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At least 271 records · Page 15

Criticality Experiments to Reduce Compensating Errors in Plutonium Nuclear Data

Compensating errors between nuclear data observables in a library can adversely impact application simulations. The primary goal of the EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) is to reduce compensating errors in nuclear data. A new criticality experiment, described in this work, was designed with the specific target nuclear data of 239 Pu fission, inelastic scattering, elastic scattering, capture, nu-bar, and prompt fission neutron spectrum (PFNS). This work will focus on the design and execution of the EUCLID experiment, performed on the Planet vertical lift critical assembly machine at the National Criticality Experiments Research Center (NCERC). The criticality experiment includes two different configurations with very different geometries: one is cube-like to minimize neutron leakage while the other is slab-like to maximize leakage. Having these two widely varying configurations allows the scattering sensitivities of 239 Pu to the neutron multiplication factor to be greatly changed while minimally impacting the other cross section sensitivities. Both configurations utilize the Pu ZPPR (Zero Power Physics Reactor) plates as fuel. The experiments were designed using a D-Optimality criteria, which is an optimization method minimizing the log-determinant of the adjusted nuclear data covariance for the target reactions. These experiments include not only inference of k eff , as done in all critical benchmark experiments, but several other responses as well, such as neutron multiplication measurements and reaction rate ratios. After analysis of the measured data is complete, adjustment of nuclear data will be performed to assess whether the new experimental data successfully reduced compensating errors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Advanced Fossil Energy Separations and Analysis Research – Thermal Desorption Using Spouted Beds

Mercury and other contaminants in emissions from coal-fired power plants are of interest due to the cost associated with capture and disposal of toxic mercury species. It had recently been postulated in the fossil energy community that spouted beds may be a viable coal pre-treatment technique for thermal desorption of mercury. Spouted beds have the potential to be a near-ideal solid-gas contactor for desorption of mercury species, especially with a few proposed design changes specific for this application. Introduction of draft tubes for spouted beds has addressed some issues with scale-up to better handle the throughput and particle size found in coal-fired power plants. In Phase I, Mainstream Engineering invented and developed a Venturi draft tube spouted bed (VDTSB) to enable process scale-up with fine coal particles and to improve heat and mass transfer. The VDTSB concept increases suction at the bottom of the bed to better entrain material (and reduce the propensity for bridging) at the bottom of the conical vessel. The main advantages of this patent-pending approach are the ability to accept a wide range of coal particle sizes, good heat/mass transfer, process scalability, and robustness. The desorber design was optimized through bed flow visualization experiments; these experiments demonstrated the increased throughput and ease of process scale-up. A high-temperature pilot-scale VDTSB desorber system was designed, fabricated, commissioned, and tested. The heat and mass transfer rates with the VDTSB were measured and compared to a baseline spouted bed with and without a conventional straight draft tube. Pilot-scale VDTSB system performance tests were completed with the Energy and Environmental Research Center (EERC) to measure the rate of mercury desorption over a range of pulverized coal particle sizes, bed temperatures, and reactor geometry. Based on performance results, an initial technoeconomic analysis (TEA) was completed to estimate the cost reduction for emissions treatment compared to current flue-gas mercury capture systems. The following was accomplished in Phase I: Developed scalable design correlations for high-throughput spouted bed systems; Determined cycle time distribution (CTD) and turnover time for straight and Venturi draft tube spouted beds, and showed the VDTSB had lower cycle time (faster turnover) than the straight draft tube (SDT); Reduced weighted-average turnover time by 14% to 43% with Venturi draft tube; narrowed the CTD by up to 75%; Measured heat and mass transfer within the pilot-scale VDTSB desorber and showed that the highest heat transfer rate was 2.98 kW/m 2 ·s with 400 µm particles at a 10 L/min motive gas flowrate; Measured mercury (Hg) desorption rate for lignite, bituminous, and subbituminous coal at 200 °C, 225 °C, 250 °C and 275 °C; Achieved 5.6×10 -10 kg/m 2 -h, 2.6×10 -10 kg/m 2 -h, and 6.5×10 -11 kg/m 2 -h Hg removal rates for lignite, bituminous, and sub-bituminous coals, respectively with no loss in volatile matter and an increase in heating value due to a reduction in moisture content; The unoptimized VDTSB pilot desorber decreased the total mercury concentration of lignite and bituminous coal tests by 61% (dry basis). The subbituminous Powder River Basin (PRB) coal showed a reduction of 18%; Based on our TEA of coal-fired power plants, implementing the VDTSB for coal pretreatment could reduce the mercury capture capital and operating expenses by 36% and 38%, respectively, which exceeded the target goal of 25% reduction; A patent application was prepared, and the results were presented at the 2017 AIChE Annual Meeting (Minneapolis, MN).

