NSWC Panama City Division

Underwater blasts propagate further and injure more readily than equivalent air blasts. Development of effective personal protection and countermeasures, however, requires knowledge of the currently unknown human tolerance to underwater blast. Current guidelines for prevention of underwater blast injury are not based on any organized injury risk assessment, human data or experimental data. The goal of this study was to derive injury risk assessments for underwater blast using well-characterized human underwater blast exposures in the open literature. The human injury dataset was compiled using 34 case reports on underwater blast exposure to 475 personnel, dating as early as 1916. Using severity ratings, computational reconstructions of the blasts, and survival information from a final set of 262 human exposures, injury risk models were developed for both injury severity and risk of fatality as functions of blast impulse and blast peak overpressure. Based on these human data, we found that the 50% risk of fatality from underwater blast occurred at 302±16 kPa-ms impulse. Conservatively, there is a 20% risk of pulmonary injury at a kilometer from a 20 kg charge. From a clinical point of view, this new injury risk model emphasizes the large distances possible for potential pulmonary and gut injuries in water compared with air. This risk value is the first impulse-based fatality risk calculated from human data. The large-scale inconsistency between the blast exposures in the case reports and the guidelines available in the literature prior to this study further underscored the need for this new guideline derived from the unique dataset of actual injuries in this study.

Automatic target recognition in sidescan sonar imagery is vital to many applications, particularly sea mine detection and classification. We expand upon the traditional offline supervised classification approach with an active learning method to automatically label new objects that are not present in the training set. This is facilitated by the option of sending difficult samples to an outlier bin, from which models can be built for new objects. The decisions of the classifier are improved by a novel active learning approach, called model trees (MT), which builds an ensemble of hypotheses about the classification decisions that grows proportionally to the amount of uncertainty the system has about the samples. Our system outperforms standard active learning methods, and is shown to correctly identify new objects much more accurately than a pure clustering approach, on a simulated sidescan sonar data set.

This work demonstrates that automated mine countermeasure (MCM) tasks are greatly facilitated by characterizing the seafloor environment in which the sensors operate as a first step within a comprehensive strategy for how to exploit information from available sensors, multiple detector types, measured features, and target classifiers, depending on the specific seabed characteristics present within the high-frequency synthetic aperture sonar (SAS) imagery used to perform MCM tasks. This approach is able to adapt as environmental characteristics change and includes the ability to recognize novel seabed types. Classifiers are then adaptively retrained through active learning in these unfamiliar seabed types, resulting in improved mitigation of challenging environmental clutter as it is encountered. Further, a segmentation constrained network algorithm is introduced to enable enhanced generalization abilities for recognizing mine-like objects from underrepresented environments within the training data. Additionally, a fusion approach is presented that allows the combination of multiple detectors, feature types spanning both measured expert features and deep learning, and an ensemble of classifiers for the particular seabed mixture proportions measured around each detected target. The environmentally adaptive approach is demonstrated to provide the best overall performance for automated mine-like object recognition.

The transition (T) matrix of Waterman has been very useful for computing fast, accurate acoustic scattering predictions for axisymmetric elastic objects, but this technique is usually limited to fairly smooth objects that are not too aspherical unless complex basis functions or stabilization schemes are used. To ease this limitation, a spherical-basis formulation adapted from approaches proposed recently by Waterman [J. Acoust. Soc. Am. 125(1), 42-51 (2009)] and Doicu, Eremin, and Wriedt [Acoustic and Electromagnetic Scattering Analysis Using Discrete Sources (Academic, London, 2000)] is suggested. This is implemented by simply transforming the high-order outgoing spherical basis functions within standard T-matrix formulations to low-order functions distributed along the object's symmetry axis. A free-field T matrix is produced in a nonstandard form, but computations with it become much more stable for elongated aspherical elastic shapes. Some advantages of this approach over the approaches of Waterman and Doicu, Eremin, and Wriedt are noted, and sample calculations for a 10:1 Al prolate spheroid and a 10:1 Al superspheroid of order 10 are given to demonstrate the enhanced stability.

