Hasil untuk "Naval architecture. Shipbuilding. Marine engineering"

Rui-Zhe Shen, Cheng-Tao Yi, Yu-Nuo Liu et al.

For coastal nations and regions, wave energy provides a localized energy solution, decreasing dependency on external energy sources and fostering the sustainable development of local economies. Effective wave height occurrence (EWHO) represents the availability of wave energy and is a crucial parameter for site selection for optimal wave energy. This paper systematically analyzes the distribution of EWHO in China seas areas using significant wave height (SWH) data in the fifth generation of ECMWF atmospheric reanalysis (ERA5) and key climate indices. Employing methods such as climate statistical analysis, linear regression, significance testing, and trend analysis, the study highlights the temporal and spatial distribution characteristics, variation trends, and correlations with climate indices of EWHO. This research aims to provide technical assistance and decision support for the development of wave energy at sea. The results indicate the following conclusions: (1) The high EWHO in the China seas is predominantly located in northern Nanhai, southern Donghai, and the eastern waters of the Philippine Islands. The EWHO is highest in winter. (2) The growth trend of EWHO is most notable in the sea area east of the line connecting the Ryukyu Islands, Taiwan, and the northeastern Philippines, peaking in spring and being relatively weak in winter. (3) The correlation between NINO3 and EWHO is most significant in Nanhai and the northeastern waters of the Philippines, peaking in February with correlation coefficients ranging from −0.30 to −0.50.

Ștefan Iulian Rață, Anișoara Gabriela Cristea

This study examines both the local and global structural strength of a 3D finite element model (FEM) representing the three cargo holds of a 47600-DWT chemical tanker. Vessels of this type require a detailed assessment of their structural behavior under extreme loading conditions as well as routine operational demands. The analysis of stress distribution and structural strength enables the identification of critical areas within the hull, providing essential insights for enhancing the vessel’s structural integrity and overall performance.

Maria Dymkowska-Malesa, Monika Radzymińska, Beata Erlichowska

Fats, including vegetable oils, are an important component of the diet. They not only have a high energy value, but also contain nutrients that are essential for the proper functioning of the human body. The increasing consumption of fried products affects the consumption of the oils used for a long time in the deep frying processes. Vegetable oils contain large amounts of unsaturated fatty acids, which are subject to oxidative and hydrolytic processes, while thermal polymerization can also occur in them. The aim of the study was to compare the oxidative stability of rapeseed and soybean oils while frying potato chips in them at 180°C. The study presents changes in the acid and peroxide values, as well as changes in the sensory characteristics of the oils under the influence of heating. The studies showed that rapeseed oil was characterized by greater sensitivity to oxidation compared to soybean oil. Soybean oil contained more hydrolysis products, but during the frying process their increase was similar to the products formed in rapeseed oil.

Hyeun-Chul Kim

Marine power systems, including generators and transformers, experience voltage stress at various frequencies. Once the stress exceeds the bearing capacity of the electrical system, it results in insulation breakdown or failure. Therefore, extensive testing is required to ensure that marine electrical insulation systems are reliable. In accordance with International Electrotechnical Commission (IEC) standards, conventional tests at commercial frequencies require over 5000 h, making them time-consuming, inefficient, and practically infeasible. This study explores frequency-based accelerated life testing to reduce the duration of testing. Insulation systems made of mica-based corona-resistant materials and epoxy resin were tested at 60, 300, 600, and 900 Hz using a variable-frequency high-voltage tester. The results show that the time to failure decreases as the frequency increases (from 381.83 h at 60 Hz to 22.33 h at 900 Hz, a 94% reduction). Power and exponential decay models effectively describe this relationship. The power model provides a better overall fit, and the exponential decay model improves the accuracy at higher frequencies. This study confirms that higher frequencies accelerate insulation degradation, shortening test times considerably. Frequency-based accelerated testing can enhance insulation system evaluation and optimize international testing standards.

