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This study has a scope limited to a specific course and changes integrated to the core of the KTH naval architecture master program. The students in the program have earlier experience from engineering applications in a general sustainability perspective and understand the basic concepts within sustainability. Therefore, to introduce further steps a new course module was introduced in 2018 focusing on safety management and social sustainability. The purpose of this study is to identify and document the pedagogic lessons for a course module where sustainable development (SD) is discipline-specific.

This study is a case study that qualitatively investigates the stainability effects of the implementation of the new course module. The course and program activities are compared to the results of a previous study in 2017 on the sustainable development learning elements (SDLEs) in the program and discussed in relation to more general SD initiatives.

From the analysis, it is identified that the perspectives presented were new to a substantial part of the students. This study also shows that the effects of the specific module here studied, with a focus on the skill of maritime social sustainability development, differ from more general sustainability literacy. The new perspective affected the thinking about the core of the students’ studies, ship design, in a way that general knowledge on sustainability has not. This was achieved with a combination of suitable tools and perspectives in combination with contextual knowledge and a frame of reference. The contextual knowledge and a frame of reference are here present in education as a result of relating the sustainability case to the core of the program.

The result relates the pedagogical change described to SDLEs and to the ambition of conceive, design, implement and operate approaches. This paper contributes to the literature by providing a discussion on how social sustainability can be implemented in engineering education and the role of integrated discipline-specific sustainability modules.

In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.

In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.

In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.

In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.

The aim of this study is to provide a holistic analysis of all possible maritime business logistics processes related to import and export shipments in a fuzzy environment through a case study of a maritime logistics company based on the as-is and to-be models within business process management (BPM).

The analyses considered the following perspectives: (i) in the stage of the process identification, the definition of the problem was carried out; (ii) in the stage of the process discovery, ocean department was divided into ocean export/import operation departments; ocean export/import operation were divided into freight collect/prepaid operation processes; ocean export/import logistics activity groups were broken down into sub-activities for freight collect/prepaid operation; the logistics activity groups and their sub-activities were defined; each sub-activity as either operation or documentation process group was classified; the durations of sub-activities were evaluated by decision-makers (DMs) as fuzzy sets (FSs); the monthly total jobs activities were estimated by DMs as FSs; the applied to monthly jobs activities of total shipments were estimated by DMs as FSs; the durations of each sub-activities were aggregated; the duration of the logistics activity groups and the sub-activities for per job were calculated; the cumulative workload of logistics activity groups and sub-activities were calculated; the duration of sub-activities for per job as operation or documentation departments were calculated, (iii) in the stage of the process analysis, cumulative ocean export/import workload as operation or documentation for freight collect/prepaid were calculated; duration of activity groups and sub-activities for per job as operation or documentation were calculated; cumulative workload activity groups and sub-activities as operation or documentation were calculated, (iv) in the stage of the process redesign, cumulative workload, process cycle time as operation and documentation group and required labor force were calculated; the process cycle time of the theoretical, the as-is model and the to-be model were calculated: (i) the theoretical minimum process cycle time without resource were calculated by the critical path method (CPM), (ii) the process cycle time of the as-is model perspective with the 1 person resource constraint and (iii) the process cycle time of the to-be model perspective with the 2-person resource constraint were calculated by the resource constrained project scheduling problem (RCPSP) method.

The methodology for analyzing the ocean department operation process was successfully implemented in a real-life case study. It is observed that the results of the to-be model can be applicable for the company. The BPM-proposed methodology is applicable for the maritime logistics industry in the present study; however, it can be applied to other companies in maritime logistics as well as other industries.

This study contributes to research using BPM methodology in maritime logistics. This is the first study the logistics process analyses were carried out in terms of including all operation processes for a company. All processes were analyzed by using BPM methodology in maritime logistics. This study demonstrated the application of the BPM as-is and to-be models to maritime logistics. The as-is and the to-be models of the BPM methodology were applied in maritime logistics.

This methodology applied in this study can enable organizations operating in the time-urgent maritime logistics sector to manage their logistics processes more efficiently, increase customer satisfaction, reduce the risks of customer loss due to poor operational performance and increase profits in the long term. Through the use of these methodologies utilizing FSs, the CPM and the RCPSP methods, this study is expected to make contributions to the BPM literature and provide original insights into the field. Furthermore, this study will undertake a comprehensive analysis of maritime logistics with respect to BPM to deliver noteworthy contributions to the maritime logistics literature and provide original perspectives into the field.

Defining building information modelling (BIM) standards for the infrastructure domain is a central issue to the successful implementation of BIM in civil engineering domains. To this end, this paper aims to present a requirements and process analysis for the ports and waterways domain to address the lack of BIM standards development, using the information delivery manual (IDM) approach and the ethos of openBIM standards.

This research uses the IDM approach. This involves the definition of use cases, process maps, exchange scenarios and subsequent exchange requirements. All these developments were sourced and validated by a series of international industry consultations.

The paper identifies 30 domain relevant use cases collated from existing sources and new cases. An overview and detailed ports and waterways process map (defining actors, activities and data exchanges). The process maps highlighted 38 exchange scenarios between various activities. Various exchange requirements were defined and are discussed in the context of the required information exchange model and the extensions required to fulfil the needs of the domain. The analysis provides the core information for the next steps of development for a substantial extension to the Industry Foundation Classes and the supporting data dictionary standards.

Because of the international scope of the research, the outcomes can be applied by any stakeholders in the domain of ports and waterways. Therefore, some variation is expected at a national and organizational level. This research has the potential to accelerate the adoption of openBIM standards within the ports and waterways domain leading to increases in efficiency, collaborative working.

