Development and analysis of radial force waves in electrical rotating machines

Vibrations in electrical machines lead to undesired operating conditions and noise. The reasons lie in the design of the machine and the lack of precision in manufacturing. In order to avoid excessive vibrations, complex numerical analyses are carried out. This work deals with the development and analysis of electromechanical excitations in asynchronous machines with a short circuit rotor. The time-dependent electromagnetic forces acting on the stator bore are simulated with the method of finite elements. Subsequently, the force waves with respect to the frequencies and amplitudes are analyzed

Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model

It recently has been demonstrated that magnetic resonance imaging can be used to map changes in brain hemodynamics produced by human mental operations. One method under development relies on blood oxygenation level-dependent (BOLD) contrast: a change in the signal strength of brain water protons produced by the paramagnetic effects of venous blood deoxyhemoglobin. Here we discuss the basic quantitative features of the observed BOLD-based signal changes, including the signal amplitude and its magnetic field dependence and dynamic effects such as a pronounced oscillatory pattern that is induced in the signal from primary visual cortex during photic stimulation experiments. The observed features are compared with the results of Monte Carlo simulations of water proton intravoxel phase dispersion produced by local field gradients generated by paramagnetic deoxyhemoglobin in nearby venous blood vessels. The simulations suggest that the effect of water molecule diffusion is strong for the case of blood capillaries, but, for larger venous blood vessels, water diffusion is not an important determinant of deoxyhemoglobin-induced signal dephasing. We provide an expression for the apparent in-plane relaxation rate constant (R2*) in terms of the main magnetic field strength, the degree of the oxygenation of the venous blood, the venous blood volume fraction in the tissue, and the size of the blood vessel

Identifying content to improve risk assessment communications within the Risk Profile: Literature reviews and focus groups with expert and non-expert stakeholders

Objective: To improve consumer decision making, the results of risk assessments on food, feed, consumer products or chemicals need to be communicated not only to experts but also to non-expert audiences. The present study draws on evidence from literature reviews and focus groups with diverse stakeholders to identify content to integrate into an existing risk assessment communication (Risk Profile). Methods: A combination of rapid literature reviews and focus groups with experts (risk assessors (n = 15), risk managers (n = 8)), and non-experts (general public (n = 18)) were used to identify content and strategies for including information about risk assessment results in the “Risk Profile” from the German Federal Institute for Risk Assessment. Feedback from initial focus groups was used to develop communication prototypes that informed subsequent feedback rounds in an iterative process. A final prototype was validated in usability tests with experts. Results: Focus group feedback and suggestions from risk assessors were largely in line with findings from the literature. Risk managers and lay persons offered similar suggestions on how to improve the existing communication of risk assessment results (e.g., including more explanatory detail, reporting probabilities for individual health impairments, and specifying risks for subgroups in additional sections). Risk managers found information about quality of evidence important to communicate, whereas people from the general public found this information less relevant. Participants from lower educational backgrounds had difficulties understanding the purpose of risk assessments. User tests found that the final prototype was appropriate and feasible to implement by risk assessors. Conclusion: An iterative and evidence-based process was used to develop content to improve the communication of risk assessments to the general public while being feasible to use by risk assessors. Remaining challenges include how to communicate dose-response relationships and standardise quality of evidence ratings across disciplines.Peer Reviewe

Road salt emissions: A comparison of measurements and modelling using the NORTRIP road dust emission model

AbstractDe-icing of road surfaces is necessary in many countries during winter to improve vehicle traction. Large amounts of salt, most often sodium chloride, are applied every year. Most of this salt is removed through drainage or traffic spray processes but a certain amount may be suspended, after drying of the road surface, into the air and will contribute to the concentration of particulate matter. Though some measurements of salt concentrations are available near roads, the link between road maintenance salting activities and observed concentrations of salt in ambient air is yet to be quantified. In this study the NORTRIP road dust emission model, which estimates the emissions of both dust and salt from the road surface, is applied at five sites in four Nordic countries for ten separate winter periods where daily mean ambient air measurements of salt concentrations are available. The model is capable of reproducing many of the salt emission episodes, both in time and intensity, but also fails on other occasions. The observed mean concentration of salt in PM10, over all ten datasets, is 4.2 μg/m3 and the modelled mean is 2.8 μg/m3, giving a fractional bias of −0.38. The RMSE of the mean concentrations, over all 10 datasets, is 2.9 μg/m3 with an average R2 of 0.28. The mean concentration of salt is similar to the mean exhaust contribution during the winter periods of 2.6 μg/m3. The contribution of salt to the kerbside winter mean PM10 concentration is estimated to increase by 4.1 ± 3.4 μg/m3 for every kg/m2 of salt applied on the road surface during the winter season. Additional sensitivity studies showed that the accurate logging of salt applications is a prerequisite for predicting salt emissions, as well as good quality data on precipitation. It also highlights the need for more simultaneous measurements of salt loading together with ambient air concentrations to help improve model parameterisations of salt and moisture removal processes

