rss_2.0Polish Maritime Research FeedSciendo RSS Feed for Polish Maritime Researchhttps://sciendo.com/journal/POMRhttps://www.sciendo.comPolish Maritime Research Feedhttps://sciendo-parsed.s3.eu-central-1.amazonaws.com/660704dd1ae47050093cdc70/cover-image.jpghttps://sciendo.com/journal/POMR140216Roll Prediction and Parameter Identification of Marine Vessels Under Unknown Ocean Disturbanceshttps://sciendo.com/article/10.2478/pomr-2024-0001<abstract><title style='display:none'>Abstract</title> <p>This paper deals with two topics: roll predictions of marine vessels with machine-learning methods and parameter estimation of unknown ocean disturbances when the amplitude, frequency, offset, and phase are difficult to estimate. This paper aims to prevent the risky roll motions of marine vessels exposed to harsh circumstances. First of all, this study demonstrates complex dynamic phenomena by utilising a bifurcation diagram, Lyapunov exponents, and a Poincare section. Without any observers, an adaptive identification applies these four parameters to the globally exponential convergence using linear second-order filters and parameter estimation errors. Then, a backstepping controller is employed to make an exponential convergence of the state variables to zero. Finally, this work presents the prediction of roll motion using reservoir computing (RC). As a result, the RC process shows good performance for chaotic time series prediction in future states. Thus, the poor predictability of Lyapunov exponents may be overcome to a certain extent, with the help of machine learning. Numerical simulations validate the dynamic behaviour and the efficacy of the proposed scheme.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00012024-03-29T00:00:00.000+00:00Analytical and Experimental Investigation of Asymmetric Floating Phenomena of Uniform Bodieshttps://sciendo.com/article/10.2478/pomr-2024-0002<abstract><title style='display:none'>Abstract</title> <p>Uniform symmetric bodies can be observed floating asymmetrically under certain circumstances. Previous explanations of this are mostly abstract and lack experimental verification, making their understanding and application difficult. This article presents in detail alternative insights into the floating equilibria of uniform prisms and parabolic cylinders. The intrinsic characteristics of the equilibrium curves are investigated, and several equilibria different from those in the literature are found. The inflection points in the equilibrium curves are analyzed quantitatively due to their significance for floating states. Furthermore, experiments have been conducted for the square prism which validate the derived equilibrium curve, and provide a practical impression of the asymmetric floating phenomenon of symmetric bodies. These results have the potential to be applied in naval and ocean engineering, such as in the design of vessels and floating offshore structures.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00022024-03-29T00:00:00.000+00:00Analysis and Experimental Verification of Improving the EEDI of a Ship using a Thruster Supplied by a Hybrid Power Systemhttps://sciendo.com/article/10.2478/pomr-2024-0005<abstract><title style='display:none'>Abstract</title> <p>In this study, the authors present a theoretical analysis and experimentally verified methods to improve the Energy Efficiency Design Index (EEDI) of ships. The improvements were studied via the application of an innovative solution of a thruster supplied by a hybrid power system on board a passenger-car ferry. The authors performed sea trials of a ship’s electrical power system supplied by battery packs with diesel generating set power units. The experimental study focused on energy balance and management, which were considered together with related power quality issues. The authors found that the application of an energy storage system to the ferry, such as batteries, with the simultaneous adaption of the operation modes of the electrical power system for current exploitation, significantly improved energy efficiency. Fuel consumption and CO<sub>2</sub> emission were reduced, while adequate parameters of electrical power quality were maintained to meet classification standards.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00052024-03-29T00:00:00.000+00:00Practical Finite-Time Event-Triggered Control of Underactuated Surface Vessels in Presence of False Data Injection Attackshttps://sciendo.com/article/10.2478/pomr-2024-0012<abstract><title style='display:none'>Abstract</title> <p>The results of studies on a trajectory-tracking problem affected by false data injection attacks (FDIAs) and internal and external uncertainties are presented in this paper. In view of the FDIAs experienced by the system, we compensate for the serious navigation deviation caused by malicious attacks by designing an online approximator. Next, we study the internal and external uncertainties introduced by environmental factors, system parameter fluctuations, or sensor errors, and we design adaptive laws for these uncertainties to approximate their upper bounds. To further enhance the response velocity and stability of the system, we introduce finite-time technology to ensure that the unmanned underactuated surface vessels (USVs) reach the predetermined trajectory-tracking target within finite time. To further reduce the update frequency of the controller, we introduced event-triggered control (ETC) technology. This saves the system’s communication resources and optimizes the system. Through Lyapunov stability theory, a strict and complete stability analysis is provided for the control scheme. Finally, the effectiveness of the control scheme is verified using two sets of simulations.