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The paper presents experimental analysis of the airflow around the differential center housing of a rear drive full-scale passenger car. The study included investigation of local airflow total and static pressure, as well as surface flow visualization. Estimation of the local airflow velocity is based on the measured pressure coefficients. The experiments were carried out at different test facilities: in a climatic wind tunnel, in a full-scale wind tunnel and on-road. Influence of side wind was modeled by the yawing of the car in the full-scale wind tunnel. The results show the asymmetrical structure of the flow in both, vertical and horizontal planes. Estimated longitudinal relative local velocity decreases from maximum Vr ≈ 0.4 at the lower surface of the center housing, to about Vr ≈ 0 above the upper surface. Side wind increases airflow velocity around the center housing within the investigated yaw range ± 20°

The focus of internal combustion (IC) engine research is the improvement of fuel economy and the reduction of the tailpipe emissions of CO2 and other regulated pollutants. Promising solutions to this challenge include the use of both direct-injection (DI) and alternative fuels such as liquefied petroleum gas (LPG). This study uses Mie-scattering and schlieren imaging to resolve the liquid and vapor phases of propane and iso-octane, which serve as surrogates for LPG and gasoline respectively. These fuels are imaged in a constant volume chamber at conditions that are relevant to both naturally aspirated and boosted, gasoline direct injection (GDI) engines. It is observed that propane and iso-octane have different spray behaviors across these conditions. Iso-octane is subject to conventional spray breakup and evaporation in nearly all cases, while propane is heavily flash-boiling throughout the GDI operating map.

High-frequency pressure probes were used to map the airflow around a full-scale truck during on-road testing and around a model-scale truck during wind tunnel testing. Several configurations were tested during each type of testing. Results are presented for on-road ‘pass-by’ tests and detail velocity and coefficient of pressure variation alongside the truck at different heights. The wind tunnel data are results of flow mapping about a 10% scale model and show the velocity and coefficient of pressure distribution under and around the model truck for different configurations.

This paper presents the conceptual design of a new low-cost measurement system for the determination of pollutant concentrations associated with aircraft operations. The proposed system employs Light Detection and Ranging (LIDAR) and passive electro-optics equipment installed in two non-collocated components. The source component consists of a tuneable small-size and low-cost/weight LIDAR emitter, which can be installed either on airborne or ground-based autonomous vehicles, or in fixed surface installations. The sensor component includes a target surface calibrated for reflectance and passive electro-optics equipment calibrated for radiance, both installed on an adjustable support. The proposed bistatic system determines the column-averaged molecular and aerosol pollutant concentrations along the LIDAR beam by measuring the cumulative absorption and scattering phenomena along the optical slant range.

The air entrainment process of a compressed natural gas transient fuel jet was investigated in a constant-volume chamber using Schlieren and particle image velocimetry (PIV) techniques. A new method of calculating air entrainment around a gaseous fuel jet is proposed using Schlieren and PIV imaging techniques. This method offers an alternative to calculation of an alternative to calculation of entrainment using LIF technique in gaseous fuel jets. Several Jet-ambient pressure ratios were tested. In each test, nitrogen was used to fill the chamber as an air surrogate before the jet of natural gas was injected. Schlieren high speed videography and PIV experiments were performed at the same conditions. Schlieren mask images were used to accurately identify the jet boundary which was then superimposed onto a PIV image. Vectors adjacent to the Schlieren mask in the PIV image were used to calculate the spatial distribution of the air entrainment at the jet boundary.

The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.