Application of Subset Simulation to Seismic Risk Analysis

This paper presents the application of a new reliability method called Subset Simulation to seismic risk analysis of a structure, where the exceedance of some performance quantity, such as the peak interstory drift, above a specified threshold level is considered for the case of uncertain seismic excitation. This involves analyzing the well-known but difficult first-passage failure problem. Failure analysis is also carried out using results from Subset Simulation which yields information about the probable scenarios that may occur in case of failure. The results show that for given magnitude and epicentral distance (which are related to the ‘intensity’ of shaking), the probable mode of failure is due to a ‘resonance effect.’ On the other hand, when the magnitude and epicentral distance are considered to be uncertain, the probable failure mode correspondsto the occurrence of ‘large-magnitude, small epicentral distance’ earthquakes

The Mixed Instrumental Controller: Using Value of Information to Combine Habitual Choice and Mental Simulation

Instrumental behavior depends on both goal-directed and habitual mechanisms of choice. Normative views cast these mechanisms in terms of model-free and model-based methods of reinforcement learning, respectively. An influential proposal hypothesizes that model-free and model-based mechanisms coexist and compete in the brain according to their relative uncertainty. In this paper we propose a novel view in which a single Mixed Instrumental Controller produces both goal-directed and habitual behavior by flexibly balancing and combining model-based and model-free computations. The Mixed Instrumental Controller performs a cost-benefits analysis to decide whether to chose an action immediately based on the available “cached” value of actions (linked to model-free mechanisms) or to improve value estimation by mentally simulating the expected outcome values (linked to model-based mechanisms). Since mental simulation entails cognitive effort and increases the reward delay, it is activated only when the associated “Value of Information” exceeds its costs. The model proposes a method to compute the Value of Information, based on the uncertainty of action values and on the distance of alternative cached action values. Overall, the model by default chooses on the basis of lighter model-free estimates, and integrates them with costly model-based predictions only when useful. Mental simulation uses a sampling method to produce reward expectancies, which are used to update the cached value of one or more actions; in turn, this updated value is used for the choice. The key predictions of the model are tested in different settings of a double T-maze scenario. Results are discussed in relation with neurobiological evidence on the hippocampus – ventral striatum circuit in rodents, which has been linked to goal-directed spatial navigation

Towards Quantitative Simulations of High Power Proton Cyclotrons

PSI operates a cyclotron based high intensity proton accelerator routinely at an average beam power of 1.3MW. With this power the facility is at the worldwide forefront of high intensity proton accelerators. The beam current is practically limited by losses at extraction and the resulting activation of accelerator components. Further intensity upgrades and new projects aiming at an even higher average beam power, are only possible if the relative losses can be lowered in proportion, thus keeping absolute losses at a constant level. Maintaining beam losses at levels allowing hands-on maintenance is a primary challenge in any high power proton machine design and operation. In consequence, predicting beam halo at these levels is a great challenge and will be addressed in this paper. High power hadron driver have being used in many disciplines of science and, a growing interest in the cyclotron technology for high power hadron drivers are being observed very recently. This report will briefly introduce OPAL, a tool for precise beam dynamics simulations including 3D space charge. One of OPAL's flavors (OPAL-cycl) is dedicated to high power cyclotron modeling and is explained in greater detail. We then explain how to obtain initial conditions for our PSI Ring cyclotron which still delivers the world record in beam power of 1.3 MW continuous wave (cw). Several crucial steps are explained necessary to be able to predict tails at the level of 3\sigma ... 4\sigma in the PSI Ring cyclotron. We compare our results at the extraction with measurements, obtained with a 1.18 MW cw production beam. Based on measurement data, we develop a simple linear model to predict beam sizes of the extracted beam as a function of intensities and confirm the model with simulations.Comment: Corrections and new figur