A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Integrated Geophysical Investigation of the St. James Fault Complex: A Case Study

We noninvasively detected the characteristics and location of a regional fault in an area of poor bedrock exposure complicated by karst weathering features in the subsurface. Because this regional fault is associated with sinkhole formation, its location is important for hazard avoidance. The bedrock lithologies on either side of the fault trace are similar; hence, we chose an approach that capitalized on the complementary strengths of very low frequency (VLF) electromagnetic, resistivity, and gravity methods. VLF proved most useful as a first-order reconnaissance tool, allowing us to define a narrow target area for further geophysical exploration. Fault-related epikarst was delineated using resistivity. Ultimately, a high-resolution gravity survey and subsequent inverse modeling using the results of the resistivity survey helped to further constrain the location and approximate orientation of the fault. The combined results indicated that the location of the fault trace needed to be adjusted 53 m south of the current published location and was consistent with a north-dipping thrust fault. Additionally, a gravity low south of the fault trace agreed with the location of conductive material from the resistivity and VLF surveys. We interpreted these anomalies to represent enhanced epikarst in the fault footwall. We clearly found that a staged approach involving a progression of methods beginning with a reconnaissance VLF survey, followed by high-resolution gravity and electrical resistivity surveys, can be used to characterize a fault and fault-related karst in an area of poor bedrock surface exposure.