20 FOSSIL-FUELED POWER PLANTS↗

Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of 0.33% and an LoD of 0.015% for quantification of Ga in a Ce matrix. This study concludes that these machine learning methods could yield robust prediction models for rapid quality control analysis of plutonium alloys.

Rao, Ashwin P. (ORCID:0000000319312568)↗

Optimal input design for aircraft parameter estimation using dynamic programming principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Klein, Vladislav↗

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Morelli, Eugene A.↗

Ultrasound-assisted facile synthesis of a new tantalum(V) metal-organic framework nanostructure: Design, characterization, systematic study, and CO{sub 2} adsorption performance

This work presents a fast route for the preparation of a new Ta(V) metal-organic framework nanostructure with high surface area, significant porosity, and small size distribution. X-ray diffraction (XRD), scanning electron microscopy (SEM), Transition electron microscopy (TEM), energy dispersive spectrometer (EDS), thermo-gravimetric analysis (TGA), differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FTIR), CHNS/O elemental analyser, and Brunauer-Emmett-Teller (BET) surface area analysis were applied to characterize the synthesized product. Moreover, the influences of ultrasonic irradiation including temperature, time, and power on different features of the final products were systematically studied using 2{sup k-1} factorial design experiments, and the response surface optimization was used for determining the best welding parameter combination. The results obtained from analyses of variances showed that ultrasonic parameters affected the size distribution, thermal behaviour, and surface area of Ta-MOF samples. Based on response surface methodology, Ta-MOF could be obtained with mean diameter of 55 nm, thermal stability of 228 °C, and high surface area of 2100 m{sup 2}/g. The results revealed that the synthesized products could be utilized in various applications such as a novel candidate for CO{sub 2} adsorption. - Graphical abstract: A facile route was used for fabrication of a new metal -organic framework based on tantalum nanostructures that have high surface area, considerable porosity, homogenous morphology, and small size distribution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance Evaluation of an Offshore Wave Measurement Buoy in Monochromatic Waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6 s to 30 s. For wave periods between 5 s and 25 s, the buoy provides accurate wave height measurements. For short periods less than 5 s, the 1.28 Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25 s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. Furthermore, analysis of three field-derived cases shows that frequency-domain estimates at 1.28 Hz agree within 2% of the corresponding 100 Hz estimates, while larger method-dependent differences are observed for the Hilbert method.

16 TIDAL AND WAVE POWER↗

Science acceleration and accessibility with self-driving labs

In the evolving landscape of scientific research, the complexity of global challenges demands innovative approaches to experimental planning and execution. Self-Driving Laboratories (SDLs) automate experimental tasks in chemical and materials sciences and the design and selection of experiments to optimize research processes and reduce material usage. This perspective explores improving access to SDLs via centralized facilities and distributed networks. We discuss the technical and collaborative challenges in realizing SDLs’ potential to enhance human–machine and human–human collaboration, ultimately fostering a more inclusive research community and facilitating previously untenable research projects.

Canty, Richard B. [North Carolina State University↗

Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy

Chemical processing of highly radioactive materials commonly takes place in heavily shielded hot cells. The remote, real-time monitoring of chemical processing streams via optical spectroscopic techniques in hot cells may be particularly useful. Here in this paper, we describe the implementation of Raman spectroscopy and chemometric analysis to monitor the dissolution of aluminum-clad targets containing irradiated aluminum–neptunium oxide cermet pellets in caustic solutions in a hot cell environment. Partial least squares regression analysis was used to generate calibration models to quantify the concentration of dissolved aluminum, nitrate, and hydroxide in solutions within the radiochemical hot cell. This work explored a systematic approach to optimize a matrix of calibration standards using a D-optimal experimental design. The Design of Experiments-based regression model, in comparison to more traditional analytical approaches, was found to be the more practical method for building calibration models, with fewer samples, to obtain informative analytical data from Raman spectra.

