Karthik K. Bodla

Microtomography-Based Simulation of Transport through Open-Cell Metal Foams

Important heat transfer parameters of aluminum foams of varying pore sizes are investigated through CT-scanning at 20 micron resolution. Small sub-samples from the resulting images are processed to generate feature-preserving, finite-volume meshes of high quality. All three foam samples exhibit similar volumetric porosity (in the range ∼91–93%), and thereby a similar thermal conductivity. Effective tortuosity for conduction along the coordinate directions is also calculated. Permeability simulations in the Darcy flow regime with air and water show that the foam permeability is isotropic and is of the order of 10−7 m2. The convective heat transfer results computed for this range of Reynolds numbers exhibit a dependence on the linear porosity, even though the corresponding volumetric porosity is the same for all the samples considered.

Advances in Fluid and Thermal Transport Property Analysis and Design of Sintered Porous Wick Microstructures

Sintered porous structures are ubiquitous as heat transport media for thermal management and other applications. In particular, low-porosity sintered packed beds are used as capillary-wicking and evaporation-enhancement structures in heat pipes. Accurate prediction and analysis of their transport characteristics for different microstructure geometries is important for improved design. Owing to the random nature and geometric complexity of these materials, development of predictive methods has been the subject of extensive prior research. The present work summarizes and builds upon past studies and recent advances in pore-scale modeling of fluid and thermal transport within such heterogeneous media. A brief review of various analytical and numerical models for simplified prediction of transport characteristics such as effective thermal conductivity, permeability, and interfacial heat transfer is presented. More recently, there has been a growing interest in direct numerical simulation of transport in realistic representations of the porous medium geometry; for example, by employing nondestructive 3D imaging techniques such as X-ray microtomography. Future research directions are identified, looking beyond techniques intended for material characterization alone, and focusing on those targeting the reverse engineering of wick structures via modeling of the physical sintering fabrication processes. This approach may eventually be employed to design intricate sintered porous structures with desired properties tailored to specific applications.

Optimization Under Uncertainty Applied to Heat Sink Design

Optimization under uncertainty (OUU) is a powerful methodology used in design and optimization to produce robust, reliable designs. Such an optimization methodology, employed when the input quantities of interest are uncertain, yields output uncertainties that help the designer choose appropriate values for input parameters to produce safe designs. Apart from providing basic statistical information, such as mean and standard deviation in the output quantities, uncertainty-based optimization produces auxiliary information, such as local and global sensitivities. The designer may thus decide the input parameter(s) to which the output quantity of interest is most sensitive, and thereby design better experiments based on just the most sensitive input parameter(s). Another critical output of such a methodology is the solution to the inverse problem, i.e., finding the allowable uncertainty (range) in the input parameter(s), given an acceptable uncertainty (range) in the output quantities of interest. We apply optimization under uncertainty to the problem of heat transfer in fin heat sinks with uncertainties in geometry and operating conditions. The analysis methodology is implemented using DAKOTA, an open-source design and analysis kit. A response surface is first generated which captures the dependence of the quantity of interest on inputs. This response surface is then used to perform both deterministic and probabilistic optimization of the heat sink, and the results of the two approaches are compared.

Optimization under uncertainty for electronics cooling design applications

Optimization under uncertainty is a powerful methodology used in design and optimization to produce robust, reliable designs. Such an optimization methodology, employed when the input quantities of interest are uncertain, yields output uncertainties that help the designer choose appropriate values for input parameters to produce safe designs. Apart from providing basic statistical information such as mean and standard deviation in the output quantities, uncertainty-based optimization produces auxiliary information such as local and global sensitivities. The designer may thus decide the input parameter(s) to which the output quantity of interest is most sensitive, and thereby design better experiments based on just the most sensitive input parameter(s). Another critical output of such a methodology is the solution to the inverse problem, i.e, finding the allowable uncertainty (range) in the input parameter(s), given an acceptable uncertainty (range) in the output quantities of interest. We apply optimization under uncertainty to the problem of heat transfer in fin heat sinks with uncertainties in geometry and operating conditions. The analysis methodology is implemented using DAKOTA, an open source design and analysis kit. A response surface is first generated which captures the dependence of the quantity of interest on inputs. This response surface is then used to perform both deterministic and probabilistic optimization of the heat sink, and the results of the two approaches are compared.

Sinusoidal Reluctance Machine With DC Winding: An Attractive Non-Permanent-Magnet Option

Important global efforts are underway toward lowering the cost of electric machines for electric and hybrid vehicles by reducing or eliminating the use of rare earth materials which have been experiencing significant price increases and volatility. Non-permanent magnet electric machines are a potential solution and are increasingly investigated by researchers worldwide. This paper presents a DC biased reluctance machine which is structurally similar to a conventional switched reluctance machine. This type of machine has a DC field winding and an AC three phase armature winding. It uses a conventional three phase inverter for the armature and an additional auxiliary DC/DC converter for the field winding. This reluctance machine is designed to achieve hybrid vehicle traction requirements of 55kW peak at 2800 rpm and 30kW continuous over a speed range going from 2800 rpm to 14000 rpm.

