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At least 433 records · Page 24

Liquid lithium applications for solving challenging fusion reactor issues and NSTX-U contributions

Steady-state fusion reactor operation presents major divertor technology challenges, including high divertor heat flux both steady-state and transients. In addition to those issues, there are unresolved issues of long term dust accumulation and associated tritium inventory and safety issues. It has been suggested that radiative liquid lithium divertor concepts with a modest lithium-loop could provide a possible solution for these outstanding fusion reactor technology issues while potentially improving the reactor plasma performance. The application of lithium (Li) in NSTX resulted in improved H-mode confinement, H-mode power threshold reduction, and reduction in the divertor peak heat flux while maintaining essentially Li-free core plasma operation even during H-modes. These promising results in NSTX and related modeling calculations motivated the radiative liquid lithium divertor (RLLD) concept and its variant, the active liquid lithium divertor concept (ARLLD), taking advantage of the enhanced Li radiation in relatively poorly confined divertor plasmas. It was estimated that only a few moles/sec of lithium injection would be needed to significantly reduce the divertor heat flux in a tokamak fusion power plant. By operating at lower temperatures ≤ 500°C than the first wall ~ 600 – 700°C, the LL-covered divertor chamber wall surfaces can serve as an effective particle pump, as impurities generally migrate toward lower temperature LL divertor surfaces. To maintain the LL purity, a closed LL loop system with a modest circulating capacity of ~ 1 liter/second (l/sec) is envisioned to sustain the steady-state operation of a 1 GW-electric class fusion power plant. By running the Li loop continuously, it can carry the dust particles and impurities generated in the vacuum vessel to outside where the dust / impurities are removed by relatively simple filter and cold/hot trap systems. Using a cold trap system, it can recover in tritium (T) in real time from LL at a rate of ~ 0.5 g / sec needed to sustain the fusion reaction while minimizing the T inventory issue. With an expected T fraction of ≤ 0.7 %, an acceptable level of T inventory can be achieved. In NSTX-U, preparations are now underway to elucidate the physics of Li plasma interactions with a number of Li application tools and Li radiation spectroscopic instruments. The NSTX-U Li evaporator which provides Li coating over the lower divertor plate, can offer important information on the RLLD concept, and the Li granule injector will test some of the key physics issue on the ARLLD concept. A LL-loop is also being prepared off line for prototyping future use on NSTX-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inference of Rock Flow and Mechanical Properties from Injection-Induced Microseismic Events During Geologic CO 2 Storage

Monitoring microseismic activities during CO 2 injection into geologic formations is important for ensuring the safety of the storage operations. The resulting data provide insight into the response of the storage formation to CO 2 injection and can be used to infer the underlying rock flow and mechanical properties. In this paper, assimilation of microseismic data is performed for dynamic characterization of the storage formation by using a stochastic simulation model to forecast the microseismic response of a geologic formation during CO 2 injection. Two modeling approaches are adopted to predict the space-time distribution of the injection-induced microseismicity. The first model is based on pore pressure relaxation assumption, while the second model uses coupled flow and geomechanics simulation to establish the complex physical relation between the storage formation properties and the corresponding microseismic responses during CO 2 injection. The stochastic predictive models in each case are used in ensemble data assimilation frameworks to estimate rock properties from the observed microseismic data. Two data assimilation methods are considered: (i) a new ensemble-based stochastic point process filter (EnPPF) that can directly integrate discrete microseismic events, and (ii) a variant of ensemble smoother, known as the ensemble smoother with multiple data assimilation (ES-MDA), which requires continuous representation of microseismic events for assimilation. The two methods are successfully applied to a geologically realistic model of the Farnsworth Field in Texas, with complex geologic flow units and interacting fault systems.

