Progress Toward Affordable High Fidelity Combustion Simulations Using Filtered Density Functions for Hypersonic Flows in Complex Geometries

Significant progress has been made in the development of subgrid scale (SGS) closures based on a filtered density function (FDF) for large eddy simulations (LES) of turbulent reacting flows. The FDF is the counterpart of the probability density function (PDF) method, which has proven effective in Reynolds averaged simulations (RAS). However, while systematic progress is being made advancing the FDF models for relatively simple flows and lab-scale flames, the application of these methods in complex geometries and high speed, wall-bounded flows with shocks remains a challenge. The key difficulties are the significant computational cost associated with solving the FDF transport equation and numerically stiff finite rate chemistry. For LES/FDF methods to make a more significant impact in practical applications a pragmatic approach must be taken that significantly reduces the computational cost while maintaining high modeling fidelity. An example of one such ongoing effort is at the NASA Langley Research Center, where the first generation FDF models, namely the scalar filtered mass density function (SFMDF) are being implemented into VULCAN, a production-quality RAS and LES solver widely used for design of high speed propulsion flowpaths. This effort leverages internal and external collaborations to reduce the overall computational cost of high fidelity simulations in VULCAN by: implementing high order methods that allow reduction in the total number of computational cells without loss in accuracy; implementing first generation of high fidelity scalar PDF/FDF models applicable to high-speed compressible flows; coupling RAS/PDF and LES/FDF into a hybrid framework to efficiently and accurately model the effects of combustion in the vicinity of the walls; developing efficient Lagrangian particle tracking algorithms to support robust solutions of the FDF equations for high speed flows; and utilizing finite rate chemistry parametrization, such as flamelet models, to reduce the number of transported reactive species and remove numerical stiffness. This paper briefly introduces the SFMDF model (highlighting key benefits and challenges), and discusses particle tracking for flows with shocks, the hybrid coupled RAS/PDF and LES/FDF model, flamelet generated manifolds (FGM) model, and the Irregularly Portioned Lagrangian Monte Carlo Finite Difference (IPLMCFD) methodology for scalable simulation of high-speed reacting compressible flows

Long-Term Care Facilities: Important Participants of the Acute Care Facility Social Network?

Background: Acute care facilities are connected via patient sharing, forming a network. However, patient sharing extends beyond this immediate network to include sharing with long-term care facilities. The extent of long-term care facility patient sharing on the acute care facility network is unknown. The objective of this study was to characterize and determine the extent and pattern of patient transfers to, from, and between long-term care facilities on the network of acute care facilities in a large metropolitan county. Methods/Principal Findings: We applied social network constructs principles, measures, and frameworks to all 2007 annual adult and pediatric patient transfers among the healthcare facilities in Orange County, California, using data from surveys and several datasets. We evaluated general network and centrality measures as well as individual ego measures and further constructed sociograms. Our results show that over the course of a year, 66 of 72 long-term care facilities directly sent and 67 directly received patients from other long-term care facilities. Long-term care facilities added 1,524 ties between the acute care facilities when ties represented at least one patient transfer. Geodesic distance did not closely correlate with the geographic distance among facilities. Conclusions/Significance: This study demonstrates the extent to which long-term care facilities are connected to the acute care facility patient sharing network. Many long-term care facilities were connected by patient transfers and further added many connections to the acute care facility network. This suggests that policy-makers and health officials should account for patient sharing with and among long-term care facilities as well as those among acute care facilities when evaluating policies and interventions. © 2011 Lee et al

Quantitative trait loci conferring grain mineral nutrient concentrations in durum wheat 3 wild emmer wheat RIL population

