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Zhang, Fan

Publications and source records attributed to Zhang, Fan.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Phase structure in segmented polyurethanes having fatty acid-based soft segments

Abstract: Structural studies on two segmented polyurethanes prepared form the modified oleic acid soft segments and butane diol/diphenylmethane diisocyanate hard segments, were carried out. Polyurethanes were thermoplastic elastomers with soft segment concentration (SSC) of 50% (TPU-50) and 70% (TPU-70). Dynamic mechanical analysis revealed the co-continuous morphology in TPU-50 and dispersed hard domains in the soft matrix in TPU-70. AFM revealed the micron size globules in TPU-70 ascribed to hard segment-rich spherulites and alternating small soft and hard domains in TPU- 50, with lateral dimensions of about 15 nm with local modulus deviations from 40 to 50 MPa, consistent with co-continuous morphology. The dispersed hard domains in the soft matrix for TPU-70, and co-continuous phases in TPU-50 morphology was confirmed. USAXS showed the domain spacing for TPU-50 was about 13.3 nm and about 11.3 nm for TPU-70. USAXS revealed that the interface between phase-separated domains exhibit a surface-fractal-like behavior.

fatty acid↗
DOE OSTI2013

Using cross-layer adaptations for dynamic data management in large scale coupled scientific workflows, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

As system scales and application complexity grow, managing and processing simulation data has become a significant challenge. While recent approaches based on data staging and in-situ/in-transit data processing are promising, dynamic data volumes and distributions, such as those occurring in AMR-based simulations, make the efficient use of these techniques challenging. In this paper we propose cross-layer adaptations that address these challenges and respond at runtime to dynamic data management requirements. Specifically we explore (1) adaptations of the spatial resolution at which the data is processed, (2) dynamic placement and scheduling of data processing kernels, and (3) dynamic allocation of in-transit resources. We also exploit coordinated approaches that dynamically combine these adaptations at the different layers. We evaluate the performance of our adaptive cross-layer management approach on the Intrepid IBM-BlueGene/P and Titan Cray-XK7 systems using Chombo-based AMR applications, and demonstrate its effectiveness in improving overall time-to-solution and increasing resource efficiency.

Computer Science↗
DOE OSTI2012

Preparation and characterization of multi-walled carbon nanotubes with nickel–phosphorous layers of high magnetic properties

Highlights: ► Impurities in crude MWNTs were effectively removed after purification treatment. ► Many Ni nanoparticles were homogenously coated on the purified MWNTs. ► The saturation magnetization (Ms) of the MWNTs with Ni–P layers is 91.5 emu/g. -- Abstract: The multi-wall carbon nanotubes (MWNTs) with nickel–phosphorous (Ni–P) layers were prepared by electroless plating method. To obtain the MWNTs with Ni–P layers of high magnetic properties, an effective purification treatment and a pre-treatment procedure were developed. The crude MWNTs, the purified MWNTs and the MWNTs with Ni–P layers were characterized by scanning electron microscope (SEM)/energy dispersive spectroscopy (EDS), transmission electron microscope (TEM), X-ray diffraction (XRD) and vibrating sample magnetometer (VSM). SEM results, TEM images and XRD results indicate that impurities in the crude MWNTs were effectively removed after the purification treatment and a large number of Ni nanoparticles were homogenously coated on the surface of the purified MWNTs. According to the VSM test, the saturation magnetization (Ms) of the MWNTs with Ni–P layers is 91.5 emu/g which is higher than results of other researchers.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Combining In-situ and In-transit Processing to Enable Extreme-Scale Scientific Analysis

With the onset of extreme-scale computing, I/O constraints make it increasingly difficult for scientists to save a sufficient amount of raw simulation data to persistent storage. One potential solution is to change the data analysis pipeline from a post-process centric to a concurrent approach based on either in-situ or in-transit processing. In this context computations are considered in-situ if they utilize the primary compute resources, while in-transit processing refers to offloading computations toa set of secondary resources using asynchronous data transfers. In this paper we explore the design and implementation of three common analysis techniques typically performed on large-scale scientific simulations: topological analysis, descriptive statistics, and visualization. We summarize algorithmic developments, describe a resource scheduling system to coordinate the execution ofvarious analysis workflows, and discuss our implementation using the DataSpaces and ADIOS frameworks that support efficient data movement between in-situ and in-transit computations. Wedemonstrate the efficiency of our lightweight, flexible framework by deploying it on the Jaguar XK6 to analyze data generated by S3D, a massively parallel turbulent combustion code. Our framework allows scientists dealing with the data deluge at extreme scale to perform analyses at increased temporal resolutions, mitigate I/O costs, and significantly improve the time to insight.

