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At least 1,243 records · Page 69

Fast and Thermal Neutron Spectrum Dosimetry Measurements in the Advanced Test Reactor large-B and small-I Positions Following the Sixth Core Internals Change-out [Slides]

The Advanced Test Reactor (ATR) has a wide variety of irradiation positions that have had experiments that were developed by users from around the world. Most experiment irradiations rely on thoroughly benchmarked numerical models. However, some irradiation positions in ATR are not as well- characterized and are complicated by spectral perturbations from control cylinder orientation. The “small I” and “large-B” irradiation positions are located nearby control cylinders and suffer from these flux perturbations from control cylinder orientations that change during an irradiation cycle to maintain the desired core power distribution. Models predicted that these types of position would exhibit both spectral shifts and amplitude changes in neutron flux, but few measurements have been conducted to benchmark these predictions. Recently, requalification testing was performed to confirm the operational readiness of the ATR following the completion of the Core Internals Change-out (CIC). These tests provided a unique opportunity to validate the analytical methods used to simulate the ATR because nearly all components in the reactor were in a clean as-built state, significantly reducing modelling uncertainties. One subset of the testing included characterization of the fast and thermal neutron flux in the “small-I” and “large-B” positions using silver, cobalt, and nickel neutron dosimetry. In contrast to typical irradiation cycles, the control cylinders were held in position during the post-CIC nuclear testing. The specific activity of these dosimeter wires was measured following two low-power tests with different control cylinder positions.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

A317_Fast and Thermal Neutron Spectrum Dosimetry Measurements in the Advanced Test Reactor large-B and small-I Positions Following the Sixth Core Internals Change-out

The Advanced Test Reactor (ATR) has a wide variety of irradiation positions that have had experiments that were developed by users from around the world. Most experiment irradiations rely on thoroughly benchmarked numerical models. However, some irradiation positions in ATR are not as well- characterized and are complicated by spectral perturbations from control cylinder orientation. The “small I” and “large-B” irradiation positions are located nearby control cylinders and suffer from these flux perturbations from control cylinder orientations that change during an irradiation cycle to maintain the desired core power distribution. Models predicted that these types of position would exhibit both spectral shifts and amplitude changes in neutron flux, but few measurements have been conducted to benchmark these predictions. Recently, requalification testing was performed to confirm the operational readiness of the ATR following the completion of the Core Internals Change-out (CIC). These tests provided a unique opportunity to validate the analytical methods used to simulate the ATR because nearly all components in the reactor were in a clean as-built state, significantly reducing modelling uncertainties. One subset of the testing included characterization of the fast and thermal neutron flux in the “small-I” and “large-B” positions using silver, cobalt, and nickel neutron dosimetry. In contrast to typical irradiation cycles, the control cylinders were held in position during the post-CIC nuclear testing. The specific activity of these dosimeter wires was measured following two low-power tests with different control cylinder positions.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation was used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78.8% (±3.9% SD) classification reproducibility in terms of OS, LRC, and FFDM, respectively. Conclusions: Pretreatment tumor texture may provide prognostic information beyond that obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ∼80%. External validation would be required to establish texture as a prognostic factor.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Effect of patterned inclusions on the fracture behavior of ceramic composites

Developments in additive manufacturing have enabled the reinforcement of ceramic composites across the scales. Understanding the fracture behavior of such composites is critical for structural design and engineering. However, systematic investigations on the relationship between the patterning characteristics and the effective fracture properties have been scarce. In this work, we propose a mixed-mode phase field model to investigate the effects of elastic modulus and pattern characteristics of circular inclusions on the fracture behavior of a ceramic composite beam. The modeling results have shown that the stiff and compliant inclusions can either repel or attract the crack. The extent of repelling and attraction can be controlled by altering the pattern characteristics. In addition, utilizing the relationship between the pattern characteristics and resulting fracture path, fracture growth can be controlled with appropriate inclusion properties. The targeted enhancement in fracture toughness can also be predicted using an effective fracture model linked with the underlying fracture path computed by the proposed mixed-mode phase field model.