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00122024-03-29T00:00:00.000+00:00Effects on of Blended Biodiesel and Heavy Oil on Engine Combustion and Black Carbon Emissions of a Low-Speed Two-Stroke Enginehttps://sciendo.com/article/10.2478/pomr-2024-0010<abstract><title style='display:none'>Abstract</title> <p>The effects of heavy fuel oil and biodiesel blends on engine combustion and emissions were studied in a marine two-stroke diesel engine. The engine was operated under propeller conditions using five different fuels with biodiesel blends of 10% (B10), 30% (B30), 50% (B50), and sulphur contents of 0.467% low sulphur fuel oil (LSFO) and 2.9% high sulphur fuel oil (HSFO). Tests have shown that using a biodiesel blend increases the engine fuel consumption due to its lower calorific value. Heavy fuel oil has a high Polycyclic aromatic hydrocarbons (PAH) content, which leads to higher exhaust temperatures due to severe afterburning in the engine. A comparison of engine soot emissions under different fuel conditions was carried out, and it was found that the oxygen content in biodiesel promoted the oxidation of soot particles during the combustion process, which reduced the soot emissions of biodiesel. Compared to HSFO, B10, B30, B50 and LSFO, the soot emission concentrations were reduced by 50.2%, 56.4%, 61% and 37.4%, respectively. In our experiments, the soot particles in the engine exhaust were sampled with a thermal float probe. Using Raman spectroscopy analysis, it was found that as the biodiesel ratio increased, the degree of carbonisation of the soot particles in the exhaust became less than that in the oxygenation process, resulting in a decrease in the degree of graphitisation.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00102024-03-29T00:00:00.000+00:00Hydrodynamic Loads on a Semi-Submersible Platform Supporting a Wind Turbine Under a Mooring System With Buoyshttps://sciendo.com/article/10.2478/pomr-2024-0003<abstract><title style='display:none'>Abstract</title> <p>In this study, the effect of a 10MW DTU wind turbine (WT) on a semi-submersible platform is examined from the point of view of its dynamic behaviour as part of a mooring system with attached buoys. The platform has a rectangular geometry, and consists of four offset and one main cylindrical members. The structure is assumed to receive both wave and wind loading simultaneously. A coupled analysis within the frequency domain is performed using two boundary element method software packages, NEMOH and HAMS. The results are presented in the form of parametric graphs for each of the software packages used and for varying wave directions. The graphs show the hydrodynamic loads exerted on the platform, the wave elevation, the added masses, the hydrodynamic damping coefficients, the mooring line tensions, and the Response Amplitude Operators (RAOs) for the motion of the platform.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00032024-03-29T00:00:00.000+00:00Re-Identifying Naval Vessels Using Novel Convolutional Dynamic Alignment Networks Algorithmhttps://sciendo.com/article/10.2478/pomr-2024-0007<abstract><title style='display:none'>Abstract</title> <p>Technological innovation for re-identifying maritime vessels plays a crucial role in both smart shipping technologies and the pictorial observation tasks necessary for marine recon- naissance. Vessels are vulnerable to varying gradations of engaging in the marine environment, which is complicated and dynamic compared to the conditions on land. Fewer picture samples along with considerable similarity are characteristics of warships as a class of ship, making it more challenging to recover the identities of warships at sea. Consequently, a convolutional dynamic alignment network (CoDA-Net) re-identification framework is proposed in this research. To help the network understand the warships within the desired domain and increase its ability to identify warships, a variety of ships are employed as origin information. Simulating and testing the winning of war vessels at sea helps to increase the network’s ability to recognize complexity so that users can better handle the effects of challenging maritime environments. The impact of various types of ships as transfer items is also highlighted. The research results demonstrate that the enhanced algorithm increases the overall first hit rate (Rank1) by approximately 5.9%; it also increases the mean average accuracy (mAP) by approximately 10.7% and the correlation coefficient by 0.997%.