Bennett, Janine C.↗
DOE OSTI2012

In Situ Processing

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97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Synergistic enhancement of iron oxide nanoparticle and gadolinium for dual-contrast MRI

Highlights: Black-Right-Pointing-Pointer MR contrast agents exert influence on T{sub 1} or T{sub 2} relaxation time of the surrounding tissue. Black-Right-Pointing-Pointer Combined use of iron oxide and Gd-DTPA can improve the sensitivity/specificity of lesion detection. Black-Right-Pointing-Pointer Dual contrast MRI enhances the delineation of tumor borders and small lesions. Black-Right-Pointing-Pointer The effect of DC-MRI can come from the high paramagnetic susceptibility of Gd{sup 3+}. Black-Right-Pointing-Pointer The effect of DC-MRI can also come from the distinct pharmacokinetic distribution of SPIO and Gd-DTPA. -- Abstract: Purpose: The use of MR contrast agents allows accurate diagnosis by exerting an influence on the longitudinal (T{sub 1}) or transverse (T{sub 2}) relaxation time of the surrounding tissue. In this study, we combined the use of iron oxide (IO) particles and nonspecific extracellular gadolinium chelate (Gd) in order to further improve the sensitivity and specificity of lesion detection. Procedures: With a 7-Tesla scanner, pre-contrasted, IO-enhanced and dual contrast agent enhanced MRIs were performed in phantom, normal animals, and animal models of lymph node tumor metastases and orthotopic brain tumor. For the dual-contrast (DC) MRI, we focused on the evaluation of T{sub 2} weighted DC MRI with IO administered first, then followed by the injection of a bolus of gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA). Results: Based on the C/N ratios and MRI relaxometry, the synergistic effect of coordinated administration of Gd-DTPA and IO was observed and confirmed in phantom, normal liver and tumor models. At 30 min after administration of Feridex, Gd-DTPA further decreased T{sub 2} relaxation in liver immediately after the injection. Additional administration of Gd-DTPA also immediately increased the signal contrast between tumor and brain parenchyma and maximized the C/N ratio to -4.12 {+-} 0.71. Dual contrast MRI also enhanced the delineation of tumor borders and small lesions. Conclusions: DC-MRI will be helpful to improve diagnostic accuracy and decrease the threshold size for lesion detection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Enabling In-situ Execution of Coupled Scientific Workflow on Multi-core Platform

Emerging scientific application workflows are composed of heterogeneous coupled component applications that simulate different aspects of the physical phenomena being modeled, and that interact and exchange significant volumes of data at runtime. With the increasing performance gap between on-chip data sharing and off-chip data transfers in current systems based on multicore processors, moving large volumes of data using communication network fabric can significantly impact performance. As a result, minimizing the amount of inter-application data exchanges that are across compute nodes and use the network is critical to achieving overall application performance and system efficiency. In this paper, we investigate the in-situ execution of the coupled components of a scientific application workflow so as to maximize on-chip exchange of data. Specifically, we present a distributed data sharing and task execution framework that (1) employs data-centric task placement to map computations from the coupled applications onto processor cores so that a large portion of the data exchanges can be performed using the intra-node shared memory, (2) provides a shared space programming abstraction that supplements existing parallel programming models (e.g., message passing) with specialized one-sided asynchronous data access operators and can be used to express coordination and data exchanges between the coupled components. We also present the implementation of the framework and its experimental evaluation on the Jaguar Cray XT5 at Oak Ridge National Laboratory.

Computer Science↗
DOE OSTI2012

A scalable messaging system for accelerating discovery from large scale scientific simulations

Emerging scientific and engineering simulations running at scale on leadership-class High End Computing (HEC) environments are producing large volumes of data, which has to be transported and analyzed before any insights can result from these simulations. The complexity and cost (in terms of time and energy) associated with managing and analyzing this data have become significant challenges, and are limiting the impact of these simulations. Recently, data-staging approaches along with in-situ and in-transit analytics have been proposed to address these challenges by offloading I/O and/or moving data processing closer to the data. However, scientists continue to be overwhelmed by the large data volumes and data rates. In this paper we address this latter challenge. Specifically, we propose a highly scalable and low-overhead associative messaging framework that runs on the data staging resources within the HEC platform, and builds on the staging-based online in-situ/in- transit analytics to provide publish/subscribe/notification-type messaging patterns to the scientist. Rather than having to ingest and inspect the data volumes, this messaging system allows scientists to (1) dynamically subscribe to data events of interest, e.g., simple data values or a complex function or simple reduction (max()/min()/avg()) of the data values in a certain region of the application domain is greater/less than a threshold value, or certain spatial/temporal data features or data patterns are detected; (2) define customized in-situ/in-transit actions that are triggered based on the events, such as data visualization or transformation; and (3) get notified when these events occur. The key contribution of this paper is a design and implementation that can support such a messaging abstraction at scale on high- end computing (HEC) systems with minimal overheads. We have implemented and deployed the messaging system on the Jaguar Cray XK6 machines at Oak Ridge National Laboratory and the Lonestar system at the Texas Advanced Computing Center (TACC), and we present the experimental performance evaluation using these HEC platforms in the paper.

Jin, Tong↗
DOE OSTI2012

In Situ Processing

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Childs, Hank↗
NASA NTRS2003

Thermodynamic Modeling of the YO(l.5)-ZrO2 System

The YO1.5-ZrO2 system consists of five solid solutions, one liquid solution, and one intermediate compound. A thermodynamic description of this system is developed, which allows calculation of the phase diagram and thermodynamic properties. Two different solution models are used-a neutral species model with YO1.5 and ZrO2 as the components and a charged species model with Y(+3), Zr(+4), O(-2), and vacancies as components. For each model, regular and sub-regular solution parameters are derived fiom selected equilibrium phase and thermodynamic data.

Jacobson, Nathan S.↗