Optimizing Pulse Combustion Parameters in Carbon Anode Baking Furnaces for Aluminum Production

Pulsating flame jets have been widely used in open-top carbon anode baking furnaces for aluminum electrolysis. Reducing energy consumption and pollutant emissions are still major challenges in baking (heat-treatment) carbon anode blocks. It is also of immense significance to bake all the anodes uniformly irrespective of their position in the furnace. Baking homogeneity can be enhanced noticeably by optimizing anode baking operational, geometrical, and physical parameters. In the present study, CFD simulations are combined with a response surface methodology to investigate and optimize the effects of pulse pressure, pulse frequency, and mainstream inlet oxygen concentration and mainstream inlet temperature. Two-levels half fractional factorial design with a center point is employed. It is perceived that pulse combustion with short pulse time and high momentum results in significant enhancement of the anode baking furnace energy efficiency. The temperature homogeneity is also significantly improved. It is found that the oxygen concentration is statistically the most significant parameter on NOx and soot formations, followed by the fuel flow rate. For NOx formation, air inlet oxygen concentration has a strong interaction with pulse duration. Coupling CFD models with the response surface methodologies demonstrated great potential in multi-objective optimization of the anode baking process with enhanced energy efficiency and baking uniformity.

Peltier Cooling for Low Concentration Photovoltaic Cells: Numerical Modeling and Feasibility Study

Thermal management of concentrating photovoltaic (CPV) panels is known as a major concern that has been investigated in the recent years. Appropriate cooling techniques must be employed to maintain optimum cell temperature, thus improving system efficiency and life cycle. Thermoelectric cooling offers several attractive characteristics including high controllability, no need to refrigerant, modularity, quiet operation and more. In this paper, the possibility of using convective cooling using a water channel along with thermoelectric cooling for a low concentration photovoltaic (LCPV) module is investigated. A numerical model is developed using COMSOL Multiphysics® and MATLAB® to assess the performance of a novel CPV-TE system. The proposed system consists of a Thermoelectric cooling (TEC) module attached to the backside of a photovoltaic (PV) cell. A water channel has been implemented on the backside of the Peltier module to provide effective heat removal using water flow. A parametric study is conducted on the proposed system by varying solar concentration incident on the PV, input current to the Peltier cooler and inlet velocity and temperature of the water flow. The temperature distribution through the system, power output from the PV module and energy consumption by the Peltier module are determined under different operational circumstances. The results are extensively discussed to provide an understanding regarding the feasibility of the proposed system.

Genetic Algorithm Based Topology Optimization of Heat Exchanger Fins Used in Aerospace Applications

Topology Optimization (TO) in the design of structural components is commonly used and well explored. However, its usage in the design of complex thermo-fluid equipment used in aerospace applications is limited and relatively new. This is because the coupling between the fluid dynamics, heat transfer, and the shape is complex and nonlinear. Furthermore, the resulting geometry from a TO analysis is often very complex and difficult to manufacture due to the free forms that can occur. With the advent of Additive Manufacturing (AM), however, it has become possible to directly manufacture complex geometries. This study develops a new Genetic Algorithm (GA) based TO combined with Computational Fluid Dynamics (CFD) to produce optimized fin shapes for heat exchangers used in aerospace applications. To implement this approach, a rectangular shaped baseline fin geometry was created using voxel representation. An initial population is generated by mutating the baseline fin a random number of times. The CFD package OpenFOAM is then used to evaluate the performance of each design, after which the optimization algorithm is applied. The GA sorts the designs using a composite fitness function that is comprised of the overall heat transfer and pressure drop, and generates new generations based on mutation and carryover of top performing designs. The study also explores the sensitivity of the GA to the various GA parameters as well as the effect of varying flow Reynolds number. In general, as Reynolds number increases, the percent improvement in the optimum relative to the baseline increases, with potentially a 60% performance improvement. Overall, the approach enables generation of novel freeform designs that may open new performance space for heat transfer applications.