Spatial and temporal variations in ammonia emissions – a freely accessible model code for Europe

Deriving a parameterisation of ammonia emissions for use in chemistry-transport models (CTMs) is a complex problem as the emission varies locally as a result of local climate and local agricultural management. In current CTMs such factors are generally not taken into account. This paper demonstrates how local climate and local management can be accounted for in CTMs by applying a modular approach for deriving data as input to a dynamic ammonia emission model for Europe. Default data are obtained from information in the RAINS system, and it is demonstrated how this dynamic emission model based on these input data improves the NH<sub>3</sub> calculations in a CTM model when the results are compared with calculations obtained by traditional methods in emission handling. It is also shown how input data can be modified over a specific target region resulting in even further improvement in performance over this domain. The model code and the obtained default values for the modelling experiments are available as supplementary information to this article for use by the modelling community on similar terms as the EMEP CTM model: the GPL licencse v3

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Similarities in network segmentations were evaluated using pairwise Dice correlations. Articular cartilage thickness was computed per-scan and longitudinally. Correlation between thickness error and segmentation metrics was measured using Pearson's coefficient. Two empirical upper bounds for ensemble performance were computed using combinations of model outputs that consolidated true positives and true negatives. Results: Six teams (T1-T6) submitted entries for the challenge. No significant differences were observed across all segmentation metrics for all tissues (p=1.0) among the four top-performing networks (T2, T3, T4, T6). Dice correlations between network pairs were high (>0.85). Per-scan thickness errors were negligible among T1-T4 (p=0.99) and longitudinal changes showed minimal bias (<0.03mm). Low correlations (<0.41) were observed between segmentation metrics and thickness error. The majority-vote ensemble was comparable to top performing networks (p=1.0). Empirical upper bound performances were similar for both combinations (p=1.0). Conclusion: Diverse networks learned to segment the knee similarly where high segmentation accuracy did not correlate to cartilage thickness accuracy. Voting ensembles did not outperform individual networks but may help regularize individual models.Comment: Submitted to Radiology: Artificial Intelligence; Fixed typo

Improved modelling of atmospheric ammonia over Denmark using the coupled modelling system DAMOS

A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM with a resolution of approximately 6 km × 6 km over Denmark) in the Danish Ammonia Modelling System, DAMOS. Thereby, it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m × 400 m for selected areas in Denmark. DAMOS has been validated against measured concentrations from the dense measuring network covering Denmark. Here measured data from 21 sites are included and the validation period covers 2–5 years within the period 2005–2009. A standard time series analysis (using statistic parameters like correlation and bias) shows that the coupled model system captures the measured time series better than the regional- scale model alone. However, our study also shows that about 50% of the modelled concentration level at a given location originates from non-local emission sources. The local-scale model covers a domain of 16 km × 16 km, and of the locally released ammonia (NH&lt;sub&gt;3&lt;/sub&gt;) within this domain, our simulations at five sites show that 14–27% of the locally (within 16 km × 16 km) emitted NH&lt;sub&gt;3&lt;/sub&gt; also deposits locally. These results underline the importance of including both high-resolution local-scale modelling of NH&lt;sub&gt;3&lt;/sub&gt; as well as the regional-scale component described by the regional model. The DAMOS system can be used as a tool in environmental management in relation to assessments of total nitrogen load of sensitive nature areas in intense agricultural regions. However, high spatio-temporal resolution in input parameters like NH&lt;sub&gt;3&lt;/sub&gt; emissions and land-use data is required