This research presents a comprehensive mooring design flow for a pendulum-based wave energy converter, including the design of extreme and operational sea states, a step-by-step mooring optimization, and a code check for Ultimate Limit State (ULS), Accidental Limit State (ALS), and Fatigue Limit State (FLS) based on the DNV standard. The numerical model built in OrcaFlex was validated through an experimental campaign and used for mooring design. Finally, a 3-leg hybrid mooring system consisting of elastic ropes and catenaries was obtained. Its comparison with the original design demonstrates a production increase of at least 20.7%, and the durability of the mooring system was also improved, mainly due to pretension and fairlead position adjustments. Besides, the safety code check results illustrate that fatigue damage functions as the primary threat for such a pitch-dominated device, indicating the importance of considering fatigue damage in preliminary design to avoid undesired mooring with high service life in ULS while significantly low design life in FLS. This work provides a comprehensive reference for future mooring design of the WECs that operate mainly on pitch motion, and the findings contribute to the research toward practical application of such wave energy technologies in rotating mass.
Regional carbon equity reflects the spatial alignment between carbon-emission responsibility and ecological carrying capacity, and represents an important dimension for understanding the distributive consequences of low-carbon transitions. As the digital economy becomes increasingly embedded in resource allocation, technological innovation, and environmental governance, whether and how it reshapes regional carbon equity remains insufficiently examined. Using panel data for 281 Chinese cities from 2010 to 2023, this study constructs a city-level carbon equity index and employs two-way fixed-effects models, mechanism tests, and a spatial Durbin model to investigate the effect of the digital economy on carbon equity, its transmission channels, and its spatial spillover effects. The results show that carbon equity in Chinese cities has improved slowly over time, although regional disparities remain pronounced and significant “high–high” and “low–low” spatial clustering patterns persist. The digital economy significantly improves urban carbon equity, with the strongest effect observed in central China. Mechanism tests indicate that the digital economy enhances carbon equity mainly by promoting industrial structure upgrading, stimulating green technological innovation, and strengthening market integration. Further spatial analysis shows that the digital economy improves carbon equity within local cities but exerts a negative spillover effect on neighboring cities, revealing a spatial pattern of “local promotion and neighboring suppression”. This study extends the literature on the environmental consequences of the digital economy by introducing a regional carbon equity perspective. It provides policy implications for optimizing the spatial allocation of digital resources, improving interregional coordination in low-carbon governance, and advancing a more equitable low-carbon transition.
Direct recycling of spent lithium-ion batteries requires selective dissociation of the cathode coating on the aluminum current collectors while minimizing cross-contamination of the recovered fractions. In this study, a chelator-based deep eutectic solvent (ChelaDES) made of levulinyl hydroxamic acid, glyceric acid, and trimethyl (2-methoxyethyl) ammonium chloride was designed as a low-temperature solvent for the selective interfacial separation of LCO, LFP, and NCA cathodes. The method uses four complementary key performance indicators (KPIs) as interfacial separation performance measures: active material removal, mass removed per unit area, bare-Al exposure, and delamination severity score. LCO showed the fastest response, reaching 93.7% active-material removal and >99% bare-Al exposure at 90 °C for 60 min. NCA showed intermediate behavior, reaching approximately 92.5% removal and 82% bare-Al exposure, while LFP exhibited threshold-controlled delamination, reaching 90.8% removal but only 66% bare-Al exposure under the same conditions. Among the kinetic models tested, the PSO-Arrhenius model provided the best overall fit for process comparison, giving apparent activation energies of 25.5, 26.5, and 28.5 kJ·mol−1 for LCO, NCA, and LFP, respectively. A strong correlation was observed for all chemistries between the removed mass per area and bare-Al exposure, which proves to be a useful, rapid quantitative proxy of foil liberation. Further purification studies with SEM-EDXS, XPS, and TGA/DTG suggested that the recovered black mass contained minimal impurities with minimal Al/Cu carryover (<0.1 wt%) and that the aluminum foil remained largely intact. Process heatmaps define the chemistry-specific operating windows, demonstrating that selective interfacial weakening, not bulk dissolution, controls separation. The process, therefore, acts as an upstream selective delamination and purification step, producing cleaner recovered black mass while preserving the current collector.
Although autonomous functioning facilitates the deployment of robotic systems in operating domains that support limited to no human oversight, establishing correspondence between task requirements and a system’s autonomous performance is still an open challenge. Several techniques for characterizing operating domains and/or quantifying autonomy have been proposed over the last three decades, however, to our knowledge, these have no discernment of sub-mode features of variation of autonomy, and some are based on metrics that are susceptible to the Goodhart’s law. This paper introduces a capability-based quantitative autonomy assessment framework for fully autonomous systems. The formulation of the framework started by establishing robot task characteristics from which three autonomy metrics, namely an essential capability set, reliability, and responsiveness, were derived. The characteristics were founded on the realization that robots ultimately replace human skilled workers, from which a relationship between human job and robot task characteristics was established. Additionally, mathematical formulations relating metrics to autonomy are also presented. To emphasize the fact that autonomy is not just a question of existence, but also one of performance of a capability, the framework represents it as a two-part measure, of level and degree of autonomy. Usage of the framework has been demonstrated on two case studies, namely an autonomous vehicle at an on-road dynamic driving task and the DARPA Subterranean Challenge analysis. The framework provides not only a tool for quantifying autonomy and monitoring the integrity of systems, but also a regulatory interface and common language for autonomous systems’ developers and users.
