First Biennial Ocean Climate Summit: Finding Solutions for San Francisco Bay Area’s Coast and Ocean. Proceedings of the Summit: April 29, 2008, Golden Gate Club, The Presidio San Francisco, California

Executive Summary: The marine environment plays a critical role in the amount of carbon dioxide (CO2) that remains within Earth’s atmosphere, but has not received as much attention as the terrestrial environment when it comes to climate change discussions, programs, and plans for action. It is now apparent that the oceans have begun to reach a state of CO2 saturation, no longer maintaining the “steady-state” carbon cycle that existed prior to the Industrial Revolution. The increasing amount of CO2 present within the oceans and the atmosphere has an effect on climate and a cascading effect on the marine environment. Potential physical effects of climate change within the marine environment, including ocean acidification, changes in wind and upwelling regimes, increasing global sea surface temperatures, and sea level rise, can lead to dramatic, fundamental changes within marine and coastal ecosystems. Altered ecosystems can result in changing coastal economies through a reduction in marine ecosystem services such as commercial fish stocks and coastal tourism. Local impacts from climate change should be a front line issue for natural resource managers, but they often feel too overwhelmed by the magnitude of this issue to begin to take action. They may not feel they have the time, funding, or staff to take on a challenge as large as climate change and continue to not act as a result. Already, natural resource managers work to balance the needs of humans and the economy with ecosystem biodiversity and resilience. Responsible decisions are made each day that consider a wide variety of stakeholders, including community members, agencies, non-profit organizations, and business/industry. The issue of climate change must be approached as a collaborative effort, one that natural resource managers can facilitate by balancing human demands with healthy ecosystem function through research and monitoring, education and outreach, and policy reform. The Scientific Expert Group on Climate Change in their 2007 report titled, “Confronting Climate Change: Avoiding the Unmanageable and Managing the Unavoidable” charged governments around the world with developing strategies to “adapt to ongoing and future changes in climate change by integrating the implications of climate change into resource management and infrastructure development”. Resource managers must make future management decisions within an uncertain and changing climate based on both physical and biological ecosystem response to climate change and human perception of and response to the issue. Climate change is the biggest threat facing any protected area today and resource managers must lead the charge in addressing this threat. (PDF has 59 pages.)

Efficient Gate-tunable light-emitting device made of defective boron nitride nanotubes: from ultraviolet to the visible

Boron nitride is a promising material for nanotechnology applications due to its two-dimensional graphene-like, insulating, and highly-resistant structure. Recently it has received a lot of attention as a substrate to grow and isolate graphene as well as for its intrinsic UV lasing response. Similar to carbon, one-dimensional boron nitride nanotubes (BNNTs) have been theoretically predicted and later synthesised. Here we use first principles simulations to unambiguously demonstrate that i) BN nanotubes inherit the highly efficient UV luminescence of hexagonal BN; ii) the application of an external perpendicular field closes the electronic gap keeping the UV lasing with lower yield; iii) defects in BNNTS are responsible for tunable light emission from the UV to the visible controlled by a transverse electric field (TEF). Our present findings pave the road towards optoelectronic applications of BN-nanotube-based devices that are simple to implement because they do not require any special doping or complex growth

Design, specification, and synthesis of aircraft electric power systems control logic

Cyber-physical systems integrate computation, networking, and physical processes. Substantial research challenges exist in the design and verification of such large-scale, distributed sensing, ac- tuation, and control systems. Rapidly improving technology and recent advances in control theory, networked systems, and computer science give us the opportunity to drastically improve our approach to integrated flow of information and cooperative behavior. Current systems rely on text-based spec- ifications and manual design. Using new technology advances, we can create easier, more efficient, and cheaper ways of developing these control systems. This thesis will focus on design considera- tions for system topologies, ways to formally and automatically specify requirements, and methods to synthesize reactive control protocols, all within the context of an aircraft electric power system as a representative application area.

This thesis consists of three complementary parts: synthesis, specification, and design. The first section focuses on the synthesis of central and distributed reactive controllers for an aircraft elec- tric power system. This approach incorporates methodologies from computer science and control. The resulting controllers are correct by construction with respect to system requirements, which are formulated using the specification language of linear temporal logic (LTL). The second section addresses how to formally specify requirements and introduces a domain-specific language for electric power systems. A software tool automatically converts high-level requirements into LTL and synthesizes a controller.

The final sections focus on design space exploration. A design methodology is proposed that uses mixed-integer linear programming to obtain candidate topologies, which are then used to synthesize controllers. The discrete-time control logic is then verified in real-time by two methods: hardware and simulation. Finally, the problem of partial observability and dynamic state estimation is ex- plored. Given a set placement of sensors on an electric power system, measurements from these sensors can be used in conjunction with control logic to infer the state of the system.

Control of dynamical systems with temporal logic specifications

This thesis is motivated by safety-critical applications involving autonomous air, ground, and space vehicles carrying out complex tasks in uncertain and adversarial environments. We use temporal logic as a language to formally specify complex tasks and system properties. Temporal logic specifications generalize the classical notions of stability and reachability that are studied in the control and hybrid systems communities. Given a system model and a formal task specification, the goal is to automatically synthesize a control policy for the system that ensures that the system satisfies the specification. This thesis presents novel control policy synthesis algorithms for optimal and robust control of dynamical systems with temporal logic specifications. Furthermore, it introduces algorithms that are efficient and extend to high-dimensional dynamical systems.

The first contribution of this thesis is the generalization of a classical linear temporal logic (LTL) control synthesis approach to optimal and robust control. We show how we can extend automata-based synthesis techniques for discrete abstractions of dynamical systems to create optimal and robust controllers that are guaranteed to satisfy an LTL specification. Such optimal and robust controllers can be computed at little extra computational cost compared to computing a feasible controller.

The second contribution of this thesis addresses the scalability of control synthesis with LTL specifications. A major limitation of the standard automaton-based approach for control with LTL specifications is that the automaton might be doubly-exponential in the size of the LTL specification. We introduce a fragment of LTL for which one can compute feasible control policies in time polynomial in the size of the system and specification. Additionally, we show how to compute optimal control policies for a variety of cost functions, and identify interesting cases when this can be done in polynomial time. These techniques are particularly relevant for online control, as one can guarantee that a feasible solution can be found quickly, and then iteratively improve on the quality as time permits.

The final contribution of this thesis is a set of algorithms for computing feasible trajectories for high-dimensional, nonlinear systems with LTL specifications. These algorithms avoid a potentially computationally-expensive process of computing a discrete abstraction, and instead compute directly on the system's continuous state space. The first method uses an automaton representing the specification to directly encode a series of constrained-reachability subproblems, which can be solved in a modular fashion by using standard techniques. The second method encodes an LTL formula as mixed-integer linear programming constraints on the dynamical system. We demonstrate these approaches with numerical experiments on temporal logic motion planning problems with high-dimensional (10+ states) continuous systems.