Data-driven online monitoring of wind turbines

Condition based maintenance is a modern approach to maintenance which has been successfully used in several industrial sectors. In this paper we present a concrete statistical approach to condition based maintenance for wind turbine by applying ideas from statistical process control. A specific problem in wind turbine maintenance is that failures of a certain part may have causes that originate in other parts a long time ago. This calls for methods that can produce timely warnings by combining sensor data from different sources. Our method improves on existing methods used in wind turbine maintenance by using adaptive alarm thresholds for the monitored parameters that correct for values of other relevant parameters. We illustrate our method with a case study that shows that our method is able to predict upcoming failures much earlier than currently used methods

Robust and Efficient Uncertainty Quantification and Validation of RFIC Isolation

Modern communication and identification products impose demanding constraints on reliability of components. Due to this statistical constraints more and more enter optimization formulations of electronic products. Yield constraints often require efficient sampling techniques to obtain uncertainty quantification also at the tails of the distributions. These sampling techniques should outperform standard Monte Carlo techniques, since these latter ones are normally not efficient enough to deal with tail probabilities. One such a technique, Importance Sampling, has successfully been applied to optimize Static Random Access Memories (SRAMs) while guaranteeing very small failure probabilities, even going beyond 6-sigma variations of parameters involved. Apart from this, emerging uncertainty quantifications techniques offer expansions of the solution that serve as a response surface facility when doing statistics and optimization. To efficiently derive the coefficients in the expansions one either has to solve a large number of problems or a huge combined problem. Here parameterized Model Order Reduction (MOR) techniques can be used to reduce the work load. To also reduce the amount of parameters we identify those that only affect the variance in a minor way. These parameters can simply be set to a fixed value. The remaining parameters can be viewed as dominant. Preservation of the variation also allows to make statements about the approximation accuracy obtained by the parameter-reduced problem. This is illustrated on an RLC circuit. Additionally, the MOR technique used should not affect the variance significantly. Finally we consider a methodology for reliable RFIC isolation using floor-plan modeling and isolation grounding. Simulations show good comparison with measurements

Atomic Force Microscope nanolithography on chromosomes to genrate single-cell genetic probes

Abstract Background Chromosomal dissection provides a direct advance for isolating DNA from cytogenetically recognizable region to generate genetic probes for fluorescence in situ hybridization, a technique that became very common in cyto and molecular genetics research and diagnostics. Several reports describing microdissection methods (glass needle or a laser beam) to obtain specific probes from metaphase chromosomes are available. Several limitations are imposed by the traditional methods of dissection as the need for a large number of chromosomes for the production of a probe. In addition, the conventional methods are not suitable for single chromosome analysis, because of the relatively big size of the microneedles. Consequently new dissection techniques are essential for advanced research on chromosomes at the nanoscale level. Results We report the use of Atomic Force Microscope (AFM) as a tool for nanomanipulation of single chromosomes to generate individual cell specific genetic probes. Besides new methods towards a better nanodissection, this work is focused on the combination of molecular and nanomanipulation techniques which enable both nanodissection and amplification of chromosomal and chromatidic DNA. Cross-sectional analysis of the dissected chromosomes reveals 20 nm and 40 nm deep cuts. Isolated single chromosomal regions can be directly amplified and labeled by the Degenerate Oligonucleotide-Primed Polymerase Chain Reaction (DOP-PCR) and subsequently hybridized to chromosomes and interphasic nuclei. Conclusions Atomic force microscope can be easily used to visualize and to manipulate biological material with high resolution and accuracy. The fluorescence in situ hybridization (FISH) performed with the DOP-PCR products as test probes has been tested succesfully in avian microchromosomes and interphasic nuclei. Chromosome nanolithography, with a resolution beyond the resolution limit of light microscopy, could be useful to the construction of chromosome band libraries and to the molecular cytogenetic mapping related to the investigation of genetic diseases.</p

Discrete Multiscale Analysis: A Biatomic Lattice System

We discuss a discrete approach to the multiscale reductive perturbative method and apply it to a biatomic chain with a nonlinear interaction between the atoms. This system is important to describe the time evolution of localized solitonic excitations. We require that also the reduced equation be discrete. To do so coherently we need to discretize the time variable to be able to get asymptotic discrete waves and carry out a discrete multiscale expansion around them. Our resulting nonlinear equation will be a kind of discrete Nonlinear Schr\"odinger equation. If we make its continuum limit, we obtain the standard Nonlinear Schr\"odinger differential equation

