Numerical Simulation and Analysis of Effect of Injection Volume on Biomass Particle Cyclone Venturi Dryer

Cyclone venturi dryer is suitable for drying materials with large particle size and wide distribution. The working process of cyclone venturi dryer is a very complicated three-dimensional and turbulent motion, so it is difficult to be studied theoretically and experimentally. In order to study the internal flow characteristics of the biomass particle cyclone venturi dryer, the computational fluid dynamics (CFD) software was used to simulate the gas-solid two-phase flow field inside the cyclone venturi dryer. The continuous phase adopts the Realizable k-ε turbulence model and the particle phase is discrete. The effects of different injection volume on the pressure, velocity, and temperature fields inside a cyclone venturi dryer were analyzed. The results showed that the maximum pressure drop and velocity change inside the dryer were at the venturi pipe. The wet material of the cyclone venturi dryer was inhaled into the venturi contraction tube by the negative pressure formed after the highspeed airflow was ejected, thus the mixture was completed in the venturi throat. The wood debris material was mixed with the high-speed hot gas flow in the venturi throat and then sprayed into the diffusion pipe. In the diffusion pipe of venturi, the heat and mass transfer process of wet wood debris and heat flow in venturi diffusion tube was completed. It is in good agreement with the simulation results. This study can provide a reference for the optimization design of the related cyclone venturi dryer structure.

A Numerical Study on the Thermal Control of Lithium Batteries by Composite Phase Change Materials and Metal Foams

This study attempts to control the temperature peaks due to the operation of the battery itself by examining a two-dimensional model to numerically investigate the thermal control of a lithium battery of a commercial electric car. The battery has the dimensions of 8 cm × 31 cm × 67 cm and its capacity is equal to 232 Ah with 5.3 kWh. Thermal control is achieved by means of an internal layer of copper or aluminum foam and phase change material (paraffin), placed on the top of the battery and the external surfaces are cooled by a convective flow. The governing equations, written assuming the local thermal equilibrium for the metal foam, are solved with the finite volume method using the commercial code Ansys-Fluent. Different cases are simulated for different thicknesses of the thermal control system and external convective heat transfer coefficient. The results are given in terms of temperature fields, liquid fraction, surface temperature profiles as a function of time and temperature distributions along the outer surface of the battery for the different cases. In addition, some comparisons with pure PCM are provided to show the advantages of the composite thermal control system with PCM inside the metal foam.

Slip Gas Flow and Heat Transfer in Confined Porous Media With Different Shape Cylinders

With the recent advances in micro devices, an accurate gas flow and heat transfer analysis become more relevant considering the slip effect. A micro-scale, multiple-relaxation-time (MRT) lattice Boltzmann method with double distribution function approach is used to simulate flow and heat transfer through circular- and diamond-shaped cylinders at the porescale level. The velocity slip and temperature jump are captured at the boundaries using a non-equilibrium extrapolation scheme with the counter-extrapolation method. A pore-scale domain of micro-cylinders comprised of circle and diamond shape are studied. It is found that the permeability increases linearly with an increase in Knudsen number for both circular- and diamond-shaped cylinders. However, the permeability increase for circular obstacle is larger than that of the diamond one. A larger surface area for diamond cylinder will offer more resistance to flow, hence resulting in lower values. For heat transfer, the Nusselt number shows an increase with increasing Reynolds number, however, it decreases with the increase in porosity. Nusselt number values are found to be higher for a circular obstacle. A variable boundary gradient for circular obstacle could be a possible explanation for this difference.

Development of a Fast Fluid Dynamics Model Based on PISO Algorithm for Simulating Indoor Airflow

Real-time or faster-than-real-time flow simulation is crucial for studying airflow and heat transfer in buildings, such as building design, building emergency management and building energy performance evaluation. Computational Fluid Dynamics (CFD) with Pressure Implicit with Splitting of Operator (PISO) or Semi-Implicit Method for Pressure Linked Equations (SIMPLE) algorithm is accurate but requires great computational resources. Fast Fluid Dynamics (FFD) can reduce the computational effort but generally lack prediction accuracy due to simplification. This study developed a fast computational method based on FFD in combination with the PISO algorithm. Boussinesq approximation is adopted for simulating buoyancy effect. The proposed solver is tested in a two-dimensional case and a three-dimensional case with experimental data. The predicted results have good agreement with the experimental results. In the two test cases, the proposed solver generates lower Root Mean Square Error (RMSE) compared to the FFD and at the same time, the proposed method reduces computational cost by a factor of 10 and 13 in the two cases compared to CFD.

