A Dual-Mode Rechargeable Lithium-Bromine/Oxygen Fuel Cell

Modeling position uncertainty of networked autonomous underwater vehicles

The deployment of Autonomous Underwater Vehicles (AUVs) for ocean observation is one of the important methods in marine scientific research. The stability of AUV attitude control determines the efficiency and safety of underwater operations. In practical systems, the actuators carried by AUVs have saturation, and the saturation of the actuators greatly affects the performance and stability of AUV attitude control. This article designs an anti-windup [Formula: see text] robust state feedback controller and an anti-windup [Formula: see text] robust dynamic output feedback controller for the pitch attitude control of AUVs to solve the pitch attitude control problem of AUVs subject to input constraints. Firstly, building a Linear-parameter varying (LPV) model for the AUV. Then, we design two anti-windup [Formula: see text] robust controllers based on LPV model. Simulation results verify the reasonable of LPV model and the effectiveness of proposed controllers. Proposed controllers can enable the system to quickly reach the desired attitude under input constraints.

Multiple field-based methods to assess the potential impacts of seismic surveys on scallops

Deployment of autonomous underwater vehicle have became a focal point for many industrial application. The main challenge to the autonomous underwater vehicle is the finite mission time during the operation in a harsh environment. The most efficient way to reduce the operational and maintenance costs, and increase the efficiency of the system, the autonomous under water vehicles have to be recharged under water during the operation. This paper proposes an analysis of one side com-pensation topology and indexes some parameters to be considered when designing an inductive contactless power transfer system for AUV charging.

In recent days, there has been an increasing demand for the deployment of autonomous underwater vehicles (AUVs) for tactical wireless acoustic communications. This requires secure and reliable AUVcommunications to protect sensitive data. However, existing methods such as cryptography and channel coding introduce extra overheads and computational complexity. This is primarily due to the inherent challenges posed by acoustic communication systems, such as limited bandwidth and low energy efficiency. To overcome these challenges, we propose using intelligent reflecting surfaces (IRSs) in conjunction with reinforcement learning (RL) techniques, resulting in what is termed as RL-assisted Buoyed-IRS-AUV (RL-BIA) links. The RL-BIA links facilitate simultaneous secure and reliable communications by dynamically adjusting its beam width and IRS’s depth in response to seawater turbulence induced by wind and tide. We introduce a comprehensive link model that accounts for pointing errors, path loss, interference, and noise. Additionally, we developed an RL model adaptable to BIA links. To integrate channel secrecy and outage probability, a non-convex Max-Min optimization problem is formulated and solved iteratively using Q-learning and State-Action-Reward-State-Action (SARSA) algorithms. Numerical results demonstrate that at a wind speed of 8.5 meters per second, the proposed approach significantly enhances channel secrecy, with the RL-BIA link achieving a remarkable 400% improvement compared to the RL-assisted buoyed-AUV(RL-BA) link.

In this chapter, the receding horizon Kalman filter is applied to underwater navigation systems. The ocean covers about two-thirds of the earth and has a great effect on human beings. However, the ocean is overlooked while we focus our attention on land and atmospheric issues; we have not been able to explore the full depths of the ocean, its abundant livings and non-living resources. For example, only recently we have discovered, by using manned submersibles, that a large amount of methane and carbon dioxide comes from the seafloor and extraordinary groups of organisms live in hydrothermal vent areas. However, a number of complex issues due to the unstructured and hazardous undersea environment make it difficult to survey in the ocean even though today’s technologies have allowed humans to land on the moon and robots to travel to Mars. Unmanned underwater vehicles (UUVs) can help us better understand marine and other environmental issues, protect the ocean resources of the earth from pollution, and efficiently utilize them for human welfare. The UUV is a platform for a variety of sensors: acoustic, magnetic, gravimetric and chemical ones. Most commercial UUVs are tethered and remotely operated, referred to as remotely operated vehicles (ROVs). Extensive use of manned submersibles and ROVs are currently limited to a few applications because of very high operational costs, operator fatigue and safety issues. The demand for advanced underwater vehicle technologies is growing and will eventually lead to fully autonomous and reliable underwater vehicles. Autonomous underwater vehicles (AUVs) were initially developed to perform missions that were not easy for ROVs and manned underwater vehicles. Since the autonomy allows AUVs to be used for risky missions such as a mine countermeasure (MCM) or under-ice operations, AUVs are replacing ROVs towed vehicles as well as manned underwater vehicles (Whitcomb, 2000). For detailed ocean surveys, an AUV acts as a more stable platform for precision sensors than ROVs or towed vehicles because an AUV is not subject to physical disturbances transmitted along the cable to the surface vessel. This absence of physical attachment also allows AUVs to measure ocean characteristics at specific depths and perform bottom-following missions as owing to its autonomy. In short, An AUV provides marine researchers with a new form of access to deeper ocean. For an AUV to successfully complete a typical survey mission, it must follow a path specified by the operator as closely as possible and arrive at a precise location for collecting data. When an AUV is not able to follow the path accurately during the mission, critical Source: Kalman Filter, Book edited by: Vedran Kordic, ISBN 978-953-307-094-0, pp. 390, May 2010, INTECH, Croatia, downloaded from SCIYO.COM

