Solid Oxide Cells (SOCs) can work efficiently in reversible operation, allowing the energy storage as hydrogen in power to gas application and providing requested electricity in gas to power application. They can easily switch from fuel cell to electrolyzer mode in order to guarantee the production of electricity, heat or directly hydrogen as fuel depending on energy demand and utilization. The proposed modeling is able to calculate effectively SOC performance in both operating modes, basing on the same electrochemical equations and system parameters, just setting the current density direction. The identified kinetic core is implemented in different simulation tools as a function of the scale under study. When the analysis mainly focuses on the kinetics affecting the global performance of small-sized single cells, a 0D code written in Fortran and then executed in Aspen Plus is used. When larger-scale single or stacked cells are considered and local maps of the main physicochemical prop... [more]

The reduction gas used in the gas-based direct reduction iron-making process contains CH4 in different concentrations, which has an important effect on the gas and heat needed for the reduction of iron oxide. To investigate the influence of CH4 on gas utilization rate and heat needed at 900 °C, the initial conditions are set as H2% + CO% = 90, CH4% + N2% = 10, gas pressure 1−9 atm, and 0.5 mol Fe2O3, and the equilibrium state composition is calculated using the minimum free energy method. The utilization rate of total gas can be improved, and gas demand can be decreased by increasing CH4 concentration or H2 concentration or reducing gas pressure. For the production of per ton of Fe from 25 °C to 900 °C, 6.08−7.29 m3 of reduction gas, and 7.338−8.952 MJ of gas sensible heat can be saved by increasing 1 m3 CH4, while 10.959−11.189 MJ of reaction heat is increased. Compared with 3390.828−3865.760 MJ of the total heat of per ton of Fe for the reduction by H2 + CO, 2.174−3.703 MJ of total h... [more]

The purpose of this work is modeling of a horizontal oil−water flow with and without the Algebraic Interfacial Area Density (AIAD) model. Software and hardware developments in the past years have significantly increased and improved the accuracy, flexibility, and performance of simulations for large and complex problems typically encountered in industrial applications. At Helmholtz-Zentrum Dresden-Rossendorf (HZDR), the focus has been concentrated on the R&D of new modeling capabilities for Euler−Euler approach where interfaces exist. In this research paper, the applicability of the AIAD model for a horizontal oil−water flow is investigated. The comparison between the standard ANSYS Fluent Eulerian Interface Capabilities (namely Multi-Fluid VOF) without AIAD and ANSYS CFX with AIAD implemented via user functions for the oil−water flow was performed. Thereafter, the obtained results were compared with existing experimental data produced by the Department of Thermodynamics and Transport... [more]

This study conducts saturation modeling in a gas hydrate (GH) sand sample with X-ray CT images using the following machine learning algorithms: random forest (RF), convolutional neural network (CNN), and support vector machine (SVM). The RF yields the best prediction performance for water, gas, and GH saturation in the samples among the three methods. The CNN and SVM also exhibit sufficient performances under the restricted conditions, but require improvements to their reliability and overall prediction performance. Furthermore, the RF yields the lowest mean square error and highest correlation coefficient between the original and predicted datasets. Although the GH CT images aid in approximately understanding how fluids act in a GH sample, difficulties were encountered in accurately understanding the behavior of GH in a GH sample during the experiments owing to limited physical conditions. Therefore, the proposed saturation modeling method can aid in understanding the behavior of GH i... [more]

Dual fuel engines constitute a viable solution for enhancing the environmental sustainability of the shipping operations. Although these engines comply with the Tier III NOx emissions regulations when operating at the gas mode, additional measures are required to ensure such compliance at the diesel mode. Hence, this study aimed to optimise the settings of a marine four-stroke dual fuel (DF) engine equipped with exhaust gas recirculation (EGR) and air bypass (ABP) systems by employing simulation and optimisation techniques, so that the engine when operating at the diesel mode complies with the ‘Tier III’ requirements. A previous version of the engine thermodynamic model was extended to accommodate the EGR and ABP systems modelling. Subsequently, a combination of optimisation techniques including multiobjective genetic algorithms (MOGA) and design of experiments (DoE) parametric runs was employed to identify both the engine and the EGR/ABP systems settings with the objective to minimise... [more]