42 ENGINEERING↗

Empirical Validation of UBEM: An Assessment of Bias in Urban Building Energy Modeling for Chicago

Residential and commercial buildings currently account for 30% of total global final energy consumption. Urban-scale building energy modeling (UBEM) can enable scalable investments and unlock building improvements by quantifying energy, demand, emissions, and cost reductions of specific measures or packages for building-specific technologies in large geographic regions. While the sophistication of UBEM data sources and technologies have increased dramatically in the past decade, there remains a knowledge gap for empirical validation and sources of bias between building-specific energy models and measured data at varying geographic scales.As UBEM continues to develop, systemic analysis of accuracy, bias, and limitations of the resulting models is necessary to inform best practices and move toward standardization. These are characterized for the Automatic Building Energy Modeling (AutoBEM) software suite with an initial case study involving metered electricity consumption data from 247,188 buildings in Chicago, Illinois, USA - averaged across years 2019-2021 - compared to the following datasets: (1) the AutoBEM-generated nation-scale Model America version 2 (MAv2) data for 596,064 buildings, (2) tax assessor data for 579,829 buildings, (3) tax assessor data filled with MAv2, and (4) 102 representative dynamic archetypes. The accuracy is reported for every building type and vintage combination, along with multiple sources of bias for unique building descriptors. The AutoBEM simulation workflow produced energy consumption estimates that closely match aggregated metered electricity consumption data for different types of buildings constructed during various time periods at the city scale - with initial normalized mean bias error of 10.9%, and 1.1% after removing outliers. Contribution of statistically significant factors including building type, land use, age, and size to variance in UBEM bias is quantified.

Garg, Ankur↗

Merged and Gridded GPM and Atmospheric River Data Product

The Global Precipitation Measurement (GPM) Mission Core Observatory satellite launched in 2014 as a joint mission between National Aeronautics and Space Administration (NASA) and JAXA. Global Precipitation Measurement (GPM) has, since that time, provided continuous, valuable dual-frequency radar and passive microwave radiometer observations. Here, we introduce a gridded data set of collocated GPM Core Observatory observational products merged with a reanalysis-derived Atmospheric river (AR) data set in the North Atlantic and North Pacific sectors. The three data sets that are merged and gridded are: (a) the NASA Goddard Profiling (GPROF) precipitation product, which uses GPM passive microwave radiometer observations to derive surface precipitation rates, (b) a water vapor data product derived from the GPM Core Observatory radiometer, provided by Remote Sensing Systems (RSS), and (c) the Mattingly et al. (2018, https://doi.org/10.1029/2018jd028714) AR data set that is specifically tuned to the high-latitude regions. This novel merged data set spans from May 2014 to December 2022 with plans to update annually through 2026 at minimum. This gridded product combines RSS passive water vapor and precipitation estimates with coincident AR detection. This data product benefits the scientific community by providing (a) user-friendly gridded satellite data compared to standard satellite data sets, while maintaining high temporal resolution, and (b) coincident satellite observations to assess the link between ARs and precipitation.

Marian E Mateling↗

Data-driven Alignment of the Tracker for the Mu2e Experiment

An alignment of the Mu2e Tracker is investigated using the Mu2e Offline Software and Millepede-II. Simulated misalignments of Tracker planes were inserted between Monte-Carlo event generation and before reconstruction using randomly generated $(x,y,z)$-translations and rotations of the rigid-body planes in the detector model. Cosmic ray muons, with no magnetic field present in the Detector Solenoid, will follow a straight-line trajectory. A maximum-likelihood fit is used to reconstruct a track and determine its parameters. Tracks traversing at least four planes, with ten registered straw hits, and a maximum time residual of $20$ ns are selected to be used in an alignment sample. The cuts were chosen to discard tracks with low information content, such as those with high levels of multiple scattering or those with low numbers of measurements contributing to a single track fit. Millepede-II produces the resulting alignment constants according to a simultaneous least-squares fit of the alignment parameters and the track parameters for all input tracks. The improved alignment constants are used to repeat the process and recover an increased number of suitable tracks, further improving the estimate of the alignment constants in subsequent iterations. A performance study of the process was conducted on a misaligned Tracker in the case of translation-only, and translation plus rotational misalignments. In both cases, the correct alignment constants were recovered to within statistical error after three global fit iterations. Additionally, a continuous integration system was developed for the \texttt{Mu2e/Offline} GitHub repository, introducing a convenient automated testing process for all proposed changes (``pull requests"). The tests developed included a full build of the software, followed by tests of the validation routines, geometry overlap checking, and multi-threading mode. Additionally, code quality checks and low-statistics physics comparison checks a re also available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ERS-1 SAR data processing

