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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale
Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.
Segmentation Certainty through Uncertainty: Uncertainty-Refined Binary Volumetric Segmentation under Multifactor Domain Shift.
Abstract not provided.
Radiative Heat Transfer Calculation on 16384 GPUs Using a Reverse Monte Carlo Ray Tracing Approach with Adaptive Mesh Refinement
Modeling thermal radiation is computationally challenging in parallel due to its all-to-all physical and resulting computational connectivity, and is also the dominant mode of heat transfer in practical applications such as next-generation clean coal boilers, being modeled by the Uintah framework. However, a direct all-to-all treatment of radiation is prohibitively expensive on large computers systems whether homogeneous or heterogeneous. DOE Titan and the planned DOE Summit and Sierra machines are examples of current and emerging GPU-based heterogeneous systems where the increased processing capability of GPUs over CPUs exacerbates this problem. These systems require that computational frameworks like Uintah leverage an arbitrary number of on-node GPUs, while simultaneously utilizing thousands of GPUs within a single simulation. We show that radiative heat transfer problems can be made to scale within Uintah on heterogeneous systems through a combination of reverse Monte Carlo ray tracing (RMCRT) techniques combined with AMR, to reduce the amount of global communication. In particular, significant Uintah infrastructure changes, including a novel lock and contention-free, thread-scalable data structure for managing MPI communication requests and improved memory allocation strategies were necessary to achieve excellent strong scaling results to 16384 GPUs on Titan.
Further Refinements to the Foundations of Cyber Zone Defense.
Abstract not provided.
Delineating transcriptional networks of prognostic gene signatures refines treatment recommendations for lymph node-negative breast cancer patients
The majority of women diagnosed with lymph node-negative breast cancer are unnecessarily treated with damaging chemotherapeutics after surgical resection. This highlights the importance of understanding and more accurately predicting patient prognosis. We define the transcriptional networks regulating well-established prognostic gene expression signatures. We find that the same set of transcriptional regulators consistently lie upstream of both ‘prognosis’ and ‘proliferation’ gene signatures, suggesting that a central transcriptional network underpins a shared phenotype within these signatures. Strikingly, the master transcriptional regulators within this network predict recurrence risk for lymph node-negative breast cancer better than currently used multigene prognostic assays, particularly in estrogen receptor-positive patients. Simultaneous examination of p16 INK4A expression, which predicts tumours that have bypassed cellular senescence, revealed that intermediate levels of p16 INK4A correlate with an intact pRB pathway and improved survival. A combination of these master transcriptional regulators and p16 INK4A , termed the OncoMasTR score, stratifies tumours based on their proliferative and senescence capacity, facilitating a clearer delineation of lymph node-negative breast cancer patients at high risk of recurrence, and thus requiring chemotherapy. Furthermore, OncoMasTR accurately classifies over 60% of patients as ‘low risk’, an improvement on existing prognostic assays, which has the potential to reduce overtreatment in early-stage patients. Taken together, the present study provides new insights into the transcriptional regulation of cellular proliferation in breast cancer and provides an opportunity to enhance and streamline methods of predicting breast cancer prognosis.
A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses
Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii . The model, i Cre1355, represents a major advance over previous models, both in content and predictive power. i Cre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using i Cre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, i Cre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.
PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite
Combustion encompasses multiscale, multiphase reacting flow physics spanning a wide range of scales from the molecular scales, where chemical reactions occur, to the device scales, where the turbulent flow is affected by the geometry of the combustor. This scale disparity and the limited measurement capabilities from experiments make modeling combustion a significant challenge. Recent advancements in high-performance computing (HPC), particularly with the Department of Energy's Exascale Computing Project (ECP), have enabled high-fidelity simulations of practical applications to be performed. The major physics submodels, including chemical reactions, turbulence, sprays, soot, and thermal radiation, exhibit distinctive computational characteristics that need to be examined separately to ensure efficient utilization of computational resources. This paper presents the multiphysics solver for the Pele code suite, called PeleMP, which consists of models for spray, soot, and thermal radiation. Here, the mathematical and algorithmic aspects of the model implementations are described in detail as well as the verification process. The computational performance of these models is benchmarked on multiple supercomputers, including Frontier, an exascale machine. Results are presented from production simulations of a turbulent sooting ethylene flame and a bluff-body swirl stabilized spray flame with sustainable aviation fuels to demonstrate the capability of the Pele codes for modeling practical combustion problems with multiphysics. This work is an important step toward the exascale computing era for high-fidelity combustion simulations providing physical insights and data for predictive modeling of real-world devices.
