gaussian regression models are developed to obtain speed-lines for the turbine map using the uncertainty of the measured efficiency.

Experimental and Numerical Study for Gas Release and Dispersion on Offshore Platforms

Accidental gas release is a major triggering event for the offshore oil and gas industry. This paper focuses on the experimental and numerical investigation for dispersion behavior of released gas on offshore platforms. For this purpose, an experimental system is designed and developed to investigate gas release and dispersion. A series of experiments are carried out, among which the scenarios with constant leakage rates and time-varying leakage rates are both emphasized. The gas concentrations at different sampling points are obtained to study the dispersion behavior and accumulation characteristics of the released gas. Furthermore, a numerical computational fluid dynamics model is established to replicate the experimental scenarios. Good agreement between experimental data and CFD simulation results is observed by calculating a series of statistical performance measures. The developed numerical model is subsequently utilized to investigate a gas release scenario on a practical offshore platform, in which a fully transient leakage rate is adopted considering the response of process protection measures. The developed numerical model could provide support for risk assessment and optimization of contingency plans against gas release accidents in offshore facilities.

Optimization Layout and Aerodynamic Performance Research on Double Nautilus Vertical-Axis Wind Turbine

The double vertical-axis wind turbine (VAWT) system serves as a high-performance design solution. The Nautilus wind turbine investigated in this research imitated the structure of a Nautilus shell and is a vertical-axis drag-type wind turbine that exhibits relatively low efficiency. Therefore, the improvement of its wind energy efficiency is of paramount importance. This paper utilizes Computational Fluid Dynamics (CFD) software, based on the Reynolds-averaged Navier–Stokes equations and dynamic meshing techniques, to conduct numerical investigations on the aerodynamic performance of the Nautilus wind turbine array layout. The effects of wind direction, spacing ratio, and rotation direction are individually studied, and the interpretations and explanations are provided based on flow field characteristics. The results show that when the wind direction is 90°, i.e., a transverse layout, the closer the spacing between the transverse turbines, the higher the average power coefficient of the entire wind turbine system, with little effect from the three rotation directions. The maximum average power coefficient reached 28.9% and the power gain factor (TPGF) reached 11.1%. The enhancement effect primarily originates from the wake interaction among neighboring turbines. The experimental results showed a deviation of 8.1% compared to the CFD simulation results, thus validating the accuracy of the numerical CFD modeling. Ultimately, several array layouts are proposed, based on the prevalent wind direction and spacing ratio research. The enhancement of the wind turbine array’s situation could significantly increase the average efficiency of the entire wind turbine cluster. Consequently, this study provides a reference for the practical application of biomimetic vertical-axis drag-type wind turbine systems in actual engineering.

Numerical Simulation and Computational Fluid Dynamics Analysis of Two-Dimensional Lid-Driven Cavity Flow Within the Weapon Bay of an Autonomous Fighter Drone

The efficient deployment of weapons in military operations is critical for mission success, and the flow of air within the weapon bay of an autonomous fighter drone plays a vital role in achieving this objective. In this paper, we present a comprehensive numerical simulation and computational fluid dynamics (CFD) analysis of the three-dimensional lid-driven cavity flow within the weapon bay of an autonomous fighter drone. To address this challenging problem, we employ CFD analysis and a multigrid approach to solve the Navier-Stokes equations for the aerodynamic problem. Our simulations include high Reynolds numbers of up to 10,000, which demonstrates the potential of CFD analysis in optimizing the design of autonomous fighter drones for military operations. We evaluate the effectiveness of the linked strongly implicit multigrid technique in estimating high-Re fine-mesh flow solutions using the vorticity-stream function formulation of the two-dimensional incompressible Navier-Stokes equations. The model issue is the driven flow in a square cavity, and we consider meshes up to 1024 x 1024 points and combinations with Reynolds numbers as high as 1000. To further improve the accuracy of our simulations, we employ one-dimensional grid clustering coordinate transformations instead of uniform mesh refinement, as the flow field exhibits one or more secondary vortices. Our findings demonstrate that CFD analysis can provide valuable insights into the complex flow dynamics within the weapon bay of autonomous fighter drones, which can lead to the optimization of their design for enhanced mission capabilities. Overall, our study highlights the significance of numerical simulations and CFD analysis in the design and optimization of autonomous fighter drones for military applications. Our results can serve as a basis for future research in the field of UAV aerodynamics and contribute to the development of more efficient and effective military operations.

