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Artificial ice shapes of various geometric fidelity were tested on a wing model based on the Common Research Model. Low Reynolds number tests were conducted at Wichita State University’s Walter H. Beech Memorial Wind Tunnel utilizing an 8.9% scale model, and high Reynolds number tests were conducted at ONERA’s F1 wind tunnel utilizing a 13.3% scale model. Several identical geometrically-scaled ice shapes were tested at both facilities, and the results were compared at overlapping Reynolds and Mach numbers. This was to ensure that the results and trends observed at low Reynolds number could be applied and continued to high, near-flight Reynolds number. The data from Wichita State University and ONERA F1 agreed well at matched Reynolds and Mach numbers. The lift and pitching moment curves agreed very well for most configurations.

We are developing a flexible and general methodology for real-time monitoring of acoustic emissions in machining applications. The goal of this work is to develop an approach to in-process monitoring which allows continuous assessment of tool wear and early warning of process exceptions. The nature of metal removal processes creates short-lived vibrations that carry information about the condition of the cutting tool and quality of cut. We wish to extract and represent these transient events without loss of important spectral structure. Other challenges include the need for system training data selection in the absence of expert labeled data, the modeling of short-term time evolution, and efficient real-time operation on an inexpensive computing platform.

In applications ranging from design of customized vehicle interiors to virtual testing of biomedical devices, the processes of modeling, design and analysis involve the simultaneous treatment of artifacts (i.e., parts designed by humans) and anatomical structures. An inherent conflict arises because the geometric descriptions are completely different. Artifact descriptions are typically the output of computer-aided design (CAD) software and consist of a collection of parametric patches that comprise the boundary of the artifact. In stark contrast, the native description of an anatomical structure typically consists of an image stack obtained using a volumetric scanning technology such as computed tomography (CT) or magnetic resonance imaging (MRI). Current practice for simultaneously dealing with both categories of entities involves working primarily in the world of CAD.

In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material.

Aerodynamic assessment of icing effects on swept wings is an important component of a larger effort to improve three-dimensional icing simulation capabilities. An understanding of ice-shape geometric fidelity and Reynolds and Mach number effects on iced-wing aerodynamics is needed to guide the development and validation of ice-accretion simulation tools. To this end, wind-tunnel testing was carried out for 8.9% and 13.3% scale semispan wing models based upon the Common Research Model airplane configuration. Various levels of geometric fidelity of an artificial ice shape representing a realistic glaze-ice accretion on a swept wing were investigated. The highest fidelity artificial ice shape reproduced all of the three-dimensional features associated with the glaze ice accretion. The lowest fidelity artificial ice shapes were simple, spanwise-varying horn ice geometries intended to represent the maximum ice thickness on the wing upper surface.

This study investigates using driver prediction to anticipate energy usage over a 160-meter look-ahead distance for a series, plug-in, hybrid-electric vehicle to improve conventional thermostatic powertrain control. Driver prediction algorithms utilize a hidden Markov model to predict route and a regression tree to predict speed over the route. Anticipated energy consumption is calculated by integrating force vectors over the look-ahead distance using the predicted incline slope and vehicle speed. Thermostatic powertrain control is improved by supplementing energy produced by the series generator with regenerative braking during events where anticipated energy consumption is negative, typically associated with declines or decelerations.

Map matching determines which road a vehicle is on based on inaccurate measured locations, such as GPS points. Simple algorithms, such as nearest road matching, fail often. We introduce a new algorithm that finds a sequence of road segments which simultaneously match the measured locations and which are traversable in the time intervals associated with the measurements. The time constraint, implemented with a hidden Markov model, greatly reduces the errors made by nearest road matching. We trained and tested the new algorithm on data taken from a large pool of real drivers.

The repairing of commercial aircraft is a complex task. Service engineers at Boeing's Commercial Aviation Services group specialize in providing crucial repair information and technical support for its many customers. This paper details factors that influence Boeing's response time to service requests and how to improve it. Information pertaining to over 5000 service requests from 2008 and 2009 was collected. From analysis of this data set, important findings were discovered. One major finding is that between 6 and 8 percent of service requests are late because time/date stamps used in reports were created in a different time zone.

At Boeing’s commercial aircraft production in Everett Washington, the organization that supplies parts to the factory floor (known internally as Company 625) is revising their methods. A new process will deliver parts in kits that correspond to the installation plans used by the mechanics. Several alternative methods are under review. The authors used simulation methods to evaluate and compare these alternatives. This study focuses on the category of parts known as standard fasteners (‘standards’). Through direct observation, interviews with experts, as well as time and motion study, the process flow of the kitting operation was mapped A simulation model was created using the simulation software ARENA to examine two scenarios: the current kitting operation in the factory cribs and the proposed centralization of kitting operation in the Company 625.

This paper develops and tests algorithms for predicting the end-to-end route of a vehicle based on GPS observations of the vehicle's past trips. We show that a large portion a typical driver's trips are repeated. Our algorithms exploit this fact for prediction by matching the first part of a driver's current trip with one of the set of previously observed trips. Rather than predicting upcoming road segments, our focus is on making long term predictions of the route. We evaluate our algorithms using a large corpus of real world GPS driving data acquired from observing over 250 drivers for an average of 15.1 days per subject. Our results show how often and how accurately we can predict a driver's route as a function of the distance already driven.

A composite of an aluminum matrix reinforced by short TiNi shape memory alloy (SMA) fibers was fabricated. The processing and thermomechanical behaviors of the composite TiNi/Al6061 were investigated experimentally and analytically. Optimal hot-pressing conditions of TiNi/Al6061 processing were identified. The shape memory effect (SME) was activated by prestraining the composite at the temperature between Ms and As, followed by heating up to Af. SME on mechanical properties, such as microhardness, yield stresses of the composite, were investigated. A computational model for the strengthening mechanism of the short fiber metal matrix composite was utilized to analyze SME on yield stress of the composite. Yield stress of the composite as a function of prestrain was predicted numerically and verified experimentally.