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00072024-03-29T00:00:00.000+00:00Fault Diagnosis of Imbalance and Misalignment in Rotor-Bearing Systems Using Deep Learninghttps://sciendo.com/article/10.2478/pomr-2024-0011<abstract><title style='display:none'>Abstract</title> <p>Rotor-bearing systems are important components of rotating machinery and transmission systems, and imbalance and misalignment are inevitable in such systems. At present, the main challenges faced by state-of-the-art fault diagnosis methods involve the extraction of fault features under strong background noise and the classification of different fault modes. In this paper, a fault diagnosis method based on an improved deep residual shrinkage network (IDRSN) is proposed with the aim of achieving end-to-end fault diagnosis of a rotor-bearing system. First, a method called wavelet threshold denoising and variational mode decomposition (WTD-VMD) is proposed, which can process original noisy signals into intrinsic mode functions (IMFs) with a salient feature. These one-dimensional IMFs are then transformed into two-dimensional images using a Gramian angular field (GAF) to give datasets for the deep residual shrinkage network (DRSN), which can achieve high levels of accuracy under strong background noise. Finally, a comprehensive test platform for a rotor-bearing system is built to verify the effectiveness of the proposed method in the field. The true test accuracy of the model at a 95% confidence interval is found to range from 84.09% to 86.51%. The proposed model exhibits good robustness when dealing with noisy samples and gives the best classification results for fault diagnosis under misalignment, with a test accuracy of 100%. It also achieves a higher testing accuracy compared to fault diagnosis methods based on convolutional neural networks and deep residual networks without improvement. In summary, IDRSN has significant value for deep learning engineering applications involving the fault diagnosis of rotor-bearing systems.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00112024-03-29T00:00:00.000+00:00Automatic Classification of Unexploded Ordnance (UXO) Based on Deep Learning Neural Networks (DLNNS)https://sciendo.com/article/10.2478/pomr-2024-0008<abstract><title style='display:none'>Abstract</title> <p>This article discusses the use of a deep learning neural network (DLNN) as a tool to improve maritime safety by classifying the potential threat to shipping posed by unexploded ordnance (UXO) objects. Unexploded ordnance poses a huge threat to maritime users, which is why navies and non-governmental organisations (NGOs) around the world are using dedicated advanced technologies to counter this threat. The measures taken by navies include mine countermeasure units (MCMVs) and mine-hunting technology, which relies on the use of sonar imagery to detect and classify dangerous objects. The modern mine-hunting technique is generally divided into three stages: detection and classification, identification, and neutralisation/disposal. The detection and classification stage is usually carried out using sonar mounted on the hull of a ship or on an underwater vehicle. There is now a strong trend to intensify the use of more advanced technologies, such as synthetic aperture sonar (SAS) for high-resolution data collection. Once the sonar data has been collected, military personnel examine the images of the seabed to detect targets and classify them as mine-like objects (MILCO) or non mine-like objects (NON-MILCO). Computer-aided detection (CAD), computer-aided classification (CAC) and automatic target recognition (ATR) algorithms have been introduced to reduce the burden on the technical operator and reduce post-mission analysis time. This article describes a target classification solution using a DLNN-based approach that can significantly reduce the time required for post-mission data analysis during underwater reconnaissance operations.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00082024-03-29T00:00:00.000+00:00Universal Sea/Fem Based Method for Estimation of Vibroacoustic Coupling Loss Factors in Realistic Ship Structureshttps://sciendo.com/article/10.2478/pomr-2024-0006<abstract><title style='display:none'>Abstract</title> <p>Despite the fact that there is an existing body of literature addressing the computation of Coupling Loss Factors (CLFs) via the Finite Element Method (FEM), no publications have sufficiently taken into account real structural joints in their approach. Previous research has focused on academic cases of trivial connections, rarely involving more than two steel plates. To enable Statistical Energy Analysis (SEA) on a real ship, a methodology for determining CLFs for non-trivial systems is proposed, considering realistic boundary conditions and irregularities that can occur in marine structures. Based on the method, a library of CLFs is created by selecting the tested connections to enable modelling of about 90% of the acoustic paths on an existing jack-up vessel. Boundary conditions were set by introducing spring elements with a stiffness calibrated to the type of connection and taking the adjacent structure into account. In previous works, CLFs were determined for basic connections of rectangular plates. The lack of scantling variations, ignoring discontinuities and only defining parallel edges in the considered models, lead to the overestimation of energy transmission in real structures. To consider the influence of the above, random deviations from the initial stiffness of the springs at individual edges and point restraints at random points are introduced in this paper.