Catalytic Combustion of Lean Methane Assisted by Electric Field over Pd/Co<Subscript>3</Subscript>O<Subscript>4</Subscript> Catalysts at Low Temperature

A series of Pd/Co₃O₄ catalysts were prepared by Self-Propagating High-Temperature Synthesis (SHS) method in this study, and electric field was applied for catalytic combustion of lean methane over Pd/Co₃O₄ catalysts at low temperature. When electric field was applied, the catalytic combustion performance of Pd/Co₃O₄ catalysts was greatly improved, and the application of electric field could reduce the load of active element Pd to some extent while maintaining the same efficiency. Based on experimental tests and the analysis results of X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), H₂-temperature-programmed reduction (H₂-TPR) and in-situ diffuse reflectance infrared Fourier transform spectroscopy (in-situ DRIFTS), the mechanism of catalytic oxidation of CH₄ over Pd/Co₃O₄ catalysts in electric field was proposed. The catalytic combustion of CH₄ occurs only when the temperature is higher than 250 °C normally, but when electric field was applied, the whole process of CH₄ oxidation was promoted significantly and the reaction temperature was reduced. Electric field could promote the reduction of the support Co₃O₄ to release the lattice oxygen, resulting in the increase of PdO_x and the surface chemisorbed oxygen, which could provide more active sites for the low-temperature oxidation of CH₄. Furthermore, electric field could accelerate the dehydroxylation of CoOOH to further enhance the activity of the catalysts.     

Automatic semantic analysis of software requirements through machine learning and ontology approach

Nowadays, software requirements are still mainly analyzed manually, which has many drawbacks (such as a large amount of labor consumption, inefficiency, and even inaccuracy of the results). The problems are even worse in domain analysis scenarios because a large number of requirements from many users need to be analyzed. In this sense, automatic analysis of software requirements can bring benefits to software companies. For this purpose, we proposed an approach to automatically analyze software requirement specifications (SRSs) and extract the semantic information. In this approach, a machine learning and ontology based semantic role labeling (SRL) method was used. First of all, some common verbs were calculated from SRS documents in the E-commerce domain, and then semantic frames were designed for those verbs. Based on the frames, sentences from SRSs were selected and labeled manually, and the labeled sentences were used as training examples in the machine learning stage. Besides the training examples labeled with semantic roles, external ontology knowledge was used to relieve the data sparsity problem and obtain reliable results. Based on the SemCor and WordNet corpus, the senses of nouns and verbs were identified in a sequential manner through the K-nearest neighbor approach. Then the senses of the verbs were used to identify the frame types. After that, we trained the SRL labeling classifier with the maximum entropy method, in which we added some new features based on word sense, such as the hypernyms and hyponyms of the word senses in the ontology. Experimental results show that this new approach for automatic functional requirements analysis is effective.     

Simulation of hydrodynamic performance of drag and double reverse propeller podded propulsors

The unsteady performance of drag and double reverse propeller podded propulsors in open water was numerically simulated using a computational fluid dynamics (CFD) method. A moving mesh method was used to more realistically simulate propulsor working conditions, and the thrust, torque, and lateral force coefficients of both propulsors were compared and analyzed. Forces acting on different parts of the propulsors along with the flow field distribution of steady and unsteady results at different advance coefficients were compared. Moreover, the change of the lateral force and the difference between the abovementioned two methods were mainly analyzed. It was shown that the thrust and torque results of both methods were similar, with the lateral force results having the highest deviation     

Study on collision between two ships using selected parameters in collision simulation

In the present analysis, several parameters used in a numerical simulation are investigated in an integrated study to obtain their influence on the process and results of this simulation. The parameters studied are element formulation, friction coefficient, and material model. Numerical simulations using the non-linear finite element method are conducted to produce virtual experimental data for several collision scenarios. Pattern and size damages caused by collision in a real accident case are assumed as real experimental data, and these are used to validate the method. The element model study performed indicates that the Belytschko-Tsay element formulation should be recommended for use in virtual experiments. It is recommended that the real value of the friction coefficient for materials involved is applied in simulations. For the study of the material model, the application of materials with high yield strength is recommended for use in the side hull structure.     

Epistemic-based investigation of the probability of hazard scenarios using Bayesian network for the lifting operation of floating objects

Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method (SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.     

CFD-based method of determining form factor <Emphasis Type="Italic">k</Emphasis> for different ship types and different drafts

The value of form factor k at different drafts is important in predicting full-scale total resistance and speed for different types of ships. In the ITTC community, most organizations predict form factor k using a low-speed model test. However, this method is problematic for ships with bulbous bows and transom. In this article, a Computational Fluid Dynamics (CFD)-based method is introduced to obtain k for different type of ships at different drafts, and a comparison is made between the CFD method and the model test. The results show that the CFD method produces reasonable k values. A grid generating method and turbulence model are briefly discussed in the context of obtaining a consistent k using CFD.     

A simulation-based probabilistic design method for arctic sea transport systems

When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this challenge. The outcome of the paper indicates that the incorporation of simulations and probabilistic design parameters into the design process enables more informed design decisions. For instance, it enables the assessment of the stochastic transport capacity of an arctic ship, as well as of its long-term ice exposure that can be used to determine an appropriate level of ice-strengthening. The outcome of the paper also indicates that significant gains in transport system cost-efficiency can be obtained by extending the boundaries of the design task beyond the individual vessel. In the case of industrial shipping, this allows for instance the consideration of port-based cargo storage facilities allowing for temporary shortages in transport capacity and thus a reduction in the required fleet size / ship capacity.     

Experimental study on reflection coefficient of curved perforated plate

A set of experiments is carried out in a towing tank to study the effects of the curvature of perforated plates on the wave reflection coefficient (C _r ). The curvature of a perforated plate can be changed by rotating a reference perforated plate aboutits origin according to the parabolic equation y=?x ². A plunger-type wave maker is used to generate regular waves. The reflection coefficients are calculated using Goda and Suzuki’s (1976) method. The results are compared with those of vertical or sloped passive wave absorbers. The comparison shows that a perforated plate with a curved profile is highly efficient in terms of reducing the wave reflection coefficient. A correlation is established to estimate the reflection coefficient of curved perforated plates as a function of both flow and geometry characteristics.     

Evaluating the impact of PSC inspectors’ professional profile: a case study of the Spanish Maritime Administration

Full-scale globalisation of trade has been accompanied by a progressive liberalisation of maritime transport. The proliferation of open registries has created a situation in which Port State Control (PSC) has become much more effective than the feeble or non-existent control exercised by those States. This study has been conducted on the influence of the professional profile of inspectors on inspection results. The objective of our paper was to evaluate the impact of PSC inspectors’ professional profile by conducting a case study of the Spanish Maritime Administration. The paper concludes with a discussion of the correlation between deficiencies detected and professional profiles.     

Blue growth and ocean governance—how to balance the use and the protection of the seas

The economic value of the oceans and maritime industry is strongly gaining in importance. As the oceans are very large and particularly sensitive ecosystems, which need to be preserved, a balance between the use and the protection of the seas has to be found. On this issue, the paper presents some thoughts starting with a brief analysis of what to understand by maritime industry which is labeled as blue economy, and a recapitulation of the main threats for the marine environment, caused by blue economy. After that, some noteworthy prerequisites and criteria for finding a sound balance between the use and the protection of the seas will be highlighted, especially the need for sustainable ocean governance is put to discussion.