The marine centrifugal pump is one of the most energy-intensive pieces of equipment in ship auxiliary machinery, and the efficient design of its hydraulic components can effectively reduce the total energy consumption of the ship system. Aiming at the complex three-dimensional twisted blade profile structure of the marine centrifugal pump, this paper optimized the clonal selection algorithm and constructed an automatic hydraulic optimization design method for the high-efficiency centrifugal pump impeller. Considering the multi-condition operation characteristics of the marine centrifugal pump, a performance test platform for the marine centrifugal pump was built, and the actual operating conditions of the model pump were tested to obtain its performance characteristics under operating conditions. The numerical simulation method was employed to capture and analyze the internal flow field and flow characteristics of the model pump. Addressing the design challenges of the marine centrifugal pump impeller, which involve multiple parameters with significant interactions, a traditional clonal selection algorithm was enhanced using a Slime Mold Algorithm, and a hybrid Clonal Selection Algorithm integrated with Slime Mold and Tangent Flight mechanisms was established. Based on the MATLAB and ANSYS platforms, an automated hydraulic optimization design framework for the centrifugal pump impeller was established. Using the optimized clonal selection algorithm, with the operational efficiency of the model pump as the optimization objective and controlling ten key geometric parameters of the blade profile through Bézier curves, the blade profile optimization design was achieved. The pump hydraulic efficiency under the rated flow condition increased by 7%. The unsteady internal flow efficiency of the optimized marine centrifugal pump was significantly improved. The blade optimization alleviated flow separation phenomena on the tangential surface of the impeller and in partial regions of the volute, reduced the flow loss area, and significantly decreased overall flow losses.
ABSTRACT We propose methods based on batching, sectioning, and generalized likelihood ratios (GLRs) for computing confidence intervals (CIs) and confidence regions (CRs) for quantiles in steady‐state simulations. Based on central limit theorems for quantile estimators, CIs and CRs can be computed from a single batch of simulated output using a GLR method to consistently estimate the unknown density function. This paper makes the following contributions: (1) We derive a GLR estimator for distribution sensitivities in the steady‐state setting and, under the geometric‐moment contraction (GMC) conditions, we establish the uniform consistency of the GLR estimators and the asymptotic validity of the respective CIs and CRs for quantiles. (2) We also establish the asymptotic validity of CIs and CRs for quantiles by batching and sectioning methods for steady‐state simulations. Numerical experiments demonstrate the validity of the aforementioned methods as the coverage rates of the CIs and CRs approach the target levels for appropriately large sample sizes. In the steady‐state setting, the sectioning and GLR methods demonstrate their respective advantages in different examples.
ABSTRACT This study addresses the gap in existing research by examining how default risk and bankruptcy risk influence financing format choices in agricultural supply chains characterized by yield uncertainty and diseconomies of scale. Using a two‐period model, we analyze the equilibrium outcomes of direct financing (DF) and guarantee financing (GF) for a representative family farm facing production‐period default risk and sales‐period bankruptcy risk. Key findings reveal that lower default risk incentivizes the family farm to increase investment, benefiting both parties, while bankruptcy risk emerges conditionally—depending on output distribution—prompting strategic input reduction to avoid insolvency. The family farm prefers GF when the agricultural firm offers a high risk‐free rate, and both the bank rate and default risk are low; otherwise, DF dominates. For the agricultural firm, GF is optimal under high diseconomies of scale or moderate diseconomies with elevated default risk. Notably, DF and GF can achieve win‐win outcomes under specific conditions, even with discrete output distributions. The introduction of zero‐interest early payment financing (EP) reshapes preferences: EP becomes a viable alternative that aligns incentives, often outperforming DF and GF. This research contributes by systematically integrating agricultural‐specific risks into financing decisions and demonstrating how strategic financing design reconciles conflicting objectives in agricultural supply chains.
