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A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data

Theoretical and modeling studies indicate that small-scale drag due to breaking gravity waves is likely to be of considerable importance for the circulation in the middle atmospheric region (approximately 40-100 km altitude) on Mars. Recent earth-based spectroscopic observations have provided evidence for the existence of circulation features, in particular, a warm winter polar region, associated with gravity wave drag. Since the Mars Observer PMIRR experiment will obtain temperature profiles extending from the surface up to about 80 km altitude, it will be extensively sampling middle atmospheric regions in which gravity wave drag may play a dominant role. Estimating the drag then becomes crucial to the estimation of the atmospheric winds from the PMIRR-observed temperatures. An interative diagnostic model based upon one previously developed and tested with earth satellite temperature data will be applied to the PMIRR measurements to produce estimates of the small-scale zonal drag and three-dimensional wind fields in the Mars middle atmosphere. This model is based on the primitive equations, and can allow for time dependence (the time tendencies used may be based upon those computed in a Fast Fourier Mapping procedure). The small-scale zonal drag is estimated as the residual in the zonal momentum equation; the horizontal winds having first been estimated from the meridional momentum equation and the continuity equation. The scheme estimates the vertical motions from the thermodynamic equation, and thus needs estimates of the diabatic heating based upon the observed temperatures. The latter will be generated using a radiative model. It is hoped that the diagnostic scheme will be able to produce good estimates of the zonal gravity wave drag in the Mars middle atmosphere, estimates that can then be used in other diagnostic or assimilation efforts, as well as more theoretical studies.

Barnes, J. R.↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fever droplets, larger size develop due to greater condencational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.

Tao, Wei-Kuo↗

Preparation, Identification, and Low-Temperature Infrared Spectra of Two Elusive Crystalline Nitrile Ices

Infrared (IR) spectra of the alkyl nitrile ices CH3CN and CH3CH2CN are relevant to the study of the low- temperature chemistry of objects within and beyond the Solar System, but the thermodynamically favored low-temperature crystalline phases of these compounds have not been presented and identified in the planetary- sciences literature. Moreover, there is a large variation in the published IR spectra of these two icy solids, including spectra that are used for the analyses of spacecraft data from the Voyager and Cassini missions. Here the IR spectra of the low-temperature crystalline forms of CH3CN and CH3CH2CN, which are the thermodynamically stable phases at Titan temperatures, are presented for the first time with all samples being made by vapor-phase deposition. Conditions are described for producing these ice phases for both compounds, and new measurements are reported of ice density and refractive index, quantities needed to compute IR absorption coefficients, band strengths, optical constants, and, ultimately, nitrile abundances in extraterrestrial environments. Comparisons are drawn between CH3CN and CH3CH2CN, an earlier prediction on their similar crystallization behaviors is verified, and previous work is examined in light of these new results, including a counterintuitive observation in which the low-temperature phase of an ice is made by heating a high-temperature phase. Applications and extensions are described.

Hudson, Reggie L.↗

Preparation, Identification, and Low-Temperature Infrared Spectra of Two Elusive Crystalline Nitrile Ices

Infrared (IR) spectra of the alkyl nitrile ices CH3CN and CH3CH2CN are relevant to the study of the low-temperature chemistry of objects within and beyond the Solar System, but the thermodynamically favored low-temperature crystalline phases of these compounds have not been presented and identified in the planetary-sciences literature. Moreover, there is a large variation in the published IR spectra of these two icy solids, including spectra that are used for the analyses of spacecraft data from the Voyager and Cassini missions. Here the IR spectra of the low-temperature crystalline forms of CH3CN and CH3CH2CN, which are the thermodynamically stable phases at Titan temperatures, are presented for the first time with all samples being made by vapor-phase deposition. Conditions are described for producing these ice phases for both compounds, and new measurements are reported of ice density and refractive index, quantities needed to compute IR absorption coefficients, band strengths, optical constants, and, ultimately, nitrile abundances in extraterrestrial environments. Comparisons are drawn between CH3CN and CH3CH2CN, an earlier prediction on their similar crystallization behaviors is verified, and previous work is examined in light of these new results, including a counter-intuitive observation in which the low-temperature phase of an ice is made by heating a high-temperature phase. Applications and extensions are described.

