Analysis and interpretation of the first monochromatic X‐ray tomography data collected at the Australian Synchrotron Imaging and Medical beamline

The first monochromatic X‐ray tomography experiments conducted at the Imaging and Medical beamline of the Australian Synchrotron are reported. The sample was a phantom comprising nylon line, Al wire and finer Cu wire twisted together. Data sets were collected at four different X‐ray energies. In order to quantitatively account for the experimental values obtained for the Hounsfield (or CT) number, it was necessary to consider various issues including the point‐spread function for the X‐ray imaging system and harmonic contamination of the X‐ray beam. The analysis and interpretation of the data includes detailed considerations of the resolution and efficiency of the CCD detector, calculations of the X‐ray spectrum prior to monochromatization, allowance for the response of the double‐crystal Si monochromator used (via X‐ray dynamical theory), as well as a thorough assessment of the role of X‐ray phase‐contrast effects. Computer simulations relating to the tomography experiments also provide valuable insights into these important issues. It was found that a significant discrepancy between theory and experiment for the Cu wire could be largely resolved in terms of the effect of the point‐spread function. The findings of this study are important in respect of any attempts to extract quantitative information from X‐ray tomography data, across a wide range of disciplines, including materials and life sciences.     

Design Element Concept of squeeze casting process

Design sensitivity analysis and the application of Design Element Concept have been explored. Exploration has focused on expressed sensitivity with respect to material property and shape of the coolant channel. The Design Element Concept has been applied to the die domain, since the design elements can be considered as a direct mapping of the blocks that make up a die. Analytical methods such as Direct Differentiation Method (DDM) and Adjoint Variable Method (AVM) have been employed in calculating the design element sensitivities. All the calculated design element sensitivities were verified with the Finite Difference Method and the results showed close agreement. From the design element sensitivities distribution in the die, the results show that convergence can be observed as more design elements are employed.     

X-ray scattering from warm dense iron

We have carried out X-ray scattering experiments on iron foil samples that have been compressed and heated using laser-driven shocks created with the VULCAN laser system at the Rutherford-Appleton Laboratory. This is the highest Z element studied in such experiments so far and the first time scattering from warm dense iron has been reported. Because of the importance of iron in telluric planets, the work is relevant to studies of warm dense matter in planetary interiors. We report scattering results as well as shock breakout results that, in conjunction with hydrodynamic simulations, suggest the target has been compressed to a molten state at several 100 GPa pressure. Initial comparison with modelling suggests more work is needed to understand the structure factor of warm dense iron.     

Application of recurrent radon precursors for forecasting large earthquakes (Mw > 6.0) near Antung,Taiwan

Radon anomalies in groundwater were recorded prior to three major earthquakes – (1) 2003 M_w = 6.8 Chengkung, (2) 2006 M_w = 6.1 Taitung, and (3) 2008 M_w = 5.4 Antung. The epicenters were located 24 km, 52 km, and 13 km, respectively, from the Antung radon-monitoring station. Prior to the three major earthquakes, radon decreased from background levels of 29.3 ± 1.7, 28.2 ± 2.1, and 27.2 ± 1.8 Bq dm^?3 to minima of 12.1 ± 0.3, 13.7 ± 0.3, and 17.8 ± 1.6 Bq dm^?3, respectively. Based on the radon precursory data, this paper correlates the observed radon minima with earthquake magnitude and precursory time. The correlations provide a possible means for forecasting local disastrous earthquakes in the southern segment of coastal range and longitudinal valley of eastern Taiwan.     

The Fluorination of C−H Bonds: Developments and Perspectives

This Review summarizes advances in fluorination by C(sp²)?H and C(sp³)?H activation. Transition‐metal‐catalyzed approaches championed by palladium have allowed the installation of a fluorine substituent at C(sp²) and C(sp³) sites, exploiting the reactivity of high‐oxidation‐state transition‐metal fluoride complexes combined with the use of directing groups (some transient) to control site and stereoselectivity. The large majority of known methods employ electrophilic fluorination reagents, but methods combining a nucleophilic fluoride source with an oxidant have appeared. External ligands have proven to be effective for C(sp³)?H fluorination directed by weakly coordinating auxiliaries, thereby enabling control over reactivity. Methods relying on the formation of radical intermediates are complementary to transition‐metal‐catalyzed processes as they allow for undirected C(sp³)?H fluorination. To date, radical C?H fluorinations mainly employ electrophilic N?F fluorination reagents but a unique Mn^III‐catalyzed oxidative C?H fluorination using fluoride has been developed. Overall, the field of late‐stage nucleophilic C?H fluorination has progressed much more slowly, a state of play explaining why C?H ¹⁸F‐fluorination is still in its infancy.     

Laboratory Investigation of LNAPL Migration in Double-Porosity Soil Under Fractured Condition Using Digital Image Analysis

