Opencg: A Combinatorial Geometry Modeling Tool for Data Processing and Code Verification

Combinatorial Geometry (CG) is one formulation for computational geometric models that is commonly used in many neutron transport simulation codes. The use of CG is advantageous since it permits an accurate yet concise representation of complex reactor models with a nominal memory footprint. OpenCG is a software package for combinatorial geometry models being developed at the Massachusetts Institute of Technology. The goal for OpenCG is to provide an easy-to-use, physics agnostic library to build geometry models of nuclear reactor cores. OpenCG is a free, open source library with an easy-to-use Python interface to provide nuclear engineers a single, powerful framework for modeling complex reactor geometries. Compatibility modules for commonly used nuclear reactor physics codes, such as OpenMC, OpenMOC, and Serpent, are being concurrently developed for rapid and easy exportation of an OpenCG model directly into the relevant input file format for each code of interest. The present work describes OpenCG and describes some of the novel and useful algorithms included with the software package.National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 112237)United States. Department of Energy (Center for Exascale Simulation of Advanced Reactors (CESAR). Contract DE-AC02-06CH11357)

Parallel performance results for the OpenMOC neutron transport code on multicore platforms

The shift toward multicore architectures has ushered in a new era of shared memory parallelism for scientific applications. This transition has introduced challenges for the nuclear engineering community, as it seeks to design high-fidelity full-core reactor physics simulation tools. This article describes the parallel transport sweep algorithm in the OpenMOC method of characteristics (MOC) neutron transport code for multicore platforms using OpenMP. Strong and weak scaling studies are performed for both Intel Xeon and IBM Blue Gene/Q (BG/Q) multicore processors. The results demonstrate 100% parallel efficiency for 12 threads on 12 cores on Intel Xeon platforms and over 90% parallel efficiency with 64 threads on 16 cores on the IBM BG/Q. These results illustrate the potential for hardware acceleration for MOC neutron transport on modern multicore and future many-core architectures. In addition, this work highlights the pitfalls of programming for multicore architectures, with a focal point on false sharing.National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 1122374)United States. Department of Energy (Center for Exascale Simulation of Advanced Reactors. Contract DE-AC02-06CH11357

The OpenMOC method of characteristics neutral particle transport code

The method of characteristics (MOC) is a numerical integration technique for partial differential equations, and has seen widespread use for reactor physics lattice calculations. The exponential growth in computing power has finally brought the possibility for high-fidelity full core MOC calculations within reach. The OpenMOC code is being developed at the Massachusetts Institute of Technology to investigate algorithmic acceleration techniques and parallel algorithms for MOC. OpenMOC is a free, open source code written using modern software languages such as C/C++ and CUDA with an emphasis on extensible design principles for code developers and an easy to use Python interface for code users. The present work describes the OpenMOC code and illustrates its ability to model large problems accurately and efficiently.National Science Foundation (U.S.). Graduate Research Fellowship Program ( Grant No. 1122374)United States. Department of Energy. Center for Exascale Simulation of Advanced Reactors (CESAR)United States. Office of the Assistant Secretary for Nuclear Energy (Nuclear Energy University Programs Fellowship)Studsvik Scandpower Graduate FellowUnited States. Department of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357

Massively parallel algorithms for method of characteristics neutral particle transport on shared memory computer architectures

Thesis: S.M., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 197-203).Over the past 20 years, parallel computing has enabled computers to grow ever larger and more powerful while scientific applications have advanced in sophistication and resolution. This trend is being challenged, however, as the power consumption for conventional parallel computing architectures has risen to unsustainable levels and memory limitations have come to dominate compute performance. Multi-core processors and heterogeneous computing platforms, such as Graphics Processing Units (GPUs), are an increasingly popular paradigm for resolving these issues. This thesis explores the applicability of shared memory parallel platforms for solving deterministic neutron transport problems. A 2D method of characteristics code - OpenMOC - has been developed with solvers for shared memory multi-core platforms as well as GPUs. The multi-threading and memory locality methodologies for the multi-core CPU and GPU solvers are presented. Parallel scaling results using OpenMP demonstrate better than ideal weak scaling and nearly perfect strong scaling on both Intel Xeon and IBM Blue Gene/Q architectures. Performance results for the 2D C5G7 benchmark demonstrate up to 50x speedup for MOC on a GPU. The lessons learned from this thesis will provide the basis for further exploration of MOC on many-core platforms and GPUs as well as design decisions for hardware vendors exploring technologies for the next generation of machines for scientific computing.by William Robert Dawson Boyd III.S.M

