Search Results (61)

The stability and functionality of offshore wind energy systems depend critically on how offshore platforms interact with the geotechnical features of the seabed. This review describes developments in five areas: (i) offshore geotechnical site investigation and strength assessment; (ii) seabed geohazard causes and deep-water mooring challenges; (iii) frameworks for seabed modeling; (iv) sediment behavior influencing anchor and mooring performance; and (v) selection of anchors based on their interactions with various soils. The review emphasizes developments in seabed assessment and modeling using field, lab, and numerical methods. It discusses how the new advances in analytical and simulation frameworks have enhanced our knowledge of anchor–mooring responses, cyclic loading behaviors, and soil–structure interactions under changing seabed conditions. The key findings reveal that: (1) cyclic loadings considerably change anchor holding capacity and evolution of seabed trenching, yet most existing design methods still use quasi-static loads; (2) site-specific data from integrated geophysical–geotechnical surveys are vital to reduce uncertainty in anchor penetration and the frictional resistance of chains; (3) geohazards, such as shallow gas, marine landslides, and seabed erosion, pose under-recognized risks to long-term anchor reliability. The lack of knowledge on the coupled, long-term evolution of the seabed–anchor–mooring line system is identified as another gap in the literature. Major gaps exist in validating the life cycle of anchor performance under real-scale storm–wave sequences for offshore geotechnical risk management in layered soils. At the end of the discussion, the current study also highlights the need for flexible, data-driven frameworks that integrate geotechnical, hydrodynamic, and structural analyses in a coupled framework to improve reliability in next-generation offshore wind energy systems. Full article

This paper analyzes a nonlinear compressor system to characterize its dynamic behavior and develop a control scheme that improves operational efficiency. A mathematical approach based on the Greitzer–Moore (GM) model is employed to predict the onset of surge and instability. Using phase-plane analysis and Jacobian linearization, the method identifies stable and unstable regions and captures the limit cycle within the unstable domain. The system is formulated in state-space form using the nonlinear GM model, and validation is performed using experimental data from a previously studied compressor. Because fixed-gain PID controllers exhibit limited robustness, an adaptive PD controller based on a Model Reference Adaptive System (MRAS) is designed. In addition, a reliable Model Predictive Control (MPC) controller is developed to enhance disturbance rejection. Simulation results demonstrate that both the adaptive PD and MPC controllers achieve stable operation under challenging conditions. Full article

Fueled by the push for “More than Moore”, three-dimensional integrated circuits (3D ICs) have become a backbone of next-generation electronics. Their complex architectures place unprecedented demands on etching technologies, which must now deliver atomic precision, stringent high-aspect-ratio (HAR) control, and virtually damage-free profiles. Meeting these challenges requires metrology capable of true 3D, quantitative analysis at the nanoscale. Atomic force microscopy (AFM) has proven essential in this regard, offering non-destructive, sub-nanometer characterization that other techniques cannot provide. This review systematically examines AFM’s pivotal role in advancing key etching processes for 3D ICs, including deep reactive ion etching of through-silicon vias (TSVs), atomic layer etching (ALE), and cryogenic plasma etching. We detail AFM’s unique contributions to quantifying sidewall roughness, verifying etch-per-cycle rates, and assessing surface damage. We also discuss how recent innovations, such as tilting-AFM, HAR probes, and automated inline systems, are overcoming traditional barriers in throughput and access to sidewalls and deep trenches. Looking forward, the integration of AFM with optical metrology, machine learning, and multi-scale modeling opens a path toward truly autonomous process control and optimization. As such, AFM stands as an indispensable tool for developing and refining the etching processes that underpin next-generation 3D semiconductor manufacturing. Full article

This study characterizes the structure and variability of baroclinic semidiurnal tidal currents at the head of the Biobio Submarine Canyon (BbC), off central Chile, based on Acoustic Doppler Current Profiler (ADCP) and moored thermistor-chain observations from two deployments conducted in 2013 and 2014 under contrasting stratification conditions. The results show that the head of the BbC is a dynamically active site of semidiurnal variability, with markedly stronger and more coherent baroclinic motions during the more stratified winter–spring 2014 period. During that deployment, semidiurnal baroclinic current amplitudes reached up to 17 cm s⁻¹, and the associated energy was concentrated near the surface and bottom. Rotary spectral analysis indicated that these semidiurnal baroclinic currents rotated anticyclonically and were closely aligned with the canyon axis. Empirical orthogonal function (EOF) analysis further showed that their vertical structure was dominated by a first baroclinic mode, which explained more than 70% of the semidiurnal baroclinic variance in 2014. In contrast, the 2013 deployment exhibited weaker and less coherent semidiurnal baroclinic variability. Taken together, these results indicate that stronger stratification favored the development of semidiurnal internal-tide-related motions over the canyon head and that the BbC provides a dynamically favorable setting for enhanced semidiurnal internal-tide activity and potentially elevated mixing, although direct turbulence or dissipation measurements were not available in this study. These findings have potential implications for local water-column structure, nutrient supply, and primary productivity in this highly productive coastal region. Full article

