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Geometric modeling for Microstructure Design and Manufacturing: A Review of Representations and modeling algorithms

COMPUTER-AIDED DESIGN 2025年 180卷

作者： Zou, Qiang Luo, Guoyue Zhejiang Univ State Key Lab CAD&CG Hangzhou 310058 Peoples R China

Microstructures, characterized by intricate structures at the microscopic scale, hold the promise of important disruptions in the field of mechanical engineering due to the superior mechanical properties they offer. One fundamental technique of microstructure design and manufacturing is geometric modeling, which generates the 3D computer models required to run high-level procedures such as simulation, optimization, and process planning. There is, however, a lack of comprehensive discussions on this body of knowledge. The goal of this paper is to compile existing microstructure modeling methods and clarify the challenges, progress, and limitations of current research. It also concludes with future research directions that may improve and/or complement current methods, such as compressive and generative microstructure representations. By doing so, the paper sheds light on what has already been made possible for microstructure modeling, what developments can be expected in the near future, and which topics remain problematic.

关键词： CAD/CAM Additive manufacturing Geometric modeling Microstructures Geometric representations modeling algorithms

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Layered modeling of Affective, Perception, and Visual Properties: Optimizing Structure With Genetic Algorithm

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2024年第5期54卷 609-618页

作者： Watanabe, Shuhei Horiuchi, Takahiko Ricoh Co Ltd Adv Technol R&D Div Ebina 2430460 Japan Chiba Univ Grad Sch Informat Chiba 2638522 Japan

To design the "Kansei value" aspect of a product, it is useful to design multilayered relationships of perceptual and affective responses via the physical or psychophysical properties of the product. However, because they are qualitative and ambiguous, designing a model is time-consuming. Moreover, the design was conducted by hypothesis and trial-and-error by the experimenter. In this article, we developed a method to automatically construct several semioptimal structures by applying a genetic algorithm to model design based on structural equation modeling, using the results of image measurement and subjective evaluation experiments on various material samples. Under set convergence conditions, the method constructed statistically optimized structures that represent the relationships among adjectives describing perception and affective, and the properties. A semantic validation was performed to determine the final model. As a result, the proposed method could be used to construct a model that can be interpreted as semantically and statistically superior compared to methods in related studies. A unique feature of this article was the use of the physical and psychophysical properties obtained by measurements in the construction of a multilayer model. Also, the advantage of this method is that it can be used to construct important structures that may be overlooked.

关键词： Mathematical models Visualization Genetic algorithms Correlation Computational modeling Numerical analysis Human-machine systems Affective perception decision-support system Kansei modeling algorithms perception

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A Data Model for Quantitative Analysis of Fire Risk in Social Units 4

A Data Model for Quantitative Analysis of Fire Risk in Socia...

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4th International Conference on System Reliability and Safety Engineering (SRSE)

作者： Zhang, Jianqi Qian, Xinming Beijing Inst Technol State Key Lab Explos Sci & Technol Beijing Peoples R China

ISBN: (纸本)9781665473880

In this paper, grey correlation analysis is applied to mine the fire IoT monitoring data. The correlation degree between 4,752 IoT monitoring data of social units and the management situation of firefighting work and operation of firefighting facilities in an ideal state was calculated. Using gray correlation analysis algorithm to calculate the personnel presence rate of fire control room, alarm accuracy rate and failure rate of automatic fire alarm system, and rank the key units according to the correlation size with the ideal situation of fire safety of social units, and establish the fire supervision and inspection unit screening model. The research results show that the fire safety situation of social units can be combined with the fire monitoring and inspection unit screening model established in this paper. By calculating the value of the correlation degree between the actual data and the ideal data and ranking them, the safety situation of monitoring and inspection units can be screened, and the efficiency of daily fire monitoring can be improved. It clarifies the different needs of different units for fire supervision and inspection, so that the fire supervision and inspection work can be targeted.

关键词： Intelligent firefighting IoT data data mining modeling algorithms

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A model for the detection of ß-glucan content in oat grain based on near infrared spectroscopy

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JOURNAL OF FOOD COMPOSITION AND ANALYSIS 2024年 129卷

作者： Yang, Zhongyu Cheng, Ze Su, Pengyan Wang, Chao Qin, Minxing Song, Xiaoyan Xiao, Lujie Yang, Wude Feng, Meichen Zhang, Meijun Shanxi Agr Univ Coll Agr Taigu 030801 Shanxi Peoples R China Shanxi Agr Univ Coll Resources & Environm Taigu 030801 Shanxi Peoples R China

Oat ss-glucan, recognized, a key functional component of oats, presents challenges in its determination due to low efficiency, cumbersome operations, and high costs, thereby posing obstacles to the large-scale production and industrialization of oats. This study aimed to clarify the quantitative relationship between ss-glucan content and near-infrared (NIR) spectra in oat grains. Utilizing 63 oat grain varieties as test materials, this study analyzed their ss-glucan content and NIR spectra. The focus of the research lay in evaluating the impact of various preprocessing and modeling methods on the accuracy of NIR spectroscopy for detecting ss-glucan content in oat grains. The results indicated that the successive projections algorithm-multiple linear regression (SPA-MLR) model with square preprocessing, along with the partial least squares regression (PLSR) and support vector machine regression (SVR) models under multiplicative scattering Correction (MSC) preprocessing, achieved high accuracy, with correlation coefficients (R2) of 0.84, 0.66, and 0.76, respectively. The SPA-MLR model, employing square preprocessing, exhibited optimal performance, with an R2 of 0.84, root mean square error (RMSE) of 0.55, mean absolute error (MAE) of 0.46, and a ratio of performance to standard deviation (RPD) of 2.45, proving effective in accurately determining the ss-glucan content in oat grains.

