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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

Abstract

The tremendous impact of large models represented by ChatGPT [1]-[3] makes it necessary to consider the practical applications of such models [4]. However, for an artificial intelligence (AI) to truly evolve, it needs to possess a physical body to transition from the virtual world to the real world and evolve through interaction with the real environments. In this context, embodied intelligence has sparked a new wave of research and technology, leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices [5].

article Article

date_range 2024

language English

link Link of the paper

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Shen Tianyu

Sun Jinlin

Kong Shihan

Wang Yutong

Li Juanjuan

Li Xuan

Wang Fei-Yue

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Featured Keywords

Artificial intelligence

Chatbots

Autonomous systems

Intelligent systems

Robots

Digital humans

Robot kinematics

Learning (artificial intelligence)

Biological system modeling

Computational modeling

Human-robot interaction

Complex systems

Deep learning

Reinforcement learning

Large language models

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Effect of corrosion on flexural strength of reinforced concrete beams with polypropylene fibers

Abstract

An experimental study was performed to investigate the effects of polypropylene fibers on uncorroded and corroded reinforced concrete beams. Three different volume fractions of polypropylene fibers having 0, 0.5, and 1.5%, were tested at four corrosion levels of 0% and approximately 5, 7, and 9%. A full scale of an accelerated corrosion pool was used for the accelerated corrosion process. Reinforced concrete beams were used for an under monotonic bending test. The contribution of the actual corrosion levels of transverse and longitudinal reinforcement bars to the total corrosion levels were obtained from reinforcement bars fully extracted from concrete. Flexural strength, bond-slip, and moment-curvature relationships were examined for uncorroded and corroded reinforced concrete beams. A new model was developed to predict the flexural strength of corroded reinforced concrete beams. The proposed model for predicting the residual flexural strength of corroded beams was compared with test data published in previous studies. Furthermore, a novel model is presented for improved predictions between the actual and theoretically estimated corrosion mass losses, based on Faraday’s law, with the aid of fully extracted reinforcement bars. The model used to predict the flexural strength of corroded reinforced concrete beams with large sizes demonstrated good agreement with current and previously published literature data. In the case of corroded beams comprising differing amounts of polypropylene fibers, the performance of the corroded beams was limited by a fiber volume fraction of 1.5% at low corrosion levels.

article Article

date_range 2018

language English

link Link of the paper

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