Shengya Liu¹, Wei Bian^1,2, Linan Li^1,*, Yang Xue^1,2, Jingxun Yin³

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2025.074804 - 06 August 2026

Abstract Offshore wind energy plays a critical role in achieving global decarbonization goals, while the dynamic response mechanisms of megawatt-scale turbines under complex environmental conditions remain insufficiently characterized. Current research often oversimplifies the effects of monopile flexibility and its interaction with soil dynamics, leading to gaps in dynamic predictions. To address this limitation, this study develops a comprehensive 15-degree-of-freedom dynamic model for a 22 MW monopile offshore wind turbine (OWT) that incorporates nonlinear pile flexibility and soil-structure interaction through p-y and Q-z curves. The integrated analytical framework, established using Euler-Lagrange equations, enables coupled analysis of… More > Graphic Abstract

Qianpeng Hao^*, Qiang Li, Changyuan Yu, Deqing Zhang, Wenze Li, Yaowen Liu, Chao Wang, Chengran Song, Xiyu Feng, Xingchao Guo

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2026.074324 - 06 August 2026

Abstract Driven by the “Carbon Peak and Carbon Neutrality” strategic goals, high penetration of renewable energy poses severe challenges to power system flexibility. Unlocking the adjustable potential of demand-side industrial loads has become a critical pathway for constructing new-type power systems. To address the limitations of existing research, including single-dimensional characterisation of adjustable potential, insufficient consideration of both best and worst solutions in evaluation methods, and a lack of cluster coordination perspectives, this paper proposes a multi-dimensional adjustable potential assessment and priority ranking method for industrial loads. Firstly, based on the Affinity Propagation (AP) and k-means… More >

Saeed Tavakoli^*, Ahmad Shakibaeinia, Najib Bouaanani

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.081925 - 30 June 2026

Abstract Fluid–structure interaction (FSI) plays a critical role in civil engineering applications, directly influencing structural safety, resilience, and performance. However, the inherent multiphysics complexity of FSI problems presents significant challenges for numerical modeling, particularly under highly dynamic flow conditions. This study presents a fully Lagrangian mesh-free framework for FSI based on the moving particle semi-implicit (MPS) method. The approach couples an enhanced weakly compressible MPS (WC-MPS) fluid solver with a hybrid total–updated Lagrangian (TL–UL) MPS formulation for elastic solids. In the solid phase, strains are evaluated in the reference configuration, while momentum balance is enforced in… More >

M. Saad Bin Ilyas¹, Sohail Masood Bhatti¹, Ghazanfar Latif^2,*, Sherif Abdelhamid³, Arfan Jaffar¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.081720 - 30 June 2026

Abstract Federated learning (FL) has emerged as a promising approach for enabling collaborative model training across distributed Internet of Medical Things (IoMT) devices without sharing sensitive data. Existing FL frameworks face significant challenges in healthcare settings, including vulnerability to adversarial attacks, lack of verifiable update integrity, and limited robustness under heterogeneous data distributions. These limitations hinder reliable deployment in critical medical applications. To address these challenges, this paper proposes RP-IoMT, a robust and privacy-preserving FL framework that integrates secure multi-party computation (MPC), zero-knowledge proof-based gradient verification, and robust aggregation mechanisms. The objective of this work is… More >

Hong Min^1,*, Yousef Ibrahim Daradkeh², Jung Taek Seo^3,*, Mohd Anjum⁴, Sana Shahab⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.080871 - 30 June 2026

Abstract This study presents a computational modeling framework for efficient and secure computation offloading in Internet of Things (IoT)-enabled smart contract systems. The integration of IoT, edge computing, and blockchain introduces significant challenges, including limited device capacity, high verification cost, and scalability constraints. Existing blockchain verification approaches depend on computationally intensive cryptographic operations that are inefficient for resource-constrained IoT devices, resulting in increased latency, energy consumption, and transaction costs. To address these issues, this study proposes the Zero-Knowledge Fuzzy Logic Offloading and Rollup (Z-FLOR) framework, an adaptive and energy-efficient model designed to enable secure and verifiable… More >

