938 resultados para Turbocharger Lag


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Decision trees have been proposed as a basis for modifying table based injection to reduce transient particulate spikes during the turbocharger lag period. It has been shown that decision trees can detect particulate spikes in real time. In well calibrated electronically controlled diesel engines these spikes are narrow and are encompassed by a wider NOx spike. Decision trees have been shown to pinpoint the exact location of measured opacity spikes in real time thus enabling targeted PM reduction with near zero NOx penalty. A calibrated dimensional model has been used to demonstrate the possible reduction of particulate matter with targeted injection pressure pulses. Post injection strategy optimized for near stoichiometric combustion has been shown to provide additional benefits. Empirical models have been used to calculate emission tradeoffs over the entire FTP cycle. An empirical model based transient calibration has been used to demonstrate that such targeted transient modifiers are more beneficial at lower engine-out NOx levels.

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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.

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Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.

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Constructing a veridical spatial map by touch poses at least two problems for a perceptual system. First, as the hand is moved through space, the locations of features may be displaced if there is an uncorrected lag between the moment the hand encounters a feature and the time that feature is encoded on a spatial map. Second, due to the sequential nature of the process, some form of memory, which itself may be subject to spatial distortions, is required for integration of spatial samples. We investigated these issues using a task involving active haptic exploration with a stylus swept back and forth in the horizontal plane at the wrist. Remembered locations of tactile targets were shifted towards the medial axis of the forearm, suggesting a central tendency in haptic spatial memory, while evidence for a displacement of perceived locations in the direction of sweep motion was consistent with processing delays.

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The use of cell numbers rather than mass to quantify the size of the biotic phase in animal cell cultures causes several problems. First, the cell size varies with growth conditions, thus yields expressed in terms of cell numbers cannot be used in the normal mass balance sense. Second, experience from microbial systems shows that cell number dynamics lag behind biomass dynamics. This work demonstrates that this lag phenomenon also occurs in animal cell culture. Both the lag phenomenon and the variation in cell size are explained using a simple model of the cell cycle. The basis for the model is that onset of DNA synthesis requires accumulation of G1 cyclins to a prescribed level. This requirement is translated into a requirement for a cell to reach a critical size before commencement of DNA synthesis. A slower gl-owing cell will spend more time in G1 before reaching the critical mass. In contrast, the period between onset of DNA synthesis and mitosis, tau(B), is fixed. The two parameters in the model, the critical size and tau(B), were determined from eight steady-state measurements of mean cell size in a continuous hybridoma culture. Using these parameters, it was possible to predict with reasonable accuracy the transient behavior in a separate shift-up culture, i.e., a culture where cells were transferred from a lean environment to a rich environment. The implications for analyzing experimental data for animal cell culture are discussed. (C) 1997 John Wiley & Sons, Inc.

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OBJECTIVE: To assess the lag structure between air pollution exposure and elderly cardiovascular diseases hospital admissions, by gender. METHODS: Health data of people aged 64 years or older was stratified by gender in São Paulo city, Southeastern Brazil, from 1996 to 2001. Daily levels of air pollutants (CO, PM10, O3, NO2, and SO2) , minimum temperature, and relative humidity were also analyzed. It were fitted generalized additive Poisson regressions and used constrained distributed lag models adjusted for long time trend, weekdays, weather and holidays to assess the lagged effects of air pollutants on hospital admissions up to 20 days after exposure. RESULTS: Interquartile range increases in PM10 (26.21 mug/m³) and SO2 (10.73 mug/m³) were associated with 3.17% (95% CI: 2.09-4.25) increase in congestive heart failure and 0.89% (95% CI: 0.18-1.61) increase in total cardiovascular diseases at lag 0, respectively. Effects were higher among female group for most of the analyzed outcomes. Effects of air pollutants for different outcomes and gender groups were predominately acute and some "harvesting" were found. CONLUSIONS: The results show that cardiovascular diseases in São Paulo are strongly affected by air pollution.

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Laggards are the last users to adopt a product. Prior literature on user-led innovation ignores laggards’ impact on innovation. In this paper, we develop the Lag-User Method, through which laggards can generate new ideas. Through six studies with 62 teams in three countries, we apply the method to different technologies and services and present our findings to executives to get managerial insights. Findings reveal that laggards who generate new ideas (lag-users) have different perceptions of user-friendly products and different unfulfilled needs. They prefer simple products. We propose that by involving lag-users in NPD, firms can improve the effectiveness of NPD.