In the safety analysis of sodium-cooled fast reactors, numerical simulations of various thermal-hydraulic phenomena with multicomponent and multiphase flows in core disruptive accidents (CDAs) are regarded as particularly difficult. In the material relocation phase of CDAs, core debris settle down on a core support structure and/or an in-vessel retention device and form a debris bed. The bed’s shape is crucial for the subsequent relocation of the molten core and heat removal capability as well as re-criticality. In this study, a hybrid numerical simulation method, coupling the multi-fluid model of the three-dimensional fast reactor safety analysis code SIMMER-IV with the discrete element method (DEM), was applied to analyze the sedimentation and bed formation behaviors of core debris. Three-dimensional simulations were performed and compared with results obtained in a series of particle sedimentation experiments. The present simulation predicts the sedimentation behavior of mixed parti... [more]

Multi-element thrusters operating with gaseous oxygen (GOX) and methane (GCH4) have been numerically studied and the results were compared to test data from the Technical University of Munich (TUM). A 3D Reynolds Averaged Navier−Stokes Equations (RANS) approach using a 60° sector as a simulation domain was used for the studies. The primary goals were to examine the effect of the turbulent Prandtl number approximations including local algebraic approaches and to study the influence of radiative heat transfer (RHT). Additionally, the dependence of the results on turbulence modeling was studied. Finally, an adiabatic flamelet approach was compared to an Eddy-Dissipation approach by applying an enhanced global reaction scheme. The normalized and absolute pressures, the integral and segment averaged heat flux were taken as an experimental reference. The results of the different modeling approaches were discussed, and the best performing models were chosen. It was found that compared to othe... [more]

In this study, advanced Computational Fluid Dynamics (CFD)-based numerical simulations have been performed in order to analyse fire propagation in a standard railway compartment. A Fire Dynamics Simulator (FDS) has been employed to mimic real world scenarios associated with fire propagation within railway carriages in order to develop safety guidelines for railway passengers. Comprehensive parametric investigations on the effects of ignition location, intensity and cabin upholstery have been carried out. It has been observed that a fire occurring near the exits of the carriage results in a lower smoke layer height, due to the local carriage geometry, than an identical fire igniting at the center of the carriage. This in turn causes the smoke density along the aisleway to vary by around 30%. Reducing the ignition energy by half has been found to restrict combustion, thus reducing smoke density and carbon exhaust gases, reducing the average temperature from 170 °C to 110 °C. Changing the... [more]

Since various foreign bodies can cause clogging and wear in single-channel pumps, considerable attention has been focused on the numerical study of solid-liquid flows in the single-channel pump. However, conventional numerical simulation cannot responsibly assess the significant effect of the particle material properties, inter-particle collision, and size on the pump. In consideration of the particle features and behaviors, the Computational Fluid Dynamics (CFD)-Discrete Element Method (DEM) coupling method was applied for the first time to simulate the solid-liquid flows in a single-channel pump. The results showed that the smaller particles possessed a wider velocity distribution range and velocity peak, while the larger particles exerted a greater contact force. Additionally, the pie-shaped particles had the most severe collisions, and spherical particles had the least in total. Furthermore, the hub and shroud wall suffered a minor contact force, but the blade and volute wall both... [more]

Wind energy is one of the fastest growing renewable energy sources, and the most developed energy extraction device that harnesses this energy is the Horizontal Axis Wind Turbine (HAWT). Increasing the efficiency of HAWTs is one important topic in current research with multiple aspects to look at such as blade design and rotor array optimization. This study looked at the effect of wingtip devices, a split winglet, in particular, to reduce the drag induced by the wind vortices at the blade tip, hence increasing performance. Split winglet implementation was done using computational fluid dynamics (CFD) on the National Renewable Energy Lab (NREL) Phase VI sequence H. In total, there are four (4) blade configurations that are simulated, the base NREL Phase VI sequence H blade, an extended version of the previous blade to equalize length of the blades, the base blade with a winglet and the base blade with split winglet. Results at wind speeds of 7 m/s to 15 m/s show that adding a winglet in... [more]

