Meso-Scale Experimental & Numerical Studies for Predicting Macro-scale Performance of Advanced Reactive Materials (ARMs)

2015 ◽  
Author(s):  
Naresh Thadhani ◽  
Arun Gokhale ◽  
Jason Quenneville ◽  
Jennifer Breidenich ◽  
Manny Gonzales ◽  
...  
2010 ◽  
Vol 160-162 ◽  
pp. 1211-1216
Author(s):  
Zhuang Liu ◽  
Xiao Qing Wu

The impregnation stage of the Resin Transfer Moulding process can be simulated by solving the Darcy equations on a mould model, with a ‘macro-scale’ finite element method. For every element, a local ‘meso-scale’ permeability must be determined, taking into account the local deformation of the textile reinforcement. This paper demonstrates that the meso-scale permeability can be computed efficiently and accurately by using meso-scale simulation tools. We discuss the speed and accuracy requirements dictated by the macro-scale simulations. We show that these requirements can be achieved for two meso-scale simulators, coupled with a geometrical textile reinforcement modeller. The first solver is based on a finite difference discretisation of the Stokes equations, the second uses an approximate model, based on a 2D simulation of the flow.


2019 ◽  
Author(s):  
Milou Straathof ◽  
Michel R.T. Sinke ◽  
Theresia J.M. Roelofs ◽  
Erwin L.A. Blezer ◽  
R. Angela Sarabdjitsingh ◽  
...  

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in many disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional connectivity and macro-scale diffusion-based structural connectivity, but no correspondence between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Locally, strong functional connectivity was found in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Distinct structure-function relationships across the brain can explain the organization of networks and may underlie variations in the impact of structural damage on functional networks and behavior.


2019 ◽  
Vol 864 ◽  
pp. 1-4 ◽  
Author(s):  
S. Luding

Fluid mechanics and rheology involve many unsolved challenges related to the transport mechanisms of mass, momentum and energy – especially when it comes to realistic, industrially relevant materials. Very interesting are suspensions or granular fluids with solid, particulate ingredients that feature contact mechanics on the micro-scale, which affect the transport properties on the continuum- or macro-scale. Their unique ability to behave as either fluid, or solid or both, can be quantified by non-Newtonian rheological rules, and results in interesting mechanisms such as super-diffusion, shear thickening, fluid–solid transitions (jamming) or relaxation/creep. Focusing on the steady state flow of a granular fluid, one can attempt to answer a long-standing question: how do realistic material properties such as dissipation, stiffness, friction or cohesion influence the rheology of a granular fluid? In a recent paper Macaulay & Rognon (J. Fluid Mech., vol. 858, 2019, R2) shed new light on the effect cohesion can have on mass transport in sheared, sticky granular fluids. On top of the usual diffusive, stochastic modes of transport, cohesion can create and stabilise clusters of particles into bigger agglomerates that carry particles over large distances – either ballistically in the dilute regime, or by their rotation in the dense regime. Importantly, these clusters must not only be larger than the particles (defining the intermediate, meso-scale), but they must also have a finite lifetime, in order to be able to exchange mass with each other, which can seriously enhance transport in sticky granular fluids by rotection, i.e. a combination of rotation and convection.


Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos

The precise control of mass and energy deposition associated with additive manufacturing (AM) processes enables the topological specification and realization of how space can be filled by material in multiple scales. Consequently, AM can be pursued in a manner that is optimized such that fabricated objects can best realize performance specifications. In the present work, we propose a computational multiscale method that utilizes the unique meso-scale structuring capabilities of implicit slicers for AM, in conjunction with existing topology optimization (TO) tools for the macro-scale, in order to generate structurally optimized components. The use of this method is demonstrated on two example objects including a load bearing bracket and a hand tool. This paper also includes discussion concerning the applications of this methodology, its current limitations, a recasting of the AM digital thread, and the future work required to enable its widespread use.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Milou Straathof ◽  
Michel R. T. Sinke ◽  
Theresia J. M. Roelofs ◽  
Erwin L. A. Blezer ◽  
R. Angela Sarabdjitsingh ◽  
...  

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional and macro-scale diffusion-based structural connectivity, but no significant correlation between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Zooming in on individual connections, we found strong functional connectivity in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Although characteristics of the applied techniques may affect where structural and functional networks (dis)agree, distinct structure-function relationships across the brain could also have a biological basis.


2018 ◽  
Vol 182 ◽  
pp. 200-211 ◽  
Author(s):  
Joseph Mouallem ◽  
Norman Chavez-Cussy ◽  
Seyed R.A. Niaki ◽  
Christian C. Milioli ◽  
Fernando E. Milioli
Keyword(s):  

2012 ◽  
Vol 31 ◽  
pp. 15-21 ◽  
Author(s):  
A. Künne ◽  
M. Fink ◽  
H. Kipka ◽  
P. Krause ◽  
W.-A. Flügel

Abstract. In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94%. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agro-environmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Bäse et al., 2007; Fink, 2006; Fink et al., 2007).


Author(s):  
P. M. Moore ◽  
F. Modica ◽  
G. J. Wiens ◽  
I. Fassi

This paper discusses the applications and development of magnetic actuators for meso-scale mechanisms. Due to their small sizes, meso-scale parts cannot be actuated using techniques typical of macro-scale mechanisms, such as servos or ball screws. Similarly, the techniques used in micro-actuation, such as the use of electrostatic force in MEMS devices, cannot be easily scaled up to the meso-scale. As a result, the use of magnetic forces for actuating meso-scale mechanisms may be capable of filling this void of actuation methods. A case study of a fixturing mechanism meant for meso-scale end-milling was analyzed. This mechanism uses two fixed-fixed beams in order to actively tune the harmonic modes of the machining operation in order to improve the stability of the cutting. It also uses magnetic forces to actuate the fixturing platform in order to provide close-loop feedback of cutting force.


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