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Maximizing biomass utilization: An integrated strategy for coproducing multiple chemicals

Journal of Energy Chemistry 2025年第1期100卷 180-191页

作者： Byeongchan Ahn Sua Jo Jonggeol Na J.Jay Liu Young-Ju Kim Wangyun Won department of Chemical and Biological engineering Korea University department of Chemical engineering (Integrated process) Kyung Hee University department of Chemical engineering and Materials Science Ewha Womans University department of Chemical engineering Pukyong National University Resources engineering Plant Research department Korea Institute of Geoscience and Mineral Resources

Lignocellulosic biomass is one of the viable solutions to alleviate the global warming. However, the limited utilization of biomass majorly focused on cellulose and hemicellulose restricts the economic and environmental feasibilities. To cope with this issue, we proposed an integrated process of co-producing 1,6-hexanediol（1,6-HDO） with tetrahydrofuran and adipic acid from biomass, referred to as Strategy A. To compare the impacts of lignin upgrading and feedstock, Strategy B, which co-produces tetrahydrofuran alone, and Strategy C, which is the traditional route to produce 1,6-HDO from fossil fuels, were used. Heat networks are also designed to reduce operating costs and indirect carbon emissions due to energy consumption, saving 87% and 83% of the heat and cooling requirements, respectively, in Strategy A. The market competitiveness of Strategy A was evaluated by determining the minimum selling price through techno-economic analysis, and sustainability was thoroughly investigated by quantifying the environmental impacts through both midpoint and endpoint life-cycle assessments（LCAs）.Strategy A was found to be the most favorable both economically（USRDSCHARDOLLAR3,402/ton） and environmentally（-26.9 kg CO2eq.）. This indicates that lignin valorization is not only economically but also environmentally preferred. Finally, changes in economic and environmental feasibilities depending on economic, process, and environmental parameters were investigated using sensitivity and uncertainty analyses. The results of these analyses provide valuable insight into bio-based chemical production.

关键词： Biorefinery Carbon mitigation Climate change Global warming Lignin utilization Bioeconomy

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Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

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Computer Modeling in engineering & Sciences 2025年第1期142卷 579-607页

作者： Pongsakon Promsawat Weerapan Sae-dan Marisa Kaewsuwan Weerawat Sudsutad Aphirak Aphithana department of Civil engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Computer engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Statistics Faculty of ScienceRamkhamkaeng UniversityBangkok10240Thailand

The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

关键词： Graph neural networks convolutional neural network deep learning dynamic multi-graph spatio-temporal

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Steel Surface Defect Recognition in Smart Manufacturing Using Deep Ensemble Transfer Learning-Based Techniques

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Computer Modeling in engineering & Sciences 2025年第1期142卷 231-250页

作者： Tajmal Hussain Jongwon Seok department of Information and Communication engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing and industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product *** light of the recent advancement of industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing *** this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual *** evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different *** ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted *** evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and *** analysis with recent studies also showed the superior performance of our methodology.

关键词： Smart manufacturing CNN steel defects ensemble models

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Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

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Computer Modeling in engineering & Sciences 2025年第1期142卷 909-931页

作者： Adel Binbusayyis Mohemmed Sha department of Software engineering College of Computer engineering and Sciences in Al-Kharj Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid *** the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the *** also possesses a better impact on averting overloading and permitting effective energy *** though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized *** overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning *** accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data ***,the pre-processed data are taken for training and *** that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in *** PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed *** hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on *** results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.

关键词： Smart Grid machine learning particle swarm optimization XGBoost dynamic inertia weight update

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Nonlinear forced vibration in a subcritical regime of a porous functionally graded pipe conveying fluid with a retaining clip

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 101-122页

作者： M.GHOLAMI M.EFTEKHARI department of Mechanical engineering Shahid Bahonar University of Kerman

This study examines the nonlinear behaviors of a clamped-clamped porous pipe made of a functionally graded material(FGM) that conveys fluids and is equipped with a retaining clip, focusing on primary resonance and subcritical dynamics. The nonlinear governing equations for the FGM pipe are derived by the extended Hamilton's principle, and subsequently discretized through the application of the Galerkin *** direct method of multi-scales is then used to solve the derived equations. A thorough analysis of various parameters, including the clip stiffness, the power-law index, the porosity, and the clip location, is conducted to gain a comprehensive understanding of the system's nonlinear dynamics. Through the analysis of the first natural frequency, the study highlights the influence of the flow velocity and the clip stiffness, while the comparisons with metallic pipes emphasize the role of FGM composition. The examination of the forced response curves reveals saddle-node bifurcations and their dependence on parameters such as the detuning parameter and the power-law index, offering valuable insights into the system's nonlinear resonant behavior. Furthermore, the frequency-response curves illustrate the hardening nonlinearities influenced by factors such as the porosity and the clip stiffness, revealing nuanced effects on the system response and resonance characteristics. This comprehensive analysis enhances the understanding of nonlinear behaviors in FGM porous pipes with a retaining clip, providing key insights for practical engineering applications in system design and optimization.

