Rapid Real-Time Interdisciplinary Ocean Forecasting Using Adaptive Sampling and Adaptive Modeling and Legacy Codes: Component Encapsulation Using XML

Abstract. We present the high level architecture of a real-time inter-disciplinary ocean forecasting system that employs adaptive elements in both modeling and sampling. We also discuss an important issue that arises in creating an integrated, web-accessible framework for such a system out of existing stand-alone components: transparent support for handling legacy binaries. Such binaries, that are most common in scien-tific applications, expect a standard input stream, maybe some command line options, a set of input files and generate a set of output files as well as standard output and error streams. Legacy applications of this form are encapsulated using XML. We present a method that uses XML doc-uments to describe the parameters for executing a binary.

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

On the optimization of low-cost FDM 3D printers for accurate replication of patient-specific abdominal aortic aneurysm geometry

Abstract Background There is a potential for direct model manufacturing of abdominal aortic aneurysm (AAA) using 3D printing technique for generating flexible semi-transparent prototypes. A patient-specific AAA model was manufactured using fused deposition modelling (FDM) 3D printing technology. A flexible, semi-transparent thermoplastic polyurethane (TPU), called Cheetah Water (produced by Ninjatek, USA), was used as the flexible, transparent material for model manufacture with a hydrophilic support structure 3D printed with polyvinyl alcohol (PVA). Printing parameters were investigated to evaluate their effect on 3D–printing precision and transparency of the final model. ISO standard tear resistance tests were carried out on Ninjatek Cheetah specimens for a comparison of tear strength with silicone rubbers. Results It was found that an increase in printing speed decreased printing accuracy, whilst using an infill percentage of 100% and printing nozzle temperature of 255 °C produced the most transparent results. The model had fair transparency, allowing external inspection of model inserts such as stent grafts, and good flexibility with an overall discrepancy between CAD and physical model average wall thicknesses of 0.05 mm (2.5% thicker than the CAD model). The tear resistance test found Ninjatek Cheetah TPU to have an average tear resistance of 83 kN/m, higher than any of the silicone rubbers used in previous AAA model manufacture. The model had lower cost (4.50 GBP per model), shorter manufacturing time (25 h 3 min) and an acceptable level of accuracy (2.61% error) compared to other methods. Conclusions It was concluded that the model would be of use in endovascular aneurysm repair planning and education, particularly for practicing placement of hooked or barbed stents, due to the model’s balance of flexibility, transparency, robustness and cost-effectiveness

A relocatable ocean model in support of environmental emergencies

During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive Relocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, and to the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.MEDESS4MS Project; TESSA Project; MyOcean2 Projectinfo:eu-repo/semantics/publishedVersio

A future for intelligent autonomous ocean observing systems

Ocean scientists have dreamed of and recently started to realize an ocean observing revolution with autonomous observing platforms and sensors. Critical questions to be answered by such autonomous systems are where, when, and what to sample for optimal information, and how to optimally reach the sampling locations. Definitions, concepts, and progress towards answering these questions using quantitative predictions and fundamental principles are presented. Results in reachability and path planning, adaptive sampling, machine learning, and teaming machines with scientists are overviewed. The integrated use of differential equations and theory from varied disciplines is emphasized. The results provide an inference engine and knowledge base for expert autonomous observing systems. They are showcased using a set of recent at-sea campaigns and realistic simulations. Real-time experiments with identical autonomous underwater vehicles (AUVs) in the Buzzards Bay and Vineyard Sound region first show that our predicted time-optimal paths were faster than shortest distance paths. Deterministic and probabilistic reachability and path forecasts issued and validated for gliders and floats in the northern Arabian Sea are then presented. Novel Bayesian adaptive sampling for hypothesis testing and optimal learning are finally shown to forecast the observations most informative to estimate the accuracy of model formulations, the values of ecosystem parameters and dynamic fields, and the presence of Lagrangian Coherent Structures

Multiscale multiphysics data-informed modeling for three-dimensional ocean acoustic simulation and prediction

Author Posting. © Acoustical Society of America, 2019. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 146(3), (2019): 1996-2015, doi:10.1121/1.5126012.Three-dimensional (3D) underwater sound field computations have been used for a few decades to understand sound propagation effects above sloped seabeds and in areas with strong 3D temperature and salinity variations. For an approximate simulation of effects in nature, the necessary 3D sound-speed field can be made from snapshots of temperature and salinity from an operational data-driven regional ocean model. However, these models invariably have resolution constraints and physics approximations that exclude features that can have strong effects on acoustics, example features being strong submesoscale fronts and nonhydrostatic nonlinear internal waves (NNIWs). Here, work to predict NNIW fields to improve 3D acoustic forecasts using an NNIW model nested in a tide-inclusive data-assimilating regional model is reported. The work was initiated under the Integrated Ocean Dynamics and Acoustics project. The project investigated ocean dynamical processes that affect important details of sound-propagation, with a focus on those with strong intermittency (high kurtosis) that are challenging to predict deterministically. Strong internal tides and NNIW are two such phenomena, with the former being precursors to NNIW, often feeding energy to them. Successful aspects of the modeling are reported along with weaknesses and unresolved issues identified in the course of the work.This work was supported by Department of Defense Multidisciplinary University Initiative (MURI) Grant No. N00014-11-1-0701, managed by the Office of Naval Research Ocean Acoustics Program, and National Science Foundation Grant No. OCE-1060430. Final manuscript preparation was supported by ONR Ocean Acoustics Grant Nos. N00014-17-1-2624 and N00014-17-1-2692. P.F.J.L. also thanks ONR and NSF for research support under Grant Nos. N00014-13-1-0518 (Multi-DA) and OCE-1061160 (ShelfIT) to MIT, respectively. The MSEAS-based series of simulations for the New Jersey shelf region examined here was accelerated toward completion by the interest in realistic 3D acoustic fields expressed by Dr. Ivars Kirsteins at the Naval Undersea Warfare Center.2020-03-3

