Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here by permission of Taylor & Francis for personal use, not for redistribution. The definitive version was published in Journal of Operational Oceanography 10 (2017): 115-126, doi:10.1080/1755876X.2017.1322026.This paper outlines strategies that would advance coastal ocean modeling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the U.S. Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of U.S. based researchers with a cross-section of coastal oceanography and ocean modeling expertise and community representation drawn from Regional and U.S. Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modeling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3-8 year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, U.S. Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal-academic partnerships benefiting IOOS stakeholders and end users.2018-05-2

Ethical Control of Unmanned Systems: lifesaving/lethal scenarios for naval operations

Prepared for: Raytheon Missiles & Defense under NCRADA-NPS-19-0227This research in Ethical Control of Unmanned Systems applies precepts of Network Optional Warfare (NOW) to develop a three-step Mission Execution Ontology (MEO) methodology for validating, simulating, and implementing mission orders for unmanned systems. First, mission orders are represented in ontologies that are understandable by humans and readable by machines. Next, the MEO is validated and tested for logical coherence using Semantic Web standards. The validated MEO is refined for implementation in simulation and visualization. This process is iterated until the MEO is ready for implementation. This methodology is applied to four Naval scenarios in order of increasing challenges that the operational environment and the adversary impose on the Human-Machine Team. The extent of challenge to Ethical Control in the scenarios is used to refine the MEO for the unmanned system. The research also considers Data-Centric Security and blockchain distributed ledger as enabling technologies for Ethical Control. Data-Centric Security is a combination of structured messaging, efficient compression, digital signature, and document encryption, in correct order, for round-trip messaging. Blockchain distributed ledger has potential to further add integrity measures for aggregated message sets, confirming receipt/response/sequencing without undetected message loss. When implemented, these technologies together form the end-to-end data security that ensures mutual trust and command authority in real-world operational environments—despite the potential presence of interfering network conditions, intermittent gaps, or potential opponent intercept. A coherent Ethical Control approach to command and control of unmanned systems is thus feasible. Therefore, this research concludes that maintaining human control of unmanned systems at long ranges of time-duration and distance, in denied, degraded, and deceptive environments, is possible through well-defined mission orders and data security technologies. Finally, as the human role remains essential in Ethical Control of unmanned systems, this research recommends the development of an unmanned system qualification process for Naval operations, as well as additional research prioritized based on urgency and impact.Raytheon Missiles & DefenseRaytheon Missiles & Defense (RMD).Approved for public release; distribution is unlimited

INTEROPERABILITY FOR MODELING AND SIMULATION IN MARITIME EXTENDED FRAMEWORK

This thesis reports on the most relevant researches performed during the years of the Ph.D. at the Genova University and within the Simulation Team. The researches have been performed according to M&S well known recognized standards. The studies performed on interoperable simulation cover all the environments of the Extended Maritime Framework, namely Sea Surface, Underwater, Air, Coast & Land, Space and Cyber Space. The applications cover both the civil and defence domain. The aim is to demonstrate the potential of M&S applications for the Extended Maritime Framework, applied to innovative unmanned vehicles as well as to traditional assets, human personnel included. A variety of techniques and methodology have been fruitfully applied in the researches, ranging from interoperable simulation, discrete event simulation, stochastic simulation, artificial intelligence, decision support system and even human behaviour modelling

Digital Twin in Naval Environment

A naval vessel is usually engaged in demanding operations that take place in a multifaceted environment. This requires a solid design of the ship as a platform and a prompt decision-making response. To support both the design and operation phases, digital tools and techniques have been widely implemented, along with a significant number of sensors and probes installed onboard. All of these features pave the way for the development of a Digital Twin model, which will be beneficial for the naval sector. In this work, relevant applications and a use case have been presented and discussed, with the goal of highlighting the added value and critical issues in the perspective of gathering them in a Digital Twin environment. The steps required to develop a shared reference digital architecture have been identified, as well as the gaps that need to be filled

Towards an optimal design for ecosystem-level ocean observatories

Four operational factors, together with high development cost, currently limit the use of ocean observatories in ecological and fisheries applications: 1) limited spatial coverage; 2) limited integration of multiple types of technologies; 3) limitations in the experimental design for in situ studies; and 4) potential unpredicted bias in monitoring outcomes due to the infrastructure’s presence and functioning footprint. To address these limitations, we propose a novel concept of a standardized “ecosystem observatory module” structure composed of a central node and three tethered satellite pods together with permanent mobile platforms. The module would be designed with a rigid spatial configuration to optimize overlap among multiple observation technologies each providing 360° coverage around the module, including permanent stereo-video cameras, acoustic imaging sonar cameras, horizontal multi-beam echosounders and a passive acoustic array. The incorporation of multiple integrated observation technologies would enable unprecedented quantification of macrofaunal composition, abundance and density surrounding the module, as well as the ability to track the movements of individual fishes and macroinvertebrates. Such a standardized modular design would allow for the hierarchical spatial connection of observatory modules into local module clusters and larger geographic module networks, providing synoptic data within and across linked ecosystems suitable for fisheries and ecosystem level monitoring on multiple scales.Peer ReviewedPostprint (author's final draft

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 341)

This bibliography lists 133 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Mission Assurance for Autonomous Underwater Vehicles

The ubiquity of autonomous vehicles (AVs) is all but inevitable, and AVs have made fantastic leaps in their capabilities, partly thanks to advances in artificial intelligence and machine learning (AI/ML). With these great capabilities should come great assurance that AVs will behave safely and achieve their operational goals, or mission, despite foreseen and unforeseen circumstances. AV software is highly complex, increasing the likelihood of faults. AI/ML decision making is poorly understood. And, all computer-based systems are vulnerable to malicious software and other cybersecurity threats. Eliminating or mitigating any one of these is an open research problem. AVs must handle all three, without the benefit of a human operator. This dissertation investigates several aspects of AV mission assurance, and offers solutions for test and evaluation starting early in the development cycle, a use case with which to experiment, and a methodology for iteratively improving assurance as more is learned about a mission and its specific risks. This dissertation focuses on autonomous underwater vehicles (AUVs). Each chapter explores particular aspects of AUV mission assurance and presents approaches to address them. We discuss the risks specific to AUV safety and mission assurance. We introduce the Digital Environment for Simulated Cyber Resilience Engineering, Test and Experimentation (DESCRETE) testbed that enables cost-effective AUV simulation, particularly with respect to system-level faults and attacks. We present the mission-assured AUV (MAAUV) use case, which we used to gather data on DESCRETE to improve the testbed and better understand mission assurance. We propose an iterative mission-assurance refinement analysis (IMARA) methodology for understanding system-failure impacts to mission. Applying IMARA to the MAAUV, we provide a guide for AUV and mission designers to best use limited assurance improvement and mitigation resources. Combining all these provides a comprehensive set of tools to improve AUV assurance