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Ab Initio Characterization of Triatomic Bromine Molecules of Potential Interest in Stratospheric Chemistry

The equilibrium structures, harmonic vibrational frequencies, quadratic force fields, dipole moments, and IR intensities of several triatomic bromine compounds of known or potential importance in stratospheric ozone depletion chemistry have been determined using the CCSD(T) electron correlation method in conjunction with a basis set of triple zeta double polarized (TZ2P) quality. Specifically, the molecules included in the present study are HOBr, HBrO, FOBr, FBrO, BrNO, BrON, Br2O, BrBrO, BrCN, BrNC, ClOBr, ClBrO, and BrClO. Very accurate isomeric energy differences have also been determined at the CCSD(T) level with atomic natural orbital basis sets that include through g-type functions. In most cases, the isomer with a normal neutral Lewis dot structure is the lowest energy form, with the single exception that FBRO is predicted to be 11.1 kcal/mol (0 K) lower in energy than FOBr. In all cases, however, the hypervalent isomer is more stable relative to the isomer with a normal Lewis dot structure as compared to the chlorine analogs. Consistent with this observation, the energy of the last three molecules given above increases in the order ClOBr less than ClBrO less than BrClO. The CCSD(T)/TZ2P geometries and vibrational frequencies are in good agreement with the available experimental data. Heats of formation are determined for all species using a combination of theoretical isomeric, homodesmic, and isodesmic reaction energies. The accuracy of these quantities is ultimately dependent on the reliability of the experimental heat of formation of HOBr.

Lee. Timothy J.↗

Ab Initio Characterization of Triatomic Bromine Molecules of Potential Interest in Stratospheric Chemistry

The equilibrium structures, harmonic vibrational frequencies, quadratic force fields, dipole moments, and IR intensities of several triatomic bromine compounds of known or potential importance in stratospheric ozone depletion chemistry have been determined using the CCSD(T) electron correlation method in conjunction with a basis set of triple zeta double polarized (TZ2P) quality. Specifically, the molecules included in the present study are HOBr, HBrO, FOBr, FBrO, BrNO, BrON, Br2O, BrBrO, BrCN, BrNC, ClOBr, ClBrO, and BrClO. Very accurate isomeric energy differences have also been determined at the CCSD(T) level with atomic natural orbital basis sets that include through g-type functions. In most cases, the isomer with a normal neutral Lewis dot structure is the lowest energy form, with the single exception that FBrO is predicted to be 11.1 kcal/mol (0 K) lower in energy than FOBr. In all cases, however, the hypervalent isomer is more stable relative to the isomer with a normal Lewis dot structure as compared to the chlorine analogs. Consistent with this observation, the energy of the last three molecules given above increases in the order ClOBr less than ClBrO less than BrClO. The CCSD(T)/TZ2P geometries and vibrational frequencies are in good agreement with the available experimental data. Heats of formation are determined for all species using a combination of theoretical isomeric, homodesmic, and isodesmic reaction energies. The accuracy of these quantities is ultimately dependent on the reliability of the experimental heat of formation of HOBr.

Lee, Timothy J.↗

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗

Focus determination for the James Webb Space Telescope Science Instruments: A Survey of Methods

The James Webb Space Telescope (JWST) is a segmented deployable telescope that will require on-orbit alignment using the Near Infrared Camera as a wavefront sensor. The telescope will be aligned by adjusting seven degrees of freedom on each of 18 primary mirror segments and five degrees of freedom on the secondary mirror to optimize the performance of the telescope and camera at a wavelength of 2 microns. With the completion of these adjustments, the telescope focus is set and the optical performance of each of the other science instruments should then be optimal without making further telescope focus adjustments for each individual instrument. This alignment approach requires confocality of the instruments after integration and alignment to the composite metering structure, which will be verified during instrument level testing at Goddard Space Flight Center with a telescope optical simulator. In this paper, we present the results from a study of several analytical approaches to determine the focus for each instrument. The goal of the study is to compare the accuracies obtained for each method, and to select the most feasible for use during optical testing.

