Engineering最新文献

{"title":"Critical Review of Intelligent Coal-Fired Power Technologies and Applications","authors":"Jizhen Liu, Zhongming Du, Qinghua Wang, Kaijun Jiang, Dan Gao","doi":"10.1016/j.eng.2025.07.036","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.036","url":null,"abstract":"With the rapid expansion of renewable energy systems, particularly wind and solar energy, coal-fired power plants (CFPPs) are expected to serve as flexible and dispatchable backup resources. This evolving role imposes new demands on their operational adaptability, efficiency, and intelligence. In this context, the intelligent transformation of CFPPs has become a key enabler for achieving both flexible operations and long-term sustainability. This paper provides a comprehensive review of the latest developments in intelligent coal-fired power technologies, focusing on three critical pillars: intelligent perception, intelligent control, and intelligent operation. Key enabling technologies, such as ubiquitous sensing systems, advanced control algorithms, and automated operation platforms, are examined in detail. Additionally, two representative engineering cases are introduced to demonstrate practical applications and benefits: the intelligent control of coal-fired units coupled with novel energy-storage systems and the implementation of unmanned operation in smart power plants. These projects highlight the transformative potential of intelligent technologies in enhancing the flexibility, efficiency, and autonomy of coal-fired power units. Finally, future perspectives on intelligent technologies are presented. The findings of this study offer valuable insights into the pathway toward clean, flexible, and intelligent coal-based power generation in an evolving energy landscape.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"79 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144824843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can Large Language Models Solve Complex Engineering Issues? Practical Applications in Reliability Systems Engineering","authors":"Yue Zhang, Yanjie Song, Yi Ren, Lining Xing, Qiang Feng, Ruifeng Xiang, Zili Wang, Witold Pedrycz","doi":"10.1016/j.eng.2025.07.037","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.037","url":null,"abstract":"No Abstract","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"7 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models","authors":"Wentao Yu, Hengtao He, Shenghui Song, Jun Zhang, Linglong Dai, Lizhong Zheng, Khaled B. Letaief","doi":"10.1016/j.eng.2025.07.032","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.032","url":null,"abstract":"This study explored the transformative potential of artificial intelligence (AI) in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output (UM-MIMO) systems. It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design: computational complexity, modeling difficulty, and measurement limitations. The study posits that AI provides a promising solution to these challenges. Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems. The first roadmap, model-driven deep learning (DL), emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework. Four essential steps are discussed: algorithmic frameworks, basis algorithms, loss-function design, and neural architecture design. The second roadmap presents channel state information (CSI) foundation models, aimed at unifying the design of different transceiver modules by focusing on their shared foundation, that is, the wireless channel. The training of a single compact foundation model is proposed to estimate the score function of wireless channels, which serve as a versatile prior for designing a wide variety of transceiver modules. Four essential steps are outlined: general frameworks, conditioning, site-specific adaptation, joint design of CSI foundation models, and model-driven DL. The third roadmap aims to explore potential directions for applying pretrained large language models (LLMs) to terahertz UM-MIMO systems. Several application scenarios are envisioned, including LLM-based estimation, optimization, search, network management, and protocol understanding. Finally, the study highlights open problems and future research directions.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"18 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144819975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge Enhanced Industrial Question-Answering Using Large Language Models","authors":"Ronghui Liu, Hao Ren, Haojie Ren, Wu Rui, Wei Cui, Xiaojun Liang, Chunhua Yang, Weihua Gui","doi":"10.1016/j.eng.2025.07.035","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.035","url":null,"abstract":"Modern industrial systems have grown increasingly extensive, complex, and hierarchical, with operations relying on numerous knowledge-based queries. These queries necessitate considerable human resources while also requiring high levels of accuracy, subjectivity, and consistency, all of which critically influence operational efficiency. To overcome these challenges, this study proposes an industrial retrieval-augmented generation (RAG) method designed to enhance large language models (LLMs) using domain-specific knowledge, thereby improving the precision of question answering. A comprehensive industrial knowledge base was constructed from diverse sources, including journal articles, theses, books, and patents. A Text classification model based on bidirectional encoder representations from transformers (BERTs) was trained to accurately classify incoming queries. Furthermore, the general text embedding–dense passage retrieval (GTE–DPR) model was employed to perform word embedding and vector similarity retrieval, facilitating the alignment of query vectors with relevant entries in the knowledge base to obtain initial responses. These initial results were subsequently refined by LLMs to produce accurate final answers. Experimental evaluations confirm the effectiveness of the proposed approach. In particular, when applied to ChatGLM2-6B, the RAG method increased the ROUGE-L score from 32.52% to 55.04% and improved accuracy from 50.52% to 73.92%. Comparable improvements were also observed with LLaMA2-7B, underscoring the RAG framework’s capability to significantly enhance the accuracy and relevance of industrial question-answering (QA) systems.