Mineral nutrient malnutrition, and particularly deficiency in zinc and iron, afflicts over 3 billion people worldwide. Wild emmer wheat, Triticum turgidum ssp. dicoccoides, genepool harbors a rich allelic repertoire for mineral nutrients in the grain. The genetic and physiological basis of grain protein, micronutrients (zinc, iron, copper and manganese) and macronutrients (calcium, magnesium, potassium, phosphorus and sulfur) concentration was studied in tetraploid wheat population of 152 recombinant inbred lines (RILs), derived from a cross between durum wheat (cv. Langdon) and wild emmer (accession G18-16). Wide genetic variation was found among the RILs for all grain minerals, with considerable transgressive effect. A total of 82 QTLs were mapped for 10 minerals with LOD score range of 3.2–16.7. Most QTLs were in favor of the wild allele (50 QTLs). Fourteen pairs of QTLs for the same trait were mapped to seemingly homoeologous positions, reflecting synteny between the A and B genomes. Significant positive correlation was found between grain protein concentration (GPC), Zn, Fe and Cu, which was supported by significant overlap between the respective QTLs, suggesting common physiological and/or genetic factors controlling the concentrations of these mineral nutrients. Few genomic regions (chromosomes 2A, 5A, 6B and 7A) were found to harbor clusters of QTLs for GPC and other nutrients. These identified QTLs may facilitate the use of wild alleles for improving grain nutritional quality of elite wheat cultivars, especially in terms of protein, Zn and Fe

On the use of model-driven engineering principles for the management of simulation experiments

Simulation experiments are an essential part of computational science and engineering. The use of simulation models is widely adopted by practitioners from diverse areas of applied sciences. Nevertheless, simulations are rarely replicated due to reuse and maintenance challenges related to models and data. In this respect, we propose that crucial and labor intensive parts of simulation experiments could be supported by model transformations. This work focuses on model-driven engineering practices to enable replicable and reusable simulation experiments. These practices are used to devote researchers' time to analyze the system under investigation rather than dealing with low level details to create a working environment. The results of our framework development work are presented

Photoinduced polymerization of thiophene using iodonium salt

Thiophene was polymerized by means of UVirradiation using diphenyliodonium hexafluorophosphate as a photoinitiator. An initiation mechanism involving electron transfer from photochemically generated onium radical cations to thiophene was proposed. N-Ethoxy-2-methylpyridinium hexafluorophosphate and triphenylsulfonium hexafluorophosphate were also found to be effective in facilitating the polymerization of thiophene. Polymerization is accompanied with the film formation on the surface of the reaction tube. The photochemically obtained polymers were characterized by FT-IR, DSC, and SEM analyses and compared with those obtained by oxidative and electrochemical means. Electrical conductivities of the samples were measured by four-probe technique

Repast HPC with optimistic time management

Copyright 2016 Society for Modeling & Simulation International (SCS).High performance computing (HPC) has great potential to speedup agent-based simulations. In parallel and distributed simulation (PADS) community, a well-known fact is that employing an optimistic time management mechanism instead of a conservative time management mechanism may provide remarkable performance enhancement, because optimistic approach avoids redundant synchronization among logical processes (LPs). In this paper, an existing optimistic time management mechanism, namely Time Warp, by Jefferson, is adapted for a distributed agent based simulation tool. We implemented Time Warp on an open source and distributed agent based modeling and simulation (ABMS) tool, namely Repast for High Performance Computing (Repast HPC), from Argonne National Laboratory, Chicago, IL, USA. We incorporated a simple and self-adaptive technique for adjusting checkpoint intervals. Two case studies have been implemented to compare our optimistic approach and existing Repast HPC's conservative approach. The experiments suggest that optimistic approach is more scalable than conservative approach in agent based simulations

Improving the performance of optimistic time management mechanism with sub-state saving

©2017 Society for Modeling & Simulation International (SCS).Optimistic approaches are scalable methods for time management in parallel and distributed simulations. In optimistic time management, logical processes advance their local time without constrained by the others in the simulation. If a logical process receives a message from its past, it goes back to a previously saved state, which is called a rollback. Even though the received message from the past would not cause any problem, rollback is performed in any case. In this paper, we presented a method to reduce the number of rollbacks, without sacrificing the accuracy of simulation. We propose to save a relatively small subset of the full simulation state to allow the logical processes to make a decision whether a rollback is really needed or not. Our technique is demonstrated in an agent-based simulation using the Time Warp algorithm adapted for optimistic time management for Repast HPC