Search Results

Models for off-road vehicles, such as farm equipment and military vehicles, require an off-road tire model in order to properly understand their dynamic behavior on off-road driving surfaces. Extensive literature can be found for on-road tire modeling, but not much can be found for off-road tire modeling. This paper presents an off-road tire model that was developed for use in vehicle handling studies. An on-road, dry asphalt tire model was first developed by performing rolling road force and moment testing. Off-road testing was then performed on dirt and gravel driving surfaces to develop scaling factors that explain how the lateral force behavior of the tire will scale from an on-road to an off-road situation. The tire models were used in vehicle simulation software to simulate vehicle behavior on various driving surfaces. The simulated vehicle response was compared to actual maximum speed before sliding vs. turning radius data for the studied vehicle to assess the tire model.

The exponential increase in the number of aircrafts and air travelers has triggered new innovations which aim to make airline services more reliable and consumer friendly. Quick and efficient maintenance actions with minimum downtime are the need of the hour. Areas that have a large potential for improvement in this regard are the real time use of diagnostic data, filtering/elimination of nuisance faults and machine learning capabilities with respect to maintenance actions. Although, numerous LRUs installed on the aircraft generate massive amounts of diagnostic data to detect any possible issue or LRU failure, it is seldom used in real time. The turnaround time for LRU maintenance can be greatly reduced if the results of the diagnostics conducted during LRU normal operation is relayed to ground stations in real-time. This enables the maintenance engineers to plan ahead and initiate maintenance actions well before the aircraft lands and becomes available for maintenance.

This study pertains to motion control algorithms using statistical calculations based on relative displacement measurements, in particular where the rattle space is strictly limited by fixed end-stops and a load leveling system that allows for roll to go undetected by the sensors. One such application is the cab suspension of semi trucks that use widely-spaced springs and dampers and a load leveling system that is placed between the suspensions, near the center line of the cab. In such systems it is possible for the suspension on the two sides of the vehicle to settle at different ride heights due to uneven loading or the crown of the road. This paper will compare the use of two moving average signals (one positive and one negative) to the use of one root mean square (RMS) signal, all calculated based on the relative displacement measurement.

Automation on Validation and Verification (V&V) leveraging Formal Methods, and in particular Model Checking, is seeing an increasing use in the Aerospace domain. In recent years, Formal Methods have been used to verify systems and software and its correctness as a way to augment traditional methods relying on simulation and testing. Recent updates to the relevant Aerospace regulations (e.g. DO178C, DO331 and DO333) now have explicit provisions for utilization of models and formal methods. In a previous paper a compositional methodology for the verification of Aerospace Systems has been described with application to Electrical Power Generation and Distribution Systems. In this paper we present an expansion of the previous work in two directions. First, we describe the application of the methodology to the validation of Proximity Sensing Systems (PSS) requirements showing the effectiveness of the method to a new aerospace domain.

Formal Methods, and in particular Model Checking, are seeing an increasing use in the Aerospace domain. In recent years, Formal Methods are now commonly used to verify systems and software and its correctness as a way to augment traditional methods relying on simulation and testing. Recent updates to the relevant Aerospace regulations (e.g. DO178C, DO331 and DO333) now have explicit provisions for utilization of models and formal methods. At the system level, Model Checking has seen more limited uses due to the complexity and abstractions needed. In this paper we propose several methods to increase the capability of applying Model Checking to complex Aerospace Systems. An aircraft electrical power system is used to highlight the methodology. Automated model-based methods such as Cone of Influence and Timer Abstractions are described. Results of those simplifications, in combination with traditional Assume-Guarantee approaches will be shown for the Electric Power System application.

This study outlines a protocol for image data collection acquired from human volunteers. The data set will serve as the foundation of a consolidated effort to develop the next generation full-body Finite Element Analysis (FEA) models for injury prediction and prevention. The geometry of these models will be based off the anatomy of four individuals meeting extensive prescreening requirements and representing the 5th and 50th percentile female, and the 50th and 95th percentile male. Target values for anthropometry are determined by literature sources. Because of the relative strengths of various modalities commonly in use today in the clinical and engineering worlds, a multi-modality approach is outlined. This approach involves the use of Computed Tomography (CT), upright and closed-bore Magnetic Resonance Imaging (MRI), and external anthropometric measurements.

Modeling the tire forces and moments (F&M) generation, during combined slip maneuvers, which involves cornering and braking/driving at the same time, is essential for the predictive vehicle performance analysis. In this study, a new semi-empirical method is introduced to estimate the tire combined slip F&M characteristics based on flat belt testing machine measurement data. This model is intended to be used in the virtual tire design optimization process. Therefore, it should include high accuracy, ease of parameterization, and fast computational time. Regression is used to convert measured F&M into pure slip multi-dimensional interpolant functions modified by weighting functions. Accurate combined slip F&M predictions are created by modifying pure slip F&M with empirically determined shape functions. Transient effects are reproduced using standard relaxation length equations. The model calculates F&M at the center of the contact patch.

