The system is based on the design of an artificial intelligence rainfall system testing platform, which combines mechanical calculations, fluid dynamics analysis, and simulation analysis to achieve simulation demonstr...
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Structural topology optimization approaches are widely used to create lightweight and efficient components through additive manufacturing. The race to lightweight components should also account for natural frequencies...
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ISBN:
(纸本)9783031765964;9783031765971
Structural topology optimization approaches are widely used to create lightweight and efficient components through additive manufacturing. The race to lightweight components should also account for natural frequencies when designing components and structures subjected to dynamic loads, as in aerospace and automotive engineering. These optimization tools require extensive manual setup, mainly when tuning input parameters that govern algorithmic functions and convergence. In this context, machine learning approaches can circumvent the trial-and-error process associated with the manual setup of simulation factors. This study presents a method that utilizes machine learning to suggest optimal input parameters, such as evolutionary rate and mesh dimensions, for creating lightweight and optimized structures while maintaining a consistent natural frequency. The framework incorporates a neural network trained on a collection of previously solved, analogous problems. A dissimilarity metric derived from problem metadata is used to determine tuning parameters. This approach can be applied to analyze and optimize product configurations where only marginal conditions may change;a Bayesian optimizer based on data coming from the neural network is used to improve the structure, substituting the topology optimization algorithm and reducing the time-to-market of a specific product.
The proceedings contain 104 papers. The topics discussed include: exploring changes in the static multipole polarizabilities of hydrogen atoms in coulomb plus inverse square root potential;optimization design of warhe...
The proceedings contain 104 papers. The topics discussed include: exploring changes in the static multipole polarizabilities of hydrogen atoms in coulomb plus inverse square root potential;optimization design of warhead fragment initial velocity;analysis and research on the movement behavior of dust particles during powder feeding;experimental study on the fastening method of shipborne equipment;study on the mechanical behavior and collapse resistance of double-casing under gypsum-salt layer;experiment and computational fluid dynamics simulation study on the effect of wind disturbance on the collection rate error of rainfall;and global well-posedness and exponential decay of 3D nonhomogeneous Navier-Stokes and magnetohydrodynamic equations with density-dependent viscosity and vacuum.
The design of soft grippers is one of the most classic problems in the design and application of robots. Researchers have provided mature and complete solutions to the design problem of grippers in recent years, such ...
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ISBN:
(纸本)9789819607709;9789819607716
The design of soft grippers is one of the most classic problems in the design and application of robots. Researchers have provided mature and complete solutions to the design problem of grippers in recent years, such as using bionics for design, mathematical modeling for simulation analysis of gripper performance. Shape and topology optimization is an effective tool for solving optimal material layout in a given field, widely used in various structural design problems, and can also be used in the structural design of flexible grippers. Compared to mature solutions with fixed force inputs, optimization tasks related to design related pressure loads remain a challenge. This article proposes a shape and topology optimization method for describing the motion pressure boundary using B-spline curves. Topological optimization is performed on the boundary shape and structure, and this method is combined to complete the design of aerodynamic compliant grippers. The design results of the clamping mechanism were post-processed and explored through pneumatic experiments to verify the feasibility of topology optimization for structural design.
As power density becomes the main constraint of multicore systems, managing power consumption using DVFS while providing the desired performance becomes increasingly critical. Reinforcement learning (RL) performs sign...
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ISBN:
(纸本)9783031783760;9783031783777
As power density becomes the main constraint of multicore systems, managing power consumption using DVFS while providing the desired performance becomes increasingly critical. Reinforcement learning (RL) performs significantly better than conventional methods in performance-power optimization under different hardware configurations and varying software applications. RL agents learn through trial-and-error by receiving rewards which is defined by an objective function (e.g. instructions-per-second (IPS)) within specified constraints (e.g. power budget). System and application requirements lead to changing objectives and constraints which in turn result in different reward functions. The RL agents adapt to these changing objectives and constraints (and hence reward functions). Equivalent-policy invariant comparison (EPIC) is a popular technique to evaluate different reward functions. EPIC provides a numerical score which quantifies the difference in two reward functions. In this work, we use this EPIC distance (score) to transfer knowledge and improve learning for changing reward functions. Experimental results using a DVFS enabled RISCV based system-on-chip implemented on an FPGA shows 16.2% lower power budget overshoots compared to a tabular Q-learning agent with direct transfer.
This paper studies the maximum power optimization method of swinging buoy wave energy power generation device (PTO system) based on the particle swarm optimization (PSO) algorithm. This device makes the float and the ...
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Designing a power plant is a complex process that requires consideration of multiple optimization criteria, such as safety, environmental impact, and efficiency. This paper introduces the use of estimation of distribu...
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Fused Deposition modeling (FDM) 3D printing technology has received widespread attention for its efficiency and reliability in prototype production, small batch production, and complex structure construction. However,...
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