Airdata calibration of a high-performance aircraft for measuring atmospheric wind profiles

The research airdata system of an instrumented F-104 aircraft has been calibrated to measure winds aloft in support of the space shuttle wind measurement investigation at the National Aeronautics and Space Administration Ames Research Center Dryden Flight Research Facility. For this investigation, wind measurement accuracies comparable to those obtained from Jimsphere balloons were desired. This required an airdata calibration more accurate than needed for most aircraft research programs. The F-104 aircraft was equipped with a research pilot-static noseboom with integral angle-of-attack and flank angle-of-attack vanes and a ring-laser-gyro inertial reference unit. Tower fly-bys and radar acceleration-decelerations were used to calibrate Mach number and total temperature. Angle of attack and angle of sideslip were calibrated with a trajectory reconstruction technique using a multiple-state linear Kalman filter. The F-104 aircraft and instrumentation configuration, flight test maneuvers, data corrections, calibration techniques, and resulting calibrations and data repeatability are presented. Recommendations for future airdata systems on aircraft used to measure winds aloft are also given

Calibration of probabilistic quantitative precipitation forecasts with an artificial neural network

A feed-forward neural network is configured to calibrate the bias of a high-resolution probabilistic quantitative precipitation forecast (PQPF) produced by a 12-km version of the NCEP Regional Spectral Model (RSM) ensemble forecast system. Twice-daily forecasts during the 2002-2003 cool season (1 November-31 March, inclusive) are run over four U.S. Geological Survey (USGS) hydrologic unit regions of the southwest United States. Calibration is performed via a cross-validation procedure, where four months are used for training and the excluded month is used for testing. The PQPFs before and after the calibration over a hydrological unit region are evaluated by comparing the joint probability distribution of forecasts and observations. Verification is performed on the 4-km stage IV grid, which is used as "truth." The calibration procedure improves the Brier score (BrS), conditional bias (reliability) and forecast skill, such as the Brier skill score (BrSS) and the ranked probability skill score (RPSS), relative to the sample frequency for all geographic regions and most precipitation thresholds. However, the procedure degrades the resolution of the PQPFs by systematically producing more forecasts with low nonzero forecast probabilities that drive the forecast distribution closer to the climatology of the training sample. The problem of degrading the resolution is most severe over the Colorado River basin and the Great Basin for relatively high precipitation thresholds where the sample of observed events is relatively small. © 2007 American Meteorological Society

On-Board Sensor-Based NO x Emissions from Heavy-Duty Diesel Vehicles

Real-world nitrogen oxides (NOx) emissions were estimated using on-board sensor readings from 72 heavy-duty diesel vehicles (HDDVs) equipped with a Selective Catalytic Reduction (SCR) system in California. The results showed that there were large differences between in-use and certification NOx emissions, with 12 HDDVs emitting more than three times the standard during hot-running and idling operations in the real world. The overall NOx conversion efficiencies of the SCR system on many vehicles were well below the 90% threshold that is expected for an efficient SCR system, even when the SCR system was above the optimum operating temperature threshold of 250 °C. This could potentially be associated with SCR catalyst deterioration on some engines. The Not-to-Exceed (NTE) requirements currently used by the heavy-duty in-use compliance program were evaluated using on-board NOx sensor data. Valid NTE events covered only 4.2–16.4% of the engine operation and 6.6–34.6% of the estimated NOx emissions. This work shows that low cost on-board NOx sensors are a convenient tool to monitor in-use NOx emissions in real-time, evaluate the SCR system performance, and identify vehicle operating modes with high NOx emissions. This information can inform certification and compliance programs to ensure low in-use NOx emissions

REMOTE SENSING OF FOLIAR NITROGEN IN CULTIVATED GRASSLANDS OF HUMAN DOMINATED LANDSCAPES

Foliar nitrogen (N) concentration of plant canopies plays a central role in a number of important ecosystem processes and continues to be an active subject in the field of remote sensing. Previous efforts to estimate foliar N at the landscape scale have primarily focused on intact forests and grasslands using aircraft imaging spectrometry and various techniques of statistical calibration and modeling. The present study was designed to extend this work by examining the potential to estimate the foliar N concentration of residential, agricultural and other cultivated grassland areas within a suburbanizing watershed. In conjunction with ground-based vegetation sampling, we developed Partial Least Squares (PLS) models for predicting mass-based foliar N across management types using input from airborne and field based imaging spectrometers. Results yielded strong predictive relationships for both ground- and aircraft-based sensors across sites that included turf grass, grazed pasture, hayfields and fallow fields. We also report on relationships between imaging spectrometer data and other important variables such as canopy height, biomass, and water content, results from which show strong promise for detection with high quality imaging spectrometry data and suggest that cultivated grassland offer opportunity for empirical study of canopy light dynamics. Finally, we discuss the potential for application of our results, and potential challenges, with data from the planned HyspIRI satellite, which will provide global coverage of data useful for vegetation N estimation

Quantification of benzene, toluene, ethylbenzene and o-xylene in internal combustion engine exhaust with time-weighted average solid phase microextraction and gas chromatography mass spectrometry

A new and simple method for benzene, toluene, ethylbenzene and o-xylene (BTEX) quantification in vehicle exhaust was developed based on diffusion-controlled extraction onto a retracted solid-phase microextraction (SPME) fiber coating. The rationale was to develop a method based on existing and proven SPME technology that is feasible for field adaptation in developing countries. Passive sampling with SPME fiber retracted into the needle extracted nearly two orders of magnitude less mass (n) compared with exposed fiber (outside of needle) and sampling was in a time weighted-averaging (TWA) mode. Both the sampling time (t) and fiber retraction depth (Z) were adjusted to quantify a wider range of Cgas. Extraction and quantification is conducted in a non-equilibrium mode. Effects of Cgas, t, Z and T were tested. In addition, contribution of n extracted by metallic surfaces of needle assembly without SPME coating was studied. Effects of sample storage time on n loss was studied. Retracted TWA–SPME extractions followed the theoretical model. Extracted n of BTEX was proportional to Cgas, t, Dg, T and inversely proportional to Z. Method detection limits were 1.8, 2.7, 2.1 and 5.2 mg m−3 (0.51, 0.83, 0.66 and 1.62 ppm) for BTEX, respectively. The contribution of extraction onto metallic surfaces was reproducible and influenced by Cgas and t and less so by T and by the Z. The new method was applied to measure BTEX in the exhaust gas of a Ford Crown Victoria 1995 and compared with a whole gas and direct injection method

MRacing Formula SAE Improving Fuel Efficiency

ME450 Capstone Design and Manufacturing Experience: Fall 2020MRacing, Mechanical Engineering, University of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/164447/1/MRacing_Formula_SAE_Improving_Fuel_Efficiency.pd