Reggie L Hudson↗

Preparation, Identification, and Low-Temperature Infrared Spectra of Two Elusive Crystalline Nitrile Ices

Infrared (IR) spectra of the alkyl nitrile ices CH3CN and CH3CH2CN are relevant to the study of the low-temperature chemistry of objects within and beyond the Solar System, but the thermodynamically favored low-temperature crystalline phases of these compounds have not been presented and identified in the planetary-sciences literature. Moreover, there is a large variation in the published IR spectra of these two icy solids, including spectra that are used for the analyses of spacecraft data from the Voyager and Cassini missions. Here the IR spectra of the low-temperature crystalline forms of CH3CN and CH3CH2CN, which are the thermodynamically stable phases at Titan temperatures, are presented for the first time with all samples being made by vapor-phase deposition. Conditions are described for producing these ice phases for both compounds, and new measurements are reported of ice density and refractive index, quantities needed to compute IR absorption coefficients, band strengths, optical constants, and, ultimately, nitrile abundances in extraterrestrial environments. Comparisons are drawn between CH3CN and CH3CH2CN, an earlier prediction on their similar crystallization behaviors is verified, and previous work is examined in light of these new results, including a counter-intuitive observation in which the low-temperature phase of an ice is made by heating a high-temperature phase. Applications and extensions are described.

Ices, IR spectroscopy, Titan, organic chemistry, i↗

An Object-oriented Computer Code for Aircraft Engine Weight Estimation

Reliable engine-weight estimation at the conceptual design stage is critical to the development of new aircraft engines. It helps to identify the best engine concept amongst several candidates. At NASA Glenn (GRC), the Weight Analysis of Turbine Engines (WATE) computer code, originally developed by Boeing Aircraft, has been used to estimate the engine weight of various conceptual engine designs. The code, written in FORTRAN, was originally developed for NASA in 1979. Since then, substantial improvements have been made to the code to improve the weight calculations for most of the engine components. Most recently, to improve the maintainability and extensibility of WATE, the FORTRAN code has been converted into an object-oriented version. The conversion was done within the NASA s NPSS (Numerical Propulsion System Simulation) framework. This enables WATE to interact seamlessly with the thermodynamic cycle model which provides component flow data such as airflows, temperatures, and pressures, etc. that are required for sizing the components and weight calculations. The tighter integration between the NPSS and WATE would greatly enhance system-level analysis and optimization capabilities. It also would facilitate the enhancement of the WATE code for next-generation aircraft and space propulsion systems. In this paper, the architecture of the object-oriented WATE code (or WATE++) is described. Both the FORTRAN and object-oriented versions of the code are employed to compute the dimensions and weight of a 300- passenger aircraft engine (GE90 class). Both versions of the code produce essentially identical results as should be the case. Keywords: NASA, aircraft engine, weight, object-oriented

Tong, Michael T.↗

An Object-Oriented Computer Code for Aircraft Engine Weight Estimation

Reliable engine-weight estimation at the conceptual design stage is critical to the development of new aircraft engines. It helps to identify the best engine concept amongst several candidates. At NASA Glenn Research Center (GRC), the Weight Analysis of Turbine Engines (WATE) computer code, originally developed by Boeing Aircraft, has been used to estimate the engine weight of various conceptual engine designs. The code, written in FORTRAN, was originally developed for NASA in 1979. Since then, substantial improvements have been made to the code to improve the weight calculations for most of the engine components. Most recently, to improve the maintainability and extensibility of WATE, the FORTRAN code has been converted into an object-oriented version. The conversion was done within the NASA's NPSS (Numerical Propulsion System Simulation) framework. This enables WATE to interact seamlessly with the thermodynamic cycle model which provides component flow data such as airflows, temperatures, and pressures, etc., that are required for sizing the components and weight calculations. The tighter integration between the NPSS and WATE would greatly enhance system-level analysis and optimization capabilities. It also would facilitate the enhancement of the WATE code for next-generation aircraft and space propulsion systems. In this paper, the architecture of the object-oriented WATE code (or WATE++) is described. Both the FORTRAN and object-oriented versions of the code are employed to compute the dimensions and weight of a 300-passenger aircraft engine (GE90 class). Both versions of the code produce essentially identical results as should be the case.

