A exhaust system consisting of a close-coupled Pd technology 32 in3 lightoff converter and Pt/Rh technology 170 in3 underfloor converter was vehicle-aged for 56000 miles on a vehicle equipped with a 3.8 l engine. Following this aging, the converters were taken off the vehicle and cut into 1″ thick sections along their axis and characterized for lightoff and warmed-up activity using a laboratory reactor to simulate vehicle exhaust. Each section was also analyzed for the quantity of oil additive poisons (phosphorus and zinc) deposited. Following this initial characterization, the phosphorus and zinc deposits were removed, and the sections were characterized again for lightoff and warmed-up activity. This procedure was used to qualitatively determine the relative contribution of oil additive poisoning and thermal sintering to the total activity deterioration as a function of axial position in the catalyst monoliths.
Analysis of the lightoff converter as taken from the vehicle showed a dramatic axial gradient in the lean and stoichiometric lightoff and warmed-up (600°C) performance for HC, CO and NOx, with most of the deterioration having taken place in the forward-most 1″ section of the converter, which was consistent with the gradient in the deposition of phosphorus (P) and zinc (Zn) in this converter. Comparison of these data sets with those obtained after removal of the P and Zn poisons indicates that most of the total deterioration of lean HC and CO activity can be attributed to P and Zn poisoning of the forwardmost 1″ section. When tested under stoichiometric conditions, most of the deterioration of HC activity is attributable to P and Zn poisoning, while most of the deterioration of CO and NOx activity is attributable to thermal deterioration. A similar activity and poison deposition gradient was detected in the underfloor converter, but to a smaller extent. 相似文献
We compared methods for predicting and understanding the source of confusion errors during military vehicle identification training. Participants completed training to identify main battle tanks. They also completed card-sorting and similarity-rating tasks to express their mental representation of resemblance across the set of training items. We expected participants to selectively attend to a subset of vehicle features during these tasks, and we hypothesised that we could predict identification confusion errors based on the outcomes of the card-sort and similarity-rating tasks. Based on card-sorting results, we were able to predict about 45% of observed identification confusions. Based on multidimensional scaling of the similarity-rating data, we could predict more than 80% of identification confusions. These methods also enabled us to infer the dimensions receiving significant attention from each participant. This understanding of mental representation may be crucial in creating personalised training that directs attention to features that are critical for accurate identification.
Practitioner Summary: Participants completed military vehicle identification training and testing, along with card-sorting and similarity-rating tasks. The data enabled us to predict up to 84% of identification confusion errors and to understand the mental representation underlying these errors. These methods have potential to improve training and reduce identification errors leading to fratricide. 相似文献
The secure operation of autonomous vehicle networks in the presence of adversarial observation is examined, in the context of a canonical double-integrator-network (DIN) model. Specifically, we study the ability of a sentient adversary to estimate the full network’s state, from noisy local measurements of vehicle motions. Algebraic, spectral, and graphical characterizations are provided, which indicate the critical role of the inter-vehicle communication topology and control scheme in achieving security. 相似文献