The motors or engines of an autonomous ground vehicles (AGV) have torque and power limitations, which limit their abilities to climb steep hills, which are defined to be hills that have high grade sections in which the vehicle is forced to decelerate. Traversal of a steep hill requires the vehicle to have sufficient momentum before entering the hill. This problem is part of a larger class of momentum-based motion planning problems such as the problem of lifting heavy objects with manipulators. Hence, solutions to the steep hill climbing problem have much wider applicability. The motion planning here is accomplished using a dynamic model of the skid-steered AGV used in the experiments along with Sampling Based Model Predictive Control (SBMPC), a recently developed input sampling planning algorithm that may be viewed as a generalization of LPA* to the direct use of kinodynamic models. The motion planning is demonstrated experimentally using two scenarios, one in which the robot starts at rest at the bottom of a hill and one in which the robot starts at rest a distance from the hill. The first scenario requires the AGV to first reverse direction so that the vehicle can gather enough momentum before reaching the hill. This corresponds to having the vehicle begin at a local minimum, which results in a problem that many traditional model predictive control methods cannot solve. It is seen that, whereas open loop trajectories can lead to vehicle immobilization, SBMPC successfully uses the information provided by the dynamic model to ensure that the AGV has the requisite momentum.

In this paper, we consider the problem of denoising and classification of SONAR signals observed under compositional noise, i.e., they have been warped randomly along the x-axis. The traditional techniques do not account for such noise and, consequently, cannot provide a robust classification of signals. We apply a recent framework that: 1) uses a distance-based objective function for data alignment and noise reduction; and 2) leads to warping-invariant distances between signals for robust clustering and classification. We use this framework to introduce two distances that can be used for signal classification: a) a y-distance, which is the distance between the aligned signals; and b) an x-distance that measures the amount of warping needed to align the signals. We focus on the task of clustering and classifying objects, using acoustic spectrum (acoustic color), which is complicated by the uncertainties in aspect angles at data collections. Small changes in the aspect angles corrupt signals in a way that amounts to compositional noise. We demonstrate the use of the developed metrics in classification of acoustic color data and highlight improvements in signal classification over current methods.

Scaled laboratory experiments are conducted to assess the efficacy of iterative, single-channel time reversal for enhancement of monostatic returns from resonant spheres in the free field and buried in a sediment phantom. Experiments are performed in a water tank using a broad-band piston transducer operating between 0.4 and 1.5 MHz and calibrated using free surface reflections. Solid and hollow metallic spheres, 6.35 mm in diameter, are buried in a consolidation of 128-microm-mean- diameter spherical glass beads. The procedure consists of exciting the target object with a broadband pulse, sampling the return using a finite time window, reversing the signal in time, and using this reversed signal as the source waveform for the next interrogation. Results indicate that the spectrum of the returns rapidly converges to the dominant mode in the backscattering response of the target. Signal-to-noise enhancement of the target echo is demonstrated for a target at several burial depths. Images generated by scanning the transducer over the location of multiple buried targets demonstrate the ability of the technique to distinguish between targets of differing type and to yield an enhancement of different modes within the response of a single target as a function of transducer position and processing bandwidth.

The need for robust teleoperated robotic arms is increasing with respect to particular dangerous maritime missions. These missions might include deactivation of underwater mines, underwater salvage, or pipeline repair. In the past, robotic arms with low degrees of freedom were not always feasible for such operations, as the lack of free motion prevented their uses in locations with small space for maneuverability. With higher degrees of freedom, the arms are able to maneuver in tighter spaces and avoid obstacles as well. The increase in the number of degrees of freedom incurs an increase in the computational complexity for determining arm poses. With respect to the 7 degrees of freedom (DOF) Schunk arm, we make observations that allow for the derivation of systems of equations to solve the inverse kinematics problem. Furthermore, we show how to solve the systems such that closed form solutions can be obtained. This approach allows us to give and prove a characterization of the number of solutions with respect to certain conditions. As a surrogate test platform for maritime missions, we have developed a simulation that uses the Robot Operating System (ROS) and ROS visualization (rviz) to simulate the moving of the arm.

A common problem in genomics is to test for associations between two or more genomic features, typically represented as intervals interspersed across the genome. Existing methodologies can test for significant pairwise associations between two genomic intervals; however, they cannot test for associations involving multiple sets of intervals. This limits our ability to uncover more complex, yet biologically important associations between multiple sets of genomic features. We introduce GINOM (Genomic INterval Overlap Model), a new method that enables testing of significant associations between multiple genomic features. We demonstrate GINOM's ability to identify higher-order associations with both simulated and real data. In particular, we used GINOM to explore L1 retrotransposable element insertion bias in lung cancer and found a significant pairwise association between L1 insertions and heterochromatic marks. Unlike other methods, GINOM also detected an association between L1 insertions and gene bodies marked by a facultative heterochromatic mark, which could explain the observed bias for L1 insertions towards cancer-associated genes.

