NSWC Dahlgren Division

The modeling of forces during needle insertion into soft tissue is important for accurate surgical simulation, preoperative planning, and intelligent robotic assistance for percutaneous therapies. We present a force model for needle insertion and experimental procedures for acquiring data from ex vivo tissue to populate that model. Data were collected from bovine livers using a one-degree-of-freedom robot equipped with a load cell and needle attachment. computed tomography imaging was used to segment the needle insertion process into phases identifying different relative velocities between the needle and tissue. The data were measured and modeled in three parts: 1) capsule stiffness, a nonlinear spring model; 2) friction, a modified Karnopp model; and 3) cutting, a constant for a given tissue. In addition, we characterized the effects of needle diameter and tip type on insertion force using a silicone rubber phantom. In comparison to triangular and diamond tips, a bevel tip causes more needle bending and is more easily affected by tissue density variations. Forces for larger diameter needles are higher due to increased cutting and friction forces.

A new density-based clustering algorithm, RNN-DBSCAN, is presented which uses reverse nearest neighbor counts as an estimate of observation density. Clustering is performed using a DBSCAN-like approach based on k nearest neighbor graph traversals through dense observations. RNN-DBSCAN is preferable to the popular density-based clustering algorithm DBSCAN in two aspects. First, problem complexity is reduced to the use of a single parameter (choice of k nearest neighbors), and second, an improved ability for handling large variations in cluster density (heterogeneous density). The superiority of RNN-DBSCAN is demonstrated on several artificial and real-world datasets with respect to prior work on reverse nearest neighbor based clustering approaches (RECORD, IS-DBSCAN, and ISB-DBSCAN) along with DBSCAN and OPTICS. Each of these clustering approaches is described by a common graph-based interpretation wherein clusters of dense observations are defined as connected components, along with a discussion on their computational complexity. Heuristics for RNN-DBSCAN parameter selection are presented, and the effects of k on RNN-DBSCAN clusterings discussed. Additionally, with respect to scalability, an approximate version of RNN-DBSCAN is presented leveraging an existing approximate k nearest neighbor technique.

Abstract The Coupled Air–Sea Processes and Electromagnetic Ducting Research (CASPER) project aims to better quantify atmospheric effects on the propagation of radar and communication signals in the marine environment. Such effects are associated with vertical gradients of temperature and water vapor in the marine atmospheric surface layer (MASL) and in the capping inversion of the marine atmospheric boundary layer (MABL), as well as the horizontal variations of these vertical gradients. CASPER field measurements emphasized simultaneous characterization of electromagnetic (EM) wave propagation, the propagation environment, and the physical processes that gave rise to the measured refractivity conditions. CASPER modeling efforts utilized state-of-the-art large-eddy simulations (LESs) with a dynamically coupled MASL and phase-resolved ocean surface waves. CASPER-East was the first of two planned field campaigns, conducted in October and November 2015 offshore of Duck, North Carolina. This article highlights the scientific motivations and objectives of CASPER and provides an overview of the CASPER-East field campaign. The CASPER-East sampling strategy enabled us to obtain EM wave propagation loss as well as concurrent environmental refractive conditions along the propagation path. This article highlights the initial results from this sampling strategy showing the range-dependent propagation loss, the atmospheric and upper-oceanic variability along the propagation range, and the MASL thermodynamic profiles measured during CASPER-East.

The use of a kinematic constraint as a pseudomeasurement in the tracking of constant-speed, maneuvering targets is considered. The kinematic constraint provides additional information about the target motion that can be processed as a pseudomeasurement to improve tracking performances. A new formulation of the constraint equation is presented, and the rationale for the new formulation is discussed. The filter using the kinematic constraint as a pseudomeasurement is shown to be unbiased, and sufficient conditions for stochastic stability of the filter are given. Simulated tracking results are given to demonstrate the potential that the new formulation provides for improving tracking performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