Davila, Pamela S.↗

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBs was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)

60 APPLIED LIFE SCIENCES↗

Metal Hydroxide and Oxyhydroxide Gas Database

In a high temperature combustion situation such as a gas turbine or rocket engine, combustion products include water vapor. This water vapor reacts with oxides in the hot-gas-path to form volatile hydroxides and oxyhydroxides. The oxides may be structural oxide components or protective oxides on alloys or non-oxide ceramics. In either case, this enhanced volatilization leads to degradation of components. Reliable thermochemical data for many metal hydroxides and oxyhydroxides has not been available. We review a database put together at NASA over many years based on experimental and ab initio computations for thermochemical data of Al, Si, Ti, Cr, Mn, Y, Zr, La, Ta, Gd, and Yb hydroxides and oxyhydroxides. Experimental methods for measuring thermodynamic quantities of metal hydroxides and oxyhydroxides are limited since the required high temperatures and high pressures preclude many conventional methods. Nonetheless, transpiration has proven a valuable tool in our laboratories for the Si-O-H, Cr-O-H, and Ti-O-H systems. Data are analyzed with second and third law methods. These data can be leveraged with quantum chemistry to provide reliable free energy functions for the third law calculation and comparison to the derived enthalpies of formation. Both wave function and DFT methods can be utilized for deriving the thermodynamic functions for the various metal hydroxides and oxyhydroxides. We have found that, in general, reasonable molecular geometries and spectroscopic data can be derived with a relatively low level of theory, i.e. DFT with the B3LYP functional. Accurate calculations of the enthalpy of formation require higher levels of theory, such as the Coupled Cluster, Singles, Doubles, and perturbative Triples CCSD(T) approach with complete basis sets (CBS). Also, corrections for hindered rotations and anharmonicity are necessary. For some symmetries, the anharmonic correction has proven to be a challenge and we have found that this is only treated properly by certain codes. The database lists the fHo(298), So(298), and Cp in the form Cp = A + BT + CT2 + D/T + E/T2, where A, B, C, D, and E are the fitting constants. Thus, it can be easily used in any of the common computational thermochemistry codes. To date, the database contains 51 gaseous species of the formula MOx(OH)y.

Metal Hydroxides↗

Spectroscopic and theoretical studies of UN and UN +

The low-energy electronic states of UN and UN+ have been examined using high-level electronic structure calculations and two-color photoionization techniques. The experimental measurements provided an accurate ionization energy for UN (IE = 50 802 +/- 5 cm -1 ). Spectra for UN+ yielded ro-vibrational constants and established that the ground state has the electronic angular momentum projection omega = 4. Ab initio calculations were carried out using the spin-orbit state interacting approach with the complete active space second-order perturbation theory method. A series of correlation consistent basis sets were used in conjunction with small-core relativistic pseudopotentials on U to extrapolate to the complete basis set limits. The results for UN correctly obtained an omega = 3.5 ground state and demonstrated a high density of configurationally related excited states with closely similar ro-vibrational constants. Similar results were obtained for UN + , with reduced complexity owing to the smaller number of outer-shell electrons. The calculated IE for UN was in excellent agreement with the measured value. Improved values for the dissociation energies of UN and UN + , as well as their heats of formation, were obtained using the Feller-Peterson-Dixon composite thermochemistry method, including corrections up through coupled cluster singles, doubles, triples and quadruples. An analysis of the ab initio results from the perspective of the ligand field theory shows that the patterns of electronic states for both UN and UN + can be understood in terms of the underlying energy level structure of the atomic metal ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic parameter inference in stochastic mesoscopic modeling

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Synergistic Effects of Turbine Wakes and Atmospheric Stability on Power Production at an Onshore Wind Farm

