Full Computational Fluid Dynamics Simulations Research Articles

An efficient strategy based on proper orthogonal decomposition for rapid determination of the location and rate of water vapor humidification in aircraft cabins

Currently, the air in commercial aircraft cabins during flights routinely exhibits extremely low relative humidity. But none of the previously published studies have addressed optimization of the humidification parameters in order to, create the desired humidity distributions in aircraft cabins at minimal cost. This study proposed an efficient strategy to accomplish the task. Under this strategy, a database of various potential humidification locations for aircraft cabins is first constructed. One scenario in the database is then selected by computational fluid dynamics (CFD)-based enumeration. Next, with the humidification location as prior information, the humidification rate and the air-supply temperature from the main ventilation system can be inversely designed by proper orthogonal decomposition. The above strategy was applied to a three-dimensional aircraft cabin model for the validated CFD cases. The results showed that an appropriate humidification for the cabin might both improve the thermal comfort of passengers and increase the humidity levels in the cabin; a decrease of the air-supply temperature from the main ventilation system would be beneficial in reducing the water vapor humidification rate required for passengers and allowing a higher humidification rate to be tolerated for the cabin walls. The parameters that improved the cabin air environment without significant moisture accumulation on walls were also provided by the proposed strategy. Compared with the full CFD simulation method, the proposed strategy is capable of providing accurate ranges of parameters while reducing the computing time by more than 95%, which demonstrates its competitive prospects.

Back to Bernoulli: a simple formula for trans-stenotic pressure gradients and retrospective estimation of flow rates in cerebral venous disease

BackgroundVenous sinus stenosis can be associated with cerebrovascular disorders. Understanding the role of blood flow disturbances in these disorders is often hampered by the lack of patient-specific flow rates. Our...

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.

Analysis of the air stream flow parameters generated by the positive pressure ventilator—full scale experiment and CFD simulation

Positioning the positive pressure ventilator in front of the door opening affects the effectiveness of the rescue operation carried out during a fire. An important factor determining the effectiveness of the positive pressure ventilator is also the layout of the rooms within the gas exchange path and the obstacles present there. The purpose of this article is to assess the feasibility of using analyses such as large eddy simulation (LES) to verify the efficiency of mobile fans under simulation conditions, without the need for time-consuming experimentation (also for complex room volumes of buildings). The article presents a comparative analysis to assess the degree of convergence of flow parameters obtained during an experiment (in a multi-story building) and computational fluid dynamics (CFD) simulations. For volumetric flow rate, convergence was achieved at levels ranging from 0.4% (for 5 m) to 11.5% (1 m), and for pressure values, the differences achieved ranged from 0.6% (5 m) to 30.1% (4 m). This paper demonstrates that the LES model can be used to perform CFD simulations in the area of assessing the performance of a positive pressure ventilator. The article also describes a test methodology for determining the flow parameters of an air stream, which can be used to perform numerical simulations.

Validation of a full scale CFD simulation of a self-propelled ship with measured hull roughness and effect of welding seams on hull resistance

This study presents the verification and validation of a full scale self-propulsion computational fluid dynamics (CFD) model including measured hull roughness and welding seams. The reference for validation is comprised of speed trial data from five sister ships. To ensure numerical accuracy, resistance and propeller open-water CFD simulations are verified and validated against model tests from two different towing tanks and discrepancies are found to be within the experimental uncertainty of model scale testing. The self-propulsion CFD results emphasise the necessity of measuring hull roughness for accurate performance calculations with discrepancies less than 3.4% on the delivered power relative to the fitted speed trial results. It is found that the empirical Townsin/Mosaad roughness formulation with measured average hull roughness, as recommended by ITTC, provides similar results, as modifying the wall functions using the Colebrook/Grigson roughness function. Homogeneous and heterogeneous roughness modelling methods are found to provide similar results for the studied ship. Modelling of the transverse welding seams on the hull surface is found to increase the total resistance by approximately 0.1% per seam, resulting in a total estimated increase in resistance of 1.5–1.8%. Finally, adding a fairing is found to significantly reduce the resistance penalty from welding seams.

