mfEGRA: Multifidelity Efficient Global Reliability Analysis through Active Learning for Failure Boundary Location

This paper develops mfEGRA, a multifidelity active learning method using data-driven adaptively refined surrogates for failure boundary location in reliability analysis. This work addresses the issue of prohibitive cost of reliability analysis using Monte Carlo sampling for expensive-to-evaluate high-fidelity models by using cheaper-to-evaluate approximations of the high-fidelity model. The method builds on the Efficient Global Reliability Analysis (EGRA) method, which is a surrogate-based method that uses adaptive sampling for refining Gaussian process surrogates for failure boundary location using a single-fidelity model. Our method introduces a two-stage adaptive sampling criterion that uses a multifidelity Gaussian process surrogate to leverage multiple information sources with different fidelities. The method combines expected feasibility criterion from EGRA with one-step lookahead information gain to refine the surrogate around the failure boundary. The computational savings from mfEGRA depends on the discrepancy between the different models, and the relative cost of evaluating the different models as compared to the high-fidelity model. We show that accurate estimation of reliability using mfEGRA leads to computational savings of $\sim$46% for an analytic multimodal test problem and 24% for a three-dimensional acoustic horn problem, when compared to single-fidelity EGRA. We also show the effect of using a priori drawn Monte Carlo samples in the implementation for the acoustic horn problem, where mfEGRA leads to computational savings of 45% for the three-dimensional case and 48% for a rarer event four-dimensional case as compared to single-fidelity EGRA

Simply having a social media profile does not make teens more likely to be bullied online. Demographics and online behavior play a larger role

For many, the internet and social media is a double edged sword. On one hand it can bring people together to socialize, discuss, and collaborate in ways unthinkable mere decades ago. On the other, it can expose us to abuse and harassment from complete and often anonymous strangers, with teenagers especially at risk. But does having a social media profile make it more likely that teenagers will be harassed online? Using national survey data of teenagers and their parents, Anirban Sengupta and Anoshua Chaudhuri find that demographic and behavioral characteristics of teenagers are stronger predictors of online abuse than simply having an online profile. They find that girls and those who post large amounts of personal information online are more prone to online harassment

Self-Contained Hybrid Electro-Hydraulic Actuators using Magnetostrictive and Electrostrictive Materials

Hybrid electro-hydraulic actuators using smart materials along with flow rectification have been widely reported in recent years. The basic operation of these actuators involves high frequency bidirectional operation of an active material that is converted into unidirectional fluid motion by a set of valves. While theoretically attractive, practical constraints limit the efficacy of the solid-fluid hybrid actuation approach. In particular, inertial loads, fluid viscosity and compressibility combine with loss mechanisms inherent in the active material to limit the effective bandwidth of the driving actuator and the total output power. A hybrid actuator was developed by using magnetostrictive TerFeNOL-D as the active driving element and hydraulic oil as the working fluid. Tests, both with and without an external load, were carried out to measure the unidirectional performance of the actuator at different pumping frequencies and operating conditions. The maximum no-load output velocity was 84 mm/s with a 51 mm long rod and 88 mm/s with a 102 mm long rod, both noted around 325 Hz pumping frequency, while the blocked force was close to 89 N. Dynamic tests were performed to analyze the axial vibration characteristics of the Terfenol-D rods and frequency responses of the magnetic circuits. A second prototype actuator employing the same actuation principle was then designed by using the electrostrictive material PMN-32%PT as the driving element. Tests were conducted to measure the actuator performance for varying electrical input conditions and fluid bias pressures. The peak output velocity obtained was 330 mm/s while the blocked force was 63 N. The maximum volume flow rate obtained with the PMN-based actuator was more than double that obtained from the Terfenol-D-based actuator. Theoretical modeling of the dynamics of the coupled structural-hydraulic system is extremely complex and several models have been proposed earlier. At high pumping frequencies, the fluid inertia dominates the viscous effects and the problem becomes unsteady in nature. Due to high pressures inside the actuator and the presence of entrained air, compressibility of the hydraulic fluid is important. A new mathematical model of the hydraulic hybrid actuator was formulated in time-domain to show the basic operational principle under varying operating conditions and to capture the phenomena affecting system performance. Linear induced strain behavior was assumed to model the active material. Governing equations for the moving parts were obtained from force equilibrium considerations, while the coupled inertia-compliance of the fluid passages was represented by a lumped parameter approach to the transmission line model, giving rise to strongly coupled ordinary differential equations. Compressibility of the working fluid was incorporated by using the bulk modulus. The model was then validated using the measured performance of both the magnetostrictive and electrostrictive-based hybrid actuators

