Feedbacks between size and density determine rapid eco-phenotypic dynamics
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Understanding the particle-scale dynamics of granular materials during rapid compaction and flow is of fundamental importance for manufacturing, planetary science, geology, and defense applications. Time-resolved 2D radiography and static 3D x-ray tomography are powerful in situ tools for studying particle-scale dynamics but provide detail only in 2D or with significant time-scale limitations, respectively. Here, we introduce a new method that uses 2D in situ x-ray imaging for determining time-resolved 3D particle-scale dynamics in rapidly compressed granular materials. The method employs initial particle packing structures obtained from x-ray tomography, a 2D x-ray image generation algorithm, and an optimization algorithm. We first describe and validate the method using finite element simulations. Furthermore, we then apply the technique to x-ray phase-contrast images obtained during rapid compaction of granular materials with varying particle morphology and sample thickness. The depth-resolved particle-scale dynamics reveal complex velocity and porosity fields evolving heterogeneously along and perpendicular to the compaction direction. We characterize these features, their fluctuations near the compaction front, and the compaction front thickness. Our technique can be applied to understanding granular dynamics during rapid compaction events, and rearrangements during slower, but non-quasi-static, flows.
RAPID is a methodology and software system to define a class of airplane configurations and directly evaluate surface grids, volume grids, and grid sensitivity on and about the configurations. A distinguishing characteristic which separates RAPID from other airplane surface modellers is that the output grids and grid sensitivity are directly applicable in CFD analysis. A small set of design parameters and grid control parameters govern the process which is incorporated into interactive software for 'real time' visual analysis and into batch software for the application of optimization technology. The computed surface grids and volume grids are suitable for a wide range of Computational Fluid Dynamics (CFD) simulation. The general airplane configuration has wing, fuselage, horizontal tail, and vertical tail components. The double-delta wing and tail components are manifested by solving a fourth order partial differential equation (PDE) subject to Dirichlet and Neumann boundary conditions. The design parameters are incorporated into the boundary conditions and therefore govern the shapes of the surfaces. The PDE solution yields a smooth transition between boundaries. Surface grids suitable for CFD calculation are created by establishing an H-type topology about the configuration and incorporating grid spacing functions in the PDE equation for the lifting components and the fuselage definition equations. User specified grid parameters govern the location and degree of grid concentration. A two-block volume grid about a configuration is calculated using the Control Point Form (CPF) technique. The interactive software, which runs on Silicon Graphics IRIS workstations, allows design parameters to be continuously varied and the resulting surface grid to be observed in real time. The batch software computes both the surface and volume grids and also computes the sensitivity of the output grid with respect to the input design parameters by applying the precompiler tool ADIFOR to the grid generation program. The output of ADIFOR is a new source code containing the old code plus expressions for derivatives of specified dependent variables (grid coordinates) with respect to specified independent variables (design parameters). The RAPID methodology and software provide a means of rapidly defining numerical prototypes, grids, and grid sensitivity of a class of airplane configurations. This technology and software is highly useful for CFD research for preliminary design and optimization processes.