3D CFD model for the analysis of the flow field through a horizontal axis wind turbine (HAWT)

With the world’s growing demand for energy, renewable energy production has become important in providing alternative sources of energy and in reducing the greenhouse effect. This study investigates the aerodynamics and performance of the WG/EV100 micro–Horizontal Axis Wind Turbine (HAWT) using Computational Fluid Dynamics (CFD). The complexity of VAWT aerodynamics, which is inherently unsteady and three-dimensional, makes high-fidelity flow models extremely demanding in terms of computational cost, limiting the analysis to mainly 2D Computational Fluid-Dynamics (CFD) approaches. This article explains how to perform a full 3D unsteady CFD simulation of HAWT. All main parts of the WG/EV100 HAWT were designed in SOLIDWORKS. Only the blade design was reverse engineered due to the unavailability of the CAD model and the complexity of its geometric characteristics. The impeller blade is scanned using a Coordi-nate Measuring Machine (CMM), and the obtained 3D scan data are exported from the PC-DMIS software to GEOMAGIC design X to obtain a CAD model of the blade.

A hybrid method for modelling wake flow of a wind turbine

A fast and accurate prediction of the wake of an upwind turbine is very important to quantify the performance of downwind turbines in offshore wind farms, which become larger and larger. The wake flow and dynamics may be quite accurately simulated by high-fidelity computational fluid dynamics (CFD) software but its computational costs are too high, in particular to simulate a long wake flow often required in engineering practice. Therefore, the wake is often modelled by simplified dynamic wake models in design practices. They are computationally efficient but could not catch all physics, depend on pre-specified empirical parameters, and are not suitable for flow near the turbine. This paper proposes a new hybrid method, in which the near wake flow is simulated by a CFD model based on Navier–Stokes equations with the turbine represented by actuator lines while the far wake flow is modelled by an improved simplified CFD-based dynamic wake model. The two models are two-way coupled at a section downwind the turbine. The newly formulated method is validated by the results of full CFD simulations in the whole domain. Its performances are investigated under different conditions. It will be demonstrated that the new method takes considerably less computational time than the full CFD tool to produce similar results.

Towards Dynamic Velocity Prediction of NACRA 17

NACRA 17 is a small foiling catamaran used in Olympic sailing. Sailing in the NACRA 17 is truly unsteady, especially in the foiling conditions. Dynamic velocity prediction has gained a lot of attention in recent years due to the unsteady nature of foiling sailboats. Different approaches have been applied to predict the motions of foiling or skimming boats in unsteady conditions. Typically, the aerodynamic forces are computed by the quasi-steady theory assumption. Static coefficients are used, and the applied velocities are corrected with boat motions. The hydrodynamic forces of a fully foiling boat can be computed in a similar fashion, but this method fails to include the effect of changes in the free surface as well as added mass. This paper proposes an approach where dynamic coefficients of the NACRA 17 hydrofoils are determined based on unsteady Computational Fluid Dynamics (CFD) simulations with a free surface. In the simulations the foil is moved in prescribed motions in one degree of freedom (DOF) at a time and dynamic coefficients are extracted for different frequencies of motion. All coefficients are combined in a coupled system of equations, and the equations can be solved in 6 DOFs in the time domain. Test scenarios with time-varying conditions are simulated and compared with full dynamic CFD simulations. The initial investigation of the approach shows promising results, but more investigations are needed to validate the approach and to identify possible limitations.

CFD-Modified Potential Simulation on Seakeeping Performance of a Barge

This study proposes a computational fluid dynamics (CFD)-modified potential (CMP) model. This hybrid model uses linear potential theory with a corrected damping ratio obtained from CFD simulations to analyze the seakeeping performance of a small vessel. According to the analysis procedure of the proposed model, a motion analysis, including the prediction of the roll and pitch damping ratio of a small barge, was conducted; to verify reliability; the results were compared to those of an experiment performed in a physical tank. The relative errors in the experiment for peak amplitude in the roll motion response amplitude operators (RAOs) using the CMP model were relatively small, whereas those obtained from only the potential analysis were large errors in all three conventionally used roll-damping ratios. In addition, the computational time consumed by the CMP model was longer than that consumed by the potential theory but faster than the full CFD simulation for all wave conditions. Subsequently, based on the motion analysis results, the seakeeping performance was evaluated in a real sea environment, and the results on the single significant amplitude (SSA) were discussed through comparison with the results of the potential analysis and experiment.

