Elemental Abundances in NGC 3516

We present RGS data from an XMM-Newton observation of the Seyfert 1 galaxy NGC 3516, taken while the continuum source was in an extreme low state. The spectrum shows numerous emission lines including the H-like lines of C, N and O and the He-like lines of N, O and Ne. These data show that the N lines are far stronger than would be expected from gas of solar abundances. Based on our photoionization models, we find that N is overabundant compared to C, O and Ne by at least a factor of 2.5. We suggest this is the result of secondary production of N in intermediate mass stars, and indicative of the history of star formation in NGC 3516.Comment: 19 pages, 3 color figures. ApJ in pres

A new method for microscale cyclic crack growth characterization from notched microcantilevers and application to single crystalline tungsten and a metallic glass

The lifetime of most metals is limited by cyclic loads, ending in fatigue failure. The progressive growth of cracks ends up in catastrophic failure. An advanced method is presented for the determination of cyclic crack growth on the microscale using a nanoindenter, which allows the characterization of > 10,000 loading cycles. It uses focused ion beam fabricated notched microcantilevers. The method has been validated by cyclic bending metallic glass and tungsten microcantilevers. The experiments reveal a stable crack growth during the lifetime of both samples. The metallic glass shows less plasticity due to the absence of dislocations, but shows shearing caused by the deformation. The crack growth rates determined in the tests follow Paris' power law relationship. The results are reliable, reproducible and comparable with macroscopic setups. Due to the flexibility of the method, it is suitable for the characterization of specific microstructural features, like single phases, grain boundaries or different grain orientations

Can a Lamb Reach a Haven Before Being Eaten by Diffusing Lions?

We study the survival of a single diffusing lamb on the positive half line in the presence of N diffusing lions that all start at the same position L to the right of the lamb and a haven at x=0. If the lamb reaches this haven before meeting any lion, the lamb survives. We investigate the survival probability of the lamb, S_N(x,L), as a function of N and the respective initial positions of the lamb and the lions, x and L. We determine S_N(x,L) analytically for the special cases of N=1 and N--->oo. For large but finite N, we determine the unusual asymptotic form whose leading behavior is S_N(z)\simN^{-z^2}, with z=x/L. Simulations of the capture process very slowly converge to this asymptotic prediction as N reaches 10^{500}.Comment: 13 pages, 6 figures, IOP format; v2: small changes in response to referee and editor comment

Quantitative analysis of positive-displacement compressor models tested in extrapolation scenarios

Testing and evaluation of select semi-empirical compressor models is carried out to quantify performance in modulation (variable speed), extrapolation, and additionally, variable superheat scenarios. Three representative literature models and an artificial neural network (ANN) model are benchmarked against the industry standard AHRI model. A methodology quantifying model performance, compared against experimental data, in said scenarios is presented. Data used is of high-fidelity taken from either a hot-gas bypass load stand or compressor calorimeter. Scroll, screw, reciprocating, and spool compressor technologies were collected with R410A, R1234ze(E), R134a, and R32 refrigerants totaling 434 experimental points. Data is divided into training, extrapolation, variable speed, and variable superheat data splits to examine model performance. Mean Absolute Percentage Error (MAPE) is computed for mass flow rate and power after training models with training data and evaluating them against the other data splits. Two literature models are true semi-empirical formulations while the other, the ANN, and AHRI model are more empirical in nature. Neither semi-empirical model predicted all compressors. When the compressor type is predicted, the semi-empirical models yield MAPE’s less than 8%, 5%, and 4% for mass flow rate and power prediction in extrapolation, modulation, and variable superheat scenarios, respectively. The exception is the Popovic and Shapiro model performing at 21% MAPE in variable superheat power prediction for the spool compressor with R1234ze(E). The ANN showed highest errors of 9.3%, 12%, and 17% in extrapolation, modulation, and variable superheat scenarios, respectively. All models outperformed the AHRI model by several orders of magnitude in these scenarios