To take full advantage of the synthetic aperature radar (SAR) to be flown on board the European Space Agency's Remote Sensing Satellite (ERS-1) (1989) and the Canadian Radarsat (1990), the implementation of a receiving station in Alaska is being studied to gather and process SAR data pertaining in particular to regions within the station's range of reception. The current SAR data processing requirement is estimated to be on the order of 5 minutes per day. The Interim Digital Sar Processor (IDP) which was under continual development through Seasat (1978) and SIR-B (1984) can process slightly more than 2 minutes of ERS-1 data per day. On the other hand, the Advanced Digital SAR Processore (ADSP), currently under development for the Shuttle Imaging Radar C (SIR-C, 1988) and the Venus Radar Mapper, (VMR, 1988), is capable of processing ERS-1 SAR data at a real time rate. To better suit the anticipated ERS-1 SAR data processing requirement, both a modified IDP and an ADSP derivative are being examined. For the modified IDP, a pipelined architecture is proposed for the mini-computer plus array processor arrangement to improve throughout. For the ADSP derivative, a simplified version is proposed to enhance ease of implementation and maintainability while maintaing real time throughput rates. These processing systems are discussed and evaluated.

Leung, K.↗

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.

Hou, Arthur Y.↗

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Scattered data interpolation is a problem of interest in numerous areas such as electronic imaging, smooth surface modeling, and computational geometry. Our motivation arises from applications in geology and mining, which often involve large scattered data sets and a demand for high accuracy. The method of choice is ordinary kriging. This is because it is a best unbiased estimator. Unfortunately, this interpolant is computationally very expensive to compute exactly. For n scattered data points, computing the value of a single interpolant involves solving a dense linear system of size roughly n x n. This is infeasible for large n. In practice, kriging is solved approximately by local approaches that are based on considering only a relatively small'number of points that lie close to the query point. There are many problems with this local approach, however. The first is that determining the proper neighborhood size is tricky, and is usually solved by ad hoc methods such as selecting a fixed number of nearest neighbors or all the points lying within a fixed radius. Such fixed neighborhood sizes may not work well for all query points, depending on local density of the point distribution. Local methods also suffer from the problem that the resulting interpolant is not continuous. Meyer showed that while kriging produces smooth continues surfaces, it has zero order continuity along its borders. Thus, at interface boundaries where the neighborhood changes, the interpolant behaves discontinuously. Therefore, it is important to consider and solve the global system for each interpolant. However, solving such large dense systems for each query point is impractical. Recently a more principled approach to approximating kriging has been proposed based on a technique called covariance tapering. The problems arise from the fact that the covariance functions that are used in kriging have global support. Our implementations combine, utilize, and enhance a number of different approaches that have been introduced in literature for solving large linear systems for interpolation of scattered data points. For very large systems, exact methods such as Gaussian elimination are impractical since they require 0(n(exp 3)) time and 0(n(exp 2)) storage. As Billings et al. suggested, we use an iterative approach. In particular, we use the SYMMLQ method, for solving the large but sparse ordinary kriging systems that result from tapering. The main technical issue that need to be overcome in our algorithmic solution is that the points' covariance matrix for kriging should be symmetric positive definite. The goal of tapering is to obtain a sparse approximate representation of the covariance matrix while maintaining its positive definiteness. Furrer et al. used tapering to obtain a sparse linear system of the form Ax = b, where A is the tapered symmetric positive definite covariance matrix. Thus, Cholesky factorization could be used to solve their linear systems. They implemented an efficient sparse Cholesky decomposition method. They also showed if these tapers are used for a limited class of covariance models, the solution of the system converges to the solution of the original system. Matrix A in the ordinary kriging system, while symmetric, is not positive definite. Thus, their approach is not applicable to the ordinary kriging system. Therefore, we use tapering only to obtain a sparse linear system. Then, we use SYMMLQ to solve the ordinary kriging system. We show that solving large kriging systems becomes practical via tapering and iterative methods, and results in lower estimation errors compared to traditional local approaches, and significant memory savings compared to the original global system. We also developed a more efficient variant of the sparse SYMMLQ method for large ordinary kriging systems. This approach adaptively finds the correct local neighborhood for each query point in the interpolation process.