ABSTRACT As an effective financing tool, crowdfunding helps entrepreneurs raise funds from the crowd and start innovative projects. Creators must carefully choose the mechanism and pricing strategy to maximize expected profit. When promoting multiple products, they shall decide whether to run a single bundled campaign (bundle funding) or two separate campaigns, each focusing on one product (separate funding). A two‐period model has been used to compare two mechanisms and several pricing policies for all‐or‐nothing (AoN) reward‐based crowdfunding campaigns. Separate funding leverages the advantage of spreading risk among multiple projects, especially if the distribution of backers' valuations is skewed. The bundling strategy can capture a more significant return if the fractions of different backers are balanced. However, in crowdfunding, creators often offer multiple price options to match different buyer preferences and boost the success rate. The menu pricing strategy of separate funding achieves a higher expected profit than bundle funding in significant parameter subspaces by spreading the risk and stimulating each project's pledging. For asymmetric bundling, separate funding may not be optimal if product heterogeneity is high. However, if the firm can adopt different pricing strategies for different products in separate funding, separate funding weakly dominates bundle funding. This study compares social welfare across different mechanisms and pricing strategies, explores the impact of complements and substitutes, and incorporates intertemporal pricing to reinforce the robustness of the findings.
The integrated development of offshore wind power and marine aquaculture represents a promising approach to the sustainable utilization of ocean resources. The present study investigated the hydrodynamic response of an innovative combination of a wind farm monopile and pontoon raft aquaculture facilities (PRAFs). Physical water tank experiments were conducted on PRAFs deployed around a wind farm monopile using the following configurations: single- and three-row arrangements of PRAFs with and without a monopile. The interaction between the aquaculture structure and the wind farm monopile was examined, with a particular focus on the mooring line tensions and bridle line tensions under different wave conditions. Utilizing the wind farm monopile foundation as an anchor, the mooring line tension was reduced significantly by 16–66% in the single-row PRAF. The multi-row PRAF arrangement experienced lower mooring line tension in comparison with the single-row PRAF arrangement, with the highest reduction of 73%. However, for the bridle line tension, the upstream component was enhanced, while the downstream one was weakened with a monopile, and they both decreased in the multi-row arrangement. Finally, we developed numerical models based on flume tank tests that examined the interactions between the monopile and PRAFs, including configurations of a single monopile, along with single- and three-row arrangements of PRAFs. The numerical simulation results confirmed that the monopile had a dampening effect on the wave propagation of 5% to 20%, and the impact of the pontoons on the monopile was negligible, implying that the integration of aquaculture facilities around wind farm infrastructure may not significantly alter the hydrodynamic loads experienced by the monopile.
Carolyn A. Reynolds, William Crawford, Prasad G. Thoppil
et al.
Abstract The impact of an eddy-resolving ocean as compared to an eddy-permitting ocean in the U. S. Navy’s Earth System Prediction Capability (ESPC) global coupled system on ocean and atmospheric forecast skill is examined. The use of an eddy-resolving (1/12°) ocean provides clear benefits to ocean forecasting skill compared to the use of an eddy-permitting (1/4°) ocean initialized using the eddy-resolving ocean analysis. The eddy-resolving ocean reduces RMSE for mixed layer depth, sea surface height anomaly, and upper-ocean temperature and salinity by as much as 20% throughout the 45-day forecast integration lead times over forecasts using the eddy-permitting ocean. The impact of eddy-resolving scales is particularly important in the energetic western boundary currents, with over 50% reduction in the SST biases in the Gulf Stream and Kuroshio Extension by the end of the 45-day forecasts, although the warm bias along the immediate east coasts of Asia and North America is increased. These ocean improvements result in reductions of air temperature bias magnitudes at long lead times, most notably over the tropics and southern extratropics. However, the impact on other atmospheric skill metrics is near neutral. Significance Statement Using an eddy-resolving ocean model as compared to a lower-resolution eddy-permitting ocean model in a global coupled system has clear benefits for the upper-ocean forecast skill on subseasonal forecasts. It also results in improvements to atmospheric forecasts, particularly for low-level atmospheric temperature biases, but the impact on other atmospheric metrics is close to neutral. The decision on how to spend limited computational resources will depend on the metrics that are a priority for the forecasting center.
AbstractThis study investigates an original equipment manufacturer's (OEM's) outsourcing choice between a competing manufacturer (CP) and a non‐competing manufacturer (NP). We develop a benchmark self‐produce strategy and two outsourcing strategies to differentiate two manufacturing service providers, and examine the optimal strategy alongside an analysis of the respective incentives (e.g., a lump‐sum payment) from the two service providers. The optimal strategy depends on the difference in production efficiency, degree of product substitution, and joint effect of the transfer payments. The transfer payments contribute to a greater range of Pareto improvements, increasing the possibility of outsourcing cooperation while highlighting the role of competition intensity on the model and outsourcing cooperation partner. Effect analysis shows that in the absence of transfer payment, the optimal strategy is beneficial to social welfare. With transfer payment, the optimal strategy is changed and the firms will be more profitable, but at the expense of customers' surplus, which may result in worse social welfare. An extended analysis of mixed strategies, in which the OEM produces part of the products and outsources the rest to CP/NP, shows that while the mixed‐CP strategy can be an optimal choice, the mixed‐NP strategy will degenerate to either self‐produce or complete outsourcing to NP under certain conditions.
