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Open Access Publications from the University of California

Scholarly Works (5 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2019)

The aim of this research is to demonstrate the feasibility of remotely sensing nuclear and radiological threat materials by leveraging recent advances in radiation detectors, unmanned systems, and contextual sensors. The broad intent is to get detectors out of the hands of humans and onto semi-autonomous systems for a wide range of use cases. The search for special nuclear material is one specific mission area where radiation detectors employed on small unmanned aerial systems could provide significant operational value by exploiting the advantages that remote access enables: improved collection time, decreased source-to-detector distance, and reduced unintentional shielding. The goals of this study are fivefold: (1) assess current capabilities for directed search and substantiate the improvement that an unmanned approach would provide, (2) expand the understanding of the background radiation environment to include building rooftops, (3) establish system requirements and map out the parameter space of trade-offs (i.e., trade space) based on an analysis of current sensor and platform capabilities, (4) investigate and optimize search methods, and (5) identify and characterize additional mission areas for further investigation.

To achieve these five goals, we started by identifying boundary conditions for signal collection time, source-to-detector distance (i.e., standoff), and intervening material attenuation for three different search modes: vehicle-mounted standoff detection, rotary-wing aerial detection, and small unmanned aerial system-based remote detection. The objective of this analysis was to calculate the theoretical reduction in detector area required to achieve the same minimum detectable activity of a Cs-137 source for a given detector material. We found that measuring from the rooftop with just 50 cm2 of detector area should detect smaller activity sources than 10,000 cm2 in a vehicle-borne approach or 5,000 cm2 in an aerial helicopter-borne approach.

Our next objective was to characterize the background radiation environment sensed from the rooftops of light industrial buildings. We conducted a measurement campaign across fifteen buildings varying in geographic location, size, shape, height, wall construction, and roofing material. We discovered the variation in the background radiation ranged up to ±50% when analyzing contributions from seven prominent background peaks. Across a single building, this variation ranged 25–40% for contributions from potassium, uranium, and thorium. We also examined the attenuation of radiation by roofing materials both in simulation and experiment. We found that typical roof construction attenuates 1461 keV gamma-rays by approximately 50% when passing normal to the roof and continues to increase as the incident angle between the source and the detector increases. This observation directly influenced our approach to developing an optimal search scheme.

With knowledge of the background and consideration of threat signatures, we then initiated an effort to develop a system architecture and design a sensor suite capable of detecting relevant threats in the anticipated environment. We employed established requirements analysis techniques to frame the development of a system that will provide tangible operational value to the user. We examined the trade space for platforms and sensors in terms of size, weight, power, cost, and visibility profile. Although our survey of capabilities is a snapshot in time, it lays the foundation for future analysis of alternatives. We recommend a platform that can move both through the air and on the ground and suggest further exploration of tube-launched systems for several military mission areas employing radiation sensors. For detectors, we recommend room temperature semi-conductors: cadmium zinc telluride for gamma-ray spectroscopy and lithium-backfilled etched-silicon diodes for neutron detection. Technologies such as real-time kinematic positioning, solid-state light depth and ranging, and thermal infrared cameras warrant further study as auxiliary contextual sensors in the system.

Assuming an overmatched system is attainable, we then constructed a method to select advantageous measurement locations and developed techniques to optimize a search pattern. We devised a nonlinear programming routine and applied threshold cuts to reduce the time to converge to a near-optimal solution. We also explored several parameters that might be used as the objective quantity depending on the mission requirements and intelligence assessment.

Finally, with the intent of removing humans from the task of operating detectors in elevated radiation areas, we sought to expand our inquiry to seven additional military mission areas. We briefly examined a historical vignette where unmanned radiation detection assets would have provided considerable value, summarized the general operational conditions, assessed the impact that remote detection might have on the speed, accuracy, fidelity, safety, or feasibility of a given mission, and identified unique challenges that might arise in developing a materiel solution. These additional areas are ripe for exploration and contribution from the broader community of researchers.

    Cover page: Radiological and Nuclear Threat Detection Using Small Unmanned Aerial Systems
    • Article
    • Peer Reviewed
    UC San Diego Previously Published Works (2018)
    Solar geoengineering refers to deliberately reducing net radiative forcing by reflecting some sunlight back to space, in order to reduce anthropogenic climate changes; a possible such approach would be adding aerosols to the stratosphere. If future mitigation proves insufficient to limit the rise in global mean temperature to less than 1.5°C above preindustrial, it is plausible that some additional and limited deployment of solar geoengineering could reduce climate damages. That is, these approaches could eventually be considered as part of an overall strategy to manage the risks of climate change, combining emissions reduction, net-negative emissions technologies and solar geoengineering to meet climate goals. We first provide a physical-science review of current research, research trends and some of the key gaps in knowledge that would need to be addressed to support informed decisions. Next, since few climate model simulations have considered these limited-deployment scenarios, we synthesize prior results to assess the projected response if solar geoengineering were used to limit global mean temperature to 1.5°C above preindustrial in an overshoot scenario that would otherwise peak near 3°C. While there are some important differences, the resulting climate is closer in many respects to a climate where the 1.5°C target is achieved through mitigation alone than either is to the 3°C climate with no geoengineering. This holds for both regional temperature and precipitation changes; indeed, there are no regions where a majority of models project that this moderate level of geoengineering would produce a statistically significant shift in precipitation further away from preindustrial levels.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
      Cover page: Solar geoengineering as part of an overall strategy for meeting the 1.5C Paris target
      • Article
      • Peer Reviewed
      UC Riverside Previously Published Works (2017)
      Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species-specific threat. Long-term demographic data sets were used to construct an individual-based model (IBM), a complex stage-based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species' life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species' responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.
        Cover page: Implications of different population model structures for management of threatened plants
        • Article
        • Peer Reviewed
        UC Riverside Previously Published Works (2016)
        The identification of species at risk of extinction is a central goal of conservation. As the use of data compiled for IUCN Red List assessments expands, a number of misconceptions regarding the purpose, application and use of the IUCN Red List categories and criteria have arisen. We outline five such classes of misconception; the most consequential drive proposals for adapted versions of the criteria, rendering assessments among species incomparable. A key challenge for the future will be to recognize the point where understanding has developed so markedly that it is time for the next generation of the Red List criteria. We do not believe we are there yet but, recognizing the need for scrutiny and continued development of Red Listing, conclude by suggesting areas where additional research could be valuable in improving the understanding of extinction risk among species.
          Cover page: Clarifying misconceptions of extinction risk assessment with the IUCN Red List.
          • Article
          • Peer Reviewed
          UC Riverside Previously Published Works (2022)
          As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of 'living in harmony with nature'1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management3. Ecosystems vary in their biota4, service provision5 and relative exposure to risks6, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth's ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework.
            Cover page: A function-based typology for Earth’s ecosystems
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