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Artificial Circulation system Algorithm:A Novel Bio-Inspired Algorithm

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Computer Modeling in engineering & Sciences 2025年第1期142卷 635-663页

作者： NerminÖzcan Semih Utku Tolga Berber department of Biomedical Technologies Dokuz Eylül UniversityIzmir35390Turkey department of Biomedical engineering Iskenderun Technical UniversityIskenderun31200Turkey department of Computer engineering Dokuz Eylül UniversityIzmir35390Turkey department of Statistics and Computer Sciences Karadeniz Technical UniversityTrabzon61080Turkey

Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering appli*** present work introduces a novel metaheuristic algorithm named the Artificial Circulatory system Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this *** work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark *** method was subsequently examined by application to 12 CEC 2022 benchmark problems of different ***,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and ***,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing *** results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and *** outperformed 42 algorithms statistically,according to post-hoc *** also outperformed 9 algorithms *** study concludes that ACSA offers competitive solutions in comparison to popüler methods.

关键词： Bio-inspired evolutionary heuristic metaheuristic optimization

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Enhanced solid-electrolyte interface efficiency for practically viable hydrogen-air fuel cell systems

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Journal of Energy Chemistry 2025年第1期100卷 356-368页

作者： Venkitesan Sakthivel Dong Jin Yoo Graduate School Department of Energy Storage/Conversion Engineering (BK21 FOUR) Hydrogen and Fuel Cell Research Center Jeonbuk National University Jeonju department of Life Science Jeonbuk National University

Proton exchange membrane fuel cells （PEMFCs） provide an appealing sustainable energy system,with the solid-electrolyte membrane playing a crucial role in its overall ***,sulfonated poly（1,4-phenylene ether-ether sulfone）(SPEES),an aromatic hydrocarbon polymer,has garnered considerable attention as an alternative to Nafion ***,the long-term durability and stability of SPEES present a significant *** this context,we introduce a potential solution in the form of an additive,specifically a core–shell-based amine-functionalized iron titanate （A–Fe2TiO5）,which holds promise for improving the lifetime,proton conductivity,and power density of SPEES in *** modified SPEES/A–Fe2TiO5composite membranes exhibited notable characteristics,including high water uptake,enhanced thermomechanical stability,and oxidative ***,the SPEES membrane loaded with 1.2 wt%of A–Fe2TiO5demonstrates a maximum proton conductivity of 155 mS cm-1,a twofold increase compared to the SPEES membrane,at 80°C under 100%relative humidity （RH）.Furthermore,the 1.2 wt%of A–Fe2TiO5/SPEES composite membranes exhibited a maximum power density of 397.37 mW cm-2and a current density of 1148 mA cm-2at 60°C under 100%RH,with an opencircuit voltage decay of 0.05 m V/h during 103 h of continuous *** study offers significant insights into the development and understanding of innovative SPEES nanocomposite membranes for PEMFC applications.

关键词： Acid-base Hybrid membrane Proton conductivity Polymer electrolyte fuel cell Single-cell performance

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Free vibration and transient response of double curved beams connected by intermediate straight beams

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 37-62页

作者： R.A.JAFARI-TALOOKOLAEI H.GHANDVAR E.JUMAEV S.KHATIR T.CUONG-LE School of Mechanical engineering Babol Noshirvani University of Technology department of Mechanical engineering Faculty of Engineering New Uzbekistan University University of Business and Science Center for engineering Application and Technology Solutions Ho Chi Minh City Open University

This paper investigates the free vibration and transient response of interconnected structures including double curved beams and intermediate straight beams,which are all constructed from functionally graded porous(FGP) materials. The strain potential and kinetic energies of each beam along with the work done by the external force are calculated. Additionally, a higher-order beam element is introduced to derive stiffness and mass matrices, along with the force vector. The curved and straight beams are discretized, and their assembled stiffness, mass matrices, and force vectors, are *** conditions at the joints are used to derive the total matrices of the entire structure. Subsequently, the natural frequencies and transient response of the system are determined. The accuracy of the mathematical model and the self-developed computer program is validated through the comparison of the obtained results with those of the existing literature and commercial software ANSYS, demonstrating excellent ***, a comprehensive study is conducted to investigate the effects of various parameters on the free vibration and transient response of the considered structure.

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Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea department of Information Convergence system Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

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An Experimental Study on Aerodynamic Sound Generated from Wake Interaction of Circular Cylinder and Airfoil with Attack Angle in Tandem

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Journal of Thermal Science 2008年第3期17卷 212-217页

作者： Mizue MUNEKATA Ryuta KOSHIISHI Hiroyuki YOSHIKAWA Hideki OHBA department of Mechanical system engineering

In our previous study, the effects of the interval between the cylinder and the airfoil on the aerodynamic sound were investigated and compared with the cases of single circular and single airfoil. In this study, the effects of the attack angle of the airfoil located downstream on the characteristics of aerodynamic sound and the wake structure are investigated at a given interval between the cylinder and the airfoil. It is found that the sound pressure level of DFN and the peak frequency decrease with increasing attack angle of airfoil because of the diffusive wake structure due to the increased back pressure of circular cylinder, which is caused by the blocking effect of airfoil. It is shown that the sound sources are corresponded to the attack points of shedding vortex form the upstream circular cylinder to the downstream airfoil. We conclude that the pressure fluctuation at the airfoil surface effects on the sound pressure level, from the flow visualizations and the exploration test of sound source.

关键词： aerodynamic sound wake interaction circular cylinder airfoil Karman's vortex flow visualization

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