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At least 1,657 records · Page 92

High-Speed Quantification of Pore-Scale Multiphase Flow of Water and Supercritical CO 2 in 2-D Heterogeneous Porous Micromodels: Flow Regimes and Interface Dynamics

The pore-scale flow of CO 2 and water in 2-D heterogeneous porous micromodels over a Ca range of nearly three orders of magnitude was explored experimentally. The porous geometry is a close reprint of real sandstone, and the experiments were performed under reservoir-relevant conditions (i.e., 8 MPa and 21°C), thus ensuring relevance to practical CO 2 operations. High-speed fluorescent microscopy and image processing were employed to achieve temporally and spatially resolved data, providing a unique view of the dynamics underlying this multiphase flow scenario. Under conditions relevant to CO 2 sequestration, final CO 2 saturation was found to decrease and increase logarithmically with Ca within the capillary and viscous-fingering regimes, respectively, with a minimum occurring during regime crossover. Specific interfacial length generally scales linearly with CO 2 saturation, with higher slopes noted at high Ca due to stronger viscous and inertial forces, as supported by direct pore-scale observations. Additionally, statistical analysis of the interfacial movements revealed that pore-scale events are controlled by their intrinsic dynamics at low Ca, but overrun by the bulk flow at high Ca. During postfront flow, while permeability is typically correlated with total CO 2 saturation in the porous domain (regardless of its mobility), the saturation of active CO 2 pathways in the current study correlated very well with permeability. This alternate approach to characterize relative permeability could serve to mitigate hysteresis in relative permeability curves. Taken together, these results provide unique insights that address inconsistent observations in the literature and previously unanswered questions about the underlying flow dynamics of this important multiphase flow scenario.

42 ENGINEERING↗

CORRLA-RS

The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.

Gurecky, William [Oak Ridge National Laboratory (O↗

Comet P/Halley - Spatial distributions and scale lengths for C2, CN, NH2, and H2O

Long-slit spectroscopic observations of Comet P/Halley on 12 dates between October 1985 and May 1986 were used to extract spatial profiles for C2, CN, NH2, and O I (1D) (which effectively map out the comet's H2O distribution), and Haser model scale lengths were fitted to these data. The preperihelion analysis yielded Haser model scale lengths of sufficient consistency that they could be used for the production rate determinations. It was found that the average parent scale lengths found for NH2 were consistent with photodissociation lifetimes for NH3 and confirm the dissociation chain NH3-NH2-NH.

Fink, Uwe↗

Another collision for the Coma cluster

The wavelet transform analysis of the Rosat position sensitive proportional counter (PSPC) images of the Coma cluster are presented. The analysis shows, on small scales, a substructure dominated by two extended sources surrounding the two bright clusters NGC 4874 and NGC 4889. On scales of about 2 arcmin to 3 arcmin, the analysis reveals a tail of X-ray emission originating near the cluster center, curving to the south and east for approximately 25 arcmin and ending near the galaxy NGC 4911. The results are interpreted in terms of a merger of a group, having a core mass of approximately 10(exp 13) solar mass, with the main body of the Coma cluster.

Vikhlinin, A.↗

Introduction to Big Earth Data Applications

Climate and weather modeling generate enormous volumes that make iterative analysis challenging, spurring the development of new ways to work with the data. A theme going across applications is the need to identify and highlight "interesting" data for the scientist to focus on. Operational applications often scale up from small, local studies to larger spatial scales with more analysis targets.

parallel processing (computers)↗

Nano-hybrids; the effect of turbine efficiency on fuel cell-turbine hybrid performance

A systems analysis was conducted to evaluate the effects of hybrid scale on overall performance. The benchmark was the highly efficient turbine in a 550 MW hybrid power system. This was compared to a nano-hybrid system of 20 kW with reduced isentropic efficiencies for the smaller scale turbomachinery. Electrical efficiency was remarkably high even with the small inefficient turbomachinery. The SOFC share of the power was a low 68% for a fixed SOFC fuel utilization (Uf) of 0.7.