Weijia Tang, Qiang Li^*, Ningyu Zhang

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.074698 - 18 June 2026

Abstract Large-scale offshore wind farm clusters (OWFCs) have been increasingly connected to the power grid, and requires advanced forecasting models to enhance the prediction accuracy of OWFC’s power output. This paper proposes a multi-source fusion with patch-guided multi-task learning for power prediction of offshore wind farm clusters. Unlike traditional graph-based approaches that rely on predefined topological relationships, which are limited in capturing the highly similar but rapidly changing meteorological conditions among closely spaced offshore farms, the proposed model employs a parameter-sharing multi-task learning network to achieves both independence and correlation among offshore wind farm clusters, followed More >

Bernard P. Zeigler^*

Digital Engineering and Digital Twin, Vol.4, pp. 1-26, 2026, DOI:10.32604/dedt.2026.082492 - 02 June 2026

Abstract As Digital Twin (DT) applications expand into complex, dynamic environments, a formal methodology is lacking to ensure that the embedded digital models remain adequate for specific stakeholder goals over time. This article introduces the Experimental Frame–System Under Test (EFSUT) methodology, providing a principled foundation for linking high-level stakeholder questions to the specific models capable of answering them. EFSUT organizes the digital engineering process around three core constructs: stakeholder questions, experimental frames that formalize observational requirements, and models related through morphisms. This structure allows developers to reason about model choice, reduction, and adequacy with technical rigor… More >

Lijuan Huang^1,2, Zhixian Liu³, Xinyu Zhou⁴, Jinping Liu^4,*, Kunyi Zheng⁴, Yimei Yang^2,4,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077655 - 08 May 2026

Abstract Many occluded and ambiguous ground truths exist in object detection, making detectors unable to obtain optimal training samples. In this article, we revisit the suboptimal sample issue in label assignment for object detection and propose a novel detector-agnostic strategy, termed FSS, to address it. FSS reformulates label assignment as the process of selecting high-quality sub-optimal samples and progressively transforming them into optimal ones. Specifically, for each candidate, we estimate the probability of being an optimal sample by jointly considering localization quality and classification confidence, thereby constructing an instance-wise probability matrix. Based on the spatial distribution More >

Segundo Esteban^1,*, Matilde Santos²

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.077663 - 27 April 2026

Abstract Wind turbines are highly efficient energy converters that exploit locally available renewable resources across many regions. In modern floating offshore wind turbines (FOWTs), strong aerodynamic and hydrodynamic loads give rise to nonlinear and tightly coupled dynamics, which typically require dedicated—and computationally demanding—simulation tools for analysis and control design. This work introduces a simplified, control-oriented mathematical model of a FOWT, derived directly from fundamental force and torque balances and explicitly incorporating the gyroscopic effect, which is often neglected in onshore wind turbines due to its comparatively lower significance. Model parameters are identified for the NREL 5-MW… More > Graphic Abstract

Seohyun Yoo, Joonseo Hyeon, Jaehyuk Cho^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077579 - 09 April 2026

Abstract Despite remarkable advances in medical large language models (LLMs), their deployment in real clinical settings remains impractical due to prohibitive computational requirements and privacy regulations that restrict cloud-based solutions. Small LLMs (sLLMs) offer a promising alternative for on-premise deployment, yet they require domain-specific fine-tuning that still exceeds the hardware capacity of most healthcare institutions. Furthermore, the impact of multilingual data composition on medical sLLM performance remains poorly understood. We present a resource-efficient fine-tuning pipeline that integrates Quantized Low-Rank Adaptation (QLoRA), Fully Sharded Data Parallelism (FSDP), and Sequence Packing, validated across two model scales: MedGemma 4B… More >