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Q-tables formation method for automated monitoring of electromechanical converters parameters with application of linear integral criterion
Published 2020-05-01“…In these models static characteristics are implemented in tabular form reflecting the dependencies between the parameters of the electromechanical converters and the linear integral criterion. …”
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323
Application research of prestressed wire strand and composite mortar for flexural strengthening of T-shaped simply supported beam bridges
Published 2025-03-01“…In order to validate the reinforcing effect of the prestressed wire strand-composite mortar method on actual bridges, this paper applies the reinforcing method to a T-shaped simply supported beam bridge and conducts load tests before and after the reinforcement to explore its improvement effect. …”
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Structural design parameters of laminated composites for marine applications: Milestone study and extended review on current technology and engineering
Published 2024-12-01“…The reviews cover the composite applications in the marine industry, novel marine characteristics for composite material, layering mechanism, material characterization, and damage mechanisms in composites due to various loading conditions in four different categories (delamination, matrix cracking, fiber breakage, and complete perforation), parametric joint method (vacuum and adhesive), and the failure criteria (debonding and interfacial delamination). …”
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326
A Hybrid Deep Transfer Learning Framework for Delamination Identification in Composite Laminates
Published 2025-01-01“…Compared to the existing transfer learning approaches, the suggested method achieved better performance, hence improving both the accuracy and robustness of delamination detection in composite structures.…”
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327
Free vibration analysis of joined composite conical-cylindrical-conical shells containing fluid
Published 2016-12-01“…This paper emphasizes advantages of CE model, the effects of the fluid filling and shell geometries on the natural frequencies of joined composite conical-cylindrical-conical shells containing fluid. …”
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328
Calculation Principle and Test Method of Main Insulation Dielectric Constant of Stator Bar
Published 2023-08-01“…Based on the calculation theory of composite dielectric constant, a simplified model of main insulation of generator stator bar is established, and the calculation method of main insulation dielectric constant is given. …”
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329
A Model Transformation Method Based on Simulink/Stateflow for Validation of UML Statechart Diagrams
Published 2025-02-01“…A model transformation method based on state refinement and semantic mapping is proposed to address the challenges of high modeling complexity and resource consumption in symbolic validation of industrial software requirements. …”
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330
Modeling and analysis of micro processes
Published 2022-01-01“…Experimental results show that the proposed method can model microprocesses and detect the deadlocks caused by synchronous or asynchronous interaction errors of the composite micro processes.…”
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331
Multidisciplinary Design Optimization of the NASA Metallic and Composite Common Research Model Wingbox: Addressing Static Strength, Stiffness, Aeroelastic, and Manufacturing Constr...
Published 2025-05-01“…This study explores the multidisciplinary design optimization (MDO) of the NASA Common Research Model (CRM) wingbox, utilizing both metallic and composite materials while addressing various constraints, including static strength, stiffness, aeroelasticity, and manufacturing considerations. …”
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332
Calculation of Shear-Bearing Capacity of Aluminum Alloy-Concrete Composite Beam
Published 2025-07-01“…An improved shear capacity formula was derived based on the tension–compression bar model and the superposition method. The proposed formula achieved an average ratio of 1.018 to finite element results, with a standard deviation of 0.151, and the proposed formula was validated against 22 FEA models, demonstrating excellent agreement with numerical results and confirming its reliability for practical engineering applications. …”
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333
Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change
Published 2025-12-01“…In this study, we develop a systematic methodology with multivariate models and machine learning algorithms to (i) model complex patterns of relationships or multi-phenotypic differences between the thermal environment and thermoregulatory, hormonal, biochemical, hematological and productive responses; and (ii) identify potential associations among biological relationships that may underlie shared and specific phenotypic patterns of adaptive responses. …”
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334
A Novel Approach for Lateral Buckling Assessment of Double Tapered Thin-Walled Laminated Composite I-Beams
Published 2022-04-01“…The purpose of this paper is to introduce a simple and novel method for discussing the lateral-torsional stability of thin-walled symmetric balanced laminated beams with varying I-section. …”
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models of muscle spindles: From traditional methods to 3D bioprinting strategies
Published 2025-07-01Get full text
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337
Thermal characteristics of commercially manufactured expanded polystyrene composite lightweight concrete
Published 2025-07-01“…This study establishes the thermal characteristics of commercially manufactured expanded polystyrene (EPS) composite lightweight concrete and investigates the results of a range of laboratory test methods, which are then compared with real-world performance. …”
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338
SELECTING OPTIMAL PROCESS PARAMETERS OF Al2O3/C COMPOSITE USING GRA WITH PCA AND TAGUCHI’S QLF APPROACH
Published 2022-09-01“…The result was the best model based on the Quality Loss Function, because the method has the biggest determination coefficient value is 99,97% where the results is better than GRA with PCA. …”
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339
Corrosion resistance prediction of high-entropy alloys: framework and knowledge graph-driven method integrating composition, processing, and crystal structure
Published 2025-07-01“…Abstract The prediction of corrosion resistance in High-entropy alloys (HEAs) faces challenges due to previous machine learning methods not fully capturing the interdependencies between composition, processing, and crystal structure. …”
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340