A Modular and Integrated Optimisation Model for Underwater Vehicles

A modular and integrated optimisation model for the design of underwater vehicles is presented. In the proposed optimisation model two modules (i.e. low fidelity and high fidelity) are incorporated and the basic geometric definition of computer aided design (CAD) is integrated with computational fluid dynamic (CFD) analysis. The hydrodynamic drag is considered as single objective with constraints on the geometric parameters of dimension, space and volume. The CAD model is implemented in MATLAB*TM and CFD model is implemented in Shipflow**TM. A real-world design example of an existing underwater vehicles is presented. The applicability of proposed optimisation model is shown. The presented results show that within given set or sets of constraints the application of optimisation model in design results into an efficient hull form.

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Non-myopic multipoint multifidelity Bayesian framework for multidisciplinary design

The adoption of high-fidelity models in Multidisciplinary Design Optimization (MDO) permits to enhance the identification of superior design configurations, but would prohibitively rise the demand for computational resources and time. Multifidelity Bayesian Optimization (MFBO) efficiently combines information from multiple models at different levels of fidelity to accelerate the MDO procedure. State-of-the-art MFBO methods currently meet two major limitations: i) the sequential adaptive sampling precludes parallel computations of high-fidelity models, and ii) the search scheme measures the utility of new design evaluations only at the immediate next iteration. This paper proposes a Non-Myopic Multipoint Multifidelity Bayesian Optimization (NM3-BO) algorithm to sensitively accelerate MDO overcoming the limitations of standard methods. NM3-BO selects a batch of promising design configurations to be evaluated in parallel, and quantifies the expected long-term improvement of these designs at future steps of the optimization. Our learning scheme leverages an original acquisition function based on the combination of a two-step lookahead policy and a local penalization strategy to measure the future utility achieved evaluating multiple design configurations simultaneously. We observe that the proposed framework permits to sensitively accelerate the MDO of a space vehicle and outperforms popular algorithms

A survey on network simulators in three-dimensional wireless ad hoc and sensor networks

© 2016 The Author(s). As steady research in wireless ad hoc and sensor networks is going on, performance evaluation through relevant network simulator becomes indispensable procedure to demonstrate superiority to comparative schemes and suitability in most literatures. Thus, it is very important to establish credibility of simulation results by investigating merits and limitations of each simulator prior to selection. Based on this motivation, in this article, we present a comprehensive survey on current network simulators for new emerging research area, three-dimensional wireless ad hoc and sensor networks which is represented by airborne ad hoc networks and underwater sensor networks by reviewing major existing simulators as well as presenting their main features in several aspects. In addition, we address the outstanding mobility models which are main components in simulation study for self-organizing ad hoc networks. Finally, open research issues and research challenges are discussed and presented

PROOF OF CONCEPT FOR 3-D PRINTABLE GEOMETRY OF MICROFLUIDIC BENTHIC MICROBIAL FUEL CELL DEVICE (MBMFC) WITH SELF-ASSEMBLED WIRING

Extensive use of Unmanned Underwater Vehicles (UUVs) and remote equipment in future Naval operations leads to an energy logistics challenge for their rechargeable batteries. A solution to this challenge is a distributed network of renewable power sources detached from mainland power grids. One potential solution is Benthic Microbial Fuel Cell (BMFC) devices. BMFCs must be optimized and upscaled to produce power at relevant scales. 3-D printing is a promising manufacturing method to achieve scalable BMFC devices. In this thesis, we devised, developed, and optimized a protocol for clearance of microfluidic channels using square cross-sections embedded within PolyJet 3-D-printed chips. The developed protocol demonstrated 75% volumetric clearance of the embedded channels. The protocol was then used to clear channels with T-shaped cross-sections, which were used to produce an experimental proof of principle for self-assembled wiring within the microchannels due to fluidic surface tension. These advancements have opened the door to embedded wiring for 3-D printed biofuel cells and other microfluidic technologies. When perfected and manufactured at scale, biofuel cells could provide a solution to the critical logistics problem of recharging UUVs and similar equipment employed in remote maritime environments, thereby making an exceptional contribution to the U.S. Navy, U.S. national security, and the related research fields.Office of Naval Research, Arlington, VA 22203Lieutenant, United States NavyApproved for public release. Distribution is unlimited