WE-AB-207B-08: Exploring and Refining the QUANTEC Guideline to Reduce Severe Hyposalivation Following IMRT for Head and Neck Cancer
Purpose: The aim of this study was to investigate the usefulness of the QUANTEC guideline to prevent xerostomia after intensity-modulated radiotherapy (IMRT) for head and neck cancer (HNC) with respect to follow-up time. In addition, we explored alternative guidelines to further reduce xerostomia. Methods: The QUANTEC guideline suggests a mean dose to the contralateral (Dmeancontra) parotid<20 Gy, or Dmeancontra and Dmean to the ipsilateral parotid (Dmeanipsi)<25 Gy. Stimulated whole mouth saliva flow measurements (WMSFM) were conducted at a median of 11 (3–24) months for 63 patients treated with IMRT for HNC to a median dose of 70 Gy in 2006–2015. Severe hyposalivation/xerostomia was defined as WMSFM ≤25% post- relative to pre-RT. Patients were stratified into a <6m (xerostomia: 27% (n=15)), and a 6–24m (xerostomia: 19% (n=10)) follow-up group. Dose-response modeling was performed using logistic regression including Dmeancontra, or Dmeancontra and Dmeanipsi. The area under the receiver-operating characteristics curve (AUC) was used to assess discriminative ability, and the agreement between the estimated and observed rate of xerostomia was given by Spearman’s rank correlation coefficient (Rs), and related p-values. Results: Of the non-xerostomia patients, 65% (<6m) and 56% (6–24m) fulfilled Dmeancontra<20 Gy. The estimated and observed rate of xerostomia agreed at <6m (AUC=0.78; Rs=0.46; p=0.001), and was 28% at Dmeancontra=20 Gy. A smaller number of non-xerostomia patients fulfilled the two-gland guideline (33% (<6m) and 26% (6–24m)), but the AUC was higher than using Dmeancontra only (<6m: AUC=0.90; Rs=0.63; p<0.0001; 6–24m: AUC=0.84; Rs=0.25; p=0.08), and the following amendment of the two-gland guideline was suggested: (0.17*Dmeancontra+0.11*Dmeanipsi-8.13)<-1.60 (<6m), and (0.05*Dmeancontra+0.02*Dmeanipsi-3.10)<-1.60 (6–24m). Conclusion: The QUANTEC guideline is effective to prevent xerostomia <6m post-RT, but its usefulness is reduced at later follow-up times. The suggested amendment to the two-gland QUANTEC guideline should be further investigated in an independent cohort of HNC patients treated with IMRT.
Refinement of the “ Candidatus Accumulibacter” genus based on metagenomic analysis of biological nutrient removal (BNR) pilot-scale plants operated with reduced aeration
Members of the “Candidatus Accumulibacter” genus are widely studied as key polyphosphate-accumulating organisms (PAOs) in biological nutrient removal (BNR) facilities performing enhanced biological phosphorus removal (EBPR). This diverse lineage includes 18 “Ca. Accumulibacter” species, which have been proposed based on the phylogenetic divergence of the polyphosphate kinase 1 (ppk1) gene and genome-scale comparisons of metagenome-assembled genomes (MAGs). Phylogenetic classification based on the 16S rRNA genetic marker has been difficult to attain because most “Ca. Accumulibacter” MAGs are incomplete and often do not include the rRNA operon. Here, we investigate the “Ca. Accumulibacter” diversity in pilot-scale treatment trains performing BNR under low dissolved oxygen (DO) conditions using genome-resolved metagenomics. Using long-read sequencing, we recovered medium- and high-quality MAGs for 5 of the 18 “Ca. Accumulibacter” species, all with rRNA operons assembled, which allowed a reassessment of the 16S rRNA-based phylogeny of this genus and an analysis of phylogeny based on the 23S rRNA gene.
Crystal structure refinement of Sr{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14}
An accurate X-ray diffraction study of Sr{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14} (STGS) crystal (a = 8.3023(10) Angstrom-Sign , c = 5.0853(2) Angstrom-Sign , sp. gr. P321, Z = 1, R/wR = 0.59/0.52%, 4004 independent reflections) is performed. The use of two independent data sets obtained on diffractometers with point and 2D detectors made it possible to determine the model structure characterized by the best reproducibility of parameters. The ordered distribution of atoms over crystallographic positions and the anharmonic character of displacements of all cations and one oxygen atom are established.
