Simulation Based Design Tool for Radial TurbineRotors

Preliminary design, optimization and CFD analysis of an organic rankine cycle radial turbine rotor

Microturbines have been developed as an important power unit for distributed generation (DG) or distributed energy resource (DER) options [1]. They have been established and are widely used in aircraft and power applications, due to their easy installation, reliability, high performance, multi-fuel capabilities and low emission [2]. However, the aerothermodynamic design of a radial turbine still poses a challenge due to its high rotational speed and high inlet temperature, which influence the centrifugal stress and the rotor structural integrity. This paper presents the numerical investigations on the aerothermodynamic design of the nozzle and the radial inflow rotor for a 600 kW simple cycle gas turbine engine using a One-dimensional Computer FORTRAN Code (OFC) [3], on the grounds of non-dimensional parameters aimed at computational and work time reduction. This program utilizes a one-dimensional solution of flow conditions through the turbine along the meanline. The referred computer program is an effective performance prediction tool mostly in the initial stage of the preliminary design and can be used to quickly investigate and calculate the number of design options prior to any details of the vane and blade geometry. In order to find the most promising design option, a computational fluid dynamics (CFD) simulation has been used to study the performance, the aerothermodynamic design and the flow characteristics of the turbine components. The OFC results were compared with the CFD simulation, a computer program for the design analysis of radial inflow turbines, and analytical results taken from specialized literature showed the results were in agreement.

While designing the power requirements of a ship, the most important factor to be considered is the ship resistance, or the sea drag forces acting on the ship. It is important to have an estimate of the ship resistance while designing the propulsion system since the power required to overcome the sea drag forces contribute to ‘losses’ in the propulsion system. There are three main methods to calculate ship resistance: Statistical methods like the Holtrop-Mennen (HM) method, numerical analysis or CFD (Computational Fluid Dynamics) simulations, and model testing, i.e. scaled model tests in towing tanks. At the start of the design stage, when only basic ship parameters are available, only statistical models like the HM method can be used. Numerical analysis/ CFD simulations and model tests can be performed only when the complete 3D design of the ship is completed. The present paper aims at predicting the calm water ship resistance using CFD simulations, using the Flow-3D software package. A case study of a roll-on/roll-off passenger (RoPax) ferry was investigated. Ship resistance was calculated at various ship speeds. Since the mesh affects the results in any CFD simulation, multiple meshes were used to check the mesh sensitivity. The results from the simulations were compared with the estimate from the HM method. The results from simulations agreed well with the HM method for low ship speeds. The difference in the results was considerably high compared to the HM method for higher ship speeds. The capability of Flow-3D to perform ship resistance analysis was demonstrated.

Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.

Computational Fluid Dynamics (CFD) simulations are widely used in mechanical engineering. Although achieving a high level of confidence in numerical modelling is of crucial importance in the field of turbomachinery, verification and validation of CFD simulations are very tricky especially for complex flows encountered in radial turbines. Comprehensive studies of radial machines are available in the literature. Unfortunately, none of them include enough detailed geometric data to be properly reproduced and so cannot be considered for academic research and validation purposes. As a consequence, design improvements of such configurations are difficult. Moreover it seems that well-developed analyses of radial turbines are used in commercial software but are not available in the open literature especially at high pressure ratios. It is the purpose of this paper to provide a fully open set of data to reproduce the exact geometry of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multipurpose Small Power Unit. First, preliminary one-dimensional meanline design and analysis are performed using the commercial software RITAL from Concepts-NREC in order to establish a complete reference test case available for turbomachinery code validation. The proposed design of the existing turbine is then carefully and successfully checked against the geometrical and experimental data partially published in the literature. Then, three-dimensional Reynolds-Averaged Navier-Stokes simulations are conducted by means of the Axcent-PushButton CFD® CFD software. The effect of the tip clearance gap is investigated in detail for a wide range of operating conditions. The results confirm that the 3D geometry is correcty reproduced. It also reveals that the turbine is shocked while designed to give a high-subsonic flow and highlight he importance of the diffuser.

Bench test and computational fluid dynamics (CFD ) simulation of the air pump loss on the 380 hydraulic retarder are completed in this paper . It turns out that the CFD simulation has nice reliability from the contrast of the air pump loss between the test and the simulation . And on this foundation , CFD simulation of two kinds of retarders with different turbulent structures is done . The contrast of the results of the simulation give the effects of different turbulent structures on cutting down the are pump loss .