Memarsadeghi, Nargess↗

Iodobutane Deep Bed Adsorption Test Report

The Department of Energy (DOE) Nuclear Technology Research and Development (NTRD) Program Material Recovery and Waste Form Development (MRWFD) Campaign Off-gas Sigma Team has supported research and development on iodine control and iodine waste forms for the past several years. As a part of this on-going research, two deep-bed iodobutane adsorption tests have been performed with higher NO x levels. High (>1,000) iodine decontamination factors (DFs, the ratios of the inlet iodine concentrations divided by the outlet iodine concentrations, when the gas flowrate is constant) were achieved with both the silver aerogel and silver zeolite sorbents. The iodine adsorption mass transfer zone (the depth of the sorbent bed in which adsorption is occurring at any specific time) for these tests was estimated at 4 inches for both sorbents under the test conditions. Silver utilization for silver aerogel sorbent reached 41% (up to 12 g adsorbed iodine per 100 g silver aerogel sorbent), while silver utilization reached 43% (up to 6.8 g adsorbed iodine per 100 g silver zeolite sorbent). These values are generally consistent with results for prior methyl iodide adsorption tests. The results also indicate that, during iodine adsorption process, the organic iodide molecule decomposes so that the iodine can be adsorbed. Even when sorbent breakthrough is reached, the organic iodide molecule continues to decompose; and the unadsorbed iodine that passes through bed is no longer in the form of the original organic iodide; but in the form of iodine compounds that are soluble in NaOH solutions, such as HI or I 2 . This research and development has included iodine adsorption tests using a laboratory-scale test system containing segmented fixed beds of iodine adsorbents in series. Non-radioactive synthetic gas mixtures were blended from air, nitrogen, NO, NO 2 , water, and the target iodine compounds to represent dissolver off-gas (DOG) streams from used nuclear fuel aqueous reprocessing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Project developer options to enhance the value of solar electricity as solar and storage penetrations increase

Increasing the penetration of photovoltaics (PV) reduces the marginal grid value of PV electricity. The declining grid value of PV with higher penetration could limit the technology's economic attractiveness and future demand. Various strategies have been proposed for preserving this value. Using a consistent framework, we analyze the net value (accounting for both cost and grid value) of more than ten strategies in the United States. Here, grid value is estimated from coincident wholesale power market prices and PV generation using observed historical prices or modeled future prices with up to 30% PV penetration. We find that established and emerging strategies designed to shift the timing of standalone PV generation at the expense of total generation—including orienting monofacial PV modules west or bifacial modules vertically—result in minor net-value benefits or penalties. Adding energy storage to such systems magnifies the net-value loss, because configurations that change the timing of PV production become redundant when the energy-shifting capabilities of storage are added. The largest net-value gains come from strategies that maximize generation (solar tracking plus oversized PV arrays) in conjunction with storage, especially at high PV penetrations. PV systems are long-lived assets. Our results suggest that efforts to promote generation-maximizing strategies today may yield increasing net-value benefits as PV and storage deployments continue to accelerate in the United States over the coming decades.

14 SOLAR ENERGY↗

Whimper of a Bang: Documenting the Final Days of the Nearby Type Ia Supernova 2011fe

Using the Hubble Space Telescope (HST) and the Large Binocular Telescope, we followed the evolution of the Type Ia supernova (SN Ia) 2011fe for an unprecedented 1840 days past B-band maximum light and over a factor of 7 million in flux. At 1840 days, the 4000–17000 Å quasi-bolometric luminosity is just (420±20) L{sub ⊙}. By measuring the late-time quasi-bolometric light curve, we present the first confident detection of {sup 57}Co decay in a SN Ia light curve and estimate a mass ratio of log({sup 57}Co/{sup 56}Co)=−1.59{sub −0.07}{sup +0.06}. We do not have a clean detection of {sup 55}Fe, but find a limit of {sup 55}Fe/{sup 57}Co<0.22 with 99% confidence. These abundance ratios provide unique constraints on the progenitor system because the central density of the exploding white dwarf(s) dictates these nucleosynthetic yields. The observed ratios strongly prefer the lower central densities of double-degenerate models ({sup 55}Fe/{sup 57}Co=0.27) over the higher central densities of near-Chandrasekhar-mass single-degenerate models ({sup 55}Fe/{sup 57}Co=0.68). However, additional theoretical studies predicting isotopic yields from a broader range of progenitor systems are motivated by these unique observations. We will continue to observe SN 2011fe for another ∼600 days with HST and possibly beyond.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal Instability in the Manufacturing of Wind Turbine Blade Spar Caps – Phase 2