This paper studies the effect of different longitudinal load conditions, roundabout cross-sectional geometry, and different semi-truck pneumatic suspension systems on roll stability in roundabouts, which have become more and more popular in urban settings. Roundabouts are commonly designed in their size and form to accommodate articulated heavy vehicles (AHVs) by evaluating such affects as off-tracking. However, the effect of the roadway geometry in roundabouts on the roll dynamics of semi-tractors and trailers are equally important, along with their entry and exit configuration. , Because the effect of the roundabout on the dynamics of trucks is further removed from the immediate issues considered by roadway planner, at times they are not given as much consideration as other roadway design factors.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

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.

Computationally efficient tire models are needed to meet the timing and accuracy demands of the iterative vehicle design process. Axisymmetric, circumferentially isotropic, planar, discretized models defined by their quasi-static constraint modes have been proposed that are parameterized by a single stiffness parameter and two shape parameters. These models predict the deformed shape independently from the overall tire stiffness and the forces acting on the tire, but the parameterization of these models is not well defined. This work develops an admissible domain of the shape parameters based on the deformation limitations of a physical tire, such that the tire stiffness properties cannot be negative, the deformed shape of the tire under quasi-static loading cannot be dominated by a single harmonic, and the low spatial frequency components must contribute more than higher frequency components to the overall tire shape.

The complexity of software development is increasing unprecedentedly with every next generation of aircraft systems. This requires to adopt new techniques of software design and verification that could optimize the time and cost of software development. At the same time these techniques need to ensure high quality of software design and safety compliance to regulatory guidelines like DO-178C [1] and its supplements DO-330[2] and DO-331[3]. To arrive at new technologies one has to evaluate the alternate methods available for software design by developing models, integration of models, auto-code generation, auto test generation and also the performance parameters like time, effort, reuse and presentation needs to be evaluated. We have made an attempt to present summary of alternate design concept study, and edge of MBD over other design techniques.

Binder jetting of sand molds and cores for metal casting provides a scalable and efficient means of producing metal components with complex geometric features made possible only by Additive Manufacturing. Topology optimization software that can mathematically determine the optimum placement of material for a given set of design requirements has been available for quite some time. However, the optimized designs are often not manufacturable using standard metal casting processes due to undercuts, backdraft and other issues. With the advent of binder-based 3D printing technology, sand molds and cores can be produced to make these optimized designs as metal castings.

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.

Aircraft weight and center of mass are two critical design and operational parameters that have to be within a design envelope to ensure a safe and efficient operation of aircraft. Previous efforts to accurately determine aircraft weight and center of mass before takeoff using landing gear shock strut pressures have failed due to the distortion of measured pressures by shock strut seal friction. Currently, aircraft loading process is controlled with loading sheets and passenger/cargo weight estimation as there are no online measurement systems that can accurately and efficiently estimate aircraft weight and determine the center of mass location before takeoff. However, errors in loading sheets, shifting cargo and errors in weight estimation could lead to incorrect loading of aircraft and, consequently, increase the risk of accidents, particularly in cargo flights.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).

Computer simulations, dummy experiments with a new enhanced upper extremity, and small female cadaver experiments were used to analyze the small female upper extremity response under side air bag loading. After establishing the initial position, three tests were performed with the 5th percentile female hybrid III dummy, and six experiments with small female cadaver subjects. A new 5th percentile female enhanced upper extremity was developed for the dummy experiments that included a two-axis wrist load cell in addition to the existing six-axis load cells in both the forearm and humerus. Forearm pronation was also included in the new dummy upper extremity to increase the biofidelity of the interaction with the handgrip. Instrumentation for both the cadaver and dummy tests included accelerometers and magnetohydrodynamic angular rate sensors on the forearm, humerus, upper and lower spine.

Human expert drivers have the unique ability to combine correlated sensory inputs with repetitive learning to build complex perceptive models of the vehicle dynamics as well as certain key aspects of the tire-ground interface. This ability offers significant advantages for navigating a vehicle through the spatial and temporal uncertainties in a given environment. Conventional traction control algorithms utilize measurements of wheel slip to help insure that the wheels do not enter into an excessive slip condition such as burnout. This approach sacrifices peak performance to ensure that the slip limits are generic enough suck that burnout is avoided on a variety of surfaces: dry pavement, wet pavement, snow, gravel, etc. In this paper, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy.

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.

A key to shortening the design cycle is to shorten the initial or conceptual design phase. An enabling technology towards this goal is an architecture called the Design Support System (DSS), which is based on the virtual prototype concept. The DSS combines knowledge with hardware and software into a system that is a model for the design process. It produces a virtual prototype of the design and maintains an intelligent design document, which is automatically updated during the design process. A design domain dependent version for automotive design, known as “Automobile Design Support System” (AutoDSS) was developed in the CADTECH Research Lab at the University of Washington.