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00062024-03-29T00:00:00.000+00:00Environmental Marine Degradation of PLA/Wood Composite as an Alternative Sustainable Boat Building Materialhttps://sciendo.com/article/10.2478/pomr-2024-0013<abstract><title style='display:none'>Abstract</title> <p>IIn this study, which can be considered a contribution to the global effort to produce sustainable materials and to search new manufacturing methods for the boat building industry, the performance of a 3D printable polylactic acid and recycled wood (PLAW) composite was investigated under the simulated operational conditions of a boat. The wood used in the composite was yellow pine (Pinus sylvestris), a local wood widely used in boat building and 8% by weight in the composite. For the study, tensile and compressive strength tests were performed in both atmospheric and post-aging conditions, using composite samples produced by the additive manufacturing method. The durations of the accelerated aging before the experiments were one, two and four weeks. During these aging periods, water spraying, a salty fog environment and a drying cycle were applied at elevated temperatures and at equal time intervals, daily. The effect of wood additive on the composite and the joining efficiency of the components were also examined with scanning and optical microscopes. The performance of the obtained composite and the effects of aging on performance were measured using two different thermal analyses: differential scanning calorimetry and thermogravimetric analysis. From the results obtained, it can be seen that PLAW composite can be used in the manufacture of structural elements subjected to relatively low loads in boats. It is an option that will provide integrity in the future interior design of wooden boats.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00132024-03-29T00:00:00.000+00:00Approximate Estimation of Man-Day in Ship Block Production: A Two-Stage Stochastic Programhttps://sciendo.com/article/10.2478/pomr-2024-0015<abstract><title style='display:none'>Abstract</title> <p>It is critical to estimate the workforce requirements for the production of blocks in shipbuilding. In this study, the number of workforce (man-day) required for the production of a passenger ship’s double bottom block was estimated. Initially, the production of the block was observed, and the average working performance of the mounting, welding, and grinding workers was recorded. Block drawings were examined and the work required was calculated. The amount of work increased, depending on any revisions required due to incorrect or incomplete designs. The average working performance of an employee is uncertain due to environmental factors, including the weather and working conditions, as well as health (both physical and mental). A two-stage stochastic programming model with recourse was established to estimate man-day required and a Sample Average Approximation (SAA) technique was used to obtain a near-optimum solution. The results of the study were compared with shipyard records and an agreement of approximately 90% was achieved.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00152024-03-29T00:00:00.000+00:00Blockchain-Enabled Transfer Learning for Vulnerability Detection and Mitigation in Maritime Logisticshttps://sciendo.com/article/10.2478/pomr-2024-0014<abstract><title style='display:none'>Abstract</title> <p>With the increasing demand for efficient maritime logistic management, industries are striving to develop automation software. However, collecting data for analytics from diverse sources like shipping routes, weather conditions, historical incidents, and cargo specifications has become a challenging task in the distribution environment. This challenge gives rise to the possibility of faulty products and traditional testing techniques fall short of achieving optimal performance. To address this issue, we propose a novel decentralised software system based on Transfer Learning and blockchain technology named as BETL (Blockchain -Enabled Transfer Learning). Our proposed system aims to automatically detect and prevent vulnerabilities in maritime operational data by harnessing the power of transfer learning and smart contract-driven blockchain. The vulnerability detection process is automated and does not rely on manually written rules. We introduce a non-vulnerability score range map for the effective classification of operational factors. Additionally, to ensure efficient storage over the blockchain, we integrate an InterPlanetary File System (IPFS). To demonstrate the effectiveness of transfer learning and blockchain integration for secure logistic management, we conduct a testbed-based experiment. The results show that this approach can achieve high precision (98.00%), detection rate (98.98%), accuracy (97.90%), and F-score (98.98), which highlights its benefits in enhancing the safety and reliability of maritime logistics processes. Additionally, the computational time of BETL (the proposed approach) was improved by 18.9% compared to standard transfer learning.