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At least 631 records · Page 35

Validation of Heat Transfer Thermal Decomposition and Container Pressurization of Polyurethane Foam.

Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. In fire environments, gas pressure from thermal decomposition of polymers can cause mechanical failure of sealed systems. In this work, a detailed uncertainty quantification study of PMDI-based polyurethane foam is presented to assess the validity of the computational model. Both experimental measurement uncertainty and model prediction uncertainty are examined and compared. Both the mean value method and Latin hypercube sampling approach are used to propagate the uncertainty through the model. In addition to comparing computational and experimental results, the importance of each input parameter on the simulation result is also investigated. These results show that further development in the physics model of the foam and appropriate associated material testing are necessary to improve model accuracy.

Scott, Sarah Nicole↗

Effect of Impurities on the Compatibility of Steels in Supercritical CO 2 at 450°–650°C

Direct-fired supercritical CO 2 (sCO 2 ) power cycles are a pathway to low-CO 2 fossil energy but contain O 2 and H 2 O in the sCO 2 from combustion. The effect of impurities on structural steels was investigated at 450°-650 °C in 30 MPa sCO 2 . The test matrix included 9 and 12%Cr ferritic-martensitic (FM) steels and conventional and advanced austenitic steels exposed for 1000-2000 h with and without additions of 1%O 2 and 0.1%H 2 O to simulate the cycle after water removal. For FM steels, the mass gains and scale thicknesses were similar with and without impurities with the formation of thick, duplex Fe-rich scales in all cases including the observation that Fe 2 O 3 only formed with 1%O 2 . For the austenitic steels, higher mass gains were observed at all temperatures with increased formation of Fe-rich oxides when impurities were added. Carbon ingress was assessed by bulk combustion analysis, glow discharge optical emission spectroscopy (GDOES) and measuring postexposure room temperature tensile properties. In conclusion, bulk C content was strongly increased at 650 °C but not at 450° or 550 °C.

36 MATERIALS SCIENCE↗

Optimization of an urea decomposition chamber using CFD and VR

Selective Catalytic Reduction (SCR) is an important air pollution control process that consists of injecting ammonia (NH 3 ) into the boiler flue gas and passing the flue gas through a catalyst bed where the NO x and NH 3 react to form nitrogen gas (N 2 ) and water vapor (H 2 O). At a coal-fired power station, a decomposition chamber uses combustion air and a natural gas burner to provide the necessary temperature, air flow and pressure to convert the injected urea solution into ammonia gas. Inspections of this decomposition chamber indicate debris formations occurring at the burner/roof prevent the chamber from achieving proper temperature for conversion and redirect the burner flame/flow, which can potentially shift the flow pattern in the chamber. In order to identify the cause of this debris formation, Computational Fluid Dynamics (CFD) and Virtual Reality (VR) have been employed to simulate and visualize the flow distribution and species concentration inside this decomposition chamber. Furthermore, by analyzing the simulation data, excessive ammonia recirculation have been identified as the cause of the debris formation at the top of the chamber. We have also conduced the parametric studies in order to optimize the existing chamber design by introducing multiple baffles to eliminate the excessive recirculation, thus minimizing debris formation.

42 ENGINEERING↗

Membrane-based Carbon Capture Process Optimization using CFD Modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.

Pedrozo, Hector A.↗

Membrane-based carbon capture process optimization using CFD modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗

Optimization of Membrane-based Carbon Capture using Dimensional Analysis, CFD and Process System Engineering

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibil-ity and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability.To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗

A massively-parallel, unstructured overset method for mesh connectivity

Here we present a method that dynamically and efficiently performs connectivity calculations between many O(10 5 ) moving, unstructured overset meshes in parallel. In order to connect overset meshes, elements exterior to the solution domain must be removed from the simulation. In regions with many overlapping meshes, elements must be selectively removed to reduce redundancy while maintaining a solution over the entire domain. Around masked regions interpolation partner pairing is required between meshes to provide boundary conditions. For general unstructured meshes, these steps involve challenging computational geometry calculations which must be efficient and automatic. For many moving meshes each step must be massively parallelized and scalable to large numbers of computational cores. To establish communication patterns a parallelized master/slave algorithm is used which minimizes global communication and storage. To remove elements a parallel ‘Forest Fire’ flood-fill algorithm is used to set a masking variable. For interpolation partner pairing, and other necessary searches, k-dimensional tree data structures (k-d trees) are extensively used. Often in a calculation, the connectivity between overset meshes remains largely the same between time steps. The temporal coherence of the various objects in the connectivity calculation is directly used to only update necessary information with time, resulting in substantial cost savings. Details of the different algorithms are presented. Resulting connectivity and timings are shown for complex geometries. Parallel scaling is demonstrated for 100,000 spherical particles within a channel up to 492,000 processors.