Abstract In the construction of an armor for ballistic protection, fibers are used in the form of a laminated composite bonded to the back of the frontal ceramic layer. The composite layer dissipates energy transmitted through the ceramic layer and controls the spall. To absorb energy locally and to spread it out fast, fibers in the composite layer must have high toughness and tensile wave speed as quantified by a primary performance index called normalizing velocity. The goal of this investigation is to increase the normalizing velocity of ultra‐high molecular weight (UHMWPE) fiber that is widely used in ballistic protection. The structure of UHMWPE is modified by hybridizing with nylon and reinforcing with carbon nanotubes. Fibers are extruded by melt‐spinning. The concentration of nylon and nanotubes is 18 and 2 wt%, respectively. After extrusion, fibers are strain‐hardened by cyclic loading to align UHMWPE molecules and nanotubes along the fiber axis. Tensile properties are determined to calculate normalizing velocity. Normalizing velocities up to 1270 m/s were obtained for the modified fiber which outperforms Spectra‐2000 and Dyneema‐SK75 by 44%–57%. Materials chemistry and structure of the fiber are investigated through differential scanning calorimetry (DSC), Raman Spectroscopy, and scanning electron microscope (SEM). It was observed that micro‐droplet formation by the nylon phase during hybridization promotes interface sliding of UHMWPE ligaments and elevates the fracture strain. Raman and SEM examination demonstrates that embedded nanotubes get aligned along the fiber axis due to strain hardening and co‐continuously deform with UHMWPE sharing the load.

In previous work, a variant of Waterman's transition (T) matrix utilizing an ansatz for problematic outgoing basis functions in standard formulations was proposed and demonstrated to improve the stability of free-field acoustic scattering calculations for elongated axisymmetric elastic objects. The ansatz replaced the basis causing instability with one consisting of low-order spherical functions made complete by distributing the functions along the axis within the object. Unfortunately, these bases are not as useful for expanding outgoing source fields along oblate axisymmetric surfaces. However, related work by Doicu, Eremin, and Wriedt, [Acoustic & Electromagnetic Scattering Analysis Using Discrete Sources, Academic Press, London (2000)], suggests using an alternate basis of low-order spherical functions made complete by analytically continuing them into the complex plane of the object's axial coordinate, distributing them along the imaginary axis of this plane. This paper will show that this alternative does extend the range of stability of our T-matrix formulation for highly oblate axisymmetric objects to frequencies attainable with competing spheroidal-basis T-matrix formulations. Nevertheless, the range is not as great as achieved for prolate shapes and an analysis of the residual noise sources suggest more optimal basis sets are possible that further stabilize scattering computations for such shapes.

We are faced with the problem of optimally placing a heterogeneous team of sensors and effector robots in an area while taking into account the environment, anticipated arrival traffic, and desired power consumption of the team. We stage the problems of anticipating arrival traffic and determining a proper power schedule as an adversarial game, incorporating our analysis of the game in the objective function which evaluates sensor positions. We obtain the set of sensor positions which performs best at the desired power consumption, evaluating the mixed strategy of sensor activity that best counters the anticipated potential arrival paths. To determine an approximate global optima for a large number of heterogeneous nodes, we employ Adaptive Simulated Annealing (ASA) to ensure our algorithm is flexible over a varied range of scenarios. We compare the proposed algorithm to a gradient-based greedy placement algorithm with a uniform power schedule within simulation.

The submarine H.L. Hunley was the first submarine to sink an enemy ship during combat; however, the cause of its sinking has been a mystery for over 150 years. The Hunley set off a 61.2 kg (135 lb) black powder torpedo at a distance less than 5 m (16 ft) off its bow. Scaled experiments were performed that measured black powder and shock tube explosions underwater and propagation of blasts through a model ship hull. This propagation data was used in combination with archival experimental data to evaluate the risk to the crew from their own torpedo. The blast produced likely caused flexion of the ship hull to transmit the blast wave; the secondary wave transmitted inside the crew compartment was of sufficient magnitude that the calculated chances of survival were less than 16% for each crew member. The submarine drifted to its resting place after the crew died of air blast trauma within the hull.

Abstract We address a class of definite integrals known as Berndt-type integrals, highlighting their role as specialized instances within the integral representation framework of the Barnes-zeta function. Building upon the foundational insights of Xu and Zhao, who adeptly evaluate these integrals using rational linear combinations of Lambert-type series and derive closed-form expressions involving products of $$\Gamma ^4(1/4)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup> <mml:mi>Γ</mml:mi> <mml:mn>4</mml:mn> </mml:msup> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>/</mml:mo> <mml:mn>4</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> </mml:math> and $$\pi ^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>π</mml:mi> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:math> , we uncover direct evaluations of the Barnes-zeta function. Moreover, our inquiry leads us to establish connections between Berndt-type integrals and Jacobi elliptic functions, as well as moment polynomials investigated by Lomont and Brillhart, a relationship elucidated through the seminal contributions of Kuznetsov. In this manner, we extend and integrate these diverse mathematical threads, unveiling deeper insights into the intrinsic connections and broader implications of Berndt-type integrals in special function and integration theory.

