1. About ICMSOA2021 Organized by Yaseen Academy, 2021 The 3rd international conference on modeling, simulation, optimization and Algorithm (ICMSOA2021) was held during 12-14 November, 2021 at Crowne Plaza Sanya City C...
1. About ICMSOA2021 Organized by Yaseen Academy, 2021 The 3rd international conference on modeling, simulation, optimization and Algorithm (ICMSOA2021) was held during 12-14 November, 2021 at Crowne Plaza Sanya City Center, Sanya, Hainan Province, China. Due to the different restrictions caused by Covid-19 according to particular provinces and cities, some of the participants participated in the physical conference at Sanya, but others had to join the conference online via Tencent Meeting. The conference looks for significant contributions to all major fields of Computational modeling, simulation, optimization and Algorithm in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Organizer: Yaseen Academy is located at Huangjiahu Lake University Town, Wuhan, Hubei, China, focusing on international academic conferences organizing and international academic journals corperation in areas of science and engineering, aiming to provide a high-level and open academic platform for global scholars, researchers and practioners. It has gathered an academic committee composed of more than 200 experts and scholars, and has successfully held many international academic conferences. Facing the vast number of experts and scholars, Yaseen Academic is a team with strong professional quality and professional ethics, it has creating a mature, deep and complete academic exchange platform, not only allowing experts and scholars to show and share their latest academic research results and realizing face-to-face academic exchanges, but also allowing the most cutting-edge scientific information, ideas, and viewpoints to be fully communicated and exchanged, which will benefit all mankind. List of Call for papers, conference Committee Members, Paper Submission, Programs are available in this pdf.
In this paper, we present a Design-Technology Co-optimization (DTCO) methodology of a heterogeneous 2.5D system that aims at integrating a passive interposer with HPC chiplets. The interposer comprises 3D high-density...
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ISBN:
(纸本)9798331516369;9798331516352
In this paper, we present a Design-Technology Co-optimization (DTCO) methodology of a heterogeneous 2.5D system that aims at integrating a passive interposer with HPC chiplets. The interposer comprises 3D high-density decoupling capacitors with the power delivery network (PDN) of the HPC chiplets. The proposed methodology is based on the discretization of the interposer into unit-cells and uses spatially distributed SPICE modeling to achieve voltage drop optimization, thus improving the performance of the chiplets at system level, in iterative loop processes. Using Electromagnetic (EM) simulation for unit-cells, incorporating boundary conditions that can be customized, we found out that neighboring cells play a significant role in the voltage drop seen inside the unit-cell as a result of resistive and inductive distributed parasitic interconnects. Consequently, these adjacent cells were incorporated into the EM simulation set-up for accurate power integrity analysis at system level.
Due to the complex electromagnetic characteristics of different devices and the limited space of the carrier, the electromagnetic compatibility problem of multi-antenna systems is becoming increasingly prominent. How ...
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Schmitt Trigger Circuits (STCs) play a crucial role in digital and analog signal processing by providing noise immunity and stable switching behavior. However, optimizing STC performance for low-power, high-speed appl...
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Schmitt Trigger Circuits (STCs) play a crucial role in digital and analog signal processing by providing noise immunity and stable switching behavior. However, optimizing STC performance for low-power, high-speed applications remains a challenging task. This study proposes a novel approach using the Multi-Objective Mayfly optimization Algorithm (MOMA) to optimize key STC parameters, including power dissipation, propagation delay, and hysteresis voltage. The optimization process was conducted using MATLAB, whereas LTSpice was employed for circuit-level validation using 0.25 mu m/2.5 V CMOS technology. To identify the best trade-off solutions, various weighting methods were applied, including Statistical Variance, Standard Deviation, CRITIC, and Mean methods, ensuring a balanced evaluation of circuit performance. Numerical results show that the optimized STC achieved a 23% reduction in propagation delay, a 38% decrease in power dissipation, and improved noise immunity while maintaining robust switching characteristics. These findings confirm the effectiveness of MOMA in designing low-power, high-performance STCs suitable for modern VLSI, biomedical, and IoT applications.
This paper studies the application of the Bayesian optimization algorithm in DHCPv6 stateful allocation, addressing the efficiency issues of traditional allocation strategies in high-load scenarios. By constructing a ...
