This study presents a highly efficient and accurate approximate method based on a convergence acceleration parameter to approximate a nonlinear multidimensional aggregation population balance equation. Optimal tuning of the acceleration parameter significantly enhances solution quality over extended temporal domains and overcomes key limitations of existing approaches. Deeper mathematical insight is provided through a discussion of the existence of the proposed approach within the framework of a nonlinear aggregation model. Convergence analysis and error estimates are established using the fixed point theorem and the contractive mapping principle, thereby proving the existence of solutions to the aggregation model. The accuracy and efficiency of the proposed approach are demonstrated by computing approximate solutions for the number density function and its moments for physically relevant kernels. For analytically tractable kernels, results are validated against exact solutions. For complex size-dependent kernels, including polymerization, Ruckenstein–Pulvermacher, and shear kernels, the obtained results are compared with the existing finite volume scheme, homotopy analysis method, and optimal decomposition method. The results show that the proposed approach achieves higher accuracy in capturing number density functions and their integral moments while requiring significantly fewer series terms than existing methods.
Aggregation schemes provide a means to reduce the computational complexity of power system operation by reducing the number of devices that are considered individually. This can be achieved with tools of computational geometry, where the feasible set is projected onto the decision variables of the point of interconnection. Set projection is computationally expensive, especially in the context of multi-period power system operation. This calls for efficiency improvements via structure exploitation of set representations. This paper proposes efficient flexibility aggregation via constrained zonotopes. We evaluate the performance of the proposed method on a 15-bus distribution grid with time-dependent elements for up to 96 timesteps. The results suggest that the presented method significantly improves computation times compared to classic polytope projection approaches.
Embodied Artificial Intelligence (EAI) is increasingly seen as a promising route toward flexible automation, also in industrial operations. Yet the term is used inconsistently, and existing surveys often address isolated components rather than the combined role of embodiment, learning, perception, action, data, and industrial deployment constraints. This paper presents a PRISMA-guided systematic literature review of recent EAI research in industrial operations. We first consolidate the terminology of EAI and define four guiding characteristics: embodiment, learning, perception-action coupling, and situated intelligence. Based on this framework, we introduce a manipulation-mobility matrix for classifying physical embodiments and analyze the reviewed literature across industrial applications, research focuses, hardware forms, input and output modalities, learning architectures, datasets, simulation environments, and training paradigms. The results show that current research is dominated by assembly and manufacturing scenarios, stationary robotic arms, vision- and language-based interfaces, and modular foundation model-centered architectures. However, tightly coupled sensorimotor learning, tactile and force feedback, situated intelligence, and validated real-world deployment remain limited. This review clarifies the current state of industrial EAI and identifies the key gaps that must be closed to enable scalable deployment in industrial operations.
The COSMO-SAC-Phi model developed by Soares et al. extends the COSMO-SAC activity-coefficient framework into a full equation of state by explicitly accounting for pressure effects. In this approach, pure substances and mixtures are represented as pseudo-mixtures consisting of the actual number of moles and an additional pseudo-component that describes free volume, or holes. In this work, we implement this extension within the openCOSMO-RS framework and evaluate it using a large and diverse set of molecules and binary systems. The resulting equation of state includes an extensive open-source parameter set with around 1800 pure-component entries, made freely available to the academic community. The four pure-component parameters were fitted to vapor-pressure and liquid-molar volume data for each substance. Model performance was assessed against two benchmark equation-of-state databases, one for pure compounds and one for binary mixtures, without introducing any binary interaction parameters. The resulting openCOSMO-RS-Phi model reproduces the accuracy of the original COSMO-SAC-Phi formulation while providing a fully open-source and accessible implementation for the scientific community. Beyond its immediate utility, it also establishes a foundation for future development of predictive EoS for electrolyte solutions.
Marine propellers are continually expected to achieve higher efficiency, lower noise, compactness, and improved manoeuvrability often simultaneously. However, conventional screw propellers are approaching their performance limits, prompting the exploration of unconventional propeller concepts for further advancement. This paper reviews recent studies on the hydrodynamic performance of several unconventional marine propellers, including tip-loaded propellers, contra-rotating propellers, rim-driven thrusters, vertical axis propellers, tandem propellers, and toroidal propellers. The review summarizes their geometric features, hydrodynamic characteristics, advantages and limitations, underlying mechanisms, and key directions for future research. The findings indicate that: (1) not all unconventional propellers enhance efficiency, yet many offer advantages in noise, vibration, or manoeuvrability; (2) simulation-base optimisation has become the state-of-the-art approach for both design and fair performance comparison among propeller types; (3) tip-loaded and contra-rotating propellers are proven to improve propulsive efficiency, while the newly proposed toroidal propeller requires further scientific investigation; and (4) despite varying levels of technological maturity, research on cavitation, scale effect, and radiated noise remains insufficient for most unconventional propellers.