Deployment and retrieval strategies for UneXploded Ordnance (UXO) in nearshore test beds face challenges for maintaining required ground truth, as this region of very-shallow water may be both hydrodynamically energetic and morphodynamically active. The Naval Surface Warfare Center Panama City Division (NSWC PCD) and the Naval Research Laboratory South (NRL South) were recently tasked by the Environmental Security Technology Certification Program (ESTCP) to set up such a test bed in 0-5 m water depth and demonstrate a capability to deploy and maintain ground truth on UXO surrogates over a period required to execute tests of multiple systems. In addition to the depths specified, a football-field sized test area able to accommodate seeding with up to 200 UXO and clutter items was requested. Systems fielded may include sonars, magnetometers, active ElectroMagnetic (EM) sensors, and Electro-Optic (EO) sensors deployed on seafloor platforms (e.g., autonomous crawlers, towed sleds), swimming Autonomous Underwater Vehicles (AUV), surface craft and Unmanned Aircraft Systems (UAS). The initial focus was on a clean sand site with any clutter mapped if present. Here, a strategy to set up a suitable nearshore test bed off Shell Island, FL with untethered targets is described and shown to be feasible for potential sensor systems.

Traditional methods of system verification call for the repeated exercise of that system in its intended environment to give confidence that it will operate as designed. Autonomous systems, however, are systems designed for sophisticated operation in stochastic environments that specifically handle the unexpected; testing all possible operational scenarios for such systems is intractably complex. In order to address this challenge, we propose a framework by which these complex systems can be represented as collections of individual abilities, each of which can be independently verified based on their inputs and outputs. We then develop a corresponding mathematical framework to provide assurance of performance against desired mission parameters by composing the results of these component abilities.

Abstract Optimal transportation theory is an area of mathematics with real‐world applications in fields ranging from economics to optimal control to machine learning. We propose a new algorithm for solving discrete transport (network flow) problems, based on classical auction methods. Auction methods were originally developed as an alternative to the Hungarian method for the assignment problem, so the classic auction‐based algorithms solve integer‐valued optimal transport by converting such problems into assignment problems. The general transport auction method we propose works directly on real‐valued transport problems. Our results prove termination, bound the transport error, and relate our algorithm to the classic algorithms of Bertsekas and Castañón.

Multipath signals present problems in a variety of signal processing application. Spatial domain approaches are often used to minimize these unwanted signals. This paper explores a time domain approach that can effectively eliminate multipath signals. The key to this approach is the use of time-shift operators. These operators allow the problem to be inverted and the original signal to be recovered.

This effort seeks to evaluate the viability of applying the principles of centrifugal, radial flow turbomachinery to propulsion/control effectors for small unmanned underwater vehicles (UUVs). Such a device would be well-suited to augmenting an autonomous vehicle's control authority in adverse underwater environments which may include surface waves and currents. Two candidate thrusters have been designed from scratch, fabricated, tested, and simulated for several scenarios of interest. These thrusters are “podded” in the sense that they are capable of rotating and directing thrust within the plane of rotation which would be tangential to a cylindrical vehicle's body surface. Physical and simulated experiments thus far involve thrusters which are isolated, that is, apart from a vehicle, in an otherwise quiescent fluid for basic thrust and torque loading measurements. Reynolds-averaged Navier-Stokes (RANS)-based finite volume methods with a multiple reference frame (MRF) approach for rotating flows were used to accomplish the numerical simulations. The v <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> _ f eddy viscosity model was used for turbulence closure. For the in-water physical tests, the thrusters were mounted to the end of a cantilever-type load cell for thrust force measurement. Lessons learned from test results with the first candidate thruster led to design changes and subsequent improvements reflected in the second prototype while adhering to vehicle geometry constraints. Preliminary results indicate promising performance metrics for integration with UUVs with satisfactory efficiency.

We present a node placement algorithm for planning the deployment of a heterogeneous, underwater sensor network. Typical node placement algorithms do not account for heterogeneous node types and consequently, do not always provide accurate estimates for the total probability of success for the overall mission objective. In our approach, we derive an objective function that couples the probability of success for all node types to be used by a mixed-integer linear programming (MILP) solver for optimal placement. To reduce the computational intensity associated with the MILP-based approach, we provide an algorithm that converts the original optimization problem into several smaller optimization problems. We also describe the accompanying MILP framework that we have developed to create and maintain MILP problems.