Yunfei Li¹, Dongjiang Wu¹, Fangyong Niu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012365

Abstract The plastic deformation assisted method plays a positive role in regulating the microstructure and mechanical properties of metal components in additive manufacturing. In this work, the effect of hammer forging force on the microstructure and mechanical properties of 316L stainless steel additive components were investigated by using synchronous-hammer-forging-assisted laser directed energy deposition method. The results show that when the hammer forging force is greater than 40 N, the grain refinement effect is obvious, the grain size decreases by more than 60 %, and the maximum strength of the polar diagram decreases by more than 75 More >

Chongdong Lin^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011631

Abstract In many real-world scenarios, such as high-speed combustion processes and re-entry flows in aerospace vehicles, the flow conditions often involve complex interactions between multiple chemical species and energy modes, leading to thermodynamic nonequilibrium effects. Traditional computational fluid dynamics (CFD) methods struggle to accurately capture these phenomena due to their simplifying assumptions regarding equilibrium thermodynamics. To solve this issue, the Multicomponent Discrete Boltzmann Method (MDBM) is proposed as a numerical approach to simulate compressible reactive flows with thermodynamic nonequilibrium effects. Based on kinetic theory, this method can capture the complex interactions between different species and energy… More >

Yang Chen¹, Jing Peng¹, Shuo Wang¹, Chao Jiang¹, Jia Li^1,*, Qihong Fang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.012299

Abstract Nuclear energy demands radiation-resistant metal materials. Multi-principal element alloys (MPEAs) show superior radiation resistance over traditional alloys due to lattice distortion, promising for advanced reactors. However, damage evolution and mechanical performance of irradiated MPEAs under loading are unclear, limiting long-term application. We investigated hardening behavior induced by irradiation defects like dislocation loops and voids in MPEAs using crystal plasticity models and experiments. Here, we developed i) a stochastic field theory-based discrete dislocation dynamics simulation. A novel cross-slip mechanism in irradiated crystals was unveiled through co-linear reactions between dislocations and diamond perfect loops [1]; ii) With… More >

Yanxue Ma¹, Xiaoling Liu^1,*, Bing Wang², Ying Liu¹

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 871-889, 2024, DOI:10.32604/sdhm.2024.052683 - 20 September 2024

Abstract In the bridge technical condition assessment standards, the evaluation of bridge conditions primarily relies on the defects identified through manual inspections, which are determined using the comprehensive hierarchical analysis method. However, the relationship between the defects and the technical condition of the bridges warrants further exploration. To address this situation, this paper proposes a machine learning-based intelligent diagnosis model for the technical condition of highway bridges. Firstly, collect the inspection records of highway bridges in a certain region of China, then standardize the severity of diverse defects in accordance with relevant specifications. Secondly, in order… More >

Guangbing Xiao^*, Ruijie Gu, Ning Sun, Yong Zhang

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1329-1348, 2024, DOI:10.32604/csse.2024.050817 - 13 September 2024

Abstract In response to the challenges posed by insufficient real-time performance and suboptimal matching accuracy of traditional feature matching algorithms within automotive panoramic surround view systems, this paper has proposed a high-performance dimension reduction parallel matching algorithm that integrates Principal Component Analysis (PCA) and Dual-Heap Filtering (DHF). The algorithm employs PCA to map the feature points into the lower-dimensional space and employs the square of Euclidean distance for feature matching, which significantly reduces computational complexity. To ensure the accuracy of feature matching, the algorithm utilizes Dual-Heap Filtering to filter and refine matched point pairs. To further More >

Ankitkumar Patel¹, Srivathsan Vasudevan^1,*, Satya Bulusu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3803-3818, 2024, DOI:10.32604/cmc.2024.052851 - 12 September 2024

Abstract Molecular Dynamics (MD) simulation for computing Interatomic Potential (IAP) is a very important High-Performance Computing (HPC) application. MD simulation on particles of experimental relevance takes huge computation time, despite using an expensive high-end server. Heterogeneous computing, a combination of the Field Programmable Gate Array (FPGA) and a computer, is proposed as a solution to compute MD simulation efficiently. In such heterogeneous computation, communication between FPGA and Computer is necessary. One such MD simulation, explained in the paper, is the (Artificial Neural Network) ANN-based IAP computation of gold (Au₁₄₇ & Au₃₀₉) nanoparticles. MD simulation calculates the forces… More >

Wei Chen^1,*, Xiaogang Wei^2,*, Hongxu Zhang², Wenpeng He²

Journal on Artificial Intelligence, Vol.6, pp. 225-240, 2024, DOI:10.32604/jai.2024.052366 - 16 August 2024

Abstract The Head-Related Transfer Function (HRTF) describes the effects of sound reflection and scattering caused by the environment and the human body when sound signals are transmitted from a source to the human ear. It contains a significant amount of auditory cue information used for sound localization. Consequently, HRTF renders 3D audio accurately in numerous immersive multimedia applications. Because HRTF is high-dimensional, complex, and nonlinear, it is a relatively large and intricate dataset, typically consisting of hundreds of thousands of samples. Storing HRTF requires a significant amount of storage space in practical applications. Based on this, More >

Yu Zhou¹, Yun Zhang¹, Guowei Li¹, Hang Yang¹, Wei Zhang¹, Ting Lyu², Yueqiang Xu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1809-1829, 2024, DOI:10.32604/cmc.2024.050975 - 15 August 2024

Abstract In current research on task offloading and resource scheduling in vehicular networks, vehicles are commonly assumed to maintain constant speed or relatively stationary states, and the impact of speed variations on task offloading is often overlooked. It is frequently assumed that vehicles can be accurately modeled during actual motion processes. However, in vehicular dynamic environments, both the tasks generated by the vehicles and the vehicles’ surroundings are constantly changing, making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios. Taking into account the actual dynamic vehicular scenarios, this paper considers the real-time… More >

Mingyuan Li^1,*, Yuanli Gu¹, Qingqiao Geng², Hongru Yu¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3877-3896, 2024, DOI:10.32604/cmc.2024.047765 - 20 June 2024

Abstract This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors. The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Convolutional Long Short Term Memory Neural Network (ConvLSTM) to predict short-term taxi travel demand. The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components, capturing sequence characteristics at different time scales and frequencies. Based on the sample entropy value of components, secondary processing of more… More >

Samar M. Alqhtani¹, Toufique A. Soomro^2,*, Faisal Bin Ubaid³, Ahmed Ali⁴, Muhammad Irfan⁵, Abdullah A. Asiri⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1539-1562, 2024, DOI:10.32604/cmes.2024.051475 - 20 May 2024

Abstract Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries. Magnetic resonance imaging (MRI) and computed tomography (CT) are utilized to capture brain images. MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders. Typically, manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention. However, early diagnosis of brain tumors is intricate, necessitating the use of computerized methods. This research introduces an innovative approach for… More > Graphic Abstract