We experimentally demonstrate single beam directional perfect absorption (to within experimental accuracy) of $p$-polarized light in the near-infrared using unpatterned, deep subwavelength films of indium tin oxide (ITO) on Ag. The experimental perfect absorption occurs slightly above the epsilon-near-zero (ENZ) frequency of ITO, where the permittivity is less than 1 in magnitude. Remarkably, we obtain perfect absorption for films whose thickness is as low as \ensuremath{\sim}1/50th of the operating free-space wavelength and whose single pass attenuation is only \ensuremath{\sim}5%. We further derive simple analytical conditions for perfect absorption in the subwavelength-film regime that reveal the constraints that the thin layer permittivity must satisfy if perfect absorption is to be achieved. Then, to get a physical insight on the perfect absorption properties, we analyze the eigenmodes of the layered structure by computing both the real-frequency/complex-wavenumber and the complex-frequency/real-wavenumber modal dispersion diagrams. These analyses allow us to attribute the experimental perfect absorption condition to the crossover between bound and leaky behavior of one eigenmode of the layered structure. Both modal methods show that perfect absorption occurs at a frequency slightly larger than the ENZ frequency, in agreement with experimental results, and both methods predict a second perfect absorption condition at higher frequencies, attributed to another crossover between bound and leaky behavior of the same eigenmode. Our results greatly expand the list of materials that can be considered for use as ultrathin perfect absorbers and provide a methodology for the design of absorbing systems at any desired frequency.

Reverberation chambers (RC), a name inspired in room acoustics, are also known in literature as reverberating, reverb, mode-stirred or mode-tuned chambers. In their basic form, they consist of a shielded metallic enclosure, forming a cavity resonator, together with some mode-stirring mechanism. The main goal of such stirring mechanism is to generate an amplitude-varying electromagnetic field that is ideally statistically uniform.

Over the past several years, the Naval Surface Warfare Center, Dahlgren Division (NSWC-DD) and its contractors have used vented test chambers to evaluate the performance of impactinitiated energetic materials. These chambers are initially sealed but have a thin steel cover plate through which a test specimen is launched onto a steel anvil on the interior. During this impact process, the test specimen perforates the thin plate and leaves a vent hole through which chamber gases are vented as the reaction takes place on the interior. The test chamber includes a variety of pressure and light measurements to gauge the performance of the test specimen. The quasi-static pressures have been the primary performance metric used to judge the performance of the material; these pressures most directly relate to the material’s ability to damage a target. This paper will derive the fundamental relationships between the peak quasistatic pressure and the total energy deposited into the gas within the chamber, thereby allowing calorimetric measurements using the vented chamber system. Particular attention will be paid to the uncertainties and assumptions associated with this derivation, including assumptions about gas properties, venting from the chamber, and distribution of the energy between kinetic and potential energy in the gas-phase.

Recently, there has been great interest in evaluating the shielding effectiveness of physically small enclosures (all linear dimensions between 0.1 and 2 m) using a reverberation chamber. In cases where the enclosure is also electrically small (linear dimensions on the order of a free-space wavelength or less), the enclosure supports only discrete resonant modes whose lineshapes have little or no overlap in frequency. This sparsely moded or “undermoded” cavity poses a number of complex challenges to defining and measuring shielding effectiveness. This study contributes to the development of a measurement process for evaluating shielding effectiveness in electrically small enclosures. Specifically, we demonstrate the performance advantages of a traveling-wave antenna (long-wire probe) as a means of fully sampling the field throughout the volume of the enclosure without the need for multiple, wall-mounted probes. Furthermore, the good impedance match of the long-wire antenna permits a large dynamic range in the shielding effectiveness measurements. A simple and fast test method is presented that is accurate and repeatable, and embodies the desired “dovetailing” of shielding effectiveness values obtained as frequency increases and the enclosure transitions from undermoded to overmoded operation. Finally, a rudimentary statistical analysis is provided to assess typical uncertainties inherent in the shielding effectiveness evaluation.

This paper provides the reader with a very brief introduction to some of the theory and methods of text data mining. The intent of this article is to introduce the reader to some of the current methodologies that are employed within this discipline area while at the same time making the reader aware of some of the interesting challenges that remain to be solved within the area. Finally, the articles serves as a very rudimentary tutorial on some of techniques while also providing the reader with a list of references for additional study.

The use of personal protective gear made from omniphobic materials that easily shed drops of all sizes could provide enhanced protection from direct exposure to most liquid-phase biological and chemical hazards and facilitate the postexposure decontamination of the gear. In recent literature, lubricated nanostructured fabrics are seen as attractive candidates for personal protective gear due to their omniphobic and self-healing characteristics. However, the ability of these lubricated fabrics to shed low surface tension liquids after physical contact with other objects in the surrounding, which is critical in demanding healthcare and military field operations, has not been investigated. In this work, we investigate the depletion of oil from lubricated fabrics in contact with highly absorbing porous media and the resulting changes in the wetting characteristics of the fabrics by representative low and high surface tension liquids. In particular, we quantify the loss of the lubricant and the dynamic contact angles of water and ethanol on lubricated fabrics upon repeated pressurized contact with highly absorbent cellulose-fiber wipes at different time intervals. We demonstrate that, in contrast to hydrophobic nanoparticle coated microfibers, fabrics encapsulated within a polymer that swells with the lubricant retain the majority of the oil and are capable of repelling high as well as low surface tension liquids even upon multiple contacts with the highly absorbing wipes. The fabric supported lubricant-swollen polymeric films introduced here, therefore, could provide durable and easy to decontaminate protection against hazardous biological and chemical liquids.