36 MATERIALS SCIENCE↗

A Simple Lagrangian Parcel Model for the Initiation of Summer-time Mesoscale Convective Systems over the Central United States

Mesoscale convective systems (MCSs) account for more than 50% of summertime precipitation over the central United States and have a significant impact on local weather and hydrologic cycle. It is hypothesized that the inadequate treatment of MCSs is responsible for the long-standing warm and dry bias over the central United States in coarse-resolution general circulation model (GCM) simulations. In particular, a better understanding of MCS initiation is still lacking. Here a single-column Lagrangian parcel model is first developed to simulate the basic features of a rising parcel. This simple model demonstrates the collective effects of boundary layer moistening and dynamical lifting in triggering convective initiation and reproduces successfully its early afternoon peak with surface equivalent potential temperature as a controlling factor. It also predicts that convection is harder to trigger in the future climate under global warming, consistent with the results from convection-permitting regional climate simulations. Then, a multicolumn model that includes an array of single-column models aligned in the east–west direction and incorporates idealized cold pool interaction mechanisms is developed. The multicolumn model captures readily the cold pool–induced upscale growth feature in MCS genesis from initially scattered convection that is organized into a mesoscale cluster in a few hours. It also highlights the crucial role of lifting effects due to cold pool collision and spreading, subsidence effect, and gust front propagation speed in controlling the final size of mesoscale clusters and cold pool regions. This simple model should be useful for understanding fundamental mechanisms of MCS initiation and providing guidance for improving MCS simulations in GCMs.

54 ENVIRONMENTAL SCIENCES↗

The role of chemical potential in compensation control in Si:AlGaN

Reduction in compensation in Si-doped Al-rich AlGaN is demonstrated via chemical potential control (CPC). The chemical potentials and the resulting formation energies of carbon on the nitrogen site (C N ) and cation vacancy complex with Si (V III + nSi III ) were related to growth variables through a thermodynamic supersaturation model, which quantitatively predicted the incorporation of C N and the generation of the V III + nSi III complex. The compensation “knee” behavior, i.e., decreasing conductivity with increasing Si incorporation beyond a certain concentration, was successfully controlled. The maximum free carrier concentration was improved by impeding the formation of V III + nSIi III complexes under III-richer conditions, while the impurity compensation by C N was reduced by making the growth environment N-richer. The results of Hall effect measurement and photoluminescence agreed well with quantitative theoretical predictions of the CPC model. Based on the developed model, the highest conductivity of 160 Ω -1 cm -1 with free carrier concentration of 3 × 10 19 cm -3 in Al 0.7 Ga 0.3 N ever reported was achieved on single crystal AlN substrates. The demonstrated predictive power of the CPC model should greatly reduce the empirical analysis or iterative experimentation that would otherwise be necessary.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of mercury (Hg) bioaccumulation with mono- and mixed Lemna minor and Spirodela polyrhiza cultures

Mercury (Hg) is a prevalent and harmful contaminant that persists in the environment. For phytoremediation, it is important to discover which plants can bioaccumulate meaningful amounts of Hg while also tolerating its toxicity. Additionally, increasing biodiversity could create a more resilient and self-sustaining system for remediation. This study explores whether mixed populations of Lemna minor and Spirodela polyrhiza can better bioaccumulate and tolerate Hg than monocultures. Mono- and mixed cultures of L. minor and S. polyrhiza were grown in mesocosms of 0.5 μg/L or 100 μg/L Hg ( HgCl2) spiked water for 96 h. Change in weight of duckweed was used to assess Hg tolerance. Diffusive gradients in thin-films (DGTs) were used as surrogate monitoring devices for bioavailable levels of Hg. For biomass growth, the mixed culture of the L. minor was greater than the monoculture at the high dose. The L. minor accumulated more Hg in the mixed culture at the low dose while the S. polyrhiza was higher in the mixed at the high dose. Hg speciation in water was modeled using Windermere Humic Aqueous Model 7 (WHAM7) to compare the bioavailable species indicated by the DGTs. Potentially due to the controlled conditions, the WHAM7 output of bioavailable Hg was almost 1:1 to that estimated by the DGTs, indicating good predictive capability of geochemical modeling and passive sampler DGT on metal bioavailability. Altogether, the mixed cultures statistically performed as well as or better than the monocultures when tolerating and bioaccumulating Hg. However, there needs to be further work to see if the significant differences translate into practical differences worth the extra resources to maintain multiple species.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice

