NSWC Corona Division

Recently, operators of complex systems such as aircraft, power plants, and networks, have been emphasizing the need for online health monitoring for purposes of maximizing operational availability and safety. The discipline of prognostics and health management (PHM) is being formalized to address the information management and prediction requirements for addressing these needs. In this paper, we will explore how standards currently under development within the IEEE can be used to support PHM applications. Particular emphasis will be placed on the role of PHM and PHM-related standards with Department of Defense (DOD) automatic test systems-related research.

The many activities that fall in the domain of test can be modeled as processes and thus can benefit from the discipline of process improvement. Process improvement is itself a process that helps organizations deliver better product, more quickly, at a competitive price. The methods of process improvement are themselves evolving. Two major schools of process improvement of the 1990s, six-sigma and lean manufacturing, are merging to a unified methodology to gain the advantages of each school. This paper overviews concepts and tools from each school. This paper also contains methods and tools from the training-within-industry (TWI) service training program, which provides a training foundation for present day lean six-sigma process improvement.

There is no doubt that system complexity is increasing. There are a number of ramifications of this increase in complexity, besides higher performance. On one hand conventional means of testing are being overwhelmed by the complexity. On the other there are more sources of information about the system. System data is fragmented by time and discipline. Early design data is not available during the operational phase. Design data is often segregated from test data. Even within a particular discipline, e.g. diagnostics, data is fragmented. Few diagnostic reasoners can exchange data. One approach to dealing with the complexity issues is to integrate these sources of information into a single picture of the state of the system. This is the approach taken by the SCC20 Diagnostic and Maintenance Control (DMC) subcommittee. The DMC is developing a family of standards that are product information exchange standards for test, diagnosis, and maintenance. This paper describes the current efforts by the DMC to integrate data from a wide range of sources into a "picture" of the diagnostic and maintenance state of a system.

The characteristics of non-line-of-sight (NLOS) ultraviolet (UV) overwater communication channels under shore-to-vessel conditions and multiple scattering effects is modeled using Monte Carlo simulations. The field experiment measured received photon distribution, and calculated path loss at distances of up to 164 meters with the support of a GPSsynchronized accelerometer. Key parameters, such as transceiver elevation angles, water surface reflection index, airborne humidity, pollution, and temperature, were considered and analyzed in path loss simulations to more accurately compare with measured data. These channel modeling and experimental results will serve as the foundation for further study of the NLOS UV overwater and maritime communication system.

The nature of test set programming can be tedious and repetitive. A test engineer can often fall victim to puffing blinders on when programming by overlooking errors when reviewing their own work. To avoid this, it makes sense to treat software like a published work where a reviewer, independent of the original programming team, checks the software for design, quality, and errors. This paper describes a disciplined and consistent process for reviewing Automatic Test Equipment (ATE) software. This type of independent review process is comprised of four major steps: Receiving, Processing, Reporting, and Following-Up. It can be conducted and repeated throughout the development life cycle to improve the quality of the software. Early involvement can influence design changes that could lead to simpler and more manageable software. Several errors can be detected prior to its release by reviewing the software with software tools such as PC-Lint/spl trade/ or Understand for C++/spl trade/. Having the discipline to follow this simple process can bring about software manageability for future modifications, easier to read software, and software that contains fewer errors.

The Department of Defense (DOD) has recognized the importance of improving asset management and has created Item Unique Identification numbers (IUIDs) to improve the situation. IUIDs will be used to track financial and contract records and obtain location and status information about parts in DoD inventory. IUIDs will also support data collection for weapon systems from build, test, operations, maintenance, repair, and overhaul histories. In addition to improving the overall logistics process, IUIDs offer an opportunity to utilize asset-specific data to improve system maintenance and support. An Office of the Secretary of Defense (OSD) Pilot Project to implement IUID on a Navy weapon system presents an immediate opportunity to evaluate this use of IUID data. This paper reports on experiments conducted to see if a set of asset-specific diagnostic classifiers trained on subsets of data is more accurate than a general, composite classifier trained on all of the data. In general, it is determined that the set is more accurate than the single classifier given enough data. However, other factors play an important role such as system complexity and noise levels in the data. Additionally, the improvements found do not arise until larger amounts of data are available. This suggests that future work should concentrate on tying the process of data collection to the estimation of the associated probabilities.

