Zhenyu Zhang¹, Quan Jin¹, Haitao Zhang¹, Zhao Liu¹, Yuyang Wu², Longfei Zhang², Renzhang Yan^2,*

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 167-191, 2025, DOI:10.32604/sdhm.2024.053190 - 15 November 2024

Abstract When the upper chord beam of the beam-string structure (BSS) is made of concrete-filled steel tube (CFST), its overall stiffness will change greatly with the construction of concrete placement, which will have an impact on the design of the tensioning plans and selection of control measures for the BSS. In order to accurately obtain the bending stiffness of CFST beam and clarify its impact on the mechanical properties of composite BSS during construction, the influence of some factors such as height-width ratio, wall thickness of steel tube, elasticity modulus of concrete, and friction coefficient on More >

Chaozhi Cai^*, Tiexin Xu, Jianhua Ren, Yingfang Xue

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 125-144, 2025, DOI:10.32604/sdhm.2024.052813 - 15 November 2024

Abstract A bearing fault diagnosis method based on the Markov transition field (MTF) and SEnet (SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions, low fault diagnosis accuracy, and poor generalization of rolling bearing. Firstly, MTF is used to encode one-dimensional time series vibration signals and convert them into time-dependent and unique two-dimensional feature images. Then, the generated two-dimensional dataset is fed into the SE-IShufflenetV2 model for training to achieve fault feature extraction and classification. This paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University… More >

Zhao-Jun Zhang¹, Wen-Wei Wang^1,2,*, Jing-Shui Zhen¹, Bo-Cheng Li¹, De-Cheng Cai¹, Yang-Yang Du¹, Hui Huang²

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 105-123, 2025, DOI:10.32604/sdhm.2024.052506 - 15 November 2024

Abstract This study aimed to investigate the moment redistribution in continuous glass fiber reinforced polymer (GFRP)-concrete composite slabs caused by concrete cracking and steel bar yielding in the negative bending moment zone. An experimental bending moment redistribution test was conducted on continuous GFRP-concrete composite slabs, and a calculation method based on the conjugate beam method was proposed. The composite slabs were formed by combining GFRP profiles with a concrete layer and supported on steel beams to create two-span continuous composite slab specimens. Two methods, epoxy resin bonding, and stud connection, were used to connect the composite… More >

Alya Penta Agharid¹, Indra Permana², Nitesh Singh¹, Fujen Wang^2,*, Susan Gustiyana²

Energy Engineering, Vol.121, No.12, pp. 3549-3571, 2024, DOI:10.32604/ee.2024.056398 - 22 November 2024

Abstract Hotel buildings are currently among the largest energy consumers in the world. Heating, ventilation, and air conditioning are the most energy-intensive building systems, accounting for more than half of total energy consumption. An energy audit is used to predict the weak points of a building’s energy use system. Various factors influence building energy consumption, which can be modified to achieve more energy-efficient strategies. In this study, an existing hotel building in Central Taiwan is evaluated by simulating several scenarios using energy modeling over a year. Energy modeling is conducted by using Autodesk Revit 2025. It… More >

Xinwei Wang^1,2,*, Ming Li¹, Hankun Bing¹, Dongxing Zhang¹, Yuanshu Zhang¹

Energy Engineering, Vol.121, No.12, pp. 3875-3898, 2024, DOI:10.32604/ee.2024.056237 - 22 November 2024

Abstract After long-term operation, the performance of components in the GTCC system deteriorates and requires timely maintenance. Due to the inability to directly measure the degree of component malfunction, it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’ health condition (degree of malfunction) through operation data of the GTCC system. The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system, and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in the GTCC system.… More >

Xiaohui Ye^1,*, Fucheng Tan¹, Xinli Song², Hanyang Dai², Xia Li², Shixia Mu², Shaohang Hao²

Energy Engineering, Vol.121, No.12, pp. 3689-3710, 2024, DOI:10.32604/ee.2024.055200 - 22 November 2024

Abstract Energy storage batteries can smooth the volatility of renewable energy sources. The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system (BESS). However, the current modeling of grid-connected BESS is overly simplistic, typically only considering state of charge (SOC) and power constraints. Detailed lithium (Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions. Additionally, there is a lack of real-time batteries risk assessment frameworks. To address these issues, in this… More >

Indra Mamad Gandidi^1,2,*, Sukarni Sukarni^3,4, Avita Ayu Permanasari³, Purnami Purnami⁵, Tuan Amran Tuan Abdullah⁶, Anwar Johari⁶, Nugroho Agung Pambudi^7,*

Energy Engineering, Vol.121, No.12, pp. 3635-3648, 2024, DOI:10.32604/ee.2024.054943 - 22 November 2024

Abstract The use of catalysts has significantly enhanced the yield and quality of in-situ pyrolysis products. However, there is a lack of understanding regarding pyrolysis approaches that utilize several low-cost natural catalysts (LCC) and their placement within the reactor. Therefore, this study aims to examine the effects of various LCC on the in-situ pyrolysis of spirulina platensis microalgae (SPM) and investigate the impact of different types of catalysts. We employed LCC such as zeolite, dolomite, kaolin, and activated carbon, with both layered and uniformly mixed LCC-SPM placements. Each experiment was conducted at a constant temperature of 500°C… More > Graphic Abstract

B. Gomathi^1,*, R. Manimegalai¹, Srivatsan Santhanam², Atreya Biswas³

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1749-1765, 2024, DOI:10.32604/csse.2024.056659 - 22 November 2024

Abstract In enterprise operations, maintaining manual rules for enterprise processes can be expensive, time-consuming, and dependent on specialized domain knowledge in that enterprise domain. Recently, rule-generation has been automated in enterprises, particularly through Machine Learning, to streamline routine tasks. Typically, these machine models are black boxes where the reasons for the decisions are not always transparent, and the end users need to verify the model proposals as a part of the user acceptance testing to trust it. In such scenarios, rules excel over Machine Learning models as the end-users can verify the rules and have more… More >

Sagiraju Srinadhraju^*, Samaresh Mishra, Suresh Chandra Satapathy

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1641-1668, 2024, DOI:10.32604/csse.2024.055612 - 22 November 2024

Abstract This paper introduces the integration of the Social Group Optimization (SGO) algorithm to enhance the accuracy of software cost estimation using the Constructive Cost Model (COCOMO). COCOMO’s fixed coefficients often limit its adaptability, as they don’t account for variations across organizations. By fine-tuning these parameters with SGO, we aim to improve estimation accuracy. We train and validate our SGO-enhanced model using historical project data, evaluating its performance with metrics like the mean magnitude of relative error (MMRE) and Manhattan distance (MD). Experimental results show that SGO optimization significantly improves the predictive accuracy of software cost More >

Saad M. Darwish^1,*, Abdul Rahman M. Sabri², Dhafar Hamed Abd², Adel A. Elzoghabi¹

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1595-1624, 2024, DOI:10.32604/csse.2024.054615 - 22 November 2024

Abstract The number of blogs and other forms of opinionated online content has increased dramatically in recent years. Many fields, including academia and national security, place an emphasis on automated political article orientation detection. Political articles (especially in the Arab world) are different from other articles due to their subjectivity, in which the author’s beliefs and political affiliation might have a significant influence on a political article. With categories representing the main political ideologies, this problem may be thought of as a subset of the text categorization (classification). In general, the performance of machine learning models… More >