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Global Sensitivity Analysis of Helmholtz Coils for Enhanced Homogeneous Magnetic Field of Electromagnetic Flowmeters
Get PDFHelmholtz coils are widely used to generate homogeneous magnetic fields. Various parameters influence the magnetic field strength and homogeneity, including coil shape, size, spacing, winding layers, winding turns, and axial and radial gaps between windings. Previous researches have partially examined these parameters through local sensitivity analysis, where each parameter is varied independently while others are held constant. However, such studies often have limited applicability due to the interdependence of parameters including coil size, spacing, and windings. This work employs a new global sensitivity analysis, reciprocal optimum solution, to investigate the interconnections between these parameters and their effects on magnetic flux density and field homogeneity. This approach eliminates the need to manually optimize variable ranges and mitigates the issues of randomness, uncertainty, and slow convergence by producing both deterministic formulas and a blueprint for designing Helmholtz coils with homogeneous magnetic fields. Using this method, we produced open-source Helmholtz coils development software. This enables users to obtain design parameters for Helmholtz coils for a required homogeneous magnetic field domain, when provided either its cross-sectional diameter or the coil spacing required for the device.</p
Income Differentials & Rate of Time Preference:A Developing Country Perspective
Get PDFEstimating time preferences in developing countries like India, is essential for designing public policies that influence savings and investment decisions. However, limited data availability and various economic constraints restrict the estimation process and its analysis. Following Lawrance (1991) framework, this paper adopts Euler equation approach to estimate individual time preferences and assess its relation with one’s income level, in the context of India. Using a national level household survey, the CMIE CPHS dataset spanning 2014-2019, the average RTP for the Indian population is estimated to be 0.0689. It means that on average, individuals in India are willing to forgo 6.89% of future consumption to have the same amount of consumption today. Furthermore, the results show that wealthier individuals are marginally more patient than poorer ones, exhibiting decreasing marginal impatience. These findings have significant policy implications for shaping redistributive, welfare, and growth policies in India
Dataset for "Zero-car households – constraint or lifestyle choice? A systematic literature review of the factors affecting non-car ownership"
No full textThe dataset contains details of 106 studies identified through a systematic review of literature. It shows the details of the study, a categorisation according to which of the five factors the study addresses: socio-demographic, psychological, life events, built environment and transport policies and services
Improving the predictive capability of empirical heat transfer correlations for hydrogen internal combustion engines
Get PDFHydrogen internal combustion is widely considered a viable technology to achieve near-zero tailpipe CO2 and NOx emissions for difficult-to-electrify applications due to the maturity of ICE technology and production facilities. One-dimensional/zero-dimensional (0D) modeling is a valuable tool for engine development due to its relatively low computational requirements, but hydrogen combustion models still require further development. A large factor is gas-to-wall heat transfer, which is higher for hydrogen combustion due to higher flame temperatures and shorter quenching distance. For accurate prediction of in-cylinder temperatures, and therefore combustion rates and knock propensity, a well calibrated heat transfer model is essential. This paper evaluates existing heat transfer models against previously published experimental cylinder pressure and heat flux data from a Cooperative Fuel Research (CFR) engine with hydrogen Port Fuel Injection (PFI). A new heat transfer correlation is developed, utilizing a new fluid properties correlation to better represent the change in viscosity and conductivity with changing hydrogen concentration. Recent developments in 0D turbulence models improve the characteristic velocity calculation, which is augmented with a combustion term. This model is tested against a second dataset from the CFR engine with lambda from 1.0 to 4.0 and compression ratios of 9–13, showing improved performance versus previously published models. Whilst the new model provides more consistent results during combustion for variations in lambda and compression ratio, it requires improvement in its prediction of heat loss during expansion, and further validation at higher engine speeds and different engine configurations
Imino‐Pyrrole Zn(II) Complexes for the Rapid and Selective Chemical Recycling of Commodity Polymers
Get PDFThree imino-pyrrole zinc complexes were prepared and applied to the rapid degradation of polylactic acid (PLA) and the depolymerization of bisphenol A polycarbonate (BPA-PC) and polyethylene terephthalate (PET). PLA alcoholysis proceeded rapidly at a range of conditions, including reflux in air. Remarkable activity was demonstrated for the solvent-free methanolysis of PLA at mild conditions with full conversion reached in 11 min at 80 °C. Various conditions were investigated including a range of PLA sources and, importantly, catalyst recycling was demonstrated. The methanolysis of BPA-PC and the glycolysis of PET were achieved, the latter giving full conversion after 1.5 h for all catalysts. The chemical recycling of mixed plastic feedstocks was investigated, including the selective and sequential degradation of a PLA/BPA-PC mixture with a single catalyst and solvent.</p
The TFIID complex is a new autoantibody target in systemic sclerosis
Get PDFSystemic sclerosis (SSc) is characterised by systemic fibrosis, vascular dysfunction, and the presence of antinuclear autoantibodies. The major SSc-associated antinuclear antibodies include anticentromere, antitopoisomerase I, anti–RNA polymerase III and antifibrillarin autoantibodies [1]. These autoantibodies are generally mutually exclusive and define clinically relevant subgroups
On quantitative convergence for stochastic processes:Crossings, fluctuations and martingales
Get PDFWe develop a general framework for extracting highly uniform bounds on local stability for stochastic processes in terms of information on fluctuations or crossings. This includes a large class of martingales: As a corollary of our main abstract result, we obtain a quantitative version of Doob's convergence theorem for -sub- and supermartingales, but more importantly, demonstrate that our framework readily extends to more complex stochastic processes such as almost-supermartingales, thus paving the way for future applications in stochastic optimization. Fundamental to our approach is the use of ideas from logic, particularly a careful analysis of the quantifier structure of probabilistic statements and the introduction of a number of abstract notions that represent stochastic convergence in a quantitative manner. In this sense, our work falls under the `proof mining' program, and indeed, our quantitative results provide new examples of the phenomenon, recently made precise by the first author and Pischke, that many proofs in probability theory are proof-theoretically tame, and amenable to the extraction of quantitative data that is both of low complexity and independent of the underlying probability space
MorekerLess – Better pose estimation with less work
Get PDFMarkerless motion capture is becoming the new norm for kinematic analysis, but some challenges remain. One of them lies in 2D pose estimation: anatomical keypoints could be labeled more accurately and should be more numerous for certain parts of the body, such as the spine. However, manually creating a new dataset or modifying annotations is extremely costly, as hundreds of thousands of images are generally required. We introduce MorekerLess, a pipeline for automatically labeling and training on any keypoint set. Results show that additional keypoints are correctly detected, and joint center estimation is improved by 0.2-0.4 cm over the current state-of-the-art. Our pipeline and models will be released at: http://github.com/davidpagnon/morekerless
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