The study of propagation medium effects on lasers continues to be an active area of research. High energy laser (HEL) propagation through planetary atmosphere is particularly nuanced as the beam generates its own flow field and suffers from additional degrading effects. Herein, we construct experimental setups conducive to probing the physics of the laser-atmosphere interaction and generating validation datasets for high fidelity predictive software. Measured and derived parameters are presented, and predictive models are generated utilizing random forest regression.

The LabWindows/CVItrade "C" language compiler has no built in method of handling errors that occur in functions or drivers. The usual method is to use an "if" statement for every function call made, but this is very tedious and generates a lot of code. Often programs simply ignore errors and keep on going and depend on an eventual test failure to prevent acceptance of the item being tested. This leads to the wrong conclusion about what really went wrong. Other languages such as C++ have "try", "catch" and "throw" for exception handling. This paper explores several methods of handling the problem with much less code

Instruments have become complex and so has the driver software for using them. This paper discusses a high-level application program interface (API) that handles the complexity instead of the test application. The API is normally written in the same language the test application uses. The API can be reused when testing similar devices. All calls made to the instrument drivers are located in the API and not in the main application to isolate them from the hardware. The API can use all driver types; interchangeable virtual instruments (IVI), Plug and Play (PnP) or custom as long as the native language supports it. The API can improve performance through various techniques such as state caching or parallel processing. Common setups and measurements are put in the API to avoid duplication of code. The API includes automatic switching by specifying the instrument and test point using symbolic names having the software safely determine the correct path. Using an API simplifies test procedures, makes system upgrades easier, enhances performance and automatically handles all instrumentation errors.

The temperature in natural convection problems is, under mild data assumptions, uniformly bounded in time. This property has not yet been proven for the standard finite element method (FEM) approximation of natural convection problems with nonhomogeneous partitioned Dirichlet boundary conditions, e.g., the differentially heated vertical wall and Rayleigh–Bénard problems. For these problems, only stability in time, allowing for possible exponential growth of <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="double-vertical-bar upper T Subscript h Superscript n Baseline double-vertical-bar"> <mml:semantics> <mml:mrow> <mml:mo fence="false" stretchy="false"> ‖ </mml:mo> <mml:msubsup> <mml:mi>T</mml:mi> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi>h</mml:mi> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi>n</mml:mi> </mml:mrow> </mml:msubsup> <mml:mo fence="false" stretchy="false"> ‖ </mml:mo> </mml:mrow> <mml:annotation encoding="application/x-tex">\| T^{n}_{h} \|</mml:annotation> </mml:semantics> </mml:math> </inline-formula> , has been proven using Gronwall’s inequality. Herein, we prove that the temperature approximation can grow at most linearly in time provided that the first mesh line in the finite element mesh is within <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="script upper O left-parenthesis upper R a Superscript negative 1 Baseline right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi class="MJX-tex-caligraphic" mathvariant="script">O</mml:mi> </mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:mi>R</mml:mi> <mml:msup> <mml:mi>a</mml:mi> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo> − </mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:annotation encoding="application/x-tex">\mathcal {O} (Ra^{-1})</mml:annotation> </mml:semantics> </mml:math> </inline-formula> of the nonhomogeneous Dirichlet boundary.

The study of propagation medium effects on lasers continues to be an active area of research. High energy laser (HEL) propagation through planetary atmosphere is particularly nuanced as the beam generates its own flow field and suffers from additional degrading effects. Herein, we construct experimental setups conducive to probing the physics of the laser-atmosphere interaction and generating validation datasets for high fidelity predictive software. Measured and derived parameters are presented and predictive models are generated utilizing random forest regression.

During a calibration test, a unit under test (UUT) is compared with a test instrument to determine if the error in the UUT is smaller than some predefined tolerances. Generally, the resultant data ...

The study of propagation medium effects on lasers continues to be an active area of research. High energy laser (HEL) propagation through planetary atmosphere is particularly nuanced as the beam generates its own flow field and suffers from additional degrading effects. Herein, we construct experimental setups conducive to probing the physics of the laser-atmosphere interaction and generating validation datasets for high fidelity predictive software. Measured and derived parameters are presented and predictive models are generated utilizing random forest regression.