Justus Bogner, Roberto Verdecchia

From its early foundations in the 1970s, empirical software engineering (ESE) has evolved into a mature research discipline that embraces a plethora of different topics, methodologies, and industrial practices. Despite its remarkable progress, the ESE research field still needs to keep evolving, as new impediments, shortcoming, and technologies emerge. Research reproducibility, limited external validity, subjectivity of reviews, and porting research results to industrial practices are just some examples of the drivers for improvements to ESE research. Additionally, several facets of ESE research are not documented very explicitly, which makes it difficult for newcomers to pick them up. With this new regular ACM SIGSOFT SEN column (SEN-ESE), we introduce a venue for discussing meta-aspects of ESE research, ranging from general topics such as the nature and best practices for replication packages, to more nuanced themes such as statistical methods, interview transcription tools, and publishing interdisciplinary research. Our aim for the column is to be a place where we can regularly spark conversations on ESE topics that might not often be touched upon or are left implicit. Contributions to this column will be grounded in expert interviews, focus groups, surveys, and position pieces, with the goal of encouraging reflection and improvement in how we conduct, communicate, teach, and ultimately improve ESE research. Finally, we invite feedback from the ESE community on challenging, controversial, or underexplored topics, as well as suggestions for voices you would like to hear from. While we cannot promise to act on every idea, we aim to shape this column around the community interests and are grateful for all contributions.

Carlos García A., Vladimiro Boselli, Aida Hejazi Nooghabi et al.

This study introduces the first 3D spectral-element method (SEM) simulation of ultrasonic wave propagation in a bottlenose dolphin (Tursiops truncatus) head. Unlike traditional finite-element methods (FEM), which struggle with high-frequency simulations due to costly linear-system inversions and slower convergence, SEM offers exponential convergence and efficient parallel computation. Using Computed Tomography (CT) scan data, we developed a detailed hexahedral mesh capturing complex anatomical features, such as acoustic fats and jaws. Our simulations of plane and spherical waves confirm SEM's effectiveness for ultrasonic time-domain modeling. This approach opens new avenues for marine biology, contributing to research in echolocation, the impacts of anthropogenic marine noise pollution and the biophysics of hearing and click generation in marine mammals. By overcoming FEM's limitations, SEM provides a powerful scalable tool to test hypotheses about dolphin bioacoustics, with significant implications for conservation and understanding marine mammal auditory systems under increasing environmental challenges.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy plays a critical role in software engineering (SE), influencing collaboration, communication, and user-centred design. Although SE research has increasingly recognised empathy as a key human aspect, there remains no validated instrument specifically designed to measure it within the unique socio-technical contexts of SE. Existing generic empathy scales, while well-established in psychology and healthcare, often rely on language, scenarios, and assumptions that are not meaningful or interpretable for software practitioners. These scales fail to account for the diverse, role-specific, and domain-bound expressions of empathy in SE, such as understanding a non-technical user's frustrations or another practitioner's technical constraints, which differ substantially from empathy in clinical or everyday contexts. To address this gap, we developed and validated two domain-specific empathy scales: EmpathiSEr-P, assessing empathy among practitioners, and EmpathiSEr-U, capturing practitioner empathy towards users. Grounded in a practitioner-informed conceptual framework, the scales encompass three dimensions of empathy: cognitive empathy, affective empathy, and empathic responses. We followed a rigorous, multi-phase methodology, including expert evaluation, cognitive interviews, and two practitioner surveys. The resulting instruments represent the first psychometrically validated empathy scales tailored to SE, offering researchers and practitioners a tool for assessing empathy and designing empathy-enhancing interventions in software teams and user interactions.

Dinesh Eswararaj, Ajay Babu Nellipudi, Vandana Kollati

The automotive industry generates vast amounts of data from sensors, telemetry, diagnostics, and real-time operations. Efficient data engineering is critical to handle challenges of latency, scalability, and consistency. Modern data lakehouse formats Delta Parquet, Apache Iceberg, and Apache Hudi offer features such as ACID transactions, schema enforcement, and real-time ingestion, combining the strengths of data lakes and warehouses to support complex use cases. This study presents a comparative analysis of Delta Parquet, Iceberg, and Hudi using real-world time-series automotive telemetry data with fields such as vehicle ID, timestamp, location, and event metrics. The evaluation considers modeling strategies, partitioning, CDC support, query performance, scalability, data consistency, and ecosystem maturity. Key findings show Delta Parquet provides strong ML readiness and governance, Iceberg delivers high performance for batch analytics and cloud-native workloads, while Hudi is optimized for real-time ingestion and incremental processing. Each format exhibits tradeoffs in query efficiency, time-travel, and update semantics. The study offers insights for selecting or combining formats to support fleet management, predictive maintenance, and route optimization. Using structured datasets and realistic queries, the results provide practical guidance for scaling data pipelines and integrating machine learning models in automotive applications.