Quantification of uncertainty in linear wave energy hydrodynamic models from experimental data

Considerable testing and modeling are required in order to fully realise, efficiently develop, and successfully industrialise the wave energy converters (WECs). Numerical modeling, full-scale measurements, and scaled prototype testing are the various methodologies that can be applied to model WECs and predict the dynamic response. Mathematical WEC models form the basis of model-based energy maximising control and directly affect the ability of model-based controllers to maximise energy capture. Linear WEC models are attractive in leading to simpler control designs, but may not cover the complete operational space. One solution is to identify a range of linear models at different operating points, which give a measure of the underlying nonlinear behaviour [1], [2]. This model set can then be used to extract a nominal model, and an associated uncertainty region, which can be used as a basis for a robust WEC controller synthesis process, such as articulated in [3].
 Recently, such an approach has been adopted using data generated from a high-fidelity numerical computational fluid dynamics (CFD) model [4]. However, numerical wave tanks (NWTs) and physical wave tanks differ significantly in terms of the range of tests which can be performed, and the contamination which can affect the measurements used to determine the data-based models e.g. measurement noise, numerical effects, wave reflections, etc [5]. As a result, the determination of nominal models and uncertainty regions in a physical wave tank may provide some advantages (and disadvantages) which need to be examined carefully. In addition, the range of post-processing techniques which could, or should, be applied to the different experimental/numerical domains, to improve the fidelity of the identified models, may differ between domains.
 In this paper, experimental testing of a WEC, by recreating a wave field similar to real-life conditions and a small-scale version of the device, is used to understand the hydrodynamic behaviour and to obtain an accurate dynamic model for WECs, which are considered to be essential towards optimal WEC design. Physical wave tank experiments, even though having their own disadvantages, overcome some difficulties of CFD-based NWT experiments, most notably huge computation time, problems in accurate representation of viscous fluids, uncertainty in the specification of an appropriate turbulence model, and propagation of incident waves [6]. 
 In this study, representative linear models of a point-absorber type WEC from a physical wave tank in the wave basin at Aalborg University are determined which give insight into the system dynamics and provide a basis for robust control of WECs. Among different stimulation techniques to excite the system dynamics in physical wave tank tests, the particular types of excitation signals covering the complete range of frequencies and amplitudes of the system dynamics, while considering limitations on the range of excitation signals or the wave tank reflections, are adopted for the determination of representative linear models. Moreover, a full investigation is carried out to ascertain the appropriate post-processing needed to optimise the signals as the basis for model identification. The model identification includes the non-parametric frequency response by means of empirical transfer function estimate (ETFE). 
 

Numerical investigation of the effect of altitude on diesel engine combustion and soot emissions

It is increasing concerned that the plateau environment will potentially increase fuel consumption in engines. Despite this, the current state of research on high altitude engines is still inadequate in providing sufficient and detailed information to counteract the decrease in engine efficiency. In addition, one of the novelty of this study was that the investigated altitudes is up to 4500 m, of which the previous studies was limited. Therefore, this study aims to investigate the effect of altitude on in-cylinder spray, combustion, and soot formation processes in diesel engines. A calibrated three-dimensional (3D) computational fluid dynamics (CFD) model of a single-cylinder, four-strokes, direct injection (DI) compression ignition, intake boost research diesel engine is established. The numerical CFD model used in this study has been validated through comparison with experimental data. It effectively investigates the in-cylinder activities and provides insights into the causes behind combustion and soot emission deterioration. The simulation is operated at altitudes of 0, 1500, 3000, 4500 m with corresponding intake pressure. It has been observed that engine performance and soot emissions deteriorate as altitude increases, and a sharp drop occurs when the altitude exceeds 3000 m, which can be attributed to the dramatic decline in combustion efficiency. The extended spray leads to a decrease in air utilization, which ultimately results in a sudden drop in combustion efficiency at altitudes above 3000 m. Overall, this study has identified that the extended penetration of the spray, caused by reduced pressure and air density, leads to poor air utilization, resulting in decreased performance and increased emissions. Hence, it is recommended that optimization of the combustion chamber geometry and injection strategies of diesel engines operating at high altitudes be undertaken to improve air utilization and combustion quality. This will serve as an avenue for further research in the future.

