Bayesian spline method for assessing extreme loads on wind turbines

This study presents a Bayesian parametric model for the purpose of estimating the extreme load on a wind turbine. The extreme load is the highest stress level imposed on a turbine structure that the turbine would experience during its service lifetime. A wind turbine should be designed to resist such a high load to avoid catastrophic structural failures. To assess the extreme load, turbine structural responses are evaluated by conducting field measurement campaigns or performing aeroelastic simulation studies. In general, data obtained in either case are not sufficient to represent various loading responses under all possible weather conditions. An appropriate extrapolation is necessary to characterize the structural loads in a turbine's service life. This study devises a Bayesian spline method for this extrapolation purpose, using load data collected in a period much shorter than a turbine's service life. The spline method is applied to three sets of turbine's load response data to estimate the corresponding extreme loads at the roots of the turbine blades. Compared to the current industry practice, the spline method appears to provide better extreme load assessment.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS670 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Soft Sensor-Based Fault-Tolerant Control on the Air Fuel Ratio of Spark-Ignition Engines

The air/fuel ratio (AFR) regulation for spark-ignition (SI) engines has been an essential and challenging control problem for engineers in the automotive industry. The feed-forward and feedback scheme has been investigated in both academic research and industrial application. The aging effect can often cause an AFR sensor fault in the feedback loop, and the AFR control performance will degrade consequently. In this research, a new control scheme on AFR with fault-tolerance is proposed by using an artificial neural network model based on fault detection and compensation, which can provide the satisfactory AFR regulation performance at the stoichiometric value for the combustion process, given a certain level of misreading of the AFR sensor

On the use of an explicit chemical mechanism to dissect peroxy acetyl nitrate formation.

Peroxy acetyl nitrate (PAN) is a key component of photochemical smog and plays an important role in atmospheric chemistry. Though it has been known that PAN is produced via reactions of nitrogen oxides (NOx) with some volatile organic compounds (VOCs), it is difficult to quantify the contributions of individual precursor species. Here we use an explicit photochemical model--Master Chemical Mechanism (MCM) model--to dissect PAN formation and identify principal precursors, by analyzing measurements made in Beijing in summer 2008. PAN production was sensitive to both NOx and VOCs. Isoprene was the predominant VOC precursor at suburb with biogenic impact, whilst anthropogenic hydrocarbons dominated at downtown. PAN production was attributable to a relatively small class of compounds including NOx, xylenes, trimethylbenzenes, trans/cis-2-butenes, toluene, and propene. MCM can advance understanding of PAN photochemistry to a species level, and provide more relevant recommendations for mitigating photochemical pollution in large cities

Pseudogap formation of four-layer BaRuO3_3 and its electrodynamic response changes

We investiaged the optical properties of four-layer BaRuO$_{3}$, which shows a fermi-liquid-like behavior at low temperature. Its optical conductivity spectra clearly displayed the formation of a pseudogap and the development of a coherent peak with decreasing temperature. Temperature-dependences of the density $n$ and the scattering rate $1/\tau$ of the coherent component were also derived. As the temperature decreases, both $n$ and $1/\tau$ decrease for four-layer BaRuO$_{3}$. These electrodynamic responses were compared with those of nine-layer BaRuO$_{3}$, which also shows a pseudogap formation but has an insulator-like state at low temperature. It was found that the relative rates of change of both $n$ and $1/\tau$ determine either metallic or insulator-like responses in the ruthenates. The optical properties of the four-layer ruthenate were also compared with those of other pseudogap systems, such as high $T_{c}$ cuprates and heavy electron systems.Comment: 7 figures. submitted to Phys. Rev.

The impacts of bias in cloud-radiation-dynamics interactions on central Pacific seasonal and El Niño simulations in contemporary GCMs

Most of the global climate models (GCMs) in the Coupled Model Intercomparison Project, phase 5 do not include precipitating ice (aka falling snow) in their radiation calculations. We examine the importance of the radiative effects of precipitating ice on simulated surface wind stress and sea surface temperatures (SSTs) in terms of seasonal variation and in the evolution of central Pacific El Niño (CP‐El Niño) events. Using controlled simulations with the CESM1 model, we show that the exclusion of precipitating ice radiative effects generates a persistent excessive upper‐level radiative cooling and an increasingly unstable atmosphere over convective regions such as the western Pacific and tropical convergence zones. The invigorated convection leads to persistent anomalous low‐level outflows which weaken the easterly trade winds, reducing upper‐ocean mixing and leading to a positive SST bias in the model mean state. In CP‐El Niño events, this means that outflow from the modeled convection in the central Pacific reduces winds to the east, allowing unrealistic eastward propagation of warm SST anomalies following the peak in CP‐El Niño activity. Including the radiative effects of precipitating ice reduces these model biases and improves the simulated life cycle of the CP‐El Niño. Improved simulations of present‐day tropical seasonal variations and CP‐El Niño events would increase the confidence in simulating their future behavior

Nanostructured luminescently labeled nucleic acids

Important and emerging trends at the interface of luminescence, nucleic acids and nanotechnology are: (i) the conventional luminescence labeling of nucleic acid nanostructures (e.g. DNA tetrahedron); (ii) the labeling of bulk nucleic acids (e.g. single‐stranded DNA, double‐stranded DNA) with nanostructured luminescent labels (e.g. copper nanoclusters); and (iii) the labeling of nucleic acid nanostructures (e.g. origami DNA) with nanostructured luminescent labels (e.g. silver nanoclusters). This review surveys recent advances in these three different approaches to the generation of nanostructured luminescently labeled nucleic acids, and includes both direct and indirect labeling methods

Coexistence of Itinerant Electrons and Local Moments in Iron-Based Superconductors

In view of the recent experimental facts in the iron-pnictides, we make a proposal that the itinerant electrons and local moments are simultaneously present in such multiband materials. We study a minimal model composed of coupled itinerant electrons and local moments to illustrate how a consistent explanation of the experimental measurements can be obtained in the leading order approximation. In this mean-field approach, the spin-density-wave (SDW) order and superconducting pairing of the itinerant electrons are not directly driven by the Fermi surface nesting, but are mainly induced by their coupling to the local moments. The presence of the local moments as independent degrees of freedom naturally provides strong pairing strength for superconductivity and also explains the normal-state linear-temperature magnetic susceptibility above the SDW transition temperature. We show that this simple model is supported by various anomalous magnetic properties and isotope effect which are in quantitative agreement with experiments.Comment: 7 pages, 4 figures; an expanded versio