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At least 883 records · Page 49

Reduction of Raman Spectroscopy Data for H2-CO2-Air Tubular Flame Measurements

An approach of reducing spontaneous Raman spectroscopy data, based on the matrix inversion method which logically removes undesired sources of the Raman scattering signals including cross-talk due to the signals from other species, is discussed. The approach contains extensive calibration of temperature-dependent system response. The Raman spectra of several cold and hot calibration flames and their resulting calibration matrix are elaborated. The structure of H2-CO2-air tubular flames, in terms of major species (CO2, O2, N2, H2O, and H2) concentrations and temperature, was successfully measured with the optical technique. The Raman spectra data used in this study are taken from a uniquely designed experimental apparatus – a tubular burner and Raman spectroscopy system at Vanderbilt University. The characteristic uncertainties for chemical species are approximately ±2% by mole fraction for hot products and ±0.5% for room temperature reactants. The approach described here for hydrogen/air tubular flames may be adapted to hydrocarbon/air tubular flames when other necessary major species, for example, CH4 and CO for methane/air tubular flame, are considered in the whole process.

Raman Spectroscopy↗

Fast Scanning Probe Microscopy via Machine Learning: Non-Rectangular Scans with Compressed Sensing and Gaussian Process Optimization

Fast scanning probe microscopy enabled via machine learning allows for a broad range of nanoscale, temporally resolved physics to be uncovered. However, such examples for functional imaging are few in number. Here, using piezoresponse force microscopy (PFM) as a model application, a factor of 5.8 reduction in data collection using a combination of sparse spiral scanning with compressive sensing and Gaussian process regression reconstruction is demonstrated. It is found that even extremely sparse spiral scans offer strong reconstructions with less than 6% error for Gaussian process regression reconstructions. Further, the error associated with each reconstructive technique per reconstruction iteration is analyzed, finding the error is similar past ≈15 iterations, while at initial iterations Gaussian process regression outperforms compressive sensing. Finally, this study highlights the capabilities of reconstruction techniques when applied to sparse data, particularly sparse spiral PFM scans, with broad applications in scanning probe and electron microscopies.

36 MATERIALS SCIENCE↗

X-ray absorption spectroscopic study of the alumina supported Fe and FeMo catalysts for methane dehydrogenation

Nanoscale Fe (5%Fe/Al 2 O 3 ) and FeMo (4.5%Fe-0.5%Mo/Al 2 O 3 ) catalysts are prepared by precipitating metal components onto alumina and then reducing in hydrogen at 700 °C for 2 hrs. Here, the catalysts are characterized before and after their exposures to methane at 700 °C, employing ex-situ X-ray absorption spectroscopy (XAS) and X-ray diffraction techniques. XAS data of the as-prepared catalysts shows that, iron precipitates onto alumina as 6L-ferrihydrite, and Mo is present as molybdate (Mo(VI)O 4 2- ). The molybdate, which binds the alumina in the as-prepared FeMo catalyst, is partially reduced to MoO 2 . The reduction of iron to metallic state is incomplete because the ferrous iron binds the alumina, forming hercynite. After several hrs of methane exposure to both the catalysts at 700 °C, a major Fe 3 C and a graphite phase are observed only in the FeMo catalyst. The observation confirms that the Mo promotes more iron to an active Fe metal, a part of that metal converts to Fe 3 C and austenite (Fe x C). Concurrently, the MoO 2 converts to Mo-oxycarbide (MoO x C y ), the latter then carburize to Mo 2 C in the FeMo catalyst. The Fe metal, Mo-oxycarbide and metal carbides are mainly responsible for the conversion of methane to H 2 and carbon. At reaction temperature > 900 °C, the Mo carbide particles agglomerate, and the excess carbon deposits on this agglomerate leading to catalyst deactivation. The deactivated catalyst is regenerated with CO 2 treatment at 1000 °C to restore its initial oxide structure.

