Showing papers by "David S. Smith published in 2012"

Bulk composition and microstructure dependence of effective thermal conductivity of porous inorganic polymer cements

Abstract: Experimental results and theoretical models are used to assess the effective thermal conductivity of porous inorganic polymer cements, often indicated as geopolymers, with porosity between 30 and 70. vol.%. It is shown that the bulk chemical composition affects the microstructure (grains size, pores size, spatial arrangement of pores, homogeneity, micro cracks, bleeding channels) with consequently the heat flow behaviour through the porous matrix. In particular, introduction of controlled fine pores in a homogeneous matrix of inorganic polymer cements results in an increase of pore volume and improvement of the thermal insulation. The variation of the effective thermal conductivity with the total porosity was found to be consistent with analytical models described by Maxwell-Eucken and Landauer.

Exposure rate constants and lead shielding values for over 1,100 radionuclides.

Abstract: The authors have assembled a compilation of exposure rate constants, ƒ-factors, and lead shielding thicknesses for more than 1,100 radionuclides described in ICRP Publication 107. Physical data were taken from well established reference sources for mass-energy absorption coefficients in air, attenuation coefficients, and buildup factors in lead and other variables.The data agreed favorably for the most part with those of other investigators; thus this compilation provides an up-to-date and sizeable database of these data, which are of interest to many for routine calculations. Emissions were also segregated by emitting nuclide, and decay product emissions were emitted from the calculated coefficients, thus for the first time providing for the calculation of exposure rates from arbitrary mixtures of nuclides in arbitrary equilibrium states.

Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods.

Abstract: Compressive sensing (CS) has been shown to enable dramatic acceleration of MRI acquisition in some applications. Being an iterative reconstruction technique, CS MRI reconstructions can be more time-consuming than traditional inverse Fourier reconstruction. We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. We demonstrate that the combination of the rapid convergence of the split Bregman algorithm and the massively parallel strategy of GPU computing can enable real-time CS reconstruction of even acquisition data matrices of dimension 40962 or more, depending on available GPU VRAM. Reconstruction of two-dimensional data matrices of dimension 10242 and smaller took ~0.3 s or less, showing that this platform also provides very fast iterative reconstruction for small-to-moderate size images.

Robustness of Quantitative Compressive Sensing MRI: The Effect of Random Undersampling Patterns on Derived Parameters for DCE- and DSC-MRI

Abstract: Compressive sensing (CS) in Cartesian magnetic resonance imaging (MRI) involves random partial Fourier acquisitions. The random nature of these acquisitions can lead to variance in reconstruction errors. In quantitative MRI, variance in the reconstructed images translates to an uncertainty in the derived quantitative maps. We show that for a spatially regularized 2 ×-accelerated human breast CS DCE-MRI acquisition with a 1922 matrix size, the coefficients of variation (CoVs) in voxel-level parameters due to the random acquisition are 1.1%, 0.96%, and 1.5% for the tissue parameters Ktrans, ve, and vp, with an average error in the mean of -2.5%, -2.0%, and -3.7%, respectively. Only 5% of the acquisition schemes had a systematic underestimation larger than than 4.2%, 3.7%, and 6.1%, respectively. For a 2× -accelerated rat brain CS DSC-MRI study with a 642 matrix size, the CoVs due to the random acquisition were 19%, 9.5%, and 15% for the cerebral blood flow and blood volume and mean transit time, respectively, and the average errors in the tumor mean were 9.2%, 0.49%, and -7.0%, respectively. Across 11000 different CS reconstructions, we saw no outliers in the distribution of parameters, suggesting that, despite the random undersampling schemes, CS accelerated quantitative MRI may have a predictable level of performance.

A modulatory effect of male voice pitch on long-term memory in women: evidence of adaptation for mate choice?

Abstract: From a functionalist perspective, human memory should be attuned to information of adaptive value for one's survival and reproductive fitness. While evidence of sensitivity to survival-related information is growing, specific links between memory and information that could impact upon reproductive fitness have remained elusive. Here, in two experiments, we showed that memory in women is sensitive to male voice pitch, a sexually dimorphic cue important for mate choice because it not only serves as an indicator of genetic quality, but may also signal behavioural traits undesirable in a long-term partner. In Experiment 1, we report that women's visual object memory is significantly enhanced when an object's name is spoken during encoding in a masculinised (i.e., lower-pitch) versus feminised (i.e., higher-pitch) male voice, but that no analogous effect occurs when women listen to other women's voices. Experiment 2 replicated this pattern of results, additionally showing that lowering and raising male voice pitch enhanced and impaired women's memory, respectively, relative to a baseline (i.e., unmanipulated) voice condition. The modulatory effect of sexual dimorphism cues in the male voice may reveal a mate-choice adaptation within women's memory, sculpted by evolution in response to the dilemma posed by the double-edged qualities of male masculinity.

Thermal conductivity of geomaterial foams based on silica fume

Abstract: Porous materials have been prepared from a solution containing sodium silicate and sodium hydroxide with the addition of silica fume. Kaolin and diatomite were also tested as additives to the initial formulation. This method yields consolidated geomaterial foams without requiring thermal treatment above $$50\,{}^{\circ}\hbox{C}$$ . The influence of chemical composition on the thermal conductivity was studied. The choice of raw materials was found to play an important role. The accuracy of thermal conductivity measurements was evaluated by comparing the steady state heat flow method with the laser flash technique for five different reference materials giving values within 6%. Using the steady state heat flow method, a value of $$0.12 \pm 0.01\,{\rm W}\,{\rm m}^{-1}\,{\rm K}^{-1}$$ was then obtained for consolidated foams, made with kaolin as the precursor, containing approximately 70% of porosity.

Thermal conductivity calculation of bio-aggregates based materials using finite and discrete element methods

Abstract: This work is about the calculation of thermal conductivity of insulating building materials made from plant particles. To determine the type of raw materials, the particle sizes or the volume fractions of plant and binder, a tool dedicated to calculate the thermal conductivity of heterogeneous materials has been developped, using the discrete element method to generate the volume element and the finite element method to calculate the homogenized properties. A 3D optical scanner has been used to capture plant particle shapes and convert them into a cluster of discret elements. These aggregates are initially randomly distributed but without any overlap, and then fall down in a container due to the gravity force and collide with neighbour particles according to a velocity Verlet algorithm. Once the RVE is built, the geometry is exported in the open-source Salome-Meca platform to be meshed. The calculation of the effective thermal conductivity of the heterogeneous volume is then performed using a homogenization technique, based on an energy method. To validate the numerical tool, thermal conductivity measurements have been performed on sunflower pith aggregates and on packed beds of the same particles. The experimental values have been compared satisfactorily with a batch of numerical simulations.