Several high-temperature gas-cooled reactor concepts (and more recently, salt-cooled designs such as the fluoride salt-cooled high-temperature reactor) feature core designs employing continuously circulating fuel pebbles. These reactor designs permit both continuous online refueling of fuel elements as well as higher overall achievable discharge burnups. However, rapid calculation of time-dependent fuel isotopic inventories proves challenging for this class of dynamic systems with current analysis tools. While iterative approaches employing coupled neutron transport have been developed to solve this issue, rapid depletion analysis techniques are needed to calculate time-dependent inventories for individual pebbles and batches (and thus the construction of full- core inventory at equilibrium). We propose a depletion analysis strategy for this type of system for cores at equilibrium. Drawing upon previous neutronic analysis of the PBMR-400 equilibrium core, we demonstrate the viability of developing collapsed one-group cross section libraries suitable for performing rapid depletion analyses with SCALE. (authors)
The Low Cost Rapid Response Spacecraft (LCRRS) is an ongoing research development project at NASA Ames Research Center (ARC), Moffett Field, California. The prototype spacecraft, called Cost Optimized Test for Spacecraft Avionics and Technologies (COTSAT) is the first of what could potentially be a series of rapidly produced low-cost satellites. COTSAT has a target launch date of March 2009 on a SpaceX Falcon 9 launch vehicle. The LCRRS research system design incorporates use of COTS (Commercial Off The Shelf), MOTS (Modified Off The Shelf), and GOTS (Government Off The Shelf) hardware for a remote sensing satellite. The design concept was baselined to support a 0.5 meter Ritchey-Chretien telescope payload. This telescope and camera system is expected to achieve 1.5 meter/pixel resolution. The COTSAT team is investigating the possibility of building a fully functional spacecraft for $500,000 parts and $2,000,000 labor. Cost is dramatically reduced by using a sealed container, housing the bus and payload subsystems. Some electrical and RF designs were improved/upgraded from GeneSat-1 heritage systems. The project began in January 2007 and has yielded two functional test platforms. It is expected that a flight-qualified unit will be finished in December 2008. Flight quality controls are in place on the parts and materials used in this development with the aim of using them to finish a proto-flight satellite. For LEO missions the team is targeting a mission class requiring a minimum of six months lifetime or more. The system architecture incorporates several design features required by high reliability missions. This allows for a true skunk works environment to rapidly progress toward a flight design. Engineering and fabrication is primarily done in-house at NASA Ames with flight certifications on materials. The team currently employs seven Full Time Equivalent employees. The success of COTSATs small team in this effort can be attributed to highly cross trained engineering team. The engineers on the team are capable of functioning in two to three engineering disciplines which allows highly efficient interdisciplinary engineering collaboration. NASA Ames is actively proposing mission concepts to use the COTSAT platform to accomplish science. If the COTSAT team validates this approach, it will allow the possibility for remote sensing missions to produce a high science yield for minimal cost and reduced schedule. Another aim of this approach is to yield an accelerated pathway from a Phase A study to mission launch. Leaders in the aerospace industry have shown interest in this methodology. Several visits and tours have been given in the lab. Although the concept of low-cost development is initially met with skepticism from some within the prohibitive aerospace industry, the project's efforts have been highly praised for the accomplishments met within a limited time and budget. Overall the development has progressed tremendously well and the team is answering critical questions for current and future low-cost small satellite developments. COTSAT subsystems are not limited to a specific weight class and could be adapted to produce smaller platforms and to fit various launch vehicles.
The rapid, sensitive, and selective detection of target analytes using electrochemical sensors are challenging. ESSENCE, a new Electrochemical Sensor that uses a Shear-Enhanced, flowthrough Nanoporous Capacitive Electrode, overcomes current electrochemical sensors' response limitations, selectivity, and sensitivity limitations. ESSENCE is a microfluidic channel packed with transducer material sandwiched by a top and bottom microelectrode. The room-temperature instrument less integration process allows the switch of the transducer materials to make up the porous electrode without modifying the electrode architecture or device protocol. ESSENCE can be used to detect both biomolecules and small molecules by simply changing the packed transducer material. Electron microscopy results confirm the high porosity. In conjunction with the non-planar interdigitated electrode, the packed transducer material results in a flow-through porous electrode. Electron microscopy results confirm the high porosity. The enhanced shear forces and increased convective fluxes disrupt the electric double layer's (EDL) diffusive process in ESSENCE. This disruption migrates the EDL to high MHz frequency allowing the capture signal to be measured at around 100 kHz, significantly improving device timing (rapid detection) with a low signal-to-noise ratio. The device’s unique architecture allows us multiple configuration modes for measuring the impedance signal. This allows us to use highly conductive materials like carbon nanotubes. We show that by combining single-walled carbon nanotubes as transducer material with appropriate capture probes, NP-µIDE has high selectivity and sensitivity for DNA (fM sensitivity, selective against non-target DNA), breast cancer biomarker proteins (p53, pg/L sensitivity, selective against non-target HER2).