This paper reviews the requirements of an identified gap in the provision of openBIM standards relevant and applicable to the domain of ports and waterways.

The maritime industry is the transport mode that contributes most to air pollution. The International Maritime Organization (IMO) identified the reduction of air pollution by ships as a crucial issue. Since 1 January 2020, ships have had to adopt strategies and new technologies to eliminate air pollution. However, ship compliance with nitrate oxide (NOx) emission restrictions is more challenging. This paper aims to identify shipowners' challenges in investing in new technologies.

This paper applied a hybrid methodology combining a survey, a balanced scorecard and fuzzy analytic hierarchy process (F-AHP) to identify and evaluate constraints and weights in investment decision-making for NOx technologies. A survey was carried out to validate constraints.

A survey was carried out, representing 5.1% of Greek-owned ships by deadweight capacity. The findings provide a weighted list of seven crucial technical and economic constraints faced by ship operators. The constraints vary from ship retrofit expenditure to crew training and waste management. Additionally, NOx emission technologies were compared. It was found that liquefied natural gas is the preferred investment option for the survey participants compared with selective catalytic reduction, exhaust gas recirculation and batteries.

Several studies have dealt with the individual technical feasibility of NOx reduction technologies. However, apart from technical feasibility for a shipowner, the selection of a NOx technology has several managerial and safety risks. Therefore, the originality of this paper is to reveal those constraints that have a higher weight on shipowners. With this cost-benefit approach, investment challenges for ship operators are revealed. Policymakers can benefit from the results of the employed methodology.

As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.

This study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.

First, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.

The scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.

We identify and further aggregate the most commonly engaged risk factors in dry port projects into dimensions. Noting the importance of developing a multi-perspective view of risk, we further assess the priority, interdependency and heterogeneity of the identified risk dimensions.

We identified 44 risk factors from the literature, which were aggregated via exploratory factor analysis (EFA) into 8 major risk dimensions. We employ a fuzzy-based decision-making trial and evaluation laboratory (DEMATEL) relationship map to articulate various relationships among the risk dimensions.

“Cost” emerged as the most important risk influencing the success of the dry port project, followed by “location,” “accessibility,” “infrastructural” and “operational,” which were also ranked prominently.

This study offers significant insight into the management of risk in dry port projects. By aggregating key risk factors into distinct dimensions, we develop a structured framework for effective risk assessment and management. The insights gleaned from the study extend globally, as it serves as a concrete knowledge base to understand potential barriers to successful dry port projects.

To provide valuable information for scholars to grasp the current situations, hotspots and future development trends of reliability analysis area.

In this paper, recent researches on efficient reliability analysis and applications in complex engineering structures like aeroengine rotor systems are reviewd.

The recent reliability analysis advances of engineering application in aeroengine rotor system are highlighted, it is worth pointing out that the surrogate model methods hold great efficiency and accuracy advantages in the complex reliability analysis of aeroengine rotor system, since its strong computing power can effectively reduce the analysis time consumption and accelerate the development procedures of aeroengine. Moreover, considering the multi-objective, multi-disciplinary, high-dimensionality and time-varying problems are the common problems in various complex engineering fields, the surrogate model methods and its developed methods also have broad application prospects in the future.

For the strong demand for efficient reliability design technique, this review paper may help to highlights the benefits of reliability analysis methods not only in academia but also in practical engineering application like aeroengine rotor system.

The purpose of this paper is to present a comprehensive analysis of the carbon footprint of the Delft University of Technology (TU Delft), including direct and indirect emissions from utilities, logistics and purchases, as well as a discussion about the commonly used method. Emissions are presented in three scopes (scope 1 reports direct process emissions, scope 2 reports emissions from purchased energy and scope 3 reports indirect emissions from the value chain) to identify carbon emission hotspots within the university’s operations.

The carbon footprint was calculated using physical and monetary activity data, applying a process and economic input-output analysis.

TU Delft’s total carbon footprint in 2018 is calculated at 106 ktCO₂eq. About 80% are indirect (scope 3) emissions, which is in line with other studies. Emissions from Real estate and construction, Natural gas, Equipment, ICT and Facility services accounted for about 64% of the total footprint, whereas Electricity, Water and waste-related carbon emissions were negligible. These findings highlight the need to reduce universities’ supply chain emissions.

A better understanding of carbon footprint hotspots can facilitate strategies to reduce emissions and finally achieve carbon neutrality. In contrast to other work, it is argued that using economic input-output models to calculate universities’ carbon footprints is a questionable practice, as they can provide only an initial estimation. Therefore, the development of better-suited methods is called for.

Scholars mainly propose and establish theoretical models of cumulative fatigue damage for their research fields. This review aims to select the applicable model from many fatigue damage models according to the actual situation. However, relatively few models can be generally accepted and widely used.

This review introduces the development of cumulative damage theory. Then, several typical models are selected from linear and nonlinear cumulative damage models to perform data analyses and obtain the fatigue life for the metal.

Considering the energy law and strength degradation, the nonlinear fatigue cumulative damage model can better reflect the fatigue damage under constant and multi-stage variable amplitude loading. In the following research, the complex uncertainty of the model in the fatigue damage process can be considered, as well as the combination of advanced machine learning techniques to reduce the prediction error.

This review compares the advantages and disadvantages of various mainstream cumulative damage research methods. It provides a reference for further research into the theories of cumulative fatigue damage.