Parallel surrogate-assisted global optimization with expensive functions – a survey

Surrogate assisted global optimization is gaining popularity. Similarly, modern advances in computing power increasingly rely on parallelization rather than faster processors. This paper examines some of the methods used to take advantage of parallelization in surrogate based global optimization. A key issue focused on in this review is how different algorithms balance exploration and exploitation. Most of the papers surveyed are adaptive samplers that employ Gaussian Process or Kriging surrogates. These allow sophisticated approaches for balancing exploration and exploitation and even allow to develop algorithms with calculable rate of convergence as function of the number of parallel processors. In addition to optimization based on adaptive sampling, surrogate assisted parallel evolutionary algorithms are also surveyed. Beyond a review of the present state of the art, the paper also argues that methods that provide easy parallelization, like multiple parallel runs, or methods that rely on population of designs for diversity deserve more attention.United States. Dept. of Energy (National Nuclear Security Administration. Advanced Simulation and Computing Program. Cooperative Agreement under the Predictive Academic Alliance Program. DE-NA0002378

Multifidelity Uncertainty Propagation via Adaptive Surrogates in Coupled Multidisciplinary Systems

Fixed point iteration is a common strategy to handle interdisciplinary coupling within a feedback-coupled multidisciplinary analysis. For each coupled analysis, this requires a large number of disciplinary high-fidelity simulations to resolve the interactions between different disciplines. When embedded within an uncertainty analysis loop (e.g., with Monte Carlo sampling over uncertain parameters), the number of high-fidelity disciplinary simulations quickly becomes prohibitive, because each sample requires a fixed point iteration and the uncertainty analysis typically involves thousands or even millions of samples. This paper develops a method for uncertainty quantification in feedback-coupled systems that leverage adaptive surrogates to reduce the number of cases forwhichfixedpoint iteration is needed. The multifidelity coupled uncertainty propagation method is an iterative process that uses surrogates for approximating the coupling variables and adaptive sampling strategies to refine the surrogates. The adaptive sampling strategies explored in this work are residual error, information gain, and weighted information gain. The surrogate models are adapted in a way that does not compromise the accuracy of the uncertainty analysis relative to the original coupled high-fidelity problem as shown through a rigorous convergence analysis.United States. Army Research Office. Multidisciplinary University Research Initiative (Award FA9550-15-1-0038

Evidence of mobile carriers with Charge Ordering gap in Epitaxial Pr0.625_{0.625}Ca0.375_{0.375}MnO3_{3} Thin Films

Epitaxial thin films of charge-ordered Pr$_{0.625}$Ca$_{0.375}$MnO$_{3}$ have been studied using variable temperature Scanning tunneling microscopy and spectroscopy (STM/STS). The as grown films were found to be granular while the annealed films show atomic terraces at all temperatures and are found to be electronically homogeneous in 78-300K temperature range. At high temperatures (T$>$T$_{CO}\approx$ 230 K) the local tunnel spectra of the annealed films show a depression in the density of states (DOS) near Fermi energy implying a pseudogap with a significant DOS at E$_F$. The gap feature becomes more robust with cooling with a sharp jump in DOS at E$_F$ at T$_{CO}$ and with a gap value of $\sim$0.3 eV at 78K. At low temperatures we find a small but finite DOS at E$_F$ indicative of some delocalized carriers in the CO phase together with an energy gap. This is consistent with bulk transport, which shows weakening of the activation gap with cooling below 200K, and indicates the presence of two types of carriers at low temperatures.Comment: 4 pages, 4 figure