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00142024-03-29T00:00:00.000+00:00Investigating Fuel Injection Strategies to Enhance Ship Energy Efficiency in Wave Conditionshttps://sciendo.com/article/10.2478/pomr-2024-0009<abstract><title style='display:none'>Abstract</title> <p>The prediction of fuel consumption and resulting transportation costs is a crucial stage in ship design, particularly for conditions involving motion in waves. This study investigates the real-time fuel consumption of a container ship when sailing in waves. The overall ship performance is evaluated using a novel non-linear coupled hull-engine-propeller interaction model. A series of towing tank experiments for hull resistance in waves and propeller performance are conducted. The ship engine is mathematically modelled by a quasi-steady-state model equipped with a linear Proportional-Integrator (PI) governor. Various scenarios of shipping transportation are studied, and the resulting instantaneous fuel consumptions and their correlation to other dynamic particulars are demonstrated. Additionally, daily fuel consumption and fuel cost per voyage distance are presented. It is also shown that the controller can effectively adjust the fuel rate, resulting in minimum fuel consumption. The study concludes that there is no correlation between fuel consumption and the frequency of fuel rates. The present framework and mathematical model can also be employed for ship design and existing ships to predict the total required energy per voyage.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00092024-03-29T00:00:00.000+00:00Study of the Hydrodynamic Characteristics of Anti-Heave Devices of Wind Turbine Platforms at Different Water Depthshttps://sciendo.com/article/10.2478/pomr-2024-0004<abstract><title style='display:none'>Abstract</title> <p>This paper focuses on the effect of water depth on the hydrodynamics of floating offshore wind turbines with open-hole anti-heave devices. The three-floating-body wind turbine platform is used as the primary research object in this paper. The effect of water depth on the reduction of the heave motion of a floating platform with anti-heave devices is systematically investigated through a series of experiments and numerical simulations. The results show high agreement between the test results and simulations, with larger values of heave motion in deep water. A wind turbine platform with anti-heave devices can effectively reduce the lifting and sinking motions when the wave period is large.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2024-00042024-03-29T00:00:00.000+00:00Optimal UV Quantity for a Ballast Water Treatment System for Compliance with Imo Standardshttps://sciendo.com/article/10.2478/pomr-2023-0056<abstract> <title style='display:none'>Abstract</title> <p>Ballast water management is an effective measure to ensure that organisms, bacteria and viruses do not migrate with the ballast water to other areas. In 2004, the International Maritime Organization adopted the International Convention on the Control and Management of Ballast Water and Ship Sediments, which regulates issues related to ballast water management. Many technologies have been researched and developed, and of these, the use of UV rays in combination with filter membranes has been shown to have many advantages and to meet the requirements of the Convention. However, the use of UV furnaces in ballast water treatment systems requires a very large capacity, involving the use of many high-power UV lamps. This not only consumes large amounts of electrical energy, but is also expensive. It is therefore necessary to find an optimal algorithm to enable the UV radiation for the UV controller in the ballast water sterilisation process to be controlled in a reasonable and effective manner. This controller helps to prolong the life of the UV lamp, reduce power consumption and ensure effective sterilisation. This paper presents a UV control algorithm and a controller for a UV furnace for a ballast water treatment system installed on a ship. The results of tests on vessels illustrate the effect of the proposed UV controller.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2023-00562023-12-11T00:00:00.000+00:00Exploration of a Model Thermoacoustic Turbogenerator with a Bidirectional Turbinehttps://sciendo.com/article/10.2478/pomr-2023-0063<abstract> <title style='display:none'>Abstract</title> <p>The utilisation of the thermal emissions of modern ship power plants requires the development and implementation of essentially new methods of using low-temperature waste heat. Thermoacoustic technologies are able to effectively use low-temperature and cryogenic heat resources with a potential difference of 500–111 K. Thermoacoustic heat machines (TAHMs) are characterised by high reliability, simplicity and environmental safety. The wide implementation of thermoacoustic energy-saving systems is hampered by the low specific power and the difficulties of directly producing mechanical work. An efficient approach to converting acoustic energy into mechanical work entails the utilisation of axial pulse bidirectional turbines within thermoacoustic heat engines. These thermoacoustic turbogenerators represent comprehensive systems that consist of thermoacoustic primary movers with an electric generator actuated by an axial-pulse bidirectional turbine. The development of such a thermoacoustic turbogenerator requires several fundamental issues to be solved. For this purpose, a suitable experimental setup and a 3D computational fluid dynamics (CFD) model of a thermoacoustic engine (TAE) with bidirectional turbines were created. The research program involved conducting physical experiments and the CFD modelling of processes in a TAE resonator with an installed bidirectional turbine. The boundary and initial conditions for CFD calculations were based on empirical data. The adequacy of the developed numerical model was substantiated by the results of physical experiments. The CFD results showed that the most significant energy losses in bidirectional turbines are manifested in the output grid of the turbine.