Experimental and Numerical CFD Modelling of the Hydrodynamic Effects Induced by a Ram Pump Waste Valve

The hydraulic ram pump or hydram is a machine capable of lifting water to a hydraulic head higher than the level of the supply source. It is a sustainable and self-sufficient device: the working principle is based on the rise of abrupt pressure variations occurring in the feeding pipeline when the liquid inside it undergoes a locally sharp change in velocity as a consequence of the sudden closure of the waste valve. Invented in 1772, the pump has been improved over the decades. Due to its simplicity, low cost and reliability, it has been widely used worldwide to provide adequate domestic water supplies, especially before the spreading of electricity and internal combustion engines. In recent years, the new attention placed on sustainability and energy transition from fossil fuels to renewable energy devices has brought a growing interest to this basic machine, essentially forgotten and abandoned in the last century; it seems promising especially in developing countries. The hydram is, in fact, a very simple machine, with only two moving parts, the waste and delivery valves. The efficiency of the hydraulic ram pump is mainly influenced by the characteristics of the waste valve. However, sufficient data are not available for the design of the hydram and the waste valve. In this work, the behaviour of the waste valve of a hydram was simulated by means of Computational Fluid Dynamics (CFD). Velocity and pressure values were analysed for different scenarios with different closing times of the valve. The data obtained from the developed numerical model were compared, in order to verify the validity of the simulations, with those collected during the operation of the hydram placed at the Laboratory of Environmental and Marine Hydraulics (LIDAM) of the University of Salerno, Italy. The numerical model thus obtained can, therefore, be used to identify the ideal configuration of the valve in order to ensure the best performance of the hydram.

Effects of Volute Structure on Energy Performance and Rotor Operational Stability of Molten Salt Pumps

A double-volute molten salt pump with two outlet pipes is proposed based on the original pump model. A numerical approach coupling finite element analysis and computational fluid dynamics (CFD) is implemented to investigate the operational stability and energy performance of two molten salt centrifugal pumps for high-temperature molten salt. The entropy production of the single-volute and double-volute molten salt pumps is investigated. The effects of the volute structures on the mechanical behavior of the impeller and shaft are considered. According to the findings, the local entropy production in the molten salt pump is dominated by the local pulsating entropy production (Spro-T), with the double-volute scheme achieving reduced energy loss. A visualization of the flow field and the local entropy production rate (LEPR) distributions indicate that the LEPR is positively correlated with the complexity of the flow, and higher levels of turbulence intensity lead to greater LEPR. The double-volute scheme enhances the complexity of the flow in the impeller, resulting in an increase in the LEPR compared with the single-volute design. However, the LEPR in the whole double-volute molten salt pump is reduced compared with the single-volute design. It is discovered that the double-volute molten salt pump experiences a less radial hydraulic force. Although the double-volute design has a slightly higher maximum equivalent stress on the impeller than the single-volute scheme, the rotor deformation is significantly less. In general, the double-volute scheme reduces energy loss and ensures better structural stability.

Machine Learning and IoT Trends for Intelligent Prediction of Aircraft Wing Anti-Icing System Temperature

Airplane manufacturers are frequently faced with formidable challenges to improving both aircraft performance and customer safety. Ice accumulation on the wings of aircraft is one of the challenges, which could result in major accidents and a reduction in aerodynamic performance. Anti-icing systems, which use the hot bleed airflow from the engine compressor, are considered one of the most significant solutions utilized in aircraft applications to prevent ice accumulation. In the current study, a novel approach based on machine learning (ML) and the Internet of Things (IoT) is proposed to predict the thermal performance characteristics of a partial span wing anti-icing system constructed using the NACA 23014 airfoil section. To verify the proposed strategy, the obtained results are compared with those obtained using computational ANSYS 2019 software. An artificial neural network (ANN) is used to build a forecasting model of wing temperature based on experimental data and computational fluid dynamics (CFD) data. In addition, the ThingSpeak platform is applied in this article to realize the concept of the IoT, collect the measured data, and publish the data in a private channel. Different performance metrics, namely, mean square error (MSE), maximum relative error (MAE), and absolute variance (R2), are used to evaluate the prediction model. Based on the performance indices, the results prove the efficiency of the proposed approach based on ANN and the IoT in designing a forecasting model to predict the wing temperature compared to the numerical CFD method, which consumes a lot of time and requires high-speed simulation devices. Therefore, it is suggested that the ANN-IoT approach be applied in aviation.

Thermodynamic performance and heat and mass transfer analysis of air source absorption heat pump for heating

To lower CO2 emission and obtain better heating efficiency compared with conventional gas boilers, this paper proposed a solar air source absorption heat pump (SAAHP) with falling film heat exchanger for district heating. The thermodynamic model is established to analyze the performance of the proposed system. The falling film generator as the key heat exchange component has been designed carefully, and then the numerical models of the falling film generation process which include one and two-dimensional numerical models are developed. According to the thermodynamic analysis, the primary energy efficiency (PEE) and heating capacity of the system are 1.65 and 45.02 kW at the generation temperature of 190 °C and ambient temperature of −7 °C, respectively, which can save 41.69 t of CO2 emissions from heating. The two-dimensional numerical model indicates the main heat and mass transfer occur between the falling film height x = 0 mm and x = 200 mm, and the interface heat transfer decreases from 74.6 kJ/(m2·s) to 40.5 kJ/(m2·s) in a typical vertical falling film generation process. In addition, the energy transfer as the inter-diffusion is corrected in the energy equation which improves the prediction accuracy by about 1.5% of the two-dimensional model. The research provides a reference for the optimization design of the generator, where one-dimensional models can quickly guide the design and selection of equipment, modified two-dimensional numerical models and Computational fluid dynamics (CFD) models can provide references for the refined optimization design, which attributes to the improvement of thermodynamic performance of the solar absorption heat pump system.

