Time-optimal path planning in dynamic flows using level set equations: realistic applications

The level set methodology for time-optimal path planning is employed to predict collision-free and fastest-time trajectories for swarms of underwater vehicles deployed in the Philippine Archipelago region. To simulate the multiscale ocean flows in this complex region, a data-assimilative primitive-equation ocean modeling system is employed with telescoping domains that are interconnected by implicit two-way nesting. These data-driven multiresolution simulations provide a realistic flow environment, including variable large-scale currents, strong jets, eddies, wind-driven currents, and tides. The properties and capabilities of the rigorous level set methodology are illustrated and assessed quantitatively for several vehicle types and mission scenarios. Feasibility studies of all-to-all broadcast missions, leading to minimal time transmission between source and receiver locations, are performed using a large number of vehicles. The results with gliders and faster propelled vehicles are compared. Reachability studies, i.e., determining the boundaries of regions that can be reached by vehicles for exploratory missions, are then exemplified and analyzed. Finally, the methodology is used to determine the optimal strategies for fastest-time pick up of deployed gliders by means of underway surface vessels or stationary platforms. The results highlight the complex effects of multiscale flows on the optimal paths, the need to utilize the ocean environment for more efficient autonomous missions, and the benefits of including ocean forecasts in the planning of time-optimal paths.United States. Office of Naval Research (Grant N00014-09-1-0676 (Science of Autonomy - A-MISSION))United States. Office of Naval Research (Grant N00014-07-1-0473 (PhilEx))United States. Office of Naval Research (Grant N00014-12-1-0944 (ONR6.2))United States. Office of Naval Research (Grant N00014-13-1-0518 (Multi-DA)

Time-optimal path planning in dynamic flows using level set equations: theory and schemes

We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.United States. Office of Naval Research (Grant N00014-09-1-0676 (Science of Autonomy - A-MISSION))United States. Office of Naval Research (Grant N00014-12-1-0944 (ONR6.2))Natural Sciences and Engineering Research Council of Canada (Postgraduate Fellowship

Anaerobic Digestion in a Flooded Densified Leachbed

A document discusses the adaptation of a patented biomass-digesting process, denoted sequential batch anaerobic composting (SEBAC), to recycling of wastes aboard a spacecraft. In SEBAC, high-solids-content biomass wastes are converted into methane, carbon dioxide, and compost

A Coupled-Mode Shallow-Water Model for Tidal Analysis: Internal Tide Reflection and Refraction by the Gulf Stream

A hydrostatic, coupled-mode, shallow-water model (CSW) is described and used to diagnose and simulate tidal dynamics in the greater Mid-Atlantic Bight region. The reduced-physics model incorporates realistic stratification and topography, internal tide forcing from a priori estimates of the surface tide, and advection terms that describe first-order interactions of internal tides with slowly varying mean flow and mean buoyancy fields and their respective shear. The model is validated via comparisons with semianalytic models and nonlinear primitive equation models in several idealized and realistic simulations that include internal tide interactions with topography and mean flows. Then, 24 simulations of internal tide generation and propagation in the greater Mid-Atlantic Bight region are used to diagnose significant internal tide interactions with the Gulf Stream. The simulations indicate that locally generated mode-one internal tides refract and/or reflect at the Gulf Stream. The redirected internal tides often reappear at the shelf break, where their onshore energy fluxes are intermittent (i.e., noncoherent with surface tide) because meanders in the Gulf Stream alter their precise location, phase, and amplitude. These results provide an explanation for anomalous onshore energy fluxes that were previously observed at the New Jersey shelf break and linked to the irregular generation of nonlinear internal waves.National Science Foundation (U.S.) (Grant OCE-1061160 (ShelfIT))National Science Foundation (U.S.) (Grant OCE-1060430)United States. Office of Naval Research (Grants N000 14-11-1-0701 (MURI- IODA))United States. Office of Naval Research (N00014-12-1-0944 (ONR6.2)

Merging multiple-partial-depth data time series using objective empirical orthogonal function fitting