Autonomous Underwater Vehicles (AUVs) are platforms suitable for a wide variety of applications in the marine environment with economic and operational advantages. In these applications an AUV performs a given task as a mission. During the mission execution, the AUV will move around the environment following paths that allow it to fulfill the mission's objectives. To achieve this, a reliable Navigation System (NS) is required. In addition to this, the current operating concept includes the deployment of multiple AUVs on a given area, thus a communication system between vehicles is also required. In the underwater environment both navigation and communication systems deals with the particular characteristics of the medium that limits the use of conventional techniques. In this work, a complete NS for an AUV is presented. The developed NS is based on an inertial navigation scheme with velocity and position aiding. The position aiding takes advantage of the communication system onboard the vehicle, which avoids the use of additional positioning systems. The fundamentals of the applied solutions are described and experimental results and implementation details are provided. Also conclusions and future works are presented.

With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUV's technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.

Hydrophone, an acoustic sensor, used to pick up acoustic signals generated by different objects present in underwater. MEMS Vector Hydrophone is a recent advancement in the field of underwater acoustic sensors that provides the direction of the incoming acoustic signals. As the main sensing elements of these hydrophones are in micrometers hence light weight, which makes them useful for deployment in Autonomous Underwater vehicles (AUVs) and Remotely Operated Underwater Vehicles (ROVs). This paper presents simulation, modeling and design optimization of four beam MEMS Vector Hydrophone, using design modeler of ANSYS Workbench. This paper presents design optimization, stress, frequency, harmonic and electro-mechanical analysis of MEMS-based four beam Vector Hydrophone. Using ANSYS software design is optimized by changing important parameters to improve design and sensitivity that can be chosen for fabrication. Static structural analysis is performed on the structure for getting an optimized location for placing piezoresistors over cantilever beams. For better understanding of structural vibrations that can be induced in the Vector Hydrophone structure, the resonant frequencies of the structure were identified and quantified. The Receiving Voltage Sensitivity is −196.73 dB (0 dB = 1 V/µPa) which is further improved to −184.86 dB by design optimization (Xue et al. in Microelectron J 38:1021–1026, 2007 [1]). By incorporating pre-amplifier having a gain of 100, Voltage sensitivity further can be enhanced up to −156.73 dB (Hang et al. in Nano-Micro Lett 6:136–142, 2014 [2]).

This paper focuses on mobile positioning for autonomous underwater vehicle (AUV) in complex underwater environments. The positioning algorithm based on time of arrival (TOA) assumes that the underwater acoustic communication between AUV and underwater sensors is real-time and reliable. The distance between the AUV and underwater sensors can be obtained through the time delay of acoustic signal transmission. However, the uncertain and complex nature of the underwater environment can cause underwater sensors to fail to receive acoustic signals from the AUV reliably. This leads to an insufficient effective observation data in the positioning solution process, causing underdetermined problems in the solution equation, and thus making it impossible to solve the AUV’s position information stably in real time. To overcome this problem, we frist established a positioning model considering the navigation velocity of the AUV. Based on this Model, we then proposed a two-step weighted least squares algorithm combined with a fast horizontal distance model for the deep sea (TWLS-HD-V). Furthermore, we derived the Cram´er-Rao Lower Bound (CRLB) of the proposed model and compared it with that of the basic model. Finally, the effectiveness of the proposed algorithm was tested on both numerical simulations and deep-sea data. In conclusion, this algorithm effectively overcomes two key challenges in complex underwater environments: sound line bending and insufficient time delay information. As a result, it improves AUV positioning accuracy and ensures reliable positioning trajectories.