Phenomenon of Fog Formation and Flow Characteristics of Droplet-Vapor-Gas Mixture in a Cooler-Condenser

Fog formation occurs in the process of condensation in the presence of non-condensable gas if the bulk temperature is lower than its saturation temperature (supersaturated). The phenomena of fogging is the formation of small condensate particles mixing with the vapor/gas stream, which creates potential problems of the vapor/gas/condensate separation and environmental pollution. Therefore, understanding of fogging mechanism and prevention of fog droplet entrainment are one of technical concerns for design and operation of cooler-condensers in the process industry. This paper presents the experimental study and numerical simulation of shell-side condensation with fog formation using a mixture of steam/non-condensable gas. The experimental data were collected on the two tube bundles (modified plastic tubes and stainless steel tubes). Using a high-speed photograph technique, the phenomenon of fog formation and flow characteristics of vapor/droplet transport were recorded over a wide range of test conditions. The numerical analysis of film and dropwise condensation, fog formation and droplet particle transport were simulated using different tube geometry and material, and flow velocity of air/droplet mixture. Based on simulation results, a new droplet trapping parameter is proposed to assess the optimal parameters of heat exchanger structural and operation conditions. Comparisons show that the numerical analysis results have a good agreement with experimental data and observations. These findings provide fundamental approach to account for the effect of fog formation, film and dropwise condensation, and droplet transport crossflow in cooler-condensers.

Curvature Change Analysis of SMART Fibers Used for Temperature Adaptive Insulation

A new method of characterizing the curvature change in thermally adaptive fibers is introduced in this paper. Based on the same principle as bi-metallic strips commonly found in thermostats, multi-component polymer fibers can be created to change their geometrical form in response to a temperature change. This works by creating fibers from two or more materials that have a mismatched Coefficient of Thermal Expansion (CTE). A temperature change leads to a change in curvature of these fibers. When fibers interact in an insulation batting structure, a temperature change leads to a thickness change in the insulation. While these fibers have visually been observed to function, there was no method to quantitatively characterize their curvature performance. This paper introduces a method that can be used to quantify fiber performance by tracking change in curvature over a specific temperature range. This is accomplished by suspending fibers on the surface of a liquid bath and changing the bath temperature. Digital images of the fiber are taken at different temperatures and analyzed using software to determine the radius of curvature. Absolute change in curvature was found to be as high as 0.5% per degree °C from 20 to −20°C for certain samples. A trend was also noted between higher initial curvature and lower overall performance. Digital image correlation was further used to investigate the time-dependence relationship of fiber curvature. Future experiments can be performed with this setup to characterize and compare curvature change performance of different fibers accurately.

An Evaluation of the Effects of Team Projects and Augmented Reality on Student Learning in Sustainable Building Science

Sustainable building design and construction involves complex systems that require multidisciplinary teams from engineering, construction, and architecture, to design and analyze the systems at every stage of the process during the building’s life cycle. However, students who are the future work force are often trained in different disciplines across different colleges. When these students are grouped together to work on the building design and analysis, learning in a multidisciplinary environment could be both beneficial and challenging due to the difference in their background. In this paper, we report our experience and analysis of data examining the learning effectiveness of the undergraduate students from three cross-college departments in architecture, construction, and engineering. Using pre- and post-semester tests on selected building science problems, we have investigated how the student’s understanding of building science had changed through team projects. Particularly, for mechanical engineering students in the design of thermal/fluid systems classes, we analyzed whether a cross-college multidisciplinary team could do better as compared to a disciplinary-specific team within the same class. We also examined the potential effects of emerging technology, augmented reality, on student learning in the same team environment. It was interesting to find that students’ learning in discipline-specific teams can be improved as in the multidisciplinary teams, due to the challenges in the complexity of the projects.