30 DIRECT ENERGY CONVERSION↗

Advanced data analysis in inertial confinement fusion and high energy density physics

Bayesian analysis enables flexible and rigorous definition of statistical model assumptions with well-characterized propagation of uncertainties and resulting inferences for single-shot, repeated, or even cross-platform data. This approach has a strong history of application to a variety of problems in physical sciences ranging from inference of particle mass from multi-source high-energy particle data to analysis of black-hole characteristics from gravitational wave observations. The recent adoption of Bayesian statistics for analysis and design of high-energy density physics (HEDP) and inertial confinement fusion (ICF) experiments has provided invaluable gains in expert understanding and experiment performance. In this Review, we discuss the basic theory and practical application of the Bayesian statistics framework. We highlight a variety of studies from the HEDP and ICF literature, demonstrating the power of this technique. Due to the computational complexity of multi-physics models needed to analyze HEDP and ICF experiments, Bayesian inference is often not computationally tractable. Two sections are devoted to a review of statistical approximations, efficient inference algorithms, and data-driven methods, such as deep-learning and dimensionality reduction, which play a significant role in enabling use of the Bayesian framework. We provide additional discussion of various applications of Bayesian and machine learning methods that appear to be sparse in the HEDP and ICF literature constituting possible next steps for the community. We conclude by highlighting community needs, the resolution of which will improve trust in data-driven methods that have proven critical for accelerating the design and discovery cycle in many application areas.

47 OTHER INSTRUMENTATION↗

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO 2 concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO 2 data relates to the correction of the soil carbon imbalance.

54 ENVIRONMENTAL SCIENCES↗

Data handling for the geometric correction of large images

Several geometric distortions are present in remotely sensed images depending on the type of sensors and the object being observed. It is often desirable to compensate for these distortions and store the images in reference to a standard coordinate system. Digital techniques for correction are versatile and introduce a minimum of radiometric errors. The main problems to be considered in this area are the determination of the corrective transformation, resampling, and the management of the large quantities of data. It is shown that, by a judicious rearrangement of the input data, considerable reductions in the required memory capacity can be achieved. The rearrangement can be accomplished in several stages. The method presented here is amenable to pipeline implementation for processing a continuous stream of images.

Ramapriyan, H. K.↗

A low cost, durable anti-reflective film for solar collectors

The physics of reflection reduction by thin films is briefly reviewed. Current techniques for the production of anti-reflective coatings are surveyed with respect to their applicabilities to solar panel covers. Techniques for the production of suitable anti-reflection coatings based on acid-hardened sodium silicate solutions are presented along with optical data for both acid-leached and silicate coatings

Pastirik, E. M.↗

Operational considerations for aerodynamic testing of large-scale wing sections in a simulated natural rain environment

One of the necessary areas of consideration for outdoor heavy rain testing is the effect of wind on both the simulated rain field and the quality and repeatability of the aerodynamic data. This paper discusses the data acquisition and subsequent reduction to nondimensional coefficients of lift and drag, with the appropriate correction for wind and rain field. Sample force data showing these effects are presented, along with estimates for accuracy and repeatability. The capability to produce high-quality data for rain drop size distribution using photographic and computerized image processing techniques was developed. Sample photographs depicting rain drop size are shown.

Campbell, Bryan A.↗

Particle data reduction in Japan

The characterization of atomized particles generated by various atomizer and the mechanics of their evaporation and combustion processes were studied. The need existed for visualizing the internal structure of flames including evaporation and combustion processes as well as for a better way of understanding spray particle generation mechanisms and internal structures. A particle sizer based on Fraunhofer diffraction for detecting particle size and in-line Fraunhofer holograms for observation of local spray particles were used. A novel visualizing technique based on Computer Technology was developed and is discussed.

Nakayama, Mitsushige↗

Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults

Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and inform manual maneuver decisions. Our multi-modal display of this information provides speech output to issue control surface failure warnings to a lesser-used communication channel and provides graphical displays with pilot-selectable !eve!s of details to issues additional information about the failure. We also describe a potential presentation for flight envelope reduction that can be viewed separately or integrated with an existing attitude indicator instrument. Preliminary results suggest that the inductive approach is capable of detecting that a control surface has failed and determining the type of fault. Furthermore, preliminary evaluations suggest that the interface discloses a concise summary of this information to the pilot.