97 MATHEMATICS AND COMPUTING↗

Biomass Burning Emissions of Black Carbon over the Maritime Continent and ENSO Variability

Fire emissions from the Maritime Continent (MC) over the western tropical Pacific are strongly influenced by El Niño–Southern Oscillation (ENSO), posing various climate effects to the Earth system. Here, in this study, we show that the historical biomass burning emissions of black carbon (BC bb ) aerosol in the dry season from the MC are strengthened in El Niño years due to the dry conditions. The eastern Pacific type of El Niño exerts a stronger modulation in BC bb emissions over the MC region than the central Pacific type of El Niño. Based on simulations using the fully coupled Community Earth System Model (CESM), the impacts of increased BC bb emissions on ENSO variability and frequency are also investigated in this study. With BC bb emissions from the MC scaled up by a factor of 10, which enables the identification of climate response from the internal variability, the increased BC bb heats the local atmosphere and changes land–sea thermal contrast, which suppresses the westward transport of the eastern Pacific surface water. It leads to an increase in sea surface temperature in the eastern tropical Pacific, which further enhances ENSO variability and increases the frequency of extreme El Niño and La Niña events. This study highlights the potential role of BC bb emissions on extreme ENSO frequency, and this role may be increasingly important in the warming future with higher wildfire risks.

54 ENVIRONMENTAL SCIENCES↗

Revealing the Mechanism of Light-Induced Degradation and Regeneration of p-type Cz-Si

The goal of this SIPS project was to develop advanced spectroscopic tools to explore boron- oxygen related defects in p-type Czochralski (Cz) monocrystalline Si (c-Si) to inform processing strategies to permanently suppress these defects and improve cell efficiency. Our work can be divided into three categories: (a) establishment of surface passivation and fast-firing protocols for light induced degradation (LID) and regeneration in p-Cz Si; (b) sample preparation and identification of spectral features for LID and hydrogen in c-Si with vibrational and electron spin resonance (ESR) spectroscopies; (c) demonstration of the interrelation between high-temperature thermal annealing, which breaks nuclei for oxygen precipitates in LID and regeneration. To our knowledge, this is the first study that has identified LID defects using ESR. The magnetic properties of the LID defects will be invaluable in validating the structure of the LID defects through atomistic simulations. The results generated from this project were disseminated through conference presentations and proceedings, and a peer reviewed publication. The tools developed in this project will be used to study other forms of degradation in c-Si including light and elevated-temperature induced degradation in p-type Cz Si and process induced degradation in n-type Cz Si.

14 SOLAR ENERGY↗

Particle Size Distribution and Its Impacts on Ash Deposition and Radiative Transfer during Oxy-Combustion of Rice Husk–Natural Gas

Rice husk (RH) co-combustion with natural gas in highly oxygen-enriched concentrations presents a net carbon-negative energy production opportunity while minimizing flue gas recycling. However, recent experiments have shown enhanced ash deposition rates in oxygen-enriched conditions, with deposition/shedding also being dependent on the particle size distribution (PSD) of the parent RH fuel. To uncover the causative mechanisms behind these observations, add-on models for ash deposition/shedding and radiative properties were employed in computational fluid dynamics simulations. The combustion scenarios investigated encompassed two types of RH (US RH, Chinese RH) with widely varying ash contents (by % mass) and inlet fuel PSD with air and O2/CO2 (70/30 vol %, OXY70) as oxidizers. Utilizing the measured fly-ash PSDs near the deposit surface and modeling the particle viscosity accurately, particle kinetic-energy (PKE)-based capture and shedding criteria were identified as the keys to accurate deposition/shedding rate predictions. The OXY70 scenarios showed higher ash-capturing propensities due to their lower PKE. Conversely, higher erosion rates were predicted in the AIR firing scenarios. In addition, the radiative characteristics across all the scenarios were dominated by the gases and were not sensitive to the fly-ash PSD. Therefore, the higher particle concentrations in the OXY70 conditions did not negatively impact the heat extraction.

