A common problem in the transfer chute is the unbalanced mass flow at the outlet conveyor. The objective consists in reducing the difference in curve averages of total mass in left and right part of the conveyor. Coupling Rocky DEM with modeFRONTIER enabled engineers to select the optimum design that reduced this difference to 0.2%.
The optimization of train movements could make the railway system even less impacting on the environment by reducing energy consumption and CO2 emissions. Only in a limited number of cases train drivers are assisted by the so called Driver Advisory System which suggests energy-eﬃcient speed proﬁles. The present study aims at minimizing energy consumption in both the planning phase, where train timetables are defined, and operational phase in which traﬃc may be perturbed by unexpected events.
A general design procedure have been developed for the application of the Immersed Particle Heat Exchanger to a novel, small scale, externally fired combined cycle capable of generating electrical and thermal power from carbon-neutral biomass. The Immersed Particle Heat Exchanger serves as the high temperature heat exchanger needed to couple the Brayton cycle with an external combustor of biom
In this paper, supersonic wing design problems for supersonic transport (SST) with integrated engine intake and nacelle was discussed to obtain design knowledge of a supersonic airfoil with respect to wing planform dependency for a realistic configuration. Optimum wing designs were analyzed considering the interference between the engine intake, the nacelle, and the wing for two different planforms using a multi-fidelity design method.
This paper presents a Multidisciplinary Design Optimization (MDO) framework that is intended to be employed in the early design stages of Unmanned Aerial Vehicles (UAVs). A development approach for modeling the sensor performance and the radar signature is proposed and it is shown that their integration in a framework which also takes into account the geometry, the aerodynamics, the stability, and the mission simulation is feasible.
A Multidisciplinary Design Optimization approach considering closed-loop flight control laws was applied to a conceptual design of a large-cabin business jet. The optimization algorithm used in this work is the Multi-Objective Genetic Algorithm of second generation (MOGA-II algorithm) using modeFRONTIER. Two types of analysis were done: mono-objective, maximizing the internal rate of return, and multi-objective, maximizing the internal rate of return and minimizing Dubai – London City mission block time.
This article has reported on an industrial R&D project aimed at identifying a cost-effective response to the more and more challenging high-speed motor requirements that presently come from the gas industry sector. To meet the very high efficiency, dynamic performance, and reliability standards required by cutting-edge turbomachinery drive applications, a special PM synchronous motor prototype has been developed.
In this study, a comparative assessment is performed between ventilation and mechanical cooling by assessing the performance of different design variants for different scenarios. This must help decision makers in the design process of residential buildings to achieve more future-proof zero energy houses. A methodology is proposed and applied to a case study building to compare the performance of both cooling strategies, and to find the most suitable strategies considering the future climate and various occupant scenarios.
The objectives of the optimisation management that considers both assembly and production Hybrid Flow-Shops lines are several: optimal numbers of machines, shifts, product priority and time-period scheduling. The approach uses a combination of DES software with an MDO (Multidisciplinary Design Optimization) software, modeFRONTIER. model is optimized following the process: 1) A Multi-objective Genetic Algorithm cycle generates a set of optimal solutions; 2) A Clustering cycle groups the solutions into different sets; 3) The selection of the preferred solution via post-processing; 4) A mono-objective optimisation of each cluster; and 5) creation of weekly scheduling with optimal results.