The increasing emission of carbon dioxide (CO2) into the environment has a significant influence on increasing global warming. The widely used carbon capture technologies (CCTs), including adsorption, absorption, cryogenics and membrane separation, have been reported previously through both experimental and simulation studies. Simulation studies are particularly considered essential tools for investigating the performance of the process from various aspects, as well as for predicting the complex behavior in any real system without actual experimental setups. This review mainly focuses on the recent advancements in computational fluid dynamics (CFD), modeling and simulation as a transformative tool for optimizing CO2 adsorption processes. The fundamentals of CFD with their role in accurately simulating complex phenomena involved in the CO2 adsorption are discussed. Parametric sensitivity analysis, hydrodynamics, kinetic and adsorption isotherms are thoroughly studied, and critical challenges, including mesh independence, model complexity, and scalability, are also addressed. The future research directions proposed include the integration of CFD with machine learning algorithms, the development of multi-scale models, and the deployment of CFD methodologies to industrial-scale applications.

Auxiliary power units (APUs) are gas turbine engines that provide high-pressure air and electrical power to aircraft systems. They provide primary power while the aircraft is parked on the ramp, starting services for the main engines, and backup power while the aircraft is in flight. Many APUs employ inlet systems which include a “pop-up” door that allow for the capture of freestream ram pressure during flight. This results in increased inlet recovery and a corresponding improvement in the performance of the APU. This APU door, when open, is exposed to airflow instability inherent in the aircraft boundary layer in the aft section of the fuselage, where APUs are typically housed. Additionally, the pop-up nature of the inlet door produces a large region of separated airflow off of the back side of the door. Systematic vortex shedding is frequently a major component of this separated region. As new APU doors are made with less rigid material to save weight, a need to better understand the unsteady aerodynamic excitations of the flow field around the door has arisen, as these new doors may be more susceptible to vibration during flight. Recent advances in Computational Fluid Dynamics (CFD) meshing tools and transient modeling have enabled a CFD study to be performed which will investigate this time-dependent phenomenon. As transient CFD analysis is still a relatively new field for commercial CFD codes, a calibration was needed to verify the accuracy of the CFD predictions and to form any calibration correction terms. Honeywell Aerospace owns a Boeing 757 flight test vehicle which is normally used to flight test propulsion engines. However, this aircraft also includes a pop-up APU inlet door that is similar to most other APU inlet door styles. This APU door was instrumented using high response pressure transducers placed on the forward and aft sides of the inlet door as well as upstream of the door to measure upstream instability. The aircraft was flown at a variety of flight conditions and APU operating points and the transient data was recorded. After the completion of the flight test, a CFD model was constructed of the B757 flight test vehicle. Because aerodynamic instability can be generated anywhere on the aircraft, the entire airframe from nose to tail was modeled. The APU inlet door geometry was also created, meshed and added to the CFD model. This CFD model was run in a transient mode to simulate the exact same flight conditions and APU operating points as were tested during the flight test. Dynamic results in the time and frequency domains predicted by the CFD analyses were compared to flight test data and correlation and calibration factors were derived.

Computational limitations of computers have emerged as a critical barrier to the advancement of Computational Fluid Dynamics (CFD). Consequently, exploring novel accelerator architectures tailored for large-scale CFD applications and closely integrated with CFD algorithmic characteristics holds significant value. Through an in-depth analysis of the finite difference method (FDM) for solving Navier–Stokes (N-S) equations, we propose a specialized accelerator architecture for FDM-based CFD (FAcc). Implemented on a 28 nm process, FAcc integrates 16,384 differential computing cores (FCores). Experimental validation demonstrates FAcc’s capability to solve N-S equations of varying complexities by flexibly configuring boundary conditions. Compared to conventional approaches, FAcc achieves significant acceleration performance, with its programmability underscoring adaptability to high-precision, large-scale CFD simulations. As the first CFD-focused accelerator designed from the instruction set architecture (ISA) level, FAcc bridges a critical gap in domain-specific hardware for CFD, offering a paradigm shift in high-performance fluid dynamics computation.