Author Posting. © IEEE, 2010. This article is posted here by permission of IEEE for personal use, not for redistribution. The definitive version was published in IEEE Journal of Oceanic Engineering 35 (2010): 710-721, doi:10.1109/JOE.2010.2052875.In this paper, a method for merging partial overlapping time series of ocean profiles into a single time series of profiles using empirical orthogonal function (EOF) decomposition with the objective analysis is presented. The method is used to handle internal waves passing two or more mooring locations from multiple directions, a situation where patterns of variability cannot be accounted for with a simple time lag. Data from one mooring are decomposed into linear combination of EOFs. Objective analysis using data from another mooring and these patterns is then used to build the necessary profile for merging the data, which is a linear combination of the EOFs. This method is applied to temperature data collected at a two vertical moorings in the 2006 New Jersey Shelf Shallow Water Experiment (SW06). Resulting profiles specify conditions for 35 days from sea surface to seafloor at a primary site and allow for reliable acoustic propagation modeling, mode decomposition, and beamforming.This work was supported by the U.S. Office of Naval Research (ONR) under Grants N00014-04-1-0146 and N00014-05-1- 0482, theONRPostdoctoral FellowshipAward under Grant N00014-08-1-0204, and by E. Livingston and T. Pawluskiewicz. The work of P. F. J. Lermusiaux and P. J. Haley was supported by the ONR under Grants N00014-07-1-1061, N00014-07-1-0501, and N00014-08-1-1097 to the Massachusetts Institute of Technology

Muscarinic Inhibition of Calcium Current and M Current in Gα_q-Deficient Mice

Activation of M₁ muscarinic acetylcholine receptors (M₁ mAChR) inhibits M-type potassium currents (I_(K(M))) and N-type calcium currents (I_(Ca)) in mammalian sympathetic ganglia. Previous antisense experiments suggested that, in rat superior cervical ganglion (SCG) neurons, both effects were partly mediated by the G-protein Gα_q (Delmas et al., 1998a; Haley et al., 1998a), but did not eliminate a contribution by other pertussis toxin (PTX)-insensitive G-proteins. We have tested this further using mice deficient in the Gα_q gene. PTX-insensitive M₁ mAChR inhibition of I_(Ca) was strongly reduced in Gα_q −/− mouse SCG neurons and was fully restored by acute overexpression of Gα_q. In contrast, M₁mAChR inhibition of I_(K(M)) persisted in Gα_q−/− mouse SCG cells. However, unlike rat SCG neurons, muscarinic inhibition of I_(K(M)) was partly PTX-sensitive. Residual (PTX-insensitive)I_(K(M)) inhibition was slightly reduced in Gα_q −/− neurons, and the remaining response was then suppressed by anti-Gα_(q/11) antibodies. Bradykinin (BK) also inhibits IK(M) in rat SCG neurons via a PTX-insensitive G-protein (G_q and/or G₁₁; Jones et al., 1995). In mouse SCG neurons, I_(K(M)) inhibition by BK was fully PTX-resistant. It was unchanged in Gα_q −/− mice but was abolished by anti-Gα_(q/11) antibody. We conclude that, in mouse SCG neurons (1) M₁ mAChR inhibition of I_(Ca) is mediated principally by G_q, (2) M₁ mAChR inhibition of I_(K(M)) is mediated partly by G_q, more substantially by G₁₁, and partly by a PTX-sensitive G-protein(s), and (3) BK-induced inhibition of I_(K(M)) is mediated wholly by G₁₁

Memory CD8⁺ T cells exhibit tissue imprinting and non-stable exposure-dependent reactivation characteristics following blood-stage Plasmodium berghei ANKA infections

Experimental cerebral malaria (ECM) is a severe complication of Plasmodium berghei ANKA (PbA) infection in mice, characterized by CD8(+) T‐cell accumulation within the brain. Whilst the dynamics of CD8(+) T‐cell activation and migration during extant primary PbA infection have been extensively researched, the fate of the parasite‐specific CD8(+) T cells upon resolution of ECM is not understood. In this study, we show that memory OT‐I cells persist systemically within the spleen, lung and brain following recovery from ECM after primary PbA‐OVA infection. Whereas memory OT‐I cells within the spleen and lung exhibited canonical central memory (Tcm) and effector memory (Tem) phenotypes, respectively, memory OT‐I cells within the brain post‐PbA‐OVA infection displayed an enriched CD69(+)CD103(−) profile and expressed low levels of T‐bet. OT‐I cells within the brain were excluded from short‐term intravascular antibody labelling but were targeted effectively by longer‐term systemically administered antibodies. Thus, the memory OT‐I cells were extravascular within the brain post‐ECM but were potentially not resident memory cells. Importantly, whilst memory OT‐I cells exhibited strong reactivation during secondary PbA‐OVA infection, preventing activation of new primary effector T cells, they had dampened reactivation during a fourth PbA‐OVA infection. Overall, our results demonstrate that memory CD8(+) T cells are systemically distributed but exhibit a unique phenotype within the brain post‐ECM, and that their reactivation characteristics are shaped by infection history. Our results raise important questions regarding the role of distinct memory CD8(+) T‐cell populations within the brain and other tissues during repeat Plasmodium infections

