Solidification of undercooled liquids

During rapid solidification processing (RSP) the amount of liquid undercooling is an important factor in determining microstructural development by controlling phase selection during nucleation and morphological evolution during crystal growth. While undercooling is an inherent feature of many techniques of RSP, the deepest undercoolings and most controlled studies have been possible in carefully prepared fine droplet samples. From past work and recent advances in studies of nucleation kinetics it has become clear that the initiation of crystallization during RSP is governed usually by heterogeneous sites located at surfaces. With known nucleant sites, it has been possible to identify specific pathways of metastable phase formation and microstructural development in alloys. These advances have allowed for a clearer assessment of the interplay between undercooling, cooling rate and particle size statistics in structure formation. New approaches to the examination of growth processes have been developed to follow the thermal behavior and morphology in small samples in the period of rapid crystallization and recalescence. Based upon the new experimental information from these studies, useful models can be developed for the overall solidification process to include nucleation behavior, thermodynamic constraints, thermal history, growth kinetics, solute redistribution and resulting structures. From the refinement of knowledge concerning the underlying factors that govern RSP a basis is emerging for an effective alloy design and processing strategy

T1T_1- and T2T_2-spin relaxation time limitations of phosphorous donor electrons near crystalline silicon to silicon dioxide interface defects

A study of donor electron spins and spin--dependent electronic transitions involving phosphorous ($^{31}$P) atoms in proximity of the (111) oriented crystalline silicon (c-Si) to silicon dioxide (SiO$_{2}$) interface is presented for [$^{31}$P] = 10$^{15}$ $\mathrm{cm}^{-3}$ and [$^{31}$P] = 10$^{16}$ $\mathrm{cm}^{-3}$ at about liquid $^4$He temperatures ($T = 5$ $\mathrm{K} - 15$ $\mathrm{K}$). Using pulsed electrically detected magnetic resonance (pEDMR), spin--dependent transitions between the \Phos donor state and two distinguishable interface states are observed, namely (i) \Pb centers which can be identified by their characteristic anisotropy and (ii) a more isotropic center which is attributed to E$^\prime$ defects of the \sio bulk close to the interface. Correlation measurements of the dynamics of spin--dependent recombination confirm that previously proposed transitions between \Phos and the interface defects take place. The influence of these electronic near--interface transitions on the \Phos donor spin coherence time $T_2$ as well as the donor spin--lattice relaxation time $T_1$ is then investigated by comparison of spin Hahn--echo decay measurements obtained from conventional bulk sensitive pulsed electron paramagnetic resonance and surface sensitive pEDMR, as well as surface sensitive electrically detected inversion recovery experiments. The measurements reveal that both $T_2$ and $T_1$ of \Phos donor electrons spins in proximity of energetically lower interface states at $T\leq 13$ K are reduced by several orders of magnitude

Optimal Design of Submarine Pressure Hull Structures using Genetic Algorithm

In this paper, a method is presented for the optimal design of submarine pressure hull structures by taking advantage of genetic algorithm techniques. The objective functions and design constraints in the process of structural optimization are based on the ultimate limit states of hull structures. One of the benefits associated with the utilization of genetic algorithm is that the optimization process can be completed within short generations of design variables for the pressure hull structure model. Applied examples confirm that the proposed method is useful for the optimal design of submarine pressure hull structures. Details of the design procedure with applied examples are documented. The conclusions and insights obtained from the study are summarized

Business process improvement with the AB-BPM methodology

A fundamental assumption of Business Process Management (BPM) is that redesign delivers refined and improved versions of business processes. This assumption, however, does not necessarily hold, and any required compensatory action may be delayed until a new round in the BPM life-cycle completes. Current approaches to process redesign face this problem in one way or another, which makes rapid process improvement a central research problem of BPM today. In this paper, we address this problem by integrating concepts from process execution with ideas from DevOps. More specifically, we develop a methodology called AB-BPM that offers process improvement validation in two phases: simulation and AB tests. Our simulation technique extracts decision probabilities and metrics from the event log of an existing process version and generates traces for the new process version based on this knowledge. The results of simulation guide us towards AB testing where two versions (A and B) are operational in parallel and any new process instance is routed to one of them. The routing decision is made at runtime on the basis of the achieved results for the registered performance metrics of each version. Our routing algorithm provides for ultimate convergence towards the best performing version, no matter if it is the old or the new version. We demonstrate the efficacy of our methodology and techniques by conducting an extensive evaluation based on both synthetic and real-life data

Summary of Surface Swipe Sampling for Beryllium on Lead Bricks and Shielding

Approximately 25,000 lbs of lead bricks at Site 300 were assessed by the Site 300 Industrial Hygienis tand Health Physicist for potential contamination of beryllium and radiation for reuse. These lead bricks and shielding had been used as shielding material during explosives tests that included beryllium and depleted uranium. Based on surface swipe sampling that was performed between July 26 and October 11, 2010, specifically for beryllium, the use of a spray encapsulant was found to be an effective means to limit removable surface contamination to levels below the DOE release limit for beryllium, which is 0.2 mcg/100 cm{sup 2}. All the surface swipe sampling data for beryllium and a timeline of when the samples were collected (and a brief description) are presented in this report. On December 15, 2010, the lead bricks and shielding were surveyed with an ion chamber and indicated dose rates less than 0.05 mrem per hour on contact. This represents a dose rate consistent with natural background. An additional suevey was performed on February 8, 2011, using a GM survey instrument to estimate total activity on the lead bricks and shielding, confirming safe levels of radioactivity. The vendor is licensed to possess and work with radioactive material

