CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Application of Radial Basis Functions in History Matching of Production Data

A successful development of oil and gas reservoirs requires a deep understanding of key subsurface complexities, possible development outcomes, and execution of optimal development actions. This is achieved through the utilization of detailed reservoir models that integrate all available data and modern reservoir simulation, which incorporates the whole spectrum of physical and chemical processes associated with development activities. To further improve reservoir models, we condition them to the collected production data through the history matching process. This process employs sequences of reservoir simulation runs to searches for changes in reservoir description that can improve reservoir model prediction accuracy. Over the past decades, multiple assisted history matching algorithms were proposed in order to speed up the process and extend it to handling multiple alternative realizations. However, the history matching process is still highly computationally expensive and associated with compromises in the robustness of the algorithms that have to be made to keep it practical. In this work, we investigate the application of fast Radial Basis Function (RBF) proxy models as a substitute for reservoir simulation in history matching. First, we review the general background in proxy modeling and state-of-the-art developments in the RBF application in engineering optimization problems. We also review the background and recent progress in the development of some popular ensemble-based and multi-objective algorithms and discuss outstanding challenges in their practical implementation. Then we introduce a modified ensemble Kalman filter method (RBF-EnKF) that utilizes RBF proxy models as a partial substitute to numerical simulation. This method improves the accuracy of the cross-covariance estimation between the model parameters and model dynamic responses for small ensemble size. To achieve higher accuracy of RBF proxy models, an improved heterogeneous and anisotropic formulation for basis functions scaling was implemented. The proposed method was tested using a synthetic case and showed significant improvement in cross-covariance estimation and good history matching results. Next, we extended the proposed RBF-EnKF algorithm for application to practical size history matching problems. This was achieved by introducing Grid Connectivity Transforms (GCT) parametrization to convert spatial variables to a set of discrete inputs for proxy models and iterative sensitivity-based GCT coefficients selection to further reduce the number of proxy model input parameters. An extended version of the algorithm outperformed EnKF with localization and showed a close match to conventional EnKF with significantly larger ensemble size in history matching of Brugge and Norne field models. Finally, we proposed a modified of Multi-objective Evolutionary Algorithm based on decomposition and dominance (MOEA/DD) that utilizes RBF proxy models to reduce computational requirements. The proposed RBF-MOEA/DD algorithm adopted the GCT parametrization and Gradual Deformation approach to enable history matching of model spatial variables such as absolute permeability. Optimization workflow was modified to incorporate RBF proxy modeling with adaptive and sparsity-based iterative improvement. The proposed method was applied to the Brugge case history matching and showed the quality of the match and computational improvement similar to the RBF-EnKF method

EXACT: Experiment for X-Ray Characterization and Timing

The Experiment for X-ray Characterization and Timing (EXACT) is a simple spectrometer designed for the purpose of measuring hard X-rays (HXRs) from solar flares with high time precision. Solar flares and coronal mass ejections are the sources of the most extreme space weather events. The plasma and energetic particles ejected in these events, when Earth-directed, pose radiation risks to spacecraft and astronauts, and in extreme cases could endanger the Earth\u27s power grid. While the effects of these solar eruptive events are starting to be well characterized, the acceleration mechanisms for the high-energy particles produced are not understood. The EXACT sensor measures bremsstrahlung HXRs from flare-accelerated electron populations to investigate their origins. The primary objectives of the project are to monitor HXR flares in the declining phase of Solar Cycle 24 and serve as a pathfinder for a simple, cost-effective HXR spectrometer that will be a high- energy counterpart to the soft X-ray monitor aboard the GOES set of spacecraft. EXACT will also perform precise timing studies of solar HXRs to investigate time-of-flight effects of electron beams and their acceleration site heights, and can perform serendipitous science in conjunction with other Xray observatories. To achieve these objectives, EXACT is a 3-axis-stabilized, sun-pointed, 3U CubeSat that uses a highenergy radiation sensor with photon time tagging to 1 µs. This high-precision time-tagging will allow the instrument to serve the additional purpose of testing/demonstrating the concept of spacecraft relative ranging using gamma-ray burst timing. It is therefore a dual-use sensor that can serve as a relative position, navigation and timing instrument for GPS/GNSS-denied satellite operations, independent of its solar purposes. Due to its simplicity and high time precision, EXACT is a versatile instrument useful for both solar and astrophysical high-energy sources. EXACT will serve as a pathfinder for a set of CubeSats that can provide continuous, long-term solar HXR monitoring, and can, with serendipitous co-observations, perform groundbreaking new science in the study of solar flare-accelerated electrons, helping to understand the basic generation of the powerful solar sources of space weather

Incidence and Mortality of Prostate Cancer in Canada during 1992–2010

In Canada, prostate cancer is the most common reportable malignancy in men. We assessed the temporal trends of prostate cancer to gain insight into the geographic incidence and mortality trends of this disease. Three independent population-based cancer registries were used to retrospectively analyze demographic data on Canadian men diagnosed with prostate cancer and men who died of prostate cancer between the years of 1992 and 2010. The incidence and mortality rates were calculated at the provincial, city, and forward sortation area (FSA) postal code levels by using population counts that were obtained from the Canadian Census of Population. The Canadian average incidence rate was 113.57 cases per 100,000 males. There has been an overall increasing trend in crude prostate cancer incidence between 1992 and 2010 with three peaks, in 1993, 2001, and 2007. However, age-adjusted incidence rates showed no significant increase over time. The national mortality rate was calculated to be 24.13 deaths per 100,000 males per year. A decrease was noted in crude and age-adjusted mortality rates between 1992 and 2010. Several provinces, cities, and FSAs had higher incidence/mortality rates than the national average. Several of the FSA postal codes with the highest incidence/mortality rates were adjacent to one another. Several Canadian regions of high incidence for prostate cancer have been identified through this study and temporal trends are consistent with those reported in the literature. These results will serve as a foundation for future studies that will seek to identify new regional risk factors and etiologic agents