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2023-00632023-12-11T00:00:00.000+00:00Transfer Function for a Controllable Pitch Propeller with Added Water Masshttps://sciendo.com/article/10.2478/pomr-2023-0060<abstract> <title style='display:none'>Abstract</title> <p>The relevance of this study lies in the fact that it presents a mathematical model of the dynamics of the propulsion system of a ship that takes into consideration the mass of water added to it. The influence of this phenomenon on the resonant frequencies of the propeller shaft is examined, and a transfer function for a controllable-pitch propeller is obtained for various operating modes. The purpose of the study is to improve the calculation of the dynamic operating modes of a controllable-pitch propeller by examining the features of a visual models. The VisSim software package is used in the study. A visual model is developed that considers the influence of the rotational speed on the value of the rotational inertia attached to the variable-pitch screw of the mass of water, and a special transfer function is proposed. The study shows that a transfer function of this type has a loop enabling negative feedback. An analysis of the operation of the propeller shaft at its resonant frequency is conducted based on the application of frequency characteristics using the transfer functions obtained. We show that in the low-frequency region, a consideration of the added rotational inertia using the proposed transfer function leads to a significant difference compared to the result obtained with the existing calculation method.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2023-00602023-12-11T00:00:00.000+00:00Use of the AHP Method for Preference Determination in Yacht Designhttps://sciendo.com/article/10.2478/pomr-2023-0055<abstract> <title style='display:none'>Abstract</title> <p>A sailing yacht is a human-centred product, the design of which revolves primarily around the wants and desires of the future owner. In most cases, these preferences are not measurable, such as a personal aesthetic feeling, or a need for comfort, speed, safety etc. The aims of this paper are to demonstrate that these preferences can be classified and represented numerically, and to show that they are correlated with the type of yacht owned. As a case study, the owner’s preferences for deck equipment are considered. These are determined by pairwise comparisons of the importance rankings for features previously defined by yacht owners, following the analytic hierarchy process (AHP) method. As a result, a quantitative representation of these preferences is established, and they are shown to be correlated with the type of yacht. The findings of the current study show that the yacht owners’ preferences can be represented numerically, leading to a utilitarian conclusion that concerns the support and even some degree of automation of the design process.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2023-00552023-12-11T00:00:00.000+00:00Strategies for Developing Logistics Centres: Technological Trends and Policy Implicationshttps://sciendo.com/article/10.2478/pomr-2023-0066<abstract> <title style='display:none'>Abstract</title> <p>Logistics centres are currently performing a key function in the development of countries through their ability to regulate goods, markets, and transport. This is shown by the infrastructure, cost, goods flow, and quality of logistical services provided by these centres. Nevertheless, in developing nations or regions with antiquated logistics infrastructure, conventional logistics centres seem to struggle to manage the volume of commodities passing through them, resulting in persistent congestion and an unsteady flow of goods inside these facilities. This issue poses a challenge to the progress of any nation. The emergence of new technology offers a potential avenue to solve the problems inherent in traditional logistics centres. Most prominently, four technologies (the Internet of Things (IoT), Blockchain, Big Data and Cloud computing) are widely applied in traditional logistics centres. This work has conducted a thorough analysis and evaluation of these new technologies in relation to their respective functions and roles inside a logistics centre. Furthermore, this work proposes difficulties in applying new technologies to logistics centres related to issues such as science, energy, cost, or staff qualifications. Finally, future development directions, related to expanding policies in technological applications, or combining each country’s policies for the logistics industry, are carefully discussed.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pomr-2023-00662023-12-11T00:00:00.000+00:00en-us-1