Dual-Solver Hybrid Computational Approach to Integrated Propulsion Aerodynamics

The demand for high-efficiency air vehicles and the development of distributed electric propulsion systems for aircraft are exposing the need for accurate aerodynamic prediction of multiple integrated propulsion systems. Conventional high-fidelity computational methods are too expensive, and low-cost low-fidelity methods make too many aerodynamic assumptions to be applied to these analyses. Dual-solver hybrid computational fluid dynamics (CFD) methods bridge the gap between these two categories of solvers, but many lack capabilities that are needed for complex vehicles. Recent improvements to the hybrid solver OVERFLOW-CHARM provide efficient and accurate analysis of integrated propulsion systems with hybrid CFD methods, as demonstrated on the wing–propeller system of the AIAA Workshop for Integrated Propeller Prediction. Predictions of propeller thrust are within 1% of conventional CFD data, and wing pressure coefficient distributions agree well with both experimental data and conventional CFD methods. The dual-solver results were obtained at half the computational cost of the full CFD simulation.

Stochastic parcel tracking in an Euler-Lagrange compartment model for fast simulation of fermentation processes.

The compartment model (CM) is a well‐known approach for computationally affordable, spatially resolved hydrodynamic modeling of unit operations. Recent implementations use flow profiles based on Computational Fluid Dynamics (CFD) simulations, and several authors included microbial kinetics to simulate gradients in bioreactors. However, these studies relied on black‐box kinetics that do not account for intracellular changes and cell population dynamics in response to heterogeneous environments. In this paper, we report the implementation of a Lagrangian reaction model, where the microbial phase is tracked as a set of biomass‐parcels, each linked with an intracellular composition vector and a structured reaction model describing their intracellular response to extracellular variations. A stochastic parcel tracking approach is adopted, in contrast to the resolved trajectories used in CFD implementations. A penicillin production process is used as a case study. We show good performance of the model compared with full CFD simulations, both regarding the extracellular gradients and intracellular pool response, using the mixing time as a matching criterion and taking into account that the mixing time is sensitive to the number of compartments. The sensitivity of the model output towards some of the inputs is explored. The coarsest representative CM requires a few minutes to solve 80 h of flow time, compared with approximately 2 weeks for a full Euler–Lagrange CFD simulation of the same case. This alleviates one of the major bottlenecks for the application of such CFD simulations towards the analysis and optimization of industrial fermentation processes.

A Compact Model for Lyophilizer Equipment Capability Estimation.

This work presents a compact model for the equipment capability limit of a common configuration of pharmaceutical lyophilizers, a product chamber separated from the condenser by a duct and isolation valve, at a wide range of design parameters. The equipment capability limit is one of the most important characteristics determining the lyophilization design space for a particular product, container, and equipment combination. Experimental measurements of equipment capability are time-consuming and expensive, especially at the production scale. Numerical modeling using computational fluid dynamics may reduce the number of experiments and provide insights into the physics of the process with high resolution. The computational fluid dynamics (CFD) modeling has been used in this work to develop a compact model for lyophilizer equipment capability. This eliminates the need for end users to create a full CFD model of the equipment and process. Full CFD and compact model simulations for laboratory and pilot-scale lyophilizers have been compared with tunable diode laser absorption spectroscopy measurements of the water vapor mass flow during ice slab tests. The compact model results average deviation from the experimental data is within 10%, whereas the full CFD simulations are within 5%. The compact model is based on several key parameters which are the main characteristics of a lyophilizer affecting the equipment capability curve. These parameters are discussed, and their effect on the modeling results is shown.

On the fast modeling of species transport in fluidized beds using recurrence computational fluid dynamics

AbstractDue to variety of scale dynamics evolved in gas–solid flows, most of its numerical description is limited to expensive short durations. This has made the slow processes therein, such as the chemical species conversion, to be out of an appropriate reach. In this work, an application of the transport‐based recurrence computational fluid dynamics (CFD) has been introduced for the fast modeling of passive scalar transport, which is considered as species conversion and heat transfer in fluidized beds. The methodology discloses the recurrent dynamics during a short‐term full CFD simulation as Lagrangian shift operations upon which a passive scalar can infinitely be traced. Apart from convecting, a proper approach based on the turbulent kinetic energy of tracked dynamics is introduced for modeling the physical diffusion of the scalar transported. Our outcomes have revealed a subtle chasing to the full CFD species simulation with a speed‐up up to 1,600.

