The study demonstrates that the rebound effect of thought suppression (Wegner, 1989) has an analog in the experience of somatic discomfort. During a cold-pressor pain induction, 63 Ss were instructed either to concentrate on their room at home (distraction), to pay close attention to their hand sensations (monitoring), or to remove awareness of those sensations from mind (suppression). Two min of postpressor pain ratings showed that monitoring produced the most rapid recovery from the pain and that suppression produced the slowest. Suppression also contaminated the interpretation of a subsequent somatic stimulation; later in the experimental hour, Ss who had suppressed their cold-pressor discomfort rated an innocuous vibration as more unpleasant than did other Ss. The strategies are discussed for their necessarily distinct processes of goal evaluation and their possibly differential drain on perceived coping capacities.

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Computer codes are widely used to describe physical processes in lieu of physical observations. In some cases, more than one computer simulator, each with different degrees of fidelity, can be used to explore the physical system. In this work, we combine field observations and model runs from deterministic multi-fidelity computer simulators to build a predictive model for the real process. The resulting model can be used to perform sensitivity analysis for the system, solve inverse problems and make predictions. Our approach is Bayesian and will be illustrated through a simple example, as well as a real application in predictive science at the Center for Radiative Shock Hydrodynamics at the University of Michigan.KEY WORDS: Computer Experiment; Gaussian process; Markov Chain Monte Carlo. arXiv:1208.2716v1 [stat.AP] 13 Aug 2012 occur, for example, because of the presence of reduced order physics in lower fidelity models, different levels of accuracy specified for numerical solvers or solutions obtained on finer grids. In these cases, a higher fidelity model is thought to better represent the physical process than a lower fidelity model, but also takes more computer time to produce an output than a lower fidelity model. So, combining relatively cheap lower fidelity model runs with more costly high fidelity runs to emulate the high fidelity model has been an significant problem of interest (Kennedy and O'Hagan, 2000;Qian et al., 2006 and.Another important application of computer models is that of calibration (e.g., Kennedy and O'Hagan, 2001;Higdon et al., 2004) where the aim is to combine simulator outputs with physical observations to build a predictive model and also estimate unknown parameters that govern the behaviour of the computer model. The latter endeavour amounts to solving a sort of inverse problem, while the former activity is a type of regression problem.Motivated by applications at the Center for Radiative Shock Hydrodynamics (CRASH) at the University of Michigan, the aim of this work is to develop new methodology to combine outputs from simulators with different levels of fidelity and field observations to make predictions of the physical system with associated measurements of uncertainty. In the spirit similar to Kennedy and O'Hagan (2000 and2001) and Higdon et al. (2004), we propose a predictive model that incorporates computer model outputs and field data, while attempting to find optimal values for some input parameters (i.e. calibration parameters). Different models are specified for each source of data (Kennedy and O'Hagan, 2000;Qian et al., 2006 and. The approach calibrates each computer model to the next highest level of fidelity model, and the simulator of the highest fidelity is then calibrated to the field measurements. All the response surfaces are Gaussian process (GP) models and the various sources of information that inform predictions of the physical system are combined with a Bayesian hierarchical model. The paper is organized as follows: In section 2, we will introduce the prop...

We describe the CRASH (Center for Radiative Shock Hydrodynamics) code, a block adaptive mesh code for multi-material radiation hydrodynamics. The implementation solves the radiation diffusion model with the gray or multigroup method and uses a flux limited diffusion approximation to recover the free-streaming limit. The electrons and ions are allowed to have different temperatures and we include a flux limited electron heat conduction. The radiation hydrodynamic equations are solved in the Eulerian frame by means of a conservative finite volume discretization in either one, two, or three-dimensional slab geometry or in two-dimensional cylindrical symmetry. An operator split method is used to solve these equations in three substeps:(1) solve the hydrodynamic equations with shock-capturing schemes, (2) a linear advection of the radiation in frequency-logarithm space, and (3) an implicit solve of the stiff radiation diffusion, heat conduction, and energy exchange. We present a suite of verification test problems to demonstrate the accuracy and performance of the algorithms. The CRASH code is an extension of the Block-Adaptive Tree Solarwind Roe Upwind Scheme (BATS-R-US) code with this new radiation transfer and heat conduction library and equation-of-state and multigroup opacity solvers. Both CRASH and BATS-R-US are part of the publicly available Space Weather Modeling Framework (SWMF).

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