Light-emitting diode (LED) digital twins enable the implementation of fast digital design flows for LED-based products as the lighting industry moves towards Industry 4.0. The LED digital twin developed in the European project Delphi4LED mimics the thermal-electrical-optical behavior of a physical LED. It consists of two parts: a package-level LED compact thermal model (CTM), coupled to a chip-level multi-domain model. In this paper, the accuracy and computation time reductions achieved by using LED CTMs, compared to LED detailed thermal models, in 3D system-level models with a large number of LEDs are investigated. This is done up to luminaire-level, where all heat transfer mechanisms are accounted for, and up to 60 LEDs. First, we characterize a physical phosphor-converted white high-power LED and apply LED-level modelling to produce an LED detailed model and an LED CTM following the Delphi4LED methodology. It is shown that the steady-state junction temperature errors of the LED CTM,... [more]

Three-level neutral-point clamped cascaded converters (3LNPC-CC) are widely used in high power nigh-voltage applications. This paper mainly discusses the open-circuit fault in DC-side of the 3LNPC-CC. Optimized by the sequence pulse modulation, a sequence smooth modulation (SSM) is proposed to keep the DC-side voltage balance while the 3LNPC-CC suffers open-circuit fault from DC-side. The SSM found efficient switch-state path through a 3-D cube model and simplified the path from thousands of switch state. The SSM avoids the complex calculation in the voltage-balancing modulation, while the dynamic character of it was less influenced. At the same time, the modulation changes the voltage level smoothly and balances the fault DC-side voltage effectively. The characters of the proposed modulation are verified by the simulation and the experiment.

Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve accurate prediction of wind power generation in China, a hybrid prediction model based on the combination of Wavelet Decomposition (WD) and Long Short-Term Memory neural network (LSTM) is constructed. Firstly, the nonstationary time series is decomposed into multidimensional components by WD, which can effectively reduce the volatility of the original time series and make them more stable and predictable. Then, the components of the original time series after WD are used as input variables of LSTM to predict the national wind power generation. Forty points were used, 80% as training samples and 20% as testing samples. The experimental results show that the MAPE of WD-LSTM is 5.831, performing... [more]

Reducing energy usage to save the environment is one of the main goals for the future. The energy losses in ventilation have a huge impact on energy consumption in buildings. In this work, the energy performance of a heat recovery wheel system equipped in an air handling unit was tested year-round, and the results compared with the simulation output for the system using TRNSYS software. The selected conditioned space was the staff offices of an H&M fashion shop, located in Eger, Hungary. Temperature, relative humidity, and air velocity sensors were placed at the wheel inlet and outlet sections to record data and determine the annual energy saving. The results revealed a good agreement between the measured and simulated results.

Unconventional reservoirs produce large volumes of oil; however, recovery factors are low. While enhanced oil recovery (EOR) with cyclic gas injection can increase recovery factors in unconventional reservoirs, the mechanisms responsible for additional recovery are not well understood. We examined cyclic gas injection recovery mechanisms in unconventional reservoirs including oil swelling, viscosity reduction, vaporization, and pressure support using a numerical flow model as functions of reservoir fluid gas−oil ratio (GOR), and we conducted a sensitivity analysis of the mechanisms to reservoir properties and injection conditions. All mechanisms studied contributed to the additional recovery, but their significance varied with GOR. Pressure support provides a small response for all fluid types. Vaporization plays a role for all fluids but is most important for gas condensate reservoirs. Oil swelling impacts low-GOR oils but diminishes for higher-GOR oil. Viscosity reduction plays a min... [more]