This paper describes a set of metrics that will help administrators of distributed, real-time (clustered) computer facilities to select the best intrusion detection system for their facilities. The metrics herein are the subset of our general metric set that particularly impact real-time and distributed processing issues. We discuss related works in this field, the role of intrusion detection in information assurance, some basic classes of intrusion detection systems, a general architecture of network intrusion detection systems, and the scorecard metrics and their application to real-time and distributed processing systems. Finally we discuss the lessons we learned using a preliminary version of the metric scorecard to test three commercial intrusion detection systems and the opportunities for further work in this area.

The purpose of this investigation was to determine what approach is best to deal with the question of how to choose the model transition matrix for the interactive multiple model filter. The desire is to determine an approach to choosing the model transition matrix that is "best" in some sense. In the study, many target tracking simulations were run using the interacting multiple models algorithm (IMM) with two models: constant velocity and constant acceleration. During these simulations, the transition matrix used and the target tracks used were varied to allow viewing of behavior of the IMM under different conditions. It is difficult to decide whether changing the probabilities gives better performance, since performance is not measured by one number, but by a balance of competing interests. Using a three-model IMM inputs were used in order to test which values should be on the diagonal and what effect changing the off-diagonal elements would have on the filter's behavior. The results obtained imply that having three models is not necessary except in exceptional cases. This leads one to pose the question: Are more models better?.

In this paper, an approach for detecting branch points using a Shack–Hartmann wavefront sensor (SHWFS) is introduced. Simulated data are created using Monte Carlo wave-optics simulations of varying turbulence strengths. It is assumed that the presence of a branch point in the SHWFS subaperture lenslet pupils causes appreciable beam spreading in the image plane. Therefore, second-moment statistics are used to quantify beam spread for each subaperture image-plane irradiance pattern. Thresholding is then employed to dictate what degree of beam spreading is sufficient to determine the presence of a branch point. Three different thresholds are imposed: liberal, moderate, and conservative. Furthermore, the collected SHWFS signal is treated as analog, digitized, and digitized with three levels of additive noise: low, moderate, and high. Monte Carlo simulations are conducted for 20 different spherical-wave Rytov numbers ( R SW ) ranging from 0.1 to 2.0. It was found that when conservative thresholds were employed, for the analog signal, digitized signal with no noise, and digitized signal with low noise, the percent of detections mostly comprised actual branch points, and false-positive detections were largely minimized. For the liberal thresholding cases, many false-positives were detected for all SHWFS signal types; however, significantly more branch points were also detected. The results presented in this paper are encouraging, and such results will inform efforts to develop branch-point tolerant least-squares reconstructors or use a SHWFS for optical-turbulence characterization in high- R SW environments.

In this paper, we present a multifield and multiscale theory leading to derivations of electric and thermal conductivities for the interface between two rough surfaces in contact, activated by mechanical load and electric current pulses. At the macroscale, the proposed approach involves multifield coupling of conduction and induction currents, with heat conduction induced by joule heating. The structural mechanics of the conducting materials are also considered. At the mesoscale and microscale, the theory contains a Weierstrass-Mandelbrot description of the rough contact surface profilometry and an asperity-based comprehensive model, respectively. They are both combined to derive homogenized macroscale properties for the interface boundary. The mechanical pressure and the repulsion effect from electric current through the microcontacts are accounted for as well. The results of the numerical analysis illustrate the dependence of the derived properties on the surface characteristics, external load, and electric current. Finally, the entire framework is applied to an actual conductor configuration of hollow cylinders under compression and a high current pulse to demonstrate the feasibility of the entire approach. In addition to providing typical simulation results for all selected fields present during the experiment, we also provide a comparison between the experimentally acquired resistance and the numerically derived resistance to validate the contact theory.

In this paper, atmospheric optical turbulence strength is estimated for realistic airborne environments using a modified phase-variance approach, as well as a modified slope-discrepancy approach. Realistic airborne environments are generated using wave-optics simulations of a plane wave propagating through increasing strengths of homogeneous atmospheric optical turbulence, both with and without aero-optical contamination (from in-flight wavefront sensor data) and additive-measurement noise. In comparison to the modified phase-variance approach, the results show that the modified slope-discrepancy approach more accurately estimates atmospheric optical turbulence strength over a wide range of conditions. Such results are encouraging for realistic airborne environments because they can be scaled to different freestream conditions as long as the boundary layer is considered canonical.