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Els bacteris són la forma dominant de vida del planeta: poden sobreviure en medis molt adversos, i en alguns casos poden generar substàncies que quan les ingerim ens són tòxiques. La seva presència en els aliments fa que la microbiologia predictiva sigui un camp imprescindible en la microbiologia dels aliments per garantir la seguretat alimentària. Un cultiu bacterià pot passar per quatre fases de creixement: latència, exponencial, estacionària i de mort. En aquest treball s’ha avançat en la comprensió dels fenòmens intrínsecs a la fase de latència, que és de gran interès en l’àmbit de la microbiologia predictiva. Aquest estudi, realitzat al llarg de quatre anys, s’ha abordat des de la metodologia Individual-based Modelling (IbM) amb el simulador INDISIM (INDividual DIScrete SIMulation), que ha estat millorat per poder fer-ho. INDISIM ha permès estudiar dues causes de la fase de latència de forma separada, i abordar l’estudi del comportament del cultiu des d’una perspectiva mesoscòpica. S’ha vist que la fase de latència ha de ser estudiada com un procés dinàmic, i no definida per un paràmetre. L’estudi de l’evolució de variables com la distribució de propietats individuals entre la població (per exemple, la distribució de masses) o la velocitat de creixement, han permès distingir dues etapes en la fase de latència, inicial i de transició, i aprofundir en la comprensió del que passa a nivell cel•lular. S’han observat experimentalment amb citometria de flux diversos resultats previstos per les simulacions. La coincidència entre simulacions i experiments no és trivial ni casual: el sistema estudiat és un sistema complex, i per tant la coincidència del comportament al llarg del temps de diversos paràmetres interrelacionats és un aval a la metodologia emprada en les simulacions. Es pot afirmar, doncs, que s’ha verificat experimentalment la bondat de la metodologia INDISIM.

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BACKGROUND: Immunotherapy offers a promising novel approach for the treatment of cancer and both adoptive T-cell transfer and immune modulation lead to regression of advanced melanoma. However, the potential synergy between these two strategies remains unclear. METHODS: We investigated in 12 patients with advanced stage IV melanoma the effect of multiple MART-1 analog peptide vaccinations with (n = 6) or without (n = 6) IMP321 (LAG-3Ig fusion protein) as an adjuvant in combination with lymphodepleting chemotherapy and adoptive transfer of autologous PBMCs at day (D) 0 (Trial registration No: NCT00324623). All patients were selected on the basis of ex vivo detectable MART-1-specific CD8 T-cell responses and immunized at D0, 8, 15, 22, 28, 52, and 74 post-reinfusion. RESULTS: After immunization, a significant expansion of MART-1-specific CD8 T cells was measured in 83% (n = 5/6) and 17% (n = 1/6) of patients from the IMP321 and control groups, respectively (P < 0.02). Compared to the control group, the mean fold increase of MART-1-specific CD8 T cells in the IMP321 group was respectively >2-, >4- and >6-fold higher at D15, D30 and D60 (P < 0.02). Long-lasting MART-1-specific CD8 T-cell responses were significantly associated with IMP321 (P < 0.02). At the peak of the response, MART-1-specific CD8 T cells contained higher proportions of effector (CCR7⁻ CD45RA⁺/⁻) cells in the IMP321 group (P < 0.02) and showed no sign of exhaustion (i.e. were mostly PD1⁻CD160⁻TIM3⁻LAG3⁻2B4⁺/⁻). Moreover, IMP321 was associated with a significantly reduced expansion of regulatory T cells (P < 0.04); consistently, we observed a negative correlation between the relative expansion of MART-1-specific CD8 T cells and of regulatory T cells. Finally, although there were no confirmed responses as per RECIST criteria, a transient, 30-day partial response was observed in a patient from the IMP321 group. CONCLUSIONS: Vaccination with IMP321 as an adjuvant in combination with lymphodepleting chemotherapy and adoptive transfer of autologous PBMCs induced more robust and durable cellular antitumor immune responses, supporting further development of IMP321 as an adjuvant for future immunotherapeutic strategies.

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This paper considers the lag structures of dynamic models in economics, arguing that the standard approach is too simple to capture the complexity of actual lag structures arising, for example, from production and investment decisions. It is argued that recent (1990s) developments in the the theory of functional differential equations provide a means to analyse models with generalised lag structures. The stability and asymptotic stability of two growth models with generalised lag structures are analysed. The paper concludes with some speculative discussion of time-varying parameters.

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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

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Diskussionsfrågan n:r 5, "Lag, moral och rättvisa i rättsskipningen - vems moral och rättvisa i förhållande till vem?" behandlades den 15 april 1999 i form av en paneldebatt

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In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.