Spikovska, Lilly↗

Elevated temperature microcantilever testing of fresh U-10Mo fuel

Proliferation concerns are the driving force to reduce the enrichment of research reactor fuel from highly enriched fuel to lower levels of enriched fuel. One promising fuel alloy that would enable a reduction in enrichment without greatly diminishing fuel performance is Uranium with 10 wt. % Molybdenum (U-10 wt-% Mo). While there is a large amount of data available on the microstructure and thermal properties of this new fuel type currently there is insufficient data available on the mechanical properties. Small scale mechanical testing techniques can be used to evaluate the mechanical properties of the as-fabricated U-10 wt% Mo components at their intended operating temperature which should improve the accuracy of the input parameters employed by modelers. In this study the mechanical properties of a U-10 wt% Mo fuel meat sample taken from an as-fabricated fuel plate for a new fuel design were evaluated using in-situ scanning electron microscopy microcantilever testing under varying temperatures between room temperature and 200 °C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Weak-Form Latent Space Dynamics Identification

This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI) algorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the data, then projects it onto test functions, and subsequently learns the local latent space models. Notably, WLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning techniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form ensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations. We demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples, including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid Burgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors consistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection simulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with LaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers' simulations compared to the corresponding full order model.

Choi, Youngsoo↗

Planetary geodetic control using satellite imaging

A new data type for planetary geodetic control using natural satellite imaging is presented. Spacecraft images of natural satellites against the planet give a direct tie between inertial space and surface features surrounding the satellite image. This technique is expected to offer a factor of 3-10 improvement in accuracy over present geodetic reduction for Mars. A specific example using Viking imaging of Phobos against Mars is given.

Duxbury, T. C.↗

Video detection and analysis techniques of transient astronomical phenomena

Low-light-level television systems have been utilized to gain information on meteors, aurorae, and other faint, transient astronomical phenomena. Such phenomena change not only their position as a function of time, but also their photometric and spectral characteristics in as little as 1/60 second, thus requiring unique methods of analysis. Data observed with television systems and recorded on video tape have been analyzed with a system utilizing both analog and digital techniques. Both off-the-shelf equipment and inhouse developments are used to isolate sequences of moving images and to store them in a form suitable for photometric and spectral reduction. Current emphasis of the analysis effort is directed at the measurement of the first-order emission lines of meteor spectra, the results of which will yield important compositional information concerning the nature of the impinging meteoroid.

Clifton, K. S.↗

Tip clearance flow in a compressor rotor passage at design and off-design conditions

The flow field in the tip clearance region of a compressor rotor at an off-design condition is reported in this paper. The earlier data at the design condition has also been re-interpreted and correlated with the blade and the flow parameters. The measurements inside the rotor tip region are acquired using a miniature hot wire sensor of 'V' configuration. The instantaneous velocity data is analyzed by the ensemble averaging technique to derive the blade-to-blade velocity field at various axial and radial locations between the rotor tip and the casing. The flow and the blade pressure data at the design condition are compared with the data at the off-design condition (lower blade loading). In addition to a reduction in the leakage velocities, its chordwise variation is also altered substantially at the lower blade loading.

Lakshminarayana, B.↗

Phased arrays for satellites and the TDRSS antennas

The design and performance of satellite phased-array systems are examined by considering several specific antennas built for spacecraft use. Particular consideration is given to: (1) the JARED (Jammer Reduction Antenna System) antenna, and adaptive phased array which can be used to null jammer signals while providing coverage to specific user areas; (2) the algorithm used in the JARED antenna; and (3) a technique that can be used to detect and locate jammers. The antennas used by the Tracking and Data Relay Satellite System (TDRSS) are then described. A significant aspect of the TDRSS is the multiple access antenna which is a 30-element phased array, providing a single steered beam on transmit and the ability to receive data from 20 simultaneous users. Also included on the TDRSS is a mesh deployable reflector and a C-band and K-band communications system.

Imbriale, W. A.↗

A data base and analysis program for shuttle main engine dynamic pressure measurements

A dynamic pressure data base management system is described for measurements obtained from space shuttle main engine (SSME) hot firing tests. The data were provided in terms of engine power level and rms pressure time histories, and power spectra of the dynamic pressure measurements at selected times during each test. Test measurements and engine locations are defined along with a discussion of data acquisition and reduction procedures. A description of the data base management analysis system is provided and subroutines developed for obtaining selected measurement means, variances, ranges and other statistics of interest are discussed. A summary of pressure spectra obtained at SSME rated power level is provided for reference. Application of the singular value decomposition technique to spectrum interpolation is discussed and isoplots of interpolated spectra are presented to indicate measurement trends with engine power level. Program listings of the data base management and spectrum interpolation software are given. Appendices are included to document all data base measurements.

Coffin, T.↗

Analysis of the Westland Data Set

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