Tyler Slater

Context: Large Language Models (LLMs) rely on static, pre-deployment safety mechanisms that cannot adapt to adversarial threats discovered after release. Objective: To design a software architecture enabling LLM-based systems to autonomously detect safety failures and synthesize defense policies at runtime, without retraining or manual intervention. Method: We propose the Self-Improving Safety Framework (SISF), grounded in the MAPE-K reference model. The framework couples a target LLM with a feedback loop: an Adjudicator detects breaches, a Policy Synthesis Module generates dual-mechanism defense policies (heuristic and semantic), and a Warden enforces them. We conducted seven experiments (10,061 evaluations) across four model families. Results: Across five reproducibility trials, SISF achieved a mean Attack Success Rate (ASR) of 0.27% (+/-0.15%), autonomously generating 240 policies per trial. Cross-model evaluation confirmed deployment portability. A held-out test showed a 68.5% proactive interception rate on unseen attacks. Stacked behind Llama Guard 4, the combined defense reduced residual ASR from 7.88% to 0.00%. Ablation confirmed both heuristic and semantic policy types are architecturally required. Conclusion: Self-adaptive architecture is a viable approach to LLM safety. SISF achieves sub-1% ASR through synchronous output monitoring, progressively shifting enforcement to fast, local Warden policies via the MAPE-K loop, offering a new pattern for building resilient AI systems.

Lei Wang, Feng Zhang, Chongwei Zheng et al.

In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

Sayaka Kochiyama, Haneesh Kesari

Intriguing physical phenomena observed in natural materials have inspired the development of several engineering materials with dramatically improved performance. Marine sponge glass fibers, for instance, have attracted interest in recent decades. We tested the glass fibers in tension and observed that the strength of these fibers scales inversely with their size. While it is expected that the strength of a material scales inversely with its size, the scaling is generally believed to be inversely proportional to the square root of the specimen dimension. Interestingly, we found that the marine sponge glass fibers' strength scaled much faster, and was inversely proportional to the square of the specimen dimension. Such non-classical scaling is consistent with the experimental measurements and classical linear elastic fracture mechanics. We hypothesize that this enhanced scaling is due to the flaw size decreasing faster than the size of the specimen. The tensile strength, as a result of non-classical, higher-order scaling, reached a value as large as 1.5 GPa for the smallest diameter specimen. The manufacturing processes through which the spicules are made might hold important lesson for further enhancing the strength of engineering materials.

Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan et al.

Large Language Models (LLMs) are being used for a wide variety of tasks. While they are capable of generating human-like responses, they can also produce undesirable output including potentially harmful information, racist or sexist language, and hallucinations. Alignment methods are designed to reduce such undesirable outputs via techniques such as fine-tuning, prompt engineering, and representation engineering. However, existing methods face several challenges: some require costly fine-tuning for every alignment task; some do not adequately remove undesirable concepts, failing alignment; some remove benign concepts, lowering the linguistic capabilities of LLMs. To address these issues, we propose Parsimonious Concept Engineering (PaCE), a novel activation engineering framework for alignment. First, to sufficiently model the concepts, we construct a large-scale concept dictionary in the activation space, in which each atom corresponds to a semantic concept. Given any alignment task, we instruct a concept partitioner to efficiently annotate the concepts as benign or undesirable. Then, at inference time, we decompose the LLM activations along the concept dictionary via sparse coding, to accurately represent the activations as linear combinations of benign and undesirable components. By removing the latter ones from the activations, we reorient the behavior of the LLM towards the alignment goal. We conduct experiments on tasks such as response detoxification, faithfulness enhancement, and sentiment revising, and show that PaCE achieves state-of-the-art alignment performance while maintaining linguistic capabilities.

Hoyong Kim, Chanil Jeon, Kiwon Kim et al.