Centrifugal Compressor Performance Prediction Using Gaussian Process Regression and Artificial Neural Networks

In this paper, we use various regression models and Artificial Neural Network (ANN) to predict the centrifugal compressor performance map. Particularly, we study the accuracy and efficiency of Gaussian Process Regression (GPR) and Artificial Neural Networks in modelling the pressure ratio, given the mass flow rate and rotational speed of a centrifugal compressor. Preliminary results show that both GPR and ANN can predict the compressor performance map well, for both interpolation and extrapolation. We also study the data augmentation and data minimzation effects using the GPR. Due to the inherent pressure ratio data distribution in mass-flow-rate and rotational-speed space, data augmentation in the rotational speed is more effective to improve the ANN performance than the mass flow rate data augmentation.

Concurrent-Flow Flame Spread Over a Thin Solid in a Narrow Confined Space in Microgravity

A numerical study is pursued to investigate the aerodynamics and thermal interactions between a spreading flame and the surrounding walls as well as their effects on fire behaviors. This is done in support of upcoming microgravity experiments aboard the International Space Station. For the numerical study, a three-dimensional transient Computational Fluid Dynamics combustion model is used to simulate concurrent-flow flame spread over a thin solid sample in a narrow flow duct. The height of the flow duct is the main parameter. The numerical results predict a quenching height for the flow duct below which the flame fails to spread. For duct heights sufficiently larger than the quenching height, the flame reaches a steady spreading state before the sample is fully consumed. The flame spread rate and the pyrolysis length at steady state first increase and then decrease when the flow duct height decreases. The detailed gas and solid profiles show that flow confinement has competing effects on the flame spread process. On one hand, it accelerates flow during thermal expansion from combustion, intensifying the flame. On the other hand, increasing flow confinement reduces the oxygen supply to the flame and increases conductive heat loss to the walls, both of which weaken the flame. These competing effects result in the aforementioned non-monotonic trend of flame spread rate as duct height varies. This work relates to upcoming microgravity experiments, in which flat thin samples will be burned in a low-speed concurrent flow using a small flow duct aboard the International Space Station. Two baffles will be installed parallel to the fuel sample (one on each side of the sample) to create an effective reduction in the height of the flow duct. The concept and setup of the experiments are presented in this work.

Methane Emissions Reduction in Liquefied Natural Gas Off-Loading Process in Refueling Stations

Recent research into methane emissions from the liquefied natural gas (LNG) supply chain has revealed uncertainty in the overall greenhouse gas emissions reduction associated with the use of LNG in heavy-duty vehicles. Methane is the main component of natural gas and a potent greenhouse gas. This study investigates the impact of five methods used to offload LNG from a tanker truck to an LNG refueling station and estimate the amount of fugitive methane emissions. The LNG offloading process time, and the final pressures of the tanker truck and refueling station are considered to evaluate the performance of the LNG offloading methods. The modeling results show that the LNG transfer by using a pressure buildup unit has a limited operating range and can increase methane emissions by 10.4% of LNG offloaded from the tanker truck. The results indicate that the LNG transfer by using a pump and an auxiliary pressure buildup unit without vapor return provides the shortest fuel offloading time with the lowest risk of venting methane to the atmosphere.

Singular Perturbation Solution for a Two-Phase Stefan Problem in Outward Solidification

Mathematical modeling of phase change process in porous media can help ensure the efficient design and operation of thermal energy storage and pipe freezing. Numerical methods generally require high computational power to be applicable in practice. Therefore, it is of great interest to develop accurate and reliable analytical frameworks. This study proposes a singular perturbation solution for a two-phase Stefan problem that describes outward solidification in a finite annular space. The problem solves cylindrical heat conduction equations for both solid and liquid phases, with consideration of a moving boundary condition. Perturbation method takes the advantages of small Stefan number as the perturbation parameter, which intrinsically occurs in porous media. Furthermore, a boundary-fixing technique is used to remove nonlinearity in the moving boundary condition. Two different time scales are separately expanded and evaluated to facilitate the construction of a composite asymptotic solution. The analytical solution is verified against a general numerical model using enthalpy method and local volume-averaged thermal properties. The results indicate that the temperature profile of both phases can be well modeled by singular perturbation theory. The analytical solution is found to have similar conclusions to the numerical analysis with much lesser computational cost.