The combination of the turning and burnishing process is an efficient approach to improve machined quality and productivity. This paper aims to optimize energy efficiency (EF), improved hardness ratio (IHR), and decreased roughness ratio (DRR) of a new hybrid turning-burnishing process. The machining parameters are the feed rate (f), turning speed (v), depth of cut (a), burnishing pressure (p), and the diameter of the compressing ball (d). A new turning-burnishing tool using compressed air has been designed and fabricated. A set of experiments for Aluminum Alloy 5083 were performed using the Taguchi method. The weightage principal component analysis (WPCA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were applied to obtain the weight values and optimal outcomes. The results indicated that optimum values of the depth of cut, pressure, diameter, feed rate, and speed are 1.00 mm, 0.4 MPa, 16.00 mm, 0.084 mm/rev, and 120 m/min, respectively. The improvemen... [more]

The diffusion−adsorption behavior of methane in coal is an important factor that both affecting the decay rate of gas production and the total gas production capacity. In this paper, we established a pore-scale Lattice Boltzmann (LB) model coupled with fluid flow, gas diffusion, and gas adsorption−desorption in the bi-dispersed porous media of coalbed methane. The Knudsen diffusion and dynamic adsorption−desorption of gas in clusters of coal particles were considered. Firstly, the model was verified by two classical cases. Then, three dimensionless numbers, Re, Pe, and Da, were adopted to discuss the impact of fluid velocity, gas diffusivity, and adsorption/desorption rate on the gas flow−diffusion−adsorption process. The effect of the gas adsorption layer in micropores on the diffusion−adsorption−desorption process was considered, and a Langmuir isotherm adsorption theory-based method was developed to obtain the dynamic diffusion coefficient, which can capture the intermediate process... [more]

The synchronous condenser (SC) has a broad application prospect in ultra-high-voltage direct current (UHVDC) systems. The SC’s loss of excitation (LOE) is an important grid-related fault that may cause damage to the UHVDC. However, as the premise of the scientific protection configuration, knowledge of the SC’s LOE feature and its impact on UHVDC is still missing. This article first analyzes the SC’s LOE feature, offering a basic cognition of this fault. Secondly, the LOE SC’s reactive power response to system voltage variation is studied in the single-machine infinite-bus system. This lends a foundation for transient UHVDC research. Finally, the LOE SC’s impacts on steady and transient UHVDC are evaluated, respectively, considering different AC strengths and system faults through PSCAD/EMTDC (V4.6, Manitoba HVDC Research Center, Winnipeg, MB, Canada) simulations. The results show that: (1) LOE the SC absorbs reactive power while maintaining synchronous operation, its excitation curren... [more]

This paper considers the issue of associated petroleum gas utilization during hydrocarbon production in remote petroleum fields. Due to the depletion of conventional oil and gas deposits around the globe, production shifts to hard-to-recover resources, such as heavy and high-viscosity oil that requires a greater amount of energy to be recovered. At the same time, large quantities of associated petroleum gas are extracted along with the oil. The gas can be utilized as a fuel for power generation. However, even the application of combined power modes (combined heat and power and combined cooling heat and power) cannot guarantee full utilization of the associated petroleum gas. Analysis of the electrical and heat loads’ graphs of several oil fields revealed that the generated thermal energy could not always be fully used. To improve the efficiency of the fuel’s energy potential conversion, an energy system with a binary power generation cycle was developed, consisting of two power install... [more]

The proppant transportation is a typical two-phase flow process in a complex cross fracture network during hydraulic fracturing. In this paper, the proppant transportation in cross fractures is investigated by the computational fluid dynamics (CFD) method. The Euler−Euler two-phase flow model and the kinetic theory of granular flow (KTGF) are adopted. The dimensionless controlling parameters are derived by dimensional analysis. The equilibrium proppant height (EPH) and the ratio of the proppant mass (RPM) in the secondary fracture to that in the whole cross fracture network are used to describe the movement and settlement of proppants in the cross fractures. The main features of the proppant transportation in the cross fractures are given, and several relative suggestions are presented for engineering application in the field. The main controlling dimensionless parameters for relative EPH are the proppant Reynolds number and the inlet proppant volume fraction. The dominating dimensionl... [more]

