On risk management of shipping system in ice-covered waters : Review, analysis and toolbox based on an eight-year polar project

Publisher Copyright: © 2022 The AuthorsWith the climate change, polar sea ice is diminishing. This, on one hand, enables the possibility for e.g., Arctic shipping and relevant resource exploitation activities, but on the other hand brings additional risks induced by these activities. Increasing research focuses have been observed on the relevant topics in the complex and harsh polar environment and its fragile ecosystem. However, from risk management perspective, there is still a lack of holistic analysis and understanding towards safe shipping in the ice-covered waters and its available models applicable for managing risks in the system. Therefore, this paper aims to establish a framework and analysis for better understanding of this gap. The paper targets a comprehensive and long-term project specifically focusing on holistic safe shipping in ice-covered waters as the analysis basis. It firstly creates a holistic framework for the shipping system in ice-covered waters and then implements review and analysis of project publications on their overall features. Quantitative prediction models are selected for a structured applicability analysis. Furthermore, an extensive review outside the project following the elements established for the holistic shipping system is conducted so that this paper provides an overview of models for the shipping system in ice-covered waters, addressing the status of the current toolbox. Moreover, it helps to identify the next scientific steps on risk management of shipping in ice-covered waters.Peer reviewe

Review of the safety engineering techniques for a complex ship system

Marine industry is leaning towards the autonomous vessels; and advanced technologies are being developed for autonomous operations. However, this rapid technological change has increased the level of complexity in ship systems. As the interactions between components are increasing further and software are getting imbedded into components, the nature of risks in modern systems can be different than in the traditional systems; where the risks were mostly limited to human errors and component failures. However, for identifying risks in modern systems, it is first important to understand the system composition and the behavior of components. Since traditional system-safety engineering techniques, developed for the relatively simpler systems in past, are still dominant in marine industry. These techniques may not be able to cope with the risks due to increasing complexity.This paper reviews and identifies a suitable modelling approach and a risk analysis method for a complex ship system. A modern modeling approach known as Systems-Modeling Language (SysML) and a modern risk analysis method known as Systems-Theoretical Process Analysis (STPA) are reviewed and compared with widely used traditional methods known as the Tree structure method and Fault Tree Analysis. SysML is a graphical modeling language that presents structural composition, component functions, behavior, constraints and requirements of a complex system. STPA is a risk analysis method that aims to identify and mitigate risks in a complex system. The review and comparison results are presented in the paper.The results of this study suggest that the modern methods are more suitable than the traditional methods when the functionality of each method are considered. However, as the modern methods are more detailed, and are focused on the functionality, they are relatively complex and require more resources for the analysis in comparison to the traditional methods. Some viable solutions to improve the drawbacks of SysML and STPA, and possible future research topics are presented.Peer reviewe

Developing fuzzy logic strength of evidence index and application in Bayesian networks for system risk management

Digitalization is becoming a trend in our modern society and systems. Meanwhile, risk analysis and management has rooted and been applied in various fields. Therefore, there is an increasing need to integrate risk analysis and management into the coming digital society. Risk has been represented digitally by the product of probability and consequence i.e. R = P x C traditionally. However, it has been increasingly discussed to include strength of evidence (SoE) in addition to the traditional consequence (C) and probability (P). Although much advance has been achieved along this direction, there still remains challenges, e.g. ambiguity in rating SoE and visual expression of risk diagrams. This paper focuses on addressing these issues and meanwhile aims to make the risk expression fully digital so that it is more efficient and flexible to be included in a system analysis and visualization. This is achieved firstly by reviewing state-of-the-art discussions on SoE assessment in risk management and identifying the remaining challenges. Then, the paper proposes an approach to address the challenges by forming a fuzzy logic SoE index based on fuzzy logic theory, which enables a transfer from linguistic variable to a digital one with the ambiguity avoided. After the SoE index is formed, it is applied into BNs as the node size index to demonstrate its practical application. Meanwhile, with the BNs forming the infrastructure to calculate and present consequences and probabilities, it showcases a new system risk management approach. All the variables in the system can be expressed in a risk diagram. This further enables an improved risk visualization, risk management and risk communication for system analysis, towards risk digitalization.Peer reviewe

Asthma, allergies and respiratory symptoms in different activity groups of swimmers exercising in swimming halls

