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1. Design and Modeling Framework for DexTeR: Dexterous Continuum Tensegrity Manipulator

   https://doi.org/10.1115/1.4056959  

   Woods, Cole; Vikas, Vishesh (June 2023, Journal of Mechanisms and Robotics)

   Abstract The field of tensegrity faces challenges in design to facilitate efficient fabrication, and modeling due to the antagonistic nature of tension and compression elements. The research presents design methodology, and modeling framework for a human-spine inspired Dexterous continuum Tensegrity manipulatoR (DexTeR). DexTeR is a continuum manipulator that comprises of an assembly of “vertebra” modules fabricated using two curved links and 12 strings, and actuated using motor-tendon actuators. The fabrication methodology involves the construction of the equivalent graph of the module and finding the Euler path that traverses every edge of the graph exactly once. The vertices and edges of the graph correspond to the holes and strings or links of the mechanism. Unlike traditional rigid manipulators, the design results in centralization of the majority of the weight of the actuators at the base with negligible effect on the manipulator dynamics. For the first time in literature, we fabricate a tensegrity manipulator that is assembled using ten modules to conceptually validate the time and cost efficiency of the approach. A dynamic model of a vertebra module is presented using the Euler–Newton approach with screw theory representation. Each rigid link is represented using a screw, a six-dimensional vector with components of angular rotation, and linear translation. The nonlinearity in the system arises from the discontinuous behavior of the strings and the “closed-chain” nature of the mechanism. The behavior of the strings is piece-wise continuous to model their slack, compliant, or tension states. 

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2. A viscoelastic Timoshenko beam: Model development, analysis, and investigation

   https://doi.org/10.1063/5.0091043  

   Zheng, Xiangcheng; Li, Yiqun; Wang, Hong (June 2022, Journal of Mathematical Physics)

   Vibrations are ubiquitous in mechanical or biological systems, and they are ruinous in numerous circumstances. We develop a viscoelastic Timoshenko beam model, which naturally captures distinctive power-law responses arising from a broad distribution of time-scales presented in the complex internal structures of viscoelastic materials and so provides a very competitive description of the mechanical responses of viscoelastic beams, thick beams, and beams subject to high-frequency excitations. We, then, prove the well-posedness and regularity of the viscoelastic Timoshenko beam model. We finally investigate the performance of the model, in comparison with the widely used Euler–Bernoulli and Timoshenko beam models, which shows the utility of the new model. 

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3. Accelerating LSTM-based High-Rate Dynamic System Models

   Ehsan Kabir, Daniel Coble (July 2023, Proc. 33rd International Conference on Field Programmable Logic and Applications (FPL 2023))

   In this paper, we evaluate the use of a trained Long Short-Term Memory (LSTM) network as a surrogate for a Euler–Bernoulli beam model, and then we describe and characterize an FPGA-based deployment of the model for use in real-time structural health monitoring applications. The focus of our efforts is the DROPBEAR (Dynamic Reproduction of Projectiles in Ballistic Environments for Advanced Research) dataset, which was generated as a benchmark for the study of real-time structural modeling applications. The purpose of DROPBEAR is to evaluate models that take vibration data as input and give the initial conditions of the cantilever beam on which the measurements were taken as output. DROPBEAR is meant to serve an exemplar for emerging high-rate “active structures” that can be actively controlled with feedback latencies of less than one microsecond. Although the Euler–Bernoulli beam model is a well-known solution to this modeling problem, its computational cost is prohibitive for the time scales of interest. It has been previously shown that a properly structured LSTM network can achieve comparable accuracy with less workload, but achieving sub-microsecond model latency remains a challenge. Our approach is to deploy the LSTM optimized specifically for latency on FPGA. We designed the model using both high-level synthesis (HLS) and hardware description language (HDL). The lowest latency of 1.42 µS and the highest throughput of 7.87 Gops/s were achieved on Alveo U55C platform for HDL design. 

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4. Contact resonance atomic force microscopy using long elastic tips

   https://doi.org/10.1088/1361-6528/ad0bd2  

   Zimron-Politi, Nadav; Tung, Ryan C (November 2023, Nanotechnology)

   Abstract In this work, a new theoretical model for contact resonance atomic force microscopy, which incorporates the elastic dynamics of a long sensing tip is presented. The model is based on the Euler–Bernoulli beam theory and includes coupling effects from the two-beam structure, also known as an ‘L-shaped’ beam in the literature. Here, high-accuracy prediction of the sample stiffness, using several vibration modes with a relative error smaller than 10% for practical working ranges, is demonstrated. A discussion on the model’s capability to predict the dynamic phenomena of eigenmode veering and crossing, as the force applied to the sample increases, is presented. The L-shaped beam model presented here is also applicable for structural applications such as: micro-electro-mechanical systems, energy harvesting, and unmanned aerial vehicle landing gear. 

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5. Predicting Needle Deflection in Soft Tissue: a Computational Modeling Approach

   https://doi.org/10.1115/IMECE2023-113833  

   Al-Safadi, Samer; Hutapea, Parsaoran (February 2024, Proceedings of the ASME 2023 International Mechanical Engineering Congress and Exposition)

   Abstract This study explores the mechanical interactions between surgical needles and soft tissues during procedures like biopsies and brachytherapy. A key challenge is needle tip deflection, which can cause deviation from the intended target. The study aims to develop an analytical model that predicts needle tip deflection during insertion by combining principles from interfacial mechanics and soft tissue deformation. A modified version of the dynamic Euler-Bernoulli beam theory is employed to model needle insertion and predict needle tip deflection. The model’s predictions are then compared to experimental data obtained from needle insertions in real tissues. The research aims to deepen our understanding of needle-tissue interactions and develop a reliable model for predicting needle deflection, ultimately enhancing surgical robots and navigation systems for safer and more precise percutaneous procedures. Pig organs are used as a material data source for a viscoelastic model, simulating needle insertion into kidney-like environments and analyzing organ deformation. The modified Euler-Bernoulli beam theory considers the viscoelastic properties of the tissue. Deflection is then calculated and compared to experimental data, with analytical deflection measurements exhibiting a 5–10% difference compared to experimental results. 

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