This report examines the complex interactions between atmospheric stability and turbine-induced wakes on downwind turbine wind speed and power production at a West Coast North American multi-MW wind farm. Wakes are generated when the upwind flow field is distorted by the mechanical movement of the wind turbine blades. This has two consequences for downwind turbines: (1) the downwind turbine encounters wind flows with reduced velocity and (2) the downwind turbine encounters increased turbulence across multiple length scales via mechanical turbulence production by the upwind turbine. This increase in turbulence on top of ambient levels may increase aerodynamic fatigue loads on the blades and reduce the lifetime of turbine component parts. Furthermore, ambient atmospheric conditions, including atmospheric stability, i.e., thermal stratification in the lower boundary layer, play an important role in wake dissipation. Higher levels of ambient turbulence (i.e., a convective or unstable boundary layer) lead to higher turbulent mixing in the wake and a faster recovery in the velocity flow field downwind of a turbine. Lower levels of ambient turbulence, as in a stable boundary layer, will lead to more persistent wakes. The wake of a wind turbine can be divided into two regions: the near wake and far wake, as illustrated in Figure 1. The near wake is formed when the turbine structure alters the shape of the flow field and usually persists one rotor diameter (D) downstream. The difference between the air inside and outside of the near wake results in a shear layer. This shear layer thickens as it moves downstream and forms turbulent eddies of multiple length scales. As the wake travels downstream, it expands depending on the level of ambient turbulence and meanders (i.e., travels in non-uniform path). Schepers estimates that the wake is fully expanded at a distance of 2.25 D and the far wake region begins at 2-5 D downstream. The actual distance traveled before the wake recovers to its inflow velocity is dependent on the amount ambient turbulence, the amount of wind shear, and topographical and structural effects. The maximum velocity deficit is estimated to occur at 1-2 D but can be longer under low levels of ambient turbulence. Our understanding of turbine wakes comes from wind tunnel experiments, field experiments, numerical simulations, and from studies utilizing both experimental and modeling methods. It is well documented that downwind turbines in multi-Megawatt wind farms often produce less power than upwind turbine rows. These wake-induced power losses have been estimated from 5% to up to 40% depending on the turbine operating settings (e.g., thrust coefficient), number of turbine rows, turbine size (e.g., rotor diameter and hub-height), wind farm terrain, and atmospheric flow conditions (e.g., ambient wind speed, turbulence, and atmospheric stability). Early work by Elliott and Cadogan suggested that power data for different turbulent conditions be segregated to distinguish the effects of turbulence on wind farm power production. This may be especially important for downwind turbines within wind farms, as chaotic and turbulent wake flows increase stress on downstream turbines. Impacts of stability on turbine wakes and power production have been examined for a flat terrain, moderate size (43 turbines) wind farm in Minnesota and for an offshore, 80 turbine wind farm off the coast of Denmark. Conzemius found it difficult to distinguish wakes (i.e., downwind velocity deficits) when the atmosphere was convective as large amounts of scatter were present in the turbine nacelle wind speed data. This suggested that high levels of turbulence broke-up the wake via large buoyancy effects, which are generally on the order of 1 km in size. On the other hand, they found pronounced wake effects when the atmosphere was very stable and turbulence was either suppressed or the length scale was reduced as turbulence in this case was mechanically produced (i.e., friction forces). This led to larger reductions at downwind turbines and maximum velocity (power) deficits reached up to 50% (70%) during strongly stable conditions. At an offshore Danish wind farm, Hansen et al. found a strong negative correlation between power deficit and ambient turbulence intensity (i.e., atmospheric stability). Under convective conditions, when turbulence levels were relatively high, smallest power deficits were observed. Power deficits approaching 35 to 40% were found inside the wind farm during stable conditions.

17 WIND ENERGY↗

Methods for Characterizing Fine Particulate Matter Using Satellite Remote-Sensing Data and Ground Observations: Potential Use for Environmental Public Health Surveillance

This study describes and demonstrates different techniques for surfacing daily environmental / hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5) for the purpose of integrating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC s) pilot study of Health and Environment Linked for Information Exchange (HELIX)-Atlanta. It described a methodology for estimating ground-level continuous PM2.5 concentrations using B-Spline and inverse distance weighting (IDW) surfacing techniques and leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement The Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA s satellite data. Hazard data have been processed to derive the surrogate exposure PM2.5 estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM2.5 not only provides a more complete daily representation of PM2.5 than either data set alone would allow, but it also reduces the errors in the PM2.5 estimated surfaces. The results of this paper have shown that the daily IDW PM2.5 surfaces had smaller errors, with respect to observations, than those of the B-Spline surfaces in the year studied. However the IDW mean annual composite surface had more numerical artifacts, which could be due to the interpolating nature of the IDW that assumes that the maxima and minima can occur only at the observation points. Finally, the methods discussed in this paper improve temporal and spatial resolutions and establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with good accuracy levels is critical.