The chemical composition and properties of fuels used in compression-ignition engines can influence engine performance significantly. Consequently, the modeling of fuel chemistry within computational fluid dynamics (CFD) simulations of diesel and other compression ignition engines is important. Modern detailed chemical mechanisms may provide predictive modeling of fuel chemistry; however, they are generally far too computationally expensive for use in CFD. We present simulations of diesel engine combustion, focusing on the prediction of ignition, using the CONVERGE CFD software package. A CFD simulation framework with models for turbulence and spray breakup and atomization is presented with a reduced global reaction model to describe fuel oxidation and ignition. The global reaction model incorporates a single parameter, the derived cetane number (DCN), to describe fuel reactivity variability. CFD simulations are compared to experiments carried out in a single-cylinder diesel engine for compositionally diverse conventional and alternative diesel and jet fuels. Model-experiment comparisons show general agreement for ignition timing and the influence of fuel variability on ignition timing. In addition, the sensitivity of CFD predictions on the chemistry, turbulence, and spray models is illustrated.

Today, many wells in heterogeneous carbonate reservoirs throughout the Middle East and Caspian Sea area are being completed with long intervals and complex completion equipment, such as limited entry liners and inflow control devices (ICDs). Accurate modeling and understanding of fluid placement during a stimulation operation through such long complex completions can be quite challenging. In this paper, an integrated approach of modeling, experiments and computational fluid dynamics (CFD) simulations will be presented. A computational tool based on a transient one-dimensional (1D) approach has been developed in-house to model stimulation through such completions. In order to validate the 1D approach for reliable fluid displacement predictions, annulus fluid displacement experiments in perforated liners supported by CFD simulations have been conducted. The experimental setup consists of an outer Lucite pipe representing the well-bore geometry and an inner aluminum pipe with multiple perforations of variable diameter. The setup mimics the real field application in a 1:1 scale with respect to the pipe and perforation diameters while the test section is limited to 27 ft. The experimental procedure is as follows: fluid is pumped into the annulus through the perforations until the annulus is completely filled,the fluid tank is switched "on-the-fly" to the tank with the displacing fluid resulting in the displacement of the annulus fluid by the displacing fluid through the perforations. The experiments and the CFD simulations indicate that even with a single open perforation inside the 27-ft test section, the three-dimensional (3D) flow field around the perforation rapidly transitions to uniform annular flow within a few feet uniformly displacing the annulus fluid. The model also provides insight into various well injection processes in sandstone and carbonate formation, such as scale squeezes, solvent treatments, and HF acid treatments. Introduction The length of production and injection intervals in a single well continues to increase in order to contact more reservoir rock with a single wellbore penetration and improve project economics. Multiple, thick stacked reservoirs are accessed by vertical and deviated wells while thinner reservoirs are being exploited with longer and longer horizontal wells1–3. To keep up with drilling capability, completion technology has advanced considerably in the past few years. Horizontal wells are "compartmentalized" using mechanical and/or swellable packers. Within a given compartment, injection and production can be controlled by use of inflow control devices (ICDs), limited entry (LE) liners, and/or sliding sleeves. The liners also make it easier to enter the completion interval with logging tools, wire line, and coiled tubing. While various tools are available to evaluate long-term, steady-state production and injection into such wells, modeling of short-term, transient injection into such completions is very challenging due to the long lateral lengths, limited entry points from the liner to each compartment, and the presence of an open annulus with occasional packer isolations. This is especially important for long wells in carbonate formations as all wells require acid stimulation upon initial completion, and occasionally throughout the well life.