The present study suggests a methodology for acquiring wave elevation fields using a depth camera sensor, with assessment results for the test uncertainty. The depth camera module of an Azure Kinect is calibrated using marker arrays on the optic table, to obtain a polynomial mapping function between the pixel-wise and physical position. For installation of the depth camera in a wave channel, the system is aligned using the built-in inertial measurement unit of Azure Kinect to be perpendicular to the calm water surface. The systematic and random standard uncertainties were evaluated from the analysis of calibration and repeated tests, respectively. The wave height measurement results for the depth camera were compared to those for the capacitance-type and ultrasonic wave height gauges. The test uncertainty of the depth camera increased in large wave stiffness conditions, where the time-of-flight sensor has a disadvantage in measurement.

Rahul Chajwa, Eliott Flaum, Kay D. Bidle et al.

Global carbon-cycle on our planet ties together the living and the non-living world, coupling ecosystem function to our climate. Gravity driven downward flux of carbon in our oceans in the form of marine snow, commonly referred to as biological pump directly regulates our climate. Multi-scale nature of this phenomena, biological complexity of the marine snow particles and lack of direct observations of sedimentation fundamentally limits a mechanistic understanding of this downward flux. The absence of a physics based understanding of sedimentation of these multi-phase particles in a spatially and temporally heterogeneous ocean adds significant uncertainty in our carbon flux predictions. Using a newly invented scale-free vertical tracking microscopy, we measure for the first time, the microscopic sedimentation and detailed fluid-structure dynamics of marine snow aggregates in field settings. The microscopically resolved in-situ PIV of large number of field-collected marine snow reveals a comet tail like flow morphology that is universal across a range of hydrodynamic fingerprints. Based on this dataset, we construct a reduced order model of Stokesian sedimentation and viscoelastic distortions of mucus to understand the sinking speeds and tail lengths of marine snow dressed in mucus. We find that the presence of these mucus-tails doubles the mean residence time of marine snow in the upper ocean, reducing overall carbon sequestration due to microbial remineralization. We set forth a theoretical framework within which to understand marine snow sinking flux, paving the way towards a predictive understanding of this crucial transport phenomena in the open ocean.

Eren Kurshan

Artificial intelligence (AI) faces a trifecta of grand challenges: the Energy Wall, the Alignment Problem and the Leap from Narrow AI to AGI. We present SAGI, a Systematic Approach to AGI that utilizes system design principles to overcome the energy wall and alignment challenges. This paper asserts that AGI can be realized through multiplicity of design specific pathways and customized through system design rather than a singular overarching architecture. AGI systems may exhibit diver architectural configurations and capabilities, contingent upon their intended use cases. Alignment, a challenge broadly recognized as AIs most formidable, is the one that depends most critically on system design and serves as its primary driving force as a foundational criterion for AGI. Capturing the complexities of human morality for alignment requires architectural support to represent the intricacies of moral decision-making and the pervasive ethical processing at every level, with performance reliability exceeding that of human moral judgment. Hence, requiring a more robust architecture towards safety and alignment goals, without replicating or resembling the human brain. We argue that system design (such as feedback loops, energy and performance optimization) on learning substrates (capable of learning its system architecture) is more fundamental to achieving AGI goals and guarantees, superseding classical symbolic, emergentist and hybrid approaches. Through learning of the system architecture itself, the resulting AGI is not a product of spontaneous emergence but of systematic design and deliberate engineering, with core features, including an integrated moral architecture, deeply embedded within its architecture. The approach aims to guarantee design goals such as alignment, efficiency by self-learning system architecture.

Rudrajit Choudhuri, Dylan Liu, Igor Steinmacher et al.

Conversational Generative AI (convo-genAI) is revolutionizing Software Engineering (SE) as engineers and academics embrace this technology in their work. However, there is a gap in understanding the current potential and pitfalls of this technology, specifically in supporting students in SE tasks. In this work, we evaluate through a between-subjects study (N=22) the effectiveness of ChatGPT, a convo-genAI platform, in assisting students in SE tasks. Our study did not find statistical differences in participants' productivity or self-efficacy when using ChatGPT as compared to traditional resources, but we found significantly increased frustration levels. Our study also revealed 5 distinct faults arising from violations of Human-AI interaction guidelines, which led to 7 different (negative) consequences on participants.

Anna Kroon, Matthieu de Schipper, Sierd de Vries et al.

