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

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

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

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

A Photometric Survey for Variables and Transits in the Field of Praesepe with KELT

The Kilodegree Extremely Little Telescope (KELT) project is a small aperture, wide-angle search for planetary transits of solar-type stars. In this paper, we present the results of a commissioning campaign with the KELT telescope to observe the open cluster Praesepe for 34 nights in early 2005. Lightcurves were obtained for 69,337 stars, out of which we identify 58 long period variables and 152 periodic variables. Sixteen of these are previously known as variable, yielding 194 newly discovered variable stars for which we provide properties and lightcurves. We also searched for planetary-like transits, finding four transit candidates. Follow-up observations indicate that two of the candidates are astrophysical false positives, with two candidates remaining as potential planetary transits.Comment: 45 pages, 16 figures. Submitted to AJ. PDF version with full resolution figures located at http://www.astronomy.ohio-state.edu/~pepper/kelt.pd