Monomiality principle, Sheffer-type polynomials and the normal ordering problem

We solve the boson normal ordering problem for $(q(a^\dag)a+v(a^\dag))^n$ with arbitrary functions $q(x)$ and $v(x)$ and integer $n$, where $a$ and $a^\dag$ are boson annihilation and creation operators, satisfying $[a,a^\dag]=1$. This consequently provides the solution for the exponential $e^{\lambda(q(a^\dag)a+v(a^\dag))}$ generalizing the shift operator. In the course of these considerations we define and explore the monomiality principle and find its representations. We exploit the properties of Sheffer-type polynomials which constitute the inherent structure of this problem. In the end we give some examples illustrating the utility of the method and point out the relation to combinatorial structures.Comment: Presented at the 8'th International School of Theoretical Physics "Symmetry and Structural Properties of Condensed Matter " (SSPCM 2005), Myczkowce, Poland. 13 pages, 31 reference

Integrated evaluation of indoor particulate exposure. The viepi project

Despite the progress made in recent years, reliable modeling of indoor air quality is still far from being obtained. This requires better chemical characterization of the pollutants and airflow physics included in forecasting tools, for which field observations conducted simultaneously indoors and outdoors are essential. The project “Integrated Evaluation of Indoor Particulate Exposure” (VIEPI) aimed at evaluating indoor air quality and exposure to particulate matter (PM) of humans in workplaces. VIEPI ran from February 2016 to December 2019 and included both numerical simulations and field campaigns carried out in universities and research environments located in urban and non-urban sites in the metropolitan area of Rome (Italy). VIEPI focused on the role played by micrometeorology and indoor airflow characteristics in determining indoor PM concentration. Short-and long-term study periods captured diurnal, weekly, and seasonal variability of airflow and PM concentration. Chemical characterization of PM10, including the determination of elements, ions, elemental carbon, organic carbon, and bioaerosol, was also carried out. Large differences in the composition of PM10 were detected between inside and outside as well as between different periods of the day and year. Indoor PM composition was related to the presence of people, to the season, and to the ventilation regime

Influence of wood species on toxicity of log-wood stove combustion aerosols: A parallel animal and air-liquid interface cell exposure study on spruce and pine smoke

Background Wood combustion emissions have been studied previously either by in vitro or in vivo models using collected particles, yet most studies have neglected gaseous compounds. Furthermore, a more accurate and holistic view of the toxicity of aerosols can be gained with parallel in vitro and in vivo studies using direct exposure methods. Moreover, modern exposure techniques such as air-liquid interface (ALI) exposures enable better assessment of the toxicity of the applied aerosols than, for example, the previous state-of-the-art submerged cell exposure techniques. Methods We used three different ALI exposure systems in parallel to study the toxicological effects of spruce and pine combustion emissions in human alveolar epithelial (A549) and murine macrophage (RAW264.7) cell lines. A whole-body mouse inhalation system was also used to expose C57BL/6 J mice to aerosol emissions. Moreover, gaseous and particulate fractions were studied separately in one of the cell exposure systems. After exposure, the cells and animals were measured for various parameters of cytotoxicity, inflammation, genotoxicity, transcriptome and proteome. Results We found that diluted (1:15) exposure pine combustion emissions (PM1 mass 7.7 ± 6.5 mg m− 3, 41 mg MJ$^{Zahl}$) contained, on average, more PM and polycyclic aromatic hydrocarbons (PAHs) than spruce (PM1 mass 4.3 ± 5.1 mg m− 3, 26 mg MJ− 1) emissions, which instead showed a higher concentration of inorganic metals in the emission aerosol. Both A549 cells and mice exposed to these emissions showed low levels of inflammation but significantly increased genotoxicity. Gaseous emission compounds produced similar genotoxicity and a higher inflammatory response than the corresponding complete combustion emission in A549 cells. Systems biology approaches supported the findings, but we detected differing responses between in vivo and in vitro experiments. Conclusions Comprehensive in vitro and in vivo exposure studies with emission characterization and systems biology approaches revealed further information on the effects of combustion aerosol toxicity than could be achieved with either method alone. Interestingly, in vitro and in vivo exposures showed the opposite order of the highest DNA damage. In vitro measurements also indicated that the gaseous fraction of emission aerosols may be more important in causing adverse toxicological effects. Combustion aerosols of different wood species result in mild but aerosol specific in vitro and in vivo effects

The negative natural rate of interest in the modern theories of Liquidity Trap and Secular Stagnation: back to Bohm-Bawerk via Samuelson

The negative natural rate of interest is since two decades eliciting theoretical and policy debates. It re-emerged, after a relatively long time, in Krugman's Liquidity Trap model. Later, it was placed at the hearth of the Secular Stagnation theory by Summers. It is argued that Krugman's negative natural rate of interest ensues from theoretical premises analogous to those present in Samuelson's overlapping-generations model. In turn, Samuelson obtained a negative equilibrium interest rate by opportunely recasting Bohm-Bawerk's three causes for a positive rate of interest. The present paper illustrates and analyses this line of thought until its recent developments