01 COAL, LIGNITE, AND PEAT↗

Fragmentation Prediction for a Brittle Ceramic: An Integrated Two-Scale Model Approach

A new implementation of a multi-scale fragmentation model is introduced that combines existing independent macro and micro-scale models into a single material model within the Library of Advanced Materials for Engineering (LAME) that can be used directly by the finite element structural mechanics code SIERRA/SM, developed at Sandia National Laboratories. The implementation not only joins existing independent fragmentation models into a single framework, but also enables further development by virtue of being integrated into SIERRA/SM. Integration with a finite element structural mechanics code for a true two-way coupling of the fragmentation models that were previously independent. Hereafter, the prior implementation will be referred to as the sequentially applied fragmentation model. In contrast, the newly developed model will be called the integrated two-scale model. The sequentially applied fragmentation model consists of two independent models applied sequentially to account for the macro-scale and microscale fragmentation. The macro-scale fragmentation behavior is calculated using an elastic gradient damage explicit material model developed to model fracture in brittle materials. The micro-scale fragmentation model is an implementation of the 1D cohesive-zone model developed by Zhou, et al. The micro-scale model is implemented by post-processing the macro-scale data that provides initial conditions for the 1D analysis. The micro-scale model is necessary to predict the resulting fragment size distribution at length scales inaccessible to the finite element based macro-scale model. The full range of fragmentation behavior is then predicted by combining the results from the two independent models. The sequentially applied fragmentation model was used to predict the fragments that result from impact loading of a brittle material, which in that case was a ceramic cylinder of commercial UO{sub 2} nuclear fuel. Understanding the fragmentation behavior of such materials is important for evaluating the risk of airborne particulate release under impact loading scenarios. This work will verify the implementation of the integrated two-scale model using the same experiment modeled by the existing sequentially applied model. The purpose of this manuscript is to introduce the new integrated two-scale fragmentation model and validate the implementation against the existing sequentially applied model for a specific case of impact loading of a brittle material. This validation case will not fully utilize the benefits of having the model integrated into the finite element code as a material model. Rather, this study will demonstrate consistency between the two fragmentation models to ensure that the success of the sequentially applied model will be duplicated by the integrated two-scale approach. Once validated, further development of the model can be made by utilizing the integration into the finite element code to create a fully two-way coupled fragmentation model that will be extended to include higher fidelity models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Real-Time Coupling of Geographically Distributed Research Infrastructures: Taxonomy, Overview, and Real-World Smart Grid Applications

Novel concepts enabling a resilient future power system and their subsequent experimental evaluation are experiencing a steadily growing challenge: large scale complexity and questionable scalability. The requirements on a research infrastructure (RI) to cope with the trends of such a dynamic system therefore grow in size, diversity and costs, making the feasibility of rigorous advancements questionable by a single RI. Analysis of large scale system complexity has been made possible by the real-time coupling of geographically separated RIs undertaking geographically distributed simulations (GDS), the concept of which brings the equipment, models and expertise of independent RIs, in combination, to optimally address the challenge. This article presents the outputs of IEEE PES Task Force on Interfacing Techniques for Simulation Tools towards standardization of GDS as a concept. First, the taxonomy for setups utilized for GDS is established followed by a comprehensive overview of the advancements in real-time couplings reported in literature. The overview encompasses fundamental technological design considerations for GDS. The article further presents four application oriented case studies (real-world implementations) where GDS setups have been utilized, demonstrating their practicality and potential in enabling the analysis of future complex power systems.

distributed laboratories↗

Numerical Analysis of Combustion Dynamics in a Full-Scale Rotating Detonation Rocket Engine using Large Eddy Simulations

Large eddy simulations (LES) using detailed chemistry and leveraging adaptive mesh refinement (AMR) are performed to gain insights into the combustion dynamics within a full-scale methane-oxygen non-premixed rotating detonation rocket engine (RDRE) employing impinging discrete injection schemes. In particular, a comparative analysis of two operating conditions corresponding to the same global equivalence ratio but different mass flow rates is carried out to investigate the resultant impact on detonation wave characteristics and RDRE global performance. Multiple co-rotating detonation waves with spatially-distributed wave structure and preferential alignment with the inner wall of the annulus (due to asymmetry in fuel distribution) are encountered under both conditions. Both cases exhibit pre-detonation deflagrative burning in the fill region, while one of the cases shows higher susceptibility to backflow into the feed plenums due to lower plenum pressures. Furthermore, heat release analysis shows that the thrust obtained from the RDRE is closely linked to the distribution of total heat release between detonative and deflagrative combustion. On the other hand, combustion efficiency is associated with the fraction of heat release occurring in fuel-rich versus fuel-lean regions within the RDRE.