Use of Machine Learning Tools to Assess Surface Dryout During Nucleate and Transition Boiling on Surfaces With Different Wetting and Substrate Properties

The work reported in this paper explored the use of machine learning tools to analyze quenching pool boiling data in the nucleate boiling range, near maximum heat flux range, and through the transition boiling range towards the Leidenfrost (minimum heat flux) point. It specifically explores the hypothesis that this sequence is a consequence of progressive dryout of the surface as the wall superheat increases. Machine learning tools are used with a heuristic model of the dryout parametric dependence to extract information about the magnitude of surface dryout as the superheat increases. From experimental data, the machine learning analysis provides an indication of how the dryout transition differs for different surface wetting characteristics and substrate materials. The wetting variations considered ranged from moderately wetted plain aluminum and copper surfaces to highly wetted nanostructured superhydrophilic surfaces. The data examined included aluminum and copper substrates. The results of the machine learning analysis indicate that the properties of the surface substrate can have a significant effect on the progressive surface dryout. In contrast, the surface wetting characteristics had a more limited effect for the surfaces tested. The paper concludes with an assessment of the implications of the findings for developing enhanced surfaces for boiling heat transfer performance.

Numerical Research on Heat Transfer Characteristics Analysis of Two Particles in Supercritical Water

In the supercritical water (SCW)-particle two-phase flow of fluidized bed, the particles that make up the particle cluster interact with each other through fluid, and it will affect the flow and heat transfer. However, due to the complex properties of SCW, the research on particle cluster is lacking, especially in terms of heat transfer. This research takes two particles as an example to study the heat transfer characteristics between SCW and another particle when one particle exists. This research uses the distance and angle between the two particles as the influencing factors to study the average heat transfer rate and local heat transfer rate. In this research, it is found that the effect is obvious when L/D = 1.1. When L = 1.1D, the temperature field and the flow field will partially overlap. The overlap of the temperature field will weaken the heat transfer between SCW and the particle. The overlap of the flow field has an enhanced effect on the heat transfer between SCW and the particle. The heat transfer between SCW and particles is simultaneously affected by these two effects, especially local heat transfer rate. In addition, this research also found that as the SCW temperature decreases, the thermal conductivity and specific heat of SCW increases, which enhances the heat transfer between SCW and the particles. This research is of great significance for studying the heat transfer characteristics of SCW-particle two-phase flow in fluidized bed.

Lightweight PEM Fuel Cell Stack for Unmanned Aerial Vehicle

Fuel cell is an electrochemical device that converts fuel into electricity. Polymer electrolyte membrane fuel cells (PEMFCs) have been used for ground transportation due to its high efficiency and zero carbon emission. When it comes to unmanned aerial vehicles (UAVs), PEMFCs can support much longer flight endurance than internal combustion engines and batteries do. However, a lightweight PEMFC stack is required in order to carry enough payload for UAVs. In this research, a lightweight fuel cell stack was developed and fabricated based on the Horizon fuel cell stack. The stack components, including end plates, bipolar plates, and interconnects were redesigned and fabricated to replace those heavy components. Additive manufacturing (3D printing) and electroplating were used to fabricate bipolar plates and interconnects, whereas the end plates were machined from Garolite XX plates. The fabricated lightweight PEMFC stacks were tested using a Scribner 850e Fuel Cell Test System. The lightweight stack assembled with six electroplated bipolar plates showed that the maximum power density estimated was 3.514 W/cm2 with 4.5 V and 1.6 A/cm2 conditions for 100 ml/min of H2. The same fuel cell stack tested at 200 ml/min and 300 ml/min showed higher maximum power densities than 100 ml/min. The presentation includes design and fabrication, performance characterization, weight reduction strategy, and future work.