This study proposes to automate the analysis of wiring diagrams to generate cable lists by using machine learning for text classification and pre-trained Deep Neural Network (DNN)-based image classification to detect cable routes. In shipyards, many drawings are produced for each ship, and analyzing these drawings, especially wiring diagrams, to generate cable lists for the Bill of Materials (BOM) can be a time-consuming and error-prone task. This process is performed manually by reading the cable routes and entering the information into a spreadsheet. To address these challenges, this study aims to automate the information extraction from wiring diagrams. The process involves extracting text from the PDF document and classifying it using machine learning, followed by using DNN-based image classification to trace cable routes and identify the relevant annotations. The developed algorithm was tested on three PDF wiring diagram samples and achieved an average accuracy of about 90%, confirming its effectiveness.
Domagoj Baresic, Nishatabbas Rehmatulla, Tristan Smith
The United Kingdom (UK) shipping industry is facing calls to set out more robust decarbonisation plans. In light of the economic challenges facing the country, including the cost-of-living crisis and energy security considerations, the UK government has outlined plans to spearhead several ‘green’ developments. It is of paramount importance to understand how best to integrate the domestic maritime sector into this process by promoting the adoption of low-carbon marine fuels such as hydrogen and ammonia. However, there is a limited understanding of what are the most suitable locations for the early adoption of such fuels in the UK. The sustainability transitions literature offers interesting insights into how marine fuel transitions can unfold, by combining the study of market factors with various non-market socio-technical forces. Previous academic work has shown the importance of location and proximity in facilitating alternative marine fuel transitions. This paper builds onto that work by applying a socio-technical transitions framework to develop a set of indicators to ascertain the suitability of potential locations for the early adoption of hydrogen and ammonia as marine fuels in the UK. This paper explores these dynamics by combining evidence from documentary sources, a UK ship voyages database, and interviews with key stakeholders. Furthermore, three specific case studies are analysed in detail to outline key drivers for the adoption of hydrogen and ammonia. The findings show that there is a significant difference across the UK in regional viability for the early adoption of hydrogen and ammonia, with some of the best suited sites being in the north of Scotland (Orkney), south of England (the Solent-Isle of Wight), and east of England (Felixstowe-Harwich).
The shipping industry faces a pressing challenge with carbon emissions, prompting a focus on speed optimization for energy conservation and emission reduction. While much research has centered on optimizing speeds in oceans and rivers, canals have received less attention, despite their unique challenges of narrow waterways and busy locks. This study fills this gap by establishing a fuel consumption prediction model integrating key environmental factors such as water depth, width, and flow velocity. Drawing upon established methodologies in speed optimization, this study augments these models with waiting time limits for each canal segment. To validate the efficacy of the model, three representative ships are selected as case studies. The findings reveal a high predictive capability of the fuel consumption model, as evidenced by R<sup>2</sup> values exceeding 0.97 across all cases. Notably, the optimization approach yields a fuel consumption reduction ranging from 4% to 5% for short waiting times. Furthermore, compared to conventional methods, the proposed optimization strategy achieves an 8.19% enhancement in fuel consumption and carbon emission reduction for long waiting times, culminating in an overall optimization rate of 11.54%. These results underscore the significance of employing the proposed speed optimization methodology, particularly during peak periods of canal congestion.
A wideband Doppler Effect is a significant challenge for underwater acoustic communications (UAC). This paper proposes a new two-stage structure of direct adaptive multi-resampling turbo equalizer (DAM-TEQ) for solving the problem of large timescale errors in time-varying channels, which uses an innovative adaptive time-domain resampling method for Doppler estimation and compensation. In this equalizer, the received signal is first fed into the first-stage structure, in which an adaptive resampling is performed using equalization coefficient detection to achieve a Doppler rough estimation. After the processing is completed, it is fed into the second-stage structure for joint equalization and decoding, effectively reducing the error of information transmission. Compared with the conventional turbo equalizer (TEQ) based on timescale estimation, the proposed equalizer can avoid the problem of the Doppler Effect not being accurately estimated in time-varying channels, with only a slight increase in complexity. Simulations and lake trails show that the equalizer can effectively perform a Doppler estimation and compensation in time-varying channels, and has a better bit error rate (BER) performance than the traditional timescale-based TEQ.