Crystal-structure refinement of Sr{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14}
The accurate X-ray diffraction study of a Sr{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} crystal was performed based on two X-ray diffraction data sets collected on a diffractometer equipped with a CCD area detector (a = 8.2776(2), c = 5.0415(1) Angstrom-Sign , sp. gr. P321, Z = 1, R/wR = 0.78/0.69%, 3645 independent reflections). The structure of Sr{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} is characterized by the presence of two mixed cation sites, which is accompanied by the anharmonic motion not only of cations, but also of two oxygen atoms in general positions. The structures and electromechanical characteristics of Sr{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} and Sr{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14} were compared. The Sr{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} structure is characterized by a larger elongation of the Sr polyhedron along the a axis and, simultaneously, by the smaller unit-cell parameter a compared with Sr{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14}, which correlates with the ratio of the piezoelectric coefficients d{sub 11}. The absence of thermally stable directions in the crystals of Sr{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} and Sr{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14} is consistent with the absence of the anomalous temperature dependence of the dielectric constant {epsilon}{sub 33}.
Accurate crystal-structure refinement of Ca{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} at 295 and 100 K and analysis of the disorder in the atomic positions
The accurate X-ray diffraction study of a Ca{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} crystal (sp. gr. P321, Z = 1) has been performed using repeated X-ray diffraction data sets collected on a diffractometer equipped with a CCD area detector at 295 and 100 K. The asymmetric disorder in the atomic positions in Ca{sub 3}Ga{sub 2}Ge{sub 4}O{sub 14} is described in two alternative ways: with the use of anharmonic atomic displacements (at 295 K R/wR = 0.68/0.60%, 3754 reflections; at 100 K R/wR = 0.90/0.70%, 3632 reflections) and using a split model (SM) (at 295 K R/wR = 0.74/0.67%; at 100 K R/wR = 0.95/0.74%). An analysis of the probability density function that defines the probability of finding an atom at a particular point in space shows that, at 295 K, five of the seven independent atoms in the unit cell are asymmetrically disordered in the vicinity of their sites, whereas only three atoms are disordered at 100 K. At both temperatures the largest disorder is observed at the 3f site on a twofold axis, which is a prerequisite for the formation of helicoidal chains of atoms along the c axis of the crystal and can serve as a structural basis for multiferroic properties of this family of crystals with magnetic ions.
Accurate Refinement of the Crystal Structure of Ba{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14} from Langasite Family and Analysis of Structural Transformations Due to Isomorphous Cation Substitutions
An accurate structure analysis of a Ba{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14} single crystal from langasite family was performed using four X-ray diffraction data sets collected on a diffractometer equipped with a CCD area detector (sp. gr. P321, Z = 1, sinθ/λ ≤ 1.35 Å{sup –1}; at 295 K a = 8.516(1) Å, c = 5.1910(6) Å, R/wR = 0.58/0.56%, Δρ{sub min}/Δρ{sub max} =–0.73/0.42 e/Å{sup 3}, 4414 independent reflections; at 106 K a = 8.5109(9) Å, c = 5.1861(9) Å, R/wR = 0.75/0.86%, Δρ{sub min}/Δρ{sub max} =–0.81/1.06 e/Å{sup 3}, 4382 reflections). The distinguishing feature of the Ba{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14} structure is a strong disorder of the Ga atom at the 3f site. Structural transformations in the series of Сa{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14}–Sr{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14}–Ba{sub 3}TaGa{sub 3}Si{sub 2}O{sub 14}–Ba{sub 3}TaFe{sub 3}Si{sub 2}O{sub 14} crystals were analyzed.
Mixed Precision Iterative Refinement with Sparse Approximate Inverse Preconditioning
Not provided.
Modeling protein structures from predicted contacts with modern molecular dynamics potentials: accuracy, sensitivity, and refinement
Protein structure prediction has become increasingly popular and successful in recent years. An essential step for fragment-free, template-free methods is the generation of a final three-dimensional protein model from a set of predicted amino acid contacts that are often described by interresidue pairwise atomic distances. Here we explore the use of modern, open-source molecular dynamics (MD) engines, which have been continually developed over the last three decades with all-atom Hamiltonians to model biomolecular structure and dynamics, to generate accurate protein structures starting from a set of inferred pairwise distances. Additionally, the ability of MD empirical physical potentials to correct inaccuracies in the predicted geometries is tested. We rigorously characterize the effect of modeling parameters on results, the effect of different amounts of error in the predicted distances on the final structures, and test the ability of post-processing analysis to sort the best models out of a set of statistical replicas. We find that with exact distances and with noisy distances, the method can produce excellent structural models, and that the molecular dynamics force field seems to help correct errors in distance predictions, resisting the effects of applied noise.