Investigation of Buoyancy Effects in Asymmetrically Heated Near-Critical Flows of Carbon Dioxide in Horizontal Microchannels Using Infrared Thermography

In this study, we use infrared thermography to calculate local heat transfer coefficients of top and bottom heated flows of near-critical carbon dioxide in an array of parallel microchannels. These data are used to evaluate the relative importance of buoyancy for different flow arrangements. A Joule heated thin wall made of Inconel 718 applies a uniform heat flux either above or below the horizontal flow. A Torlon PAI test section consists of three parallel microchannels with a hydraulic diameter of 923 μm. The reduced inlet temperature (TR = 1.006) and reduced pressure (PR = 1.03) are held constant. For each heater orientation, the mass flux (520 kgm−2s−2 ≤ G ≤ 800 kgm−2s−2) and heat flux (4.7 Wcm−2 ≤ q″ ≤ 11.1 Wcm−2) are varied. A 2D resistance network analysis method calculates the bulk temperatures and heat transfer coefficients. In this analysis, we divide the test section into approximately 250 segments along the stream-wise direction. We then calculate the bulk temperatures using the enthalpy from the upstream segment, the heat flux in a segment, and the pressure. To isolate the effect of buoyancy, we screen the data to omit conditions where flow acceleration may be important or where relaminarization may occur. In the developed region of the channel, there was a 10 to 15 percent reduction of the local heat transfer coefficients for the upward heating mode compared to downward heating with the same mass and heat fluxes. Thus buoyancy effects should be considered when developing correlations for these types of flow.

Machine Learning for Chaotic Rayleigh Transitions

This paper is a preliminary report on work done to explore the use of unsupervised machine learning methods to predict the onset of turbulent transitions in natural convection systems. The Lorenz system was chosen to test the machine learning methods due to the relative simplicity of the dynamic system. We developed a robust numerical solution to the Lorenz equations using a fourth order Runge-Kutta method with a time step of 0.001 seconds. We solved the Lorenz equations for a large range of Raleigh ratios from 1–1000 while keeping the geometry and Prandtl number constant. We calculated the spectral density, various descriptive statistics, and a cluster analysis using unsupervised machine learning. We examined the performance of the machine learning system for different Raleigh ratio ranges. We found that the automated cluster analysis aligns well with well known key transition regions of the convection system. We determined that considering smaller ranges of Raleigh ratios may improve the performance of the machine learning tools. We also identified possible additional behaviors not shown in z-axis bifurcation plots. This unsupervised learning approach can be leveraged on other systems where numerical analysis is computationally intractable or more difficult. The results are interesting and provide a foundation for expanding the study for Prandtl number and geometry variations. Future work will focus on applying the methods to more complex natural convection systems, including the development of new methods for Nusselt correlations.

Flow Dynamics Over Two Cylinders in Tandem Subjected to Different Heating Cases

Heated and unheated flows with forced convection over two fixed circular cylinders in tandem are studied numerically for 80 ≤ Re ≤ 250 and 1 ≤ T* ≤ 2.3. Three different spacing ratios (L/D) = [2, 4, 8] are considered under three heating conditions. The scenarios considered are (1) heated upstream and unheated downstream cylinders, (2) unheated upstream and heated downstream cylinders and (3) heated upstream and downstream cylinders. These scenarios represent the limiting case for a cross-flow heat exchanger, where the downstream tubes are at increasingly lower or higher temperature for cooling or heating, respectively. The global aerodynamic forces on the cylinder as vortices shed was investigated. The flow is visualized by plotting the streamlines, temperature fields, and velocity magnitude contours for the different spacing ratios and compared to the flow regimes in literature namely, Extended-body, Reattachment, and Co-shedding regimes. The drag and surface heat transfer coefficients are analyzed for different scenarios. The effect of heating on the fluid properties and the resulted wakes in the flow are found to be strongly influenced by Re and L/D. The scenario of heated upstream and unheated downstream cylinders was found to increase the mean drag coefficient Cd on the upstream cylinder for L/D = 2 & 4 but is not as evident for the downstream cylinder. The heat transfer coefficient h on the upstream cylinder remained approximately the same regardless of a heated or unheated downstream cylinder. In contrast, h of the downstream cylinder decreases for the scenario of heated upstream and downstream cylinder.