Krishnamoorthy, Gautham (ORCID:0000000255205092)↗

Transport of anthropogenic and biomass burning aerosols from Europe to the Arctic during spring 2008

During the POLARCAT-France airborne campaign in April 2008, pollution originating from anthropogenic and biomass burning emissions was measured in the European Arctic. We compare these aircraft measurements with simulations using the WRF-Chem model to investigate model representation of aerosols transported from Europe to the Arctic. Modeled PM 2.5 is evaluated using European Monitoring and Evaluation Programme (EMEP) measurements in source regions and POLARCAT aircraft measurements in the Scandinavian Arctic. Total PM 2.5 agrees well with the measurements, although the model overestimates nitrate and underestimates organic carbon in source regions. Using WRF-Chem in combination with the Lagrangian model FLEXPART-WRF, we find that during the campaign the research aircraft sampled two different types of European plumes: mixed anthropogenic and fire plumes from eastern Europe and Russia transported below 2 km, and anthropogenic plumes from central Europe uplifted by warm conveyor belt circulations to 5–6 km. Both modeled plume types had undergone significant wet scavenging (> 50% PM 10 ) during transport. Modeled aerosol vertical distributions and optical properties below the aircraft are evaluated in the Arctic using airborne lidar measurements. Model results show that the pollution event transported aerosols into the Arctic (> 66.6° N) for a 4-day period. During this 4-day period, biomass burning emissions have the strongest influence on concentrations between 2.5 and 3 km altitudes, while European anthropogenic emissions influence aerosols at both lower (~ 1.5 km) and higher altitudes (~ 4.5 km). As a proportion of PM 2.5 , modeled black carbon and SO 4 = concentrations are more enhanced near the surface in anthropogenic plumes. The European plumes sampled during the POLARCAT-France campaign were transported over the region of springtime snow cover in northern Scandinavia, where they had a significant local atmospheric warming effect. We find that, during this transport event, the average modeled top-of-atmosphere (TOA) shortwave direct and semi-direct radiative effect (DSRE) north of 60° N over snow and ice-covered surfaces reaches +0.58 W m −2 , peaking at +3.3 W m −2 at noon over Scandinavia and Finland.

54 ENVIRONMENTAL SCIENCES↗

Uinta Basin CarbonSAFE II: Storage Complex Feasibility (Final Report)

The primary objective of this CarbonSAFE Phase II project was to establish the technical and commercial feasibility of a commercial-scale CO 2 geological storage complex for Deseret Power Electric Cooperative Bonanza Power Plant and other CO 2 sources in the northeast Uinta Basin, Utah, with the goal to securely store at least 50 million metric tons of captured CO 2 and accelerate CO 2 capture, utilization, and storage (CCUS) deployment. The project team established high-potential technical and commercial feasibility for a storage site within the east Uinta Basin (Utah), in the Cretaceous sandstones (Frontier, Dakota, and Buckhorn), Entrada Sandstone, Nugget Sandstone, and/or Weber Sandstone southwest of the Bonanza coal-fired power plant. This project collected and analyzed state-of-the-art data to characterize the storage complex consistent with Environmental Protection Agency (EPA) permitting standards. The team conducted extensive analog studies, outcrop mapping, and data sampling, which largely contributed to understanding the subsurface lithology and facies. Existing data were obtained and assessed from Utah Division of Oil, Gas, and Mining (DOGM), Utah Geological Survey (UGS), Colorado Geological Survey (CGS), U.S. Geological Survey (USGS), and EPA. These data were analyzed using state-of-the-art CCUS technologies for Societal Considerations, Site Characterization, Modeling and Simulations, Risk Assessment, Management and Monitoring, potential Underground Injection Control (UIC) Class VI Well Permitting, and Technical/Economic Feasibility. Through these high-resolution data collection and feasibility studies, this project was expected to provide a reference for initiating Underground Injection Control (UIC) and other commercial-scale geological storage permitting processes in the Western United States, ultimately contributing to the nation's decarbonization goals through low-risk, cost-effective commercial-scale carbon capture, utilization, and storage (CCUS) projects.

42 ENGINEERING↗

Enabling Technologies for High-Throughput Screening of Nano-Porous Materials: Collaboration with the Nanoporous Materials Genome Center

The overarching goal of this research was to develop new methodologies to enable the accurate and efficient modeling of complex materials using computer simulations. Using inter-molecular interaction energies calculated via an accurate but computationally expensive approach (symmetry-adapted perturbation theory), we parameterized efficient next-generation “force fields” to utilize in subsequent simulations. Since the resulting force fields incorporate much of the relevant physics of inter-molecular interactions, they consequently exhibit high transferability from one material to another. This transferability enables the modeling of a wide range of novel materials without additional computational cost. While this approach is quite general, a particular emphasis of this research involved applications to so-called “metal-organic framework”(MOF) materials relevant to energy-intensive gas separations. We focused specifically on CO 2 /N 2 selectivity, which is a key metric for post combustion CO 2 capture efforts at coal-fired power plants. The gas adsorption capacities and selectivity of the MOFs can be tailored via careful functionalization. We have demonstrated that our force fields exhibit predictive accuracy for a wide variety of functionalized MOFs, thus opening the door for the computational design of “tailored” materials for particular separations. Finally, we have also demonstrated the importance of accounting for the presence of reactive contaminant species when evaluating the performance of MOFs in practical applications.