XMT-based direct simulation of flow and heat transfer through open-cell aluminum foams

Three aluminum foam samples of varying pore sizes - 10 ppi, 20 ppi and 40 ppi - are CT-scanned using a commercial X-ray scanner at 20 micron resolution for measuring and comparing important heat transfer parameters such as effective thermal conductivity and Nusselt number. Small sub-samples from the resulting stack of images are processed to generate featurepreserving high-quality finite-volume meshes. It is observed that all three foam samples exhibit similar volumetric porosity (in the range ∼ 91–93%), and thereby a similar thermal conductivity. For the domain sizes considered, the samples exhibit anisotropic conduction along the three coordinate directions of the mesh, which is attributed to the randomness of the structure and the small domain sizes considered. The values of average effective thermal conductivity are compared with a number of previous experimental and simulation results. Effective tortuosity for conduction along the coordinate directions is also calculated. Permeability simulations in the Darcy flow regime with air and water show that foam permeability is isotropic and is of the order of 10−7 m2. The resulting friction factor variation with Reynolds number is validated against published results. Nusselt numbers are also computed for this range of Reynolds numbers. The heat transfer results exhibit a dependence on the linear porosity, even though the corresponding volumetric porosity is the same for all the samples considered.

Sinusoidal reluctance machine with DC winding: An attractive non-permanent magnet option

Important global efforts are underway toward lowering the cost of electric machines for electric and hybrid vehicles by reducing or eliminating the use of rare-earth materials which have been experiencing significant price increases and volatility. Non-permanent-magnet (non-PM) electric machines are a potential solution and are increasingly investigated by researchers worldwide. This paper presents a DC-biased reluctance machine, which is structurally similar to a conventional switched reluctance machine. This type of machine has a DC field winding and an AC three-phase armature winding. It uses a conventional three phase inverter for the armature and an additional auxiliary DC/DC converter for the field winding. This reluctance machine is designed to achieve hybrid vehicle traction requirements of 55 kW peak at 2800 r/min and 30 kW continuous over a speed range going from 2800 to 14 000 r/min.

Simulated Microstructural Evolution and Design of Porous Sintered Wicks

Porous structures formed by sintering of powders, which involves material-bonding under the application of heat, are commonly employed as capillary wicks in two-phase heat transport devices such as heat pipes. These sintered wicks are often fabricated in an ad hoc manner, and their microstructure is not optimized for fluid and thermal performance. Understanding the role of sintering kinetics—and the resulting microstructural evolution—on wick transport properties is important for fabrication of structures with optimal performance. A cellular automaton model is developed in this work for predicting microstructural evolution during sintering. The model, which determines mass transport during sintering based on curvature gradients in digital images, is first verified against benchmark cases, such as the evolution of a square shape into an areapreserving circle. The model is then employed to predict the sintering dynamics of a sideby-side, two-particle configuration conventionally used for the study of sintering. Results from previously published studies on sintering of cylindrical wires are used for validation. Randomly packed multiparticle configurations are then considered in two and three dimensions. Sintering kinetics are described by the relative change in overall surface area of the compact compared to the initial random packing. The effect of sintering parameters, particle size, and porosity on fundamental transport properties, viz., effective thermal conductivity and permeability, is analyzed. The effective thermal conductivity increases monotonically as either the sintering time or temperature is increased. Permeability is observed to increase with particle size and porosity. As sintering progresses, the slight increase observed in the permeability of the microstructure is attributed to a reduction in the surface area. [DOI: 10.1115/1.4026969]

Particle image velocimetry study on dual cooling jet flows

With the advance of the Internet of Things (IoT), electronics are becoming more prevalent in applications outside the traditional consumer electronics environment. Current electronic systems are often challenged by operation at extreme low temperature, high temperature, rapid cycling temperature, vibration, or dust-filled environments. Typical systems for these environments are natural convection cooled and sealed to protect the interior electronics from the exterior environment but this has as consequence that efficient heat removal is challenging, limiting electronics capability. Application of fans is often considered to negatively impact reliability. Dual Cool Jet (DCJ) is a variant of variable orifice synthetic jet(VO-SJ) consisting of piezo actuated metal disks that are mechanically configured to form a miniature thin form factor air mover. The DCJ does not require bearings or a DC motor making the air mover potentially lower cost and more reliable, making it an attractive candidate for electronics in harsher environments. DCJ produces a pulsing jet of high velocity air flow, imparting momentum on the adjacent fluid creating series of counter rotating vortex pairs. The flow field produced by a DCJ has been numerically studied and has proven to be a complex function of the transient aero-mechanical interaction between the disks and the internal air volume. This study provides a unique insight in the air flow field of a DCJ by publishing time-resolved particle image velocimetry and displacement measurement results. These results show that the variable orifice nature of DCJ (2.5X area change) plays a key role in generating a difference between ingestion and expulsion velocity of as much as 8x, resulting in a new flow generated by the device. The study explores the effect of DCJ actuation frequency and its effect on the flow characteristics. The results aid to better understand the application of synthetic jets like DCJ and further help to advance future technology applications.

Test results for a high temperature non-permanent magnet traction motor

Commercially available hybrid and electric vehicles are generally using rare earth PM motors because of their compactness and very good efficiency. But the supply security and price volatility of rare-earth materials are still major concerns for the hybrid and electric vehicle industry. Hence, global efforts are underway in several countries on using reduced or non-rare earth materials, developing non-permanent magnet solutions and taking cost out by trading off between material properties and cost. Non-permanent magnet machines are generally known to be less power dense than permanent magnet counterparts. But the absence of permanent magnets in these machines makes them well suited for high temperature applications provided appropriate stator winding insulation materials are used. This offers a degree of freedom in improving their power density because they can operate at higher electrical loading while maintaining acceptable efficiency. This paper presents a high temperature DC biased reluctance machine which is structurally similar to a conventional switched reluctance machine. This non-permanent magnet machine has a DC field winding and an AC three phase armature winding. The machine is equipped with a high temperature 280oC rated insulation system. Test results showing machine performance under continuous operation against the FreedomCar 2020 specifications as well as at high temperature up to 280oC are presented. A 43% improvement in power density was achieved by going to high temperature.