A dynamic analysis of a compressor system is presented to characterize its behavior and establish a mathematical framework for identifying stable and unstable operating regions. The study is grounded in the nonlinear Moore–Greitzer model, which describes compressor dynamics in terms of mass flow and pressure rise as functions of rotor speed. To predict the onset of surge and system instability, advanced nonlinear techniques are employed, including the Jacobian matrix, linear parameter-varying (LPV) modeling, Bendixson’s criterion, and phase plane analysis. These tools enable the identification of both stable and unstable regions, as well as the limit cycle associated with surge phenomena. All of these analyses of the compressor are innovative. Accurate prediction of compressor surge and instability is essential for defining and designing effective control strategies, as surge can damage the compressor, interrupt downstream flow, and inherently represents an unstable operating condition. However, analysis alone is insufficient for practical compressor operation. Therefore, three active control methods are considered: Proportional–Integral–Derivative (PID), Linear Quadratic Regulator (LQR), and Model Predictive Control (MPC). The comparative analysis reveals that insufficient consideration of varying system conditions in LQR design may lead to inferior performance relative to MPC and PID control, particularly under changing disturbances. In contrast, MPC and PID exhibit stronger robustness to disturbance variations and provide effective disturbance rejection. In the proposed approach, MPC simulations are conducted to evaluate controller performance. Due to disturbances in the closed-loop model, the LQR controller demonstrates reduced robustness compared to PID and MPC. Under surge-related disturbances, the minimum input mass flow by both PID and MPC controllers is 0.495 (very close to setpoint), and both controllers exhibit an overshoot of 33% and a rise time of 3 s. Full article

This study investigates the floating wind turbine (FWT)–Net cage integrated platform, where the net cage is rigidly connected to the FWT foundation. The platform is numerically modeled using time-domain simulations in OrcaFlex V11.1, based on representative environmental conditions of the South China Sea. The operational performance of two layouts of the platform is evaluated and compared, considering both power generation efficiency and residual volume ratio as key indicators. The results show that the FWT–Net cage integrated platform exhibits superior hydrodynamic stability, characterized by reduced surge and pitch motions, lower mooring force fluctuations, and a higher residual cage volume. Additionally, the platform achieves better power generation efficiency and a higher residual volume ratio, indicating more effective use of the aquaculture space. Based on these findings, an improved integrated design incorporating additional outer net cages is proposed. This design demonstrates enhanced aquaculture capacity while maintaining power generation. The results provide valuable insights for the design of FWT–Net cage integration, promoting the efficient and sustainable utilization of marine space. Full article

The emergence of chiplet-based architectures represents a paradigm shift in post-Moore’s Law computing systems, offering substantial cost and yield advantages through functional disaggregation. However, the heterogeneity of inter-chiplet communication introduces unique performance challenges that conventional partitioning strategies fail to address. In this work, the ways in which poor workload partitioning degrades communication performance in chiplet-based systems are comprehensively characterized. We demonstrate, through a detailed experimental analysis, that suboptimal workload partitioning can increase inter-chiplet communication latency by up to a factor of 10 and inflate network congestion beyond sustainable levels as systems scale. Our findings show that optimized partitioning strategies can achieve an 87.4% reduction in inter-chiplet traffic, improve system throughput by a factor of 8.75, and enhance energy efficiency by a factor of 10.3 compared to naive partitioning approaches. We further characterize how these effects scale with system size, revealing that the communication overhead can consume 85% of the execution time in poorly partitioned 16-chiplet systems, compared to only 35% in well-partitioned configurations. This work provides essential insights into the communication-aware design space of chiplet systems and validates the critical importance of sophisticated workload partitioning algorithms. Full article

This paper aims to simplify the form of the MPBT inverse, further explore its properties, and discuss when it coincides with other generalized inverses. Notably, the MPBT inverse coincides with the Moore–Penrose inverse when the index of the matrix is at most 1; the MPBT inverse equals the MPCEP-inverse when the index of the matrix is at most 2. Additionally, new characterizations of bi-EP matrices are presented, based on some properties of the MPBT inverse. Finally, MPBT matrices constructed via the MPBT inverse are shown to be equal to B-T matrices. Full article