Sandy nourishments can provide additional sediment to the coastal system to maintain its recreational or safety function under rising sea levels. These nourishments can be implemented at sandy beach systems, but can also be used to reinforce gray coastal infrastructure (e.g., dams, dikes, seawalls). The Hondsbossche Dunes project is a combined shoreface, beach, and dune nourishment of 35 million m<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mn>3</mn></msup></semantics></math></inline-formula> sand. The nourishment was built to replace the flood protection function of an old sea-dike while creating additional space for nature and recreation. This paper presents the evolution of this newly created sandy beach system in the first 5 years after implementation based on bathymetric and topographic surveys, acquired every three to six months. A significant coastline curvature is created by the nourishment leading to erosion in the central 7 km bordered by zones with accretion. However, over the five-year period, net volume losses from the project area were less than 5% of the initial nourished sand volume. The man-made cross-shore beach profile rapidly mimics the characteristics of adjacent beaches. The slope of the surfzone is adjusted within two winters to a similar slope. The initially wide beaches (i.e., up to 225 m) are reduced to about 100 m-wide. Simultaneously, the dune volume has increased and the dune foot migrated seaward at the entire nourished site, regardless of whether the subaqueous profile gained or lost sediment. Our results show that the Hondsbossche Dunes nourishment, built with a natural slope and wide beach, created a positive sediment balance in the dune for a prolonged period after placement. As such, natural forces in the years after implementation provided a significant contribution to the growth in dune volume and related safety against flooding.

XU Chenhui, YU Fanghui, HE Defeng

Considering the state monitoring problem of flexible joint robots (FJRs) caused by the easy deformation in practice, a distributed receding horizon estimation algorithm based on disturbance blocks is proposed. Based on distributed consistent receding horizon estimation, the proposed algorithm reduces the computational amount and achieves rapidity by designing the disturbance block and applying it to the process disturbance sequence in the estimation window to reduce the variables related to optimization. By analyzing the feasibility and convergence of the proposed algorithm based on the maximum block length, the assumptions are made under which the existence of equivalent solution to the optimization problem of the algorithm is guaranteed, and the results are extended to the case that the process disturbance can be divided into arbitrary blocks. The simulation results show that the proposed algorithm can effectively shorten the computation time without affecting the estimation error compared with the algorithm without disturbance blocks.

Tiechao BAI, Jian XU, Lijie ZHENG et al.

ObjectiveThe thermal comfort of a ship's cabin has an important influence on the life and work of the crew. However, it takes a long time to design the air supply parameters using experimental research and the traditional numerical simulation trial method. Therefore, an inverse design method based on proper orthogonal decomposition (POD) is applied to the design of air supply parameters in a typical cabin. MethodIn this paper, a three-dimensional numerical model is established using the computational fluid dynamics (CFD) method. After obtaining the results of the flow field, temperature field and concentration field, combined with the inverse design method based on POD, the optimal thermal comfort and minimum pollutant concentration in the breathing zone of a nine-person cabin are taken as the optimization objectives. ResultsThe results show that the inverse design method based on POD can be used for the inverse optimization of multiple parameters and objectives. Compared with the traditional algorithm, it can save time by more than 90% and greatly improve the design efficiency of the transmission of cabin air supply parameters. ConclusionsThe POD method can be applied to the design of a ship's living quarters. The appropriate range of air supply parameters obtained by reverse design can provide references for the selection of the air supply parameters.

Deniz Öztürk, Kadir Sarıöz

The risks associated with the navigation of large tankers in restricted waterways have resulted in continuing development of routing measures such as Traffic Separation Schemes (TSS). This is generally subject to discussion between the administration and ship operators which may find some navigational rules and regulations unnecessarily restrictive. Motivated by the need for an objective and scientific method to determine the vessel characteristics and environmental conditions for a safe passage through a restricted waterway, this paper presents an optimized routing procedure based on maneuvering simulations and non-linear direct search techniques which can be used to determine the best attainable route for large tankers in restricted waterways and specified environmental conditions. The mathematical model for predicting the maneuvering performance is based on a modular approach in which the hydrodynamic, propeller and rudder forces are computed separately, while environmental forces are estimated by semi-empirical methods. The objective of the optimization procedure is to determine the required number and magnitude of rudder control commands for remaining within a specified TSS and minimizing a grounding or collision possibility.