As the wind turbine industry continues to develop, the technology surrounding the design, development, and manufacturing of blades requires advancement as well. Wind turbine blades continue to increase in size, increasing the cost and time associated with manufacturing. Simulation driven manufacturing cycle design is required for the industry to maintain manufacturing schedules and optimize the manufacturing process. A recent effort to reduce the cycle time of wind blade spar caps encountered a recurring manufacturing defect during the exotherm and curing of the resin system after filling in the vacuum-assisted resin transfer molding (VARTM) process. Thermal waves developed in sections of the spar cap resulting in unacceptable part tolerances, requiring the parts to be thrown out. The first phase of this IACMI project focused on characterizing the fabric and epoxy system used in manufacturing and simulating the manufacturing process to determine the root cause of the thermal waves. The second phase of this project refined and validated the manufacturing simulations. The simulation workflow was then used to analyze multiple cure cycle options to determine if the thermal waves would appear. The estimated filling time from the filling simulation was shown to match well to experiment, and the temperature history from the curing simulation lined up well with experiment. This indicates that these simulations could be used to evaluate future curing cycles to be used with manufacturing. It is recommended that the distortion simulation work be completed for this project, as it would allow for further manufacturing cycle evaluation through the prediction of stresses and strains in the part. This could provide indicators of defects like the thermal waves seen in manufacturing earlier.

17 WIND ENERGY↗

Total Cost of Ownership Reduction Using Passive Pre-Chamber Ignition in Natural Gas Engines

Spark plug durability is a factor affecting the total cost of ownership (TCO) of spark-ignited natural gas engines, with some heavy-duty platforms requiring plug replacement after only 750 hours of operation. The high ignition energy demand under lean or diluted conditions accelerates electrode wear, shortening plug life and increasing maintenance frequency. This work evaluates passive pre-chamber (PC) ignition operating at lowered spark energies as a strategy to reduce spark energy requirements and extend plug durability, thereby lowering TCO. Experiments were conducted on a medium-duty Cummins 6.7L ISB engine at 1600 RPM and 50% load under varying exhaust gas recirculation (EGR) dilution levels (0–40%). Two passive pre-chambers with 1.1 mm and 1.6 mm nozzle diameters were compared with conventional spark ignition (SI). SI was operated with a fixed coil dwell of 4 ms (~90 mJ), while the PC configuration was tested across 2–4 ms dwell times (~30–90 mJ). Cylinder pressure analysis revealed that PC ignition sustained stable combustion at significantly lower spark energies than SI, with improved combustion stability at ~30 mJ compared with SI at ~90 mJ. The PC system also extended the dilution tolerance beyond that achievable with SI, while delivering up to ~2% higher indicated thermal efficiency and reducing the COV by nearly 90% at 30% EGR. A TCO analysis was conducted to assess the economic benefit of adopting a passive PC system operating at reduced spark energies compared to SI. It was found that adopting a passive PC system could reduce TCO by approximately $11,000 per engine over a five-year operational period, primarily due to fuel savings, extended spark plug life, and reduced maintenance frequency. These projections were weighed against the additional hardware cost of the pre-chamber, yielding a rapid estimated return on investment of ~300 operating hours. Therefore, this work motivates continued research and development of passive PC technology and its commercial adoption in natural gas engines used in transportation applications.

Dhotre, Akash [University of Minnesota]↗

Understanding Thermal Transport in Polymer –Silver Nanowire Composites

Understanding thermal transport across filler-polymer interfaces and filler-filler contacts within polymer composites is of great importance for better thermal design of the composites that are widely used in high-performance heat exchangers, energy storage devices, and flexible electronics. Over the past several decades, considerable progress has been made in improving the thermal conductivity of polymer composites, but several key questions concerning the influence of interfacial thermal resistance, or Kapitza resistance, still remain. Firstly, the thermal properties of these composites are highly dependent on thermal transport through the filler network and its contacts. For metallic nanofillers, the thermal conductivity is often estimated using the Wiedemann-Franz law based on electrical conductivity; however, it remains a question whether the Wiedemann-Franz law still holds at nanoscale contacts. Through investigation of silver nanowires of varying sizes, we were able to demonstrate that the Lorenz number for silver nanowire increases with decreasing nanowire diameter. Examination of the corresponding electrical and thermal conductivities indicate that these changes are due to that the relative contribution of phonons becomes more significant as a result of elastic stiffening. Furthermore, we show that for silver nanowires, the contact thermal resistance is ~8 times lower than that of multi-walled carbon nanotube (MWCNT) of similar diameters. Additionally, through systematic studies of electrospun polymer-silver nanowire composite nanofibers, we investigated the impact of interface morphology on the thermal conductivity enhancement of the composite system and probed the value of the Kapitza resistance for individual polymer-filler interfaces. For polymer nanofibers containing continuous, single silver nanowires, the thermal conductivity increases linearly with increasing volume fraction of silver, which is consistent with the prediction of percolation theory for samples above the percolation limit. By comparing this linear trend to the measured thermal conductivities of composite nanofibers with more complex structures, we were able to determine the resistance associated with any additional polymer-filler boundaries. In doing so we find that the thermal boundary resistance for polyvinylpyrrolidone (PVP)–silver interfaces is significantly lower than that of comparable polymer-MWCNT composite systems.Together our studies provide new insights into thermal transport in polymer nanocomposites and should help facilitate the design of high performance polymeric thermal interface material.

