Journal: Materials

Article Title: Reduced Order Multiscale Simulation of Diffuse Damage in Concrete

doi: 10.3390/ma14143830

Figure Lengend Snippet: Schematic illustration of the multiscale computational homogenisation approach considered in this paper.

Article Snippet: Mesoscale models can be formulated using a variety of discretisation methods, such as the Finite Element Method (FEM) [ , , , , ], the Discrete Element Method (DEM) [ ], and Fast Fourier Transform (FFT)-based homogenisation methods [ , , ].

Techniques: Homogenization

Journal: Materials

Article Title: Reduced Order Multiscale Simulation of Diffuse Damage in Concrete

doi: 10.3390/ma14143830

Figure Lengend Snippet: Material parameters for the large quarzitic aggregates and the calibrated parameters for mortar, containing a volume fraction φ q u a r t z = 30.34 % of fine quarzitic aggregates. The mortar matrix is assumed to contain a 8.3% volume fraction of initial microcracks with an initial aspect ratio of 23. In the investigated concrete sample, the material properties of the mortar matrix with a volume fraction of φ q u a r t z = 43.95 % are determined by varying the volume fraction of aggregate accordingly in the Mori–Tanaka based homogenisation procedure, while keeping other parameters unchanged (group Model parameters ). The following sources are used to determine the parameters: [ 1 − 3 ]—Experiment, [ 4 , 5 ] aspect ratio is taken within the range measured in [ 69 ], 6 —[ 24 , 70 ].

Article Snippet: Mesoscale models can be formulated using a variety of discretisation methods, such as the Finite Element Method (FEM) [ , , , , ], the Discrete Element Method (DEM) [ ], and Fast Fourier Transform (FFT)-based homogenisation methods [ , , ].

Techniques: Homogenization

Journal: Materials

Article Title: Reduced Order Multiscale Simulation of Diffuse Damage in Concrete

doi: 10.3390/ma14143830

Figure Lengend Snippet: Schematic illustration of the IDD homogenisation scheme.

Article Snippet: Mesoscale models can be formulated using a variety of discretisation methods, such as the Finite Element Method (FEM) [ , , , , ], the Discrete Element Method (DEM) [ ], and Fast Fourier Transform (FFT)-based homogenisation methods [ , , ].

Techniques: Homogenization

Journal: eLife

Article Title: Encounter complexes and dimensionality reduction in protein–protein association

doi: 10.7554/eLife.01370

Figure Lengend Snippet: Unbound structures were used both for the receptor, EIN (chain A from PDB entry 1ZYM) and for the ligand, HPr (chain P from PDB entry 2JEL). Encounter complexes were generated using Fast Fourier transform (FFT) based sampling. ( A ) Cartoon of the specific complex formed by EIN and HPr, shown in grey and yellow, respectively. The locations of the paramagnetic tags E5C-EDTA-Mn + and E32C-EDTA-Mn 2+ on HPr are encircled and are shown in red and blue, respectively. ( B ) Centers of HPr structures in the encounter complex ensemble. Colors indicate classification as follows ( 8 ): blue, Class I (i.e., overlapping with the specific complex); magenta, patch 1 of Class II (i.e., non-overlapping) positions; red, patch 2 of Class II positions; and pink, additional Class II position outside the main patches. ( C ) Ligand IRMSD vs PIPER energy score. ( D ) Two representative HPr poses, colored light blue and dark blue, from Class I. ( E ) Two representative HPr poses (in different shades of magenta) from Patch 1 of Class II. ( F ) View of the EIN–HPr complex and the centers of HPr poses after rotating 180° around the vertical axis (the bound HPr is now on the left side, almost completely hidden by EIN). ( G ) Representative HPr poses (in different shades of red) from Patch 2 of Class II, shown in the rotated view. DOI: http://dx.doi.org/10.7554/eLife.01370.003

Article Snippet: DB: Owns stock in Acpharis Inc which licensed FFT based sampling program PIPER for commerical use.

Techniques: Generated, Sampling