Ultra-short-term load demand forecasting is significant to the rapid response and real-time dispatching of the power demand side. Considering too many random factors that affect the load, this paper combines convolution, long short-term memory (LSTM), and gated recurrent unit (GRU) algorithms to propose an ultra-short-term load forecasting model based on deep learning. Firstly, more than 100,000 pieces of historical load and meteorological data from Beijing in the three years from 2016 to 2018 were collected, and the meteorological data were divided into 18 types considering the actual meteorological characteristics of Beijing. Secondly, after the standardized processing of the time-series samples, the convolution filter was used to extract the features of the high-order samples to reduce the number of training parameters. On this basis, the LSTM layer and GRU layer were used for modeling based on time series. A dropout layer was introduced after each layer to reduce the risk of overfi... [more]

The overall cost of a hydropower plant is mainly due to the expenses of civil works, mechanical equipment (turbine and control units) and electrical components. The goal of a new draft tube design is to obtain a geometry that reduces investment costs, especially the excavation ones, but the primary driver is to increase overall machine efficiency, allowing for a reduced payback time. In the present study, an optimization study of the elbow-draft tube assembly of a Kaplan turbine was conducted. First, a CFD model for the complete turbine was developed and validated. Next, an optimization of the draft tube alone was performed using a design of experiments technique. Finally, several optimum solutions for the draft tube were obtained using a response surface technique aiming at maximizing pressure recovery and minimizing flow losses. A selection of optimized geometries was subsequently post-checked using the validated model of the entire turbine, and a detailed flow analysis on the obtain... [more]

In this paper the magnetic nanoparticle aggregation procedure in a microchannel in the presence of external magnetic field is investigated. The main goal of the work was to establish a numerical model, capable of predicting the shape of the nanoparticle aggregate in a magnetic field without extreme computational demands. To that end, a specialized two-phase CFD model and solver has been created with the open source CFD software OpenFOAM. The model relies on the supposed microstucture of the aggregate consisting of particle chains parallel to the magnetic field. First, the microstructure was investigated with a micro-domain model. Based on the theoretical model of the particle chain and the results of the micro-domain model, a two-phase CFD model and solver were created. After this, the nanoparticle aggregation in a microchannel in the field of a magnet was modeled with the solver at different flow rates. Measurements with a microfluidic device were performed to verify the simulation re... [more]

Lost circulation occurs when the returned fluid is less than what is pumped into the well due to loss of fluid to pores or fractures. A lost-circulation event is a common occurrence in a geothermal well. Typical geothermal reservoirs are often under-pressured and have larger fracture apertures. A severe lost-circulation event is costly and may lead to stuck pipe, well instability, and well abandonment. One typical treatment is adding lost-circulation materials (LCMs) to seal fractures. Conventional LCMs fail to properly seal fractures because their mechanical limit is exceeded at elevated temperatures. In this paper, parametric studies in numerical simulations are conducted to better understand different thermal effects on the sealing mechanisms of LCMs. The computational fluid dynamics (CFDs) and the discrete element method (DEM) are coupled to accurately capture the true physics of sealing by granular materials. Due to computational limits, the traditional Eulerian−Eulerian approach... [more]

A good understanding of different rock types and their distribution is critical to locate oil and gas accumulations in the subsurface. Traditionally, rock core samples are used to directly determine the exact rock facies and what geological environments might be present. Core samples are often expensive to recover and, therefore, not always available for each well. Wireline logs provide a cheaper alternative to core samples, but they do not distinguish between various rock facies alone. This problem can be overcome by integrating limited core data with largely available wireline log data with machine learning. Here, we presented an application of machine learning in rock facies predictions based on limited core data from the Umiat Oil Field of Alaska. First, we identified five sandstone reservoir facies within the Lower Grandstand Member using core samples and mineralogical data available for the Umiat 18 well. Next, we applied machine learning algorithms (ascendant hierarchical cluste... [more]