36 MATERIALS SCIENCE↗

Lignin Derived Ionic Liquids: Synthesis and Application for Biopolymer Processing (CRADA Final Report)

We have established a scalable and economically viable process to convert lignin into ionic liquids for use in biopolymer processing. We have studied the four main topics: 1) lignin depolymerization to produce vanillin through oxidation, 2) lignin reduction to produce guaiacols, 3) oxidation process scale up, and 4) ionic liquid synthesis and application for biopolymer processing. The main accomplishment is summarized below: A maximal vanillin yield of 4.9% (8.8% total product yield) was achieved under optimal oxidation conditions using design of experiments (DOE); Aminophenol with 94.5% purity was synthesized via reductive amination using vanillin isolated from ion-exchange chromatography; At a higher lignin loading (10%), the vanillin yield in the scale up reaction was lower than the bench scale reaction; The filtration-based downstream separation of the scale-up process was able to recover 76% of vanillin; A maximal lignin reduction product (guaiacols) yield of 6.5% was achieved in the presence of Ru/C, formic acid, and methanol; The lignin reduction product yield and composition were affected by the use of different solvent and catalytic reagents (methanol in combination of Ru/C and formic acid gives the highest product yield); Lignin oxidation and reduction products: vanillin, acetovanillone, guaiacols, and eugenol are successfully used for IL synthesis; XX based ILs showed cellulose solubility with up to xx%; Technoeconomic analysis results indicate the potential of producing affordable ILs from kraft lignin (MSP: $14/kg); Life-cycle assessment results show the potential to reduce GHG emissions by up to 85% relative to existing ILs ([Ch][Lys]) with GHG emission: 1.2 kg CO 2e /kg of IL produced.

09 BIOMASS FUELS↗

Interlaced Characterization and Calibration (ICC) for Improved Computational Simulation Credibility

Accurate material characterization and model calibration are pivotal for simulations used for high-consequence engineering decisions. Current characterization and calibration methods (1) use simplified test specimen geometries and global data, (2) cannot guarantee that sufficient characterization data is collected for a specific model of interest, (3) provide only mean parameter values with no uncertainty quantification, and (4) are sequential, inflexible, and time-consuming. This work developed a new paradigm—coined Interlaced Characterization and Calibration (ICC)—which drives forward the state-of-the-art in model calibration by bringing together recent advancements into one improved workflow. The ICC paradigm (1) employs tools to efficiently use full-field data to calibrate high-fidelity material models, (2) aligns the data needed with the data collected by adopting an optimal experimental design protocol, (3) provides uncertainty metrics on the calibrated model parameters, and (4) incorporates these advances into a quasi real-time feedback loop. The ICC framework was validated synthetically with both low-fidelity and high-fidelity simulations paired with several different elastoplastic material models, and was also demonstrated experimentally with an aluminum 6061 cruciform exemplar specimen. Results showed that the ICC framework—in which Bayesian optimal experimental design actively guided the experiment— resulted in calibrations with similar or better accuracy than predetermined experiments based on subject matter expertise. Moreover, the ICC framework produced a complete model calibration— with quantified uncertainties on model parameters—in 1 week, a 5 - 10× increase in efficiency over traditional approaches. Thus, the ICC paradigm improves both the calibration process and quality, by (1) improving efficiency, which increases agility of solid mechanics modeling and enables utilization of computational simulation (CompSim) at earlier stages of the design cycle and (2) providing quantified, and in some cases reduced, parameter uncertainties, which increases confidence in model predictions and supports credible decision making.

97 MATHEMATICS AND COMPUTING↗

Promoted Ru/PrOx Catalysts for Mild Ammonia Synthesis

Ammonia synthesis is one of the most important chemical reactions. Due to thermodynamic restrictions and the reaction requirements of the current commercial iron catalysts, it is also one of the worst reactions for carbon dioxide emissions and energy usage. Ruthenium-based catalysts can substantially improve the environmental impact as they operate at lower pressures and temperatures. In this work, we provide a screening of more than 40 metals as possible promoter options based on a Ru/Pr2O3 catalyst. Cesium was the best alkali promoter and was held constant for the series of double-promoted catalysts. Ten formulations outperformed the Ru-Cs/PrOx benchmark, with barium being the best second promoter studied and the most cost-effective option. Designs of experiments were utilized to optimize both the pretreatment conditions and the promoter weight loadings of the doubly promoted catalyst. As a result, optimization led to a more than five-fold increase in activity compared to the unpromoted catalyst, therefore creating the possibility for low-ruthenium ammonia synthesis catalysts to be used at scale. Further, we have explored the roles of promoters using kinetic analysis, X-ray Photoelectron Spectroscopy (XPS), and in situ infrared spectroscopy. Here, we have shown that the role of barium is to act as a hydrogen scavenger and donor, which may permit new active sites for the catalyst, and have demonstrated that the associative reaction mechanism is likely used for the unpromoted Ru/PrOx catalyst with hydrogenation of the triple bond of the dinitrogen occurring before any dinitrogen bond breakage.