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Last decades have seen a lot of research on Analog Design Automation. The most recent approaches are based on Reinforcement Learning (RL). This paper describes a new learning strategy enhancing the most recent Proxima...
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In this study, the effects of tray shape, loading thickness, electrode gap, vacuum level, and vacuum pulsation ratio on the heating performance during radio frequency pulsed vacuum drying (RFPVD) were systematically i...
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In this study, the effects of tray shape, loading thickness, electrode gap, vacuum level, and vacuum pulsation ratio on the heating performance during radio frequency pulsed vacuum drying (RFPVD) were systematically investigated. First, based on the established RF heating model, the radiative heat transfer equation was coupled to improve the accuracy of heat transfer simulation under vacuum conditions. simulation results showed that the temperature uniformity index (TUI) in RF heating stage was reduced to 0.13 by suppressing the edge aggregation effect of the electric field with circular tray. Additionally, single-layer stacking and increased loading thickness effectively improved the heating rate;however, the resulting enhancement of edge aggregation resulted in the TUI increased to 0.31. When a loading thickness of 45 mm was applied, adjusting the electrode gap to 95 mm increased the heating rate and avoided the localized overheating during the heating stage. At a defined drying temperature, an appropriate vacuum level modulated the moisture evaporation rate to optimize the temperature distribution. The RFPVD experiments verified that ideal temperature distribution uniformity (TUI <0.112) and post-drying moisture content consistency (coefficient of variation<5 %) could be obtained using multi-parameter optimization guided by simulation results. This study provides a theoretical basis and process optimization strategy for improving heating uniformity in RFPVD drying of granular materials.
OptiStruct software is applied for structural optimization of the motor structure to solve the problem of resonance in a specific operating frequency range and reduce the motor operating noise. Comparing the experimen...
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The numerical studies for film cooling performance have gained considerable interest for the development of advanced gas turbines and aero-engines. However, the accuracy of Reynolds-Averaged Navier-Stokes simulations ...
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ISBN:
(纸本)9780791887998
The numerical studies for film cooling performance have gained considerable interest for the development of advanced gas turbines and aero-engines. However, the accuracy of Reynolds-Averaged Navier-Stokes simulations is significantly influenced by the uncertainties associated with turbulence modeling closure coefficients. The traditional Monte Carlo methods for uncertainty quantification are computationally prohibitive as the cost of constructing an accurate response surface increases exponentially with the number of input parameters. The active subspace method, developed recently as a means of dimension reduction, incurs a moderate cost when dealing with high-dimensional uncertain inputs. In this study, the active subspace (AS) method is applied to quantify the modeling uncertainties related to SST turbulence modeling parameters in a fan-shaped film cooling simulation. The results reveal that the quantified modeling uncertainties exhibit distinct characteristics across different blowing ratios, and the response functions are constructed based on the primary control parameters. Subsequently, the turbulence model parameters are optimized to minimize the computational error based on the response functions. In the optimized test point, the average relative errors decrease to 1.3% and 0.3%, respectively, under blowing ratios of 0.5 and 2.5 after optimization. Furthermore, a set of unified model parameters is optimized and applied across different blowing ratios (0.5, 1.5, 2.5), resulting in average relative error of 4.3%, 3.7%, and 3.1%, respectively, demonstrating the advantages of the AS method for modeling uncertainty quantification and optimization in film cooling simulation.
Recent research on mobile robots has focused on increasing their adaptability to unpredictable and unstructured environments using soft materials and structures. However, the determination of key design parameters and...
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ISBN:
(纸本)9798350377712;9798350377705
Recent research on mobile robots has focused on increasing their adaptability to unpredictable and unstructured environments using soft materials and structures. However, the determination of key design parameters and control over these compliant robots are predominantly iterated through experiments, lacking a solid theoretical foundation. To improve their efficiency, this paper aims to provide mathematics modeling over two locomotion, crawling and swimming. Specifically, a dynamic model is first devised to reveal the influence of the contact surfaces' frictional coefficients on displacements in different motion phases. Besides, a swimming kinematics model is provided using coordinate transformation, based on which, we further develop an algorithm that systematically plans human-like swimming gaits, with maximum thrust obtained. The proposed algorithm is highly generalizable and has the potential to be applied in other soft robots with similar multiple joints. simulation experiments have been conducted to illustrate the effectiveness of the proposed modeling.
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