Al-Hamdan, Mohammad Z.↗

Scale-adaptive tensor algebra for local many-body methods of electronic structure theory

While the formalism of multiresolution analysis (MRA), based on wavelets and adaptive integral representations of operators, is actively progressing in electronic structure theory (mostly on the independent-particle level and, recently, second-order perturbation theory), the concepts of multiresolution and adaptivity can also be utilized within the traditional formulation of correlated (many-particle) theory which is based on second quantization and the corresponding (generally nonorthogonal) tensor algebra. In this paper, we present a formalism called scale-adaptive tensor algebra (SATA) which exploits an adaptive representation of tensors of many-body operators via the local adjustment of the basis set quality. Given a series of locally supported fragment bases of a progressively lower quality, we formulate the explicit rules for tensor algebra operations dealing with adaptively resolved tensor operands. The formalism suggested is expected to enhance the applicability and reliability of local correlated many-body methods of electronic structure theory, especially those directly based on atomic orbitals (or any other localized basis functions).

Liakh, Dmitry I↗

Niobium coaxial cavities with internal quality factors exceeding 1.4 × 10 9 for circuit quantum electrodynamics

Group-V materials such as niobium and tantalum have become popular choices for extending the performance of circuit quantum electrodynamics (cQED) platforms, allowing for quantum processors and memories with reduced error rates and more modes. The complex surface chemistry of niobium, however, makes identifying the main modes of decoherence difficult at millikelvin temperatures and single-photon powers. We use niobium coaxial quarter-wave cavities to study the impact of etch chemistry, prolonged atmospheric exposure, and the significance of cavity conditions prior to and during cooldown—in particular, niobium hydride evolution—on single-photon coherence. We demonstrate cavities with quality factors Q int ≳ 1.4 × 10 9 in the single-photon regime, a 15-fold improvement over aluminum cavities of the same geometry. We rigorously quantify the sensitivity of our fabrication process to various loss mechanisms and demonstrate a two- to fourfold reduction in the two-level system loss tangent and a three- to fivefold improvement in the residual resistance over traditional buffered chemical polishing etching techniques. Finally, we demonstrate transmon integration and coherent cavity control while maintaining a cavity coherence of 11.3 ms. The accessibility of our method, which can be easily replicated in academic laboratory settings, together with the demonstration of its performance, mark an advancement in three-dimensional cQED.

Oriani, Andrew E. [Chicago U., EFI; Chicago U.] (O↗

SU-E-T-422: Fast Analytical Beamlet Optimization for Volumetric Intensity-Modulated Arc Therapy

Purpose: To implement a fast optimization algorithm on CPU/GPU heterogeneous computing platform and to obtain an optimal fluence for a given target dose distribution from the pre-calculated beamlets in an analytical approach. Methods: The 2D target dose distribution was modeled as an n-dimensional vector and estimated by a linear combination of independent basis vectors. The basis set was composed of the pre-calculated beamlet dose distributions at every 6 degrees of gantry angle and the cost function was set as the magnitude square of the vector difference between the target and the estimated dose distribution. The optimal weighting of the basis, which corresponds to the optimal fluence, was obtained analytically by the least square method. Those basis vectors with a positive weighting were selected for entering into the next level of optimization. Totally, 7 levels of optimization were implemented in the study.Ten head-and-neck and ten prostate carcinoma cases were selected for the study and mapped to a round water phantom with a diameter of 20cm. The Matlab computation was performed in a heterogeneous programming environment with Intel i7 CPU and NVIDIA Geforce 840M GPU. Results: In all selected cases, the estimated dose distribution was in a good agreement with the given target dose distribution and their correlation coefficients were found to be in the range of 0.9992 to 0.9997. Their root-mean-square error was monotonically decreasing and converging after 7 cycles of optimization. The computation took only about 10 seconds and the optimal fluence maps at each gantry angle throughout an arc were quickly obtained. Conclusion: An analytical approach is derived for finding the optimal fluence for a given target dose distribution and a fast optimization algorithm implemented on the CPU/GPU heterogeneous computing environment greatly reduces the optimization time.

