A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors

Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research

A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors

Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research.close

On the use of autonomous unmanned vehicles in response to hazardous atmospheric release incidents

Recent events have induced a surge of interest in the methods of response to releases of hazardous materials or gases into the atmosphere. In the last decade there has been particular interest in mapping and quantifying emissions for regulatory purposes, emergency response, and environmental monitoring. Examples include: responding to events such as gas leaks, nuclear accidents or chemical, biological or radiological (CBR) accidents or attacks, and even exploring sources of methane emissions on the planet Mars. This thesis presents a review of the potential responses to hazardous releases, which includes source localisation, boundary tracking, mapping and source term estimation. [Continues.]</div

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Autonomous Monitoring of Contaminants in Fluids

The litigation and mitigation of maritime incidents suffer from a lack of information, first at the incident location, then throughout the evolution of contaminants such as spilled oil through the surrounding environment. Prior work addresses this through ocean and oil models, model directed sensor guidance and other observation methods such as satellites. However, each of these approaches and research fields have short-comings when viewed in the context of fast-response to an incident, and of constructing an all-in-one framework for monitoring contaminants using autonomous mobile sensors. In summary, models often lack consideration of data-assimilation or sensor guidance requirements, sensor guidance is specific to source locating, oil mapping, or fluid measuring and not all three, and data assimilation methods can have stringent requirements on model structure or computation time that may not be feasible. This thesis presents a model-based adaptive monitoring framework for the estimation of oil spills using mobile sensors. In the first of a four-stage process, simulation of a combined ocean, wind and oil model provides a state trajectory over a finite time horizon, used in the second stage to solve an adjoint optimisation problem for sensing locations. In the third stage, a reduced-order model is identified from the state trajectory, utilised alongside measurements to produce smoothed state estimates in the fourth stage, which update and re-initialise the first-stage simulation. In the second stage, sensors are directed to optimal sensing locations via the solution of a Partial Differential Equation (PDE) constrained optimisation problem. This problem formulation represents a key contributory idea, utilising the definition of spill uncertainty as a scalar PDE to be minimised subject to sensor, ocean, wind and oil constraints. Spill uncertainty is a function of uncertainty in (i) the bespoke model of the ocean, wind and oil spill, (ii) the reduced order model identified from sensor data, and (iii) the data assimilation method employed to estimate the states of the environment and spill. The uncertainty minimisation is spatio-temporally weighted by a function of spill probability and information utility, prioritising critical measurements. In the penultimate chapter, numerical case-studies spanning a 2500 km2 coastal area are presented. Here the monitoring framework is compared to an industry standard method in three scenarios: A spill monitoring and prediction problem, a retrodiction and monitoring problem and a source locating problem

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Department of Mechanical EngineeringThe potential danger of invisible hazardous substance leakage accident is increasing, such as hazardous chemical leakage accidents in industrial complexes, potential risks of aging nuclear power plants, and international chemical terrorism threats. In particular, hazardous chemical, biological, or radioactive substances leaked into the atmosphere cause irreversible damage to nature, and there is a risk of human damage if prompt action is not taken. Therefore, estimating the emission source and the amount of invisible hazardous substances is required to minimize human casualties and increase public safety. As the risk of hazardous material leakage and potential terrorism increases in random places, it is difficult using traditional systems such as pre-installed ground sensors in a specific area. This thesis proposes autonomous search method for estimating the source of hazardous materials using a mobile sensor attached to an unmanned aerial vehicle (UAV). Since the mobile sensor can be freely deployed to any arbitrary places, it is possible to monitor a wider area with a relatively low cost. Besides, this approach is an unmanned autonomous system, so it has the advantage of minimizing secondary human casualties that may additionally occur during search. The source term estimation (STE) using mobile sensors is considered to be a challenging problem because the sensor measurements from atmospheric gas dispersion are sparse, intermittent, and time-varying due to the turbulence and the sensor noise. Thus, Bayesian inference-based estimation technique, sequential Monte Carlo method (i.e., particle filter), is used to estimate the source by using the inaccurate measurements which is easily influenced by air turbulence and sensor noise in this thesis. The autonomous search algorithms using information theory are also proposed. In the proposed algorithms, the information entropy (i.e., uncertainty of estimation) is calculated by using information theory and the agent choose the action to move to the next sensing location that can minimize the expected uncertainty. In other words, the proposed information-theoretic search algorithm is reward-based decision making approaches that use information entropy as a reward. The receding horizon and Gaussian mixture model clustering approaches are adopted to improve the search performance in various environment. Since the time required to compute all of the respective rewards increases as the number of action candidates increases, the policy-based autonomous source term search and estimation algorithm is proposed using deep neural network and reinforcement learning approach to determine efficient search path considering continuous action space. Furthermore, this thesis proposes a cooperative search method for multiple unmanned mobile vehicles based on game theory. The inaccuracy of sensor measurement values can be reduced by using multiple mobile sensors with the fusion approach, so the source of hazardous substances can be quickly estimated. The negotiation based on the game theory can improve the group search performance for source term estimation and search. Finally, to verify the performance of the proposed algorithm, numerical simulation and flight test results using an actual gas measurement sensor and multicopter drone are presented.ope

Options for a new integrated natural resources monitoring framework for Wales. Phase 1 project report

Healthy natural resources underpin significant economic sectors in Wales including agriculture, fisheries, tourism and forestry, they also make a significant contribution across Cabinet policies including the health and well-being agenda. In order to develop policies that build social, economic and environmental resilience and to evaluate policy implementation, a robust natural resources monitoring framework is required. Current monitoring activities are of varying quality, not sufficiently aligned to the new legislative and policy landscape, disjointed and when considered as a whole, potentially not as cost-effective as they could be. This project was tasked with identifying options and developing recommendations for an integrated natural resources monitoring framework for Wales reflecting the ambitions and integrating principles of the Environment Act and Well Being of Future Generations Act. The monitoring community, the Welsh Government and Natural Resources Wales Core Evidence Group, the project team, stakeholders and partners, have agreed on a set of recommendations

Faculty of Engineering and Design. Research Review

STUDENTS AND ACADEMICS - This publication introduces you to the department or school and then each faculty member’s research areas, research applications, and their most recent activities. A comprehensive index can be found at the back of this publication to help guide you by specific areas of interest, as well as point out interdisciplinary topics and researchers. INDUSTRY LEADERS - This publication includes information regarding specific facilities, labs, and research areas of departments and schools as well as individual faculty members and researchers. A comprehensive index can be found at the back of this publication to help guide you by specific areas of interest, as well as point out interdisciplinary topics and researchers