关键词： Oats ss-glucan Near infrared spectroscopy Feature selection modeling algorithms

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Advanced high order field-to-field modeling for wafer edge control 33

Advanced high order field-to-field modeling for wafer edge c...

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Conference on Optical Microlithography XXXIII

作者： Habets, Boris Buhl, Stefan Kim, Wan-Soo Lomtscher, Patrick Bald, Holger Hoeer, Tobias Qoniac GmbH Dr Kuelz Ring 15 D-01067 Dresden Germany

ISBN: (纸本)9781510634220

In leading-edge lithography, field-by-field corrections, also known as corrections per exposure, are well established. Many manufacturers use a combination of the traditional higher order wafer and intra-field polynomial corrections, combined with linear field-by-field corrections. However, non-linear wafer deformations are usually strongest at the wafer edge. Therefore, specific high order field-by-field corrections are the ultimate correction method to mitigate the effects of these non-linear wafer deformations. However, determining the appropriate amount of high order field-to-field corrections is not trivial. At the wafer edge, exposure fields are often incomplete, so the fields contain less overlay marks and have a less regular distribution than fields that are completely on the wafer. Therefore, even on dense measurements, it is challenging to model these fields with a high order model without applying overcorrection. On the other hand, the metrology capacity for dense measurements is high, so these can typically only be performed with low frequency. Alternatively, smart field-by-field modeling algorithms are available to compute higher order effects based on reduced sampling plans. In this paper, we study different algorithmic approaches to optimize modeling algorithms for both dense and sparse (reduced) sampling plans. We compare the impact of varying the frequency of dense sampling to the performance of different modeling algorithms on sparse sampling.

关键词： Field-by-field corrections correction per exposure (CPE) HOPC overlay edge modeling modeling algorithms dense and sparse sampling OVALiS

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Accurate and Efficient algorithms for Cognitive Radio modeling Applications Under the i.n.i.d. Paradigm

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2015年第5期64卷 1750-1765页

作者： Amich, Amine Imran, Muhammad Ali Tafazolli, Rahim Cheraghi, Parissa Univ Surrey Fac Engn & Phys Sci Ctr Commun Syst Res Guildford GU2 7XH Surrey England Qualcomm Farnborough Hants England

Given that the statistical analysis of the frequency band of interest are available, it has been shown that adaptive searching for white spaces could improve by 70% when compared with random searching. In this paper, we characterize and provide a statistical estimation of the number of channels available for opportunistic usage by secondary users (SUs) in a spectrum band. However, following the independent but not identically distributed (i.n.i.d.) paradigm, predicting the exact distribution of the count of available channels is not only computationally intense due to the number of combinations but infeasible in practice, as well, even for frequency bands with a moderate number of channels. Existing research has resorted to approximations that lacked accuracy and efficiency. To resolve this problem, we propose three novel methods based on convolution, recursive, and hybrid convolution-recursive methods that can efficiently compute the exact distribution in frequency bands with a large number of channels. We assess their efficiency by analyzing each algorithm's time complexity and running time and then further comparing their performance against existing models in the literature. Moreover, knowing the availability of the channel's immediate neighbors can allow efficient power management and prioritize channel allocation to SUs. Therefore, we categorize available channels into three different types based on the occupancy of its two adjacent channels and then model their availability. Additionally, from a network performance analysis perspective, predicting the count of available channels has to be evaluated against the probability of detecting these channels within the same i.n.i.d. framework. Respectively, we propose a novel approach to calculate the probability of detecting multiple channels simultaneously. Finally, we validate the effectiveness of the proposed models using several real-time measurements and further present two associated applications where one feat

关键词： Channel availability cognitive radio (CR) energy efficiency exact distribution IEEE 802.22 modeling algorithms modeling techniques spectrum availability modeling

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Wavelet-based modeling of spectral bidirectional reflectance distribution function data

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OPTICAL ENGINEERING 2004年第10期43卷 2327-2339页

作者： Claustres, L Boucher, Y Paulin, M Univ Toulouse 3 Inst Rech & Informat F-31062 Toulouse 4 France Off Natl Etudes & Rech Aerospatiales Dept Opt Theor & Appl F-31055 Toulouse France

The bidirectional reflectance distribution function (BRDF) is an important surface property, commonly used to describe reflected light patterns. However, the BRDF is a complex function since it has four angular degrees of freedom and also depends on the wavelength. The direct use of BRDF data set may be inefficient for scene modeling algorithms, for example. Thus, models provide compression and additional functionalities like interpolation. One common way consists in fitting an analytical model to the measurements data set using an optimization technique. But this approach is usually restricted to a specific class of surfaces, to a limited angular or spectral range, and the modeling quality may strongly depend on the optimization algorithm chosen. Moreover, analytical models are unable to actually handle the BRDF dependence on wavelength. We present a new numerical model for acquired spectral BRDF to overcome these drawbacks. This model is based on a separation between the spectral and the geometrical aspects of the BRDF, each of them projected into the appropriate wavelet space. After a brief introduction to the BRDF, the advantages of wavelets and the construction of the model are explained. Then, the performances of modeling are presented and discussed for a large collection of measured and synthetic BRDF data sets. Finally, the robustness of the model is tested with synthetic noisy BRDF data. (C) 2004 Society of Photo-Optical Instrumentation Engineers.

关键词： reflected light BRDF modeling algorithms wavelets

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