Reactor agnostic MGXC generation for fine-mesh deterministic neutron transport simulations

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2017.Cataloged from PDF version of thesis.Includes bibliographical references (pages 487-495).A key challenge for full-core transport methods is reactor agnostic multi-group cross section (MGXS) generation. Monte Carlo (MC) presents the most accurate method for MGXS generation since it does not require any approximations to the neutron flux. This thesis develops novel methods that use MC to generate the fine-spatial mesh MGXS that are needed by high-fidelity transport codes. These methods employ either engineering-based or statistical clustering algorithms to accelerate the convergence of MGXS tallied on fine, heterogeneous spatial meshes by Monte Carlo. The traditional multi-level approach to MGXS generation is replaced by full-core MC calculations that generate MGXS for multi-group deterministic transport codes. Two pinwise spatial homogenization schemes are introduced to model the clustering of pin-wise MGXS due to spatial self-shielding spectral effects. The Local Neighbor Symmetry (LNS) scheme uses a nearest neighbor-like analysis of a reactor geometry to determine which fuel pins should be assigned the same MGXS. The inferential MGXS (iMGXS) scheme applies unsupervised machine learning algorithms to "noisy" MC tally data to identify clustering of pin-wise MGXS without any knowledge of the reactor geometry. Both schemes simultaneously account for spatial self-shielding effects while also accelerating the convergence of the MC tallies used to generate MGXS. The LNS and iMGXS schemes were used to model MGXS clustering from radial geometric heterogeneities in a suite of 2D PWR benchmarks. Both schemes reduced U-238 capture rate errors by up to a factor of four with respect to schemes which neglect to model MGXS clustering. In addition, the schemes required an order of magnitude fewer MC particle histories to converge MGXS for multi-group deterministic calculations than a reference MC calculation. These results demonstrate the potential for single-step MC simulations of the complete heterogeneous geometry as a means to generate reactor agnostic MGXS for deterministic transport codes. The LNS and iMGXS schemes may be valuable for reactor physics analyses of advanced LWR core designs and next generation reactors with spatial heterogeneities that are poorly modeled by the engineering approximations in today's methods for MGXS generation.by William Robert Dawson Boyd, III.Ph. D

Immunocompromised patients with acute respiratory distress syndrome: Secondary analysis of the LUNG SAFE database

Background: The aim of this study was to describe data on epidemiology, ventilatory management, and outcome of acute respiratory distress syndrome (ARDS) in immunocompromised patients. Methods: We performed a post hoc analysis on the cohort of immunocompromised patients enrolled in the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) study. The LUNG SAFE study was an international, prospective study including hypoxemic patients in 459 ICUs from 50 countries across 5 continents. Results: Of 2813 patients with ARDS, 584 (20.8%) were immunocompromised, 38.9% of whom had an unspecified cause. Pneumonia, nonpulmonary sepsis, and noncardiogenic shock were their most common risk factors for ARDS. Hospital mortality was higher in immunocompromised than in immunocompetent patients (52.4% vs 36.2%; p < 0.0001), despite similar severity of ARDS. Decisions regarding limiting life-sustaining measures were significantly more frequent in immunocompromised patients (27.1% vs 18.6%; p < 0.0001). Use of noninvasive ventilation (NIV) as first-line treatment was higher in immunocompromised patients (20.9% vs 15.9%; p = 0.0048), and immunodeficiency remained independently associated with the use of NIV after adjustment for confounders. Forty-eight percent of the patients treated with NIV were intubated, and their mortality was not different from that of the patients invasively ventilated ab initio. Conclusions: Immunosuppression is frequent in patients with ARDS, and infections are the main risk factors for ARDS in these immunocompromised patients. Their management differs from that of immunocompetent patients, particularly the greater use of NIV as first-line ventilation strategy. Compared with immunocompetent subjects, they have higher mortality regardless of ARDS severity as well as a higher frequency of limitation of life-sustaining measures. Nonetheless, nearly half of these patients survive to hospital discharge. Trial registration: ClinicalTrials.gov, NCT02010073. Registered on 12 December 2013