Verification of the Parallel Pin-Wise Core Simulator pCTF/PARCSv3.2 in Operational Control Rod Drop Transient Scenarios

This is an Accepted Manuscript of an article published by Taylor & Francis in Nuclear Science and Engineering on 2017, available online: https://www.tandfonline.com/doi/full/10.1080/00295639.2017.1320892[EN] Thanks to advances in computer technology, it is feasible to obtain detailed reactor core descriptions for safety analysis of the light water reactor (LWR), in order to represent realistically the fuel elements design, as is the case for three-dimensional coupled simulations for local neutron kinetics and thermal hydraulics. This scenario requires an efficient thermal-hydraulic code that can produce a response in a reasonable time for large-scale, detailed models. In two-fluid codes, such as the thermal-hydraulic subchannel code COBRA-TF, the time restriction is even more important, since the set of equations to be solved is more complex. We have developed a message passing interface parallel version of COBRA-TF, called pCTF. The parallel code is based on a cell-oriented domain decomposition approach, and performs well in models that consist of many cells. The Jacobian matrix is computed in parallel, with each processor in charge of calculating the coefficients related to a subset of the cells. Furthermore, the resulting system of linear equations is also solved in parallel, by exploiting solvers and preconditioners from PETSc. The goal of this study is to demonstrate the capability of the recently developed pCTF/PARCS coupled code to simulate large cores with a pin-by-pin level of detail in an acceptable computational time, using for this purpose two control rod drop operational transients that took place in the core of a three-loop pressurized water reactor. As a result, the main safety parameters of the core hot channel have been calculated by the coupled code in a pin level of detail, obtaining best estimate results for this transient.This work has been partially supported by the Universitat Politecnica de Valencia under Projects COBRA_PAR (PAID-05-11-2810) and OpenNUC (PAID-05-12), and by the Spanish Ministerio de Economia y Competitividad under Projects SLEPc-HS (TIN2016-75985-P) and NUC-MULTPHYS (ENE2012-34585).Ramos Peinado, E.; Roman Moltó, JE.; Abarca Giménez, A.; Miró Herrero, R.; Bermejo, JA.; Ortego, A.; Posada-Barral, JM. (2017). Verification of the Parallel Pin-Wise Core Simulator pCTF/PARCSv3.2 in Operational Control Rod Drop Transient Scenarios. Nuclear Science and Engineering. 187(3):254-267. https://doi.org/10.1080/00295639.2017.1320892S2542671873Cuervo, D., Avramova, M., Ivanov, K., & Miró, R. (2006). Evaluation and enhancement of COBRA-TF efficiency for LWR calculations. Annals of Nuclear Energy, 33(9), 837-847. doi:10.1016/j.anucene.2006.03.011Ramos, E., Roman, J. E., Abarca, A., Miró, R., & Bermejo, J. A. (2016). Control rod drop transient analysis with the coupled parallel code pCTF-PARCSv2.7. Annals of Nuclear Energy, 87, 308-317. doi:10.1016/j.anucene.2015.09.016T. DOWNAR et al. “PARCS v2.7 U.S. NRC Core Neutronics Simulator: User Manual” (2006).T. DOWNAR et al. “PARCS v2.7 U.S. NRC Core Neutronics Simulator: Theory Manual” (2006)

Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models

Introduction: Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction. Methods: We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curves and compared it to nested Cox models obtained by robust backward selection procedures. Results: A prognostic index derived from of a multivariate Cox regression model incorporating molecular and clinico-pathological covariates (nodal status, tumor size, nuclear grade, and age) is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), the most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model. Conclusions: Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays.This work was supported by a grant from the Susan G Komen Foundation (to YK)

Application of a pilot control banding tool for risk level assessment and control of nanoparticle exposures

Control Banding (CB) strategies offer simplified solutions for controlling worker exposures to constituents that are found in the workplace in the absence of firm toxicological and exposure data. These strategies may be particularly useful in nanotechnology applications, considering the overwhelming level of uncertainty over what nanomaterials and nanotechnologies present as potential work-related health risks, what about these materials might lead to adverse toxicological activity, how risk related to these might be assessed, and how to manage these issues in the absence of this information. This study introduces a pilot CB tool or 'CB Nanotool' that was developed specifically for characterizing the health aspects of working with engineered nanoparticles and determining the level of risk and associated controls for five ongoing nanotechnology-related operations being conducted at two Department of Energy (DOE) research laboratories. Based on the application of the CB Nanotool, four of the five operations evaluated in this study were found to have implemented controls consistent with what was recommended by the CB Nanotool, with one operation even exceeding the required controls for that activity. The one remaining operation was determined to require an upgrade in controls. By developing this dynamic CB Nanotool within the realm of the scientific information available, this application of CB appears to be a useful approach for assessing the risk of nanomaterial operations, providing recommendations for appropriate engineering controls, and facilitating the allocation of resources to the activities that most need them