Background Respiratory symptoms are common in competitive swimmers. However, among these and in swimmers at other activity levels the swimming distance, the total spent time in swimming halls and their medical background varies. Our objectives were, first, to assess their medical histories and the associations with respiratory symptoms among swimmers in different activity groups and then second, to study the pulmonary function findings and related medications in competitive swimmers who exercise in swimming hall environments the most. Methods First, 1118 participants consisting of 133 competitive-, 734 fitness- and 251 occasional swimmers answered questionnaires concerning their medical background, their respiratory symptoms in connection to swimming distance and their amount of time spent in swimming halls. Secondly, in 130 competitive swimmers, pulmonary function was tested by spirometry and a specific questionnaire was used to assess respiratory symptoms, medical histories and prescribed medication. Results Respiratory symptoms were reported by 18% of the studied swimmers. Competitive swimmers had significantly more symptoms than fitness- and occasional swimmers. Naturally competitive swimmers swum more than 2000 m and stayed by the pool more than 90 min, longer than the other activity groups of swimmers. Spirometry testing showed airway obstruction in 15 swimmers, which was 12% of the 130 competitive swimmers. 21 of them, had physician-diagnosed asthma and 16 of these individuals had prescribed medication for it. Conclusions Competitive swimmers had the highest swimming hall exposure and reported significantly more respiratory symptoms. A high prevalence of airway obstruction findings in competitive swimmers with asthma and allergies suggests a need for future recommendations for regular testing and special medical care for competitive swimmers.Peer reviewe

Impact of similarity measures on causal relation based feature selection method for clustering maritime accident reports

Abstract: Unsupervised document clustering is an automated process in which documents are analyzed based on their similarity. In this paper, we propose a new feature selection method based on causal relations to classify maritime accident reports in unsupervised manner. We also compare the impact of different similarity measures on proposed feature selection method. Based on the analysis, we conclude that the proposed feature selection method has better performance over the conventional method due to the effect of dimensionality curse. The impact of similarity measures improves with the proposed feature selection method. In the analysis, we have compared Correlation, Cosine, Spearman, Bray-Curtis, Euclidean, City-block, Squared-Euclidean, Standardized Euclidean, and, Chebychev similarity measures. The first two produced the best results, followed by the next two. The rest did not produce good results with the maritime accident reports used in our analysis. Interestingly Chi-Square gave good results with proposed method in our analysis

Hazard Identification in Winter Navigation

In this report, a hazard identification in winter navigation has been performed in order to detect, determine, list and categorize different relevant hazards threatening the safety performance and development of the winter navigation operations. The analysis presented in this report aims to gather all available information from different sources in order to detect hazards for the practice of winter navigation, having a particular consideration of winter navigation hazards of oil tankers operation and/or vessels with similar characteristics. The report introduces the implemented framework to detect the relevant hazards of winter navigation and describes in details the three utilized sources to detect those hazards: hazard identification workshops with winter navigation experts, accident cases analysis, and analysis of accident statistics of 5 winters. Results obtained are presented after the performed collection and data analysis. Finally, discussion and conclusions are drawn