The California Current System: A multiscale overview and the development of a feature-oriented regional modeling system (FORMS)

17 USC 105 interim-entered record; under review.Over the past decade, the feature-oriented regional modeling methodology has been developed and applied in several ocean domains, including the western North Atlantic and tropical North Atlantic. This methodology is model-independent and can be utilized with or without satellite and/or in situ observations. Here we develop new feature-oriented models for the eastern North Pacific from 36◦ to 48◦N – essentially, most of the regional eastern boundary current. This is the firsttime feature-modeling has been applied to a complex eastern boundary current system. As a prerequisite to feature modeling, prevalent features that comprise the multiscale and complex circulation in the California Current system (CCS) are first overviewed. This description is based on contemporary understanding ofthe features and their dominant space and time scales of variability. A synergistic configuration of circulation features interacting with one another on multiple and sometimes overlapping space and time scales as a meander-eddy-upwelling system is presented. The second step is to define the feature-oriented regional modeling system (FORMS). The major multiscale circulation features include the mean flow and southeastward meandering jet(s) of the California Current (CC), the poleward flowing California Undercurrent (CUC), and six upwelling regions along the coastline. Next, the typical synoptic width, location, vertical extent, and core characteristics of these features and their dominant scales of variability are identified from past observational, theoretical and modeling studies. The parameterized features are then melded with the climatology, in situ and remotely sensed data, as available. The methodology is exemplified here for initialization of primitiveequation models. Dynamical simulations are run as nowcasts and short-term (4–6 weeks) forecasts using these feature models (FM) as initial fields and the Princeton Ocean Model (POM) for dynamics. The set of simulations over a 40-day period illustrate the applicability of FORMS to a transient eastern boundary current region such as the CCS. Comparisons are made with simulations initialized from climatology only. The FORMS approach increases skill in severalfactors, including the: (i) maintenance of the low-salinity pool in the core of the CC; (ii) representation of eddy activity inshore of the coastal transition zone; (iii) realistic eddy kinetic energy evolution; (iv) subsurface (intermediate depth) mesoscale feature evolution; and (v) deep poleward flow evolution.This work was funded by the Office of Naval Research grants N00014-03-1-0411 and N00014-03-1-0206 at the University of Massachusetts at Dartmouth. Leslie Rosenfeld’s participation was supported by ONR grant N00014-03-WR-20009. PFJL, PJH and WGL are grateful to ONR for support under grant N00014-08-1-1097, N00014-08-1-0680 and MURI-ASAP to the Massachusetts Institute of Technology

Issues and progress in the prediction of ocean submesoscale features and internal waves

Data-constrained dynamical ocean modeling for the purpose of detailed forecasting and prediction continues to evolve and improve in quality. Modeling methods and computational capabilities have each improved. The result is that mesoscale phenomena can be modeled with skill, given sufficient data. However, many submesoscale features are less well modeled and remain largely unpredicted from a deterministic event standpoint, and possibly also from a statistical property standpoint. A multi-institution project is underway with goals of uncovering more of the details of a few submesoscale processes, working toward better predictions of their occurrence and their variability. A further component of our project is application of the new ocean models to ocean acoustic modeling and prediction. This paper focuses on one portion of the ongoing work: Efforts to link nonhydrostatic-physics models of continental-shelf nonlinear internal wave evolution to data-driven regional models. Ocean front-related effects are also touched on.United States. Office of Naval Research (United States. Dept. of Defense. Multidisciplinary University Research Initiative (Ocean Acoustics Program Award N00014-11-1-0701))United States. Office of Naval Research (Grant N00014-12-1-0944)National Science Foundation (U.S.) (Grant OCE-1061160