Importance Sampling for Pathwise Sensitivity of Stochastic Chaotic Systems

This paper proposes a new pathwise sensitivity estimator for chaotic SDEs. By introducing a spring term between the original and perturbated SDEs, we derive a new estimator by importance sampling. The variance of the new estimator increases only linearly in time $T,$ compared with the exponential increase of the standard pathwise estimator. We compare our estimator with the Malliavin estimator and extend both of them to the Multilevel Monte Carlo method, which further improves the computational efficiency. Finally, we also consider using this estimator for the SDE with small volatility to approximate the sensitivities of the invariant measure of chaotic ODEs. Furthermore, Richardson-Romberg extrapolation on the volatility parameter gives a more accurate and efficient estimator. Numerical experiments support our analysis.Comment: 29 pages, 31 figure

AC Loss Calculation on a 6.5 MVA/25 kV HTS Traction Transformer with Hybrid Winding Structure

HTS wire cost is a critical factor for successful commercialization of HTS traction transformer technology. Wire cost might be minimized without significantly increasing AC loss by introducing a hybrid winding structure: the end-part of the windings is wound with high-cost high-I c wires; the central-part of the windings is wound with low-cost low-I c wires. We report AC loss simulation results on HTS windings with both HV and LV windings wound with REBCO wires. The 2D axisymmetric FEM simulation was carried out using H-formulation. The HV windings are wound with 4 mm-wide wires and LV windings are wound with 8/5 (eight 5 mm - wide strands) Roebel cables. Both HV and LV windings have a hybrid structure in order to reduce the wire cost. Flux diverters are placed at the end of the windings to reduce AC loss. Significant HTS wire cost reduction could be achieved without compromising AC loss by using hybrid windings. This may help commercialize HTS traction transformer technology

Design of a single-phase 6.5 MVA/25 kV superconducting traction transformer for the Chinese Fuxing high-speed train

Traction transformers are critical components of Chinese high-speed-trains. We are currently building a single–phase 6.5 MVA superconducting traction transformer which can achieve targets of less than 3 tons of transformer system weight, better than 99% efficiency, and 43% short-circuit impedance. The proposed transformer consists of four single-phase 25 kV/1.9 kV HTS windings, operating at 65 K, each of which drives a motor. The design incorporates Roebel cable in the LV windings to cope with large current and minimize AC loss. We present 2D FEM AC loss modelling results that identify the critical parameters that contribute to AC loss. We show that the combination of winding length ≥1 m, high performance Fujikura wires, and flux diverters arranged at the end of HV and LV windings, can restrain AC loss in the HTS windings to under 2 kW. We introduce an open-loop cooling system concept with sub-cooler integrated inside the transformer cryostat that can achieve total system weight under 3 tons assuming 2.5 kW total heat load and 8 h of continuous running time. A nominal efficiency of 99.5% can be achieved for this total heat load. The entire superconducting transformer system can be readily fit in the space allocated for conventional transformers in the Chinese Fuxing trains

Superconducting traction transformer:Traction - the HTS Transformer Killer Application?

An ongoing project to develop HTS traction transformers for the Chinese Fuxing high-speed train is demonstrating that the high power density accessible using high temperature superconductors (HTS) can produce spectacular results: the existing 6.5 MVA traction transformers can be replaced with drop-in superconducting transformers which can achieve targets of less than 3 tons transformer system weight and 99.5% efficiency compared to 6 tons and 95% in the existing devices. The key to achieving these impressive figures is minimising the AC loss of the HTS windings. New high-performance wire, high current HTS Roebel conductor, high aspect-ratio windings, and flux diverters placed at the winding ends all contribute to reducing the electrical loss to less than 2 kW

Bayesian Activity Estimation and Uncertainty Quantification of Spent Nuclear Fuel Using Passive Gamma Emission Tomography

In this paper, we address the problem of activity estimation in passive gamma emission tomography (PGET) of spent nuclear fuel. Two different noise models are considered and compared, namely, the isotropic Gaussian and the Poisson noise models. The problem is formulated within a Bayesian framework as a linear inverse problem and prior distributions are assigned to the unknown model parameters. In particular, a Bernoulli-truncated Gaussian prior model is considered to promote sparse pin configurations. A Markov chain Monte Carlo (MCMC) method, based on a split and augmented Gibbs sampler, is then used to sample the posterior distribution of the unknown parameters. The proposed algorithm is first validated by simulations conducted using synthetic data, generated using the nominal models. We then consider more realistic data simulated using a bespoke simulator, whose forward model is non-linear and not available analytically. In that case, the linear models used are mis-specified and we analyse their robustness for activity estimation. The results demonstrate superior performance of the proposed approach in estimating the pin activities in different assembly patterns, in addition to being able to quantify their uncertainty measures, in comparison with existing methods

Dietary yeast influences ethanol sedation in Drosophila via serotonergic neuron function

Abuse of alcohol is a major clinical problem with far- reaching health consequences. Understanding the environmental and genetic factors that contribute to alcohol- related behaviors is a potential gateway for developing novel therapeutic approaches for patients that abuse the drug. To this end, we have used Drosophila melanogaster as a model to investigate the effect of diet, an environmental factor, on ethanol sedation. Providing flies with diets high in yeast, a routinely used component of fly media, increased their resistance to ethanol sedation. The yeast- induced resistance to ethanol sedation occurred in several different genetic backgrounds, was observed in males and females, was elicited by yeast from different sources, was readily reversible, and was associated with increased nutrient intake as well as decreased internal ethanol levels. Inhibition of serotonergic neuron function using multiple independent genetic manipulations blocked the effect of yeast supplementation on ethanol sedation, nutrient intake, and internal ethanol levels. Our results demonstrate that yeast is a critical dietary component that influences ethanol sedation in flies and that serotonergic signaling is required for the effect of dietary yeast on nutrient intake, ethanol uptake/elimination, and ethanol sedation. Our studies establish the fly as a model for diet- induced changes in ethanol sedation and raise the possibility that serotonin might mediate the effect of diet on alcohol- related behavior in other species.Flies fed a high yeast diet consume more nutrients, have decreased levels of internal ethanol when exposed to ethanol vapor and require longer exposure to ethanol to become sedated (ie, increased ST50). Our studies implicate serotonergic neurons as key regulators of nutrient consumption and therefore, the effect of dietary yeast on ethanol sedation in flies.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155987/1/adb12779.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155987/2/adb12779_am.pd

Millennial‐scale climatic change during the Last Interglacial Period: Superparamagnetic sediment proxy from Paleosol S1, western Chinese Loess Plateau

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94646/1/grl12218.pd