We present a description of the Antarctic Ice Sheet model configuration submitted to the ISMIP6-Antarctica-2300 experiment using the MPAS-Albany Land Ice model, along with three new sets of simulations: (1) a set of extended simulations to 2500 for three forced experiments and to 2775 for the control experiment; (2) a sensitivity analysis of our model configuration to parameters controlling basal sliding and sub-shelf melt, and to model structural choices including the choice of the energy and stress balances; and (3) a 72-member ensemble run on graphics processing units (GPUs) and analysis of variance to determine the primary sources of uncertainty in our ice-sheet model projections. Our extended simulations predict rapid retreat beginning after 2300 for SSP1-2.6 forcing and after 2500 for present-day (control) forcing, primarily in the Amundsen Sea Embayment. We find that varying the sub-shelf melt parameter between the 5th to 95th percentile values for a mean-Antarctic calibration target results in an up to ∼ ± 40 % change in sea-level contribution relative to our baseline simulations that used the median value. Using a linear basal sliding law reduces sea-level contribution by 51 %–73 % relative to our baseline nonlinear sliding law with an exponent of 1/5. When using basal sliding law exponents of 1/3 and 1/10, the overall difference from our baseline simulations at 2300 is on the order of 10 %. The Amundsen Sea Embayment region displays a strongly non-linear dependence of mass loss on the sliding law exponent, with no discernible relationship between the sliding law exponent and the mass loss by 2300, while the sectors feeding the Ross and Filchner-Ronne ice shelves exhibit more mass loss with a more-plastic sliding law. Our model fidelity sensitivity experiments reveal a 9 %–31 % increase in sea-level contribution when using a depth-integrated stress balance approximation relative to our three-dimensional solver, while using a fixed-in-time temperature field increases sea-level contribution by 14 %–88 % relative to two thermomechanically coupled configurations. Our 72-member ensemble and analysis of variance show that the uncertainty in long-term projections is dominated by the choice of Earth system model forcing and the presence or absence of hydrofracture forcing, rather than uncertainty in sliding and sub-shelf melt parameters.

58 GEOSCIENCES↗

Driving Down HB-LED Costs. Implementation of Process Simulation Tools and Temperature Control Methods of High Yield MOCVD Growth

The overall objective of this multi-faceted program is to develop epitaxial growth systems that meet a goal of 75% (4X) cost reduction in the epitaxy phase of HB-LED manufacture. A 75% reduction in yielded epitaxy cost is necessary in order to achieve the cost goals for widespread penetration of HB-LED's into back-lighting units (BLU) for LCD panels and ultimately for solid-state lighting (SSL). To do this, the program will address significant improvements in overall equipment Cost of Ownership, or CoO. CoO is a model that includes all costs associated with the epitaxy portion of production. These aspects include cost of yield, capital cost, operational costs, and maintenance costs. We divide the program into three phases where later phases will incorporate the gains of prior phases. Phase one activities are enabling technologies. In collaboration with Sandia National Laboratories we develop a Fluent-compatible chemistry predictive model and a set of mid-infrared and near-ultraviolet pyrometer monitoring tools. Where previously the modeling of the reactor dynamics were studied within FLUENT alone, here, FLUENT and Chemkin are integrated into a comprehensive model of fluid dynamics and the most advanced transport equations developed for Chemkin. Specifically, the Chemkin model offered the key reaction terms for gas-phase nucleation, a key consideration in the optimization of the MOCVD process. This new predictive model is used to design new MOCVD reactors with optimized growth conditions and the newly developed pyrometers are used monitor and control the MOCVD process temperature to within 0.5°C run-to-run and within each wafer. This portion of the grant is in collaboration with partners at Sandia National Laboratories. Phase two activities are continuous improvement projects which extend the current reactor platform along the lines of improved operational efficiency, improved systems control for throughput, and carrier modifications for increased yield. Programmatically, improvements made in Phase I are applied to developments of Phase II when applicable. Phase three is the culmination of the individual tasks from both phases one and two applied to proposed production platforms. We selectively combine previously demonstrated tasks and other options to develop a high-volume production-worthy MOCVD system demonstrating >3x throughput, 1.3x capital efficiency, and 0.7x cost of ownership. In a parallel demonstration we validate the concept of an improved, larger deposition system which utilizes the predictive modeling of chemistry-based flow analysis and extensions of the improvements demonstrated on the current platforms. This validation includes the build and testing of a prototype version of the hardware and demonstration of 69% reduction in the cost of ownership. Also, in this phase we present a stand-alone project to develop a high-temperature system which improves source efficiency by 30% while concurrently increasing growth rate by 1.3x. The material quality is held to the same material quality specifications of our existing baseline processes. The merits of other line item tasks in phase three are discussed for inclusion on next-generation platforms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling of the TRIGA IPR-R1 research reactor with the Serpent2/RINNOVO Nodal core analysis package