RANS CFD Model for Global Performance Evaluation of Floating Vessel in Extreme Head Waves

Extreme waves acting on the floating vessel would cause serious physical behavior and could cause a catastrophic incident. Such phenomena should be put of high interest during the designing step of the floating vessel. The numerical CFD (Computational Fluid Dynamics) viscous fluid approach along with the recent development of computer hardware gives us advantages to simulate a huge number of scenarios in the very early design phase. The current study will explain the CFD method to investigate the global performance of stationer floating vessel Fn = 0 on its motion and green water occurrence due to extreme waves λ/L = 2.0. Based on the simulation results, the CFD model can handle well the green water on deck phenomenon during extreme head waves. The water on deck affected vessel pitch motion amplitude not symmetric under regular waves i.e. 8 degrees by stern and 6 degrees by bow. Similar results were also found in heave motion amplitude by the maximum +4 centimeter and minimum -12 centimeter. Those asymmetric results of heave & pitch motion amplitude under regular waves indicate the contribution of green water to the vessel motion. In addition, green water on deck only affects the motion amplitude but not the motion frequency.

Flow-Induced Forces for a Group of One Large and Several Small Structures in the Sheared Turbulent Flow

Evaluating the hydrodynamic force fluctuations acting on each structure in a group of subsea objects of different cross-section shapes, sizes and relative positions represents a challenge due to the sensitivity of the vortex shedding process, especially for a variety of sheared flows. The present study uses the numerical 2D computational fluid dynamics model to estimate the flow-induced forces on a group of small circular and D-shaped cylinders in the linear and parabolic sheared flow, which are placed in proximity to a larger structure of the squared cross-section. This allows us to evaluate loads, which are affected by the presence of subsea equipment located on the seabed. The average Reynolds number of the considered linear flow profile is 3900, while the parabolic flow profile has the maximum Reynolds number of 3900. The k-ω SST turbulence model is used for simulations. The work demonstrates the effect of the cross-sectional shape of smaller cylinders on hydrodynamic coefficients, explores the effect from the spacing in between the structures and highlights differences between loads in the linearly sheared and parabolic flow. The results obtained show that the presence of the squared cylinder notably influences the mean drag coefficient on the first cylinder, for both circular and D-shaped cylinders. The parabolic sheared flow profile in this series leads to the highest mean drag and the highest amplitudes of the fluctuating drag and lift coefficients.

A numerical investigation on thermal analysis of RPC based solar thermochemical reactor for two-step H2O splitting cycle for hydrogen production

Ceria based solar thermochemical cycle is a high-temperature based redox chemical reactions to split H2O or CO2to produce hydrogen and/or syngas. The redox reactions are carried out in a reactor cavity thus the analysis and optimization of design as well as thermal analysis is a crucial factor to improve the solar-to-fuel conversion efficiency. This paper proposes the hybrid design of cylindrical and hemispherical cavity and its effects of geometrical parame-ters such as reticulated porous ceria (RPC) thickness (15 mm, 20 mm, and 25 mm) and gas flow gap (5 mm&10 mm) on temperature and flux distribution and solar-to-fuel efficiency for both steady-state and transient condition. A numerical computational fluid dynamics (CFD) analysis is carried out to study heat and mass transfer as well as geometrical design consid-eration of the STCR cavity under SolTrace generated Gaussian distributed concentrated solar flux. Two-step water-splitting reaction in the Solar Thermochemical cavity reactor (STCR) using ceria (CeO2) has been modeled to explore the oxygen evolution/reaction rate and to estimate solar-to-fuel efficiency and its relationship with geometrical factors. The RPC of 25 mm thickness yields the highest oxygen evolution rate of 0.34 mL/min/gCeO2 and solar-to-fuel efficiencies are 7.82%, 12.07% and 16.18% for 15 mm, 20 mm and 25 mm of RPC thickness, respectively without heat recovery. The operating conditions and optimized geometric factors, based on result analysis and comparison, are discussed in detail.