33 ADVANCED PROPULSION SYSTEMS↗

Designing for Maintainability and System Availability

The final goal for a delivered system (whether a car, aircraft, avionics box or computer) should be its availability to operate and perform its intended function over its expected design life. Hence, in designing a system, we cannot think in terms of delivering the system and just walking away. The system supplier needs to provide support throughout the operating life of the product. Here, supportability requires an effective combination of reliability, maintainability, logistics and operations engineering (as well as safety engineering) to have a system that is available for its intended use throughout its designated mission lifetime. Maintainability is a key driving element in the effective support and upkeep of the system as well as providing the ability to modify and upgrade the system throughout its lifetime. This paper then, will concentrate on maintainability and its integration into the system engineering and design process. The topics to be covered include elements of maintainability, the total cost of ownership, how system availability, maintenance and logistics costs and spare parts cost effect the overall program costs. System analysis and maintainability will show how maintainability fits into the overall systems approach to project development. Maintainability processes and documents will focus on how maintainability is to be performed and what documents are typically generated for a large scale program. Maintainability analysis shows how trade-offs can be performed for various alternative components. The conclusions summarize the paper and are followed by specific problems for hands-on training.

Lalli, Vincent R.↗

Boosting Big National Lab Data

Introduction: Big data. Love it or hate it, solving the world’s most intractable problems requires the ability to make sense of huge and complex sets of data and do it quickly. Speeding up the process – from hours to minutes or from weeks to days – is key to our success. One major source of such big data are physical experiments. As many will know, these physical experiments are commonly used to solve challenges in fields such as energy security, manufacturing, medicine, pharmacology, environmental protection and national security. Experiments use different instruments and sensor types to research for example the validity of new drugs, the base cause for diseases, more efficient energy sources, new materials for every day goods, effective methods for environmental cleanup, the optimal ingredients composition for chocolate or determine how to preserve valuable antics. This is done by experimentally determining the structure, properties and processes that govern biological systems, chemical processes and materials. The speed and quality at which we can acquire new insights from experiments directly influences the rate of scientific progress, industrial innovation and competitiveness. And gaining new groundbreaking insights, faster, is key to the economic success of our nations. Recent years have seen incredible advances in sensor technologies, from house size detector systems in large experiments such as the Large Hadron Collider and the ‘Eye of Gaia’ billion pixel camera detector to high throughput genome sequencing. These developments have led to an exponential increase in data volumes, rates and variety produced by instruments used for experimental work. This increase is coinciding with a need to analyze the experimental results at the time they are collected. This speed is required to optimize the data taking and quality, and also to enable new adaptive experiments, where the sample is manipulated as it is observed, e.g. a substance is injected into a tissue sample and the gradual effect is observed as more of the substance is injected, providing better insights into the natural processes that are occurring, as well as result driven sampling adjustment to capture particularly interesting features --- as they emerge. The Department of Energy’s Pacific Northwest National Laboratory (PNNL) is recognized for it’s expertise in the development of new measurement techniques and their application to challenges of national importance. So it was obvious to us to address the need for in-situ analysis of large scale experimental data. We have a wide range of experimental instruments on site, in facilities such as DOE’s national scientific user facility, the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). Commonly, scientists would create an individual analysis pipeline for each of those instruments; but even the same type of instrument would not necessarily share the same analysis tools. With the rapid increase of data volumes and rates we were facing two key challenges: how to bring a wider set of capabilities to bear to achieve in-situ analysis, and how to do so across a wide range of heterogeneous instruments at affordable costs and in a reasonable timeframe. We decided to take an unconventional approach to the problem, rather than developing customized, one-off solutions for specific instruments we wanted to explore if a more common solution could be found that would go beyond shared, basic infrastructures such as data movement and workflow engines.