Polyolefins comprise a major fraction of single-use plastics, yet their catalytic deconstruction/recycling has proven challenging due to their inert saturated hydrocarbon connectivities. Here a very electrophilic, formally cationic earth-abundant single-site organozirconium catalyst chemisorbed on a highly Brønsted acidic sulfated alumina support and characterized by a broad array of experimental and theoretical techniques, is shown to mediate the rapid hydrogenolytic cleavage of molecular and macromolecular saturated hydrocarbons under mild conditions, with catalytic onset as low as 90 °C/0.5 atm H 2 with 0.02 mol% catalyst loading. For polyethylene, quantitative hydrogenolysis to light hydrocarbons proceeds within 48 min with an activity of > 4000 mol(CH 2 units)·mol(Zr) –1 ·h –1 at 200 °C/2 atm H 2 pressure. Under similar solventless conditions, polyethylene-co–1-octene, isotactic polypropylene, and a post-consumer food container cap are rapidly hydrogenolyzed to low molecular mass hydrocarbons. Regarding mechanism, theory and experiment identify a turnover-limiting C-C scission pathway involving ß-alkyl transfer rather than the more common σ-bond metathesis.
Abstract X-ray bursts are among the brightest stellar objects frequently observed in the sky by space-based telescopes. A type-I X-ray burst is understood as a violent thermonuclear explosion on the surface of a neutron star, accreting matter from a companion star in a binary system. The bursts are powered by a nuclear reaction sequence known as the rapid proton capture process (rp process), which involves hundreds of exotic neutron-deficient nuclides. At so-called waiting-point nuclides, the process stalls until a slower β + decay enables a bypass. One of the handful of rp process waiting-point nuclides is 64 Ge, which plays a decisive role in matter flow and therefore the produced X-ray flux. Here we report precision measurements of the masses of 63 Ge, 64,65 As and 66,67 Se—the relevant nuclear masses around the waiting-point 64 Ge—and use them as inputs for X-ray burst model calculations. We obtain the X-ray burst light curve to constrain the neutron-star compactness, and suggest that the distance to the X-ray burster GS 1826–24 needs to be increased by about 6.5% to match astronomical observations. The nucleosynthesis results affect the thermal structure of accreting neutron stars, which will subsequently modify the calculations of associated observables.
Improving our representation of convective cell processes requires better quantification of convective clouds throughout their entire life cycle. This includes gaining a clearer understanding of the controls on key convective cloud properties, such as updraft intensity, particle size distributions, rainfall rates, and hydrometeor species. Our inability to improve convective cloud process modeling stems, in part, from a limited understanding of convective cell properties, particularly given how rapidly these storms evolve. This lack of detailed observations in the most intense and organized convective storms is especially significant, as large errors remain in representing these clouds, which are critical for severe weather prediction and Earth system model performance. Cloud and precipitation radars are essential tools for studying cloud microphysics and dynamics, particularly in deeper convective clouds. The recent U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s third Mobile Facility (AMF3) Bankhead National Forest (BNF) deployment provides a unique opportunity to investigate important land–atmosphere interactions, as well as the environmental controls on deep convective cloud processes, in a location favorable for frequent convection. We operate the X/Ka-band Scanning ARM Cloud Radar (X/Ka SACR) using a scan strategy optimized to capture these rapidly evolving clouds and their properties, thereby improving studies of deep convective cloud processes. This effort is strengthened by a complementary and coordinated partnership with ongoing university and multi-agency radar activities collocated in north Alabama—a unique opportunity to examine clouds and precipitation from a lifetime-centric perspective.
RAPIDS II is a simulation-based intelligent tutoring system environment. It is a system for producing computer-based training courses that are built on the foundation of graphical simulations. RAPIDS II simulations can be animated and they can have continuously updating elements.
