Engineering topics

Rajagopal, Manjunath C.

Publications and source records attributed to Rajagopal, Manjunath C..

5 records

DOE OSTI2024

Method and apparatus for fabricating a hybrid tube

An apparatus for fabricating a hybrid tube includes a rotatable mandrel and a first housing configured to translate alongside the rotatable mandrel while dispensing a first strip to be helically wound about the mandrel. The first housing includes an angle adjustment mechanism to control a dispensation angle of the first strip. The apparatus also includes least one energy or adhesive source for bonding overlapping strip portions on the rotatable mandrel and forming the hybrid tube. The at least one energy or adhesive source is configured for translation alongside the rotatable mandrel.

Sinha, Sanjiv↗

DOE OSTI2020

Intrinsic thermal interfacial resistance measurement in bonded metal–polymer foils

Heat conduction through bonded metal–polymer interfaces often limits the overall heat transfer in electronic packaging, batteries, and heat recovery systems. To design the thermal circuit in such systems, it is essential to measure the thermal interfacial resistance (TIR) across ~1 µm to 100 µm junctions. Previously reported TIR of metal–polymer junctions utilize ASTM E1530-based two-block systems that measure the TIR by applying pressure across the interface through external heating and cooling blocks. Here, we report a novel modification of the ASTM-E1530 technique that employs integrated heaters and sensors to provide an intrinsic TIR measurement of an adhesively bonded metal–polymer junction. We design the measurement technique using finite element simulations to either passively suppress or actively compensate the lateral heat diffusion through the polymer, which can minimize the systematic error to ≲5%. Through proof-of-concept experiments, we report the TIR of metal–polymer interfaces made from DuPont’s Pyralux double-side copper-clad laminates, commonly used in flexible printed circuit boards. Our TIR measurement errors are <10%. We highlight additional sources of errors due to non-idealities in the experiment and discuss possible ways to overcome them. Our measurement technique is also applicable to interfaces that are electrically insulating such as adhesively joined metal–metal junctions and sputter-coated or welded metal–polymer junctions. Altogether, the technique is capable of measuring TIR ≳10 –5 m 2 KW –1 in bonded metal–polymer foils and can be tailored for in situ measurements in flexible electronics, circuit packaging, and other hybrid metal–polymer systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Fouling modeling and prediction approach for heat exchangers using deep learning

In this article, we develop a generalized and scalable statistical model for accurate prediction of fouling resistance using commonly measured parameters of industrial heat exchangers. This prediction model is based on deep learning where a scalable algorithmic architecture learns non-linear functional relationships between a set of target and predictor variables from large number of training samples. Here, the efficacy of this modeling approach is demonstrated for predicting fouling in an analytically modeled cross-flow heat exchanger, designed for waste heat recovery from flue-gas using room temperature water. The performance results of the trained models demonstrate that the mean absolute prediction errors are under 10 –4 KW –1 for flue-gas side, water side and overall fouling resistances. The coefficients of determination (R 2 ), which characterize the goodness of fit between the predictions and observed data, are over 99%. Even under varying levels of measurement noise in the inputs, we demonstrate that predictions over an ensemble of multiple neural networks achieves better accuracy and robustness to noise. We find that the proposed deep-learning fouling prediction framework learns to follow heat exchanger flow and heat transfer physics, which we confirm using locally interpretable model agnostic explanations around randomly selected operating points. Overall, we provide a robust algorithmic framework for fouling prediction that can be generalized and scaled to various types of industrial heat exchangers.

42 ENGINEERING↗

DOE OSTI2020

Thermal conductivity measurement of the interaction layer between UMo and Al produced by high-energy heavy ion irradiation

In this work, we report the first direct thermal conductivity measurement results for Al-UMo interaction layer (IL), which is typically observed in UMo/Al dispersion fuel plates under irradiation. The investigated IL was formed by irradiating Al coated UMo substrate using 80 MeV iodine ions at 180 degrees C up to 3.03 x 10 17 ions/cm 2 fluence. Microstructural characterization indicated that the induced IL is amorphous with an approximately (U 0.8 ,Mo 0.2 )Al 5.3 stoichiometry, which is similar to that formed under in-pile irradiation. Focused ion beam (FIB) was used to prepare nine specimens of various lengths from the IL that could be suspended across a microfabricated device for thermal conductivity measurement. The measured thermal conductivity values of the IL were significantly lower than the values for both the original UMo fuel and the Al. The successful measurement of the Al-UMo IL provides valuable information for the development and qualification of UMo/Al dispersion fuels for research and test reactor conversion applications, and further demonstrates the promising capabilities of utilizing the suspended bridge method in nuclear fuel research.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Composite Structured Surfaces for Durable Dropwise Condensation

Dropwise condensation of steam on hydrophobic substrates has a 10X higher heat transfer coefficient compared to filmwise condensation. To promote dropwise condensation, low surface energy hydrophobic coatings (polymers) are typically utilized. The low intrinsic thermal conductivity (k < 1 W/(m · K)) of polymers, coupled with high heat transfer coefficient of dropwise condensation (100 kW/(m 2 · K)), necessitates that the coating be thin (< 1µm) in order to avoid reducing the overall heat exchanger conductance. However, thin polymeric films easily degrade. The two opposing requirements result in the need for optimization between the durability (thick coating) and the heat transfer (thin coating). To enable high thermal conductivity in thicker coatings, we develop metal-polymer structured surfaces. By using porous structures as inter-connected heat-conducting backbones that are filled with hydrophobic materials, we enable tuning of the coating effective thermal conductivity and surface energy. Three metal structures were studied; micro/nanowires, inverse opals, and sintered spheres. Heat transfer performance was calculated using three-dimensional finite element method simulations with two distinct boundary conditions; convection at the walls and isothermal walls. Interestingly, the overall conductance shows up to 40% difference depending on the boundary condition used in calculating the composite coating effective thermal conductivity. We use our model to predict the heat transfer performance as a function of metal fraction by volume and by surface area for condensation. By coupling our thermal simulations with a previously verified analytical model for predicting wetting behavior on heterogeneous surfaces, we propose a regime map to predict dropwise-to-filmwise transition. Furthermore, our work not only forms a starting point for the development of durable dropwise condensing surfaces, it identifies important considerations needed for computing effective thermal conductivity of composites.

42 ENGINEERING↗