A new engineering approach to predict the long-term hydrostatic strength of unplasticized poly(vinyl chloride) pipes

Extruded polymer pipes are qualified using pressurized pipe tests. With these tests the long-term hydrostatic strength is determined by subjecting the pipes to an internal pressure, while measuring the time-to-failure. Although these tests can be accelerated (at higher temperatures), they remain time consuming and require a spacious experimental setup. To circumvent this costly method a model based approach is proposed by which the long-term hydrostatic strength is predicted. Using short term measurements, the input parameters for this approach can be determined. In this engineering approach the effects of physical aging are included. The approach is capable to quantitatively predict the (long-term) failure time of pipe sections under internal pressure

Analysis of the entanglement between two individual atoms using global Raman rotations

Making use of the Rydberg blockade, we generate entanglement between two atoms individually trapped in two optical tweezers. In this paper we detail the analysis of the data and show that we can determine the amount of entanglement between the atoms in the presence of atom losses during the entangling sequence. Our model takes into account states outside the qubit basis and allows us to perform a partial reconstruction of the density matrix describing the two atom state. With this method we extract the amount of entanglement between pairs of atoms still trapped after the entangling sequence and measure the fidelity with respect to the expected Bell state. We find a fidelity $F_{\rm pairs} =0.74(7)$ for the 62% of atom pairs remaining in the traps at the end of the entangling sequence

Dutch gas distribution grid goes green:decision support tool for local biogas utilization

A Decision Support Tool (DST) has been developed that will aid Distribution Service Operators (DSOs) in their decision making process on which investments to make in the gas distribution grid in order to facilitate the use of biogas. The DST considers both the conversion of biogas to electricity as well as upgrading the biogas to green gas and consequently injecting it into the gas grid. Based on a starting configuration - i.e. a gas grid, gas consumers connected to this grid, and biomass locations -, in combination with several building blocks - e.g. a digester installation, an upgrading plant, and a CHP installation -, the tool generates several solutions to utilize the biomass. The DST generates solutions and determines for each solution two performance criteria: CO2 emission reduction and costs. Showing these solutions, gives the DSOs insight in the available options and which trade-offs can be made. A case study has been performed for the gas grid of the Dutch municipality of Zutphen. This case study showed that cost-wise there is a preference for centralization, i.e. digesting biomass at a central location and upgrading the biogas at a central location to green gas. Furthermore, conversion of biogas to electricity led to the highest CO2 emission reduction, but also to the highest cost.Furthermore, the case study showed that the DST basically works, and that it is a good way to explore the possible investment options. The tool however needs further improvements. For instance, more performance indicators (e.g. energy usage and reliability) will be included. Furthermore, the interaction with the electricity grid will be incorporated and multiple gas qualities in the distribution grid will be introduced. Also more boundary conditions should be added to the DST, for instance taking the topology of the area into account when laying pipeline

Barrier properties of ALD W_1.55N thin films

W1.5N films grown by ALD from WF6, NH3, C2H4 and SiH4 as precursors were tested as Cu diffusion barriers in p+/n diodes and capacitors with SiO2 as a dielectric. I-V and C-V, C-t characteristics were measured before and after anneal. The layers exhibit excellent barrier properties against both Cu and Al interaction with silicon. No changes of current and capacitance attributed to a barrier failure were observed after annealing at 400°C. Samples without the barrier showed a drastic change of the I-V characteristics. The composition of the films was W1.5N as determined with RBS, being a mixture of WN and W2N phases The RMS- roughness was as low as 0.5-0.7 nm for a film with a thickness of 25 nm.</p

Influence of local and remote white matter conductivity anisotropy for a thalamic source on EEG/MEG field and return current computation

nverse methods are used to reconstruct current sources in the human brain by means of Electroencephalogra- phy (EEG) and Magnetoencephalography (MEG) measure- ments of event related fields or epileptic seizures. There exists a persistent uncertainty regarding the influence of anisotropy of the white matter compartment on neural source reconstruc- tion. In this paper, we study the sensitivity to anisotropy of the EEG/MEG forward problem for a thalamic source in a high resolution finite element volume conductor. The influence of anisotropy on computed fields will be presented by both high resolution visualization of fields and return current flow and topography and magnitude error measures. We pay particular attention to the influence of local conductivity changes in the neighborhood of the source. The combination of simulation and visualization provides deep insight into the effect of white matter conductivity anisotropy. We found that for both EEG and MEG formulations, the local presence of electrical anisotropy in the tissue surroun- ding the source substantially compromised the forward field computation, and correspondingly, the inverse source recons- truction. The degree of error resulting from the uncompen- sated presence of tissue anisotropy depended strongly on the proximity of the anisotropy to the source; remote anisotropy had a much weaker influence than anisotropic tissue that included the source

Regularisation, Systematicity and Naturalness in a Silent Gesture Learning Task

Typological analysis of the world’s language shows that, of the 6 possible basic word orders, SOV and SVO orders are predominant, a preference supported by experimental studies in which participants improvise gestures to describe events. Silent gesture studies have also provided evidence for natural ordering patterns, where SOV and SVO orders are used selectively depending on the semantics of the event, a finding recently supported by data from natural sign languages. We present an artificial language learning task using gesture to ask to what extent preferences for natural ordering patterns, in addition to biases for regular languages, are at play during learning in the manual modality