Our problem of interest is to cluster vertices of a graph by identifying underlying community structure. Among various vertex clustering approaches, spectral clustering is one of the most popular methods because it is easy to implement while often outperforming more traditional clustering algorithms. However, there are two inherent model selection problems in spectral clustering, namely estimating both the embedding dimension and number of clusters. This article attempts to address the issue by establishing a novel model selection framework specifically for vertex clustering on graphs under a stochastic block model. The first contribution is a probabilistic model which approximates the distribution of the extended spectral embedding of a graph. The model is constructed based on a theoretical result of asymptotic normality for the informative part of the embedding, and on simulation results providing a conjecture for the limiting behavior of the redundant part of the embedding. The second contribution is a simultaneous model selection framework. In contrast with traditional approaches, our model selection procedure estimates embedding dimension and number of clusters simultaneously. Based on our conjectured distributional model, a theorem on the consistency of the estimates of model parameters is presented, providing support for the utility of our method. Algorithms for our simultaneous model selection (SMS) for vertex clustering are proposed, demonstrating superior performance in simulation experiments. We illustrate our method via application to a collection of brain graphs.

The Coupled Air-Sea Processes and Electromagnetic ducting Research (CASPER) is a multidisciplinary research initiative aimed at quantifying electromagnetic (EM) ducting and the associated atmospheric processes. The project involved two field campaigns on both coasts of the US. Coordinated measurements among research vessels/platforms and at the shore were made in both field campaigns resulting in a large amount of data for both the atmospheric environment and EM propagation. This paper presents a general overview of the second field campaign, CASPER-West and the ducting conditions encountered during the field campaign. Examples of the measured propagation are also given.

Radio-frequency wireless communications and sensor networks are currently being deployed in structures that comprise confined, reflective spaces that are electromagnetically coupled. Such structures are commonly found in aviation, shipping, automotive, and warehousing industries. In this paper, a general time-dependent model is presented whose solutions directly provide key properties of the wireless communications channel in multiply connected reverberant spaces. The model equations can be solved numerically for any number of cavities and for any level (weak or strong) of coupling between the cavities. The wireless channel properties investigated in this paper include power delay profile, rms time delay spread, coherence bandwidth, average received channel power, signal-strength fading statistics, and maximum field environment. Measured and modeled channel properties are presented for two and three coupled, highly multipath spaces. These channel model parameters aid in making electromagnetic compatibility assessments of wireless network emissions in these environments.

The hybrid inverter fed motor drive with two cascaded multilevel inverters is an attractive option for high performance high power applications such as naval ship propulsion systems due to a number of unique features. There is a natural split between a higher-voltage lower-frequency "bulk" inverter and a lower-voltage higher-frequency "conditioning" inverter in the cascaded system which matches the availability of semiconductor devices. Furthermore, the bulk inverter may be a commercial-off-the-shelf (COTS) motor drive meaning that only the conditioning inverter needs to be custom made. However, a drive involving a COTS bulk inverter would require a distributed conditioning inverter control which works completely independent of the bulk inverter control. In this paper, a set of distributed control methods are developed for the hybrid inverter drive with cascaded bulk and conditioning inverters, requiring only single dc source. Moreover, a solution to the practical problem of instant synchronization between the two inverters is presented. Laboratory measurements on a 3.7-kW induction motor drive validate the proposed control. Various practical considerations (such as low m-index performance and capacitor precharging options) are discussed and their solutions provided

Metasurfaces and metamaterials have been explored extensively in recent years for their ability to enable a variety of innovative microwave devices. However, because their exotic properties often arise from resonant structures, the large field enhancements under high-power microwave illumination can lead to dielectric breakdown and damage to the device. In order to develop metasurfaces and metamaterials capable of being utilized in high-power microwave applications, this paper investigates techniques for reducing the maximum field enhancement factor (MFEF) in several types of structures from the literature. Starting with a simple Sievenpiper metasurface, this paper evaluates the dependence of MFEF on the structure design parameters. For more complex metasurface geometries, a genetic algorithm is demonstrated that can evolve structures that have minimal MFEF. In addition, negative-index and low-index metamaterials are evaluated for field enhancement. By optimizing for low loss and by operating in the resonance tails, metamaterials with low MFEF can be realized for high-power applications. To illustrate this, a quad-beam focusing metamaterial lens is presented with an MFEF less than 5 over the entire operating band.