Tong, Michael T.↗

Counterdiabatic Driving with Performance Guarantees

Counterdiabatic (CD) driving has the potential to speed up adiabatic quantum state preparation by suppressing unwanted excitations. However, existing approaches either require intractable classical computations or are based on approximations that do not have performance guarantees. We propose and analyze a nonvariational, system-agnostic CD expansion method and analytically show that it converges exponentially quickly in the expansion order. In finite systems, the required resources scale inversely with the spectral gap, which we argue is asymptotically optimal. To extend our method to the thermodynamic limit and suppress errors stemming from high-frequency transitions, we leverage finite-time adiabatic protocols. In particular, we show that a time determined by the quantum speed limit is sufficient to prepare the desired ground state, without the need to optimize the adiabatic trajectory. Numerical tests of our method on the quantum Ising chain show that our method can outperform state-of-the-art variational CD approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Resolving the Chemical Formula of Nesquehonite via NMR Crystallography, DFT Computation, and Complementary Neutron Diffraction

Nesquehonite is a magnesium carbonate mineral relevant to carbon sequestration envisioned for carbon capture and storage of CO 2 . Its chemical formula remains controversial today, assigned as either a hydrated magnesium carbonate [MgCO 3 · 3H 2 O], or a hydroxy- hydrated- magnesium bicarbonate [Mg(HCO 3 )OH · 2H 2 O]. Here, the resolution of this controversy is central to understanding this material‘s thermodynamic, phase, and chemical behavior. In an NMR crystallography study, using rotational-echo double-resonance 13 C{ 1 H} (REDOR), 13 C- 1 H distances are determined with precision, and the combination of 13 C static NMR lineshapes and density functional theory (DFT) calculations are used to model different H atomic coordinates. [MgCO 3 · 3H 2 O] is found to be accurate, and evidence from neutron powder diffraction bolsters these assignments. Refined H positions can help understand how H-bonding stabilizes this structure against dehydration to MgCO 3 . More broadly, these results illustrate the power of NMR crystallography as a technique for resolving questions where X-ray diffraction is inconclusive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-scale computational screening and mechanistic insights of cyclic amines as solvents for improved lignocellulosic biomass processing

A computational screening workflow for the efficient deconstruction of cellulose, lignin and hemicellulose fractions of lignocellulosic biomass using cyclic amines as solvents. Lignocellulosic biomass is a promising feedstock for production of affordable fuels and chemicals from renewable resources. Effective solubilization and subsequent deconstruction of its cellulose, hemicellulose, and lignin fractions is essential for the viability of future biorefineries. This study used quantum chemistry-based equilibrium thermodynamics methods to evaluate the potential of 650 cyclic amines to solubilize cellulose, hemicellulose, and lignin. The activity coefficients of solvent - biopolymer interactions were predicted using the COSMO-RS (COnductor-like Screening MOdel for Real Solvents) method and used to identify cyclic amines that can efficiently dissolve and extract selective fractions of biopolymers during biomass pretreatment. Among the 650 cyclic amines, 1-piperazineethanmaine was predicted to be an effective solvent for extracting all three polymers and was experimentally shown to achieve the highest lignin removal (97.1%). Non-covalent interaction, reduced density gradient and quantum chemical calculations were performed to elucidate the dissolution mechanism of lignin, cellulose and hemicellulose and gain further molecular level insights into the interactions between the cyclic amines and biomass polymers that promote efficient solubilization and extraction. These analyses indicated that 1-piperazineethanmaine and 1-methylimidazole make noncovalent van der Waals, electrostatic interactions and hydrogen bonding with lignin, leading to enhanced lignin removal, while the strong intramolecular hydrogen bonding interactions in cellulose and hemicellulose result in weaker solvent-biopolymer interactions. Overall, the computational approach provided an efficient method for identifying cyclic amines tailored for optimal biomass pretreatment and resulted in the identification of a potential new class of solvents for effective biomass pretreatment.

Kumar, Nikhil↗

High-throughput design of high-performance lightweight high-entropy alloys

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

36 MATERIALS SCIENCE↗

Density functional theory calculations of the thermodynamic and kinetic properties of point defects in β -U