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"38 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144824844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IgG Fucosylation: An Emerging Key Player in the Treatment of Severe COVID-19","authors":"Caiping Zhao, Jingrong Wang, Yuan Liu, Baoling Shang, Danna Lin, Yao Xiao, Hong Ren, Yue Li, Wen Rui, Xu Zou, Hudan Pan, Liang Liu","doi":"10.1016/j.eng.2025.08.004","DOIUrl":"https://doi.org/10.1016/j.eng.2025.08.004","url":null,"abstract":"Protein glycosylation is one of the most vital modifications. Understanding the role of protein glycosylation in coronavirus disease 2019 (COVID-19) is the key elucidating its pathogenesis and developing therapeutic strategies. We conducted a case-control study to examine the total fucosylation levels and the levels of individual immunoglobulin G (IgG) subtypes in the serum of COVID-19 patients. Notably, we identified 13 glycosyltransferase-related and glycosidase-related genes displaying differential expression among COVID-19 patients. Our findings from the detection of serum fucosylation levels in COVID-19 patients revealed a diminished degree of glycosylation. Furthermore, the analysis of the levels of different IgG subtypes revealed an increase in IgG1 fucosylation and a decrease in IgG2 fucosylation, with the latter being linked to patients’ body temperature and disease progression. The change in COVID-19 disease severity from mild to severe may be related to fucosylation. The single-cell sequencing analysis revealed the expression of members of the fucosyltransferase family in the plasma cells and plasmablasts of COVID-19 patients. We leveraged the recommended medication for severe COVID-19, <em>Fuzheng Jiedu</em> Decoction (FZJDD), to confirm the importance of fucosylation in severe COVID-19. The network pharmacology analysis of FZJDD revealed that fucosylation inhibition might contribute to its antiviral effects against COVID-19. We assessed the efficacy of this compound in septic mice, by monitoring serum fucosylation levels, and found that FZJDD significantly alleviated inflammation in lipopolysaccharide (LPS)-induced septic mice. Concurrently, the analysis of plasma fucosylation levels in septic mice indicated a marked decrease in total fucosylation. The glycan analysis revealed the involvement of α1, 6-fucosyltransferase (FUT8) and α-<em>L</em>-fucosidase 1 (FUCA1), a pair of interacting fucosidases, in COVID-19 pathogenesis. This study revealed substantial alterations in fucosylation among patients with severe COVID-19, with the primary variations observed in the IgG2 subtype. These changes are intricately coordinated by the mutual regulation of the FUT8 and FUCA1 enzymes. Furthermore, the endorsement of FZJDD as a recommended therapeutic option for severe COVID-19 underscores the promising potential of defucosylation as a viable treatment strategy for this disease.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"23 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144824919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneous Household Responses and Indoor Temperature Inequality in the Clean Heating Transition","authors":"Xinzhu Zheng, Ling Zhang, Yuxin Bai, Jianhui Cong, Tianyi Zhang, Yue Ren, Jie Li, Yang Su, Junyuan Xu, Can Wang","doi":"10.1016/j.eng.2025.07.034","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.034","url":null,"abstract":"The residential clean heating transition has proven effective in reducing air pollution and improving public health. However, most research to date has focused on its economic and environmental implications, with limited attention being paid to household behavioral responses and heating experiences. To address this gap, we conducted household surveys in Linfen, a city in northern China, and analyzed residents’ self-reported indoor temperatures, heating costs, and heated areas before and after the transition. The results reveal substantial disparities across clean heating pathways. Compared with households that are continuing to use coal or biomass, those switching to gas experienced a 1.7 °C drop in indoor temperature and an annual cost increase of 1318 CNY, suggesting energy-limiting behaviors in response to higher expenses. In contrast, households adopting electric heating reported a 1.2 °C temperature increase without a significant rise in costs. Further analysis using the Gini coefficient and Oshima index shows that indoor temperature inequality increased among coal-to-gas households, while no such trend was observed among coal-to-electricity households. These findings highlight the importance of incorporating behavioral responses and thermal equity into the design of clean heating strategies.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"5 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144819349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning-Based Matching Game for Task Scheduling and Resource Collaboration in Intent-Driven Task-Oriented Networks","authors":"Jiaorui Huang, Min Cao, Chungang Yang, Zhu Han, Tong Li","doi":"10.1016/j.eng.2025.07.033","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.033","url":null,"abstract":"With the rapid advancement of satellite communication technologies, space information networks (SINs) have become essential infrastructure for complex service delivery and cross-domain task coordination, facilitating the transition toward an intent-driven task-oriented coordination paradigm across the space, ground, and user segments. This study presents a novel intent-driven task-oriented network (IDTN) framework to address task scheduling and resource allocation challenges in SINs. The scheduling problem is formulated as a three-sided matching game that incorporates the preference attributes of entities across all network segments. To manage the variability of random task arrivals and dynamic resources, a context–aware linear upper-confidence-bound online learning mechanism is integrated to reduce decision-making uncertainty. Simulation results demonstrate the effectiveness of the proposed IDTN framework. Compared with conventional baseline methods, the framework achieves significant performance improvements, including a 4.4%–28.9% increase in average system reward, a 6.2%–34.5% improvement in resource utilization, and a 5.6%–35.7% enhancement in user satisfaction. The proposed framework is expected to facilitate the integration and orchestration of space-based platforms.