Characterisation and Optimisation of a Real-Time Diesel engine model

Accurate real-time engine models are an essential step to allow the development of control algorithms in parallel to the development of engine hardware using hardware-in-the-loop applications. A physics-based model of the engine high-pressure air path and combustion chamber is presented. The model was parameterised using data from a small set of carefully selected operating conditions for a 2.0 l diesel engine. The model was subsequently validated over the complete engine operating map with exhaust gas recirculation and without exhaust gas recirculation. A high level of fit was achieved with R2 values above 0.94 for the mean effective pressure and above 0.99 for the air flow rate. The model run time was then reduced for real-time application by using forward differencing and single-precision floating-point numbers and by calculating the in-cylinder prediction for only a single cylinder. A further improvement of 25% in the run time was achieved by improving the submodels, including the strategic use of one-dimensional and two-dimensional look-up tables with optimised resolution. The model exceeds the performance of similar models in the literature, achieving a crank angle resolution of 0.5° at 4000 r/min. This simulation step size still yields good accuracy in comparison with a crank angle resolution of 0.1° and was validated against the experimental results from a New European Driving Cycle. The real-time model allows the development of control strategies before the engine hardware is available, meaning that more time can be spent to ensure that the engine can meet the performance and the emissions requirements over its full operating range

Analysis and Modeling of the Transient Thermal Behavior of Automotive Turbochargers

Turbochargers are a key technology to deliver fuel consumption reductions on future internal combustion engines. However, the current industry standard modeling approaches assume the turbine and compressor operate under adiabatic conditions. Although some state of the art modeling approaches have been presented for simulating the thermal behavior, these have focused on thermally stable conditions. In this work, an instrumented turbocharger was operated on a 2.2 liter diesel engine and in parallel a onedimensional lumped capacity thermal model was developed. For the first time this paper presents analysis of experimental and modeling results under dynamic engine operating conditions. Engine speed and load conditions were varied to induce thermal transients with turbine inlet temperatures ranging from 200 to 800 C; warm-up behavior from 25 C ambient was also studied. Following a model tuning process based on steady operating conditions, the model was used to predict turbine and compressor gas outlet temperatures, doing so with an RMSE of 8.4 and 7.1 C, respectively. On the turbine side, peak heat losses from the exhaust gases were observed to be up to double those observed under thermally stable conditions due to the heat accumulation in the structure. During warm-up, the model simplifications did not allow for accurate modeling of the compressor, however on the turbine side gas temperature prediction errors were reduced from 150 to around 40 C. The main benefits from the present modeling approach appear to be in turbine outlet temperature prediction, however modeling improvements are identified for future work

Critical evaluation of on-engine fuel consumption measurement

To enable continued development and facilitate the adoption of new internal combustion engine technologies, the accuracy and repeatability of measurement methods used for verification need to be improved upon. A variety of methods are available for the measurement of fuel consumption based on the volumetric or gravimetric principle or by equating carbon in the fuel to carbon in the exhaust flow. Measurements of fuel consumption from five different experimental campaigns with varying engine set-ups are presented, highlighting discrepancies between gravimetric fuel balance and exhaust feed gas carbon balance. Differences were larger for cold-start tests and if all correction factors are neglected offsets can reach 7 per cent. The carbon balance and gravimetric methods have been considered independently to identify sources of inaccuracy and improvements have been suggested in the form of correction factors. The carbon balance estimate is dependent on a number of separate measurements, all taken at different conditions. To account for these, two correction factors were compared, the first proposed by the British Standards Institution and the second derived from the experimental conditions of each of the measurements. The gravimetric measurement was affected by changes in fuel temperature within the fuelling circuit and a corrective method was proposed based on the change in fuel density. When correction factors were applied to each of the measurement techniques for the five experimental campaigns, discrepancies were less than 1 per cent, which, in most cases, was small enough for there to be no statistically significant difference between measurements. In addition, in some cases the scatter of results was reduced, contributing to improved test-to-test repeatability. The improved performance when using correction factors was explained by including known disturbances, such as fuel temperature and ambient humidity, as inputs to the measurement system. </jats:p

A virtual engine laboratory for teaching powertrain engineering

A virtual engine laboratory application for use in automotive engineering education is proposed to allow the practical teaching of powertrain calibration. The laboratory software is built as a flexible Matlab tool that can easily be transferred for applications in other disciplines and promotes the link between teaching and research

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis)

Putting Public Safety First: 13 Strategies for Successful Supervision and Reentry

Outlines organizational- and case management-level strategies to reduce recidivism through risk reduction and behavior change, such as by aligning resources with risk factors. Describes each practice's benefits, evidence base, and examples from the field

Active site binding and sequence requirements for inhibition of HIV-1 reverse transcriptase by the RT1 family of single-stranded DNA aptamers

Nucleic acid aptamers can potentially be developed as broad-spectrum antiviral agents. Single-stranded DNA (ssDNA) aptamer RT1t49 inhibits reverse transcriptases (RT) from HIV-1 and diverse lentiviral subtypes with low nanomolar values of Kd and IC50. To dissect the structural requirements for inhibition, RT-catalyzed DNA polymerization was measured in the presence of RT1t49 variants. Three structural domains were found to be essential for RT inhibition by RT1t49: a 5′ stem (stem I), a connector and a 3′ stem (stem II) capable of forming multiple secondary structures. Stem I tolerates considerable sequence plasticity, suggesting that it is recognized by RT more by structure than by sequence-specific contacts. Truncating five nucleotides from the 3′ end prevents formation of the most stable stem II structure, yet has little effect on IC50 across diverse HIV-1, HIV-2 and SIVCPZ RT. When bound to wild-type RT or an RNase H active site mutant, site-specifically generated hydroxyl radicals cleave after nucleotide A32. Cleavage is eliminated by either of two polymerase (pol)-active site mutants, strongly suggesting that A32 lies within the RT pol-active site. These data suggest a model of ssDNA aptamer–RT interactions and provide an improved molecular understanding of a potent, broad-spectrum ssDNA aptamer

Survey for Transiting Extrasolar Planets in Stellar Systems: III. A Limit on the Fraction of Stars with Planets in the Open Cluster NGC 1245

We analyze a 19-night photometric search for transiting extrasolar planets in the open cluster NGC 1245. An automated transit search algorithm with quantitative selection criteria finds six transit candidates; none are bona fide planetary transits. We characterize the survey detection probability via Monte Carlo injection and recovery of realistic limb-darkened transits. We use this to derive upper limits on the fraction of cluster members with close-in Jupiter-radii, RJ, companions. We carefully analyze the random and systematic errors of the calculation. For similar photometric noise and weather properties as this survey, observing NGC 1245 twice as long results in a tighter constraint on "Hot Jupiter", HJ, companions than observing an additional cluster of similar richness as NGC 1245 for the same length of time as this survey. This survey observed ~870 cluster members. If 1% of stars have 1.5 RJ HJ companions, we expect to detect one planet for every 5000 dwarf stars observed for a month. To reach a ~2% upper limit on the fraction of stars with 1.5 RJ HJ companions, we conclude a total sample size of ~7400 dwarf stars observed for at least a month will be needed. Results for 1.0 RJ companions, without substantial improvement in the photometric precision, will require a small factor larger sample size.Comment: 24 pages, 15 figures, submitted A