Mechanical ventilation in patients with cardiogenic pulmonary edema: a sub-analysis of the LUNG SAFE study

International audienceBackground: Patients with acute respiratory failure caused by cardiogenic pulmonary edema (CPE) may require mechanical ventilation that can cause further lung damage. Our aim was to determine the impact of ventilatory settings on CPE mortality. Methods: Patients from the LUNG SAFE cohort, a multicenter prospective cohort study of patients undergoing mechanical ventilation, were studied. Relationships between ventilatory parameters and outcomes (ICU discharge/ hospital mortality) were assessed using latent mixture analysis and a marginal structural model. Results: From 4499 patients, 391 meeting CPE criteria (median age 70 [interquartile range 59-78], 40% female) were included. ICU and hospital mortality were 34% and 40%, respectively. ICU survivors were younger (67 [57-77] vs 74 [64-80] years, p < 0.001) and had lower driving (12 [8-16] vs 15 [11-17] cmH 2 O, p < 0.001), plateau (20 [15-23] vs 22 [19-26] cmH 2 O, p < 0.001) and peak (21 [17-27] vs 26 [20-32] cmH 2 O, p < 0.001) pressures. Latent mixture analysis of patients receiving invasive mechanical ventilation on ICU day 1 revealed a subgroup ventilated with high pressures with lower probability of being discharged alive from the ICU (hazard ratio [HR] 0.79 [95% confidence interval 0.60-1.05], p = 0.103) and increased hospital mortality (HR 1.65 [1.16-2.36], p = 0.005). In a marginal structural model, driving pressures in the first week (HR 1.12 [1.06-1.18], p < 0.001) and tidal volume after day 7 (HR 0.69 [0.52-0.93], p = 0.015) were related to survival. Conclusions: Higher airway pressures in invasively ventilated patients with CPE are related to mortality. These patients may be exposed to an increased risk of ventilator-induced lung injury

Outcome of acute hypoxaemic respiratory failure: insights from the LUNG SAFE Study

Background: Current incidence and outcome of patients with acute hypoxaemic respiratory failure requiring mechanical ventilation in the intensive care unit (ICU) are unknown, especially for patients not meeting criteria for acute respiratory distress syndrome (ARDS). Methods: An international, multicentre, prospective cohort study of patients presenting with hypoxaemia early in the course of mechanical ventilation, conducted during four consecutive weeks in the winter of 2014 in 459 ICUs from 50 countries (LUNG SAFE). Patients were enrolled with arterial oxygen tension/inspiratory oxygen fraction ratio ≤300 mmHg, new pulmonary infiltrates and need for mechanical ventilation with a positive end-expiratory pressure of ≥5 cmH2O. ICU prevalence, causes of hypoxaemia, hospital survival and factors associated with hospital mortality were measured. Patients with unilateral versus bilateral opacities were compared. Findings: 12 906 critically ill patients received mechanical ventilation and 34.9% with hypoxaemia and new infiltrates were enrolled, separated into ARDS (69.0%), unilateral infiltrate (22.7%) and congestive heart failure (CHF; 8.2%). The global hospital mortality was 38.6%. CHF patients had a mortality comparable to ARDS (44.1% versus 40.4%). Patients with unilateral-infiltrate had lower unadjusted mortality, but similar adjusted mortality compared to those with ARDS. The number of quadrants on chest imaging was associated with an increased risk of death. There was no difference in mortality comparing patients with unilateral-infiltrate and ARDS with only two quadrants involved. Interpretation: More than one-third of patients receiving mechanical ventilation have hypoxaemia and new infiltrates with a hospital mortality of 38.6%. Survival is dependent on the degree of pulmonary involvement whether or not ARDS criteria are reached

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis

International audienceTwo acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. Methods: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. Findings: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90–0·95) in EARLI and 0·88 (0·84–0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81–0·94] vs 0·92 [0·88–0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). Interpretation: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. Funding: US National Institutes of Health and European Society of Intensive Care Medicine

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p&lt;0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p&lt;0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status