Two-way fluid–structure interaction (FSI) simulation of wind turbines has gained significant attention in recent years due to the growth of offshore wind energy development. Strong coupling procedures in these simulations predict realistic behavior with higher accuracy but result in increased computational costs and potential numerical instabilities. This paper proposes a mixed weak and strong coupling approach for the FSI simulation of a 5 MW wind turbine. The deformation of the turbine blade is calculated using a weak coupling approach, ensuring blade deflection meets a convergence criterion before rotating to the next azimuthal position. Fluid and solid solvers are partitioned, utilizing the commercial software packages STAR-CCM+ and Abaqus, respectively. Flexible and rigid blade cases are modeled, and the calculated loads, power, and blade tip displacement for the rotor at a constant rotating speed are compared. The proposed model is validated, showing good agreement with the existing literature and results comparable to those from another validated wind turbine simulator. The effect of rotor–tower interaction is evident in the results. Based on our calculations, the power production of flexible blades is evaluated to be 9.6% lower than that of rigid blades.
Reducing energy consumption and carbon emissions from ships is a major concern. The development of hybrid technologies offers a new direction for the rational distribution of energy. Therefore, this paper establishes a torque model for internal combustion engines and motors based on first principles and fitting the data collected from the test platform; in turn, it develops a model for fuel consumption and carbon emissions. Furthermore, the effect of irregular waves using an extended Kalman filter is estimated as well as feedback to the controller as a disturbance variable. Then, a parallel hybrid ship energy management strategy based on a new real-time nonlinear model of predictive control is designed to achieve energy conservation and emission decrease. A hybrid algorithm of chaotic optimization combined with grey wolf optimization is utilized to solve the nonlinear optimization problem in the nonlinear model predictive control strategy and a local refined search is performed using sequential quadratic programming. Through the comparison of fuel consumption, carbon emissions, real-time performance, and the engine load path, the superiority of the nonlinear model predictive control energy management strategy based on the chaotic grey wolf optimization algorithm is verified.
Artem Alekseevich Khalturin, Konstantin Dmitrievich Parfenchik, Vadim Anatolievich Shpenst
Given that the recent rapid growth of offshore production, especially in the Arctic region of the Russian Federation, is causing increased concern about oil spills on the water surface, this issue is especially relevant and important today. These pollutants have a devastating impact on the world’s marine biosphere. Therefore, effective and reliable methods and instruments must be used for operational spill detection in order to detect a remote oil spill. Several methods for oil spill monitoring and Russian developments in this area were described, including their features, advantages, and drawbacks. In cases when use in difficult Arctic conditions was anticipated, due to the harsh climate and ice-covered water surface, it was not always possible for spill detection instruments to be utilized. Despite this, such methods as radar, infrared, and ultraviolet were proven to be effective during this research. Ultimately, the combination of these methods returned the greatest volume of information to offshore platform staff about a detected oil spill. The information provided includes the spread area of the spill, the thickness of the leak, and the chemical composition of the oil.
Kevin L. Jensen, Michael S. McDonald, Mia K. Dhillon
et al.
Electron sources exploiting field emission generally have sharp geometries in the form of cones and wires. Often, they operate under elevated temperatures. A sharply curved emitter affects the emission barrier past which the electrons must be emitted via thermal-field processes, as does a space charge in metal-insulator-metal and metal-oxide-semiconductor devices: all can be examined using the Gamow factor θ(E) on which the general thermal-field equation is based. A methodology to evaluate θ(E) based on shape factor methods is given that emphasizes analytical methods, speed, and accuracy of execution and is applied to curvature and space-charge modified barriers characterized by the addition of a quadratic barrier term. The implications for thermal, field, and thermal-field emission are assessed. In addition to the known temperature rise that attends current through a wire, tapering of the emitter apex is a source of additional temperature increases, which are assessed using a simple model that provides an upper temperature limit appropriate for tip-on-post or poor thermally conductive materials.