97 MATHEMATICS AND COMPUTING↗

SCALE modeling of foil irradiations at WSU’s TRIGA with sensitivity/uncertainty analysis

We report the Washington State University TRIGA reactor was modeled in the SCALE system’s KENO neutron transport code. The model includes 119 fuel rods, a central boral control rod, 4 control blades, 5 irradiation ports, and 20 graphite reflector blocks within a rectangular aluminum grid box. The model accurately simulated the irradiation of depleted uranium and highly enriched uranium foils and predicted reaction rate ratios for 238 U(n,2n) 237 U / 238 U(n,γ) 239 U and 99 Mo / fission, which compared favorably to empirical values previously measured at Los Alamos. Finally, a sensitivity/uncertainty analysis was performed using the continuous-energy TSUNAMI-3D module of SCALE.

237Np↗

Genome-Scale 13 C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae .

Synthetic biology is a rapidly developing field that pursues the application of engineering principles and development approaches to biological engineering. Synthetic biology is poised to change the way biology is practiced, and has important practical applications: for example, building genetically engineered organisms to produce biofuels, medicines, and other chemicals. Traditionally, synthetic biology has focused on manipulating a few genes (e.g., in a single pathway or genetic circuit), but its combination with systems biology holds the promise of creating new cellular architectures and constructing complex biological systems from the ground up. Enabling this merge of synthetic and systems biology will require greater predictive capability for modeling the behavior of cellular systems, and more comprehensive data sets for building and calibrating these models. The so-called "-omics" data sets can now be generated via high throughput techniques in the form of genomic, proteomic, transcriptomic, and metabolomic information on the engineered biological system. Of particular interest with respect to the engineering of microbes capable of producing biofuels and other chemicals economically and at scale are metabolomic datasets, and their insights into intracellular metabolic fluxes. Metabolic fluxes provide a rapid and easy to understand picture of how carbon and energy flow throughout the cell. Furthermore, we present a detailed guide to performing metabolic flux analysis and modeling using the open source JBEI Quantitative Metabolic Modeling (jQMM) library. This library allows the user to transform metabolomics data in the form of isotope labeling data from a 13 C labeling experiment into a determination of cellular fluxes that can be used to develop genetic engineering strategies for metabolic engineering.The jQMM library presents a complete toolbox for performing a range of different tasks of interest in metabolic engineering. Various different types of flux analysis and modeling can be performed such as flux balance analysis, 13 C metabolic flux analysis, and two-scale 13 C metabolic flux analysis (2S- 13 C MFA). 2S- 13 C MFA is a novel method that determines genome-scale fluxes without the need of every single carbon transition in the metabolic network. In addition to several other capabilities, the jQMM library can make model based predictions for how various genetic engineering strategies can be incorporated toward bioengineering goals: it can predict the effects of reaction knockouts on metabolism using both the MoMA and ROOM methodologies. In this chapter, we will illustrate the use of the jQMM library through a step-by-step demonstration of flux determination and knockout prediction in a complex eukaryotic model organism: Saccharomyces cerevisiae ( S. cerevisiae ). Included with this chapter is a digital Jupyter Notebook file that provides a computable appendix showing a self-contained example of jQMM usage, which can be changed to fit the user's specific needs. As an open source software project, users can modify and extend the code base to make improvements at will, allowing them to share their development work and contribute back to the jQMM modeling community.

-Omics data↗

Introduction to Big Earth Data Applications

Climate and weather modeling generate enormous volumes that make iterative analysis challenging, spurring the development of new ways to work with the data. At the same time in the Earth Observation area, technology advances are enabling new sensors and satellites that will increase data volume, velocity and application variety. Scaling up can also be seen when operational applications expand from small, local studies to larger spatial scales with more analysis targets.

Christopher Lynnes↗

Scaling of the beam-plasma discharge

A theoretical analysis is presented of the scaling of the critical beam current required for ignition and the narrow band emissions observed for beam currents less than critical in a beam plasma discharge experiment. The theory of the two-stream interaction between a nonrelativistic cold electron beam and a plasma in the presence of a magnetic field is developed, and conditions for the two-stream instability and the resulting amplification are derived. It is shown that the experimentally observed scaling is consistent with the assumption that the ignition triggering occurs when an instability near the electron plasma frequency is excited. Finally, it is shown that the wave emissions observed in the subthreshold range can be explained by the excitation of the kinetic instability of the upper branch and convective saturation.