Density functional theory (DFT) calculations of the thermodynamic and kinetic properties of point defects in the β phase of uranium are reported. Defect energies and entropies were calculated using 2 x 2 x 2 supercells and the Generalized Gradient Approximation (GGA) of Perdew-Burke-Ernzerhof (PBE) for the exchange-correlation potential. Due to computational cost, calculations of the vibrational properties governing entropies were performed by only displacing atoms within (roughly) the 3rd or 4th nearest neighbor shell of the defect, which implicitly assumes that atoms beyond this distance are unaffected by the defect. Migration barriers were estimated by nudged elastic band (NEB) calculations. The low symmetry of the β-U phase (the unit cell is tetragonal and contains 30 atoms) results in many point defect configurations and even more migration pathways. A connectivity map, starting from the most stable point defects, was developed in order to identify the rate-limiting step controlling the net diffusion rate in each crystallographic direction. The uranium self-diffusivity tensor was calculated by combining the defect formation energies, entropies, migration barriers and attempt frequencies. The fastest diffusion rate was determined to be a vacancy mechanism in the z crystallographic direction. The predicted uranium self-diffusivity for this mechanism agrees well with available experimental data. Finally, the diffusion mechanisms and rates identified in this study will inform fuel performance models of swelling and gas evolution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Synthetic Accessibility and Sodium Ion Conductivity of the Na8–x A x P2O9 (NAP) High-Temperature Sodium Superionic Conductor Framework

Advancement of solid-state electrolytes (SSEs) for all solid-state batteries typically focuses on modification of a known structural framework to improve conductivity, e.g., cation substitution for an immobile ion or varying the concentration of the mobile ions. Novel frameworks can be disruptive by enabling fast ion conduction aided by different structure and diffusion mechanisms, thereby unlocking optimal conductors with different properties. Herein, we perform a high-throughput survey of a structural framework for sodium ion conduction, Na8–x A x P2O9 (NAP), to understand the family’s thermodynamic stability, synthesizability, and ionic conduction. We show that the parent phase Na4TiP2O9 (NTP) undergoes a structural distortion (with accompanying conductivity transition) due to unstable phonons arising from pseudo-Jahn–Teller mode in the 1D titanium chains. Screening compounds in which Ti is substituted by other metals computationally reveal a number of candidates that are predicted to be low in formation energy and have high predicted ionic conductivities. High-throughput experimental and subsequent methodology optimization trials deliver one new compound, Na4SnP2O9 (NSP). X-ray diffraction (XRD), microscopy, and spectroscopy characterization indicate that the room-temperature structure of NSP is similar to the high-temperature, orthorhombic NTP phase but with some small unresolved structural differences. These uncharacterized structural details are speculated to limit the ion conductivity. Temperature-dependent XRD and electrochemical impedance spectroscopy indicate multiple coupled conductivity–structure transitions at a high temperature. We demonstrate the challenges with synthesis development and a priori identification of promising SSE phases as a major bottleneck in new (energy) materials development.

Chemical reactions↗

Metal–organic frameworks as O 2 -selective adsorbents for air separations

Oxygen is a critical gas in numerous industries and is produced globally on a gigatonne scale, primarily through energy-intensive cryogenic distillation of air. The realization of large-scale adsorption-based air separations could enable a significant reduction in associated worldwide energy consumption and would constitute an important component of broader efforts to combat climate change. Certain small-scale air separations are carried out using N 2 -selective adsorbents, although the low capacities, poor selectivities, and high regeneration energies associated with these materials limit the extent of their usage. In contrast, the realization of O 2 -selective adsorbents may facilitate more widespread adoption of adsorptive air separations, which could enable the decentralization of O 2 production and utilization and advance new uses for O 2 . Here, we present a detailed evaluation of the potential of metal–organic frameworks (MOFs) to serve as O 2 -selective adsorbents for air separations. Drawing insights from biological and molecular systems that selectively bind O 2 , we survey the field of O 2 -selective MOFs, highlighting progress and identifying promising areas for future exploration. As a guide for further research, the importance of moving beyond the traditional evaluation of O 2 adsorption enthalpy, ΔH, is emphasized, and the free energy of O 2 adsorption, ΔG, is discussed as the key metric for understanding and predicting MOF performance under practical conditions. Based on a proof-of-concept assessment of O 2 binding carried out for eight different MOFs using experimentally derived capacities and thermodynamic parameters, we identify two existing materials and one proposed framework with nearly optimal ΔG values for operation under user-defined conditions. While enhancements are still needed in other material properties, the insights from the assessments herein serve as a guide for future materials design and evaluation. Computational approaches based on density functional theory with periodic boundary conditions are also discussed as complementary to experimental efforts, and new predictions enable identification of additional promising MOF systems for investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of a hybrid kinetics/mixing-controlled combustion model for turbulent premixed and diffusion combustion using KIVA-2