The Serpent2/RINNOVO nodal core analysis code system, a dedicated tool for modeling research reactors, has the capability to accurately predict important core physics parameters involved in the safety of reactor operation, such as various reactivity coefficients, control rod and bank worths including the shutdown margin, power distributions as well as local neutron flux predictions at various core locations of high importance, e.g., at irradiation rigs. In this work, a hexagonal model of the unrodded initial core of the Brazilian IPR-R1 Mark I type TRIGA nuclear reactor has been created using the Serpent2/RINNOVO code system. The choice of employing a hexagonal core geometry representation has mainly been made to facilitate subsequent fuel shuffling operations and core follow calculations of this reactor. Numerical results in terms of the core eigenvalue and the assembly power distribution have then been compared against corresponding full core Serpent2 results to prove feasibility of using the Serpent2/RINNOVO code system for modeling small and highly heterogeneous TRIGA reactors. Overall, RINNOVO predicts the power distribution very accurately but the eigenvalue error still remains quite large. In light of being the very first evaluation of a TRIGA reactor with the RINNOVO nodal core simulator, these results are also considered to be very preliminary. Improved accuracy is expected by incorporating a proper methodology in the current code system for computing discontinuity factors for multi-assembly configurations. Furthermore, improved results are expected by increasing the number of energy groups used by RINNOVO in these core calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each daily CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.

60 APPLIED LIFE SCIENCES↗

Transient fuel performance analysis for the preliminary fuel concept of general atomics fast modular reactor

This study investigates the transient fuel performance of General Atomics Fast Modular Reactor (GA-FMR) during accident scenarios, focusing on the behavior of its innovative fuel system that combines high-assay low enriched uranium dioxide (HALEUO2) fuel with SiGA® ceramic matrix composite silicon carbide cladding. The preliminary fuel design’s response was analyzed during reactivity-initiated accidents (RIA) and loss of coolant accidents (LOCA) using BISON fuel performance analysis code, which included both the diffusion enhanced and BISON-FASTGRASS coupled UO 2 models. The RIA analysis demonstrated that effective reactivity control reduced fuel temperature, though with transient fission gas release resulting in additional tensile stress state on the cladding. LOCA simulations revealed differing predictions between the two models: the BISON UO 2 model showed more transient fission gas release but minimal pellet expansion, while the BISON-FASTGRASS UO 2 model predicted less pronounced fission gas release but more fuel swelling and thermal expansion, potentially leading to pellet-cladding mechanical interaction. Here, these findings highlight critical areas for fuel design optimization and identify knowledge gaps requiring further experimental and computational investigation to advance GA-FMR fuel development.