Chemistry↗

A SEARCH FOR STELLAR-MASS BLACK HOLES VIA ASTROMETRIC MICROLENSING

While dozens of stellar-mass black holes (BHs) have been discovered in binary systems, isolated BHs have eluded detection. Their presence can be inferred when they lens light from a background star. We attempt to detect the astrometric lensing signatures of three photometrically identified microlensing events, OGLE-2011-BLG-0022, OGLE-2011-BLG-0125, and OGLE-2012-BLG-0169 (OB110022, OB110125, and OB120169), located toward the Galactic Bulge. These events were selected because of their long durations, which statistically favors more massive lenses. Astrometric measurements were made over one to two years using laser-guided adaptive optics observations from the W. M. Keck Observatory. Lens model parameters were first constrained by the photometric light curves. The OB120169 light curve is well fit by a single-lens model, while both OB110022 and OB110125 light curves favor binary lens models. Using the photometric fits as prior information, no significant astrometric lensing signal was detected and all targets were consistent with linear motion. The significant lack of astrometric signal constrains the lens mass of OB110022 to 0.05–1.79 M {sub ⊙} in a 99.7% confidence interval, which disfavors a BH lens. Fits to OB110125 yielded a reduced Einstein crossing time and insufficient observations during the peak, so no mass limits were obtained. Two degenerate solutions exist for OB120169, which have a lens mass between 0.2–38.8 M {sub ⊙} and 0.4–39.8 M {sub ⊙} for a 99.7% confidence interval. Follow-up observations of OB120169 will further constrain the lens mass. Based on our experience, we use simulations to design optimal astrometric observing strategies and show that with more typical observing conditions the detection of BHs is feasible.

79 ASTRONOMY AND ASTROPHYSICS↗

A VLBI variance-covariance analysis interactive computer program

An interactive computer program (in FORTRAN) for the variance covariance analysis of VLBI experiments is presented for use in experiment planning, simulation studies and optimal design problems. The interactive mode is especially suited to these types of analyses providing ease of operation as well as savings in time and cost. The geodetic parameters include baseline vector parameters and variations in polar motion and Earth rotation. A discussion of the theroy on which the program is based provides an overview of the VLBI process emphasizing the areas of interest to geodesy. Special emphasis is placed on the problem of determining correlations between simultaneous observations from a network of stations. A model suitable for covariance analyses is presented. Suggestions towards developing optimal observation schedules are included.

Bock, Y.↗

Construction and control of large space structures

Recent NASA research efforts on space construction are reviewed. Preliminary results of the EASE/ACCESS Shuttle experiments are discussed. A 45-foot beam was constructed on orbit in 30 minutes using a manual assembly technique at a work station. A large tetrahedron was constructed several times using a free floating technique. The capability of repair, utilities installation, and handling the structures using a mobile foot restraint on the RMS was also demonstrated. Implications of the experiments for Space Station are presented. Models of 5-meter Space Station structure together with neutral buoyancy simulations suggest manual assembly techniques are feasible. Selected research on control of flexible structures is discussed. To support planned flight experiments, studies of the design and optimal placement of distributed active dampers are underway.

Card, M. F.↗

A numerical approach to controller design for the ACES facility

In recent years the employment of active control techniques for improving the performance of systems involving highly flexible structures has become a topic of considerable research interest. Most of these systems are quite complicated, using multiple actuators and sensors, and possessing high order models. The majority of analytical controller synthesis procedures capable of handling multivariable systems in a systematic way require considerable insight into the underlying mathematical theory to achieve a successful design. This insight is needed in selecting the proper weighting matrices or weighting functions to cast what is naturally a multiple constraint satisfaction problem into an unconstrained optimization problem. Although designers possessing considerable experience with these techniques have a feel for the proper choice of weights, others may spend a significant amount of time attempting to find an acceptable solution. Another disadvantage of such procedures is that the resulting controller has an order greater than or equal to that of the model used for the design. Of course, the order of these controllers can often be reduced, but again this requires a good understanding of the theory involved.