The development of solid-state batteries (SSBs) is crucial for advancing next-generation battery technology. Compared to conventional lithium-ion batteries using organic liquid electrolytes, SSBs offer higher energy density, improved safety, and wide operating temperature range. Nonetheless, constructing a practical SSB with lithium-metal anode (LMA) and optimal inorganic solid electrolyte (SE) presents significant challenges. In this presentation, we introduce our findings addressing the two primary obstacles impeding the remarkable advancement of SSBs.The electrochemical instability at the interface between LMA and SE is the first persistent issue to overcome. Solid materials constituting SSBs exhibit distinct physical and chemical properties. When these materials, in the form of electrodes or electrolytes, are assembled into an electrochemical cell configuration, they establish solid–solid interfaces within the energy storage system. Achieving electrochemically stable SSBs requires non-reactive interfaces between LMA and SE with conformal contact. Previous studies have predominantly focused on developing interface modification methods to enhance the long-term cycling stability of SSBs. However, such approaches often offer phenomenological solutions without a thorough understanding of the interface dynamics. Additionally, the role of charges within an electric field in the operation of lithium-ion batteries is often overlooked. The LMA-SE interface of SSBs experiences an in situ electric field during the charging process, where the SEs exhibit semiconducting properties distinct from liquid electrolytes. Consequently, identifying the governing mechanism of interface stabilization cannot rely solely on conventional electrochemical techniques or a materials science perspective alone.Interface modeling by tailoring energy band alignment is a fundamental approach to achieving the cycling stability of SSBs. In this study, we used Li1.3Al0.3Ti1.7(PO4)3 (LATP), a representative NASICON-type SE, alongside a Li-metal foil. Although LATP possesses excellent electrochemical stability with a high anodic limit (4.31 V) and small decomposition energy (- 65 meV per atom at 5 V), its direct contact with LMA leads to the formation of a reactive interface having mixed ionic-electronic conducting interphases (MCI). The presence of MCI expedites the reduction of LATP’s metallic constituents by enabling electron transfer across the interface. Given the heightened risk of interfacial instability in the electrochemical cell, controlling interfacial reactions is imperative for constructing SSBs. Herein, we deposited titanium (45 nm) onto the surface of LATP to stabilize the inherently reactive LMA-LATP interface. The pure transition metal interlayer transformed into an ion-conducting crystal structure through electrochemical interactions with Li-metal. This titanium compound self-induced interlayer (TSI) served as a stable Li-ion conductor and electron buffer between LMA and LATP. Lithium symmetric cells having TSI maintained constant overpotential over 1000 cycles and exhibited significantly reduced impedance.Another critical obstacle to realizing practical SSBs is the intrinsic structural instability of SEs. This physical instability shortens the lifespan of SSBs and severely diminishes their electrochemical performance at the typical ambient temperatures of electric vehicle power batteries (25-50 °C). Over the past decade, various solid-state Li-ion conductors have been developed such as Li7La3Zr2O12 (garnet-type oxide SE) and Li6PS5Cl (argyrodite-type sulfide SE). By associating lattice dynamics and ionic transport in these materials, previous studies could improve the ionic conductivity of SE through major substitution with large cations like tantalum or partial substitution with large anions. Recently, antiperovskite-type SEs with the anion-centered unit of Li3AB, where A represents hydroxyl and B represents halogen groups, have attracted attention. The representative composition Li2OHCl is renowned for its facile fabrication process through solid-state reaction, high ionic conductivity (10-3 S cm-1), and excellent compatibility with LMA. Still, significant limitations exist in its use for constructing practical SSBs, as is common with most other types of SEs.We found that substituting trace amounts of aliovalent cations to modify atomic interactions in SEs can significantly enhance the electrochemical reliability of SSBs. This strategy effectively resolves the intrinsically unstable structure of SEs and simultaneously enhances the LMA-SE interfaces. As a proof-of-concept, we substituted lithium in Li2OHCl with metal elements that do not experience crystal field stabilization energy. The resulting modified electrolytes led to prolonged lifespan and superior rate performance in lithium symmetric cells at room temperature. The cells with the modified SEs exhibited a remarkable critical current density exceeding 10.5 mA cm-2 and maintained a stable voltage profile for 3000 hours at 10.0 mA cm-2, whereas the pristine cells achieved a relatively low critical current density of 2.0 mA cm-2 and a short lifespan of 1000 hours at 1.0 mA cm-2. These findings underscore a strong correlation between the physical properties of inorganic materials and the electrochemical stability of SSBs. Finally, we anticipate that the revealing results will contribute to the advancement of high-power SSBs employing solid electrolytes and metallic electrodes.