Cryogenic CMOS technology provides a promising approach to surpass the Boltzmann limit and advance Moore’s Law, addressing the increasing demand for high-performance computing. However, at cryogenic temperatures, the subthreshold swing (SS) of the device saturates due to the band-tail effect. This study presents a 3-vertically stacked gate-all-around nanosheet (NS) transistor featuring room-temperature O radical interface passivation. This approach leverages the high reactivity of O radicals to minimize etch-induced damage, passivate interface defects, reduce thermal budget, and ensure uniformity in complex 3D structures. Structural characterization revealed a uniform 0.76-nm-thick interface layer, with a surface roughness of 0.103 nm and an interface trap density of 2.72 × 10¹¹ cm⁻²·eV⁻¹ at 300 K. Thereby, the band-tail-induced SS saturation at cryogenic temperatures is effectively mitigated. Experimental results confirm a lower characteristic temperature T_v for reaching the saturation plateau, and a saturated SS of 15.4 mV/dec at 4.5 K. Furthermore, reducing disorder-induced defects substantially suppresses the band tail state-assisted carrier emission, thereby minimizing subthreshold leakage. This enables the device to achieve an off-state current below 1 pA/μm at a temperature under 77 K, reaching 0.18 pA/μm at 4.5 K. Additionally, a reduction in 25.4% in drain-induced barrier lowering (DIBL), with a 9% boost in transconductance (G_m) peak is achieved at 4.5 K. The enhanced subthreshold switching, reduced leakage, and improved G_m in this interfacial-optimized NS FET strongly supports cryo-CMOS as a viable solution for energy-efficient computing. Full article

Measuring water motion is essential for oceanography, coastal engineering, and marine environmental monitoring. A wide range of sensing technologies is used to quantify water velocity, wave motion, and flow dynamics, each suited to specific spatial and temporal scales. This paper presents a comprehensive review of modern sensor technologies for marine flow measurement, covering mechanical, electromagnetic, pressure-based, acoustic, optical, MEMS-based, inertial, Lagrangian, and remote-sensing approaches. The operating principles, strengths, and limitations of each technology are examined alongside their suitability for different environments and deployment platforms, including moorings, buoys, vessels, autonomous underwater vehicles, and drifters. Special attention is given to rapidly advancing fields such as MEMS flow sensors, multi-sensor fusion, and hybrid systems that combine inertial, acoustic, and optical data. Applications range from high-resolution turbulence measurements to large-scale current mapping and wave characterization. Remaining challenges include biofouling, performance degradation in energetic shallow waters, uncertainties in indirect velocity estimation, and long-term calibration stability. By synthesizing the state of the art across sensing modalities, this review provides a unified perspective on current technological capabilities and identifies key trends shaping the future of marine flow measurement. Full article

This study investigated the chemical recycling of poly(ethylene terephthalate) (PET) fiber residues from two sources—high-molar mass mooring ropes and low-molar mass textile-grade fibers—to produce functional oligomers. Glycolysis was carried out using polyethylene glycol (PEG400) as the depolymerizing agent, and two catalysts were assessed, zinc acetate and lithium octoate, with the latter reported on for the first time in this application. Reactions were performed for 180 min under mechanical stirring, inert atmosphere, reflux, and controlled heating. The resulting oligomers were characterized by Fourier-transform infrared spectroscopy (FTIR), hydroxyl and acidity indices, and thermogravimetric analysis (TGA). Both PET feedstocks showed high reactivity toward glycolysis. Monitoring the reactions by acidity index indicated that conversion reached equilibrium at approximately 120 min. ATR-FTIR confirmed the formation of ester and hydroxyl groups, consistent with oligomer structures. Glycolysis of PET derived from mooring ropes produced oligoesters with hydroxyl values of 228 and 242 mgKOH/g for zinc acetate and lithium octoate, respectively, and molar masses of 1296 and 1338 g/mol for zinc acetate and lithium octoate, respectively. These values are suitable for subsequent syntheses such as polyester polyol production. Full article