36 MATERIALS SCIENCE↗

Weak and Strong Connectivity Regimes for a General Time Elapsed Neuron Network Model

For large fully connected neuron networks, we study the dynamics of homogenous assemblies of interacting neurons described by time elapsed models. Under general assumptions on the firing rate which include the ones made in previous works (Pakdaman et al. in Nonlinearity 23(1):55–75, 2010; SIAM J Appl Math 73(3):1260–1279, 2013, Mischler and Weng in Acta Appl Math, 2015), we establish accurate estimate on the long time behavior of the solutions in the weak and the strong connectivity regime both in the case with and without delay. Our results improve (Pakdaman et al. 2010, 2013) where a less accurate estimate was established and Mischler and Weng (2015) where only smooth firing rates were considered. Our approach combines several arguments introduced in the above previous works as well as a slightly refined version of the Weyl’s and spectral mapping theorems presented in Voigt (Monatsh Math 90(2):153–161, 1980) and Mischler and Scher (Ann Inst H Poincaré Anal Non Linéaire 33(3):849–898, 2016).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Binary operations on neuromorphic hardware with application to linear algebraic operations and stochastic equations

Abstract Non-von Neumann computational hardware, based on neuron-inspired, non-linear elements connected via linear, weighted synapses—so-called neuromorphic systems—is a viable computational substrate. Since neuromorphic systems have been shown to use less power than CPUs for many applications, they are of potential use in autonomous systems such as robots, drones, and satellites, for which power resources are at a premium. The power used by neuromorphic systems is approximately proportional to the number of spiking events produced by neurons on-chip. However, typical information encoding on these chips is in the form of firing rates that unarily encode information. That is, the number of spikes generated by a neuron is meant to be proportional to an encoded value used in a computation or algorithm. Unary encoding is less efficient (produces more spikes) than binary encoding. For this reason, here we present neuromorphic computational mechanisms for implementing binary two’s complement operations. We use the mechanisms to construct a neuromorphic, binary matrix multiplication algorithm that may be used as a primitive for linear differential equation integration, deep networks, and other standard calculations. We also construct a random walk circuit and apply it in Brownian motion simulations. We study how both algorithms scale in circuit size and iteration time.

97 MATHEMATICS AND COMPUTING↗

SECARB Initial Injection Period Reservoir Modeling Report

The Southeast Carbon Sequestration Partnership Phase III Anthropogenic Test at Citronelle Field is the United States’ largest CO 2 capture and transportation, injection, storage and monitoring project using CO 2 derived from a coal-fired power station. The project represents a U.S. Department of Energy research and development initiative designed to demonstrate deep underground injection and containment of 100,000 tonnes or more of anthropogenic-source CO 2 . A series of reservoir modeling runs will be performed during the pre-injection, injection, and post-injection phases of the project and will be used to predict plume migration and areal extent. Pressure, temperature, and downhole measurements (seismic, fluid and logging), all data collected as a part of the monitoring program, are utilized as reservoir performance parameters to tune the existing geophysical and geochemical simulation models. The ability to represent site injection activities with the produced detailed simulation models lend credence to long-term forecasts of CO 2 fate and the progress of the CO 2 plume. This report provides an assessment of the simulation model results for CO 2 injection at the Citronelle Anthropogenic Test site from the period of August 20, 2012 to August 31, 2013.

01 COAL, LIGNITE, AND PEAT↗

SECARB Second Injection Period Reservoir Modeling Report

The Southeast Carbon Sequestration Partnership Phase III Anthropogenic Test at Citronelle Field is the United States’ largest CO 2 capture and transportation, injection, storage and monitoring project using CO 2 derived from a coal-fired power station. The project represents a U.S. Department of Energy research and development initiative designed to demonstrate deep underground injection and containment of 100,000 tonnes or more of anthropogenic-source CO 2 . A series of reservoir modeling runs will be performed during the pre-injection, injection, and post-injection phases of the project and will be used to predict plume migration and areal extent. Pressure, temperature, and downhole measurements (seismic, fluid and logging), all data collected as a part of the monitoring program, are utilized as reservoir performance parameters to tune the existing geophysical and geochemical simulation models.

01 COAL, LIGNITE, AND PEAT↗