A 1D mean line model for centrifugal compressors with variable inlet guide vanes

This paper considers a 1D in‐line analytical model for centrifugal compressors with variable inlet guide vanes. A theoretical 1D model is developed to predict the effect of varying the inlet guide vane angle at different rotational speeds. An iterative algorithm is presented, which provides a fast and efficient method for evaluating the performance of the compressor under different operating conditions. The results from the analytical 1D model are presented and compared to full 3D CFD (computational fluid dynamics) simulations. The simulations validate the assumptions used in the 1D model and show good agreement between the two approaches over a range of vane angles. Qualitatively, both demonstrate the same trends as the vane angle and rotational velocities are varied. Quantitatively, the pressure ratio was found to agree within 8% and the temperature gain to within 15%. The 1D model was then modified to introduce a 5% loss in the diffuser and this was found to improve the 1D model predictions, with the pressure within 2% of the CFD value.

Inverse design of aircraft cabin ventilation by integrating three methods

To create a healthy and comfortable aircraft cabin, air-supply parameters of the cabin ventilation system must be designed appropriately. Several methods, such as the computational fluid dynamics (CFD)-based genetic algorithm, CFD-based adjoint method and CFD-based proper orthogonal decomposition (POD), have been developed in recent years for conducting an inverse design. The target environmental performance is specified first, and then the corresponding air-supply parameters are inversely solved with the use of a particular method. However, each method has its pros and cons in terms of efficiency and accuracy. To expedite the inverse design process, this study proposed to integrate the above three methods. The genetic algorithm was adopted first to circumscribe ranges of the air-supply parameters. Next, POD was applied to further narrow the ranges and estimate the optimal air-supply parameters for each design criterion. Finally, the estimated optimal design from POD was supplied to the adjoint method for fine tuning. The above strategy was applied to a five-row aircraft cabin to determine the air-supply opening sizes, directions and temperatures. Criteria that had been proposed specifically for aircraft cabins were used as design targets. Results show that the proposed integration was able to provide the optimal design for each design target. The integrated optimal design was superior to the design provided by each individual method. The bottleneck in further acceleration of the integrated design was the hundreds of design cases resolved by full CFD simulation.

Numerical and Experimental Fluid–Structure Interaction-Study to Determine Mechanical Stresses Induced by Rotating Stall in Unshrouded Centrifugal Compressor Impellers

Unshrouded industrial centrifugal compressor impellers operate at high rotational speeds and volume flow rates. Under such conditions, the main impeller blade excitation is dominated by high frequency interaction with stationary parts, i.e., vaned diffusers or inlet guide vanes (IGVs). However, at severe part load operating conditions, sub-synchronous rotating flow phenomena (rotating stall) can occur and cause resonant blade vibration with significant dynamic (von-Mises) stress in the impeller blades. To ensure high aerodynamic performance and mechanical integrity, part load conditions must be taken into account in the aeromechanical design process via computational fluid dynamics (CFD) and finite element method (FEM) analyzes anchored by experimental verification. The experimental description and quantification of unsteady interaction between rotating stall cells and an unshrouded centrifugal compression stage in two different full scale compression units by Jenny and Bidaut (“Experimental Determination of Mechanical Stress Induced by Rotating Stall in Unshrouded Impellers of Centrifugal Compressors”, ASME J. Turbomach. 2016; 139(3):031011-031011-10) were reproduced in a scaled model test facility to enhance the understanding of the fluid–structure interaction (FSI) mechanisms and to improve design guide lines. Measurements with strain gauges and time-resolved pressure transducers on the stationary and rotating parts at different positions identified similar rotating stall patterns and induced stress levels. Rotating stall cell induced resonant blade vibration was discovered for severe off-design operating conditions and the measured induced dynamic von-Mises stress peaked at 15% of the mechanical endurance limit of the impeller material. Unsteady full annulus CFD simulations predicted the same rotating stall pressure fluctuations as the measurements. The unsteady Reynold's Averaged Navier-Stokes simulations were then used in FEM FSI analyses to predict the stress induced by rotating stall and assess the aerodynamic damping of the corresponding impeller vibration mode shape. Excellent agreement with the measurements was obtained for the stall cell pressure amplitudes at various locations. The relative difference between measured and mean predicted stress from fluid–structure interaction was 17% when resonant blade vibration occurred. The computed aerodynamic damping was 27% higher compared to the measurement.