Lee, Soon K. [Argonne National Laboratory (ANL), A↗

Modeling Studies on the Transport of Benzene and H2S in CO2-Water Systems

In this study, reactive transport simulations were used to assess the mobilization and transport of organics with supercritical CO{sub 2} (SCC), and the co-injection and transport of H{sub 2}S with SCC. These processes were evaluated at conditions of typical storage reservoirs, and for cases of hypothetical leakage from a reservoir to an overlying shallower fresh water aquifer. Modeling capabilities were developed to allow the simulation of multiphase flow and transport of H{sub 2}O, CO{sub 2}, H{sub 2}S, as well as specific organic compounds (benzene), coupled with multicomponent geochemical reaction and transport. This included the development of a new simulator, TMVOC-REACT, starting from existing modules of the TOUGH2 family of codes. This work also included an extensive literature review, calculation, and testing of phase-partitioning properties for mixtures of the phases considered. The reactive transport simulations presented in this report are primarily intended to illustrate the capabilities of the new simulator. They are also intended to help evaluate and understand various processes at play, in a more qualitative than quantitative manner, and only for hypothetical scenarios. Therefore, model results are not intended as realistic assessments of groundwater quality changes for specific locations, and they certainly do not provide an exhaustive evaluation of all possible site conditions, especially given the large variability and uncertainty in hydrogeologic and geochemical parameter input into simulations. The first step in evaluating the potential mobilization and transport of organics was the identification of compounds likely to be present in deep storage formations, and likely to negatively impact freshwater aquifers if mobilized by SCC. On the basis of a literature review related to the occurrence of these organic compounds, their solubility in water and SCC, and their toxicity (as reflected by their maximum contaminant levels MCL), benzene was selected as a key compound for inclusion into numerical simulations. Note that considering additional organic compounds and/or mixtures of such compounds in the simulations was beyond the scope of this study, because of the effort required to research, calculate, and validate the phase-partitioning data necessary for simulations. The injection of CO{sub 2} into a deep saline aquifer was simulated, followed by modeling the leaching of benzene by SCC and transport of benzene to an overlying aquifer along a hypothetical leakage pathway. One- and two-dimensional models were set up for this purpose. The target storage formation was assumed to initially contain about 10{sup -4} ppm benzene. Model results indicate that: (1) SCC efficiently extracts benzene from the storage formation. (2) Assuming equilibrium, the content of benzene in SCC is roportional to the concentration of benzene in the aqueous and solid phases. (3) Benzene may co-migrate with CO{sub 2} into overlying aquifers if a leakage pathway is present. Because the aqueous solubility of benzene in contact with CO{sub 2} is lower than the aqueous solubility of CO{sub 2}, benzene is actually enriched in the CO{sub 2} phase as the plume advances. (4) For the case studied here, the resulting aqueous benzene concentration in the overlying aquifer is on the same order of magnitude as the initial concentration in the storage formation. This generic modeling study illustrates, in a semi-quantitative manner, the possible mobilization of benzene by SCC. The extent to which the mobilization of this organic compound evolves temporally and spatially depends on a large number of controlling parameters and is largely site specific. Therefore, for more 'truly' predictive work, further sensitivity studies should be conducted, and further modeling should be integrated with site-specific laboratory and/or field experimental data. The co-injection of H{sub 2}S with CO{sub 2} into a deep saline aquifer was also simulated. In addition, the model considered leakage of the supercritical CO{sub 2}+H{sub 2}S mixture along a preferential pathway to an overlying fresh-water aquifer, followed by reaction of the CO{sub 2}+H{sub 2}S mixture with that aquifer. A simple 2-D model that included a storage formation and a sealing aquitard was developed to simulate the movement of H{sub 2}S in a typical CO{sub 2} storage formation. Model results indicate that H{sub 2}S is stripped off at the edge of the advancing supercritical plume, because of the H{sub 2}S preferential solubility in water compared to CO{sub 2}. The magnitude of H{sub 2}S preferential dissolution, however, decreases with decreasing temperature and pressure. To capture this behavior and evaluate the breakthrough of H{sub 2}S through a leakage pathway (from the deep storage formation to a shallower aquifer), another model was constructed, considering a storage formation, an overlying aquifer, and a vertical leakage pathway between them.

54 ENVIRONMENTAL SCIENCES↗

Investigation of an Intermittent Binary Control Strategy for Distributed Aerodynamic Control Devices for Load Alleviation in Wind Turbine Blades

A study was conducted of an intermittent binary control strategy for trailing edge flaps and leading edge spoilers installed on wind turbine blades for the purpose of load alleviation. Cost estimation models were developed for the systems to predict overall impact on levelized cost of energy over the lifecycle of the turbine system. Aeroelastic simulations of turbines with the control strategy implemented showed improved levelized cost for some, but not all cases.

17 WIND ENERGY↗

Assimilation of Wave Imaging Radar Observations for Real-time Wave-by-Wave Forecasting

