Peiyan Wang^1,*, Haoyu Wang¹, Minghui Liu², Fuchao Liu¹, Zhufeng Yue¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011318

Abstract The virtual test is supported by the physical test data, and a high-precision simulation model needs to be established to maximize the alignment between the simulation prediction results and the physical test data. It can replace other physical tests and achieve the goal of reducing the design cycle time and cost. However, due to the errors caused by the position and angle deviation of the strain gauge paste, as well as the sensitivity coefficient of the strain gauge and the wire, it is difficult for the simulation results to correspond to the test results in… More >

Jiayu Chen¹, Yingchun Bai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011393

Abstract Mega-casting techniques are widely used to manufacture large piece of thin-walled structures for vehicle body in Automotive industries, especially with the rapid growing electric vehicle market. Topology optimization is effective design method to reach higher mechanical performance yet lightweight potential for casting structures [1-3]. Most of existing works is focused on geometric-type casting constraints such as drawn angle, partion line, undercut, and enclose holes. However, the challenges in mega-casting arise from the complexities in the casting process such as filling and solidification, and the corresponding defects have larger influences on the structural performances [4-6]. Partial… More >

Zefu Li¹, Weidong Yang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011671

Abstract For composite materials incorporating porous structures with multi-walled carbon nanotubes (MWCNTs), the effects of pores and MWCNT agglomeration significantly impact electrical conductivity. Theoretical modeling of the piezoresistive behavior is crucial for understanding the electromechanical response of porous MWCNT/polymer nanocomposites. Currently, there is limited theoretical modeling that considers the combined effects of porosity and MWCNT agglomeration on the electrical conductivity and piezoresistive performance of porous MWCNT/polymer composites. Addressing this gap, this paper presents a multiscale modeling approach for the strain-dependent piezoresistive behavior of porous MWCNT/polymer nanocomposites. The model considers the influence of porosity and MWCNT agglomeration, More >

Binbin Guo^1,2, Hui Ying Yang^1,*, Jiaming Bai^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012673

Abstract Due to excellent electrical conductivity, stretchability, and biocompatibility, electrically conductive hydrogels have been widely used in flexible wearable strain sensors. Generally, conductive fillers need to be integrated with the hydrogel matrix to impart electrical conductivity. According to the method of composite formation between electronic conductive fillers and hydrogel matrix, conductive hydrogels can be classified into embedded conductive and coated conductive hydrogels. Additionally, due to the intrinsic chemical and physical crosslinking networks, traditional hydrogels are not degradable, resulting in severe environmental pollution problems. Herein, we designed electrically conductive and degradable hydrogels for the epidermal strain sensor… More >

Zhibo Yang, Xiaohan Huang, Bingdong Wang, Bin Hu, Zhenyong Zhang^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3001-3019, 2024, DOI:10.32604/cmc.2024.053369 - 15 August 2024

Abstract With the widespread use of machine learning (ML) technology, the operational efficiency and responsiveness of power grids have been significantly enhanced, allowing smart grids to achieve high levels of automation and intelligence. However, tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks, making it urgent to enhance their robustness. To address this, we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree ensembles. Our algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws, ensuring training data accurately reflects possible More >

Kun Liu^1,2, Peiran Li³, Yu Zhang^1,*, Jia Ren¹, Ming Li⁴, Xianyu Wang², Cong Li²

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2535-2555, 2024, DOI:10.32604/cmc.2024.052166 - 15 August 2024

Abstract When learning the structure of a Bayesian network, the search space expands significantly as the network size and the number of nodes increase, leading to a noticeable decrease in algorithm efficiency. Traditional constraint-based methods typically rely on the results of conditional independence tests. However, excessive reliance on these test results can lead to a series of problems, including increased computational complexity and inaccurate results, especially when dealing with large-scale networks where performance bottlenecks are particularly evident. To overcome these challenges, we propose a Markov blanket discovery algorithm based on constrained local neighborhoods for constructing undirected… More >

Cinthia T. Lucero¹, María de los Á. Ruíz², Fabiola Pagliero¹, Carolina Castaño¹, Mariela L. Ambrosino¹, Graciela S. Lorda^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1081-1099, 2024, DOI:10.32604/phyton.2024.050762 - 27 June 2024

Abstract Beneficial microbes can improve soil health by promoting soil structure, nutrient cycling, and disease suppression. In addition, a wide array of rhizospheric microbes are responsible for producing metabolically active compounds including various types of plant growth regulators. So, microbial biodiversity studies could contribute to the improvement of agricultural practices in deprived areas, such as the Pampean semiarid region. The vast majority of studies conducted on endophytic microorganisms have focused on intensive crop legume species. In contrast, little attention has been paid to microorganisms of native legumes, whose ecology is not directly affected by human action.… More >

Chengpeng Zhang, Junfeng Shi^*, Caiping Huang

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 465-483, 2024, DOI:10.32604/sdhm.2024.048705 - 05 June 2024

Abstract In this paper, an intelligent damage detection approach is proposed for steel-concrete composite beams based on deep learning and wavelet analysis. To demonstrate the feasibility of this approach, first, following the guidelines provided by relevant standards, steel-concrete composite beams are designed, and six different damage incidents are established. Second, a steel ball is used for free-fall excitation on the surface of the steel-concrete composite beams and a low-temperature-sensitive quasi-distributed long-gauge fiber Bragg grating (FBG) strain sensor is used to obtain the strain signals of the steel-concrete composite beams with different damage types. To reduce the… More >

Fuju Zhou^*, Li Li, Tengfei Jia, Yongchang Yin, Aixiang Shi, Shengrong Xu

Energy Engineering, Vol.121, No.6, pp. 1697-1711, 2024, DOI:10.32604/ee.2024.047680 - 21 May 2024

Abstract When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changing the states of tie-switches and load demands. Computation speed is one of the major performance indicators in power grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault power grids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient. The tedious training process of the reinforcement learning model can be conducted offline, so the model shows satisfactory performance in real-time operation, More >

Yuping Bian^*, Xiu Wan, Xiaoyu Zhou

Energy Engineering, Vol.121, No.6, pp. 1637-1656, 2024, DOI:10.32604/ee.2024.047678 - 21 May 2024

Abstract To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general More >