Merlog 2030: merikuljetusten logistiikka ja ulkomaankaupan kilpailukyky

Väylämaksujen uudistustarpeen taustalla on muun muassa kauppalaivastolle tulevat uudet kansainväliset energiatehokkuuden ja päästövähennysten vaatimukset. Nämä muutokset vaikuttavat myös jäänmurron tarpeen suunnitteluun merkittävästi, kun otetaan huomioon niin muuttuvat aluskoot, liikennemäärät ja vaihtelevat jääolosuhteet Suomen merialueella. Selvityksessä hyödynnetään Aalto-yliopiston WINMOS-mallinnusta jäänmurron vaikutusarvion pohjana. Simulaation avulla mallinnetaan jäänmurron tarpeita erilaisissa jääolosuhteissa ottaen huomioon alusten jäissäkulkukyvyn muutokset uusien EEDI-alusten tullessa liikenteeseen. Lisäksi selvitystyössä vertaillaan väylämaksurakenteita eri maissa ja väylämaksujen ohjausvaikutusta kauppalaivaston jäissäkulkuominaisuuksia valittaessa. Mallinnusten perusteella selityksessä arvioidaan talvimerenkulun kustannusten muutosten vaikutuksia merenkulkutaloudelle ja kansataloudelle yleensä. Merenkulun kansainvälisen sääntelyn vaikutukset Suomen merenkulun rakenteeseen, kustannuksiin ja erityisesti talvimerenkulun toteutusedellytyksiin tulevat 2020-luvulla olemaan merkittäviä. Keskeisimpiä, osin hankalasti ennakoitavia sääntelymuutosten vaikutuksia syntyy mm. EEDI- määräysten muutoksista erityisesti ro-ro- ja irtolastialusten aluskannan muutoksiin (mm. asennettu koneteho; rungon koko ja erityisesti leveys mahdollisesti yli 26 m:n aluksiin; keskimääräisen aluskoon kasvu). Selvityksessä on tarkasteltu Suomeen liikennöivän aluskannan kehitystä 2010-luvulla, ja arvioitu sen perusteella, miten aluskanta tulee kehittymään vouteen 2030 mennessä. Mikäli aluskannan kehitys jatkuu samanlaisena vuoteen 2030 saakka, on Suomeen liikennöivä aluskalusto keskimäärin noin 23 % kannattavuudeltaan (DWT) suurempaa kuin vuonna 2017. Olettaen, että muutos aluskoossa on symmetrinen koko aluskalustolle, ja muiden muuttujien pysyessä ennallaan, vuoden 2030 kuljetussuorite kyettäisiin kuljettamaan 13 % nykyistä pienemmällä määrällä aluskäyntejä. Tässä selvityksessä talvimerenkulkua vuonna 2030 mallinnettiin WINMOS-mallinnuksen skenaarioissa, joissa lähtöarvona oli nykyinen jäänmurtajien määrä (9). Tarkastelussa oli myös skenaariot, jossa ns. EEDI-alusten osuus kaikista aluskäynneistä oli 35 %, ja samalla leveydeltään yli 26 m:n alusten määrä oli kasvanut. Talvimerenkulun järjestelmän herkkyyttä muutoksille mallinnettiin simuloimalla tilanteita, joissa jäänmurto toteutetaan nykyistä suuremmilla ja pienemmillä murtajamäärillä. Yhden murtajan lisäyksellä kovan jäätalven viivekustannukset pysyvät nykyisellä tasolla, useammalla lisämurtajalla saavutetaan varsin vähän kustannussäästöjä. Murtajamäärän vähentäminen nykyisestä sen sijaan lisää viivästysten aiheuttamia kustannuksia merkittävästi. Tuloksia tulkittaessa tulee muistaa, että tässä tarkastelussa kuljetusten volyymit pysyivät ennallaan viivästyksistä huolimatta. Todellisuudessa viivästyksillä on kuitenkin merkittävä vaikutus liiketoiminnan kilpailukyvylle. Viivästysten kilpailukykyhaitta vastaa arviolta 0,6–2,1 prosenttia tuotteen arvosta päivää kohden. Viivästysten kasvaessa Suomen ulkomaankauppa menettää vähitellen hintakilpailukykyään, ja täten kaupan volyymi vähenee. Tässä esiteltyjä viivästyskustannuksia voidaankin pitää kustannusten miniminä. Selvityksen tulokset tukevat käsitystä, jonka mukaan merenkulun uusien kansainvälisten sääntelyjen vaikutukset Suomen kauppamerenkulkuun ja logistiikan kustannuksiin ovat merkittäviä. Jäänmurron suorituskyvyllä on merkittävä vaikutus koko logistisen ketjun viiveisiin. Tämän selvityksen päätulos jäänmurron kapasiteetin osalta on, että kapasiteetin nosto ei merkittävästi vähennä viivästyksistä aiheutuvia kustannuksia, mutta kapasiteetin lasku nostaa kustannuksia nopeasti ja merkittävästi

An investigation on the speed dependence of ice resistance using an advanced CFD+DEM approach based on pre-sawn ice tests

Over the past decades, the underlying mechanism of level ice resistance changing with ship speed has not been fully understood, particularly the resistance component due to ship interactions with broken ice pieces. Pre-sawn ice test can negate icebreaking component from the whole resistance of a ship in level ice, providing an effective approach to decompose ship-ice interactions and investigate the speed-dependent resistance from broken ice pieces. This work has built a computational model that can realistically simulate a ship advancing in a pre-sawn ice channel. The model applies Computational Fluid Dynamics (CFD) to solve the flow around an advancing ship, which is coupled with an enhanced Discrete Element Method (DEM) to model pre-sawn ice pieces. Model-scale experiments have also been conducted at the Aalto Ice Tank to validate the simulations, which shows the computational model can provide a reasonable estimation of the pre-sawn ice's resistance and movement around the ship. Upon validation, the dependence of ice resistance on ship speed was analysed. The simulations enable underwater monitoring of the ice motions, indicating that the speed dependence results from the mass of ice submerged underneath the ship and the displacement of broken ice induced by the ship. The identified relationships are more complex than the widely-used assumption that ice resistance linearly changes with ship speed in all cases, which provides a deeper understanding of ice resistance. As such, the findings from this study can potentially facilitate improvements in relevant empirical equations, useful for ship design, operational strategies and maritime management in polar regions

On reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach

Analyzing the reliability of autonomous ships has recently attracted attention mainly due to epistemic uncertainty (lack of knowledge) integrated with automatic operations in the maritime sector. The advent of new random failures with unrecognized failure patterns in autonomous ship operations requires a comprehensive reliability assessment specifically aiming at estimating the time in which the ship can be trusted to be left unattended. While the reliability concept is touched upon well through the literature, the operational trustworthiness needs more elaboration to be established for system safety, especially within the maritime sector. Accordingly, in this paper, a probabilistic approach has been established to estimate the trusted operational time of the ship machinery system through different autonomy degrees. The uncertainty associated with ship operation has been quantified using Markov Chain Monte-Carlo simulation from likelihood function in Bayesian inference. To verify the developed framework, a practical example of a machinery plant used in typical short sea merchant ships is taken into account. This study can be exploited by asset managers to estimate the time in which the ship can be left unattended. Keywords: reliability estimation, Bayesian inference, autonomous ship, uncertainty.</p