This project addressed Topic 3: “Wave Measurement Instrumentation for Feed Forward Controls” under the FOA number DE-FOA-0000971. The overall goal of the program was to develop a phase-resolving wave forecasting technique for application to the active control of Wave Energy Conversion (WEC) devices. We have developed an approach that couples a wave imaging marine radar with a phase-resolving linear wave model for real-time wave field reconstruction and forward propagation of the wave field in space and time. The scope of the project was to develop and assess the performance of this novel forecasting system. Specific project goals were as follows: Develop and verify a fast, GPU-based (Graphical Processing Unit) wave propagation model suitable for phase-resolved computation of nearshore wave transformation over variable bathymetry; Compare the accuracy and speed of performance of the wave model against a deep water model in their ability to predict wave field transformation in the intermediate water depths (50 to 70 m) typical of planned WEC sites; Develop and implement a variational assimilation algorithm that can ingest wave imaging radar observations and estimate the time-varying wave conditions offshore of the domain of interest such that the observed wave field is best reconstructed throughout the domain and then use this to produce model forecasts for a given WEC location; Collect wave-resolving marine radar data, along with relevant in situ wave data, at a suitable wave energy test site, apply the algorithm to the field data, assess performance, and identify any necessary improvements; and Develop a production cost estimate that addresses the affordability of the wave forecasting technology and include in the Final Report. The developed forecasting algorithm (“Wavecast”) was evaluated for both speed and accuracy against a substantial synthetic dataset. Early in the project, performance tests definitively demonstrated that the system was capable of forecasting in real-time, as the GPU-based wave model backbone was very computationally efficient. The data assimilation algorithm was developed on a polar grid domain in order to match the sampling characteristics of the observation system (wave imaging marine radar). For verification purposes, a substantial set of synthetic wave data (i.e. forward runs of the wave model) were generated to be used as ground truth for comparison to the reconstructions and forecasts produced by Wavecast. For these synthetic cases, Wavecast demonstrated very good accuracy, for example, typical forecast correlation coefficients were between 0.84-0.95 when compared to the input data. Dependencies on shadowing, observational noise, and forecast horizon were also identified. During the second year of the project, a short field deployment was conducted in order to assess forecast accuracy under field conditions. For this, a radar was installed on a fishing vessel and observations were collected at the South Energy Test Site (SETS) off the coast of Newport, OR. At the SETS site, simultaneous in situ wave observations were also available owing to an ongoing field project funded separately. Unfortunately, the position and heading information that was available for the fishing vessel were not of sufficient accuracy in order to validate the forecast in a phase-resolving sense. Instead, a spectral comparison was made between the Wavecast forecast and the data from the in situ wave buoy. Although the wave and wind conditions during the field test were complex, the comparison showed a promising reconstruction of the wave spectral shape, where both peaks in the bimodal spectrum were represented. However, the total reconstructed spectral energy (across all directions and frequencies) was limited to 44% of the observed spectrum. Overall, wave-by-wave forecasting using a data assimilation approach based on wave imaging radar observations and a physics-based wave model shows promise for short-term phase-resolved predictions. Two recommendations for future work are as follows: first, we would recommend additional focused field campaigns for algorithm validation. The field campaign should be long enough to capture a range of wave conditions relevant to the target application and WEC site. In addition, it will be crucial to make sure the vessel of choice has high accuracy position and heading instrumentation (this instrumentation is commercially available but not standard on commercial fishing vessels). The second recommendation is to expand the model physics in the wave model backbone to include some nonlinear effects. Specifically, the third-order correction to the wave speed due to amplitude dispersion would be the next step in order to more accurately represent the phase speeds of large amplitude waves.

16 TIDAL AND WAVE POWER↗

Carbon-Based Metal-Free ORR Electrocatalysts for Fuel Cells: Past, Present, and Future

Replacing precious platinum with earth-abundant materials in fuel cells for oxygen reduction reaction (ORR) has been the objective worldwide for several decades. In last ten years, the carbon-based metal-free ORR electrocatalysts is the fastest-growing branch in this area. Great progresses have been made in promoting the performance and understanding the underlying ORR process. This article presents a comprehensive review of this filed by emphasizing on the emerging issues such as the design and controllable construction of porous structures and doping configurations, mechanistic understanding from the model catalysts and the combined experimental and theoretical studies, and more importantly, the performance evaluation in a full cell. Centering these topics, the most up-to-date results are presented, along with the remarks and perspectives for the future development of carbon-based metal-free ORR electrocatalysts.

Yang, Lijun↗

Hydration of Portland cement with additions of calcium sulfoaluminates

The effect of mineral additions based on calcium aluminates on the hydration mechanism of ordinary Portland cement (OPC) was investigated using isothermal calorimetry, thermal analysis, X-ray diffraction, scanning electron microscopy, solid state nuclear magnetic resonance and pore solution analysis. Results show that the addition of a calcium sulfoaluminate cement (CSA) to the OPC does not affect the hydration mechanism of alite but controls the aluminate dissolution. In the second blend investigated, a rapid setting cement, the amorphous calcium aluminate reacts very fast to ettringite. The release of aluminum ions strongly retards the hydration of alite but the C-S-H has a similar composition as in OPC with no additional Al to Si substitution. As in CSA-OPC, the aluminate hydration is controlled by the availability of sulfates. The coupling of thermodynamic modeling with the kinetic equations predicts the amount of hydrates and pore solution compositions as a function of time and validates the model in these systems.

36 MATERIALS SCIENCE↗