This research presents a novel thermomechanical model of a rotatable spherical shell characterized by changing thermal conductivity, situated within the framework of the Moore–Gibson–Thompson (MGT) theorem of generalized thermoelasticity. The governing differential equations in the Laplace transform domain, utilizing non-dimensional variables, have been applied to a thermoelastic, isotropic, homogeneous spherical shell subjected to ramp-type thermal loading. The numerical distributions of temperature increase, volumetric strain, and invariant average stress are illustrated in figures for varying values of thermal conductivity, ramp-time heat, rotation speed, and Moore–Gibson–Thompson relaxation time, and are analyzed. The variable thermal conductivity impacts all analyzed functions and substantially modifies the behaviour of the thermomechanical spherical shell. The ramp-time heat, rotational speed, and relaxation time of the Moore–Gibson–Thompson parameters substantially influence the distributions of temperature increase, volumetric strain, and invariant stress. Full article

Accurate measurement of sea-surface winds is critical for climate science, physical oceanography, and the rapidly expanding offshore wind energy sector. Buoy-based platforms—moored meteorological buoys, drifters, and floating LiDAR systems (FLS)—provide practical alternatives to fixed offshore structures, especially in deep water where bottom-founded installations are economically prohibitive. Yet these floating platforms are subject to continuous pitch, roll, heave, and yaw motions forced by wind, waves, and currents. Such six-degree-of-freedom dynamics introduce multiple error pathways into the measured wind signal. This paper synthesizes the current understanding of motion-induced measurement errors and the techniques developed to compensate for them. We identify four principal error mechanisms: (1) geometric biases caused by sensor tilt, which can underestimate horizontal wind speed by 0.4–3.4% depending on inclination angle; (2) contamination of the measured signal by platform translational and rotational velocities; (3) artificial inflation of turbulence intensity by 15–50% due to spectral overlap between wave-frequency buoy motions and atmospheric turbulence; and (4) beam misalignment and range-gate distortion specific to scanning LiDAR systems. Compensation strategies have progressed through four recognizable stages: fundamental coordinate-transformation and velocity-subtraction algorithms developed in the 1990s; Kalman-filter-based multi-sensor fusion emerging in the 2000s; Response Amplitude Operator modeling tailored to FLS platforms in the 2010s; and data-driven machine-learning approaches under active development today. Despite this progress, key challenges persist. Sensor reliability degrades under extreme sea states precisely when accurate data are most needed. The coupling between high-frequency platform vibrations and turbulence remains poorly characterized. No unified validation framework or benchmark dataset yet exists to compare methods across platforms and environments. We conclude by outlining research priorities: end-to-end deep-learning architectures for nonlinear error correction, adaptive algorithms capable of all-sea-state operation, standardized evaluation protocols with open datasets, and tighter integration of intelligent software with next-generation low-power sensors and actively stabilized platforms. Full article

To address the issues of insulation layer damage and conductor exposure in offshore floating photovoltaic systems occurring in shallow marine regions characterized by significant tidal ranges under multi-field coupling effects, an overhead cable laying scheme based on the hybrid pile–floater structure is proposed, while its mechanical response is investigated in this paper. The motion response model of the floating platform, considering wind load, wave load, current load, and mooring load, as well as the equivalent density and mathematical model of the overhead cable are established. The mechanical response characteristics of the overhead cable are analyzed through finite element analysis software. The results indicate that the overhead cable’s mechanical response is influenced by the span length and coupled wind–ice loads. Specifically, the tension exhibits a nonlinear increasing trend, while the deflection shows differential variations driven by the antagonistic interaction between wind and ice loads. The influence of ice loads on the configuration of overhead cables is significantly weaker than that of wind loads. This study provides crucial theoretical support for enhancing the lifespan of the overhead cable. Full article

The Soft Yoke Mooring (SYM) system is a critical single-point mooring method for Floating Production Storage and Offloading systems (FPSOs) in shallow waters. Its articulated thrust roller bearing operates long-term in harsh marine environments, making it prone to failure and difficult to diagnose. To address the issues of non-stationary signals and fault features submerged in strong noise caused by the bearing’s non-rotational oscillatory motion, this paper proposes an adaptive improved diagnosis scheme based on Minimum Entropy Deconvolution (MED). By optimizing Finite Impulse Response (FIR) filter parameters to adapt to the oscillatory operating conditions and combining joint analysis of time-domain indicators and envelope spectra, precise identification of bearing faults is achieved. Research shows that this method effectively enhances fault impact components. After MED processing, the kurtosis value of the fault signal can be significantly increased from approximately 2.6 to over 8.6. Its effectiveness in noisy environments was verified through simulation. Experiments conducted on a 1:10 scale soft yoke model demonstrated that the MED denoising and filtering signal analysis method can effectively identify damage in the thrust roller bearing of the SYM system under marine conditions characterized by high noise and complex frequencies. This study provides an efficient and reliable method for fault diagnosis of non-rotational oscillatory bearings in complex marine environments, holding significant engineering application value. Full article