Hypothesis-driven compartment model for stirred bioreactors utilizing computational fluid dynamics and multiple pH sensors

The ability to understand and predict mixing behaviour in stirred bioreactors through the use of mathematical models is an effective strategy to improve or ensure the performance of a process. Historically, compartment models have been developed to facilitate the prediction of hydrodynamics and in the last decade, computational fluid dynamics (CFD) has become the standard tool to assess this in detail. Despite the continuous increase in computational capacity, performing CFD simulations of bioreactors remains a challenge in industry, where the need for simplified models is apparent due to the complex phenomena occurring at the industrial scale. The combination of CFD and compartment models has been investigated in this work using a pilot scale stirred bioreactor equipped with three Rushton disc turbines and multiple pH sensors as a case study. A hypothesis-driven compartmentalization strategy, comprised of five steps, has been developed and applied to the pilot scale stirred bioreactor. The compartmentalization resulted in 56 compartments with unidirectional flow between adjacent compartments. The performance of the methodology was evaluated against a data-driven compartment approach and the full CFD simulation, in terms of its ability to recreate transient tracer profiles following top and bottom feeding of the tracer. The data-driven compartment model proved to be the most accurate of the three investigated methods, whereas the hypothesis-driven compartment method had a 10–12% higher error on prediction. Nevertheless, the developed methodology should be considered a viable alternative to conventional CFD methods, especially when models of complex phenomena – for example multi-dimensional population balance models – are to be incorporated in the final model as well.

A novel wake model for wind farm design on complex terrains

A numerical wake model that is capable of simulating wind turbine wake effects over complex terrains is proposed in this work. Currently, full computational fluid dynamics (CFD) simulations are required to simulate wake effects over complex terrains. Due to their high computational cost, it is difficult to apply expensive CFD simulations in the wind farm design process as optimization algorithms often require large number of solution evaluations. The proposed wake model solves a simplified variation of the Navier-Stokes equations, in which simplifications and assumptions have been implemented in order to reduce computational cost while maintaining accuracy. This model was validated by comparing with full CFD simulations with reasonable accuracy. In general, the model produces accurate results while keeping the computational cost two orders of magnitude lower than that of full CFD simulations. The low computation time highlights the model's potential to be used for optimizing wind farm layouts on complex terrains.

An optimized CFD method for conceptual flow design of water cooled ceramic blanket

Computational Fluid Dynamics (CFD) is a significant method for conceptual design of Water Cooled Ceramic Blanket (WCCB), since it could provide three-dimensional results with high accuracy. However, full CFD modeling and simulation toward the whole blanket flow channels is computationally expensive. An optimized CFD method based on partial modeling toward manifold regions is developed to overcome this disadvantage. Several flow conditions inside the First Wall (FW) and Cooling Plates (CPs) are simulated by the proposed method and the full modeling method. The maximum difference in mass flow rate prediction is 1.2%. The highest reductions in mesh size and modeled volume are 64.1% and 75.6% respectively. Results indicate that the newly developed method could provide accurate predictions with little computing resource requirements.

Inverse design of aircraft cabin environment using computational fluid dynamics-based proper orthogonal decomposition method

To design a comfortable aircraft cabin environment, designers conventionally follow an iterative guess-and-correction procedure to determine the air-supply parameters. The conventional method has an extremely low efficiency but does not guarantee an optimal design. This investigation proposed an inverse design method based on a proper orthogonal decomposition of the thermo-flow data provided by full computational fluid dynamics simulations. The orthogonal spatial modes of the thermo-flow fields and corresponding coefficients were firstly extracted. Then, a thermo-flow field was expressed into a linear combination of the spatial modes with their coefficients. The coefficients for each spatial mode are functions of air-supply parameters, which can be interpolated. With a quick map of the cause–effect relationship between the air-supply parameters and the exhibited thermo-flow fields, the optimal air-supply parameters were determined from specific design targets. By setting the percentage of dissatisfied and the predicted mean vote as design targets, the proposed method was implemented for inverse determination of air-supply parameters in two aircraft cabins. The results show that the inverse design using computational fluid dynamics-based proper orthogonal decomposition method is viable. Most of computing time lies in the construction of data samples of thermo-flow fields, while the proper orthogonal decomposition analysis and data interpolation is efficient.