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"79 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144819346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full-Scale Applications of a Sulfur-Based Autotrophic Denitrification Biofilter for Polishing Secondary Effluent: Annual Performance, Improved Winter Performance, and Microbial Community Succession","authors":"Jia-Min Xu, Hao-Ran Xu, Chong-Gang Liang, Ze-Run Cheng, Xu-Chen Ba, Gui-Jiao Zhang, Da-Heng Ren, Na Zhang, Jia-Qiang Lv, Yi-Lu Sun, Aijie Wang, Hao-Yi Cheng","doi":"10.1016/j.eng.2025.08.003","DOIUrl":"https://doi.org/10.1016/j.eng.2025.08.003","url":null,"abstract":"Sulfur-based denitrification (SADeN) technology is a cost-saving and low-carbon alternative for treating organic-deficient wastewater. However, the use of this technology in full-scale applications is still limited. Crucial concerns for biological processes, such as changes in seasonal performance and the ways in which it responds to low temperatures, have yet to be studied in real SADeN processes. Herein, two SADeN biofilters in parallel (downflow, with a design water treatment capacity of 8000 m³·d^–1 each) were systematically investigated over a period of more than 400 days. Seasonal variations in denitrification rates were observed, with an average difference of up to 2 times between summer and winter. The use of thiosulfate was verified as an efficient strategy to improve the performance of SADeN biofilters in winter, which was found to have an overstoichiometric enhancement effect (OSEE), with 24.79%–331.50% more nitrate removal than that calculated according to thiosulfate dosages. Analyzing the biofilter vertically revealed that the OSEE occurred because thiosulfate rapidly consumed dissolved oxygen in the upper zone of the bed and activated the electron flux of the sulfur-based reactive filler (SReF) in the lower zone. Microbial community analysis further suggested that this increase in electron flux may be associated with the abundance recovery of sulfur autotrophic denitrifiers and the stability recovery of the microbial eco-networks. This study offers a paradigm for the full-scale application of SADeN technology in real wastewater treatment plants, providing an in-depth understanding of the role of dosing thiosulfate in tackling low-temperature challenges.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"46 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144802865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer Vision-Assisted High-Throughput Screening of Crystallization Additives for Crystal Size, Shape, and Agglomeration Regulation","authors":"Jian Liu, Tuo Yao, Muyang Li, Sohrab Rohani, Jingkang Wang, Zhenguo Gao, Junbo Gong","doi":"10.1016/j.eng.2025.02.023","DOIUrl":"https://doi.org/10.1016/j.eng.2025.02.023","url":null,"abstract":"Additives are widely employed to regulate the morphology, size, and agglomeration degree of crystalline materials during crystallization to enhance their functional, physical, and powder properties. However, the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments, making them time-consuming, resource-intensive, and reliant on the operator’s experience level. To overcome these challenges, we proposed a computer vision-assisted high-throughput additive screening system (CV-HTPASS) which comprises a high-throughput additive screening device, <em>in situ</em> imaging equipment, and an artificial intelligence (AI)-assisted image-analysis algorithm. Using the CV-HTPASS, we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties, generating thousands of crystal images with diverse crystal morphologies. To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency, the AI-based image-analysis algorithm was implemented innovatively for the segmentation, classification, and data mining of crystals with four morphologies to further screen the target additive. Subsequently, scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology, reduced agglomeration degree, narrowed crystal size distribution, and improved powder properties. The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments. Further, it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"31 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144802927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting Global Energy System Transformation Toward Carbon Neutrality: A Four-Stage Pathway of System Integration","authors":"Linwei Ma, Maximilian Arras","doi":"10.1016/j.eng.2025.07.031","DOIUrl":"https://doi.org/10.1016/j.eng.2025.07.031","url":null,"abstract":"The global energy landscape has undergone profound changes since the industrial revolution, characterized by three major shifts in primary energy sources [<span><span>1</span></span>]. These include the transition from biomass to coal between 1850 and 1950, followed by the shift from coal to oil from 1950 to 2000 and the more recent move toward a diversified energy structure at the beginning of the 21st century. Each shift was driven by visible crises—deforestation, air pollution, and oil supply disruptions—and the competitiveness of new technologies [<span><span>2</span></span>,<span><span>3</span></span>]. Currently, achieving carbon neutrality by 2050–2070 has become a global policy target, with 151 countries committed to national carbon neutrality goals by May 2024 [<span><span>4</span></span>]. In this context, energy system transformation (EST), also referred to as energy transition, has become a central concept representing the urgent need for radical structural changes in energy systems within a relatively short timeframe. Specifically, primary energy sources and carriers must predominantly derive from renewable energy and electricity, with an accelerated shift away from fossil fuels [<span><span>5</span></span>]. However, EST toward carbon neutrality presents a significantly more complex challenge. Aacademic discussions on EST have become increasingly popular in recent years. An early example is that Steve Rayner concluded <em>energy system must be recognized to be as much a social system as it is a technical one</em> after discussions of climate science and policy in his paper published in 2010 [<span><span>6</span></span>].","PeriodicalId":11783,"journal":{"name":"Engineering","volume":"2 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144792373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}