Numerical and Experimental Optimization Study on a Fast, Zero Emission Catamaran

This paper reviews a state-of-the-art zero emission propulsion system for a battery-powered small craft. The main aspects considered are the available propulsion systems, energy storage, and dock battery charging. This underlying activity is part of the KISS project, a research and development program in the frame of the EU-funded “Piano Operativo Regionale CALABRIA FESR-FSE 2014–2020 ASSE I–PROMOZIONEDELLA RICERCA E DELL’INNOVAZIONE”, which is aimed at designing and building a physical prototype. Its hull form is based on previous research conducted by the authors, and the powering performances were preliminarily predicted by CFD simulation. The KISS project represents a successful example of an electric small craft with performances and a mission profile comparable to competitors with conventional propulsion. Such a target has been achieved by a concurrent design that considers the hull form, engine, propulsion system, and energy storage onboard. Safety issues and the regulatory frame are also highlighted.

*† ‡ § An efficient and high-fidelity design approach is proposed by combining global and local optimization methods for wing planform and surface design. For enhanced design results, aerodynamic shape optimization process is carried out via 2-stage with different optimization strategy. In the first stage, global optimization techniques are applied to planform design with a few geometric design variables. In the second stage, local optimization techniques are used for wing surface design with a lot of design variables to maintain a sufficient design space with high DOF (Degree of Freedom) geometric change. For global optimization, meta-modeling techniques such as RS (Response Surface) and Kriging methods are used in conjunction with Genetic Algorithm (GA). For local optimization, a discrete adjoint variable method is used. By the successive combination of global and local optimization techniques, drag minimization is performed for a multi-body aircraft configuration while maintaining the baseline lift and the wing weight at the same time. Through the design process, performances of the test models are remarkably improved in comparison with the single stage design approach. The capability of proposed design framework including wing planform design variables can be evaluated by the drag decomposition method which can provide improvement of induced drag and wave drag, respectively.

In this work, optimization methodologies of the kinematics of flapping wings in forward and hover flights are considered. Particularly, local and global optimization algorithms are combined with the unsteady vortex lattice method (UVLM) to determine the most efficient kinematics. In the first problem, the kinematic optimization of a three-dimensional flapping wing in forward flight with active shape morphing is aimed at maximizing the propulsive efficiency under lift and thrust constraints. Results show that due to the quasi-concavity of the objective function associated with the flapping kinematics employed in forward flight, local gradient-based optimizers perform very well in terms of accuracy and computational cost. In the second problem, the objective is to identify the optimized kinematics of a twodimensional hovering wing that minimize the aerodynamic power under lift constraint. The results show that using a hybrid optimization algorithm (combination of local and global schemes) accelerates the convergence to optimal points and avoids being trapped at local minimum points. While the efficiency of using a local optimizer, a global optimizer, or a hybrid of the two depends on the nature of the problem and associated design space, it is determined that hybrid optimization is best suited for determining local minima.

This paper makes an extensive description of a real fuel distribution problem. It includes the description of the elements, process, constraints and difficulties of the real problem, as well as the description of the efficient system that has been designed to solve it. This system combines a global strategy working with the whole set of orders and vehicles – global optimisation – and a local one – local optimisation – that tries to improve parts of the global solution, concretely pairs of routes. Both parts are combination of Simulated Annealing and a Route Building Heuristic. The main objective is to obtain good quality results in little time with this aim, the system has been parallelised, and, as a consequence, the same quality results can be obtained dividing the time by the number of processors. Satisfactory average results were obtained: the experts in the company ratified that solutions for problems with 170 orders are obtained in a couple of minutes, and savings greater than 10% are obtained as well. On the other hand, in problems of Solomon's benchmark, average results are very good in distance, whereas in vehicles, they are under 10% worse than the optimal one. This experimentation has been always done by limiting the number of solutions explored to 32,000.

This paper proposes a congestion control method for a wireless mesh network. Each intermediate node has separate transmission buffers for each of next hop nodes. By following the mathematical reaction-diffusion formulation, an intermediate node simultaneously performs 'local optimization' control that balances buffer occupancy among its transmission buffers and 'global optimization' control that suppresses the variation in occupancy between intermediate nodes along the path. As a result, packets are distributed over the whole path and further a network and buffer overflow is prevented. The results of our simulation show that the proposed method can provide better communication quality under loaded condition.

This paper describes the development of three candidate hull forms for 190,000 DWT ore carrier for operation in ice covered water. It builds on Hyundai Heavy Industries expertise in ore carrier design, and discusses some of the changes required for operation in heavy ice conditions. The overall concept was to have a target speed of 6 knots in land fast ice 1.7m thick and 15 knots in open water. Three candidate bow shapes were designed and analyzed, based on a common stern arrangement. The development of the hull form included three methods of predicting the performance of the ships in ice. Empirical analysis was carried out for all three hulls, based on experience gained from model experiments on bulk carrier hull forms in ice. Numerical analysis was carried out on all three bow shapes using a computer program (based on the discrete element method) to simulate the interaction between the ship and the ice. Physical model experiments were carried out for resistance and propulsion in level ice, pack ice and ridges on the selected design. As a result of the model experiments, the selected bow shape was modified to reduce its resistance in ice. The improved performance of the modified hull was confirmed with additional numerical simulations.