Rowland, H. L.↗

Hot Spots and Persistence of Nitrate in Aquifers Across Scales

Here, nitrate-N (NO 3 - - N) is one of the most pervasive contaminants in groundwater. Nitrate in groundwater exhibits long-term behavior due to complex interactions at multiple scales among various geophysical factors, such as sources of nitrate-N, characteristics of the vadose zone and aquifer attributes. To minimize contamination of nitrate-N in groundwater, it is important to estimate hot spots (>10 mg/L of NO 3 - - N), trends and persistence of nitrate-N in groundwater. To analyze the trends and persistence of nitrate-N in groundwater at multiple spatio-temporal scales, we developed and used an entropy-based method along with the Hurst exponent in two different hydrogeologic settings: The Trinity and Ogallala Aquifers in Texas at fine (2 km × 2 km), intermediate (10 km × 10 km) and coarse (100 km × 100 km) scales. Results show that nitrate-N exhibits long-term persistence at the intermediate and coarse scales. In the Trinity Aquifer, overall mean nitrate-N has declined with a slight increase in normalized marginal entropy (NME) over each decade from 1940 to 2008; however, the number of hot spots has increased over time. In the Ogallala Aquifer, overall mean nitrate-N has increased with slight moderation in NME since 1940; however, the number of hot spots has significantly decreased for the same period at all scales.

58 GEOSCIENCES↗

Analysis of fission gas release in LWR fuel using the BISON code

Recent advances in the development of the finite-element based, multidimensional fuel performance code BISON of Idaho National Laboratory are presented. Specifically, the development, implementation and testing of a new model for the analysis of fission gas behavior in LWR-UO2 fuel during irradiation are summarized. While retaining a physics-based description of the relevant mechanisms, the model is characterized by a level of complexity suitable for application to engineering-scale nuclear fuel analysis and consistent with the uncertainties pertaining to some parameters. The treatment includes the fundamental features of fission gas behavior, among which are gas diffusion and precipitation in fuel grains, growth and coalescence of gas bubbles at grain faces, grain growth and grain boundary sweeping effects, thermal, athermal, and transient gas release. The BISON code incorporating the new model is applied to the simulation of irradiation experiments from the OECD/NEA International Fuel Performance Experiments database, also included in the IAEA coordinated research projects FUMEX-II and FUMEX-III. The comparison of the results with the available experimental data at moderate burn-up is presented, pointing out an encouraging predictive accuracy, without any fitting applied to the model parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sea Level Rise Impacts on Wastewater Treatment Systems Along the U.S. Coasts

As sea levels rise, coastal communities will experience more frequent and persistent nuisance flooding, and some low-lying areas may be permanently inundated. Critical components of lifeline infrastructure networks in these areas are also at risk of flooding, which could cause significant service disruptions that extend beyond the flooded zone. Thus, identifying critical infrastructure components that are exposed to sea level rise is an important first step in developing targeted investment in protective actions and enhancing the overall resilience of coastal communities. Wastewater treatment plants are typically located at low elevations near the coastline to minimize the cost of collecting consumed water and discharging treated effluent, which makes them particularly susceptible to coastal flooding. For this analysis, we used geographic information systems to assess the exposure of wastewater infrastructure to various sea level rise projections at the national level. We then estimated the number of people who would lose wastewater services, which could be more than five times as high as previous predictions of the number of people at risk of direct flooding due to sea level rise. We also performed a regional comparison of wastewater exposure to marine and groundwater flooding in the San Francisco Bay Area. Overall, this analysis highlights the widespread exposure of wastewater infrastructure in the United States and demonstrates that local disruptions to infrastructure networks may have far-ranging impacts on areas that do not experience direct flooding.Plain Language Summary Wastewater treatment plants are susceptible to flooding resulting from sea level rise. Previous estimates of wastewater exposure have only considered the impacts of marine flooding at the local or regional scale. In this analysis, we quantify the exposure to marine flooding across the coastal United States and then consider the relative impacts of marine and groundwater flooding at the regional scale in the San Francisco Bay Area. We also estimate the number of people who may lose access to wastewater services if no actions are taken to prevent flooding at wastewater treatment plants. We find that the number of people impacted by sea level rise due to loss of wastewater services could be five times as high as previous predictions of the number of people who experience direct flooding of their homes or property. We also find that groundwater flooding poses a significant threat to wastewater plants in the San Francisco Bay region.

54 ENVIRONMENTAL SCIENCES↗