Two alloy compositions in the Ni-Nb system (Ni60Nb40 and Ni85Nb15) were produced by rapidly quenching from the melt with the piston anvil technique. The Ni60Nb40 was transformed to a metastable, partially crystalline state by heat treatment in a differential scanning calorimeter. The Ni85Nb15 was fully crystalline, with the majority of the grains composed of collections of primary dendrite arms. Both compositions were irradiated with 4 MeV Ni++ ions. The irradiation induced microstructures were examined by transmission electron microscopy and compared with thermally aged samples. The thermal evolution was arrested by ion irradiation in the temperature range studied, by inhibiting the nucleation of the NiNb phase. No irradiation induced voids were observed. It is found that the ion irradiation drives the microstructure along a different path than thermal evolution.
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Strong CO adsorption and facile CO dimerization are the key challenges in electrochemical CO2 reduction towards multi-carbon (C2+) products. We recently showed that CoPc immobilized on a single-walled carbon nanotube can selectively reduce CO2 to methanol. This is enabled through molecular strain, which dramatically improves the CO adsorption energy to CoPc, which in turn facilitates methanol formation. We now examine the extended Phthalocyanine (PcEx) dual atom catalyst (DAC), which is intrinsically strained and contains two catalyst centers, making it a candidate for reducing CO to C2+ products. Using Quantum Mechanics (QM), we screened 20 elements embedded in the PcEx, seeking catalysts with weak hydrogen binding, strong CO binding, and facile CO dimerization. We identi>ied Fe, Ru, Co, and Ir as the best performers and subsequently evaluated the entire CO to C2H4 mechanism (9 steps) using each of these elements as catalysts. In terms of limiting potential and overall exergonicity, we identi>ied CoPcEx as the best catalyst, followed by IrPcEx. We then examined the full CO to C2H4 mechanism on the bimetallic IrCoPcEx catalyst using grand canonical QM to obtain the reaction energetics as a function of applied potential. We conclude that the bimetallic IrCoPcEx is most promising for ef>iciently converting CO to ethylene.
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Model-based optimization for real-time forecasting in unconventional reser-voirs requires novel methods and work?ows since the strategies and work?ows used in conventional reservoirs are either inapplicable, or prohibitively expen-sive and time-consuming. Insu?cient site data and computational expense of high-?delity simulations mean that work?ows with high-?delity simulations are not ideal for usage in comprehensive uncertainty quanti?cation stud-ies that require 1000s of forward model runs. We present an alternative, novel work?ow for unconventional reservoirs, based on the interplay between reduced-order models and machine-learning. Our physics-informed machine-learning (PIML) work?ow addresses the challenges to real-time reservoir management in uncoventionals, namely lack of data (the time-frame for which the wells have been producing), and computational expense of high-?delity modeling. We use the machine-learning paradigm of transfer-learning to bind together fast but less accurate reduced-order models with slow, but accurate high-?delity models and circumvent the di?culties inherent in the current state-of-the-art for unconventionals. Such a PIML work?ow, grounded in physics, is a viable candidate for real-time history matching and production forecasting in a fractured shale gas reservoir. The signi?cance of our approach is that while it is developed for a particu-lar well and site in the Marcelus Shale gas reservoir of the Appalachian basin (MSEEL), it is not wedded to it. We expect the same work?ow can be ap-plied to other shale formations (e.g., Woodford, Barnett, Utica, EagleFord) should site-data become available, using the same set of machine-learning techniques from transfer learning. Some ?ne-tuning (or minimal retraining of the neural networks) will be required to transfer knowledge across shale gas sites/formations but it is a clearly superior alternative to developing a new machine-learning model altogether when considering a di?erent site.
Thick (>20 μm) films of bottlebrush block copolymers self-assemble within minutes of thermal annealing between hard interfaces. Photonic properties are modified by thickness-dependent gradients of grain size and orientation between the surface and bulk.
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