The present study proposes a systematic approach to weight and rank performance leading indicators for the safety barriers established against liquefied natural gas (LNG) leaks onboard the marine LNG units. To achieve the paper's target, a literature review of publications relevant to a set of issues related to the risk of marine LNG leaks is conducted. Based on that review, a comprehensive list of 51 performance leading indicators is developed. In addition, a hybrid multi-criteria decision-making (MCDM) approach is adopted to weight and rank the proposed indicators. The results indicate that the indicators’ ranking favours those that monitor the performance of aspects whose failure led to historical process leaks. Examples of these aspects are the integrity of the maintenance management system and the efficiency of developing and following safety-critical procedures. In addition, the results of the MCDM model showed stability against slight changes in the criteria’s weights. The study also discusses the possible uses of the indicators developed and weighted in this study within the safety and risk management in the marine LNG field.
In this work, a turbulent diffusion flame burning a methane-hydrogen mixture (1:1 by volume) under MILD combustion conditions and different co-flow compositions is investigated. The visible flame region extracted from flame images is compared with flame regions obtained from numerical simulations using several variables as potential flame markers. Quantitative metrics are employed to assess the level of agreement between numerically identified flame regions and flame photographs. The results indicate that the spatial distribution of the ground-state CH radical mass fraction provides the most accurate prediction of the visible flame envelope among the variables considered. Although ground-state CH does not emit in the visible range, its concentration peaks in the reaction zone where electronically excited species responsible for visible chemiluminescence are formed, leading to a strong spatial correlation with the observed luminous flame region. Other radicals, such as H, O and OH also exhibit a reasonable agreement with the flame region due to their presence in overlapping zones of intense chemical activity. In addition, reaction rates associated with key elementary reactions involving CH were examined and found to provide comparable flame-region predictions, with agreement levels exceeding 90%. The present results demonstrate the capability of combining Computational Fluid Dynamics (CFD) and image-processing techniques to validate turbulent diffusion flame simulations through direct comparison of flame-region geometry and represent one of the first studies to systematically compare experimentally observed visible flame regions with numerical flame markers under MILD combustion conditions for methane/hydrogen flames.
Recent studies show that six of nine Planetary Boundaries have been exceeded, highlighting the need to shift from relative to absolute environmental sustainability. However, there is still a limited understanding of the combined influence of consumption change, technological development, and contextual factors in determining whether passenger transportation can achieve it. Therefore, the goal of this study is to understand how changes in consumption, technology and contextual factors influence the achievement of absolute environmental sustainability in this area. Specifically, this study aims to assess whether shifts towards lower-impact alternatives are enough, how technological development and contextual factors interact in shaping absolute environmental sustainability, and what insights these findings generate for policymaking. To this end, the study adopts a three-level analysis approach: a diagnostic assessment of how European transportation respects specific environmental thresholds, an evaluation of a set of passenger transport consumption alternatives, and a case study in regional aviation examining how contextual factors influence achieving absolute environmental sustainability. The results show that most ambitious shifts towards lower-impact alternatives are currently insufficient to bring transport within environmental thresholds. Furthermore, environmental performance emerges not as an intrinsic property of a transport technology, but as an outcome of the sociotechnical configuration in which it operates, with contextual factors producing impact variations of up to fourfold for the same technology. For policymaking, this research provides insights into the need to govern burden shifting, align technology incentives with operational context, manage demand and potential rebound effects, and coordinate cross-sectoral access to energy.
In this paper we study Hamiltonian functions that are quotients of analytic functions and we introduce the notion of isochronous singularity for the corresponding Hamiltonian vector fields, in the sense that they have a singularity and a family of periodic orbits with the same period around that singularity. We study all these Hamiltonian vector fields and in particular we focus on the ones whose Hamiltonian functions are of the form H(x, y) = P(x, y)/S(x, y) where P(x, y), S(x, y) are homogeneous polynomials and the unique zero of S is the origin. We see that these vector fields behave as in the case of homogeneous polynomial vector fields with an isochronous center at the origin. We also describe all Hamiltonian vector fields having an isochronous singularity at the origin whose Hamiltonian is the form H(x, y) = P(x, y)/(x(2) + y(2)), where P(x, y) is a quartic homogeneous polynomial. Among these Hamiltonian vector fields, we characterize those having an isochronous singularity at the origin with P(x, y) even and we see that P(x, y) cannot be odd. Finally, we characterize all Hamiltonian vector fields with an isochronous singularity of period T whose Hamiltonians are of the form y(2)/2 +V(x), where V(x) = V-1(x)/V-2(x), V-i(x) are analytic functions around x = 0 and V2(0) = 0. We prove that up to a shift and adding a constant all such potentials have the form V(x) = pi(2)(x(2) + a(4)/x(2))/(2T(2)c(2)) with a, c is an element of R \ {0}.
Addressing the scenario of lake-based shipping environments where enclosed waterways, dense routes, and heavy traffic yield compact, complex trajectory patterns and conceal abnormal movements, a semi-supervised deep learning-based ship trajectory abnormal detection method is proposed. Firstly, an adaptive grid partitioning strategy is proposed that divides the study area into high- and low-density regions using kernel density estimation. The grid size in each region is then determined by the average nearest-neighbour distance among trajectory points within that region. Secondly, a joint network architecture is designed that integrates a convolutional-deconvolutional autoencoder with a Transformer classifier. The convolutional-deconvolutional autoencoder extracts local spatial features and latent structures of the trajectories in an unsupervised manner, while the Transformer classifier further models the global temporal dependencies of the trajectories. Finally, a dynamic weighted joint loss function and a two-stage optimisation strategy are introduced to coordinate reconstruction and classification objectives. Experimental results demonstrate that the proposed method achieves an average detection accuracy of 87.9%, precision of 94.6%, recall of 80.6%, and an F1 of 87.0% on the real AIS datasets of Lake Superior and Lake Huron, significantly outperforming existing supervised and unsupervised methods.