Time-evolving acoustic propagation modeling in a complex ocean environment

During naval operations, sonar performance estimates often need to be computed in-situ with limited environmental information. This calls for the use of fast acoustic propagation models. Many naval operations are carried out in challenging and dynamic environments. This makes acoustic propagation and sonar performance behavior particularly complex and variable, and complicates prediction. Using data from a field experiment, we have investigated the accuracy with which acoustic propagation loss (PL) can be predicted, using only limited modeling capabilities. Environmental input parameters came from various sources that may be available in a typical naval operation. The outer continental shelf shallow-water experimental area featured internal tides, packets of nonlinear internal waves, and a meandering water mass front. For a moored source/receiver pair separated by 19.6 km, the acoustic propagation loss for 800 Hz pulses was computed using the peak amplitude. The variations in sound speed translated into considerable PL variability of order 15 dB. Acoustic loss modeling was carried out using a data-driven regional ocean model as well as measured sound speed profile data for comparison. The acoustic model used a two-dimensional parabolic approximation (vertical and radial outward wavenumbers only). The variance of modeled propagation loss was less than that measured. The effect of the internal tides and sub-tidal features was reasonably well modeled; these made use of measured sound speed data. The effects of nonlinear waves were not well modeled, consistent with their known three-dimensional effects but also with the lack of measurements to initialize and constrain them.Netherlands. Ministry of DefenceUnited States. Office of Naval Research (Grant N00014-12-1-0944 (ONR6.2))United States. Office of Naval Research (Grant N00014-08-1-1097 (ONR6.1))United States. Office of Naval Research (Grant N00014-08-1-0680 (PLUS-SEAS)

Using Interpolation to Estimate System Uncertainty in Gene Expression Experiments

The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical) treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements

The Re-Emergence of Percutaneous Fasciotomy in the Management of Dupuytren’s Disease

Dupuytren’s disease is a common condition. Its management has gradually evolved but still remains a source of much controversy. Recently there has been a resurgence in the popularity of percutaneous needle fasciotomy. It is a simple method that uses a hypodermic needle as a scalpel blade. It is usually performed in the out-patient setting under local anaesthesia without a tourniquet. It has few complications and allows almost immediate return to work with few restrictions

Circulation and intrusions northeast of Taiwan : chasing and predicting uncertainty in the cold dome

Author Posting. © The Oceanography Society, 2011. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 24 no. 4 (2011): 110–121, doi:10.5670/oceanog.2011.99.An important element of present oceanographic research is the assessment and quantification of uncertainty. These studies are challenging in the coastal ocean due to the wide variety of physical processes occurring on a broad range of spatial and temporal scales. In order to assess new methods for quantifying and predicting uncertainty, a joint Taiwan-US field program was undertaken in August/September 2009 to compare model forecasts of uncertainties in ocean circulation and acoustic propagation, with high-resolution in situ observations. The geographical setting was the continental shelf and slope northeast of Taiwan, where a feature called the "cold dome" frequently forms. Even though it is hypothesized that Kuroshio subsurface intrusions are the water sources for the cold dome, the dome's dynamics are highly uncertain, involving multiple scales and many interacting ocean features. During the experiment, a combination of near-surface and profiling drifters, broad-scale and high-resolution hydrography, mooring arrays, remote sensing, and regional ocean model forecasts of fields and uncertainties were used to assess mean fields and uncertainties in the region. River runoff from Typhoon Morakot, which hit Taiwan August 7–8, 2009, strongly affected shelf stratification. In addition to the river runoff, a cold cyclonic eddy advected into the region north of the Kuroshio, resulting in a cold dome formation event. Uncertainty forecasts were successfully employed to guide the hydrographic sampling plans. Measurements and forecasts also shed light on the evolution of cold dome waters, including the frequency of eddy shedding to the north-northeast, and interactions with the Kuroshio and tides. For the first time in such a complex region, comparisons between uncertainty forecasts and the model skill at measurement locations validated uncertainty forecasts. To complement the real-time model simulations, historical simulations with another model show that large Kuroshio intrusions were associated with low sea surface height anomalies east of Taiwan, suggesting that there may be some degree of predictability for Kuroshio intrusions.We thank the National Science Council of Taiwan as well as the Office of Naval Research for generous support of this effort