Summary The current stage is characterized by high activity of the world community in the field of research of deep-water oil and gas basins and new promising types of solid minerals. A promising direction in terms of improving the efficiency and reliability of exploration results on hydrocarbon and solid mineralsof the world ocean is the use of Autonomous unmanned underwater vehicles, which allow for detailed large-scale bottom surveys, quickly and efficiently. The required component of the Autonomous underwater complex is the means of measuring the components of the magnetic and gravitational fields. The report provides an overview of modern foreign and domestic technologies in the field of underwater deep-sea gravimetric and magnetometric surveys, analyzes the results of such works and formulates a range of exploration tasks that are promising for their application.

The detection and localization of targets of interest in the very shallow water areas and especially in the surf zone are much more difficult problems than in the deep ocean. To overcome these problems, it is necessary to augment existing fleet sensor capability with additional technology. Furthermore in keeping with Navy policy, it is desirable to remove the diver from harms way. A potential solution is to utilize a small autonomous underwater vehicle (AUV) instrumented with both a buried target sonar and the real time tracking gradiometer (RTG). This paper describes the procedures required to successfully place a magnetic gradient sensor array on an AUV. The first step was to magnetically characterize the AUV. This was accomplished by passing the AUV by a stationary RTG and then by externally mounting that RTG at several locations on the AUV which was then placed in simulated at-sea motion on a nonmagnetic three-axis motion table. Analysis of the data revealed that the favored location of a magnetic sensor is near the nose of the vessel and that the initial degradation, in this location, caused by the presence of the powered AUV was 30 dB above sensor noise. The degradation was caused primarily by the vehicle's electrical systems. Initial measurements also revealed the presence of several ferromagnetic components that should be replaced with nonmagnetic equivalents when practical. A detailed plan of magnetic noise mitigation is also presented. It involves several steps for implementation, including the substitution of nonferrous components for ferrous, maximizing the separation between the sensor and magnetic field sources, minimizing current loops and using auxiliary current and magnetic field sensors capable of generating noise-canceling signals.

We, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), are developing an autonomous underwater vehicle (AUV) whose main mission is monitoring a site at the sea bottom for the carbon dioxide capture and storage (CCS). The AUV cruises very near the sea bottom, and is equipped with chemical sensors in order to detect escape of CO2 from sub-bottom. Of course, the position information of the AUV is critical information for the monitoring. In this paper, a conceptual design of navigation of the AUV is described. Recently, navigation of AUV is implemented by integrating multiple navigation devices including inertial navigation system (INS), Doppler velocity log (DVL), depth sensor, acoustic navigation system, and others. The AUV under construction will be equipped with these navigation sensors, and will integrate those sensors’ outputs to navigate herself. In order to measure the absolute position of the AUV the acoustic method is one of fundamental technique. At the first step of development of the AUV, three acoustic methods are considered to adopt. The three methods are super short baseline (SSBL) method which is a tracking from support ship or other surface station, long baseline (LBL) which is navigation based on preplaced acoustic transponders, and virtual LBL (VLBL) which is navigation based on only single transponder. These acoustic methods are integrated with the navigation result of INS, depth sensor, and DVL. The three methods are used in each appropriate case. Which feature of observation is desired simplicity, accuracy, or independence from support ship and time efficiency? The acoustic method is influenced by environment, and also output of other sensors is depending on the environment, for example the DVL miss the data when the terrain is with many up-hills and down-hills. The integration or filtering parameters of the navigation should be adjusted depending on the influential environmental factor.

Minimizing deep sea data collection delay with autonomous underwater vehicles