This paper presents the results from a numerical simulation study to investigate wave trapping by a series of trapezoidal porous submerged breakwaters near a vertical breakwater, as well as the seabed response around the vertical breakwater. An integrated model, based on the volume-averaged Reynolds-averaged Navier–Stokes (VARANS) equations is developed to simulate the flow field, while the dynamic Biot’s equations are used for simulating the wave-induced seabed response. The reflection of the wave energy over the submerged breakwaters, caused by the vertical breakwater, can be reserved, indicating that the existence of the submerged breakwaters in the front of the vertical breakwater can either provide shelter or worsen the hazards to the vertical breakwater. Numerical examples show two different modes under the Fabry–Pérot (F–P) resonance condition of the wave transformation, namely the wave reflection (Mode 1) and the wave trapping (Mode 2). The distance between the submerged breakwaters and the vertical breakwater, is a key parameter dominating the local hydrodynamic process and the resultant dynamic stresses around the vertical breakwater. The numerical results indicated that more submerged breakwaters and a higher porosity of submerged breakwaters will obviously dissipate more wave energy, and hence induce a smaller wave force on the rear vertical breakwater and liquefaction area around the vertical breakwater.
Kasumi Morita, Masashi Mouri, Riccardo Fincato
et al.
This paper investigates the fatigue cyclic deformation behavior of mid-carbon steel. Uniaxial tensile loading tests and fatigue tests under constant and multi-step amplitude loading steps are performed to characterize the influence of loading history. The material is shown to exhibit different uniaxial ratcheting behavior depending on loading history. A smooth and gradual increase in cyclic softening is observed under smaller stress/strain conditions. Based on experimental characterization, numerical investigations are carried out to reproduce the cyclic stress–strain behavior under different variable amplitude load ranges. The nonlinear material behavior is reproduced by means of an elastoplasticity model called the Fatigue SS Model (hereafter, FSS model). The main feature of the FSS model is the ability to describe the cyclic softening behavior within a macroscopically elastic stress state. The good agreement between experimental and numerical results proves the reliability of the model to catch a realistic material response in fatigue problems. Furthermore, the present study introduces a method for the prediction of fatigue crack initiation life under variable loading conditions based on cumulative plastic work.
AbstractWe develop a robust queueing network analyzer algorithm to approximate the steady‐state performance of a single‐class open queueing network of single‐server queues with Markovian routing. The algorithm allows nonrenewal external arrival processes, general service‐time distributions and customer feedback. The algorithm is based on a decomposition approximation, where each flow is partially characterized by its rate and a continuous function that measures the stochastic variability over time. This function is a scaled version of the variance‐time curve, called the index of dispersion for counts (IDC). The required IDC functions for the external arrival processes can be calculated from the model primitives or estimated from data. Approximations for the IDC functions of the internal flows are calculated by solving a set of linear equations. The theoretical basis is provided by heavy‐traffic limits for the flows established in our previous papers. A robust queueing technique is used to generate approximations of the mean steady‐state performance at each queue from the IDC of the total arrival flow and the service specification at that queue. The algorithm's effectiveness is supported by extensive simulation studies.
Jeong-Yeob Chae, Chanhyung Jeon, Pyeongjoong Kim
et al.
Typhoon-induced strong winds can dramatically change the oceanic environment, occasionally resulting in sudden stratification changes. In July 2015, two consecutive typhoons, Chanhom and Nangka, passed over the Yellow and East/Japan Seas within a week. Remarkable temperature variations were observed near the southeastern coast of Korea, caused by typhoon-induced upwelling and downwelling events, which altered the energy of semidiurnal internal tides. During the typhoon-induced downwelling event, the energy of semidiurnal internal tides near the southeastern coast of Korea varied independently from the barotropic tidal forcing. Data-assimilated numerical simulation results reveal that the pycnocline, which is typically tilted toward the coast, enables the semidiurnal internal tidal energy to propagate toward shallow regions after being generated off the coast. Meanwhile, the downwelling event deepens the pycnocline near the coast and reflects and concentrates the semidiurnal internal tide energy near the bottom off the coast. A simple mechanism using the ratio between the wave characteristic slope and the bottom slope is proposed to explain the observed variations of semidiurnal internal tide energy near the coast. This paper demonstrates a case study showing that typhoon passage can modify the energetics of internal tides, which has the potential to cause unusual short-term coastal environmental changes.