Gas production from shale gas reservoirs plays a significant role in satisfying increasing energy demands. Compared with conventional sandstone and carbonate reservoirs, shale gas reservoirs are characterized by extremely low porosity, ultra-low permeability and high clay content. Slip flow, diffusion, adsorption and desorption are the primary gas transport processes in shale matrix, while Darcy flow is restricted to fractures. Understanding methane diffusion and adsorption, and gas flow and equilibrium in the low-permeability matrix of shale is crucial for shale formation evaluation and for predicting gas production. Modeling of diffusion in low-permeability shale rocks requires use of the Dusty gas model (DGM) rather than Fick’s law. The DGM is incorporated in the TOUGH2 module EOS7C-ECBM, a modified version of EOS7C that simulates multicomponent gas mixture transport in porous media. Also included in EOS7C-ECBM is the extended Langmuir model for adsorption and desorption of gases. In this study, a column shale model was constructed to simulate methane diffusion and adsorption through shale rocks. The process of binary \(\hbox {CH}_{4}{-}\hbox {N}_{2}\) diffusion and adsorption was analyzed. A sensitivity study was performed to investigate the effects of pressure, temperature and permeability on diffusion and adsorption in shale rocks. The results show that methane gas diffusion and adsorption in shale is a slow process of dynamic equilibrium, which can be illustrated by the slope of a curve in \(\hbox {CH}_{4}\) mass variation. The amount of adsorption increases with the pressure increase at the low pressure, and the mass change by gas diffusion will decrease due to the decrease in the compressibility factor of the gas. With the elevated temperature, the gas molecules move faster and then the greater gas diffusion rates make the process duration shorter. The gas diffusion rate decreases with the permeability decrease, and there is a limit of gas diffusion if the permeability is less than \(1.0\,\times \,10^{-15}\, \hbox { m}^{2}\). The results can provide insights for a better understanding of methane diffusion and adsorption in the shale rocks so as to optimize gas production performance of shale gas reservoirs.     

The Effect of Fuel-Injection Timing on In-cylinder Flow and Combustion Performance in a Spark-Ignition Direct-Injection (SIDI) Engine Using Particle Image Velocimetry (PIV)

This study applies particle image velocimetry (PIV) to an optical spark-ignition direct-injection engine in order to investigate the effects of fuel-injection on in-cylinder flow. Five injection timing combinations, each employing a stoichiometric 1:1 split ratio double-injection strategy, were analysed at an engine speed of 1200 RPM and an intake pressure of 100 kPa. Timings ranged from two injections in the intake stroke to two injections in the compression stroke, resulting in a variety of in-cylinder environments from well-mixed to highly turbulent. PIV images were acquired at a sampling frequency of 5 kHz on a selected swirl plane. The flow fields were decomposed into mean and fluctuating components via two spatial filtering approaches — one using a fixed 8 mm cut-off length, and the other using a mean flow speed scaled cut-off length which was tuned in order to match the turbulent kinetic energy (TKE) profile of a 300 Hz temporal filter. From engine performance tests, the in-cylinder pressure traces, indicated mean effective pressure (IMEP), and combustion phasing data showed very high sensitivity to injection timing variations. To explain the observed trend, correspondence between the measured flow and these performance parameters was evaluated. An expected global trend of increasing turbulence with retarded injection timing was clearly observed; however, relationships between TKE and burn rate were not as obvious as anticipated, suggesting that turbulence is not the predominant factor associated with injection timing variations which impacts engine performance. Stronger links were observed between bulk flow velocity and burn rate, particularly during the early stages of flame development. Injection timing was also found to have a significant impact on combustion stability, where it was observed that low-frequency flow fluctuation intensity revealed strong similarities with the coefficient of variance (CoV) of IMEP, suggesting that these fluctuations are a suitable measure of cycle-to-cycle variation — likely due to the influence of bulk flow on flame kernel development.     

An Extension of the Stefan-Type Solution Method Applicable to Multi-component,Multi-phase 1D Systems

We present an extension of the Stefan-type solution method applicable to multi-component, multi-phase 1D porous flows, and illustrate the method by applying it to phase separation dynamics in an NaCl–\(\hbox {H}_2\hbox {O}\)-saturated hydrothermal heat pipe. For this example, three mathematical models are constructed. The first two models concern the rate of progression of two interfaces, one separating brine from two-phase fluid and another separating two-phase fluid from single-phase liquid at seawater salinity. The brine layer model shows that the layer may reach quasi-steady-state thickness even while the salt content of the layer continues to increase; the two-phase layer model shows how variable heat flux at the top of the layer leads to departure from the linear growth rate predicted by a simpler model. The third model concerns the temperature profile in the entire column. The governing advection–diffusion equation has highly variable coefficients, with no negligible terms in it in the region of parameter space considered. We present a method to solve this type of equation by constructing a propagator and a corresponding Green’s function. Finally, we show how to use the developed framework to test the internal consistency of numerical simulations, again using the 1D heat pipe as an example.     

Altered Phase Interactions between Spontaneous Blood Pressure and Flow Fluctuations in Type 2 Diabetes Mellitus: Nonlinear Assessment of Cerebral Autoregulation

Cerebral autoregulation is an important mechanism that involves dilatation and constriction in arterioles to maintain relatively stable cerebral blood flow in response to changes of systemic blood pressure. Traditional assessments of autoregulation focus on the changes of cerebral blood flow velocity in response to large blood pressure fluctuations induced by interventions. This approach is not feasible for patients with impaired autoregulation or cardiovascular regulation. Here we propose a newly developed technique—the multimodal pressure-flow (MMPF) analysis, which assesses autoregulation by quantifying nonlinear phase interactions between spontaneous oscillations in blood pressure and flow velocity during resting conditions. We show that cerebral autoregulation in healthy subjects can be characterized by specific phase shifts between spontaneous blood pressure and flow velocity oscillations, and the phase shifts are significantly reduced in diabetic subjects. Smaller phase shifts between oscillations in the two variables indicate more passive dependence of blood flow velocity on blood pressure, thus suggesting impaired cerebral autoregulation. Moreover, the reduction of the phase shifts in diabetes is observed not only in previously-recognized effective region of cerebral autoregulation (<0.1 Hz), but also over the higher frequency range from ∼0.1 to 0.4 Hz. These findings indicate that type 2 diabetes mellitus alters cerebral blood flow regulation over a wide frequency range and that this alteration can be reliably assessed from spontaneous oscillations in blood pressure and blood flow velocity during resting conditions. We also show that the MMPF method has better performance than traditional approaches based on Fourier transform, and is more suitable for the quantification of nonlinear phase interactions between nonstationary biological signals such as blood pressure and blood flow.