A parametric study on seakeeping assessment of fast ships in conceptual design stage

Multi-fidelity Co-Kriging surrogate model for ship hull form optimization

In complex, semi-structured orchard environments, mobile inspection robots often suffer from excessive turning points, low search efficiency, limited trajectory-tracking accuracy, and poor adaptability to dynamic obstacles. To address these issues, this study proposes an integrated autonomous navigation method that employs an improved A* algorithm for global path planning, a Fuzzy-Weighted Dynamic Window Approach (FW-DWA) for local path optimization, and a model predictive control (MPC)-based trajectory-tracking controller. First, a dynamic heuristic-weight adjustment strategy is introduced into the conventional A* algorithm, in which a correction factor adaptively tunes the heuristic weight; a two-stage node optimization procedure then removes hazardous and redundant nodes to improve path smoothness and safety. Second, the FW-DWA, grounded in fuzzy control theory, uses goal distance and obstacle distance to update the weights of the heading, clearance, and velocity evaluation functions in real time, thereby enhancing obstacle avoidance in dynamic environments. Finally, a discrete kinematic model is established to design the MPC Controller, which achieves high-precision tracking through receding-horizon optimization and feedback correction. Experiments conducted in real orchards demonstrate that the proposed method reduces path length by 5.79%, shortens planning time by 3.64%, and increases the minimum safety distance by 50%. Comparative results further show that the MPC Controller attains a mean position error of 0.032 m and a mean heading error of 3.14°, clearly outperforming a conventional Proportional–Integral–Derivative (PID) controller. These findings provide an effective solution for reliable autonomous navigation of orchard inspection robots and offer a valuable reference for smart agricultural robotics applications.

This paper discusses the hydrodynamic optimization of hull form mainly. The study has been carried out using an integrated tool for hydrodynamic optimization, incorporating a CAD modeler for definition and parametric modification of hull forms, CFD codes for the evaluation of hydrodynamic performance and software for optimization and decision making. A study includes the geometric modeling, hydrodynamic analysis, design evaluation and shape variation of a DTMB5415. Genetic Algorithm is utilized to explore the design space and to improve the hull shape. The most relevant feature of the tool is its capability to carry out and automatically evaluate parametric modifications of DTMB5415's shape, providing an assessment of the shape variants and proposing one or several `Pareto optimal' shapes. The hydrodynamic design process is implemented: An advanced parametric modeling kernel is applied for efficient form generation and variation. The hydrodynamic performance is analyzed by state-of-the-art Computational Fluid Dynamics (CFD) codes for calm water resistance. A commercial optimization system is used to integrate the various CAD and CFD tools and to carry out the optimization.

We propose two approaches to overcome limitation of convex programming technique for analog design automation. Analog design performance constraints are cast in posynomial inequality format for suitability into convex optimization based application. But in most cases original equations are not in posynomial so, either they are deliberately modeled or approximated. This leads to inaccuracy. Our first approach is based on exploiting apparent benefit of convex programming based global optimizer but still making use of highly accurate non-posynomial or signomial model. To achieve that, we combine both global and local optimizer. Global optimizer handles less accurate posynomial equation ensuring global optimality. And the initial guess obtained therefore is used by local optimizer to handle accurate signomial model. Second approach demonstrates that the targeted region to be modeled for circuit sizing can be reduced which invariably leads to better model accuracy. We develop low dropout regulator (LDO) performance metrics in posynomial and signomial format for use in the proposed methodology.

GL-GAN: Adaptive global and local bilevel optimization for generative adversarial network

An inter-area mode oriented pole-shifting method (named: IAMO-PS) with coordination of control efforts is proposed in this paper to tune power oscillation damping controllers under multiple operating conditions. Firstly, to provide incentives for developing IAMO-PS, a pole-shifting method (named: SCCS-PS), which tunes the controllers by moving all closed loop poles to a sequentially compressed conic section in the complex plane, is proposed to investigate impact of other modes on the control of inter-area modes. Thus, compared to SCCS-PS, a specific pole placement suitable for damping control of inter-area modes is implemented in IAMO-PS. Moreover, since a novel index is proposed to effectively measure control effort of the controller, IAMO-PS is capable of reasonably allocating the control burden among different controllers, which will be attractive for applications in practice. Optimization of both methods is solved by the efficient method of sequential quadratic programming, and a two-stage optimization procedure is proposed for IAMO-PS so that a feasible solution can be easily obtained in practical applications. Both methods are applied for control coordination in the New England and New York interconnected systems. Simulation results verify the effectiveness of IAMO-PS in robustly mitigating inter-area oscillations and coordinating control efforts, and some beneficial conclusions are also confirmed by comparing control results of the two methods.

This paper studies a novel wireless surveillance scenario, where a half-duplex legitimate monitor (E), aided by an intelligent reflecting surface (IRS), aims to eavesdrop the frequency division multiple access based suspicious broadcasting communication from a suspicious transmitter (ST) to multiple suspicious receivers (SRs). Under this setup, instead of eavesdropping the ST over all frequency bands (FBs), E proactively jams over certain <i>undesirable</i> FBs, i.e., jams certain SRs via E-SRs and E-IRS-SRs links, to deliberately force the ST reallocating more transmit power over the unjammed (eavesdroppable) <i>desirable</i> FBs. Then as a reward, E itself can achieve better eavesdropping over those FBs accordingly. Our objective is to maximize the <i>sum ergodic eavesdropping rate</i> of E, by jointly optimizing the set of jammed FBs, the jamming power allocation of E and the reflection coefficients at the IRS. A two-stage optimization procedure is proposed: i) given each possible jammed set, the jamming power allocation and the reflection coefficients are optimized via successive convex approximation and alternative iterations; ii) the optimal and sub-optimal jammed sets are further determined using the exhaustive search and the designed heuristic scheme. Results show the effectiveness of the proposed scheme compared to competitive benchmarks.

Solid-state production of polygalacturonase by Aspergillus sojae ATCC 20235