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Creators/Authors contains: "Bhattacharyya, Anurag"

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  1. ABSTRACT In topology optimization of compliant mechanisms, the specific placement of boundary conditions strongly affects the resulting material distribution and performance of the design. At the same time, the most effective locations of the loads and supports are often difficult to find manually. This substantially limits topology optimization's effectiveness for many mechanism design problems. We remove this limitation by developing a method which automatically determines optimal positioning of a prescribed input displacement and a set of supports simultaneously with an optimal material layout. Using nonlinear elastic physics, we synthesize a variety of compliant mechanisms with large output displacements, snap‐through responses, and prescribed output paths, producing designs with significantly improved performance in every case tested. Compared to optimal designs generated using manually designed boundary conditions used in previous studies, the mechanisms presented in this paper see performance increases ranging from 47% to 380%. The results show that nonlinear mechanism responses may be particularly sensitive to boundary condition locations and that effective placements can be difficult to find without an automated method. 
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    Free, publicly-accessible full text available January 15, 2026
  2. In current engineering practice, computer-aided design (CAD) tools play a key role in the design and fabrication of most mechanical systems, including the design of most vehicles. This software tends to rely heavily on human designers to provide the basic design concept, with the software being used to computationally render an existing design, or to perform modifications to a design to achieve incremental improvements in performance. However, an emerging class of computational methods, known astopology optimizationmethods, offers the potential for trueblack boxcomputational design. Under this general framework, practitioners provide the algorithm with the constitutive properties of the design materials, and the mechanical function being designed for (e.g. maximum stiffness under a given loading condition), and the algorithm autonomously generates a description of the corresponding structure. With some exceptions, existing topology optimization methods are limited to generating static, single-body designs. In this study, we present a novel method that builds upon the current state of the art by combining multiple collocated planar design domains to achieve automated computational synthesis of multi-body wheeled vehicles. This capability represents an important step on the path toward automated computational design of increasingly complex, innovative and impactful mechanical systems. 
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  3. null (Ed.)
    We present a novel optimization framework for optimal design of structures exhibiting memory characteristics by incorporating shape memory polymers (SMPs). SMPs are a class of memory materials capable of undergoing and recovering applied deformations. A finite-element analysis incorporating the additive decomposition of small strain is implemented to analyze and predict temperature-dependent memory characteristics of SMPs. The finite element method consists of a viscoelastic material modelling combined with a temperature-dependent strain storage mechanism, giving SMPs their characteristic property. The thermo-mechanical characteristics of SMPs are exploited to actuate structural deflection to enable morphing toward a target shape. A time-dependent adjoint sensitivity formulation implemented through a recursive algorithm is used to calculate the gradients required for the topology optimization algorithm. Multimaterial topology optimization combined with the thermo-mechanical programming cycle is used to optimally distribute the active and passive SMP materials within the design domain. This allows us to tailor the response of the structures to design them with specific target displacements, by exploiting the difference in the glass-transition temperatures of the two SMP materials. Forward analysis and sensitivity calculations are combined in a PETSc-based optimization framework to enable efficient multi-functional, multimaterial structural design with controlled deformations. 
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