A normally-open thermally-actuated microvalve was designed (using microfabrication/soft-lithography techniques involving 3D Printed molds), assembled and tested. The motivation of the research work is to develop an array of microvalves for precise delivery of water to individual plants in a field (with the goal of developing smart irrigation systems for high value cash-crops in the agricultural sector). It is currently impossible to control application of irrigation-water at the level of a single plant. If such a capability were practically available on farms, the result would be a step change in precision agriculture, such that the output of every plant in a farm field could be optimized (i.e., food-water-energy nexus in sustainability applications). The aim of this study is to develop and test a microfluidic system (consisting of a microvalve array) that could be controlled, capillary by capillary, to deliver the needed amount of water to individual plants in a large field. Two types of test fluids were leveraged for thermo-hydraulic actuation of the microvalves developed in this study: (a) Design-I: using air, and (b) Design-II: using Phase Change Material (PCM). The PCM used in this study is PureTemp29. The proposed approach enabled a simple and cheap design for microvalves that can be manufactured easily and are robust to weather conditions (e.g., when exposed to the elements in orchards and open fields). Other advantages include: safe and reliable operation; low power consumption; can tolerate anomalous pressure loads/fluctuations; simple actuation; affords easy control schemes; is amenable for remote control; provides long-term reliability (life-cycle duration estimated to be 3∼5 years); can be mass produced and is low maintenance (possibly requiring no maintenance over the life time of operation). The microvalve consists of two layers: a flow layer and a control layer. The control layer is heated from below and contains a microfluidic chamber with a flexible polymeric thin-membrane (200 microns in thickness) on top. The device is microfabricated from Poly-Di-Methyl-Siloxane (PDMS) using soft lithography techniques (using a 3D Printed mold). The control chamber contains either air (thermo-pneumatic actuation) or PCM (thermo-hydraulic actuation involving repeated melting/freezing of PCM). The flow layer contains the flow channel (inlet and outlet ports, horizontal section and valve seat). The experimental results from testing the efficacy of the two types of micro-valves show a 60% reduction (for thermo-pneumatic actuation using air) and 40% reduction (for thermo-hydraulic actuation using PCM) in water flow rates for similar actuation conditions (i.e., heater temperature values). PCM design is expected to consume less power (lower OPEX) for long-term actuation but may have slower actuation speed and have higher manufacturing costs (CAPEX). Air actuation design is expected to consume more power (higher OPEX) for longer-term operation but may have faster actuation speeds and lower manufacturing costs (CAPEX). Computational Fluid Dynamics (CFD) simulations were performed to investigate the effect of flowing water (in the microfluidic channel) on the average absolute pressure and temperature of air in the actuation chamber. The CFD simulations were performed using a commercial tool (Ansys™ 2019R1®). The results from the CFD simulations are presented in this study.

An electrochemical membrane bioreactor (EMBR) has recently been developed for energy recovery and wastewater treatment. The hydrodynamics of the EMBR would significantly affect the mass transfers and reaction kinetics, exerting a pronounced effect on reactor performance. However, only scarce information is available to date. In this study, the hydrodynamic characteristics of the EMBR were investigated through various approaches. Tracer tests were adopted to generate residence time distribution curves at various hydraulic residence times, and three hydraulic models were developed to simulate the results of tracer studies. In addition, the detailed flow patterns of the EMBR were acquired from a computational fluid dynamics (CFD) simulation. Compared to the tank-in-series and axial dispersion ones, the Martin model could describe hydraulic performance of the EBMR better. CFD simulation results clearly indicated the existence of a preferential or circuitous flow in the EMBR. Moreover, the possible locations of dead zones in the EMBR were visualized through the CFD simulation. Based on these results, the relationship between the reactor performance and the hydrodynamics of EMBR was further elucidated relative to the current generation. The results of this study would benefit the design, operation and optimization of the EMBR for simultaneous energy recovery and wastewater treatment.

In response to a solicitation for Computational Fluid Dynamic (CFD) simulations of flow in a T-junction from the Nuclear Energy Agency of the Organization for Economic Co-operation and Development (OECD/NEA) [1], Structural Integrity (SI) Associates of San Jose, CA, USA has completed a simulation using the commercially available CFD code ANSYS-CFX. The simulation was carried out for geometry and flow conditions matching an experiment underway at Vattenfall Research and Development in Sweden where two streams of differing temperature mix in a T-junction. The benchmark was to be a blind test of CFD simulations. Experimental results were not released until after benchmark participants submitted the results of their simulation to the OECD/NEA. The CFD simulation done by SI was carried out on an all hexahedral mesh of 1,881,504 elements generated using the ANSYS Mechanical Finite Element program. The mesh was then transferred into the CFX program and, after applying proper boundary conditions, a time-dependent simulation was done using the Large Scale Eddy Simulation (LES) turbulence model [2] with Wall Adjusting Local Eddy Viscosity (WALE) sub-grid scale (SGS) turbulence model [2, 3]. Comparisons of the CFD results to the Vattenfall data show close correspondence for mean and root-mean-square (rms) turbulent temperature fluctuations.

CFD simulation and experimental validation of a GM type double inlet pulse tube refrigerator