Frazier, W. Garth↗

Distributed Space Mission Design for Earth Observation Using Model-Based Performance Evaluation

Distributed Space Missions (DSMs) are gaining momentum in their application to earth observation missions owing to their unique ability to increase observation sampling in multiple dimensions. DSM design is a complex problem with many design variables, multiple objectives determining performance and cost and emergent, often unexpected, behaviors. There are very few open-access tools available to explore the tradespace of variables, minimize cost and maximize performance for pre-defined science goals, and therefore select the most optimal design. This paper presents a software tool that can multiple DSM architectures based on pre-defined design variable ranges and size those architectures in terms of predefined science and cost metrics. The tool will help a user select Pareto optimal DSM designs based on design of experiments techniques. The tool will be applied to some earth observation examples to demonstrate its applicability in making some key decisions between different performance metrics and cost metrics early in the design lifecycle.

Constellation↗

Angular Distributions of High-Mass Dilepton Production in Hadron Collisions

The SeaQuest experiment is a fixed-target dimuon experiment currently running at the Fermi National Accelerator Laboratory (FNAL). By utilizing the high-intensity, 120 GeV proton beam delivered by the FNAL Main Injector (MI), SeaQuest is able to measure proton-induced Drell-Yan dimuon production off of various nuclear targets in kinematic regions inaccessible to previous similar experiments. A suitably large fraction of the final dataset has been recorded, reconstructed, and analyzed. Very preliminary results from light-sea flavor asymmetry, nuclear dependence, and partonic energy loss analyses have been presented at numerous international conferences. A novel, FPGA-based trigger system has been designed, implemented, and optimized for the SeaQuest experiment. By implementing the trigger decision logic in FPGA firmware, it is more adaptable to changing experimental conditions. Additionally, the peripheral tasks of timing alignment, “trigger matrix” generation, and firmware uploading have been mostly automated, reducing the likelihood of user error in the maintenance and operation of the trigger system. Significant upgrades to hardware and firmware have greatly improved the performance of the trigger system since the 2012 commissioning run of SeaQuest. Four additional v1495 modules were added to facilitate thorough pulser testing of the firmware designs and in-situ pulser tests of all compiled firmware. These pulser tests proved crucial for diagnosing many errors that may have otherwise gone unnoticed. A significant change to the internal clocking of the trigger system eliminated a subtle source of rate-dependent trigger efficiency. With this upgrade, the trigger finally meets the “dead-time free” design specification. Drell-Yan dimuon data have been collected and analyzed for central θCS , with nearly flat acceptance in φCS , in the mass range 5.0 GeV < Mγ* < 10.0 GeV at forward xF with the SeaQuest spectrometer at FNAL. A very preliminary extraction of λ has been performed, and the remaining difficulties in extracting ν have been evaluated. Although the results are not yet publishable, significant progress has been made in developing this very challenging angular distributions analysis. A simple scheme for correcting for the angular acceptances of the spectrometer, trigger, and reconstruction has been developed and demonstrated. A generally applicable correction for the kinematically-dependent, rate-dependent reconstruction efficiency has been developed and applied to all current analyses on SeaQuest data. This rate-dependence correction was the first major hurdle in the path to publication of many preliminary SeaQuest results. The last remaining major correction for all analyses, but especially important for the angular parameter extraction, is the full characterization, rate-dependence correction, and subtraction of the combinatoric background contribution to the reconstructed dimuon sample. Independently, an intuitive, kinematic derivation of the single-event definitions of the Drell-Yan angular parameters has been developed under the assumption of unpolarized annihilating quarks within unpolarized nuclei. At O(αs), where the quarks remain co-planar with the hadrons in the photon rest frame, this kinematic method reproduces the Lam-Tung relation and derives an additional equality for µ2, which is only interpretable for single-event parameters. This method has been extended to the case of quark non- coplanarity, and the coplanar equalities become inequalities. A new equality was discovered, which should be obeyed by single-event parameters even in the case of a non-coplanar quark axis. The non-coplanar parameter relations have been used to derive constraints on the experimentally accessible values of λ and ν. These constraints are compared with existing data and have been found consistent, except in the cases where significant contributions from non-zero Boer-Mulders functions are expected. Finally, the kinematically- derived parameter definitions have been applied to high-precision CMS data. The relative contributions of the qq¯ and qg processes to the Z-boson “Drell-Yan” cross-section have been extracted. Further, an average measure of non-coplanarity, likely caused by O(α2) and higher processes, has been extracted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