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27 results on '"Bhat, Chandan"'

3. An Insight into the Warping Spatial Sampling Method in Subsurface Radar Imaging and Its Experimental Validation.

Author

Maisto, Maria Antonia, Bhat, Chandan, and Solimene, Raffaele

Subjects
*MICROWAVE imaging, *BORN approximation, *SAMPLING methods, *BURIED pipes (Engineering), *GROUND penetrating radar, *OPTICAL disks, *RADAR
Abstract

In this paper, we are concerned with microwave subsurface imaging achieved by inverting the linearized scattering operator arising from the Born approximation. In particular, we consider the important question of reducing the required data to achieve imaging. This can help to reduce the radar system's cost and complexity and mitigate the imaging algorithm's computational burden and the needed storage resources. To cope with these issues, in the framework of a multi-monostatic/multi-frequency configuration, we introduce a new spatial sampling scheme, named the warping method, that allows for a significant reduction in spatial measurements compared to other literature approaches. The basic idea is to introduce some variable transformations that "warp" the measurement space so that the reconstruction point-spread function obtained by adjoint inversion is recast as a Fourier-like transformation, which provides insights into how to achieve the sampling. In our previous contributions, we focused on presenting and checking the theoretical background with simple numerical examples. In this contribution, we briefly review the key components of the warping method and present its experimental validation by considering a realistic subsurface scattering scenario for the case of a buried water pipe. Essentially, we show that the latter succeeds in reducing the number of data compared to other approaches in the literature, without significantly affecting the reconstruction results. [ABSTRACT FROM AUTHOR]

Published
2023
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5. Tandem Neural Network Based Design of Multiband Antennas

Author

Gupta, Aggraj, Karahan, Emir Ali, Bhat, Chandan, Sengupta, Kaushik, and Khankhoje, Uday K.

Abstract

We present a deep neural network-based framework for designing multiband microstrip antennas given a desired impedance matching spectrum. The approach enables a design methodology that generates the desired antenna structures rapidly (under a second) through an effective deep learning-enabled search of a large design space and eliminates the need for extensive domain knowledge of antenna design. The framework is built on our innovations in tandem neural networks consisting of two cascaded neural networks. Our structures are parameterized in an exponentially large design space of discrete variables (pixels), leading to the realization of nonintuitive structures. This end-to-end synthesis in terms of discrete variables is enabled by introducing a new type of “smooth thresholding” (ST) activation function, which, along with crucial regularization terms in the network loss function, aids in designing our structures. We perform extensive neural network optimizations and study various trade-offs in the design process. We demonstrate the efficacy of our methods by generating single and dual-band resonant structures, which can be up to 50% more compact in terms of area, and up to 18% thinner in terms of substrate height than conventional structures, while retaining competitive performance parameters in terms of gain, polarization properties, radiation efficiency (RE), and fractional bandwidth (FBW).

Published
2023
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27. Solder Joint Reliability & Prognostication of Lead Free Electronics in Harsh Thermo-Mechanical Environments

Author

Bhat, Chandan

Subjects
Mechanical Engineering
Abstract

The trends in the electronic packaging industry are to design smaller packages that have higher complexity, and to improve package reliability while reducing costs. These needs in the packaging industry have lead to a newer generation of chip architectures, such as: Chip Scale Packages, Plastic Ball Grid Arrays, and Flip Chips. However, despite the increased performance capabilities of these leading-edge package types, their thermo-mechanical reliability is a concern for harsh environment applications. In this study, the thermo-mechanical reliability of a new architecture (D-PackTM) has been studied using finite element methods. Life prediction relationships based on damage accumulation principles have been used to calculate the characteristic life, and has been compared with thermal shock data. Failure analysis of the tested assemblies has been conducted to correlate failure locations with predictions from FEM. While reliability analysis of any component is critical, it is also important to monitor the condition / state of the system from time to time in order to improve the system availability and upkeep. So far, traditional health monitoring methodologies have relied on reactive methods of failure detection often providing little on no insight into the remaining useful life of the system. Detection of system-state significantly prior to catastrophic failure can significantly impact the reliability and availability of electronic systems. Previously, Lall [2004, 2005] have developed methodologies for health management and interrogation of system state of electronic systems based on leading indicators for eutectic Sn-Pb & 95.5Sn4.0Ag0.5Cu solders. Examples of damage pre-cursors include micro-structural evolution, intermetallics. In this study, a mathematical approach for interrogation of system state under cyclic thermo-mechanical and iso-thermal stresses has been developed for 4-different lead-free solder alloy systems. Data has been collected for leading indicators of failure for alloy systems including, SnAgCu, SnAgCuBi, SnAgCuBiNi, SnAg second-level interconnects under the application of thermo-mechanical loads. Methodology presented resides in the pre-failure space of the system in which no macro-indicators such as cracks or delamination exist. Systems subjected to thermo-mechanical damage have been interrogated for system state and the computed damage state correlated with known imposed damage. The approach involves the use of condition monitoring devices which can be interrogated for damage proxies at finite time-intervals. Interrogation techniques are based on non-linear least-squares methods. Various techniques including the Levenberg-Marquardt Algorithm have been investigated. The system’s residual life is computed based on residual-life computation algorithms.

Published
2008

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