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Technical Paper

Ultrasonic Cavitation Based Casting of Aluminum Matrix Nanocomposites for Automobile Structures

2006-04-03
2006-01-0290
The properties of aluminum alloys reinforced by ceramic nanoparticles (less than 100nm) would be enhanced considerably while the ductility is retained over that of the native alloy. The potential of bulk Al-based metal matrix nano-composites (Al MMNCs) cannot be fully developed for industrial applications unless complex structural Al MMNC components can be fabricated cost effectively, such as by casting. Reliable bulk Al MMNCs cannot be cast unless the nanoparticles can be dispersed and distributed uniformly in molten Al alloys. This paper investigates a high volume production method for high performance aluminum matrix nanocomposites, in particular, the application of high intensity ultrasonic cavitation in mixing and dispersing nano-sized ceramic particles in Al melts to cast bulk Al MMNCs for complex automobile structures. Nano-sized SiC particles have been dispersed in molten aluminum alloy A356 for casting.
Technical Paper

Traffic State Identification Using Matrix Completion Algorithm Under Connected and Automated Environment

2021-12-15
2021-01-7004
Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.
Technical Paper

Reinventing the Internal Combustion (IC) Engine Head and Exhaust Gaskets

2002-03-04
2002-01-0332
This paper describes how a blend of silicon polymers, mixed with the right combination of fillers, enables the production of durable rubber IC engine head and exhaust gaskets. The resin blend, when mixed with glass fiber reinforcement, produces a liquid sealant suitable for exhaust gasket applications. The exhaust sealant and laminate head gaskets were tested on Ford 460 truck engines at Jasper Engine Company and completed more than 5,000 hours of durability testing without incident. Fabric reinforced polymer (FRP) head and exhaust gaskets can be laser cut from molded laminates, creating a ceramic glass-sealed edge. Thermogravimetric scans of typical gasket laminate material reveal an 88%-yield at 1000°C. FRP head gaskets also enable the cost-effective production of multiple spark ignition (MSI) head gaskets.
Technical Paper

PIV Measurements of In-Cylinder Flow in a Four-Stroke Utility Engine and Correlation with Steady Flow Results

2004-09-27
2004-32-0005
Large-scale flows in internal combustion engines directly affect combustion duration and emissions production. These benefits are significant given increasingly stringent emissions and fuel economy requirements. Recent efforts by engine manufacturers to improve in-cylinder flows have focused on the design of specially shaped intake ports. Utility engine manufacturers are limited to simple intake port geometries to reduce the complexity of casting and cost of manufacturing. These constraints create unique flow physics in the engine cylinder in comparison to automotive engines. An experimental study of intake-generated flows was conducted in a four-stroke spark-ignition utility engine. Steady flow and in-cylinder flow measurements were made using three simple intake port geometries at three port orientations. Steady flow measurements were performed to characterize the swirl and tumble-generating capability of the intake ports.
Technical Paper

Feature Extraction from Non-Linear Geometric Models in Design-for-Manufacturing

1994-09-01
941672
Automatic manufacturability analysis of injection moldings, sheet metal castings, stampings, forgings, etc., using knowledge-based heuristics depends on shape features, which are abstractions of the three dimensional (3D) geometric model of the parts. Conventional CAD systems do not explicitly contain shape feature information, therefore such information needs to be extracted from them. So far, extraction of shape features has been restricted to models with simple geometric shapes such as planar, cylindrical or conical shapes. Extending shape feature extraction to non-linear geometric models will allow Design For Manufacturability (DFM) analysis of non-linear models. This paper presents an approach to extract features from non-linear geometric models. The approach is based on abstract geometric entities called C-loops. The formation of a C-loop depends on a geometric entity called a silhouette. The C-loops are derived from the silhouette boundaries of an object.
Journal Article

Active Learning Optimization for Boundary Identification Using Machine Learning-Assisted Method

2022-03-29
2022-01-0783
Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.
Technical Paper

A Study on the Effects of Fuel Viscosity and Nozzle Geometry on High Injection Pressure Diesel Spray Characteristics

1997-02-24
970353
The objective of this study was to investigate the effects of fuel viscosity and the effects of nozzle inlet configuration on the characteristics of high injection pressure sprays. Three different viscosity fuels were used to reveal the effects of viscosity on the spray characteristics. The effects of nozzle inlet configuration on spray characteristics were studied using two mini-sac six-hole nozzles with different inlet configurations. A common rail injection system was used to introduce the spray at 90 MPa injection pressure into a constant volume chamber pressurized with argon gas. The information on high pressure transient sprays was captured by a high speed movie camera synchronized with a pulsed copper vapor laser. The images were analyzed to obtain the spray characteristics which include spray tip penetration, spray cone angle at two different regions, and overall spray Sauter Mean Diameter (SMD).
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