60 APPLIED LIFE SCIENCES↗

An {alpha}-cluster model for {sub {Lambda}}{sup 9}Be spectroscopy

An {alpha}-cluster model is applied to study low-lying spectrum of the {sub {Lambda}}{sup 9}Be hypernucleus. The three-body {alpha}{alpha}{Lambda} problem is numerically solved by the Faddeev equations in configuration space using phenomenological pair potentials. We found a set of the potentials that reproduces experimental data for the ground state (1/2{sup +}) binding energy and excitation energy of the 5/2{sup +} and 3/2{sup +} states, simultaneously. This set includes the Ali-Bodmer potential of the version 'e' for {alpha}{alpha} and modified Tang-Herndon potential for {alpha}{Lambda} interactions. The spin-orbit {alpha}{Lambda} interaction is given by modified Scheerbaum potential. Low-lying energy levels are evaluated applying a variant of the analytical continuation method in the coupling constant. It is shown that the spectral properties of {sub {Lambda}}{sup 9}Be can be classified as an analog of {sup 9}Be spectrum with the exception of several 'genuine hypernuclear states'. This agrees qualitatively with previous studies. The results are compared with experimental data and new interpretation of the spectral structure is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Exploring Heterogeneous Multicore Architectures for Advanced Embedded Uncertainty Quantification

We explore rearrangements of classical uncertainty quantification methods with the aim of achieving higher aggregate performance for uncertainty quantification calculations on emerging multicore and many core architectures. We show a rearrangement of the stochastic Galerkin method leads to improved performance and scalability on several computational architectures whereby uncertainty information is propagated at the lowest levels of the simulation code improving memory access patterns, exposing new dimensions of fine grained parallelism, and reducing communication. We also develop a general framework for implementing such rearrangements for a diverse set of uncertainty quantification algorithms as well as computational simulation codes to which they are applied.

97 MATHEMATICS AND COMPUTING↗

The MidAmerica Regional Microgrid Education and Training (MARMET) Consortium

The primary goal of this project was to integrate cutting-edge research and advanced instructional methods to create a flexible, evolving approach to microgrid and distributed energy resources training for all levels of student. This goal entailed the rapid development of modular material to capture and reflect the newest trends in electric power microgrid engineering and to make it available in traditional and non-traditional settings. It was our goal to develop course material that can be readily integrated into either existing courses or organized into new courses. The target audiences include technicians, contractors and consultants, inspectors, policy makers, supervisors, and engineers and undergraduate and graduate students. The main project objectives were to: 1) Perform a gap analysis to identify the research/educational/training needs and define specific implementation plans for these activities in distributed technology and Smart Grid power engineering by working with Department of Energy, the National Network Administrator (NNA) and other Distributed Technology Training Consortia (DTTC). 2) Develop learning content related to, and driven by, microgrid research, consisting of one or more multimedia-based modules. Over the life of the project MARMET provided training to 11,012 students and developed 154,432 contact hours of material (see the IREC NNA, DE-EE0006342, final project report for added details on MARMET evaluation and assessment metrics, as well as an overview of the entire GEARED network. 3) Provide a variety of delivery mechanisms and venues for face-to-face and on-line instruction in power system engineering and related smart grid operations, including university-based courses, short courses, and workshops. 4) Assemble and engage highly-qualified advisory and steering committees of experts from utilities, universities, national laboratories, and product suppliers for this DTTC, to guide and advise the activities of the DTTC, and to assist in creating student internships, coops, research projects and academic competitions for GEARED students within the DTTC and nationally. 5) Convene regular meetings of Consortia partners to disseminate research results among the participants (universities, utilities, and industry). 6) Develop recruitment mechanisms to publicize GEARED student opportunities and highlight the educational benefits of GEARED participation to assure long-term sustainability of student recruitment and retention. 7) Participate in GEARED National Network activities to identify and adopt best practices across all GEARED consortia. 8) Organize, host and manage at least one annual Student-Centered Research Conference on behalf of the GEARED Network during the period of performance; participate in each annual national Student-Centered Research Conference.

14 SOLAR ENERGY↗

A new scheme for multidimensional line transfer. II - ETLA method in one dimension with application to iron K-alpha lines

The 1D version of the radiation hydrodynamics computer code ALTAIR is discribed. It is an implementation of the equivalent two-level atom method, and also incorporates a variety of other iterative techniques to achieve a fast, accurate solution of the problem of coupled atomic kinetics and radiative transfer. All the techniques are described in sufficient detail to enable their use by others. The application of the program is illustrated by a set of calculations of the iron X-ray emission spectrum from intercloud hot gas that may exist in the broad-line region of active galactic nuclei. These calculations demonstrate that such spectra may be a rich load to mine for information about the hot gas in AGNs, and also that the concept of 'the iron K-alpha line' inadequately depicts the spectrum.

Castor, John I.↗

An Integrated Planning Representation Using Macros, Abstractions, and Cases

Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.

Baltes, Jacky↗