Two dimensional calculations were made of spark ignited premixed-charge combustion and direct injection stratified-charge combustion in gasoline fueled piston engines. Results are obtained using kinetic-controlled combustion submodel governed by a four-step global chemical reaction or a hybrid laminar kinetics/mixing-controlled combustion submodel that accounts for laminar kinetics and turbulent mixing effects. The numerical solutions are obtained by using KIVA-2 computer code which uses a kinetic-controlled combustion submodel governed by a four-step global chemical reaction (i.e., it assumes that the mixing time is smaller than the chemistry). A hybrid laminar/mixing-controlled combustion submodel was implemented into KIVA-2. In this model, chemical species approach their thermodynamics equilibrium with a rate that is a combination of the turbulent-mixing time and the chemical-kinetics time. The combination is formed in such a way that the longer of the two times has more influence on the conversion rate and the energy release. An additional element of the model is that the laminar-flame kinetics strongly influence the early flame development following ignition.

Nguyen, H. Lee↗

Evaluation of a hybrid kinetics/mixing-controlled combustion model for turbulent premixed and diffusion combustion using KIVA-II

Two-dimensional calculations were made of spark ignited premixed-charge combustion and direct injection stratified-charge combustion in gasoline fueled piston engines. Results are obtained using kinetic-controlled combustion submodel governed by a four-step global chemical reaction or a hybrid laminar kinetics/mixing-controlled combustion submodel that accounts for laminar kinetics and turbulent mixing effects. The numerical solutions are obtained by using KIVA-2 computer code which uses a kinetic-controlled combustion submodel governed by a four-step global chemical reaction (i.e., it assumes that the mixing time is smaller than the chemistry). A hybrid laminar/mixing-controlled combustion submodel was implemented into KIVA-2. In this model, chemical species approach their thermodynamics equilibrium with a rate that is a combination of the turbulent-mixing time and the chemical-kinetics time. The combination is formed in such a way that the longer of the two times has more influence on the conversion rate and the energy release. An additional element of the model is that the laminar-flame kinetics strongly influence the early flame development following ignition.

Nguyen, H. Lee↗

PAYCOS: A new multidisciplinary analysis program for hypersonic vehicle design

The Payload Conceptual Sizing Code (PAYCOS), a new multidisciplinary computer program for use in the conceptual development phase of hypersonic lifting vehicles (HV's), is described. The program allows engineers to rapidly determine the feasibility of an HV concept and then improve upon the concept by means of optimization theory. The code contains analysis modules for aerodynamics, thermodynamics, mass properties, flight stability, controls, loads, structures, and packaging. Motivation for the code lies with the increased complexity of HV's over their body-of-revolution ballistic predecessors. With these new shapes, the need to rapidly screen out poor concepts and actively develop new and better concepts is an even more crucial part of the early design process. Preliminary results are given which demonstrate the optimization capabilities of the code.

Stubbe, J. R.↗

Presentation Summary: State of the AGN: Progress Toward Understanding Black Hole Accretion Processes

Accretion of plasma onto black holes power some of the most powerfulsystems in the cosmos. Supermassive black holes at the centers ofgalaxies represent the high-mass limit of these objects and so accountfor the most luminous accretors. As a result, their influence spansvast spatial and temporal scales of cosmic phenomena: intraclusterheating, intergalactic media, galactic feedback and star formation,kiloparsec-scale jets/outflows, variability over time scales of minutesto centuries, and luminous multi-wavelength electromagnetic emissionextending all the way down to its event horizon. Their intrigue isheightened by the fact that they lie at the intersection of variousphysical laws---e.g., general relativistic gravity,magnetohydrodynamics, radiation, high-energy particle physics,thermodynamics, and photo-ionization---which all must be reconciled toarrive at a fundamental understanding and probe for new physics, liketests of general relativity. These physics ingredients must beincorporated into simulations performed somehow on dynamical scalesranging from that of the event horizon to parsec-scales. Fortunately,new computational and theoretical techniques---such as GPU computing,radiation transport, and and novel gridding techniques---are enablingprogress to larger scales, more degrees of freedom, and even to binarysystems. Some of the topics we will survey include recent progress onsimulating the relationship between the disk-jet interaction, howtilted black holes behave, radiation-dominated flow, and how binaryAGN affect the standard picture of black hole accretion. Along theway, we will highlight how new technologies have enabled thesescientific rewards. Future directions and open questions will beprovided to inspire discussion and interaction during the session.

Black Holes↗