Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “AGGLOMERATION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Impact Of Particle Agglomeration On Accumulation Rates In The Glass Discharge Riser Of HLW Melter

The major factor limiting waste loading in continuous high-level radioactive waste (HLW) melters is an accumulation of particles in the glass discharge riser during a frequent and periodic idling of more than 20 days. An excessive accumulation can produce robust layers a few centimeters thick, which may clog the riser, preventing molten glass from being poured into canisters. Since the accumulation rate is driven by the size of particles we investigated with x-ray microtomography, scanning electron microscopy, and image analysis the impact of spinel forming components, noble metals, and alumina on the size, concentration, and spatial distribution of particles, and on the accumulation rate. Increased concentrations of Fe and Ni in the baseline glass resulted in the formation of large agglomerates that grew over the time to an average size of ~185+-155 {mu}m, and produced >3 mm thick layer after 120 h at 850 deg C. The noble metals decreased the particle size, and therefore significantly slowed down the accumulation rate. Addition of alumina resulted in the formation of a network of spinel dendrites which prevented accumulation of particles into compact layers.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Parallel Element Agglomeration Algebraic Multigrid and Upscaling Library

ParFELAG is a parallel distributed memory C++ library for numerical upscaling of finite element discretizations. It provides optimal complesity algorithms ro build multilevel hierarchies and solvers that can be used for solving a wide class of partial differential equations (elliptic, hyperbolic, saddle point problems) on general unstructured mesh (under the assumption that the topology of the agglomerated entities is correct). Additionally, a novel multilevel solver for saddle point problems with divergence constraint is implemented.

Source record↗
DOE OSTI2018

Evolution of a Modified Binomial Random Graph by Agglomeration

In the classical Erdős–Rényi random graph G(n, p) there are n vertices and each of the possible edges is independently present with probability p. The random graph G(n, p) is homogeneous in the sense that all vertices have the same characteristics. On the other hand, numerous real-world networks are inhomogeneous in this respect. Such an inhomogeneity of vertices may influence the connection probability between pairs of vertices. The purpose of this paper is to propose a new inhomogeneous random graph model which is obtained in a constructive way from the Erdős-Rényi random graph G(n, p). Given a configuration of n vertices arranged in N subsets of vertices (we call each subset a super-vertex), we define a random graph with N super-vertices by letting two super-vertices be connected if and only if there is at least one edge between them in G(n, p). Our main result concerns the threshold for connectedness. We also analyze the phase transition for the emergence of the giant component and the degree distribution. Even though our model begins with G(n, p), it assumes the existence of some community structure encoded in the configuration. Furthermore, under certain conditions it exhibits a power law degree distribution. Both properties are important for real-world applications.

97 MATHEMATICS AND COMPUTING↗