Thermal transport↗

Understanding Thermal Transport in Polymer - Silver Nanowire Composites

Understanding thermal transport across filler-polymer interfaces and filler-filler contacts within polymer composites is of great importance for better thermal design of the composites that are widely used in high-performance heat exchangers, energy storage devices, and flexible electronics. Over the past several decades, considerable progress has been made in improving the thermal conductivity of polymer composites, but several key questions concerning the influence of interfacial thermal resistance, or Kapitza resistance, still remain. Firstly, the thermal properties of these composites are highly dependent on thermal transport through the filler network and its contacts. For metallic nanofillers, the thermal conductivity is often estimated using the Wiedemann-Franz law based on electrical conductivity; however, it remains a question whether the Wiedemann-Franz law still holds at nanoscale contacts. Through investigation of silver nanowires of varying sizes, we were able to demonstrate that the Lorenz number for silver nanowire increases with decreasing nanowire diameter. Examination of the corresponding electrical and thermal conductivities indicate that these changes are due to that the relative contribution of phonons becomes more significant as a result of elastic stiffening. Furthermore, we show that for silver nanowires, the contact thermal resistance is ~8 times lower than that of multi-walled carbon nanotube (MWCNT) of similar diameters. Additionally, through systematic studies of electrospun polymer-silver nanowire composite nanofibers, we investigated the impact of interface morphology on the thermal conductivity enhancement of the composite system and probed the value of the Kapitza resistance for individual polymer-filler interfaces. For polymer nanofibers containing continuous, single silver nanowires, the thermal conductivity increases linearly with increasing volume fraction of silver, which is consistent with the prediction of percolation theory for samples above the percolation limit. By comparing this linear trend to the measured thermal conductivities of composite nanofibers with more complex structures, we were able to determine the resistance associated with any additional polymer-filler boundaries. In doing so we find that the thermal boundary resistance for polyvinylpyrrolidone (PVP)–silver interfaces is significantly lower than that of comparable polymer-MWCNT composite systems. Together our studies provide new insights into thermal transport in polymer nanocomposites and should help facilitate the design of high performance polymeric thermal interface material.

Matthew L. Fitzgerald↗

Kinetics of Diffusional Droplet Growth in a Liquid/Liquid Two-Phase System

We address the problem of diffusional interactions in a finite sized cluster of spherical particles for volume fractions, V(sub v) in the range 0-0.01. We determined the quasi-static monopole diffusion solution for n particles distributed at random in a continuous matrix. A global mass conservation condition is employed, obviating the need for any external boundary condition. The numerical results provide the instantaneous (snapshot) growth or shrinkage rate of each particle, precluding the need for extensive time-dependent computations. The close connection between these snapshot results and the coarsegrained kinetic constants are discussed. A square-root dependence of the deviations of the rate constants from their zero volume fraction value is found for the higher V(sub v) investigated. This behavior is consistent with predictions from diffusion Debye-Huckel screening theory. By contrast, a cube-root dependence, reported in earlier numerical studies, is found for the lower V(sub v) investigated. The roll-over region of the volume fraction where the two asymptotics merge depends on the number of particles, n, alone. A theoretical estimate for the roll-over point predicts that the corresponding V(sub v) varies as n(sup -2), in good agreement with the numerical results.

Glicksman, M. E.↗

Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization

Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA) census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.

54 ENVIRONMENTAL SCIENCES↗